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Aetna Aetna
Clinical Policy Bulletin:
Breast Transillumination, Electrical Impedance Scanning (EIS), and Elastography
Number: 0386


Policy

  1. Aetna considers transillumination (light scanning or diaphanography) of the breast experimental and investigational because this technique has not been established by the peer-reviewed medical literature to be an acceptable alternative to conventional mammography in detecting breast cancer.

  2. Aetna considers electrical impedance scanning (EIS) of the breast to be experimental and investigational because there is inadequate evidence in the peer-reviewed published medical literature of the ability of this method to distinguish benign from malignant breast lesions or the effectiveness of EIS of the breast in improving clinical outcomes.

  3. Aetna considers breast elastography by any method (i.e., ultrasound or magnetic resonance) experimental and investigational because there is insuffcient evidence of its effectiveness in improving clinical outcomes.

See also CPB 0105 - Magnetic Resonance Imaging (MRI) of the BreastCPB 0269 - Breast Biopsy ProceduresCPB 0337 - BreastAlert Differential Temperature SensorCPB 0517 - Breast Ductal Lavage and Fiberoptic Ductoscopy; and CPB 0584 - Mammography.



Background

Mammography remains the generally accepted standard for breast cancer screening and diagnosis.  However, efforts to provide new insights regarding the origins of breast disease and to find different approaches for addressing several key challenges in breast cancer, including detecting disease in mammographically dense tissue, distinguishing between malignant and benign lesions, and understanding the impact of neoadjuvant chemotherapies, has lead to the investigation of several novel methods of breast imaging for breast cancer management.

Breast Transillumination:

Breast transillumination (also known as light scanning, diaphanography, optical imaging, optical mammography, dynamic optical breast imaging (DOBI), optical transillumination spectroscopy, diffuse optical spectroscopy (DOS), and transillumination breast spectroscopy) is based on the theory that normal and abnormal tissues reflect different light intensities.  Various transilluminators have been created to screen and diagnose cancers of the breast.  One such device, the Computed Tomography Laser Mammography (CTLM) (Imaging Diagnostic Systems Inc., Fort Lauderdale, FL), is a near-infrared (NIR) laser breast imaging system that measures the absorption of NIR light by hemoglobin.  Another method currently under investigation is opto-acoustic tomography (OAT) imaging.  This hybrid imaging technique combines optic and acoustic imaging to map the distribution of optical absorption within biological tissues by means of laser-induced ultrasonic signals.

Breast transilluminators have not been proven to be an acceptable alternative to conventional mammography.  The U.S. Food and Drug Administration (FDA)'s Obstetrics and Gynecology Devices Advisory Panel (1991) considered the clinical utility of breast transilluminators and concluded that "[e]xcept in investigational settings, the devices do not provide meaningful clinical information and should not be used in the clinical evaluation of breast tissue, neither alone nor in conjunction with other techniques."  An Agency for Healthcare Research and Quality Clinical Practice Guideline (Bassett et al, 1994) concluded that “[l]ight scanning (diaphanography and transillumination) should not be used for screening or diagnostic evaluation of the breast”.  The British Columbia Cancer Agency (2001) has concluded that “[a]t the present state of development, transillumination is not an appropriate imaging device for breast cancer screening.”  The American Cancer Society (2009) stated that these experimental imaging tests are still in the earliest stages of research.

Electrical Impedance Scanning (EIS):

Experimental studies have shown that significant changes occur in the electrical properties of breast cancer tissue compared to the surrounding normal tissue.  This phenomenon motivated studies on cancer detection using electrical impedance techniques.  Some evidence has been found that malignant breast tumors have lower electrical impedance than surrounding normal tissues.  This observation has led to the proposal that electrical impedance could be used as an indicator for breast cancer detection.  However, the separation of malignant tumors from benign lesions based on impedance measurements needs further investigation.  There are no prospective clinical studies demonstrating the clinical utility of electrical impedance scanning (EIS) in distinguishing benign from malignant breast lesions, either in place of or as an adjunct to mammography or magnetic resonance imaging.  An assessment of technologies for breast cancer screening and diagnosis conducted by the Institute of Medicine of the National Academy of Sciences (2001) concluded that “[c]linical data suggest the technology [EIS] could play a role in breast cancer detection, but more study is needed to define a role in relation to existing technologies.”

Stojadinovic et al (2005) presented preliminary results on the use of EIS for the early detection of breast cancer in young women.  They stated that EIS appears promising for early detection of breast cancer, and identification of young women at increased risk for having the disease at time of screening.  Positive EIS-associated breast cancer risk compares favorably with relative risks of conditions commonly used to justify early breast cancer screening.  The authors also noted that more data are needed to ascertain more accurately the actual sensitivity.  These investigators also believe that EIS has promise as a breast cancer screening modality for a group of women for whom no effective screening modality currently exists.  Electrical impedance scanning seems to identify a population at increased risk for having breast cancer for whom further imaging examinations may be warranted.

On August 29, 2006, the FDA's Obstetrics and Gynecology Devices Panel voted unanimously not to recommend approval of Mirabel Medical Systems' T-Scan 2000 ED bioimpedance device, which is designed to evaluate the risk of breast cancer in asymptomatic women aged 30 to 39 years with no family history of breast cancer and no other known risk factors.  The device would be employed in combination with clinical breast examination for this age group whose annual examination does not usually entail mammography.

The FDA panel decided that the data did not provide a reasonable assurance of the effectiveness to support the device's proposed indication.  Furthermore, some panel members were concerned with other aspects of the clinical trial: (i) the apparent differences in the characteristics of the 2 trial populations (1,751 women aged 30 to 39 years in the study arm designed to measure specificity and 390 women aged 30 to 45 years in the study arm measuring sensitivity), (ii) a lack of ethnicity data, and (iii) a "high" false-positive rate (Taulbee, 2006).

Blackmore et al (2007) stated that risk assessment by parenchymal density pattern, a strong physical indicator of future breast cancer risk, is available with the onset of mammographic screening programmes.  However, due to the use of ionizing radiation, mammography is not recommended for use in younger women, thereby rendering risk assessment unattainable at an earlier age.  These investigators reported on the use of visible and near infra-red light on 292 women with radiologically normal mammograms to determine if transillumination breast spectroscopy (TIBS) can identify women with a high parenchymal density pattern as an intermediate indicator of breast cancer risk.  Principal component analysis was used to reduce the spectral data and generate density scores for each woman.  To assess the accuracy of TIBS, logistic regression was used to calculate crude and adjusted odds ratios (OR) and 95 % confidence intervals (CI) for each score.  Receiver operator characteristic curves and area under the curve (AUC) were also calculated for the crude and adjusted logistic models.  Optical information relating to tissue chromophores, such as water, lipid and hemoglobin content, was sufficient to identify women with high parenchymal density.  The resulting AUC for the final and most parsimonious multi-variate logistic model was 0.922 (95 % CI: 0.878 to 0.967).  The authors concluded that TIBS provides information correlating to high parenchymal density and is a promising tool for risk assessment, particularly for younger women.  Furthermore, Blackmore and colleagues (2008) also reported that TIBS scores may prove useful as intermediate markers in studies of breast cancer etiology and prevention.

In a prospective, two-cohort trial of pre-menopausal women, Stojadinovic et al (2008) estimated the relative probability of breast cancer in T-Scan+ women compared to randomly selected young women.  The Specificity (S(p))-Cohort evaluated T-Scan specificity in 1,751 asymptomatic women aged 30 to 39.  The Sensitivity)S(n))-Cohort evaluated T-Scan sensitivity in 390 women aged 45 to 30 scheduled for biopsy.  Specificity, sensitivity, and conservative estimate of disease prevalence were used to calculate relative probability.  In the S(p)-Cohort, 93 of 1,751 women were T-Scan+ (S(p) = 94.7 %; 95 % CI: 93.7 to 95.7 %).  In the S(n)-Cohort, 23 of 87 biopsy-proven cancers were T-Scan+ (S(n) = 26.4 %; 95 % CI: 17.4 to 35.4 %).  Given S(p) = 94.7 %, S(n) = 26.4 % and prevalence of 1.5 cancers/1,000 women (aged 30 to 39), the relative probability of a T-Scan+ woman having Br-Ca is 4.95: (95 % CI: 3.16 to 7.14).  The authors concluded that EIS can identify a subset of young women with a relative probability of breast cancer almost 5 times greater than in the population of young women at-large.  The drawbacks of this study were discussed by the afore-mentioned FDA panel.

In a prospective, multi-center study, Wang et al (2010) reported the sensitivity and specificity for the combination of EIS and ultrasound in identifying breast cancer and calculated the relative risk of breast cancer in young women (n = 583) aged 45 years and under scheduled for mammary biopsy.  Of the 583 cases, 143 were diagnosed with breast cancer.  The sensitivities of EIS, ultrasound and the combination method were 86.7 % (124/143), 72 % (103/143), and 93.7 % (134/143) and the specificities were 72.9 % (321/440), 82.5 % (363/440), and 64.1 % (282/440), respectively.  The relative possibilities of breast cancer for the positive young women detected by EIS, ultrasound, and the combination method were 8.67, 5.77, and 14.84, respectively.  The authors concluded that the combination of EIS and ultrasound is likely to become an applicable method for early detection of breast cancer in young women. 

Elastography:

Elastography refers to the measurement of elastic properties of tissues and is based on the principle that malignant tissue is harder than benign tissue.  Manual palpation in the detection of breast cancer suggests that breast elastography could potentially provide a diagnostic tool for detecting cancerous lesions deeper within the breast.  The technique is typically performed with ultrasound (US), but research with magnetic resonance (MR) is also under way.  Advantages of the US elastography are ubiquitous applicability and cost-effectiveness.  Magnetic resonance elastography (MRE) offers improved reconstruction and the possibility to assess potential anisotropic properties. 

There are 3 main types of US elasticity imaging: (i) elastography that tracks tissue movement during compression to obtain an estimate of strain, (ii) sonoelastography that uses color Doppler to generate an image of tissue movement in response to external vibrations, and (iii) tracking of shear wave propagation through tissue to obtain the elastic modulus.

The SonixTouch Ultrasound Imaging System received 510(k) marketing clearance by the FDA in October, 2008.  The device includes an elastography imaging mode.  Mechanical pressure with the hand on the transducer produces an imaging sequence similar to the B-mode sequence except the system will acquire the radio-frequency signal instead of acquiring B mode data.  The algorithm extracts a strain value information for every point on the image.  The elastography image then color-codes the stiff versus softer structures.

Magnetic resonance elastography is a phase-contrast-based magnetic resonance imaging (MRI) technique that can directly visualize and quantitatively measure propagating acoustic strain waves in tissue subjected to harmonic mechanical excitation.  The data acquired allows the calculation of local quantitative values of shear modulus and the generation of images that depict tissue elasticity or stiffness.

Garra et al (1997) examined the feasibility of elastography to determine the appearance of various breast lesions and the potential of elastography to diagnosis breast lesions.  A total of 46 breast lesions were examined with elastography.  Patients underwent biopsy or aspiration of all lesions, revealing 15 fibroadenomas, 12 carcinomas, 6 fibrocystic nodules, and 13 other lesions.  The elastogram was generated from radio-frequency data collected with use of a 5-MHz linear-array transducer.  The elastogram and corresponding sonogram were evaluated by a single observer for lesion visualization, relative brightness, and margin definition and regularity.  The sizes of the lesions at each imaging examination and at biopsy were recorded and compared.  Softer tissues such as fat appeared as bright areas on elastograms.  Firm tissues, including parenchyma, cancers, and other masses, appeared darker.  The cancers were statistically significantly darker than fibroadenomas (p < 0.005) and substantially larger on the elastogram than on the sonogram.  A total of 73 % of fibroadenomas and 56 % of solid benign lesions could be distinguished from cancers by using lesion brightness and size difference.  Some cancers that appeared as areas of shadowing on sonograms appeared as discrete masses on elastograms.  The authors concluded that elastography has the potential to be useful in the evaluation of areas of shadowing on the sonogram and that it may be helpful in the distinction of benign from malignant masses.

Lorenzen et al (2002) explored the potential of elasticity as a parameter for the diagnosis of breast lesions using MRE in 15 female patients with malignant tumors of the breast, 5 patients with benign breast tumors, and 15 healthy volunteers.  Malignant invasive breast tumors documented the highest values of elasticity with a median of 15.9 kPa and a wide range of stiffnesses between 8 and 28 kPa.  In contrast, benign breast lesions represented low values of elasticity, which were significantly different from malignant breast tumors (median elasticity: 7.0 kPa; p = 0.0012).  This was comparable to the stiffest tissue areas in healthy volunteers (median elasticity 7.0 kPa), whereas breast parenchyma (median: 2.5 kPa) and fatty breast tissue (median: 1.7 kPa) showed the lowest values of elasticity. Two invasive ductal carcinomas had elasticity values of 8 kPa and two stiff parenchyma areas in healthy volunteers had elasticities of 13 and 15 kPa.  These lesions could not be differentiated by their elasticity.  The authors concluded that MRE is a promising new imaging modality with the capability to assess the viscoelastic properties of breast tumors and the surrounding tissues; however, there is an overlap in the elasticity ranges of soft malignant tumors and stiff benign lesions.

Sinkus et al (2005) examined the viscoelastic shear properties of breast lesions measured by MRE applied in the course of standard MR mammography to 15 patients with different pathologies (6 breast cancer cases, 6 fibroadenoma cases and 3 mastopathy cases).  Breast cancer appeared on average 2.2 (p < 0.001) times stiffer.  All breast cancer cases showed a good delineation to the surrounding breast tissue with an average elevation of a factor of 3.3 (p < 1.4 x 10(-6)).  However, the results were not found to be useful for separating benign from malignant lesions.

Giuseppetti et al (2005) assessed the diagnostic accuracy of elastography in characterizing nodular breast lesions.  A total of 82 patients who received mammographic, US and elastographic evaluation in a single session at two Italian centers between January and August 2004 according to identical protocols exhibited 91 nodules that were subjected to cytological/histological examination.  Lesions were classified and scored and the sensitivity and specificity of elastography calculated.  Overall sensitivity and specificity were 79 % and 89 %, respectively.  However, sensitivity was 86 % and 65 % and specificity 100 % and 62 % for lesions less than 2 cm and greater than 2 cm in diameter, respectively.  The authors concluded that larger studies are needed to establish semiological patterns.

Itoh et al (2006) evaluated the diagnostic performance of real-time elastography (RTE) by using the extended combined autocorrelation method (CAM) to differentiate benign from malignant breast lesions, with pathologic diagnosis as the reference standard.  Conventional US and RTE with CAM were performed in 111 women (mean age of 49.4 years; age range of 27 to 91 years) who had breast lesions (59 benign, 52 malignant).  Elasticity images were assigned an elasticity score according to the degree and distribution of strain induced by light compression.  The area under the curve and cut-off point, both of which were obtained by using a receiver operating characteristic curve analysis, were used to assess diagnostic performance.  Mean scores were examined by using a Student t test.  Sensitivity, specificity, and accuracy were compared by using the standard proportion difference test or the Delta-equivalent test.  For elasticity score, the mean +/- standard deviation was 4.2 +/-  0.9 for malignant lesions and 2.1 +/- 1.0 for benign lesions (p < 0.001). When a cut-off point of between 3 and 4 was used, elastography had 86.5 % sensitivity, 89.8 % specificity, and 88.3 % accuracy.  When a best cut-off point of between 4 and 5 was used, conventional US had 71.2 % sensitivity, 96.6 % specificity, and 84.7 % accuracy.  Elastography had higher sensitivity than conventional US (p < 0 .05).  By using equivalence bands for non-inferiority or equivalence, it was shown that the specificity of elastography was not inferior to that of conventional US and that the accuracy of elastography was equivalent to that of conventional US.  The authors concluded that US elastography with the proposed imaging classification had almost the same diagnostic performance as conventional US.

Thomas et al (2006) compared the sensitivity and specificity of elastography with that of B-mode US and mammography in 300 patients with histologically confirmed breast lesions (168 benign, 132 malignant).  Evaluation was by means of the 3-dimensional (3-D) finite-element method.  The data were color-coded and superimposed on the B-mode US scan.  The images were evaluated by two independent readers.  The results were compared with mammography, histology, and the data obtained by previous US investigations.  Sensitivity and specificity in the differentiation of benign and malignant lesions were 87 % and 85 %, respectively, for mammography and 94 % and 83 % for B-mode US.  The 2 examiners were in very good agreement in their evaluation of the elastograms (kappa: 0.86).  Elastography had a sensitivity of 82 % and a specificity of 87 %.  Elastography was superior to B-mode US in diagnosing Breast Imaging Reporting and Data System (BI-RADS) 3 lesions (92 % versus 82 % specificity) and in lipomatous involution (80 % versus 69 % specificity).

Zhang et al (2006) investigated the clinical value of RTE in the diagnosis of breast cancer in 120 patients with breast lumps (135 lesions).  Patients were examined with B-mode imaging, color Doppler flowing imaging (CDFI) and RTE.  The elastogram was graded using a 5-score evaluating method.  The post-operative pathological diagnosis was used as the gold standard, and the sensitivity, specificity and accuracy of RTE and 2-D US combined with RTE in diagnosis of breast cancer were calculated.  When the score greater than 4 was set for cut-off criteria of malignancy, the sensitivity, specificity and accuracy of RTE was 85.45 %, 83.75 % and 84.4 %, respectively.  When 2-D US combined with RTE was used, the sensitivity, specificity and accuracy increased up to 100 %, 95 % and 97 %, respectively.

Thomas et al (2006) evaluated whether RTE could improve the differentiation and characterization of benign and malignant breast lesions.  Real-time elastography was carried out in 108 potential breast tumor patients with cytologically/histologically confirmed focal breast lesions (59 benign, 49 malignant; median age, 53.9 years; range of 16 to 84 years).  Tumor and healthy tissue were differentiated by measurement of elasticity based on the correlation between tissue properties and elasticity modulus.  Evaluation was performed using the 3-D finite element method, in which the information is color-coded and superimposed on the B-mode US image.  A second observer evaluated the elastography images, in order to improve the objectivity of the method.  The results of B-mode scan and elastography were compared with those of histology and previous sonographic findings.  Sensitivities and specificities were calculated, using histology as the gold standard.  B-mode US had a sensitivity of 91.8 % and a specificity of 78 %, compared with sensitivities of 77.6 % and 79.6 % and specificities of 91.5 % and 84.7 %, respectively, for the two observers evaluating elastography.  Agreement between B-mode US and elastography was good, yielding a weighted kappa of 0.67.  The authors concluded that RTE improves the specificity of breast lesion diagnosis and is a promising new approach for the diagnosis of breast cancer. 

Zhi et al (2007) compared the use of US elastography with mammography, and sonography in the diagnosis of solid breast lesions.  From September 2004 to May 2005, 296 solid lesions from 232 consecutive patients were diagnosed as benign or malignant by mammography and sonography and further analyzed with US elastography.  The diagnostic results were compared with histopathologic findings.  The sensitivity, specificity, accuracy, positive and negative predictive values, and false-positive and -negative rates were calculated for each modality and the combination of US elastography and sonography.  Of 296 lesions, 87 were histologically malignant, and 209 were benign.  Ultrasound elastography was the most specific (95.7 %) and had the lowest false-positive rate (4.3 %) of the 3 modalities.  The accuracy (88.2 %) and positive predictive value (PPV) (87.1 %) of US elastography were higher than those of sonography (72.6 % and 52.5 %, respectively).  The sensitivity values, negative predictive values (NPV), and false negative rates of the 3 modalities had no differences.  A combination of US elastography and sonography had the best sensitivity (89.7 %) and accuracy (93.9 %) and the lowest false-negative rate (9.2 %).  The specificity (95.7%) and PPV (89.7%) of the combination were better, and the false-positive rate (4.3%) of the combination was lower than those of mammography and sonography.  The authors concluded that US elastography is a promising technique for evaluating breast lesions.

Tardivon et al (2007) evaluated elastography in the characterization of breast nodules in 122 lesions.  Elastography (Hitachi, 7.5- to 13-MHz probe; Ueno classification, scores 1-3 = benign, 4-5 = malignant) was evaluated in 125 sub-clinical lesions in 114 patients.  The results were compared to those of the American College of Radiology's BI-RADS sonography categories (benign = 2 and 3, malignant = 4 and 5) and to the results of the percutaneous samples taken and/or surgery (122 lesions evaluated, 59 % less than 10 mm, 61 cancers, 61 benign lesions).  There were 3 technical failures (2.4 %).  The elastography was in agreement with histology for 101 lesions, with 13 false-negative results and 8 false-positive results (sensitivity, 78.7 %; specificity, 86.9 %; PPV, 85.7 %; NPV, 80.3 %); versus agreement with the BI-RADS classification for 98 lesions with one false-negative result and 23 false-positive results (sensitivity, 98.4 %; specificity, 47.5 %; PPV, 65.2 %; NPV, 96.7 %).

Cho et al (2008) compared the diagnostic performances of conventional US and US elastography for the differentiation of non-palpable breast masses, and to evaluate whether elastography is helpful at reducing the number of benign biopsies, using histological analysis as a reference standard.  Conventional US and RTE images were obtained for 100 women who had been scheduled for a US-guided core biopsy of 100 non-palpable breast masses (83 benign, 17 malignant).  Two experienced radiologists unaware of the biopsy and clinical findings analyzed conventional US and elastographic images by consensus, and classified lesions based on degree of suspicion regarding the probability of malignancy.  Results were evaluated by receiver operating characteristic (ROC) curve analysis.  In addition, the authors investigated whether a subset of lesions were categorized as suspicious by conventional US, but as benign by elastography.  Areas under the ROC curves (Az values) were 0.901 for conventional US and 0.916 for elastography (p = 0.808).  For BI-RADS category 4a lesions, 44 % (22 of 50) had an elasticity score of 1 and all were found to be benign.  The authors concluded that elastography had a diagnostic performance comparable to that of conventional US for the differentiation of non-palpable breast masses.

Researchers have tested the feasibility of breast elastography and the results confirm the hypothesis that breast elastography can quantitatively depict the elastic properties of breast tissues and reveal high shear elasticity in known breast tumors.  However, the clinical benefits of elastography imaging are still under evaluation and no clinical diagnosis can be made other than being able to tell whether or not a structure inside the patient is stiffer than another one.  Further research is needed to evaluate the potential clinical applications of breast elastography, such as detecting breast carcinoma and characterizing suspicious breast lesions.

Kumm and Szabunio (2010) evaluated the application and diagnostic performance of elastography for the characterization of breast lesions in patients referred for biopsy.  Subjects referred for ultrasound-guided biopsy of sonographically apparent breast lesions were included in this study.  The Hitachi Hi-Vision 900 ultrasound was used to generate index test results for elastography scoring (ES) and for strain ratio (SR) measurement.  Sensitivity, specificity, PPV and NPV were determined using pathologic results from 14-gauge core needle biopsy as the reference standard.  A total of 310 lesions in 288 patients were included in this series.  Of these 310 lesions, 223 (72 %) were benign and 87 (28 %) were malignant.  Sensitivity was 0.76 for ES and 0.79 for SR.  Specificity was 0.81 for ES and 0.76 for SR.  The PPV was 0.60 for ES and 0.57 for SR; the NPV was 0.90 for ES and 0.90 for SR.  Strain ratio values for malignant lesions were significantly higher (median ratios of 10.5 and 2.7, respectively, p < 0.001).  The authors concluded that while the initial clinical performance of elastography imaging shows potential to reduce biopsy of low-risk lesions, a large-scale trial addressing appropriate patient selection, diagnostic parameters, and practical application of this technique is needed before widespread clinical use.

Siegmann et al (2010) assessed the additional value of MRE to contrast-enhanced (ce) MRI for breast lesion characterisation.  A total fo 57 suspected breast lesions in 57 patients (mean age of 52.4 years) were examined by ce MRI and MRE.  All lesions were classified into BI-RADS categories.  Viscoelastic parameters, e.g., alpha0 as an indicator of tissue stiffness, were calculated. Histology of the lesions was correlated with BI-RADS and viscoelastic properties.  The PPV for malignancy, and the sensitivity and specificity of ce MRI were calculated.  The ROC curves were separately calculated for both ce MRI and viscoelastic properties and conjoined to analyse the accuracy of diagnostic performance.  The lesions (mean size of 27.6 mm) were malignant in 64.9 % (n = 37) of cases.  The PPV for malignancy was significantly (p < 0.0001) dependent on BI-RADS classification.  The sensitivity of ce MRI for breast cancer detection was 97.3 % (36/37), whereas specificity was 55 % (11/20).  If ce MRI was combined with alpha0, the diagnostic accuracy could be significantly increased (p < 0.05; AUC(ce MRI) = 0.93, AUC(combined) = 0.96).  The authors concluded that the combination of MRE and ce MRI could increase the diagnostic performance of breast MRI.  Moreover, they stated that further investigations of larger cohorts and smaller lesions (in particular those only visible on MRI) are needed to validate these findings.

Yi et al (2012) evaluated the diagnostic value of sonoelastography by correlation with histopathology compared with conventional ultrasound on the decision to biopsy.  Prospectively determined BI-RADS categories of conventional ultrasound and elasticity scores from strain sonoelastography of 1,786 non-palpable breast masses (1,523 benign and 263 malignant) in 1,538 women were correlated with histopathology.  The sensitivity and specificity of 2 imaging techniques were compared regarding the decision to biopsy.  These researchers also investigated whether there was a subset of benign masses that were recommended for biopsy by B-mode ultrasound but that had a less than 2 % malignancy rate with the addition of sonoelastography.  The mean elasticity score of malignant lesions was higher than that of benign lesions (2.94 +/- 1.10 versus 1.78 +/- 0.81) (p < 0.001).  In the decision to biopsy, B-mode ultrasound had higher sensitivity than sonoelastography (98.5 % versus 93.2 %) (p < 0.001), whereas sonoelastography had higher specificity than B-mode ultrasound (42.6 % versus 16.3 %) (p < 0.001).  BI-RADS category 4a lesions with an elasticity score of 1 had a malignancy rate of 0.8 %.  The authors concluded that sonoelastography has higher specificity than B-mode ultrasound in the differentiation between benign and malignant masses and has the potential to reduce biopsies with benign results.

Landoni and colleagues (2012) developed a quantitative method for breast cancer diagnosis based on elastosonography images in order to reduce whenever possible unnecessary biopsies.  The proposed method was validated by correlating the results of quantitative analysis with the diagnosis assessed by histopathologic examination.  A total of 109 images of breast lesions (50 benign and 59 malignant) were acquired with the traditional B-mode technique and with elastographic modality.  Images in Digital Imaging and COmmunications in Medicine format (DICOM) were exported into a software, written in Visual Basic, especially developed to perform this study.  The lesion was contoured and the mean grey value and softness inside the region of interest (ROI) were calculated.  The correlations between variables were investigated and receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of the proposed method.  Pathologic results were used as standard reference.  Both the mean grey value and the softness inside the ROI resulted statistically different at the t-test for the 2 populations of lesions (i.e., benign versus malignant): p <0.0001.  The area under the curve (AUC) was 0.924 (0.834 to 0.973) and 0.917 (0.826 to 0.970) for the mean grey value and for the softness respectively.  The authors concluded that quantitative elastosonography is a promising ultrasound technique in the detection of breast cancer; but large prospective trials are needed to determine if quantitative analysis of images can help to overcome some pitfalls of this method.

In a meta-analysis, Sadigh et al (2012) reviewed evidence on diagnostic performance of strain ratio and length ratio, 2 different strain measurements in ultrasound elastography (USE), for differentiating benign and malignant breast masses.  A literature search of PubMed and other medical and general purpose databases from inception through January 2012 was conducted.  Published studies that evaluated the diagnostic performance of USE alone reporting either strain ratio or length ratio for characterization of focal breast lesions and using cytology (fine needle aspiration) or histology (core biopsy) as a reference standard were included.  Summary diagnostic performance measures were assessed using bi-variate generalized linear mixed modeling.  A total of 9 studies reported strain ratio for 2,087 breast masses (667 cancers, 1,420 benign lesions).  Summary sensitivity and specificity were 88 % (95 % CI: 84 to 91 %), and 83 % (95 % CI: 78-88 %), respectively.  The positive and negative likelihood ratios (LR) were 5.57 (95 % CI: 3.85 to 8.01) and 0.14 (95 % I: 0.09 to 0.20), respectively.  The inconsistency index for heterogeneity was 6 % (95 % CI: 1 to 22 %) for sensitivity and 8 % (95 % CI: 3 to 24 %) for specificity.  Analysis of 3 studies reporting length ratio for 450 breast masses demonstrated sensitivity and specificity of 98 % (95 % CI: 93 to 99 %) and 72 % (95 % CI: 31 to 96 %), respectively.  Strain ratio and length ratio have good diagnostic performance for distinguishing benign from malignant breast masses.  The authors concluded that although, this performance may not be incrementally superior to that of BI-RADS in B-mode ultrasound, the application of USE using strain ratio or length ratio in combination with USB may have the potential to benefit the patients, and this requires further comparative effectiveness and cost-effectiveness analyses.

Vreugdenburg et al (2013) evaluated all the available evidence of safety, effectiveness and diagnostic accuracy for three emerging classes of technology promoted for breast cancer screening and diagnosis: Digital infrared thermal imaging (DITI), EIS and elastography.  A systematic search of seven biomedical databases (EMBASE, PubMed, Web of Science, CRD, CINAHL, Cochrane Library, Current Contents Connect) was conducted through March 2011, along with a manual search of reference lists from relevant studies.  The principal outcome measures were safety, effectiveness, and diagnostic accuracy.  Data were extracted using a standardized form, and validated for accuracy by the secondary authors.  Study quality was appraised using the quality assessment of diagnostic accuracy studies tool, while heterogeneity was assessed using forest plots, Cooks' distance and standardized residual scatter plots, and I (2) statistics.  From 6,808 search results, a total of 267 full-text articles were assessed, of which 60 satisfied the inclusion criteria.  No effectiveness studies were identified.  Only 1 EIS screening accuracy study was identified, while all other studies involved symptomatic populations.  Significant heterogeneity was present among all device classes, limiting the potential for meta-analyses.  Sensitivity and specificity varied greatly for DITI (Sens = 0.25 to 0.97, Spec = 0.12 to 0.85), EIS (Sens = 0.26 to 0.98, Spec = 0.08-to 0.81) and ultrasound elastography (Sens = 0.35 to 1.00, Spec = 0.21 to 0.99).  The authors concluded that there is currently insufficient evidence to recommend the use of these technologies for breast cancer screening.  Moreover, the high level of heterogeneity among studies of symptomatic women limits inferences that may be drawn regarding their use as diagnostic tools.  They stated that future research employing standardized imaging, research and reporting methods is needed.

 
CPT Codes / HCPCS Codes / ICD-9 Codes
CPT codes not covered for indications listed in the CPB:
There is no specific CPT code for breast transillumination
0346T
Other CPT codes related to the CPB:
77055
77056
77057
ICD-9 codes not covered for indications listed in the CPB:
174.0 - 174.9 Malignant neoplasm of female breast
198.81 Secondary malignant neoplasm of the breast
217 Benign neoplasm of breast
233.0 Carcinoma in situ of breast
610.0 - 611.9 Disorders of breast


The above policy is based on the following references:
  1. National Coverage Determination (NCD) for Transillumination Light Scanning or Diaphanography (30.9).
  2. Sabel M, Aichinger H. Recent developments in breast imaging. Phys Med Biol. 1996;41(3):315-368.
  3. Gandjbakhche AH, Nossal R, Bonner RF. Resolution limits for optical transillumination of abnormalities deeply embedded in tissues. Med Phys. 1994;21(2):185-191.
  4. Jackson VP, Hendrick RE, Feig SA, et al. Imaging of the radiographically dense breast. Radiology. 1993;188(2):297-301.
  5. Heywang-Kobrunner SH. Nonmammographic breast imaging techniques. Curr Opin Radiol. 1992;4(5):146-154.
  6. Jarlman O, Andersson I, Balldin G, et al. Diagnostic accuracy of lightscanning and mammography in women with dense breasts. Acta Radiol. 1992;33(1):69-71.
  7. Jarlman O, Balldin G, Andersson I, et al. Relation between lightscanning and the histologic and mammographic appearance of malignant breast tumors. Acta Radiol. 1992;33(1):63-68.
  8. Braddick MR. Audit of a breast cancer screening programme using clinical examination and lightscanning. Health Bull (Edinb). 1991;49(6):299-303.
  9. Centers for Disease Control. Inappropriate use of transillumination for breast cancer screening -- Wisconsin, 1990. MMWR Morb Mortal Wkly Rep. 1991;40(18):293-296.
  10. Alveryd A, Andersson I, Aspegren K, et al. Lightscanning versus mammography for the detection of breast cancer in screening and clinical practice. A Swedish multicenter study. Cancer. 1990;65(8):1671-1677.
  11. Gordenne W, Bauduin E. Diagnostic accuracy of new imaging techniques in breast diseases. J Belge Radiol. 1989;72(1):35-38.
  12. No authors listed. Reassessment of transillumination light scanning for the diagnosis of breast cancer. Health Technol Assess Rep. 1988;(2):1-7.
  13. Bassett LW, Hendrick RE, Bassford TL, et al. Quality determinants of mammography. Clinical Practice Guideline No. 13. AHCPR Publication No. 95-0632. Rockville, MD: Agency for Health Care Policy and Research; October 1994.
  14. Malich A, Fuchsjager M. Electrical impedance scanning in classifying suspicious breast lesions. Invest Radiol. 2003;38(5):302-304.
  15. Zou Y, Guo Z. A review of electrical impedance techniques for breast cancer detection. Med Eng Phys. 2003;25(2):79-90.
  16. Glickman YA, Filo O, Nachaliel U, et al. Novel EIS postprocessing algorithm for breast cancer diagnosis. IEEE Trans Med Imaging. 2002;21(6):710-712.
  17. Cherepenin VA, Karpov AY, Korjenevsky AV, et al. Three-dimensional EIT imaging of breast tissues: System design and clinical testing. IEEE Trans Med Imaging. 2002;21(6):662-667.
  18. Kerner TE, Paulsen KD, Hartov A, et al. Electrical impedance spectroscopy of the breast: Clinical imaging results in 26 subjects. IEEE Trans Med Imaging. 2002;21(6):638-645.
  19. Martin G, Martin R, Brieva MJ, Santamaria L. Electrical impedance scanning in breast cancer imaging: Correlation with mammographic and histologic diagnosis. Eur Radiol. 2002;12(6):1471-1478.
  20. Kerne TE, Hartov A, Soho SK, et al. Imaging the breast with EIS: an initial study of exam consistency. Physiol Meas. 2002;23(1):221-236.
  21. Wersebe A, Siegmann K, Krainick U, et al. Diagnostic potential of targeted electrical impedance scanning in classifying suspicious breast lesions. Invest Radiol. 2002;37(2):65-72.
  22. Malich A, Bohm T, Facius M, et al. Additional value of electrical impedance scanning: Experience of 240 histologically-proven breast lesions. Eur J Cancer. 2001;37(18):2324-2330.
  23. Malich A, Boehm T, Facius M, et al. Differentiation of mammographically suspicious lesions: Evaluation of breast ultrasound, MRI mammography and electrical impedance scanning as adjunctive technologies in breast cancer detection. Clin Radiol. 2001;56(4):278-283.
  24. Cherepenin V, Karpov A, Korjenevsky A, et al. A 3D electrical impedance tomography (EIT) system for breast cancer detection. Physiol Meas. 2001;22(1):9-18.
  25. Wang W, Tang M, McCormick M, Dong X. Preliminary results from an EIT breast imaging simulation system. Physiol Meas. 2001;22(1):39-48.
  26. Malich A, Fritsch T, Anderson R, et al. Electrical impedance scanning for classifying suspicious breast lesions: First results. Eur Radiol. 2000;10(10):1555-1561.
  27. Perlet C, Kessler M, Lenington S, et al. Electrical impedance measurement of the breast: Effect of hormonal changes associated with the menstrual cycle. Eur Radiol. 2000;10(10):1550-1554.
  28. Ohmine Y, Morimoto T, Kinouchi Y, et al. Noninvasive measurement of the electrical bioimpedance of breast tumors. Anticancer Res. 2000;20(3B):1941-1946.
  29. Hayes JC. Electrical impedance images for breast gain FDA approval. Diagn Imaging (San Franc). 1999;21(6):19-20.
  30. Radai MM, Abboud S, Rosenfeld M. Evaluation of impedance technique for detecting breast carcinoma using a 2-D numerical model of the torso. Ann N Y Acad Sci. 1999;873:360-369.
  31. Chauveau N, Hamzaoui L, Rochaix P, et al. Ex vivo discrimination between normal and pathological tissues in human breast surgical biopsies using bioimpedance spectroscopy. Ann N Y Acad Sci. 1999;873:42-50.
  32. Jossinet J, Schmitt M. A review of parameters for the bioelectrical characterization of breast tissue. Ann N Y Acad Sci. 1999;873:30-41.
  33. U.S. Food and Drug Administration (FDA). FDA approves new breast imaging device. FDA Talk Paper. T99-18. Rockville, MD: FDA; April 19, 1999. Available at: http://www.fda.gov/bbs/topics/ANSWERS/ANS00950.html. Accessed September 5, 2003.
  34. National Academy of Sciences, Institute of Medicine, National Cancer Policy Board, Committee on the Early Detection of Breast Cancer. Mammography and Beyond: Developing Technologies for the Early Detection of Breast Cancer. Washington, DC: National Academy Press; 2001.
  35. BC Cancer Agency. Breast - diagnosis. Types of cancer and sequelae. Patient/Public Information. Vancouver, BC; BC Cancer Agency; revised November 2001. Available at: http://www.bccancer.bc.ca/. Accessed June 16, 2004.
  36. Tromberg BJ, Cerussi A, Shah N, et al. Imaging in breast cancer: Diffuse optics in breast cancer: detecting tumors in pre-menopausal women and monitoring neoadjuvant chemotherapy. Breast Cancer Res. 2005;7(6):279-285.
  37. Stojadinovic A, Nissan A, Gallimidi Z, et al. Electrical impedance scanning for the early detection of breast cancer in young women: Preliminary results of a multicenter prospective clinical trial. J Clin Oncol. 2005;23(12):2703-2715.
  38. Taulbee P. FDA panel rejects Mirabel's bioimpedance device for breast scanning. FDC Reports: The Gray Sheet. 2006;32(36):8.
  39. Athanasiou A, Vanel D, Fournier L, Balleyguier C. Optical mammography: A new technique for visualizing breast lesions in women presenting non palpable BIRADS 4-5 imaging findings: Preliminary results with radiologic-pathologic correlation. Cancer Imaging. 2007;7:34-40.
  40. Stojadinovic A, Nissan A, Shriver CD, et al. Electrical impedance scanning as a new breast cancer risk stratification tool for young women. J Surg Oncol. 2008;97(2):112-120.
  41. Blackmore KM, Knight JA, Jong R, Lilge L. Assessing breast tissue density by transillumination breast spectroscopy (TIBS): An intermediate indicator of cancer risk. Br J Radiol. 2007;80(955):545-556.
  42. Blackmore KM, Knight JA, Lilge L. Association between transillumination breast spectroscopy and quantitative mammographic features of the breast. Cancer Epidemiol Biomarkers Prev. 2008;17(5):1043-1050.
  43. Ophir J, Céspedes I, Ponnekanti H, et al. Elastography: A quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging. 1991;13:111–134.
  44. Céspedes I, Ophir J, Ponnekanti H, Maklad N. Elastography: Elasticity imaging using ultrasound with application to muscle and breast in vivo. Ultrason Imaging. 1993;15:73-88.
  45. Fowlkes JB, Emelianov SY, Pipe JG, et al. Magnetic-resonance imaging techniques for detection of elasticity variation. Med Phys. 1995;22(11 Pt 1):1771-1778.
  46. Garra BS, Céspedes EI, Ophir J, et al. Elastography of breast lesions: Initial clinical results. Radiology. 1997;202:79-86.
  47. Manduca A, Oliphant TE, Dresner MA, et al. Magnetic resonance elastography: Non-invasive mapping of tissue elasticity. Med Image Anal. 2001;5(4):237-254.
  48. Lorenzen J, Sinkus R, Lorenzen M, et al. Elastography of the breast: Preliminary clinical results. Rofo. 2002;174(7):830-834.
  49. McKnight AL, Kugel JL, Rossman PJ, et al. MR elastography of breast cancer: Preliminary results. AJR. 2002;178(6):1411-1417.
  50. Souchon R, Soualmi L, Bertrand M, et al. Ultrasonic elastography using sector scan imaging and a radial compression. Ultrasonics. 2002;40(1-8):867-871.
  51. Lorenzen J, Sinkus R, Adam G. [Elastography: Quantitative imaging modality of the elastic tissue properties] Rofo. 2003;175(5):623-630.
  52. Xydeas T, Siegmann K, Sinkus R, et al. Magnetic resonance elastography of the breast: Correlation of signal intensity data with viscoelastic properties. Invest Radiol. 2005;40(7):412-420.
  53. Sinkus R, Tanter M, Xydeas T, et al. Viscoelastic shear properties of in vivo breast lesions measured by MR elastography. Magn Reson Imaging. 2005;23(2):159-165.
  54. Giuseppetti GM, Martegani A, Di Cioccio B, Baldassarre S. Elastosonography in the diagnosis of the nodular breast lesions: Preliminary report. Radiol Med. 2005;110(1-2):69-76.
  55. Zhang XF, Liu XM, Bao XF, et al. [Application of real-time tissue elastography in diagnosis of breast cancer]. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2006;35(4):444-447.
  56. Thomas A, Kümmel S, Fritzsche F, et al. Real-time sonoelastography performed in addition to B-mode ultrasound and mammography: Improved differentiation of breast lesions? Acad Radiol. 2006;13(12):1496-1504.
  57. Thomas A, Fischer T, Frey H, et al. Real-time elastography--an advanced method of ultrasound: First results in 108 patients with breast lesions. Ultrasound Obstet Gynecol. 2006;28(3):335-340.
  58. Itoh A, Ueno E, Tohno E, et al. Breast disease: Clinical application of US elastography for diagnosis. Radiology. 2006;239: 341-350.
  59. Garra BS. Imaging and estimation of tissue elasticity by ultrasound. Ultrasound Q. 2007;23(4):255-268.
  60. Tardivon A, El Khoury C, Thibault F, et al. [Elastography of the breast: A prospective study of 122 lesions]. J Radiol. 2007;88(5 Pt 1):657-662.
  61. Liufu V, Hiller J. Breast cancer diagnosis using ultrasound elasticity imaging. Prioritising Summary Update. Canberra, ACT: Adelaide Health Technology Assessment; November 2008.
  62. Cho N, Moon WK, Park JS, et al. Nonpalpable breast masses: Evaluation by US elastography. Korean J Radiol. 2008;9(2):111-118.
  63. U.S. Food and Drug Administration (FDA) 510(k). Regen SonixTouch Ultrasound Scanner. Summary of Safety and Effectiveness. 510(k) No. K083095. Rockville, MD: FDA. October 31, 2008. Available at. http://www.accessdata.fda.gov/cdrh_docs/pdf8/K083095.pdf. Accessed on July 23, 2009.
  64. Fleury Ede F, Fleury JC, Piato S, Roveda D Jr. New elastographic classification of breast lesions during and after compression. Diagn Interv Radiol. 2009;15(2):96-103.
  65. Mundy L, Liufu V, Braunack-Mayer A, et al. New and emerging technologies for breast cancer detection. National Horizon Scanning Emerging Technology Bulletin. Canberra, ACT: Adelaide Health Technology Assessment; February 2009.
  66. Center for Devices and Radiological Health. Summary minutes of the 45th meeting of the obstetrics and gynecology devices panel (draft). Rockville, Maryland: US Food and Drug Administration, Center for Devices and Radiological Health, 1991.
  67. Poellinger A, Martin JC, Ponder SL, et al. Near-infrared laser computed tomography of the breast first clinical experience. Acad Radiol. 2008;15(12):1545-1553.
  68. Tromberg BJ, Pogue BW, Paulsen KD, et al. Assessing the future of diffuse optical imaging technologies for breast cancer management. Med Phys. 2008;35(6):2443-2451.
  69. Köstli KP, Frenz M, Weber HP, et al. Optoacoustic tomography: Time-gated measurement of pressure distributions and image reconstruction. Appl Opt. 2001;40(22):3800-3809.
  70. American Cancer Society [website]. Mammograms and other breast imaging procedures. American Cancer Society, Inc. Revised 09/30/2009. Available at: http://www.cancer.org/docroot/CRI/content/CRI_2_6X_Mammography_
    and_other_Breast_Imaging_Procedures_5.asp
    . Accessed on March 24, 2010.
  71. Imaging Diagnostic Systems, Inc [website]. Computed tomography laser mammography (CTLM). Imaging Diagnostic Systems, Inc., .Fort Lauderdale, FL. Available at: http://www.imds.com/. Accessed on March 24, 2010.
  72. Wang T, Wang K, Yao Q, et al. Prospective study on combination of electrical impedance scanning and ultrasound in estimating risk of development of breast cancer in young women. Cancer Invest. 2010;28(3):295-303.
  73. Moon WK, Choi JW, Cho N, et al. Computer-aided analysis of ultrasound elasticity images for classification of benign and malignant breast masses. AJR Am J Roentgenol. 2010;195(6):1460-1465.
  74. Kumm TR, Szabunio MM. Elastography for the characterization of breast lesions: Initial clinical experience. Cancer Control. 2010;17(3):156-161.
  75. Kyle JR, Kyle MD, Raghavan R, et al. Analysis of light scattering from human breast tissue using a custom dual-optical scanning near-field optical microscope. J Biophotonics. 2011;4(3):193-205.
  76. Yi A, Cho N, Chang JM, et al. Sonoelastography for 1786 non-palpable breast masses: Diagnostic value in the decision to biopsy. Eur Radiol. 2012;22(5):1033-1040.
  77. Landoni V, Francione V, Marzi S, et al. Quantitative analysis of elastography images in the detection of breast cancer. Eur J Radiol. 2012;81(7):1527-1531.
  78. Sadigh G, Carlos RC, Neal CH, Dwamena BA. Accuracy of quantitative ultrasound elastography for differentiation of malignant and benign breast abnormalities: A meta-analysis. Breast Cancer Res Treat. 2012;260(2):428-436.
  79. Gonzalez J, Decerce J, Erickson SJ, et al. Hand-held optical imager (Gen-2): Improved instrumentation and target detectability. J Biomed Opt. 2012;17(8):081402-1.
  80. Vreugdenburg TD, Willis CD, Mundy L, Hiller JE. A systematic review of elastography, electrical impedance scanning, and digital infrared thermography for breast cancer screening and diagnosis. Breast Cancer Res Treat. 2013;137(3):665-676.


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