Magnetic Resonance Imaging (MRI) of the Breast

Number: 0105

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References


Policy

Scope of Policy

This Clinical Policy Bulletin addresses magnetic resonance imaging (MRI) of the breast.

  1. Medical Necessity

    Aetna considers magnetic resonance imaging (MRI) of the breast medically necessary for any of the following:

    1. With or without contrast materials for members who have had a recent (within the past year) conventional mammogram and/or breast sonogram, in any of the following circumstances where MRI of the breast may affect their clinical management:

      1. For individuals who received radiation treatment to the chest between ages 10 and 30 years, such as for Hodgkin disease, Wilm's tumors; or
      2. To assess tumor location, size, and extent before and/or after neoadjuvant chemotherapy in persons with locally advanced breast cancer, for determination of eligibility for breast conservation therapy; or
      3. To detect implant rupture in symptomatic members; or
      4. To detect suspected local tumor recurrence in members with breast cancer who have undergone mastectomy and breast reconstruction with an implant; or
      5. To detect local tumor recurrence in individuals with breast cancer who have radiographically dense breasts or old scar tissue from previous breast surgery that compromises the ability of combined mammography and ultrasonography; or
      6. To detect the extent of residual cancer in the recently post-operative breast with positive pathological margins after incomplete lumpectomy when the member still desires breast conservation and local re-excision is planned; or
      7. To guide localization of breast lesions to perform needle biopsy when suspicious lesions exclusively detected by contrast-enhanced MRI can not be visualized with mammography or ultrasonography; or
      8. To localize the site of primary occult breast cancer in individuals with adenocarcinoma suggestive of breast cancer discovered as axillary node metastasis or distant metastasis without focal findings on physical examination or on mammography/ultrasonography; or
      9. To map the extent of primary tumors and identify multi-centric disease in persons with any of the following:

        1. Multifocal or multicentric breast cancer
        2. Before neoadjuvant systemic therapy
        3. Adenocarcinoma in axillary lymph node without a breast primary site identified on mammogram/ultrasound
        4. Invasive lobular carcinoma
        5. Paget's disease of the breast; or
      10. Contralateral breast examination for members with any of the following:

        1. Multifocal or multicentric breast cancer
        2. Before neoadjuvant systemic therapy
        3. Adenocarcinoma in axillary lymph node without a breast primary site identified on mammogram/ultrasound
        4. Invasive lobular carcinoma
        5. Paget's disease of the breast; or
      11. Lesion characterization (nipple retraction, unilateral drainage from the nipple that is bloody or clear) when all other imaging examinations, such as ultrasound and mammography, and physical examination are inconclusive for the presence of breast cancer; or
      12. After breast conservation therapy in women who exhibit suspicious clinical or imaging findings that remain indeterminate after complete mammographic and sonographic evaluations; or
      13. Evaluation of inconclusive or conflicting findings on mammography or ultrasound that is not a discrete palpable mass;
    2. As an adjunct to mammography for screening of women considered to be at high genetic risk of breast cancer because of any of the following (mammography must have been performed within the past year; mammography not required for women under age 30 years):

      1. Carry or have a first-degree relative who carries a genetic mutation in PTEN gene (Cowden and Bannayan-Riley-Ruvalcaba syndromes) (screening beginning at age 30 for PTEN); or
      2. Carry a genetic mutation in the TP53 gene (Li-Fraumeni syndrome) (screening beginning at age 20 years or age of earliest diagnosed breast cancer in the family for TP53); or
      3. Carry a PALB2 mutation (beginning at age 30); or
      4. Carry a genetic mutation in Puetz-Jaeger syndrome (STK11/LKB1 gene variations) (beginning age 30 years); or
      5. Carry a genetic mutation in CDH1 or NF1 (beginning at age 30); or
      6. Carry a genetic mutation in ATM, CHEK2, or NBN (beginning at age 40); or
      7. Carry a genetic mutation in BARD1, RAD51C, or RAD51D (beginning at age 40); or
      8. Confirmed presence of BRCA1 or BRCA2 mutation (beginning age 25 years); or
      9. First degree blood relative with BRCA1 or BRCA2 mutation and are untested; or
      10. Have a lifetime risk of breast cancer of 20 to 25 % or more using standard risk assessment models (BRCAPRO, Claus model, Gail model, or Tyrer-Cuzick);
    3. To detect intra-capsular (silent) rupture of silicone gel-filled breast implants. Screening for silent intra-capsular rupture more frequently than every 2 years is not considered medically necessary; 
    4. Phyllodes tumor (cystosarcoma phyllodes), indicated preoperatively to establish extent of disease, where diagnosis has been established by biopsy; or
      Newly diagnosed Paget's disease; 
    5. To follow up a probable benign lesion on MRI (BI-RADS 3 lesions) that was originally detected by MRI:

      1. Follow-up MRI of BI-RADS 3 lesions is considered medically necessary every 6 months for up to two years
      2. If repeat imaging is BI-RADS 1 or 2, then imaging reverts to routine per individuals risk profile
      3. MRI is not considered medically necessary for initial evaluation of BI-RADS 3 lesions.

    Note: Aetna considers computer-aided detection of malignancy integral to MRI of the breast and not separately reimbursed.

  2. Experimental and Investigational

    The following breast MRI indications are considered experimental and investigational because the effectiveness of these approaches has not been established (not an all-inclusive list): 

    1. Dermatomyositis as an indication for use of MRI for breast cancer screening; 
    2. Quantitative measurements of breast density; 
    3. Screening of persons with APC or GALNT12 mutations; 
    4. Surveillance of asymptomatic individuals with breast cancer or carcinoma in situ who have completed primary therapy and who are not at high genetic risk of breast cancer; 
    5. To confirm implant rupture in symptomatic individuals whose ultrasonography shows rupture, especially with implants more than 10 years old (ultrasound sufficient to proceed with removal); 
    6. To diagnose fat necrosis post-breast reduction surgery; 
    7. To differentiate benign from malignant breast disease, especially clustered micro-calcifications; 
    8. To differentiate cysts from solid lesions (ultrasound indicated); 
    9. To evaluate breasts before biopsy in an effort to reduce the number of surgical biopsies for benign lesions; 
    10. To evaluate suspicious (BI-RADS 4 or 5) lesions found on mammogram and/or ultrasound. (A lesion categorized as have BI-RADS 4 or 5 should be biopsied.); 
    11. To evaluate persons with lobular carcinoma in situ (LCIS), ductal carcinoma in situ (DCIS) or atypical ductal hyperplasia (ADH);
    12. To evaluate retro-pectoral fat grafting in breast reduction; 
    13. To provide an early prediction of response to adjuvant breast cancer chemotherapy in guiding choice of chemotherapy regimen; 
    14. To screen for breast cancer in members with average risk of breast cancer; 
    15. To screen BRCA-positive men; 
    16. To screen individuals with MUTYH mutation; 
    17. Women with dense breasts and/or fibrocystic breast disease who are asymptomatic and have no additional risk factors;
    18. Post-surgical intra-operative breast MRI for quantifying tumor deformation and detecting residual breast cancer;
    19. Quantitative breast MRI for predicting the risk of breast cancer recurrence.
  3. Related Policies

    1. CPB 0584 - Mammography

Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

CPT codes covered if selection criteria are met:

19085 Biopsy, breast, with placement of breast localization device(s) (eg, clip, metallic pellet), when performed, and imaging of the biopsy specimen, when performed, percutaneous; first lesion, including magnetic resonance guidance
19086     each additional lesion, including magnetic resonance guidance (List separately in addition to code for primary procedure)
19287 Placement of breast localization device(s) (eg clip, metallic pellet, wire/needle, radioactive seeds), percutaneous; first lesion, including magnetic resonance guidance
19288     each additional lesion, including magnetic resonance guidance (List separately in addition to code for primary procedure)
77046 - 77047 Magnetic resonance imaging, breast, without contrast material
77048 - 77049 Magnetic resonance imaging, breast, without and with contrast material(s), including computer-aided detection (CAD real-time lesion detection, characterization and pharmacokinetic analysis), when performed

CPT codes not covered for indications listed in the CPB:

0697T Quantitative magnetic resonance for analysis of tissue composition (eg, fat, iron, water content), including multiparametric data acquisition, data preparation and transmission, interpretation and report, obtained without diagnostic MRI examination of the same anatomy (eg, organ, gland, tissue, target structure) during the same session; multiple organs
0698T Quantitative magnetic resonance for analysis of tissue composition (eg, fat, iron, water content), including multiparametric data acquisition, data preparation and transmission, interpretation and report, obtained with diagnostic MRI examination of the same anatomy (eg, organ, gland, tissue, target structure); multiple organs (List separately in addition to code for primary procedure)

Other CPT codes related to the CPB:

15769 Grafting of autologous soft tissue, other, harvested by direct excision (eg, fat, dermis, fascia)
15771 Grafting of autologous fat harvested by liposuction technique to trunk, breasts, scalp, arms, and/or legs; 50 cc or less injectate
+15772     each additional 50 cc injectate, or part thereof (List separately in addition to code for primary procedure)
19100 - 19103 Breast biopsy
19120 - 19126 Excision breast lesion
19300 - 19307 Mastectomy procedures
19357 - 19369 Breast reconstruction
20926 Tissue grafts, other (eg, paratenon, fat, dermis)
76641 Ultrasound, breast, unilateral, real time with image documentation, including axilla when performed; complete
76642     limited
77065 - 77067 Diagnostic mammography, including computer-aided detection (CAD) when performed
88245 - 88269 Chromosome analysis
88271 - 88275 Molecular cytogenetics

HCPCS codes covered if selection criteria are met:

C7502 Percutaneous breast biopsies using magnetic resonance guidance, with placement of breast localization device(s) (eg, clip, metallic pellet), when performed, and imaging of the biopsy specimen, when performed, all lesions unilateral or bilateral (for single lesion biopsy, use appropriate code)
C8903 Magnetic resonance imaging with contrast, breast; unilateral
C8905 Magnetic resonance imaging without contrast followed by with contrast, breast; unilateral
C8906 Magnetic resonance imaging with contrast, breast; bilateral
C8908 Magnetic resonance imaging without contrast followed by with contrast, breast; bilateral

HCPCS codes not covered for indications listed in the CPB:

C8937 Computer-aided detection, including computer algorithm analysis of breast mri image data for lesion detection/characterization, pharmacokinetic analysis, with further physician review for interpretation (list separately in addition to code for primary procedure)

Other HCPCS codes related to the CPB:

G0202 - G0206 Mammography
L8600 Implantable breast prosthesis, silicone or equal

ICD-10 codes covered if selection criteria are met:

C50.011 - C50.929 Malignant neoplasm of breast [Multifocal or multicentric breast cancer]
C77.3 Secondary and unspecified malignant neoplasm of axilla and upper limb lymph nodes
C79.81 Secondary malignant neoplasm of breast
D05.00 – D05.02, D05.80 - D05.92 Carcinoma in situ of breast
N60.81 - N60.89 Other benign mammary dysplasias
N64.52 Nipple Discharge
N64.53 Retraction of nipple
Q85.01 Neurofibromatosis, type 1
Q85.81, Q85.82, Q85.83, Q85.9 Other phakomatoses, not elsewhere classified [Cowden syndrome]
R92.2 Inconclusive mammogram
R92.8 Other abnormal and inconclusive findings on diagnostic imaging of breast
T85.41+ - T85.49+ Mechanical complications of breast prosthesis and implant
T85.690+ - T85.698+ Other mechanical complications of other specified internal prosthetic devices, implants and grafts
Z12.31 - Z12.39 Encounter for screening for malignant neoplasm breast
Z15.01 Genetic susceptibility to malignant neoplasm of breast [not covered for BRCA-positive men]
Z15.02 Genetic susceptibility to malignant neoplasm of ovary
Z15.09 Genetic susceptibility to other malignant neoplasm [Genetic mutation in CDH1, ATM, CHEK2, NBN, BARD1, RAD51C and RAD51D] [Not covered for screening women positive for APC and GLANT12 genes, individuals with MUTYH mutation]
Z40.01 Prophylactic breast removal
Z40.02 Encounter for prophylactic removal of ovary(s)
Z80.3 Family history of malignant neoplasm of breast
Z80.41 Family history of malignant neoplasm of ovary
Z85.3 Personal history of malignant neoplasm of breast
Z85.43 Personal history of malignant neoplasm of ovary
Z90.10 - Z90.13 Acquired absence of breast and nipple
Z92.3 Personal history of irradiation [to chest]
Z98.82 Breast implant status

ICD-10 codes not covered for indications listed in the CPB:

D05.10 – D05.12 Intraductal carcinoma in situ of breast
D24.1 - D24.9 Benign neoplasm of breast
D48.60 - D48.62 Neoplasm of uncertain behavior of breast
M33.00 - M33.99 Dermatopolymyositis
N60.01 - N60.09 Solitary cyst of breast
N60.11 - N60.19 Diffuse cystic mastopathy
N60.21 - N60.29 Fibroadenosis of breast
N64.1 Fat necrosis of breast
N64.9 Disorder of breast, unspecified
R92.0 Mammographic microcalcification found on diagnostic imaging of breast
R99 Ill-defined and unknown cause of mortality

Background

Mammography is the only screening test proven to lower breast cancer morbidity and mortality.  Although mammography is an effective screening tool, it does have limitations, especially in women with dense breasts.  New imaging techniques are being developed to overcome these limitations, enhance cancer detection, and improve patient outcome.  Digital mammography, computer-aided detection (CAD), breast ultrasound, and breast magnetic resonance imaging (MRI) are frequently used adjuncts to mammography in today's clinical practice.

An expert panel convened by the American Cancer Society recommended the use of MRI for screening women at a 20 to 25 % or greater lifetime risk for breast cancer (Saslow et al, 2007).  The panel states that, in addition to mammography, annual screening using MRI is recommended for women who:

  • Carry or have a first-degree relative who carries a genetic mutation in the TP53 or PTEN genes (Li-Fraumeni syndrome and Cowden and Bannayan-Riley-Ruvalcaba syndromes)
  • Have a BRCA 1 or 2 mutation
  • Have a first-degree relative with a BRCA 1 or 2 mutation and are untested
  • Have a lifetime risk of breast cancer of 20 to 25 % or more using standard risk assessment models
  • Received radiation treatment to the chest between ages 10 and 30, such as for Hodgkin Disease.

The ACS guidelines recommend use of MRI in addition to, not in place of, mammography for screening high-risk women (Saslow et al, 2007).  The guidelines explain that all of the clinical trials screened participants with both MRI and mammography at the same time.  The guidelines state that there is no evidence to support one approach over the other.  "For the majority of women at high risk, it is critical that MRI screening be provided in addition to, not instead of, mammography, as the sensitivity and cancer yield of MRI and mammography combined is greater than for MRI alone."

The guideline provides information about 3 risk assessment models available for calculating breast cancer risk (BRCAPRO, Claus model, and Tyrer-Cuzick).  Software for each model is available online (see Appendix below).  The 3 risk models utilize different combinations of risk factors, are derived from different data sets, and vary in the age to which they calculate cumulative breast cancer risk.  As a result, they may generate different risk estimates for a given patient.  This variability is an indicator that the risk models provide approximate, rather than precise, estimates of breast cancer risk.  According to ACS guidelines, each of the risk models can be used for the purpose of identifying patients who would benefit from breast MRI screening (Saslow et al, 2007).  In addition, the Gail model is widely used in research studies and clinical counseling to predict a woman's lifetime risk of developing breast cancer.  Calculation of a 5-year and lifetime breast cancer risk according to the Gail model can be performed by accessing the National Cancer Institute's website and searching for information on breast cancer risk.

The ACS panel also identified several risk subgroups for which the available data are insufficient to recommend either for or against MRI screening (Saslow et al, 2007).  They include women with a personal history of breast cancer, carcinoma in situ, atypical hyperplasia, and extremely dense breasts on mammography.

Although ultrasound is sufficient to confirm rupture of breast implants in women with symptoms, MRI may be necessary to detect intra-capsular rupture of silicone gel-filled breast implants in asymptomatic women.  The sensitivity of plastic surgeons familiar with implants to diagnose rupture is 30 % compared to 89 % for MRI (Holmich et al, 2005).  The FDA therefore recommends that women with silicone gel-filled breast implants have regular breast MRIs over their lifetime to screen for silent rupture.  The FDA-approved labeling of silicone gel-filled breast implants recommends that the first MRI be performed 3 years post-operatively, then every 2 years thereafter.  The FDA recommends that the MRI have at least a 1.5 Tesla magnet, a dedicated breast coil, and a radiologist experienced with breast implant MRI films for signs of rupture.

Houssami et al (2008) reviewed the evidence on MRI in staging the affected breast to determine its accuracy and impact on treatment.  These researchers estimated summary receiver operating characteristic curves, positive predictive value (PPV), true-positive (TP) to false-positive (FP) ratio, and examined their variability according to quality criteria.  Pooled estimates of the proportion of women whose surgery was altered were calculated.  Data from 19 studies showed MRI detects additional disease in 16 % of women with breast cancer (n = 2,610).  Magnetic resonance imaging incremental accuracy differed according to the reference standard (RS; p = 0.016) decreasing from 99 % to 86 % as the quality of the RS increased.  Positive predictive value was 66 % (95 % confidence interval [CI]: 52 % to 77 %) and TP:FP ratio was 1.91 (95 % CI: 1.09 to 3.34). Conversion from wide local excision (WLE) to mastectomy was 8.1 % (95 % CI: 5.9 to 11.3), from WLE to more extensive surgery was 11.3 % in multi-focal/multi-centric disease (95 % CI: 6.8 to 18.3).  Due to MRI-detected lesions (in women who did not have additional malignancy on histology) conversion from WLE to mastectomy was 1.1 % (95 % CI: 0.3 to 3.6) and from WLE to more extensive surgery was 5.5 % (95 % CI: 3.1 to 9.5).  The authors concluded that MRI staging causes more extensive breast surgery in an important proportion of women by identifying additional cancer, however there is a need to reduce FP MRI detection.  They stated that randomized trials are needed to determine the clinical value of detecting additional disease which changes surgical treatment in women with apparently localized breast cancer.

In a review on the utility of MRI for the screening and staging of breast cancer, Patani and Mokbel (2008) stated that while MRI can facilitate local staging, especially the evaluation of ipsilateral multi-centric or multi-focal lesions as well as synchronous contralateral disease that may be missed by conventional imaging; however, efficacy with respect to clinically relevant and patient oriented end-points has yet to be addressed in the context of clinical trials.

Computer-aided detection has been used to aid radiologists’ interpretation of contrast-enhanced MRI of the breast, which is sometimes used as an alternative to mammography or other screening and diagnostic tests because of its high sensitivity in detecting breast lesions, even among those in whom mammography is less accurate (e.g., younger women and those with denser breasts).  However, MRI has a high FP rate because of the difficulty in differentiating between benign and malignant lesions.  The use of CAD may also reduce the time needed to interpret breast MRI images, which currently takes much longer than reading mammograms. 

The BlueCross and BlueShield Association’s Technology Evaluation Center (TEC) Medical Advisory Panel (2006) assessed the evidence on the use of CAD with MRI of the breast by comparing the sensitivity, specificity, and recall rate (percentage of patients asked to come back for further evaluation) of MRI with and without the use of commercially available CAD systems in detecting malignant lesions, evaluating the extent of disease in women with cancer, or gauging the impact of treatment.  According to this assessment, many of the studies on the use of CAD with MRI of the breast mainly reported on the development of CAD systems, or testing new CAD approaches.  The assessment noted that few of them evaluated commercially available CAD systems.  Several of those that did, reported on the development and testing of approaches that underlie one of the commercially available systems (3TP); the assessment stated that it is not clear to what degree the current 3TP system has or has not been modified compared to these earlier approaches.  Although the studies had to have separate testing data sets to be included in the TEC assessment, these data sets often were enriched with more cancer cases or consisted exclusively of cases in which lesions had been found.  The TEC assessment found, as a result, the range of sensitivities and specificities cannot be applied to the populations usually found in a clinical setting.  The TEC assessment also found that many of the studies of CAD systems were retrospective, and reported primarily on their development and testing; thus, these studies lacked the rigor and generalizability of a large, prospective, well-designed study.

The TEC assessment stated that the literature is unclear on how CAD systems are to be used.  In the case of CAD with mammography, the radiologist reads the original films first, makes a diagnosis, and then reviews the CAD results.  The TEC assessment explained that, because CAD is not 100 % sensitive, lesions detected by mammography both before the use of CAD and after viewing the CAD results may be worked up.  Thus, CAD can add to the sensitivity of mammography, but not its specificity.  The TEC assessment noted, however, with MRI of the breast, the sensitivity is already high, and the focus is mainly on enhancing the specificity.  In some studies, it appears that CAD was intended as an adjunct to the initial MRI reading, just as with CAD and mammography.  In other studies, it was proposed as a way of speeding up the MRI reading process, and the precise protocol to be followed in reading the MRI images is unclear.  In addition, unlike in the case of CAD with mammography, in the documents regarding the FDA clearance it did not specify that CAD must be added only after an initial reading of the images alone, although it did say for one system that “patient management decisions should not be made based solely on the results of the CADstream analysis”.  The TEC assessment observed that the impact of CAD on the accuracy of MRI of the breast may depend partly on how the CAD results are incorporated into the reading and diagnostic process.

Based on the available evidence, the Blue Cross and Blue Shield Association Medical Advisory Panel concluded that there is insufficient evidence to evaluate if the use of CAD systems would maintain or increase the sensitivity, specificity, and recall rates of MRI of the breast.  The TEC assessment concluded that, given the inability to evaluate these intermediate outcomes, it is impossible to evaluate the impact of CAD on health outcomes such as treatment success and survival of patients with breast cancer.

There is limited evidence on the predictive value of preoperative MRI in persons who are newly diagnosed with early stage breast cancer, and no consistent evidence that a pre-operative breast MRI confers a benefit to the patient by improving clinical outcomes or surgical procedures.  Lehman et al (2009) stated that use of breast MRI in the pre-operative evaluation of patients recently diagnosed with breast cancer has increased significantly over the past 10 years because of its well-documented high sensitivity for detecting otherwise occult breast cancer in the affected and contralateral breasts.  However, published research reports on the impact of this improved cancer detection are limited.  Equally important are growing concerns that the quality of breast MRI may vary significantly across practice sites, and therefore the published value of MRI may not be achieved for many patients.  These researchers described the peer-reviewed, published clinical research trials evaluating breast MRI in patients with newly diagnosed breast cancer on which the National Comprehensive Cancer Network (NCCN) practice guidelines on breast cancer were based.  The current NCCN guidelines (2011) recommend that breast MRI be considered for patients with a newly diagnosed breast cancer to evaluate the extent of cancer or presence of multi-focal or multi-centric cancer in the ipsilateral breast; and for screening of the contralateral breast cancer at the time of initial diagnosis (category 2B).

Lehman and colleagues (2007) conducted a study to examine if MRI could improve on clinical breast examination and mammography in detecting contralateral breast cancer soon after the initial diagnosis of unilateral breast cancer.  A total of 969 women with a recent diagnosis of unilateral breast cancer and no abnormalities on mammographic and clinical examination of the contralateral breast underwent breast MRI.  The diagnosis of MRI-detected cancer was confirmed by means of biopsy within 12 months after study entry.  The absence of breast cancer was determined by means of biopsy, the absence of positive findings on repeat imaging and clinical examination, or both at 1 year of follow-up.  MRI detected clinically and mammographically occult breast cancer in the contralateral breast in 30 of 969 women who were enrolled in the study (3.1 %).  The sensitivity of MRI in the contralateral breast was 91 %, and the specificity was 88 %.  The negative predictive value of MRI was 99 %.  A biopsy was performed on the basis of a positive MRI finding in 121 of the 969 women (12.5 %), 30 of whom had specimens that were positive for cancer (24.8 %); 18 of the 30 specimens were positive for invasive cancer.  The mean diameter of the invasive tumors detected was 10.9 mm.  The additional number of cancers detected was not influenced by breast density, menopausal status, or the histologic features of the primary tumor.  The authors concluded that MRI can detect cancer in the contralateral breast that is missed by mammography and clinical examination at the time of the initial breast-cancer diagnosis.

Bernard and associates (2010) evaluated the prevalence of synchronous, occult contralateral breast cancer detected by MRI but not by mammography or clinical breast examination in women with newly diagnosed breast cancer, including those aged 70 years or older.  These investigators reviewed MRI results for women with newly diagnosed breast cancer who underwent bilateral breast MRI after negative mammography and clinical examination.  The prevalence of pathologically confirmed contralateral carcinoma diagnosed solely by MRI was determined and analyzed in the context of age, breast density, family history, menopausal status, and primary-tumor characteristics.  Logistic regression was used to explore the association between contralateral carcinoma and potential patient risk factors.  A total of 425 women were evaluated, of whom 129 (30 %) were aged 70 years or older.  A contralateral biopsy was recommended and performed solely on the basis of MRI in 72 of the 425 women (17 %).  Sixteen of these 72 women (22 %) had pathologically confirmed carcinoma, including 7 in the older subgroup.  The prevalence of clinically and mammographically occult contralateral carcinoma detected by MRI was 3.8 % (16/425) overall and 5.4 % (7/129) in the group of older women.  When potential risk factors for contralateral breast cancer were evaluated, post-menopausal status was the only significant predictor of contralateral cancer detected by MRI (p = 0.016).  The authors concluded that contralateral breast screening with MRI should be considered in post-menopausal women with newly diagnosed breast cancer, even those aged 70 years or older at diagnosis.

On the other hand, Houssami and Hayes (2009) noted that randomized controlled trials (RCTs) have shown equivalent survival for women with early stage breast cancer who are treated with breast-conservation therapy (local excision and radiotherapy) or mastectomy.  Decades of experience have shown that breast-conservation therapy provides excellent local control based on defined standards of care.  Magnetic resonance imaging has been introduced in pre-operative staging of the affected breast in women with newly diagnosed breast cancer because it detects additional foci of cancer that are occult on conventional imaging.  The median incremental (additional) detection for MRI has been estimated as 16 % in meta-analysis.  In the absence of consensus on the role of pre-operative MRI, these investigators reviewed data on its detection capability and its impact on treatment.  They outlined that the assumptions behind the adoption of MRI, namely that it will improve surgical planning and will lead to a reduction in re-excision surgery and in local recurrences, have not been substantiated by trials.  Evidence consistently shows that MRI changes surgical management, usually from breast conservation to more radical surgery; however, there is no evidence that it improves surgical care or prognosis.  Emerging data indicate that MRI does not reduce re-excision rates and that it causes FPs in terms of detection and unnecessary surgery; overall there is little high-quality evidence at present to support the routine use of pre-operative MRI.  The authors concluded that RCTs are needed to establish the clinical, psychosocial, and long-term effects of MRI and to show a related change in treatment from standard care in women newly affected by breast cancer.

Furthermoer, Solin (2010) stated that for the woman with a newly diagnosed early stage breast cancer, the routine use of pre-operative breast MRI is not indicated beyond conventional breast imaging (i.e., mammography with correlation ultrasound as indicated).  There is no consistent evidence that a pre-operative breast MRI confers a benefit to the patient by improving clinical outcomes or surgical procedures.  In a meta-analysis of studies reporting on the use of pre-operative breast MRI for the patient with an established index cancer, multi-focal or multi-centric disease was found on breast MRI in 16 % of the patients, a rate substantially higher than the rate of local recurrence after breast conserving surgery plus definitive radiation treatment.  In the largest retrospective study of patients treated with breast conserving surgery plus radiation, no gain was found for adding a breast MRI to conventional breast imaging.  No randomized clinical trial has been designed to evaluate long-term clinical outcomes associated with adding a pre-operative breast MRI.  Adding pre-operative breast MRI can alter clinical management in ways that are potentially harmful to patients (e.g., increased ipsilateral mastectomies, increased contralateral prophylactic mastectomies, increased work-ups, and delay to definitive surgery).  The authors concluded that the routine use of pre-operative breast MRI is not warranted for the typical patient with a newly diagnosed early stage breast cancer.

There are no clinical studies of breast MRI in BRCA-positive men.  Neither the American Cancer Society guidelines nor the National Comprehensive Cancer Network (NCCN) guidelines recommend breast MRI screening for men.

Wurdinger et al (2005) evaluated the MRI appearance of phyllodes breast tumors and to differentiate them from fibro-adenomas.  MR images were obtained on a 1.5-T imager. T1- and T2-weighted sequences and dynamic 2D fast-field echo T1-weighted sequences were performed.  MR images of 23 patients with 24 phyllodes breast tumors (1 malignant, 23 benign) were analyzed with respect to morphology and contrast enhancement.  The tumors were compared with the MRI appearance of 81 fibro-adenomas of 75 patients.  Well-defined margins were seen in 87.5 % of the phyllodes tumors and 70.4 % of the fibro-adenomas, and a round or lobulated shape in 100 % and 90.1 %, respectively.  A heterogeneous internal structure was observed in 70.8 % of phyllodes tumors and in 49.4 % of fibro-adenomas.  Non-enhancing internal septations were found in 45.8 % of phyllodes tumors and 27.2 % of fibro-adenomas.  A significantly greater increase in signal was seen on T2-weighted images in the tissue surrounding phyllodes tumors (21 %) compared with fibro-adenomas (1.2 %).  Most of both lesions appeared with low signal intensity on T1- and T2-weighted images.  After the administration of contrast material, 33.3 % of phyllodes tumors and 22.2 % of fibro-adenomas showed a suspicious signal intensity-time course.  The authors concluded that phyllodes breast tumors and other fibro-adenomas can not be precisely differentiated on breast MRI.  Phyllodes tumors have benign morphologic features and contrast enhancement characteristics suggestive of malignancy in 33 % of cases.

Biondi et al (2009) stated that phyllodes tumors are unusual biphasic fibro-epithelial neoplasms of the breast, accounting for less than 1 % of all breast tumors and raising issues of diagnosis and therapeutic choice.  They can grow quickly and when the maximum diameter is greater than 10 cm, they are known as giant phyllodes tumors.  Ultrasound, mammography and fine needle aspiration are not effective.  A potentially useful diagnostic modality is MRI.  Core tissue biopsy or incisional biopsy represent the preferred means of pre-operative diagnosis.  Conservative treatment can be effective also in giant tumors depending upon the size of the tumor and the breast if a complete excision with an adequate margin of normal breast tissue can be achieved, so avoiding local recurrence often accompanied by worse histopathology.  The authors reported the case of a giant benign phyllode tumor of the breast treated with conservative surgery, quadrantectomy and oncoplasty.  No local recurrence at 4 years follow-up.

An UpToDate review on "Phyllodes tumors of the breast" (Grau et al, 2011) states that the role of MRI in the diagnosis and management of phyllodes tumors is not clear.  A retrospective study of 30 patients with biopsy confirmed phyllodes tumors showed that malignant phyllodes tumors are seen as well-circumscribed tumors with irregular walls, high signal intensity on T1-weighted images and low signal intensity on T2-weighted images.  Cystic change may be seen as well.  Interestingly, a rapid enhancement pattern is seen more commonly with benign rather than malignant phyllodes tumors, which is the opposite of the pattern seen with adenocarcinomas of the breast.  When the diagnosis of a phyllodes tumor has been made on core biopsy, breast MRI may prove helpful in determining the extent of disease and facilitating pre-operative planning.  However, the use of breast MRI in surgical planning for phyllodes tumors is controversial as there are very little data on its role in this setting as they are so rare.

Furthermore, the NCCN Clinical Practice Guideline on breast cancer (2011) mentions the use of ultrasonography and mammography for the work-up of patients with phyllodes tumor; but does not mention the use of MRI in the management of these patients.

In a retrospective cohort study, Weber and colleagues (2012) examined the effect of pre-operative MRI on the reoperation rate in women with operable breast cancer. Women with operable breast cancer treated by a single surgeon between January 1, 2006, and December 31, 2010 were included in this study; selective pre-operative MRI based on breast density and histologic findings were carried out.  Main outcome measures were reoperation rate and pathologically avoidable mastectomy at initial operation.  Of 313 patients in the study, 120 underwent pre-operative MRI.  Patients undergoing MRI were younger (mean age, 53.6 versus 59.5 years; p < 0.001), were more often of non-Hispanic white race/ethnicity (61.7 % versus 52.3 %, p < 0.05), and more likely had heterogeneously dense or very dense breasts (68.4 % versus 22.3 %, p < 0.001).  The incidence of lobular carcinoma (8.3 % in the MRI group versus 5.2 % in the no MRI group, p = 0.27) and the type of surgery performed (mastectomy versus partial mastectomy, p = 0.67) were similar in both groups.  The mean pathological size of the index tumor in the MR imaging group was larger than that in the no MRI group (2.02 versus 1.72 cm, p = 0.009), but the extent of disease was comparable (75.8 % in the MR imaging group versus 82.9 % in the no MRI group had pathologically localized disease, p = 0.26).  The reoperation rate was similar between the 2 groups (19.1 % in the MRI group versus 17.6 % in the no MRI group, p = 0.91) even when stratified by breast density (p = 0.76), pT2 tumor size (p = 0.35), or lobular carcinoma histologic findings (p = 0.26).  Pathologically avoidable mastectomy (multi-focal or multi-centric MRI and uni-focal histopathological findings) was observed in 12 of 47 patients (25.5 %) with pre-operative MRI who underwent mastectomy.  The authors concluded that the selective use of pre-operative MRI to decrease reoperation in women with breast cancer is not supported by these data.  In a considerable number of patients, MRI over-estimated the extent of disease.

Plana et al (2012) estimated the diagnostic accuracy of MRI in detecting additional lesions and contralateral cancer not identified using conventional imaging in primary breast cancer.  These investigators conducted a systematic review and meta-analyses to estimate diagnostic accuracy indices and the impact of MRI on surgical management.  A total of 50 articles were included (n = 10,811 women).  MRI detected additional disease in 20 % of women and in the contralateral breast in 5.5 %.  The summary PPV of ipsilateral additional disease was 67 % (95 % CI: 59 to 74 %).  For contralateral breast, the PPV was 37 % (95 % CI: 27 to 47 %).  For ipsilateral lesions, MRI devices greater than or equal to 1.5 Tesla (T) had higher PPV (75 %, 95 % CI: 64 to 83 %) than MRI with less than 1.5 T (59 %, 95 % CI: 53 to 71 %).  Similar results were found for contralateral cancer, PPV 40 % (95 % CI: 29 to 53 %) and 19 % (95 % CI: 8 to 39 %) for high- and low-field equipments, respectively.  True-positive MRI findings prompted conversion from wide local excision (WLE) to more extensive surgery in 12.8 % of women while in 6.3 % this conversion was inappropriate.  The authors concluded that MRI shows high diagnostic accuracy, but MRI findings should be pathologically verified because of the high FP rate.  They stated that future research on this emerging technology should focus on patient outcome as the primary end-point.

Prevos et al (2012) examined if MRI can identify pre-treatment differences or monitor early response in breast cancer patients receiving neoadjuvant chemotherapy.  PubMed, Cochrane library, Medline and Embase databases were searched for publications until January 1, 2012.  After primary selection, studies were selected based on pre-defined inclusion/exclusion criteria.  Two reviewers assessed study contents using an extraction form.  In 15 studies, which were mainly under-powered and of heterogeneous study design, 31 different parameters were studied.  Most frequently studied parameters were tumor diameter or volume, K(trans), K(ep), V(e), and apparent diffusion coefficient (ADC).  Other parameters were analyzed in only 2 or less studies.  Tumor diameter, volume, and kinetic parameters did not show any pre-treatment differences between responders and non-responders.  In 2 studies, pre-treatment differences in ADC were observed between study groups.  At early response monitoring significant and non-significant changes for all parameters were observed for most of the imaging parameters.  The authors concluded that evidence on distinguishing responders and non-responders to neoadjuvant chemotherapy using pre-treatment MRI, as well as using MRI for early response monitoring, is weak and based on under-powered study results and heterogeneous study design.  Thus, the value of breast MRI for response evaluation has not yet been established.

The American Society of Clinical Oncology’s clinical practice guideline update on “Breast cancer follow-up and management after primary treatment” (Khatcheressian et al, 2013) provided recommendations on the follow-up and management of patients with breast cancer who have completed primary therapy with curative intent.  A systematic review of the literature published from March 2006 through March 2012 was completed using Medline and the Cochrane Collaboration Library.  An Update Committee reviewed the evidence to determine whether the recommendations were in need of updating.  There were 14 new publications that met inclusion criteria: 9 systematic reviews (3 included meta-analyses) and 5 RCTs.  After its review and analysis of the evidence, the Update Committee concluded that no revisions to the existing ASCO recommendations were warranted.  Regular history, physical examination, and mammography are recommended for breast cancer follow-up.  Physical examinations should be performed every 3 to 6 months for the first 3 years, every 6 to 12 months for years 4 and 5, and annually thereafter.  For women who have undergone breast-conserving surgery, a post-treatment mammogram should be obtained 1 year after the initial mammogram and at least 6 months after completion of radiation therapy.  Thereafter, unless otherwise indicated, a yearly mammographic evaluation should be performed.  The use of complete blood counts, chemistry panels, bone scans, chest radiographs, liver ultrasounds, pelvic ultrasounds, computed tomography scans, [(18)F]fluorodeoxyglucose-positron emission tomography scans, MRI, and/or tumor markers (carcinoembryonic antigen, CA 15-3, and CA 27.29) is not recommended for routine follow-up in an otherwise asymptomatic patient with no specific findings on clinical examination.

Korteweg et al (2011) evaluated the feasibility of 7-T breast MRI by determining the intrinsic sensitivity gain compared with 3-T in healthy volunteers and explored clinical application of 7-T MRI in breast cancer patients receiving neoadjuvant chemotherapy (NAC).  In 5 volunteers, the signal-to-noise ratio (SNR) was determined on proton density MRI at 3-T using a conventional 4-channel bilateral breast coil and at 7-T using a dedicated 2-channel unilateral breast coil, both obtained at identical scan parameters.  Subsequently, consecutive breast cancer patients on NAC were included.  The 7-T breast MRI protocol consisted of diffusion-weighted imaging, 3-D high-resolution (450 μm isotropic) T1-weighted fat-suppressed gradient-echo sequences and quantified single voxel (1)H-magnetic resonance spectroscopy.  Morphology was scored according to the MRI Breast Imaging-Reporting and Data System (BI-RADS)-lexicon, and the images were compared with 3-T and histopathologic findings.  Image quality was evaluated using a 5-point scale.  A 5.7-fold higher SNR was measured at 7-T than at 3-T, which reflected the advantages of a higher field strength and the use of optimized radiofrequency coils.  Three breast cancer patients were included and received a total of 13 7-T MRI examinations.  The image quality of the high-resolution examinations was at least satisfactory, and good to excellent in 9 of the 13 examinations performed.  More anatomic detail was depicted at 7-T than at 3-T.  In 1 case, a fat plane between the muscle and tumor was visible at 7-T, but not at the clinically performed 3-T examination, suggesting that there was no muscle invasion, which was confirmed by pathology.  Changes in tumor apparent diffusion coefficient values could be monitored in 2 patients and were found to increase during NAC, consistent with published results from studies at lower field strengths.  Apparent diffusion coefficient values increased respectively from 0.33 × 10(-3) mm(2)/s to 1.78 × 10(-3) mm(2)/s after NAC and from 1.20 × 10(-3) mm(2)/s to 1.44 × 10(-3) mm(2)/s during NAC.  Choline concentrations as low as 0.77 mM/kg(water) could be detected.  In 1 patient, choline levels showed an overall decrease from 4.2 mM/kg(water) to 2.6 mM/kg(water) after NAC and the tumor size decreased correspondingly from 3.9 × 4.1 × 5.6 cm(3) to 2.0 × 2.7 × 2.4 cm(3).  All 7-T MRI findings were consistent with pathology analysis.  The authors concluded that dedicated 7-T breast MRI is technically feasible, can provide more SNR than at 3-T, and has diagnostic potential.

An UpToDate review on “MRI of the breast and emerging technologies” (Slanetz, 2014) states that “High field strength MRI -- High field strength magnets (3-Tesla and 7-Tesla) provide higher signal to noise ratios than conventional breast MRI, performed with 1.5-Tesla field strength magnets.  The high field strength magnets result in higher spatial resolution and improved detection of breast cancers <5 mm in size than conventional techniques.  However, there are no large prospective trials that show clinical advantage for high field strength MRI.  In addition, the lack of widespread availability of higher field magnets limits applicability to clinical practice”.

Diagnosis of Fat Necrosis Post-Breast Reduction Surgery

Tuncbilek et al (2011) stated that non-traumatic rapid growing giant fat necrosis of the breast mimicking breast tumors is a rare clinical manifestation.  The imaging features of the fat necrosis that range from benign to malign findings may be better explained with associated etiology.  These researchers reported the case of a 54-year old woman with a rapid growing, fibrous, and hard giant mass originating in the sub-areolar region of the left breast.  Mammography and MRI demonstrated a heterogeneous, well circumscribed mass in 12 × 12 cm size in the left breast.  The lesion was suspected as a malignant tumor and underwent core biopsy.  The histopathology examination of the biopsy revealed mononuclear cells, foamy, vacuolated, and bubbly cells containing fat.  Excision biopsy of the mass was performed and the final pathological diagnosis was confirmed as fat necrosis.  The authors concluded that the wide clinical and radiologic manifestations of fat necrosis are still difficult to diagnose even with the new diagnostic modalities and a great proportion of these lesions need a biopsy to diagnose.

The American College of Radiology (ACR)’s Appropriateness Criteria on “Nonpalpable mammographic findings (excluding calcifications)” (2012) suggested considering “Return to screening mammography if the area can be confidently determined to be related to prior surgery (i.e., by scar marker) or the sequelae of trauma (e.g., presence of fat necrosis)”.  This was rendered a “4” rating (4, 5, 6 ratings denote “May be appropriate”).  The ACR’s Appropriateness Criteria on “Nonpalpable mammographic findings (excluding calcifications)” does not mention the use of MRI.

Kerridge et al (2015) stated that “Fat necrosis of the breast is a challenging diagnosis due to the various appearances on mammography, ultrasound, CT, positron emission tomography-computed tomography (PET-CT), and MRI.  Although mammography is more specific, ultrasound is a very important tool in making the diagnosis of fat necrosis.  MRI has a wide spectrum of findings for fat necrosis and the appearance is the result of the amount of the inflammatory reaction, the amount of liquefied fat, and the degree of fibrosis”.  In fact, specificity of post-operative MRI may be lowered by enhancing granulation tissue or fat necrosis at the surgical site.

An eMedicine’s review on “Postsurgical Breast Imaging” (Ackerman, 2015) did not mention breast MRI as a diagnostic tool for fat necrosis of the breast.

Furthermore, Radiopaedia.org’s Information Sheet on “Fat Necrosis of the Breast” (2015) stated that “Fat necrosis within the breast is a pathological process that occurs when there is saponification of local fat.  It is a benign inflammatory process and is becoming increasingly common with greater use of breast conserving surgery and mammoplasty procedures”.  It mentions mammography and breast ultrasound for the diagnosis of fat necrosis; but not breast MRI.

Routine Screening / Evaluation of Individuals with Nipple Discharge

The Institute for Clinical Systems Improvement’s clinical guideline on “Diagnosis of breast disease” (ICSI, 2012) provided the following information

  • Patients with a bloody or clear discharge should be referred to a radiologist and/or surgeon for further evaluation
  • A mammogram and ultrasound should be obtained with presence of bloody or clear discharge to rule out malignancy
  • Most pathologic nipple discharges should be treated with duct excision.  The use of ductography and/or MRI ductography is dependent on the decision of the surgeon and radiologist.

The Alberta Provincial Breast Tumor Team’s clinical guideline on “Magnetic resonance imaging for breast cancer screening, pre-operative assessment, and follow-up” (2012) stated that:

  • MRI is not recommended for the routine screening of patients with nipple discharge.

van Gelder et al (2015) noted that unilateral bloody nipple discharge (UBND) is mostly caused by benign conditions such as papilloma or ductal ectasia.  However, in 7 to 33 % of all nipple discharge, it is caused by breast cancer.  Conventional diagnostic imaging like mammography (MMG) and ultrasonography (US) is performed to exclude malignancy.  Preliminary investigations of breast magnetic resonance imaging (MRI) assume that it has additional value.  With an increasing availability of MRI, it is of clinical importance to evaluate this.  These investigators evaluated the additional diagnostic value of MRI in patients with UBND in the absence of a palpable mass, with normal conventional imaging.  All women with UBND in the period November 2007 to July 2012 were included.  In addition to the standard work-up (patient's history, physical examination, MMG, and US), MRI was performed.  Data from these examinations and treatment were collected retrospectively.  A total of 111 women (mean age 52 years; range of 23 to 80) were included.  In 9 (8 %) patients, malignancy was suspected on MRI while conventional imaging was normal.  In 8 (89 %) of these patients, histology was obtained, 2 by core biopsy and 6 by terminal duct excision.  Benign conditions were found in 6 patients (86 %) and a (pre)malignant lesion in 2 patients.  In both cases, it concerned a ductal carcinoma in-situ, which was treated with breast-conserving therapy.  Moreover, in 2 cases of (pre)malignancy, the MRI was interpreted as negative.  The authors concluded that in patients with UBND who showed no signs of a malignancy on conventional diagnostic examinations, the added value of a breast MRI is limited, since a malignancy can be demonstrated in less than 2 %.

An UpToDate review on “Nipple discharge” (Golshan and Iglehart, 2015) states that “Magnetic resonance imaging -- MRI is a relatively sensitive imaging modality with low to moderate specificity.  The role of MRI in the evaluation of nipple discharge is evolving.  In 52 patients with suspicious nipple discharge who were studied with a breast MRI; the sensitivity and specificity for malignancy were 77 and 62 %, respectively, with a median follow-up of 14 months.  The positive predictive value of MRI in this series was 56 %.  The significant false positive rate and somewhat limited availability of MR-guided biopsy limits the utility of this modality.  If MR is going to be used in this setting, it should be done in a facility that has MR biopsy capabilities.  MR ductography -- MR ductography is a different technique than standard breast MRI.  It utilizes heavy T2 weighting, which accentuates the visibility of fluid containing structures.  No directly instilled or intravenous contrast material is necessary.  MR ductography provides a 3D image and can show the precise shape and location of the abnormal duct and lesion in the breast.  However, this technique will not reveal ducts that are not dilated or those with low signal intensity on heavily T2-weighted images, due to hemorrhage or the presence of proteinaceous contents within the duct …. The workup of suspicious nipple discharge should include ultrasound and mammography.  The role of imaging is to determine whether there are any underlying lesions that may account for the symptom of nipple discharge and to target the area for surgical localization.  However, imaging studies do not reliably identify cancer or high-risk lesions in patients with nipple discharge.  Other diagnostic testing, including ductography, breast magnetic resonance imaging, magnetic resonance ductography, and ductoscopy can be helpful in selected women but are not routinely necessary for the work-up of nipple discharge”.

Furthermore, an UpToDate review on “MRI of the breast and emerging technologies” (Slanetz, 2015) states that “Although some have proposed breast MRI imaging for the evaluation of spontaneous nipple discharge when mammography and ultrasound of the periareolar area fail to identify a focal finding, we do not feel there is a role for MRI for this purpose.  A negative MRI does not preclude disease and pathologic nipple discharge should be managed with a terminal duct excision”.

Post-Surgical Intra-Operative Breast MRI for Quantifying Tumor Deformation and Detecting Residual Breast Cancer

Gombos and associates (2016) employed intra-operative supine MRI to quantify breast tumor deformation and displacement secondary to the change in patient positioning from imaging (prone) to surgery (supine) and evaluated residual tumor immediately after breast-conserving surgery (BCS).  A total of 15 women gave informed written consent to participate in this prospective HIPAA-compliant, institutional review board-approved study between April 2012 and November 2014; 12 patients underwent lumpectomy and post-surgical intra-operative supine MRI; 6 of 12 patients underwent both pre- and post-surgical supine MRI.  Geometric, structural, and heterogeneity metrics of the cancer and distances of the tumor from the nipple, chest wall, and skin were computed.  Mean and standard deviations (SDs) of the changes in volume, surface area, compactness, spherical disproportion, sphericity, and distances from key landmarks were computed from tumor models.  Imaging duration was recorded.  The mean differences in tumor deformation metrics between prone and supine imaging were as follows: volume, 23.8 % (range of -30 % to 103.95 %); surface area, 6.5 % (range of -13.24 % to 63 %); compactness, 16.2 % (range of -23 % to 47.3 %); sphericity, 6.8 % (range of -9.10 % to 20.78 %); and decrease in spherical disproportion, -11.3 % (range of -60.81 % to 76.95 %).  All tumors were closer to the chest wall on supine images than on prone images.  No evidence of residual tumor was seen on MRI obtained after the procedures.  Mean duration of pre- and post-operative supine MRI was 25 minutes (range of 18.4 to 31.6 minutes) and 19 minutes (range of 15.1 to 22.9 minutes), respectively.  The authors concluded that intra-operative supine breast MRI, when performed in conjunction with standard prone breast MI, enabled quantification of breast tumor deformation and displacement secondary to changes in patient positioning from standard imaging (prone) to surgery (supine) and may help clinicians evaluate for residual tumor immediately after BCS.  These preliminary findings need to be validated by well-designed studies.

Quantitative Breast MRI Predicting the Risk of Breast Cancer Recurrence

Li and colleagues (2016) examined the relationships between computer-extracted breast MRI phenotypes with multi-gene assays of MammaPrint, Oncotype DX, and PAM50 to assess the role of radiomics in evaluating the risk of breast cancer recurrence.  Analysis was conducted on an institutional review board-approved retrospective data set of 84 de-identified, multi-institutional breast MR examinations from the National Cancer Institute Cancer Imaging Archive, along with clinical, histopathological, and genomic data from the Cancer Genome Atlas.  The data set of biopsy-proven invasive breast cancers included 74 (88 %) ductal, 8 (10 %) lobular, and 2 (2 %) mixed cancers.  Of these, 73 (87 %) were estrogen receptor (ER)-positive, 67 (80 %) were progesterone receptor (PR)-positive, and 19 (23 %) were human epidermal growth factor receptor (EGFR)2-positive.  For each case, computerized radiomics of the MRI yielded computer-extracted tumor phenotypes of size, shape, margin morphology, enhancement texture, and kinetic assessment. Regression and receiver operating characteristic analysis were conducted to assess the predictive ability of the MR radiomics features relative to the multigene assay classifications. Results Multiple linear regression analyses demonstrated significant associations (R2 = 0.25 to 0.32, r = 0.5 to 0.56, p < 0.0001) between radiomics signatures and multi-gene assay recurrence scores.  Important radiomics features included tumor size and enhancement texture, which indicated tumor heterogeneity.  Use of radiomics in the task of distinguishing between good and poor prognosis yielded area under the receiver operating characteristic curve values of 0.88 (standard error [SE], 0.05), 0.76 (SE, 0.06), 0.68 (SE, 0.08), and 0.55 (SE, 0.09) for MammaPrint, Oncotype DX, PAM50 risk of relapse based on subtype, and PAM50 risk of relapse based on subtype and proliferation, respectively, with all but the latter showing statistical difference from chance.  The authors concluded that quantitative breast MRI radiomics showed promise for image-based phenotyping in assessing the risk of breast cancer recurrence.

Surveillance in Women after Breast Conservation Therapy

In a prospective study, Kim and colleagues (2017) examined the diagnostic performance and tissue changes in early (1 year or less) breast MRI surveillance in women who underwent BCS for breast cancer.  Between April 2014 and June 2016, a total of 414 women (mean age of 51.5 years; range of 21 to 81 years) who underwent 422 early surveillance breast MRI examinations (median of 6.0 months; range of 2 to 12 months) after BCS were studied.  The cancer detection rate, PPV of biopsy, sensitivity, specificity, accuracy, and area under the curve (AUC) of surveillance MRI, mammography, and US were assessed.  Follow-up was also obtained in 95 women by using PET/ CT.  Background parenchymal enhancement (BPE) changes in the contralateral breast were assessed according to adjuvant therapy by using the McNemar test.  Of 11 detected cancers, 6 were seen at MRI only, 1 was seen at MRI and mammography, 2 were seen at MRI and US, 1 was seen at mammography only, and 1 was seen at PET/CT only; 3 MRI-depicted cancers were observed at the original tumor bed, and 2 MRI-depicted cancers were observed adjacent to the original tumor.  Among 2 false-negative MRI diagnoses (2 cases of ductal carcinoma in-situ [DCIS]), 1 cancer had manifested as calcifications at mammography without differentiated enhancement at MRI, and the other cancer was detected at PET/CT, but MRI results were negative because of marked BPE, which resulted in focal lesion masking.  The PPV of biopsy and the sensitivity, specificity, accuracy, and AUC for MR imaging were 32.1 % (9 of 28), 81.8 % (9 of 11), 95.1 % (391 of 411), 94.7 % (400 of 422), and 0.88, respectively.  The sensitivity of surveillance MRI (81.8 %; 95 % CI: 48.2 % to 97.7 %) was higher than that of mammography (18.2 %; 95 % CI: 2.3 % to 51.8 %) and US (18.2 %; 95 % CI: 2.3 % to 51.8 %), with an overlap in CIs.  The BPE showed a significant decrease in the group of patients who received adjuvant chemotherapy (43 BPE decreases and 4 BPE increases) and the group of patients who received hormone therapy (55 BPE decreases and 2 BPE increases) (p < 0.0001 for both).  The authors concluded that early MRI surveillance after BCS can be useful in patients who have breast cancer, with superior sensitivity compared with that of mammography and US.  The BPE tends to be decreased at short-term follow-up MRI in patients who receive adjuvant therapy.

Cho and co-workers (2017) noted that younger women (aged less than or equal to 50 years) who underwent BCS may benefit from breast MRI screening as an adjunct to mammography.  In a prospective, multi-center, non-randomized study, these researchers ascertained the cancer yield and tumor characteristics of combined mammography with MRI or US screening in women who underwent BCS for breast cancers and who were 50 years or younger at initial diagnosis.  This trial was conducted from December 1, 2010, to January 31, 2016, at 6 academic institutions.  A total of 754 women who were 50 years or younger at initial diagnosis and who had undergone BCS for breast cancer were recruited to participate in the study.  Reference standard was defined as a combination of pathology and 12-month follow-up.  Participants underwent 3 annual MRI screenings of the conserved and contralateral breasts in addition to mammography and US, with independent readings.  Main outcomes measures were cancer detection rate (CDR), sensitivity, specificity, interval cancer rate, and characteristics of detected cancers.  Subjects underwent a total of 2,065 mammograms, US, and MRI screenings; 17 cancers were diagnosed, and most of the detected cancers (13 of 17 [76 %]) were stage 0 or stage 1.  Overall cancer detection rate (8.2 versus 4.4 per 1,000; p = 0.003) or sensitivity (100 % versus 53 %; p = 0.01) of mammography with MRI was higher than that of mammography alone.  After the addition of US, the cancer detection rate was higher than that by mammography alone (6.8 versus 4.4 per 1,000; p = 0.03).  The specificity of mammography with MRI or US was lower than that by mammography alone (87 % or 88 % versus 96 %; p < 0.001).  No interval cancer was found.  The authors concluded that the findings of this study suggested that the addition of MRI to mammography screening improved the detection of early-stage breast cancers at acceptable specificity in women who had BCS at 50 years or younger.  They stated that these results can be used not only to inform patient and clinician decision-making regarding the best methods of screening after BCS but also to develop more personalized screening guidelines and recommendations for women at increased risk for breast cancer.

The National Cancer Institute’s Breast cancer screening (PDQ) (2017) stated that breast MRI is used in women for diagnostic evaluation, including evaluating the integrity of silicone breast implants, assessing palpable masses after surgery or radiation therapy, detecting mammographically and sonographically occult breast cancer in patients with axillary nodal metastasis, and pre-operative planning for some patients with known breast cancer.|

Furthermore, the American Society of Breast Surgeons’ “Consensus Guideline on Diagnostic and Screening Magnetic Resonance Imaging of the Breast” (2017) support the use of breast MRI for the further evaluation of suspicious clinical or imaging findings that remain indeterminate after complete mammographic and sonographic evaluations.

Screening MRI in Women with a Person History of Breast Cancer

Lehman et al (2016) noted that screening MRI is recommended for individuals at high-risk for breast cancer, based on genetic risk or family history (GFH); however, there is insufficient evidence to support screening MRI for women with a personal history (PH) of breast cancer. These researchers compared screening MRI performance in women with PH versus GFH of breast cancer. They analyzed case-series registry data, collected at time of MRI and at 12-month follow-up, from their regional Clinical Oncology Data Integration project. MRI performance was compared in women with PH with those with GFH. Chi-square testing was used to identify associations between age, prior history of MRI, and clinical indication with MRI performance; logistic regression was used to determine the combined contribution of these variables in predicting risk of a false-positive exam. All statistical tests were 2-sided. Of 1,521 women who underwent screening MRI from July 2004 to November 2011, 915 had PH and 606 had GFH of breast cancer. Overall, MRI sensitivity was 79.4 % for all cancers and 88.5 % for invasive cancers. False-positive exams were lower in the PH versus GFH groups (12.3 % versus 21.6 %, p < 0.001), specificity was higher (94.0 % versus 86.0 %, p < 0.001), and sensitivity and cancer detection rate were not statistically different (p > 0.99). Age (p < 0.001), prior MRI (p < 0.001), and clinical indication (p < 0.001) were individually associated with initial false-positive rate; age and prior MRI remained statistically significant in multi-variable modeling (p = 0.001 and p < 0.001, respectively). The authors concluded that MRI performance was superior in women with PH compared with women with GFH. They stated that screening MRI warrants consideration as an adjunct to mammography in women with a PH of breast cancer. They stated that these findings suggested that MRI can enhance surveillance in women with a personal history of breast cancer by detecting mammographically occult invasive breast cancers while they are small and node-negative.

The authors stated that this study had limitation. First, it did not have detailed treatment history on all patients, nor sufficient numbers to compare smaller subgroups within the personal history cohort. These areas are important topics for further study. Also, these findings were from a single center, where breast MRI surveillance in women with a PH of breast cancer was used based on individual discussions of patients with their care providers. At the authors ’institution, decisions regarding MR surveillance were made on a case-by-case basis and after discussion of potential benefits and harms. In general, MRI tends to be offered more to women with dense breast tissue who are young and whose primary breast cancer was mammographically occult, but the decisions vary based on provider and patient-shared decision-making. Currently, given the equivocal recommendations by organizations with guidelines for surveillance of women following treatment, there is likely variation in practice of surveillance MRI after successful breast cancer treatment both within and outside of the authors’ center. At their institution, surveillance MRI may be more common, while at other institutions MRI may be reserved for those considered at the very highest risk for recurrence (i.e., patients with prior high-risk cancers or patients who did not receive radiation after breast-conserving surgery or who did not complete recommended hormonal therapy).

Commenting on the aforementioned study, Evans and Maxwell (2016) stated the following:

The authors did admit some other drawbacks to the study, including lack of treatment information and pathology of prior cancers; 4 of the breast cancers did not have information on whether they were ipsilateral or contralateral, and of the 16 with information half were ipsilateral, with most having the same pathology, suggesting they were recurrences rather than new primaries. Other drawbacks include the fact that the MRI scans were not read independently of the mammography findings and the diagnostic contribution of mammography was not presented, and it was therefore impossible to ascertain from these data the added effect of MRI on cancer detection and false-positive rates.

The authors pointed out that there were currently no recommendations in the United States for MRI surveillance of PH women. MRI screening of GFH women at very high-risk and who had a personal history of breast cancer is recommended in guidelines outside the United States, but MRI is not recommended for follow-up of PH women who are not otherwise at increased risk. The authors should nonetheless be congratulated for collating data that reflect current practice of MRI screening of higher-risk women in the United States, and the data did suggest that MRI may be a useful tool in early detection in the PH group, with better overall performance than in the predominantly moderate risk GFH group.

Although prevention of further primaries by risk-reducing mastectomy improves survival in women with BRCA mutations, there are still conflicting results regarding whether MRI in BRCA1 GFH women improves survival, and it may be more effective in BRCA2 and other women at very high-risk. There is some evidence in PH women that early detection of recurrences and new primaries with mammography improves survival, and other studies have suggested an additional diagnostic benefit of MRI over mammography although no survival advantage has been established. Nonetheless, selective use of MRI for post-treatment surveillance in those at high-risk of recurrence or in whom further malignancy may be otherwise difficult to detect (young women, those with dense breasts, and those with a mammographically occult first cancer) may have a place. A prospective multi-center study would help to answer these important questions.

Hedge et al (2017) stated that for women with a personal history of breast cancer (PHBC), no validated mechanisms exist to calculate future contralateral breast cancer (CBC) risk. The Manchester risk stratification guidelines were developed to evaluate CBC risk in women with a PHBC, primarily for surgical decision-making. This tool may be informative for the use of MRI screening, as CBC risk is an assumed consideration for high-risk surveillance. A total of 322 women with a PHBC were treated with unilateral surgery within the authors’ multi-disciplinary breast clinic. These researchers calculated lifetime CBC risk using the Manchester tool, which incorporates age at diagnosis, family history, genetic mutation status, estrogen receptor positivity, and endocrine therapy use. Uni-variate and multi-variate logistic regression analyses (UVA/MVA) were performed, evaluating whether CBC risk predicted MRI surveillance. For women with invasive disease undergoing MRI surveillance, 66 % had low, 23 % above-average, and 11 % moderate/high risk for CBC. On MVA, previous mammography-occult breast cancer [odds ratio (OR) 18.95, p < 0.0001], endocrine therapy use (OR 3.89, p = 0.009), dense breast tissue (OR 3.69, p = 0.0007), mastectomy versus lumpectomy (OR 3.12, p = 0.0041), and CBC risk (OR 3.17 for every 10 % increase, p = 0.0002) were associated with MRI surveillance. No pathologic factors increasing ipsilateral breast cancer recurrence were significant on MVA. The authors concluded that although CBC risk predicted MRI surveillance, 89 % with invasive disease undergoing MRI had less than 20% calculated CBC risk. Concerns related to future breast cancer detectability (dense breasts and/or previous mammography-occult disease) predominate decision-making. Pathologic factors important for determining ipsilateral recurrence risk, aside from age, were not associated with MRI surveillance.

The authors stated that this study had several limitations. Given the retrospective nature of this analysis, it was possible that there was incomplete information about the actual clinical decision making used for selecting MRI surveillance. Also, given that study was limited to a single institution, there were institutional and patient cohort qualities that may have introduced selection bias. Patient preference was not a factor noted in the medical records, although this may have been an unrecorded aspect to decision-making for MRI surveillance utilization. Furthermore, while the decision for MRI surveillance was made as part of a multi-disciplinary discussion, formal institutional standards were not in place for this decision-making. In addition, some patients who were undergoing mammography alone may be doing so based on health insurance-based factors or an inability to pay out-of-pocket for MRI surveillance, although this was a factor that was difficult to discern from retrospective medical record review. With that noted, few patients (4 %) met NCCN indications for MRI surveillance based on CBC risk and did not receive it. Moreover, to maximize statistical power for comparison, categories like breast density had multiple stratifications grouped together. Perhaps with a larger sample size and with more categories delineated, different results may be found. Lastly, this study examined predictors for MRI surveillance use and evaluated the rationale recorded for recommending this surveillance tool. However, it did not evaluate the actual outcomes of MRI surveillance in this cohort, as the cohort follow-up time was too short to do so (all patients were treated within the past 5 years). This analysis also did not specifically account for ipsilateral breast cancer recurrence risk, although the pathologic factors associated with this risk were all individually noted to be insignificant on MVA for the selection of MRI surveillance. Moreover, the Manchester algorithm has yet to undergo additional validation studies to ensure that it reliably calculates CBC risk. Finally, additional factors including breast tissue density may impact CBC risk and yet are not formally included in the Manchester tool.

Park and colleagues (2018) noted that women with a PH of breast cancer are at increased risk of future breast cancer events, and may benefit from supplemental screening methods that could enhance early detection of subclinical disease. However, current literature on breast MRI surveillance is limited. These researchers examined outcomes of surveillance breast MRI in women with a PH of breast cancer. They reviewed 1,053 consecutive breast MR examinations that were performed for surveillance in 1,044 women (median age of 53 years; range of 20 to 85 years) previously treated for breast cancer between August 2014 and February 2016. All patients had previously received supplemental surveillance with ultrasound. Cancer detection rate (CDR), abnormal interpretation rate and characteristics of MR-detected cancers were assessed, including extra-mammary cancers. These investigators also calculated the PPV1, PPV3, sensitivity and specificity for MR-detected intra-mammary lesions. Performance statistics were stratified by interval following initial surgery. The CDR for MR-detected cancers was 6.7 per 1,000 examinations (7 of 1,053) and was 3.8 per 1,000 examinations (4 of 1,053) for intra-mammary cancers. The overall abnormal interpretation rate was 8.0 %, and the abnormal interpretation rate for intra-mammary lesions was 7.2 %. The PPV1, PPV3, sensitivity and specificity for intra-mammary lesions was 5.3 % (4 of 76), 15.8 % (3 of 19), 75.0 % (3 of 4) and 98.3 % (1,031 of 1,049), respectively. For MR examinations performed less than or equal to 36 months after surgery, the overall CDR was 1.4 per 1,000 examinations. For MR examinations performed greater than 36 months after surgery, the overall CDR was 17.4 per 1,000 examinations. The authors concluded that these findings suggested that surveillance breast MR imaging may be considered in women with a history of breast cancer, considering the low abnormal interpretation rate and its high specificity. However, the cancer detection rate was low and implementation may be more effective after more than 3 years after surgery. Moreover, these researchers stated that further research on the appropriate timing for surveillance breast MR imaging initiation is needed, especially in patients who have undergone pre-operative breast MR imaging and supplemental surveillance US.

The authors noted that this study had several drawbacks. First, this was a retrospective study from a single institution. Although their institution recently implemented breast MRI into their post-treatment surveillance protocol to be performed 2 and 5 years after surgery, MRI was also performed at the request of clinicians or patients and therefore, the intervals between surgery and MRI were variable. Second, patients underwent surveillance with mammography and US prior to MRI, which could have affected the true cancer yield of MRI. Third, the median interval between initial breast cancer surgery and first-time surveillance MR examination (30.1 months, range of 12.1 to 240.2 months) was relatively short.

Breast MRI for Further Evaluation of Equivocal Findings on Digital Breast Tomosynthesis

Niell and colleagues (2018) evaluated the utility of MRI as a problem-solving tool for equivocal findings on diagnostic DM) and digital breast tomosynthesis (DBT).  Breast MRI examinations performed from March 2011 to November 2014 were retrospectively reviewed to identify those examinations that were performed to further assess equivocal findings on combined DM and DBT (DM/DBT) examinations.  All patients underwent diagnostic ultrasound (US) in conjunction with their DM/DBT examination.  Imaging reports were retrospectively reviewed for BI-RADS findings and assessments of diagnostic DM/DBT and diagnostic MRI examinations.  A review of the electronic medical records provided information on demographic data, cancer diagnoses, and pathologic findings.  Differences in the PPV and negative predictive values (NPVs) of DM/DBT and MRI were compared using a generalized estimating equation for correlated binary data.  Of 5,330 MRI examinations performed during the study, 67 (1 %) were performed for evaluation of an equivocal finding, including 27 asymmetries (40 %), 16 focal asymmetries (24 %), 5 masses (7 %), and 19 architectural distortion (28 %); MRI correlates were identified in 22 of 67 examinations (33 %).  Biopsies yielded a cancer diagnosis for 5 of 67 patients (7 %).  For MRI, the PPV and NPV were 19 % and 98 %, respectively, whereas for DM/DBT they were 6 % and 90 %, respectively (p = 0.009 and p = 0.059, respectively).  The frequency of recommendations for breast MRI to evaluate equivocal findings decreased exponentially in the 3 years after DBT implementation.  The authors concluded that as clinical implementation of DBT becomes increasingly widespread, breast radiologists need an algorithm for addressing the small number of inconclusive findings that remain equivocal despite thorough DM/DBT and US examinations.  They stated that breast MRI is a useful adjunctive tool for these selected cases.

Evaluation of Retro-Pectoral Fat Grafting in Breast Reduction

Guimaraes and colleagues (2019) noted that one of the challenges in breast reduction is to maintain breast projection with 45 % of its volume in the upper pole and 55 % in the lower pole.  Although widely used in breast surgeries, the behavior of fat grafts is still not completely understood.  In a pilot study, these researchers evaluated by MRI the survival of fat transferred to the retro-pectoral plane in patients undergoing breast reduction, in the search for an oncologically safe procedure with high predictability and reproducibility.  This trial was carried out with 7 patients who underwent breast reduction combined with fat grafting in the sub-muscular plane; aspirated fat was processed by sedimentation; MRI of the breasts was performed pre-operatively and at 1 and 6 months post-operatively.  Fat survival was calculated as the difference between the volumes of fat measured pre-operatively and post-operatively by MRI divided by the volume of grafted fat.  A total of 14 breasts were operated on and received on average 119.6 ml of autologous fat in the sub-muscular plane.  Fat survival rate was 43.9 % at 1 month after surgery, decreasing to 23.4 % in the late post-operative period.  The mean antero-posterior projection of the grafted tissue was 1.51 cm at 1 month post-operatively, decreasing to 1.07 cm in the late post-operative period.  The authors concluded that retro-pectoral fat grafting may contribute to maintaining the fullness of the upper pole of the breasts.  These investigators stated that this is an innovative experimental model for future studies on fat harvesting, preparation and grafting techniques, allowing the evaluation of fat graft survival.

Breast MRI with Contrast for Follow-Up/Surveillance in Invasive Breast Cancer, or Ductal Carcinoma In Situ

According to NCCN’s Imaging Appropriate Use Criteria for “Breast Cancer” (Version.2.2018), breast MRI with contrast is not indicated for follow-up/surveillance in invasive breast cancer, or DCIS.

Evaluation of Atypical Ductal Hyperplasia

An UpToDate review on “Atypia and lobular carcinoma in situ: High-risk lesions of the breast” (Sabel and Collins, 2019) states that “Magnetic resonance imaging (MRI) of the breast is more sensitive than mammography in detecting invasive breast cancers in high-risk women, but it is less specific, especially for younger women.  A large number of unnecessary biopsies will be generated while finding cancer in only a small group of patients.  Despite that, MRI can detect smaller cancers and more node-negative malignancies in high-risk women than other imaging modalities; however, there is no evidence for a reduction in mortality or improved disease-free survival from screening with MRI.  There are insufficient data to support annual screening with MRI for women who are of an average risk, or an intermediate risk, such as those with a biopsy revealing AH or LCIS.  A prospective database that included 776 women with LCIS found that women screened with MRI in addition to mammography and clinical breast examinations (n = 455) had the same crude breast cancer detection rate of 13 % at a median of 58 months of follow-up.  MRI was not associated with earlier stage of detection, smaller tumor size, or node negativity.  Consequently, guidelines from major groups, including the American Cancer Society (ACS) and the NCCN, only integrate breast MRI into their recommendations for breast cancer surveillance in high-risk women (i.e., an estimated lifetime risk of breast cancer greater than 20 to 25 %, calculated using BRCAPRO or a similar model based on family history, rather than the Gail model)”.

Quantitative Measurements of Breast Density

Sindi and colleagues (2019) noted that breast density, a measure of dense fibro-glandular tissue relative to non-dense fatty tissue, is confirmed as an independent risk factor of breast cancer.  Although there has been an increasing interest in the quantitative assessment of breast density, no research has examined the optimal technical approach of breast MRI in this aspect.  These researchers carried out a systematic review and meta-analysis to analyze the current studies on quantitative assessment of breast density using MRI and to determine the most appropriate technical/operational protocol.  Databases (PubMed, Embase, ScienceDirect, and Web of Science) were searched systematically for eligible studies.  Single-arm meta-analysis was conducted to determine quantitative values of MRI in breast density assessments.  Combined means with their 95 % CI were calculated using a fixed-effect model.  Furthermore, subgroup meta-analyses were performed with stratification by breast density segmentation/measurement method.  In addition, alternative groupings based on statistical similarities were identified via a cluster analysis employing study means and standard deviations in a Nearest Neighbor/Single Linkage.  A total of 38 studies matched the inclusion criteria for this systematic review; 21 of these studies were judged to be eligible for meta-analysis.  The results indicated, generally, high levels of heterogeneity between study means within groups and high levels of heterogeneity between study variances within groups.  The studies in 2 main clusters identified by the cluster analysis were also subjected to meta-analyses.  The review confirmed high levels of heterogeneity within the breast density studies, considered to be due mainly to the applications of MR breast-imaging protocols and the use of breast density segmentation/measurement methods.  The authors concluded that further research should be performed to determine the most appropriate protocol and method for quantifying breast density using MRI.

The authors stated that this meta-analysis had several drawbacks.  First, the heterogeneity of study aims, the study design utilized, and the technical/operational methods applied, for instance, the MR breast-imaging protocol, MR scanner manufacturer, and the static magnetic field strength presented challenges for performing the meta-analysis.  Second, the breast density segmentation/measurement algorithm used was another drawback.  Although these researchers classified the included studies into discrete subgroups (i.e., FCM, FCM and N3, and interactive semi-automated threshold), and applied stratified analyses, the heterogeneity remained.  Third, the definition of the breast density was inconsistent because some studies reported it as a percentage of dense breast volume, while the others as a percentage of breast density.  Fourth, among the 38 studies included in this analysis, only 21 studies were eligible for meta-analysis due to the statistical requirements for the input values that should be in identical expression of measurement and dispersion.  Furthermore, some of the included studies used the same set of the subject multiple times for different purpose and feature.  Although these investigators decided to rectify the issue by selecting one of the results of data at random, or by any meaningful clinical criterion, the heterogeneity continued to exist.  Notwithstanding these drawbacks, the study further supported the idea of developing a standard MRI protocol for the quantitative assessment of breast density.

Abbreviated Breast MRI (FAST MRI) for Breast Cancer Screening

Abbreviated breast MRI (also known as FAST MRI) is an approach that entails shorter image acquisition and interpretation time; it has been studied for screening and diagnosis of breast cancer.

Choi and associates (2018) the usefulness of abbreviated breast MRI (abMRI), including fat-suppressed T2-weighted imaging, pre- and post-contrast image acquisition, and subtracted maximum-intensity projection imaging, for the screening of women with a history of breast cancer surgery.  Between October 2014 and March 2016, a total of 799 abMRI examinations were performed for 725 women with a history of breast cancer surgery.  The image acquisition time was 8.5 mins.  Screening MMG, US and abMRI were generally performed around the same time.  The cancer detection rate, PPVs for recall and biopsy, sensitivity and specificity of screening MRI, and rate of malignancy belonging to each BI-RADS category were assessed; abMRI detected 12 malignancies in 12 women (15.0 cancers per 1,000 cases); 7 of these 12 malignancies were initially invisible on US and MMG, although subsequent targeted US revealed lesions corresponding to the MRI-detected lesions.  The PPVs for recall and biopsy and sensitivity and specificity values for screening MRI were 12.4, 61.5, 100, and 89.2 %, respectively.  The rates of malignancies belonging to categories 1, 2, 3, and 4 of the BI-RADS were 0, 0, 4.8, and 57.1 %, respectively.  The authors concluded that the  diagnostic performance of screening abMRI for women with a history of breast cancer surgery was acceptable, with the advantages of short examination and interpretation times and low costs; therefore, it could be used as a main screening modality that may replace conventional imaging in breast cancer survivors.

Leithner and co-workers (2019) stated that MRI of the breast is the most sensitive test for breast cancer detection and out-performs conventional imaging with MMG, DBT, or US.  However, the long scan time and relatively high costs limit its widespread use.  Hence, it is currently only routinely implemented in the screening of women at an increased risk of breast cancer.  To overcome these limitations, abbreviated dynamic contrast-enhanced (DCE)-MRI protocols have been introduced that substantially shorten image acquisition and interpretation time while maintaining a high diagnostic accuracy.  Efforts to develop abMRI protocols reflect the increasing scrutiny of the disproportionate contribution of radiology to the rising overall healthcare expenditures.  Healthcare policy makers are now focusing on curbing the use of advanced imaging examinations such as MRI while continuing to promote the quality and appropriateness of imaging.  An important cornerstone of value-based healthcare defines value as the patient's outcome over costs.  Therefore, the concept of a fast, abMRI examination is very appealing, given its high diagnostic accuracy coupled with the possibility of a marked reduction in the cost of an MRI examination. Given recent concerns about gadolinium-based contrast agents, unenhanced MRI techniques such as diffusion-weighted imaging (DWI) are also being investigated for breast cancer diagnosis.  The authors concluded that although further larger prospective studies with rigorous standardization, and reproducibility studies are needed, initial results with abMRI protocols suggested that it appeared feasible to offer screening breast DCE-MRI to a broader population.

These researchers stated that although results from previous studies examining abMRI protocols were promising, they might not be generalizable to a broad population.  To-date, these protocols have only been examined for breast cancer screening and still have to be evaluated for their value in the diagnostic setting or for neoadjuvant chemotherapy response assessment.  Furthermore, the calculated time for these protocols may not reflect the entire time of the examination, as there are other work-flow considerations such as set-up, room turn-over, safety screening, and IV placement that must be considered.  However, with training of personnel and work‐flow optimization an abMRI examination will still be substantially shorter than one with a full protocol and allow higher volume patient throughput.  Another aspect that needs to be considered is that, although in the study setting reading times can be substantially shortened, it has to be seen where this will translate into clinical reality where an MRI interpretation may also include reviewing patient's history and priors.  These investigators stated that abMRI protocols still need refinement, standardization across sites, and validation by prospective multi-center trials before they can be implemented into clinical routine.  Nevertheless, it can be expected that abMRI protocols will play an important role in breast imaging in the future.

Geach and colleagues (2021) synthesized evidence comparing abbreviated breast MRI (abMRI) to full-protocol MRI (fpMRI) in breast cancer screening.  These investigators carried out a systematic search in multiple data-bases.  Cohort studies without enrichment, presenting accuracy data of abMRI in screening, for any level of risk (population, moderate, high risk) were included.  Level of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).  Meta-analyses (bi-variate random effects model) were performed for abMRI, with fpMRI and histology from fpMRI-positive cases as reference standard, and with follow-up to symptomatic detection added to the fpMRI.  The review also covered evidence comparing abMRI with mammographic techniques.  The title and abstract review retrieved 23 articles; 5 studies (6 articles) were included (2,763 women, 3,251 screening rounds).  GRADE assessment of the evidence was very low because the reference standard was interpreted with knowledge of the index test and biopsy was not obtained for all abMRI positives.  The overall sensitivity for abMRI, with fpMRI (and histology for fpMRI positives) as reference standard, was 94.8 % (95 % CI: 85.5 to 98.2) and specificity as 94.6 % (95 % CI: 91.5 to 96.6); 3 studies (1,450 women, 1,613 screening rounds) presented follow-up data, enabling comparison between abMRI and fpMRI.  Sensitivities and specificities for abMRI did not differ significantly from those for fpMRI (p = 0.83 and p = 0.37, respectively).  The authors concluded that a very low level of evidence suggested abMRI could be accurate for breast cancer screening.  Moreover, these investigators stated that further research is needed, with follow-up to interval cancer, to determine the effect its use could have on clinical outcome.

An and co-workers (2020) examined the feasibility of abMRI in women with a personal history (PH) of breast cancer as a screening tool.  These investigators retrospectively reviewed 1,880 screening abMRIs in 763 women with a PH of breast cancer (median age of 55 years; range of 23 to 89 years) between October 2015 and October 2016.  The total acquisition times of abMRI were 8.3 mins and 2.8 mins with and without T2-weighted imaging, respectively.  The tissue diagnosis or 1-year follow-up status was used as the reference standard.  The characteristics of tumor recurrences detected on abMRI screenings were analyzed.  The CDRs and additional CDRs for the 1st round and overall rounds of abMRI screening were calculated.  The recall rate, sensitivity, specificity, PPV for recall (PPV1) and biopsy (PPV3) for the 1st round of abMRI screening were calculated.  The diagnostic performance of the combination of MMG and US was compared with that of abMRI by receiver operating characteristic (ROC) curve analysis; 15 of a total of 21 recurrences were detected on the 1st round of abMRI screening: 93.3 % were node-negative T1 tumors (median tumor size of 1.02 cm; range of 0.1 to 2 cm) or Tis; 66.7 % were high-grade tumors; 8 of these 15 were mammographically and ultrasonographically occult.  The CDR and additional CDR for the 1st round of abMRI screening were 0.019 and 0.010 per woman, respectively.  The sensitivity, specificity, recall rate, PPV1 and PPV3 for the 1st round of abMRI screening were 100 %, 96.0 %, 14.3 %, 13.8 % and 58.3 %, respectively.  For detecting secondary cancer, abMRI showed a higher sensitivity and PPV than the combination of MMG and US (95.2 %, 57.1 % versus 47.6 %, 38.5 %).  The area under the ROC curve was higher for abMRI (0.966; 95 % CI: 0.951 to 0.978) than the combination of MMG and US (0.727; 95 % CI: 0.694 to 0.759) (p < 0.0001).  The authors concluded that  abMRI improved cancer detection with a high specificity, sensitivity and PPV in women with a PH of breast cancer.  These researchers stated that abMRI could be a useful screening tool for detecting secondary cancer considering its high diagnostic performance and short examination time.

The authors stated that this study had several drawbacks.  First, this was a retrospective study from a single institution.  Selection bias could have affected the true cancer yield of abMRI, which might limit the generalizability of these findings.  Second, the authors’ institution recently implemented abMRI screening into surveillance protocols; thus, the interval between the initial surgery and the 1st round of abMRI screening varied.  Third, these researchers did not examine the effect of using T2WI for the evaluation of incidental breast lesions in decreasing unnecessary recall and excluding false positive findings.  Fourth, these investigators could not examine the appropriate interval/frequency, the cost-effectiveness or the survival benefit of abMRI screening.  These researchers stated that continued prospective, randomized, multi-center study is needed for the wide application of abMRI screening in this population.

Furthermore, an UpToDate review on “MRI of the breast and emerging technologies” (Slanetz, 2020) states that “Abbreviated breast MRI for breast cancer screening consists of a shortened imaging protocol such that patients are on the MRI scanner for no more than 10 to 15 minutes in total, as compared with 25 to 40 minutes for a full diagnostic study.  There are a few retrospective studies in women with variable risk profiles and breast density that have shown that the abbreviated MRI protocol has comparable sensitivity with the full diagnostic protocol.  In addition, one study in women with prior breast surgery showed that when an abbreviated MRI protocol was compared with screening breast US and mammography, the MRI detected all 12 cancers, 7 of which were not detected on the other modalities, suggesting that abbreviated MRI may eventually have a role in screening women at increased risk for breast cancer.  However, at present, this approach remains investigational”.

Breast MRI Screening for Women Positive for APC, CHEK2 and GALNT12 Genes

National Comprehensive Cancer Network’s Biomarkers Compendium (2020) does not list APC and GALNT12 to be associated with breast cancer (invasive or non-invasive).

Narod (2021) discussed the findings of 2 large case-control studies that analyzed the associations between a number of putative cancer susceptibility genes and breast cancer risk.  The study by Dorling et al (2021) included 34 genes and 113,000 women from 25 countries, and the study by Hu et al (2021) included 28 genes and 64,000 women from the U.S.  Variants in 8 genes -- BRCA1, BRCA2, PALB2, BARD1, RAD51C, RAD51D, ATM, and CHEK2 -- had a significant association with breast cancer risk in both studies.  Furthermore, there was a significant association for variants in MSH6 in the international study only and for variants in CDH1 in the U.S.  The distribution of mutations among women with breast cancer (case patients) was different from the distribution among unaffected women (controls).  Among case patients, the majority of mutations were in BRCA1, BRCA2, and PALB2, and among controls, the majority of mutations were in CHEK2 and ATM. This difference is a consequence of the relative penetrance of mutations in BRCA1, BRCA2, and PALB2, which were associated with a high risk of breast cancer, and of mutations in CHEK2 and ATM, which were associated with a moderate risk.  There are a few management options.  Most breast cancers that occur in women with a mutation in ATM or CHEK2 are estrogen receptor positive, so these women may be candidates for anti-estrogen therapies such as tamoxifen, raloxifene, or aromatase inhibitors.  However, chemoprevention studies have not been performed in women who carry a mutation in ATM or CHEK2, and the uptake of tamoxifen is low, even among carriers of a BRCA1 or BRCA2 mutation.  Preventive salpingo-oophorectomy is not justified; and preventive mastectomy is a questionable approach for women with a lifetime breast cancer risk of 20 % to 25 %.  For the majority of women with a mutation in ATM or CHEK2, management consists of screening alone.  The NCCN clinical practice guideline on “Genetic/familial high-risk assessment: Breast, ovarian, and pancreatic” (Version 1.2022) recommends screening with MRI (with contrast) starting at 40 years of age for carriers of variants in these genes; however, such intensified surveillance in these women has not yet proven to reduce mortality.

Hu and colleagues (2021) carried out a population-based case-control study using a customized multi-gene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium.  Associations between pathogenic variants in each gene and the risk of breast cancer were examined.  These researchers found that pathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03 % of case patients and in 1.63 % of controls.  Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with ORs of 7.62 and 5.23, respectively.  Pathogenic variants in PALB2 were associated with a moderate risk.  Pathogenic variants in BARD1, RAD51C, and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM, CDH1, and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer.  Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657_661del5 founder pathogenic variant in NBN, were not associated with an increased risk of breast cancer.  The authors concluded that this study provided estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population.  These estimates could inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes.

The authors stated that this study had several drawbacks.  Enrollment was restricted to women 50 years of age or older in certain population-based studies in the CARRIERS consortium, which had the potential to influence the generalizability of the aggregate estimates of the prevalence of pathogenic variants in BRCA1 and BRCA2 to younger women; however, sensitivity analyses that excluded the Women’s Health Initiative and the Cancer Prevention Study II (studies that involved women at an older age at enrollment) did not substantially influence the findings.  Furthermore, the statistical model for penetrance estimation was based on the assumptions that the underlying population-based SEER rates, prevalence of pathogenic variants, and age-specific estimates of ORs reflected those in the general population.  These investigators stated that future studies are needed to examine the calibration of the probability estimates.  Another potential drawback was that the sequencing was carried out in a research laboratory rather than a commercial genetic-testing facility.  However, the customized QIAseq panel was shown to have high sensitivity and specificity for pathogenic variants in predisposition genes.  Additionally, because all samples were sequenced in a single center and variants were called through a single pipeline, issues with bioinformatics and batch effects were minimized.  In addition, it was not possible to study the effects of individual pathogenic variants on breast cancer risk because of the rarity of the variants.

Gallagher et al (2021) discussed comprehensive breast cancer risk assessment for CHEK2 and ATM pathogenic variant carriers with the incorporation of a polygenic risk score and the Tyrer-Cuzick model.  These researchers described comprehensive risk prediction models for women of European ancestry combining PV status, PRS, and individual clinical variables.  This study included de-identified clinical records from 358,095 women of European ancestry who received testing with a multi-gene panel (September 2013 to November 2019).  Model development included CHEK2 PV carriers (n = 4,286), ATM PV carriers (n = 2,666), and women negative for other breast cancer risk gene PVs (n = 351,143).  Odds ratios (ORs) were calculated using multivariable logistic regression with adjustment for familial cancer history.  Risk estimates incorporating PV status, PRS, and Tyrer-Cuzick v7.02 were calculated using a Fixed-Stratified method that accounts for correlations between risk factors.  Stratification of PV carriers into risk categories on the basis of remaining lifetime risk (RLR) was assessed in independent cohorts of PV carriers.  ORs for association of PV status with breast cancer were 2.01 (95 % CI,: 1.88 to 2.16) and 1.83 (95 % CI: 1.68 to 2.00) for CHEK2 and ATM PV carriers, respectively.  ORs for PRS per 1 standard deviation (SD) were 1.51 (95 % CI: 1.37 to 1.66) and 1.45 (95 % CI: 1.30 to 1.64) in CHEK2 and ATM PV carriers, respectively.  Using the combined model (PRS plus Tyrer-Cuzick plus PV status), RLR was low (less than or equal to 20 %) for 24.2 % of CHEK2 PV carriers, medium (20 % to 50 %) for 63.8 %, and high (greater than 50 %) for 12.0 %.  Among ATM PV carriers, RLR was low for 31.5 % of patients, medium for 58.5 %, and high for 9.7 %.  The authors concluded that in CHEK2 and ATM PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.

These investigators stated that this study had several drawbacks.  First, it included potential valuation bias because it was based on a clinical testing population cohort.  However, it has been previously shown that this potential bias could be avoided by accounting for family history in the logistic regression model.  Second, this study used only women of European ancestry.  These researchers stated that further studies are needed to examine polygenic breast cancer risk for women of non-European ancestry, including PV carriers and non-carriers.  Furthermore, the clinical factors included in this risk assessment included PV carrier status, factors from the Tyrer-Cuzick model, and a SNP-based PRS.  Incorporation of additional clinical factors such as breast density may be needed to further customize risk calculations.  Finally, this study was carried out using an 86-SNP PRS and a prospectively tested clinical patient cohort collected as early as 2013 without storage of residual test materials per state regulations.  The 86-SNP PRS was developed using the most impactful SNPs published at the time, although recent studies have reported additional PRSs containing more SNPs, which may be tested prospectively using large cohorts in the future.  Recent literature has shown that increasing the number of SNPs in a PRS provided only incrementally more information than a PRS with a smaller SNP composition.  The authors stated that although future work may expand the SNP profiles for commercially available PRSs, this and other recent work showed that these risk models provide important clinical information to inform individual patient cancer risks.

Furthermore, National Comprehensive Cancer Network’s clinical practice guidelines on “Breast cancer” (Version 1.2022) and “Breast cancer screening and diagnosis” (Version 1.2021) do not mention CHEK2 mutation as a risk factor for development of breast cancer.

Atypical Lobular Hyperplasia at High Risk for Breast Cancer

An UpToDate on “Atypia and lobular carcinoma in situ: High-risk lesions of the breast” (Sabel and Collins, 2022) stated that “Magnetic resonance imaging (MRI) of the breast is more sensitive than mammography in detecting invasive breast cancers in high-risk women, but it is less specific, especially for younger women.  A large number of unnecessary biopsies will be generated while finding cancer in only a small group of patients.  Despite that, MRI can detect smaller cancers and more node-negative malignancies in high-risk women than other imaging modalities; however, there is no evidence for a reduction in mortality or improved disease-free survival from screening with MRI.  There are insufficient data to support annual screening with MRI for women who are of an average risk, or an intermediate risk, such as those with a biopsy revealing atypical hyperplasia (AH) or lobular carcinoma in situ (LCIS).  A prospective database that included 776 women with LCIS found that women screened with MRI in addition to mammography and clinical breast examinations (n = 455) had the same crude breast cancer detection rate of 13 % at a median of 58 months of follow-up.  MRI was not associated with earlier stage of detection, smaller tumor size, or node negativity.  Consequently, guidelines from major groups, including the American Cancer Society (ACS) and the NCCN, only integrate breast MRI into their recommendations for breast cancer surveillance in high-risk women (i.e., an estimated lifetime risk of breast cancer greater than 20 to 25 %, calculated using BRCAPRO or a similar model based on family history, rather than the Gail model)”.

Furthermore, NCCN Clinical Practice Guidelines “Breast cancer screening and diagnosis” (Version 1.2022) provided the following information:

Consider annual MRI screening for individuals with atypical ductal hyperplasia (ADH) or lobular neoplasia (lobular carcinoma in situ (LCIS)/atypical lobular hyperplasia (ALH)) and ≥ 20 % residual lifetime risk.

Women with LCIS or ALH/ADH with a lifetime risk of ≥ 20 % should be considered for breast MRI based on emerging evidence of the benefits.

MUTYH Mutation

National Comprehensive Cancer Network’s Biomarkers Compendium (2022) does not list breast cancer to be associated with MUTYH mutation.

Women with Dense Breasts and/or Fibrocystic Breast Disease

In 2020, ACOG re-affirmed their 2015 Committee Opinion statement: “Women with dense breasts have a modestly increased risk of breast cancer and experience reduced sensitivity of mammography to detect breast cancer.  However, evidence is lacking to advocate for additional testing until there are clinically validated data that indicate improved screening outcomes.  Currently, screening mammography remains the most useful tool for breast cancer detection and consistently has demonstrated a reduction in breast cancer mortality.  The American College of Obstetricians and Gynecologists does not recommend routine use of alternative or adjunctive tests to screening mammography in women with dense breasts who are asymptomatic and have no additional risk factors.  The American College of Obstetricians and Gynecologists recommends that health care providers comply with state laws that may require disclosure to women of their breast density as recorded in a mammogram report”.

Furthermore, National Comprehensive Cancer Network’s clinical practice guideline on “Breast cancer” (Version 4.2022) states that “The use of MRI I the workup remains controversial.  Breast MRI advocates note its high sensitivity for evaluation of extent of disease, particularly for invasive cancer and in dense breast where mammographically occult disease is more likely to elude preoperative detection.  MRI detractors note that MRI has a high percentage of false-positive findings, resulting in further diagnostic workup – including MRI-guided biopsy – in many circumstances.  MRI findings tend to overestimate extent of disease, resulting in increased frequency of mastectomies.  MRI findings alone are not sufficient to determine whether BCT [breast-conserving therapy] is optimal, as additional tissue sampling is needed to verify true malignant disease warranting excision”.


Appendix

Breast Cancer Staging

Information about breast cancer staging is available from the National Cancer Institute at the following website: Breast Cancer Treatment.

Breast Cancer Risk Assessment Models

Software for each of the breast cancer models referenced the American Cancer Society guidelines (Saslow et al, 2007) is available via the internet:

Breast cancer risk can also be estimated online using the Gail Model Breast Cancer Risk Assessment Tool available from the National Cancer Institute's website: Breast Cancer Risk Assessment Tool or at the following link: Gail Model for Breast Cancer Risk.


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