Total Body Photography, Dermoscopy and Other Selected Noninvasive Dermatologic Tests

Number: 0188

Policy

1. Aetna considers total body photography (TBP) and dermoscopy (also known as total body imaging, digital epiluminescence microscopy (DELM), epiluminescence microscopy [ELM], incidence light microscopy, skin videomicroscopy, melanomography, in-vivo cutaneous surface microscopy, dermatoscopy, and magnified oil immersion diascopy) (e.g., MoleSafe) medically necessary when used for evaluation of members with a history or close family history of any of the following conditions:   

   1. Atypical nevi; or
   2. Dysplastic nevi; or
   3. Melanoma; or
   4. Non-melanoma skin cancers

   Repeat studies are not typically required more frequently than every 24 months. 

   Aetna considers TBP and dermoscopy experimental and investigational for all other indications because their effectiveness for indications other than the ones listed above has not been established.

2. Aetna considers computerized TBP systems (e.g., MelaFind, MoleMapCD, MoleMate) experimental and investigational because they have not been shown to provide better health outcomes than conventional TBP.

3. Aetna considers the following approaches (not an all-inclusive list) experimental and investigational for evaluating dysplastic and atypical nevi for early detection of malignant cutaneous melanomas because their clinical value for this indication has not been established.

   • Confocal scanning laser microscopy
   • Electrical impedance devices
   • High-resolution (high-frequency) ultrasonography
   • Multi-photon laser scanning microscopy (also known as multi-photon fluorescence microscopy or multi-photon excitation microscopy)
   • Multi-spectral image analysis
   • Non-invasive gene expression "patch biopsy" (e.g., DermTech Pigmented Lesion Assay (PLA))
   • Optical coherence tomography
   • Reflectance confocal microscopy (RCM)
   • Spectroscopy (electrical impedance and optical, e.g., Dermasensor)
   • Teledermatology / teledermoscopy
   • Visual image analysis.

Background

Total body photography (TBP) and dermoscopy (also known as total body imaging, digital epiluminescence microscopy (DELM), epiluminescence microscopy [ELM], incidence light microscopy, skin videomicroscopy, melanomography, in-vivo cutaneous surface microscopy, dermatoscopy, and magnified oil immersion diascopy) are established techniques for detecting and monitoring dysplastic and atypical nevi for early detection of malignant cutaneous melanomas. 

A skin lesion is a nonspecific term that refers to any change in the skin surface. Skin lesions may have color (pigment), be raised, flat, large, small, fluid filled or exhibit other characteristics. A lesion may be benign, malignant or premalignant.

Skin cancers are often referred to as being nonmelanoma or melanoma, with nonmelanoma skin cancers behaving less aggressively than melanoma. The two most common types of nonmelanoma skin cancer arise from cells in layers of the epidermis (skin) for which they are named. Basal cell skin cancer originates in the basal (lowest) layer of the epidermis, while squamous cell skin cancer starts in the squamous (outer) layer of the epidermis. Most skin cancers occur on skin that is regularly exposed to sunlight or other ultraviolet radiation. Melanoma is another type of skin cancer that is less common, but more harmful.

The fact that dysplastic and atypical nevi may appear as potential precursors of cutaneous malignant melanoma (CMM) has made possible early identification of individuals who are at increased risk for developing CMM.  Moreover, there is ample evidence that early resection of malignant melanoma is associated with an excellent prognosis.  Thus, it is important that individuals with dysplastic or atypical nevi receive regular cutaneous examination to identify new and changing nevi. 

Melanoma originates in the melanocytes and usually presents as a brown or black lesion, but can appear as pink, tan, white or nonpigmented (no color).Melanoma can appear anywhere on the body and may be difficult to detect in early phases. Surgical removal of the lesion is the standard treatment for melanoma.

Surveillance technologies have been developed in an attempt to find skin cancer, particularly melanoma, early and to assist with identifying malignant skin lesions without using a biopsy or excising (removing) the lesion. However, more than 90% of melanomas that arise in the skin can be recognized with the naked eye. Biopsy is necessary when there is a sufficient index of suspicion. Histopathologic examination remains the gold standard for skin cancer diagnosis.

Mole mapping/Total body and single lesion photography uses digital cameras for recording and storing images which can be compared over time to determine if a lesion has changed. If video images are recorded, this may be referred to as video-dermoscopy. Total body photography is helpful for patients with numerous nevi, to identify changes in these lesions during regular examinations.

Dermoscopy is a technique that may be utilized to see patterns and structures in lesions that are not perceptible to the naked eye, and is also known as dermatoscopy, digital epiluminescence microscopy (DELM), in vitro cutaneous surface microscopy, magnified oil immersion diascopy, mole mapping and melanomography. A dermoscope (handheld magnification tool) is used for examination of the skin lesions, which allows 10x or higher magnification by using high intensity light. Oil may be applied to the surface of the lesion to make the skin more transparent, but may not be necessary if a polarized light source and lens are used. DermLite is one example of a US Food and Drug Administration (FDA) approved dermoscope. Dermoscopes may be combined with cameras, software and computerized systems that save and store images. MicroDERM is one example of a digital dermoscope and software system.

A dermoscope (e.g., MoleMax II™) is a specialized microscope that is used for in vivo examination of pigmented skin lesions, in order to distinguish melanocytic from non-melanocytic pigmented lesions and determine whether melanocytic pigmented lesions are likely to be malignant.  Even though most malignant melanocytic lesions can be identified on the basis of unaided visual inspection alone, there are many lesions that are not readily distinguished by examination with the naked eye.

The dermoscope can also be used to visualize the subsurface layers of the skin.  With the addition of the oil immersion technique, the epidermis becomes translucent, permitting macroscopic evaluation of the dermo-epidermal junction.  Most studies have shown that this method improves diagnostic accuracy of pigmented skin lesions by 20 % to 30 % with respect to simple clinical observation, especially by an expert dermatologist.

Since its introduction, dermoscopy has undergone extensive improvements; the instruments have become more readily available; and the diagnostic indications, benefits, and limitations have been better delineated.  Dermoscopy has developed into a powerful tool to discriminate between melanocytic and non-melanocytic pigmented skin lesions, and to distinguish benign from malignant melanocytic lesions in order to avoid inopportune surgical treatments for low risk lesions.  Although dermoscopy does not show 100 % sensitivity in diagnosing CMM, it is more accurate than un-aided visual inspection in detecting thin CMM.  Features of pigmented lesions identified by dermoscopy should be integrated with data from the history and physical examination.

The recent advent of digital imaging systems for acquiring and archiving total body skin images has resulted in greater dissemination of this technique.  Although computer-based systems supposedly will provide sophisticated functionalities for automated feature extraction and lesion assessment for quantitative analysis, there is a need to better standardize computerized TBP systems if they are going to be used more extensively.

There is insufficient evidence that computerized TBP systems such as MoleMapCD provide better health outcomes than conventional TBP.  In this regard, Schindewolf et al (1994) ascertained if conventional color slides or directly digitized images should be used for a reliable recognition of malignant melanoma.  The authors concluded that both image acquisition techniques allow a reliable detection of malignant melanoma and both are appropriate as input for an image analysis system regarding its efficiency as a diagnostic tool.  Furthermore, Brown (2002) examined the various diagnostic techniques for melanoma.  A total of 6 general categories dealing with diagnostic techniques for melanoma were identified:

1. naked-eye clinical examination alone,
2. clinical examination with the aid of TBP,
3. epiluminescence microscopy (ELM),
4. digital ELM,
5. computer-assisted techniques, and
6. teledermatology. 

Because of the research citing the poor diagnostic accuracy (DA) of non-dermatologists, increased DA with dermatologists experienced in ELM techniques, and the importance of early melanoma diagnosis, the recommendation is to refer patients with suspicious pigmented skin lesions to experienced dermatologists, preferably those who use ELM or digital ELM.

In a review on skin imaging, Rallan and Harland (2004) stated that mole scanners are increasingly available on a commercial basis even though computer diagnosis of pigmented lesions is currently no better than diagnosis by human experts, and other imaging techniques, such as high-resolution ultrasonography, spectroscopy and optical coherence tomography, may yet find a role in diagnosis and disease monitoring.

Starritt et al (2005) stated that the value of targeted high-resolution ultrasound (US) examination in detecting sentinel lymph node (SLN) metastases in patients with newly diagnosed primary cutaneous melanomas has not yet been fully evaluated.  These investigators examined the threshold size of metastatic melanoma deposits in SLNs that are able to be detected by targeted US examination before initial melanoma surgery (n = 304).  Metastatic disease was present in SLNs from 33 node fields in 31 patients.  The US results in 7 of these cases were suggestive of metastatic disease; 26 node fields contained positive nodes not detected by US.  Undetected deposits had diameters that are less than 4.5 mm.  These researchers concluded that the findings of this study suggest that a targeted US examination of SLNs can detect metastatic melanoma deposits down to approximately 4.5 mm in diameter.  They further noted that, however, most metastatic melanoma deposits in SLNs are considerably smaller than this at the time of initial staging, thus targeted high-resolution ultrasound can not be considered cost-effective in this setting.

Confocal laser scanning microscopy is similar to dermoscopy, however uses a low-power laser beam projected through a lens on a specific point on the skin and then detects the light reflected from the focal point through a filter. The reflected light is transformed into an electrical signal, which is recorded as an image by a computer. This technology purports to be capable of producing images of skin lesions at various depths below the skin’s surface. One example of such technology is the VivaScope.

Gerger et al (2006) noted that in vivo CLSM examination appeared to be a promising method for the non-invasive assessment of melanoma and non-melanoma skin tumors.  This is in agreement with the observation of Menzies (2006), who stated that the use of automated instruments for the diagnosis of cutaneous melanoma is still in an experimental phase, and its utility is dependent on the evidence that such instruments give a clinically useful expert second opinion.  Currently, other non-invasive diagnostic techniques such as in vivo CLSM are reserved for clinical research settings.

Gerger and colleagues (2009) stated that In vivo confocal microscopy represents a novel imaging tool that allows the non-invasive examination of skin cancer morphology in real time at a "quasi-histopathological" resolution viewing micro-anatomical structures and individual cells.  Numerous morphological confocal features of melanocytic skin tumors have been described and histopathological correlates of confocal structures have been previously elucidated.  Recently, several studies have evaluated the diagnostic accuracy of in vivo confocal microscopy for melanocytic skin tumors, investigating approximately 50,000 tumor images.  Remarkably, sensitivity superior to the diagnostic accuracy achieved with dermoscopy could be reached by this imaging modality.  These studies represented a significant contribution to the body of research necessary for the evaluation and implementation of in vivo confocal microscopy in clinical practice to avoid many currently unnecessary biopsies.  In vivo confocal microscopy probably augurs a sea change in the way melanocytic skin tumors are evaluated in the future and will ultimately move the art of histological diagnosis closer to the bedside.

Sanki et al (2009) re-assessed traditional ultrasound descriptors of SLN metastases to:

1. determine the minimum cross-sectional area (CSA) of an SLN metastasis detectable by US, and
2. establish whether targeted, high-resolution US of SLNs identified by lymphoscintigraphy before initial melanoma surgery can be used as a substitute for excisional SLN biopsy. 

High-resolution US was performed on SLNs identified in 871 lymph node fields in 716 patients; SLN biopsy was performed within 24 hours of lymphoscintigraphy and US examination.  The CSA of each SLN metastatic deposit was determined sonographically and histologically.  The sensitivity of targeted US in the detection of positive SLNs was 24.3 % (95 % confidence interval [CI]: 19.5 % to 28.7 %), and the specificity was 96.8 % (95 % CI: 95.9 % to 97.7 %).  The sensitivity was highest for neck SLNs (45.8 %) and improved with greater Breslow thickness.  The median histologic CSA of the SLN metastatic deposits was 0.39 mm(2) (12.75 mm(2) for US true-positive results and 0.22 mm(2) for US false-negative results).  True-positive, US-detected SLNs had significantly greater CSAs (t-test p < 0.001) than undetected SLN metastases and were more likely to be spherical in cross-section.  More than 2 sonographic descriptors of SLN metastases or rounding of the node alone were factors highly suggestive of a melanoma deposit.  The authors concluded that high-resolution US is not an appropriate substitute for SLN biopsy, but it is of value in pre-operative SLN assessment and post-operative monitoring.  These findings are in agreement with those of Kunte et al (2009) who reported that high resolution B-mode US can not replace SLN biopsy, especially in the detection of micro-metastases, but it remains the most important method to assess the lymph node status for macrometastases pre-surgically.

Glud et al (2009) noted that dermoscopy is considered to be the gold standard for the clinical assessment of pigmented skin lesions.  In expert hands, this instrument improves both sensitivity and specificity for the diagnosis of melanoma, however, the outcome is highly dependent on the skills and experience of the examiner.  Spectrophotometric intra-cutaneous analysis (SIAscopy) is a new, commercially available method of analyzing pigmented skin lesions non-invasively.  The diagnosis is based on objective features such as the presence of dermal pigment, vascularity of the lesion, and the integrity of collagen.  These researchers examined the usefulness of SIAscopy for the clinical diagnosis of malignant melanoma in a prospective, unbiased manner.  They enrolled 65 patients with 83 lesions, where the diagnosis of melanoma could not be ruled out on the basis of the clinical evaluation by a non-dermatologist.  All lesions were investigated by dermoscopy and SIAscopy and subsequently excised.  Histopathologically, 12 lesions were diagnosed as malignant melanoma.  Both dermoscopy and SIAscopy over-estimated the proportion of possible malignant lesions (n = 24 and n = 41, respectively) and had sensitivities of 92 % and 100 %, respectively.  The specificity of dermoscopy in this study was 81 % against 59 % for SIAscopy.  These findings showed that dermoscopy remains the best diagnostic tool for the pre-operative diagnosis of pigmented skin lesions.

An Agency for Healthcare Research and Quality's Technical Brief on "Noninvasive diagnostic techniques for the detection of skin cancers" (Parsons et al, 2011) stated that multi-photon laser scanning microscopy (also known as multi-photon fluorescence microscopy or multi-photon excitation microscopy) uses more than 1 photon excitation to illuminate endogenous fluorophores in skin tissues, which emits a fluorescence signal to be captured by a detector.  Similar to CSLM, multi-photon laser scanning microscopy uses laser beam and allows imaging of tissues beyond the superficial epidermis.  Unlike CSLM, this technique does not use a confocal pinhole filter.  Evidence of the current application of this modality is sparse.  Systematic literature search identified 3 narrative reviews and 2 diagnostic studies of multi-photon microscopy or tomography.  These investigators identified 2 registered cross-sectional studies that assess the use of this technology for skin lesion evaluation.  Both studies are based in Taiwan and are recruiting participants.  The only commercially available device for multi-photon tomography is DermaInspect, manufactured by JenLab in Germany.  The authors could not determine the FDA clearance status for this device on the FDA CDRH database; and listed multi-photon laser scanning microscopy as one of the investigational devices for the detection of skin cancers.

Glud et al (2009) stated that spectrophotometric intra-cutaneous analysis (SIAscopy) is a new, commercially available method of analyzing pigmented skin lesions non-invasively.  The diagnosis is based on objective features such as the presence of dermal pigment, vascularity of the lesion, and the integrity of collagen.  The objective of this study was to examine the usefulness of SIAscopy for the clinical diagnosis of malignant melanoma in a prospective, unbiased manner.  These investigators enrolled 65 patients with 83 lesions, where the diagnosis of melanoma could not be ruled out on the basis of the clinical evaluation by a non-dermatologist.  All lesions were investigated by dermoscopy and SIAscopy and subsequently excised.  Histopathologically, 12 lesions were diagnosed as malignant melanoma.  Both dermoscopy and SIAscopy over-estimated the proportion of possible malignant lesions (n = 24 and 41, respectively) and had sensitivities of 92 and 100 %, respectively.  The specificity of dermoscopy in this study was 81 % against 59 % for SIAscopy.  These findings showed that dermoscopy remains the best diagnostic tool for the pre-operative diagnosis of pigmented skin lesions.  However, as the SIAscope in addition to the SIAgraph images produces dermoscopic images, it holds the advantages in training and archiving.

Ascierto et al (2010) stated that SPT could represent a promising technique for the diagnosis of cutaneous melanoma (CM) at earlier stages of the disease.  These investigators evaluated the role of SPT in CM early detection.  During a health campaign for malignant melanoma at National Cancer Institute of Naples, these researchers identified a subset of 54 lesions to be addressed to surgical excision and histological examination.  Before surgery, all patients were investigated by clinical and ELM screenings; selected lesions underwent SPT analysis.  For SPT, these investigators used a video SPT imaging system (Spectroshade MHT S.p.A., Verona, Italy).  Among the 54 patients harboring cutaneous pigmented lesions, these researchers performed comparison between results from the SPT screening and the histological diagnoses as well as evaluation of both sensitivity and specificity in detecting CM using either SPT or conventional approaches.  For all pigmented lesions, agreement between histology and SPT classification was 57.4 %.  The sensitivity and specificity of SPT in detecting melanoma were 66.6 % and 76.2 %, respectively.  The authors concluded that although SPT is still considered as a valuable diagnostic tool for CM, its low accuracy, sensitivity, and specificity represent the main hamper for the introduction of such a methodology in clinical practice.  Dermoscopy remains the best diagnostic tool for the pre-operative diagnosis of pigmented skin lesions.

Smith and Macneil (2011) discussed recent developments in the non-invasive imaging of skin, in particular at how such imaging may be used at present or in the future to detect CM.  A Medline search was performed for articles using imaging techniques to evaluate CM, including melanoma metastasis.  A total of 9 different techniques were found: dermoscopy, confocal laser scanning microscopy (including multi-photon microscopy), optical coherence tomography, high-frequency ultrasound, positron emission tomography, magnetic resonance imaging, and Fourier, Raman, and photo-acoustic spectroscopies.  The authors concluded that despite the variety of techniques available for detecting melanoma, there remains a critical need for a high-resolution technique to answer the question of whether tumors have invaded through the basement membrane.

In a prospective, multi-center, blinded study, Monheit et al (2011) examined the safety and effectiveness of MelaFind, a non-invasive and objective computer-vision system designed to aid in detection of early pigmented cutaneous melanoma.  The diagnostic performance of MelaFind and of study clinicians was evaluated using the histologic reference standard.  Standard images and patient information for a subset of 50 randomly selected lesions (25 melanomas) were used in a reader study of 39 independent dermatologists to estimate clinicians' biopsy sensitivity to melanoma.  A total of 1,383 patients with 1,831 lesions enrolled from January 2007 to July 2008; 1,632 lesions (including 127 melanomas – 45 % in situ-with median Breslow thickness of invasive lesions, 0.36 mm) were eligible and evaluable for the study end points.  Main outcome measures included sensitivity of MelaFind; specificities and biopsy ratios for MelaFind and the study investigators; and biopsy sensitivities of independent dermatologists in the reader study.  The measured sensitivity of MelaFind was 98.4 % (125 of 127 melanomas) with a 95 % lower confidence bound at 95.6 % and a biopsy ratio of 10.8:1; the average biopsy sensitivity of dermatologists was 78 % in the reader study.  Including borderline lesions (high-grade dysplastic nevi, atypical melanocytic proliferations, or hyperplasias), MelaFind's sensitivity was 98.3 % (172 of 175), with a biopsy ratio of 7.6:1.  On lesions biopsied mostly to rule out melanoma, MelaFind's average specificity (9.9 %) was superior to that of clinicians (3.7 %) (p = 0.02).  The authors concluded that MelaFind is a safe and effective tool to assist in the evaluation of pigmented skin lesions.  However, it is unclear if an instrument with such a low specificity is clinically useful.

Mohr et al (2013) stated that previous studies have shown statistically significant differences in electrical impedance between various cutaneous lesions.  Electrical impedance spectroscopy (EIS) may therefore be able to aid clinicians in differentiating between benign and malignant skin lesions.  These researchers developed a classification algorithm to distinguish between melanoma and benign lesions of the skin with a sensitivity of at least 98 % and a specificity of approximately 20 % higher than the diagnostic accuracy of dermatologists.  A total of 1,300 lesions were collected in a multi-center, prospective, non-randomized clinical trial from 19 centers around Europe.  All lesions were excised and subsequently evaluated independently by a panel of 3 expert dermatopathologists.  From the data 2 classification algorithms were developed and verified.  For the first classification algorithm, approximately 40 % of the data were used for calibration and 60 % for testing.  The observed sensitivity for melanoma was 98.1 % (101/103), non-melanoma skin cancer 100 % (25/25) and dysplastic nevus with severe atypia 84.2 % (32/38).  The overall observed specificity was 23.6 % (66/280).  For the second classification algorithm, approximately 55 % of the data were used for calibration.  The observed sensitivity for melanoma was 99.4 % (161/162), for non-melanoma skin cancer was 98.0 % (49/50) and dysplastic nevus with severe atypia was 93.8 % (60/64).  The overall observed specificity was 24.5 % (116/474).  The authors concluded that EIS has the potential to be an adjunct diagnostic tool to help clinicians differentiate between benign and malignant (melanocytic and non-melanocytic) skin lesions.  They stated that further studies are needed to confirm the validity of the automatic assessment algorithm.

MoleSafe

According to its website, MoleSafe is a comprehensive skin documentation system designed to expose layers of skin lesions not typically viewed during a regular examination by dermatologists.  The MoleSafe system produces high-resolution diagnostic images and creates a profile for a person’s skin that is monitored for any changes in lesions.  The MoleSafe process involves 6 important steps:

• Meeting with a melanographer to discuss medical history and address skin concerns
• Total body photography – A series of 25 pictures is taken of 96 %of the body’s surface
• Total body dermoscopy – A visual exam is performed and any abnormal lesion is examined with a dermatoscope
• Digital melanogram – Images from the exam are compiled into a digital record of the skin, along with other information, including lesion coding and history
• Dermoscopist report is created – Dermoscopist report of suspicious legions included with recommendations for treatment and ongoing surveillance
• Patient education – Educating patients on skin cancer risk factors and tips for protecting skin against UV radiation

Non-Melanocytic Skin Cancer

Fargnoli et al (2012) noted that over the past 20 years, dermoscopy has remarkably enhanced the diagnostic accuracy of pigmented skin lesions and, more recently, of non-pigmented skin disorders, including skin cancers, inflammatory and infectious diseases.  With respect to non-melanoma skin cancers (NMSC), dermoscopy is an effective diagnostic tool for the clinical assessment of BCC, Bowen's disease, actinic keratosis (AK) and SCC.  Besides its relevance for diagnostic purposes, further applications of dermoscopy in the management of NMSC have been suggested in the pre-operative evaluation, in monitoring the outcome of topical, light-based or laser treatments and in the post-treatment follow-up.

Lallas et al (2013) noted that dermoscopy has become an integrative part of the clinical examination of skin tumors. This is because it significantly improves the early diagnosis of melanoma and NMSC including BCC and keratinocyte skin cancer compared with the unaided eye.  Besides its value in the non-invasive diagnosis of skin cancer, dermoscopy has also gained increased interest in the management of NMSC.  Dermoscopy has been used in the pre-operative evaluation of tumor margins, monitoring of the outcomes of topical treatments and post-treatment follow-up.

Babino and associates (2015) stated that dermoscopy is a non-invasive tool that allows the identification of specific morphological features in different skin tumors, improving significantly the early diagnosis of melanoma and NMSC.  This tool has also gained increased interest in the management of NMSC therapy and in the post-treatment follow-up.

Deinlein  and colleagues (2016) noted that dermatoscopy is an integral part of every clinical skin examination, as it markedly enhances the early detection of melanocytic and NMSC compared to naked-eye inspection.  Besides its diagnostic use, this non-invasive method is increasingly important in the selection of as well as the response assessment to various therapies used for NMSC, including BCC, AK, SCC, and also rare tumors such as Merkel cell carcinoma, angiosarcoma, or dermato-fibrosarcoma protuberans.  The authors stated that dermatoscopy is a valid tool for the pre-operative assessment of tumor margins in BCC, but also for follow-up of AK after topical treatment. 

Furthermore, the Canadian Cancer Society (2016) lists dermoscopy as one of the methods used for diagnosing non-melanoma skin cancer.

Non-Invasive Gene Expression "Patch Biopsy" (e.g., DermTech Pigmented Lesion Assay (PLA))

According to DermTech, the Pigmented Lesion Assay (PLA; DermTech) entails non-invasive gene expression tests to aid the clinical diagnosis of skin cancer and other skin conditions.  It was developed to provide physicians with a non-invasive option for the biopsy of clinically atypical pigmented lesions using an adhesive patch rather than a scalpel.  The PLA is used for the detection of melanoma in atypical skin lesions or moles and utilizes a sample collected with the Adhesive Patch Skin Biopsy Kit.  It provides ribonucleic acid (RNA) gene expression score for 2 genes (CMIP and LINC00518).  The PLA can be used to reduce unnecessary surgical biopsy procedures by ruling out false positives based on visual assessment prior to performing a surgical removal.  It may also be used to provide immediate information on lesions that require 6 to 12 months follow-up for change.  This non-invasive biopsy approach has additional utility in patient populations that are anti-coagulated, at increased risk for infection and scaring, or at risk for wound complications, and for lesions in cosmetically sensitive areas.

Gerami et al (2014) developed a non-invasive genomic method using messenger RNA (mRNA) to classify pigmented skin lesions as either benign or malignant.  An adhesive patch method was used to obtain cells from the surface of melanocytic lesions; mRNA was extracted and a genomic signature was formulated in a training set of benign and malignant melanocytic neoplasms and subsequently tested in a validation set.  A 2-gene signature assessing the expression levels of CMIP and LINC00518 was able to differentiate melanomas from nevi in an independent validation set of 42 melanomas and 22 nevi with a sensitivity of 97.6 % and specificity of 72.7 %.  The authors concluded that these findings suggested that mRNA molecular signatures can serve as a highly useful non-invasive method of differentiating melanoma from nevi and decrease the number of unnecessary biopsies.  Moreover, they stated that larger and more diverse sets of melanomas and nevi are needed for additional validation of the molecular expression profiling in various subsets of melanocytic neoplasms.

Clarke and associates (2015) identified a gene expression signature that reliably differentiated benign and malignant melanocytic lesions and evaluated its potential clinical applicability.  These investigators described the development of a gene expression signature and its clinical validation using multiple independent cohorts of melanocytic lesions representing a broad spectrum of histopathologic subtypes.  Using quantitative reverse-transcription polymerase chain reaction (RT-PCR) on a selected set of 23 differentially expressed genes, and by applying a threshold value and weighting algorithm, these researchers developed a gene expression signature that produced a score that differentiated benign nevi from malignant melanomas.  The gene expression signature classified melanocytic lesions as benign or malignant with a sensitivity of 89 % and a specificity of 93 % in a training cohort of 464 samples.  The signature was validated in an independent clinical cohort of 437 samples, with a sensitivity of 90 % and specificity of 91 %.  The authors concluded that the performance, objectivity, reliability and minimal tissue requirements of this test suggested that it could have clinical application as an adjunct to histopathology in the diagnosis of melanocytic neoplasms.

Yao et al (2016) previously reported clinical performance of a novel non-invasive and quantitative PCR (qPCR)-based molecular diagnostic assay (the PLA) that differentiates primary cutaneous melanoma from benign pigmented skin lesions through 2 target gene signatures, LINC00518 (LINC) and preferentially expressed antigen in melanoma (PRAME).  This study focused on analytical characterization of this PLA, including qPCR specificity and sensitivity, optimization of RNA input in qPCR to achieve a desired diagnostic sensitivity and specificity, and analytical performance (repeatability and reproducibility) of this 2-gene PLA.  All target qPCRs demonstrated a good specificity (100 %) and sensitivity (with a limit of detection of 1-2 copies), which allows reliable detection of gene expression changes of LINC and PRAME between melanomas and non-melanomas.  Through normalizing RNA input in qPCR, these researchers converted the traditional gene expression analyses to a binomial detection of gene transcripts (i.e., detected or not detected).  By combining the binomial qPCR results of the 2 genes, an improved diagnostic sensitivity (raised from 52 % to  65 % to 71 % at 1 pg of total RNA input, and to 91 % at 3 pg of total RNA input) was achieved.  The authors concluded that this 2-gene PLA demonstrated a high repeatability and reproducibility (coefficient of variation less than 3 %) and all required analytical performance characteristics for the commercial processing of clinical samples.

Gerami et al (2017) noted that clinical and histopathologic assessment of pigmented skin lesions remains challenging even for experts.  Differentiated and accurate non-invasive diagnostic modalities are highly desirable.  These researchers sought to provide clinicians with such a tool.  A 2-gene classification method based on LINC00518 and preferentially expressed antigen in melanoma (PRAME) gene expression was evaluated and validated in 555 pigmented lesions (157 training and 398 validation samples) obtained non-invasively via adhesive patch biopsy.  Results were compared with standard histopathologic assessment in lesions with a consensus diagnosis among 3 experienced dermatopathologists.  In 398 validation samples (87 melanomas and 311 non-melanomas), LINC00518 and/or PRAME detection appropriately differentiated melanoma from non-melanoma samples with a sensitivity of 91 % and a specificity of 69 %.  These investigators established LINC00518 and PRAME in both adhesive patch melanoma samples and underlying formalin fixed paraffin embedded (FFPE) samples of surgically excised primary melanomas and in melanoma lymph node metastases.  The authors concluded that this non-invasive 2-gene pigmented lesion assay classified pigmented lesions into melanoma and non-melanoma groups and may serve as a tool to help with diagnostic challenges that may be inherently linked to the visual image and pattern recognition approach.  The main drawback is that this technology cannot be used on mucous membranes, palms of hands, and soles of feet.

An UpToDate review on "Clinical features and diagnosis of cutaneous melanoma" (Swetter and Geller, 2017) does not mention non-invasive gene expression test/patch biopsy as a management tool.

Yao and associates (2017) noted that a number of diagnoses in clinical dermatology are currently histopathologically confirmed and this image recognition-based confirmation generally requires surgical biopsies.  The increasing ability of molecular pathology to corroborate or correct a clinical diagnosis based on objective gene expression, mutation analysis, or molecular microbiome data is on the horizon and would be further supported by a tool or procedure to collect samples non-invasively.  This study characterized such a tool in form of a "bladeless" adhesive patch-based skin biopsy device.  The performance of this device was evaluated through a variety of complementary technologies including assessment of sample biomass, electron microscopy demonstrating the harvesting of layers of epidermal tissue, and isolation of RNA and DNA from epidermal skin samples.  Samples were obtained by application of adhesive patches to the anatomical area of interest.  Biomass assessment demonstrated collection of approximately 0.3 mg of skin tissue per adhesive patch and electron microscopy confirmed the nature of the harvested epidermal skin tissue.  The obtained tissue samples were stored in a stable fashion on adhesive patches over a wide range of temperatures (-80 degree C to +60 degree C) and for extended periods of time (7 days or more).  Total human RNA, human genomic DNA and microbiome DNA yields were 23.35 + 15.75 ng, 27.72 + 20.71 ng and 576.2 + 376.8 pg, respectively, in skin samples obtained from combining 4 full patches collected non-invasively from the forehead of healthy volunteers.  The authors concluded that the adhesive patch skin sampling procedure was well-tolerated and provided robust means to obtain skin tissue, RNA, DNA, and microbiome samples without involving surgical biopsies.  The non-invasively obtained skin samples can be shipped cost effectively at ambient temperature by mail or standard courier service, and were suitable for a variety of molecular analyses of the skin microbiome as well as of keratinocytes, T cells, dendritic cells, melanocytes, and other skin cells involved in the pathology of various skin conditions and conditions where the skin can serve as a surrogate target organ.

In a secure web-based, multiple-reader-multiple-case study, Ferris and colleagues (2017) determined the utility of the PLA for LINC00518/PRAME expression in decisions to biopsy a series of pigmented skin lesions.  Board-certified dermatologists each evaluated 60 clinical and dermoscopic images of clinically atypical pigmented lesions, first without and then with PLA gene expression information and were asked whether the lesions should be biopsied.  Data were collected from March 24, 2014, through November 13, 2015.  Participants were given a report for each lesion, which included the results of an assay for expression of LINC00518/PRAME and a PLA score with data on the predictive values of the information provided.  Main outcomes measures were biopsy sensitivity and specificity with versus without PLA data.  A total of 45 dermatologists (29 men and 16 women) performed the evaluation.  After incorporating the PLA into their decision as to whether to biopsy a pigmented lesion suggestive of melanoma, dermatologists improved their mean biopsy sensitivity from 95.0 % to 98.6 % (p = 0.01); specificity increased from 32.1 % to 56.9 % (p < 0.001) with PLA data.  The authors concluded that the non-invasive PLA enabled dermatologists to significantly improve biopsy specificity while maintaining or improving sensitivity.  They stated that this finding may increase the number of early melanomas biopsied and reduce the number of benign lesions biopsied, thereby improving patient outcomes and reducing health care costs.

Ferris et al (2018) stated that approximately 3 million surgical pigmented skin lesion biopsies are carried out every year in the U.S. alone to diagnose fewer than 200,000 new cases of invasive melanoma and melanoma in-situ using the current standard of care that includes visual assessment and histopathology.  A recently described non-invasive adhesive patch-based gene expression rule-out test [pigmented lesion assay (PLA)] may be helpful in identifying high-risk pigmented skin lesions to aid with surgical biopsy decisions.  These researchers determined the real-world clinical performance of PLA use and examined how the PLA changes physician behavior in an observational cohort analysis of 381 patients assessed with the PLA.  All (100 %) of 51 PLA(+) test results were clinically managed with surgical biopsy.  Of these, 19 (37 %) were melanomas, corresponding to a number needed to biopsy of 2.7 and a biopsy ratio of 1.7.  All melanomas were histopathologically classified as melanoma in-situ or stage 1.  Nearly all (99 %) of 330 PLA(-) test results were clinically managed with surveillance.  None of the 3 follow-up biopsies performed in the following 3 to 6 months, were diagnosed as melanoma histopathologically.  The estimated sensitivity and specificity of the PLA from these data sets are 95 % and 91 %, respectively.  Overall, 93 % of PLA results positive for both LINC00518 and PRAME were diagnosed histopathologically as melanoma.  PRAME-only and LINC00518-only lesions were melanomas histopathologically in 50 % and 7 %, respectively.  The authors concluded that the PLA changed clinical management of pigmented lesions and demonstrated high clinical performance.  The likelihood of positive histopathologic diagnosis of melanoma was higher in PLA results that were positive for both LINC00518 and PRAME. 

The authors stated that an inherent key limitation of this study was the assumption that PLA(−) lesions not biopsied at 3 to 6 months were true negatives.  In underlying validation studies, all lesions examined by PLA were also surgically biopsied so that consensus histopathology diagnoses could be established and correlated with PLA results.  In this study, the objective was to examine if clinicians follow the biopsy guidance the PLA offers.  Other than subjecting all PLA(−) patients to the very surgical biopsy this technology helps minimize, there is no other good way to estimate true negatives.  Studies using dermoscopy to follow suspicious melanoma lesions indicated that melanomas will undergo observable changes within 3 to 6 months, while changes in early melanoma in-situ may be more difficult to evaluate.  A study to examine findings with up to 2 years of follow-up has been initiated recently.  Nonetheless, these researchers  could not rule out that some PLA(−) lesions may not have been adequately re-assessed in the follow-up period and these investigators certainly recommended erring on the side of caution and surgically biopsying a lesion in question if additional risk factors, further clinical suspicion, or patient concern mandate such a step.  These researchers did not recommend the use of the PLA if a frank melanoma is suspected.  Another perceived limitation was that the validation study by Gerami et al (2017) and this real-world utility study reported different specificity numbers (69 % versus 91 %).  Potential reasons for the noted difference included study objectives and design, physician environment and bias (validation studies were performed by academic investigators who directed pigmented lesion clinics and routinely used tools such as total body photography and dermoscopy that may not be used routinely by all dermatologists in clinical practice), required assumptions, and possibly most importantly a lower prevalence of melanoma in biopsied real-world lesions (5 %, 19 of 381 cases) in line with reports from other comparable studies and settings.  It should be noted that L.K.F., P.G., G.P., and D.M.S. are scientific advisors to DermTech.

Ferris et al (2019a) noted that tools that help reduce the number of surgical biopsies performed on benign lesions have the potential to improve patient care.  The PLA is a non-invasive tool validated against histopathology that helps rule out melanoma and the need for surgical biopsies of atypical pigmented skin lesions.  Genetic information is collected using adhesive patches and the expression of 2 genes, LINC00518 and PRAME, is measured.  Using genetic material collected non-invasively and to further validate the PLA, somatic hotspot mutations in genes known to be drivers of early melanoma development (BRAF other than V600E, NRAS and the TERT promoter) can also be identified.  The frequency of these hotspot mutations in samples of early melanoma was 77 % and higher than the 14 % found in non-melanoma samples (p < 0.0001).  TERT promoter mutations were the most prevalent mutation type in PLA positive melanomas; 82 % of PLA negative lesions had no mutations and 97 % of histopathologically confirmed melanomas were PLA and/or mutation positive (cohort 1, n = 103).  Mutation frequencies were similar in prospectively collected real-world PLA samples (cohort 2, n = 519), in which 88 % of PLA negative samples had no mutations.  The authors concluded that combining gene expression and mutation analyses enhanced the ability to non-invasively detect early cutaneous melanoma.  Moreover, these researchers stated that not all TERT promoter mutations, the mutation type observed in 79 % of melanomas confirmed by histopathologic consensus diagnosis, may be created equal.  Borah et al (2015) found TERT promoter mutations at position –124 in most of their urothelial cancer cell lines studies, and this mutation may confer tumor aggressiveness and facilitate the establishment of cell lines.  Although further studies are needed to examine the roles that different TERT promoter mutations may play in the progression of melanocytic lesions, it is of interest to note that –124 mutations were the mutation type most often observed in melanomas positive for both LINC and PRAME.

Ferris and colleagues (2019b) stated that the Pigmented Lesion Assay (PLA, sensitivity of 91 to 95 %, specificity of 69 to 91 %, negative predictive value [NPV] of greater than 99 %) is a commercially available, non-invasive gene expression test that helps dermatologists guide pigmented lesion management decisions and rule out melanoma.  Earlier studies have demonstrated high clinical utility and no missed melanomas in a 3 to 6 months follow-up period.  These researchers provided 12-month follow-up data on PLA(-) tests, and to further confirm utility.  They carried out a 12-month chart review follow-up of 734 pigmented lesions that had negative PLA results from 5 U.S. dermatology centers; 13 of these lesions (1.8 %) were biopsied in the follow-up period and submitted for histopathologic review.  None of the lesions biopsied had a histopathologic diagnosis of melanoma.  The test's utility was studied further in a registry (n = 1,575, 40 U.S. dermatology offices, 62 participating providers), which demonstrated that 99.9 % of PLA(-) lesions were clinically monitored, thereby avoiding a surgical procedure, and 96.5 % of all PLA(+) lesions were appropriately biopsied, most commonly with a tangential shave.  The authors concluded that this long-term follow-up study confirmed the PLA's high NPV and high utility in helping guide the management of pigmented lesions to avoid unnecessary surgical procedures.

The authors stated that inherent limitations of the data presented included the assumption that lesions of patients not returning to follow-up visits at the site of PLA testing within a 12-month follow-up period were true negatives.  Furthermore, these investigators could not rule out that some PLA(-) lesions may not have been adequately re-assessed within the 12-month follow-up period and they recommended erring on the side of caution and performed a surgical biopsy of a lesion in question if additional risk factors and further clinical suspicion or patient concern mandated such a step.  Further limitations inherent to studies designed to evaluate melanoma rule-out tests and platforms in real-world settings included the low prevalence of melanoma compared to how common benign lesions of clinically similar appearance are in given target populations.  However, it was comforting to consider that the non-invasive gene expression platform used here lends itself to validation study comparisons that can exceed the quality level of randomized control groups.  With this platform it is possible to obtain non-invasive gene expression information and histopathology reads from the same lesion.

In a discussion of "emerging" diagnostic technologies, guidelines on cutaneous melanoma from the American Academy of Dermatology (Swetter et al, 2019) state that "Noninvasive genomic methods (eg, adhesive patch "biopsy") are being investigated to further classify melanocytic lesions as either benign or malignant to guide the need for further biopsy".

Robinson and Jansen (2020) noted that physician appointments for non-essential care ceased during COVID-19.  These researchers pilot tested a telehealth solution for patients to rule out melanomas and need for surgical biopsies based on genomic analyses of pigmented lesion samples obtained via adhesive patches.  Surveys examined skin self-examination (SSE) anxiety.  Under remote clinician guidance, patients or partners obtained samples using adhesive patches (DermTech, La Jolla, CA).  SSE anxiety increased.  Guided self-sampling led to molecular risk factor analyses in 7/7 (100 %) of cases compared to 9/10 (90 %) randomly selected physician-sampled control cases.  The authors concluded that adhesive patch (DermTech) self-sampling under remote physician guidance is a viable specimen collection option.  This was a proof-of-concept (pilot) study with small sample size (n = 7 for the DermTech group); its findings need to be validated by well-designed studies.

Brouha et al (2020) stated that the pigmented lesion assay (PLA) is a non-invasive gene expression test that aids clinicians in ruling out melanoma via a genomics approach, which elevates pigmented lesion management beyond what the eye can see.  It improves care with a negative predictive value (NPV) of greater than 99 % while reducing biopsies by 90 % and while reducing cost.  This registry study described in this study (53 U.S. dermatology offices, 90 providers, median patient age of 48 years, 60.80 % female and 39.20 % male patients) assesses real-world utility to determine if the PLA changes clinical practice.  Of 3,418 pigmented skin lesions clinically suspicious for melanoma and assessed by PLA, 324 lesions (9.48 %) were PLA(+) and 3,094 (90.52 %) were negative.  A PLA test result was positive if LINC, PRAME, or both target genes are detected; these molecular pathology findings are known to correspond with histopathology findings of in-situ or invasive primary melanoma in 7 %, 50 %, and 93 %, respectively.  The 9.48 % PLA(+) cases consisted of 5.15 % LINC only, 1.93 % PRAME only, and 2.40 % LINC and PRAME double-positive cases.  Notably, PLA(+) lesions were surgically biopsied 97.53 % while PLA(-) cases were clinically monitored and not biopsied in 99.94 % of the cases.  The authors concluded that these findings demonstrated that community-based clinicians who employ the PLA to improve pigmented lesion management used the test’s results to guide how they practice.  Pigmented lesions with PLA(+) test results were subjected to surgical biopsies, whereas PLA(-) lesions were followed clinically and not biopsied.  It should be noted that this study was partially supported by DermTech, Inc; and BB, LF, MS, RM, and GP are advisors to, and BJ and ZY are employees of, DermTech.

Brouha et al (2021) noted that melanoma is diagnosed in approximately 200,000 individuals within the U.S. each year and is responsible for more than 6,850 deaths.  Currently, clinical suspicion guides biopsy decisions and melanoma is confirmed in approximately 4 % of biopsied lesions. A non-invasive 2-gene expression test (2-GEP) was demonstrated to enhance the physical examination by examining genomic atypia to guide biopsy decisions.  These researchers examined the corresponding histopathology of real-world 2-GEP-positive cases.  Cutaneous lesions suspicious for melanoma (n = 3,418) were 2-GEP tested by 90 licensed clinicians in real-world practice.  2-GEP-positive lesions (genomically atypical as indicated by the detection of LINC and/or PRAME) were biopsied in 316 out of 324 (97.5 %) cases and 313 pathology reports were available for analysis.  Biopsied 2-GEP-positive lesions were separated into diagnostic subgroups based on corresponding pathology reports.  The prevalence of melanoma in biopsies of 2-GEP-positive lesions was 18.7 %.  Gene expression of both LINC and PRAME was present in ever-increasing percentages of melanocytic lesions as pathology reports demonstrated increasing levels of atypia.  Notably, 47.5 % of the histopathologically-confirmed melanomas demonstrated this double positive genomic signature while 23.7 % were single-positive for LINC and 28.8 % were single-positive for PRAME.  The authors concluded that these findings showed that biopsied 2-GEP-positive lesions were enriched almost 5-fold for advanced histopathologic features compared to those biopsied based solely on visual assessment criteria.  The close correlation between genomic atypia and atypical pathology should be considered when planning treatment of a 2-GEP-positive lesion.  Consideration of genomic atypia may be a superior approach to guide biopsy decisions and manage pigmented lesions.

An UpToDate review on "Melanoma: Clinical features and diagnosis" (Swetter and Geller, 2020) lists "adhesive patch genomic analysis" as one of the support techniques for clinical diagnosis.  It notes that "Adhesive patch genomic analysis – A noninvasive test that uses genetic information from cells collected from the surface of melanocytic lesions with an adhesive patch was developed to help in the decision to biopsy an atypical, melanocytic lesion.  The so-called "pigmented lesion assay" (PLA) measures the expression of the genes LINC and PRAME.  Overexpression of these 2 genes appears to be associated with the presence of somatic mutations in BRAF non-V600E, NRAS, and TERT, which are involved in melanoma development and progression".  However, adhesive patch genomic analysis/pigmented lesion assay (PLA) is not mentioned in the "Summary and Recommendations" section of this review.

National Comprehensive Cancer Network’s clinical practice guideline on "Cutaneous melanoma" (Version 1.2021) states that "[a]vailable, noninvasive pre-biopsy imaging and molecular technologies have not been prospectively compared for diagnostic accuracy. . . Pre-diagnostic noninvasive genomic patch testing may also be helpful to guide biopsy decisions." 

There is an ongoing clinical trial on "Targeted Melanoma Detection with Skin Self-Examination During COVID-19 Restricted Physician Access (TMD)" (ClinicalTrials.gov ID NCT04420273).  This trial entails physician supervised non-invasive adhesive patch-based home sample collection of a concerning mole for genomic analysis (last updated September 4, 2020).  

Computerized Total Body Photography Systems

Marchesini et al (2002) noted that early detection and prompt excision of cutaneous melanoma is of paramount importance to improve patient survival, and the clinician should be aware of the clinical features that suggest the presence of a malignant lesion.  The clinical diagnosis is mainly based on observation of the color and shape of a given skin lesion.  Unfortunately, evaluation of a pigmented lesion is to a large extent subjective and is closely related to the experience of the clinician.  To overcome this problem, optical imaging techniques using different instrumentation (i.e., color video camera, ELM, reflectance spectrophotometry [SPT]) and computer image analysis have been proposed in an attempt to provide quantitative measurements in an objective and reproducible fashion.  The different procedures employed to perform the diagnosis automatically all have a common denominator: mimicking the eye and the brain of the clinician by image processing and computerized analysis programs, respectively.  Sensitivity and specificity data reported in the literature suggest that the computer-based diagnosis of melanoma does not greatly differ from the diagnostic capability of an expert clinician, and is independent of the optical acquisition method employed to analyze the lesions.  Most of the computer-processed morphometric variables useful in automated diagnosis are not recognizable nor can be objectively evaluated by the human eye, except that of lesion dimension.  However, several questions should be answered before assessing the actual usefulness, including the potential and limitations, of computer-based diagnostic procedures. 

In a randomized, controlled trial, Walter et al (2012) examined if adding a novel computerized diagnostic tool, the MoleMate system (SIAscopy with primary care scoring algorithm), to current best practice results in more appropriate referrals of suspicious pigmented lesions to secondary care, and to assess its impact on clinicians and patients.  Subjects were 1,297 adults with pigmented skin lesions not immediately diagnosed as benign.  Patients were assessed by trained primary care clinicians using best practice (clinical history, naked eye examination, 7-point checklist) either alone (control group) or with the MoleMate system (intervention group).  Main outcome measures included appropriateness of referral, defined as the proportion of referred lesions that were biopsied or monitored.  Secondary outcomes related to the clinicians (diagnostic performance, confidence, learning effects) and patients (satisfaction, anxiety).  Economic evaluation, diagnostic performance of the 7-point checklist, and 5-year follow-up of melanoma incidence were also secondary outcomes and will be reported later.  A total of 1,297 participants with 1,580 lesions were randomized: 643 participants with 788 lesions to the intervention group and 654 participants with 792 lesions to the control group.  The appropriateness of referral did not differ significantly between the intervention or control groups: 56.8 % (130/229) versus 64.5 % (111/172); difference -8.1 % (95 % CI: -18.0 % to 1.8 %).  The proportion of benign lesions appropriately managed in primary care did not differ (intervention 99.6 % versus control 99.2 %, p = 0.46), neither did the percentage agreement with an expert decision to biopsy or monitor (intervention 98.5 % versus control 95.7 %, p = 0.26).  The percentage agreement with expert assessment that the lesion was benign was significantly lower with MoleMate (intervention 84.4 % versus control 90.6 %, p < 0.001), and a higher proportion of lesions were referred (intervention 29.8 % versus control 22.4 %, p = 0.001).  A total of 36 histologically confirmed melanomas were diagnosed: 18/18 were appropriately referred in the intervention group and 17/18 in the control group.  Clinicians in both groups were confident, and there was no evidence of learning effects, and therefore contamination, between groups.  Patients in the intervention group ranked their consultations higher for thoroughness and reassuring care, although anxiety scores were similar between the groups.  The authors concluded that there was no evidence that the MoleMate system improved appropriateness of referral.  The systematic application of best practice guidelines alone was more accurate than the MoleMate system, and both performed better than reports of current practice.  Therefore, the systematic application of best practice guidelines (including the s7-point checklist) should be the paradigm for management of suspicious skin lesions in primary care.

Ferrante di Ruffano and colleagues (2018a) stated that early accurate detection of all skin cancer types is essential to guide appropriate management and to improve morbidity and survival.  Melanoma and cutaneous squamous cell carcinoma (cSCC) are high-risk skin cancers which have the potential to metastasize and ultimately lead to death, whereas basal cell carcinoma (BCC) is usually localized with potential to infiltrate and damage surrounding tissue.  Anxiety around missing early curable cases needs to be balanced against inappropriate referral and unnecessary excision of benign lesions.  Computer-assisted diagnosis (CAD) systems use artificial intelligence to analyze lesion data and arrive at a diagnosis of skin cancer.  When used in un-referred settings ("primary care"), CAD may assist general practitioners (GPs) or other clinicians to more appropriately triage high-risk lesions to secondary care.  Used alongside clinical and dermoscopic suspicion of malignancy, CAD may reduce unnecessary excisions without missing melanoma cases.  In a Cochrane review, these investigators determined the accuracy of CAD systems for diagnosing cutaneous invasive melanoma and atypical intra-epidermal melanocytic variants, BCC or cSCC in adults, and compared its accuracy with that of dermoscopy.  These researchers undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials (CENTRAL); Medline; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform.  They studied reference lists and published systematic review articles.  Studies of any design that evaluated CAD alone, or in comparison with dermoscopy, in adults with lesions suspicious for melanoma or BCC or cSCC, and compared with a reference standard of either histological confirmation or clinical follow-up were selected for analysis.  Two review authors independently extracted all data using a standardized data extraction and quality assessment form (based on QUADAS-2).  They contacted authors of included studies where information related to the target condition or diagnostic threshold were missing.  These investigators estimated summary sensitivities and specificities separately by type of CAD system, using the bi-variate hierarchical model.  They compared CAD with dermoscopy using

1. all available CAD data (indirect comparisons), and
2. studies providing paired data for both tests (direct comparisons).  They tested the contribution of human decision-making to the accuracy of CAD diagnoses in a sensitivity analysis by removing studies that gave CAD results to clinicians to guide diagnostic decision-making.

A total of 42 studies were included in this study, 24 evaluating digital dermoscopy-based CAD systems (Derm-CAD) in 23 study cohorts with 9,602 lesions (1,220 melanomas, at least 83 BCCs, 9 cSCCs), providing 32 datasets for Derm-CAD and 7 for dermoscopy; 18 studies evaluated spectroscopy-based CAD (Spectro-CAD) in 16 study cohorts with 6,336 lesions (934 melanomas, 163 BCC, 49 cSCCs), providing 32 datasets for Spectro-CAD and 6 for dermoscopy.  These consisted of 15 studies using multi-spectral imaging (MSI), 2 studies using electrical impedance spectroscopy (EIS) and 1 study using diffuse-reflectance spectroscopy.  Studies were incompletely reported and at unclear to high risk of bias across all domains.  Included studies inadequately addressed the review question, due to an abundance of low-quality studies, poor reporting, and recruitment of highly selected groups of participants.  Across all CAD systems, these researchers found considerable variation in the hardware and software technologies used, the types of classification algorithm employed, methods used to train the algorithms, and which lesion morphological features were extracted and analyzed across all CAD systems, and even between studies evaluating CAD systems.  Meta-analysis found CAD systems had high sensitivity for correct identification of cutaneous invasive melanoma and atypical intra-epidermal melanocytic variants in highly selected populations, but with low and very variable specificity, particularly for Spectro-CAD systems.  Pooled data from 22 studies estimated the sensitivity of Derm-CAD for the detection of melanoma as 90.1 % (95 % CI: 84.0 % to 94.0 %) and specificity as 74.3 % (95% CI: 63.6 % to 82.7 %).  Pooled data from 8 studies estimated the sensitivity of MSI-CAD as 92.9 % (95 % CI: 83.7 % to 97.1 %) and specificity as 43.6 % (95 % CI: 24.8 % to 64.5 %).  When applied to a hypothetical population of 1,000 lesions at the mean observed melanoma prevalence of 20 %, Derm-CAD would miss 20 melanomas and would lead to 206 false-positive results for melanoma.  MSI-CAD would miss 14 melanomas and would lead to 451 false diagnoses for melanoma.  Preliminary findings suggested that CAD systems were at least as sensitive as assessment of dermoscopic images for the diagnosis of invasive melanoma and atypical intra-epidermal melanocytic variants.  These investigators were unable to make summary statements regarding the use of CAD in un-referred populations, or its accuracy in detecting keratinocyte cancers, or its use in any setting as a diagnostic aid, because of the paucity of studies.  The authors concluded that in highly selected patient populations all CAD types demonstrated high sensitivity, and could prove useful as a back-up for specialist diagnosis to assist in minimizing the risk of missing melanomas.  However, the evidence base is currently too poor to understand whether CAD system outputs translate to different clinical decision-making in practice.  Insufficient data are available on the use of CAD in community settings, or for the detection of keratinocyte cancers.  The evidence base for individual systems is too limited to draw conclusions on which might be preferred for practice.  Moreover, they stated that prospective comparative studies are needed to evaluate the use of CAD systems as diagnostic aids, by comparison to face-to-face dermoscopy, and in participant populations that are representative of those in which the test would be used in practice.

High-Frequency Ultrasonography

In a Cochrane review, Dinnes and colleagues (2018a) evaluated the diagnostic accuracy of high-frequency ultrasound (HFUS) to assist in the diagnosis of (a) cutaneous invasive melanoma and atypical intra-epidermal melanocytic variants, (b) cSCC, and (c) BCC in adults.  These researchers undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; Medline; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform.  They studied reference lists as well as published systematic review articles.  Studies evaluating HFUS (20 MHz or more) in adults with lesions suspicious for melanoma, cSCC or BCC versus a reference standard of histological confirmation or clinical follow-up were selected for analysis.  Two review authors independently extracted all data using a standardized data extraction and quality assessment form (based on QUADAS-2).  Due to scarcity of data and the poor quality of studies, these investigators did not undertake a meta-analysis for this review.  For illustrative purposes, they plotted estimates of sensitivity and specificity on coupled forest plots.  The authors included 6 studies, providing 29 datasets: 20 for diagnosis of melanoma (1,125 lesions and 242 melanomas) and 9 for diagnosis of BCC (993 lesions and 119 BCCs).  They did not identify any data relating to the diagnosis of cSCC.  Studies were generally poorly reported, limiting judgements of methodological quality; 50 % the studies did not set out to establish test accuracy, and all should be considered preliminary evaluations of the potential usefulness of HFUS.  There were particularly high concerns for applicability of findings due to selective study populations and data-driven thresholds for test positivity.  Studies reporting qualitative assessments of HFUS images excluded up to 22 % of lesions (including some melanomas) due to lack of visualization in the test.  Derived sensitivities for qualitative HFUS characteristics were at least 83 % (95 % CI: 75 % to 90 %) for the detection of melanoma; the combination of 3 features (lesions appearing hypoechoic, homogenous and well defined) demonstrating 100 % sensitivity in 2 studies (lower limits of the 95 % CIs were 94 % and 82 %), with variable corresponding specificities of 33 % (95 % CI: 20 % to 48 %) and 73 % (95 % CI: 57 % to 85 %), respectively.  Quantitative measurement of HFUS outputs in 2 studies enabled decision thresholds to be set to achieve 100 % sensitivity; specificities were 93 % (95 % CI: 77 % to 99 %) and 65 % (95 % CI: 51 % to 76 %).  It was not possible to make summary statements regarding HFUS accuracy for the diagnosis of BCC due to highly variable sensitivities and specificities.  The authors concluded that insufficient data are available on the potential value of HFUS in the diagnosis of melanoma or BCC.  Given the between-study heterogeneity, unclear to low methodological quality and limited volume of evidence, these researchers cannot draw any implications for practice.  The main value of the preliminary studies included may be in providing guidance on the possible components of new diagnostic rules for diagnosis of melanoma or BCC using HFUS that will require future evaluation.  They stated that a prospective evaluation of HFUS added to visual inspection and dermoscopy alone in a standard healthcare setting, with a clearly defined and representative population of participants, would be needed for a full and proper evaluation of accuracy.

Optical Coherence Tomography

Reggiani et al (2015) stated that non-melanoma skin cancer (NMSC) is the most common malignancy in fair skinned populations.  Dermoscopy, reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) are non-invasive imaging techniques that play an important role in diagnosis of skin tumors.  These investigators provided new insights into the role of non-invasive techniques in the diagnosis of NMSCs, concentrating especially on dermoscopy, RCM and OCT.  They performed a PubMed search concerning the role of dermoscopy, RCM and OCT in the diagnosis of NMSC.  Duplicated studies, single-case report, and papers with language other than English were excluded from analysis.  New and old literature about early diagnosis of NMSC through non-invasive imaging techniques were analyzed.  The role and the diagnostic accuracy of dermoscopy, RCM and OCT for the diagnosis of NMSC were reported.  The authors concluded that the development of non-invasive diagnostic devices (especially dermoscopy, RCM and OCT) allows tissue imaging in-vivo contributing to a more accurate diagnosis of skin cancer, sparing time for the patient and costs for the public health system.

In a Cochrane review, Ferrante di Ruffano and colleagues (2018b) determined the diagnostic accuracy of OCT for the detection of cutaneous invasive melanoma and atypical intra-epidermal melanocytic variants, BCC, or cSCC in adults.  These researchers undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; Medline; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform.  They studied reference lists and published systematic review articles.  These investigators included studies of any design evaluating OCT in adults with lesions suspicious for invasive melanoma and atypical intra-epidermal melanocytic variants, BCC or cSCC, compared with a reference standard of histological confirmation or clinical follow-up.  Two review authors independently extracted data using a standardized data extraction and quality assessment form (based on QUADAS-2); the unit of analysis was lesions.  Where possible, these researchers estimated summary sensitivities and specificities using the bi-variate hierarchical model.  They included 5 studies with 529 cutaneous lesions (282 malignant lesions) providing 9 datasets for OCT, 2 for visual inspection alone, and 2 for visual inspection plus dermoscopy.  Studies were of moderate-to-unclear quality, using data-driven thresholds for test positivity and giving poor accounts of reference standard interpretation and blinding.  Studies may not have been representative of populations eligible for OCT in practice, for example due to high disease prevalence in study populations, and may not have reflected how OCT is used in practice, for example by using previously acquired OCT images.  It was not possible to make summary statements regarding accuracy of detection of melanoma or of cSCC because of the paucity of studies, small sample sizes, and for melanoma differences in the OCT technologies used (high-definition versus conventional resolution OCT), and differences in the degree of testing performed prior to OCT (i.e., visual inspection alone or visual inspection plus dermoscopy).  Pooled data from 2 studies using conventional swept-source OCT alongside visual inspection and dermoscopy for the detection of BCC estimated the sensitivity of OCT as 95 % (95 % CI: 91 % to 97 %) and specificity of 77 % (95 % CI: 69 % to 83 %).  When applied to a hypothetical population of 1,000 lesions at the mean observed BCC prevalence of 60 %, OCT would miss 31 BCCs (91 fewer than would be missed by visual inspection alone and 53 fewer than would be missed by visual inspection plus dermoscopy), and OCT would lead to 93 false-positive results for BCC (a reduction in unnecessary excisions of 159 compared to using visual inspection alone and of 87 compared to visual inspection plus dermoscopy).  The authors concluded that insufficient data are available on the use of OCT for the detection of melanoma or cSCC.  Initial data suggested conventional OCT may have a role for the diagnosis of BCC in clinically challenging lesions, with this meta-analysis showing a higher sensitivity and higher specificity when compared to visual inspection plus dermoscopy.  However, the small number of studies and varying methodological quality meant implications to guide practice cannot currently be drawn.  These investigators stated that appropriately designed prospective comparative studies are needed, given the paucity of data comparing OCT with dermoscopy and other similar diagnostic aids such as reflectance confocal microscopy.

Reflectance Confocal Microscopy

Gerger et al (2005) stated that in vivo confocal laser scanning microscopy (CLSM) represents a novel imaging tool that allows the examination of skin morphology in real time at a resolution equal to that of conventional microscopes.  These researchers tested the applicability of CLSM to the diagnostic discrimination of benign nevi and melanoma.  Five independent observers without previous experience in CLSM received a standardized instruction about diagnostic CLSM features.  Subsequently, 117 melanocytic skin tumors (90 benign nevi and 27 melanoma), imaged using a commercially available, near-infrared, reflectance confocal laser scanning microscope, were evaluated by each observer.  Overall, sensitivity of 88.2 % and specificity of 97.6 % was achieved by the 5 observers.  Logistic regression analysis revealed that mainly cytomorphology, architecture and keratinocyte cell borders should be taken into account for diagnostic decisions.  Remarkably, using the presence or absence of monomorphic melanocytes as a single diagnostic criterion, the classification results with a sensitivity of 98.2 % and a specificity of 98.9 % were superior to the intuitive, integrative judgment of the observers.  These investigators concluded that this first sensitivity and specificity study with CLSM has yielded promising results.  Furthermore, Marghoob and Halpern (2005) stated that the future of CLSM looks bright; however, much work is needed before the application of this technology in routine clinical practice. 

Psaty and Halpern (2009) noted that diagnostic aids such as TBP and dermoscopy, improve clinicians' ability to diagnose melanoma beyond un-aided visual inspection, and are considered mainstream methods for early detection.  Emerging technologies such as in vivo reflectance confocal microscopy are currently being investigated to determine their utility for non-invasive diagnosis of melanoma.

Longo et al (2103) stated that reflectance confocal microscopy (RCM) is a novel technique that allows visualization of the skin at nearly histological resolution although limited laser depth penetration hampers visualization of the deep dermis.  These researchers examined if the diagnostic accuracy of RCM was comparable to histopathology for the diagnosis of nodular lesions, and identified possible limitations of this technique.  They retrospectively evaluated 140 nodules by means of RCM while blinded from the histopathological diagnosis.  At the end of the study the patient codes were broken and the evaluations were matched with histopathological diagnosis before performing statistical analysis.  The study consisted of 140 nodular lesions (23 "pure" nodular melanomas, 9 melanoma metastases, 28 basal cell carcinomas (BCCs), 6 invasive squamous cell carcinomas (SCCs), 32 naevi, 14 seborrheic keratoses, 17 dermatofibromas, 5 vascular lesions and 6 other lesions).  Reflectance confocal microscopy correctly diagnosed 121 of 140 lesions (86.4 %); 8 of 140 (5.7 %) lesions revealed discordance between histopathology and confocal microscopy.  Eight of the 140 (5.7 %) cases were not evaluable by means of RCM due to the presence of ulceration or hyperkeratosis and 3 cases showed a non-specific pattern.  Interestingly, confocal microscopy reached a 96.5 % sensitivity and 94.1 % specificity (area under curve 0.970) (95 % CI: 0.924 to 1.015) (p < 0.001) for the diagnosis of melanoma.  The authors concluded that this study was retrospective and lesions were not included on the basis of their diagnostic difficulty.  They noted that despite the limited laser depth penetration of RCM, this imaging tool represents an effective instrument in diagnosing nodular lesions; however, for fully ulcerated lesions or when a marked hyperkeratosis is present, biopsy should always be performed.  They stated that prospective studies on difficult-to-diagnose nodules should be performed to analyze further the pros and cons of RCM in skin cancer diagnosis.

In a Cochrane review, Dinnes and colleagues (2018b) determined the diagnostic accuracy of RCM for the detection of cutaneous invasive melanoma and atypical intra-epidermal melanocytic variants in adults with any lesion suspicious for melanoma and lesions that are difficult to diagnose, and compared its accuracy with that of dermoscopy.  These researchers undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; Medline; Embase; and 7 other databases.  They studied reference lists and published systematic review articles.  Studies of any design that evaluated RCM alone, or RCM in comparison to dermoscopy, in adults with lesions suspicious for melanoma or atypical intra-epidermal melanocytic variants, compared with a reference standard of either histological confirmation or clinical follow-up were selected for analysis.  Two review authors independently extracted all data using a standardized data extraction and quality assessment form (based on QUADAS-2).  They contacted authors of included studies where information related to the target condition or diagnostic threshold were missing.  They estimated summary sensitivities and specificities per algorithm and threshold using the bi-variate hierarchical model.  To compare RCM with dermoscopy, these investigators grouped studies by population (defined by difficulty of lesion diagnosis) and combined data using hierarchical summary receiver operating characteristic (SROC) methods.  Analysis of studies allowing direct comparison between tests was undertaken.  To facilitate interpretation of results, the authors computed values of specificity at the point on the SROC curve with 90 % sensitivity as this value lies within the estimates for the majority of analyses.  They examined the impact of using a purposely developed RCM algorithm and in-person test interpretation.  The search identified 18 publications reporting on 19 study cohorts with 2,838 lesions (including 658 with melanoma), which provided 67 datasets for RCM and 7 for dermoscopy.  Studies were generally at high or unclear risk of bias across almost all domains and of high or unclear concern regarding applicability of the evidence.  Selective participant recruitment, lack of blinding of the reference test to the RCM result, and differential verification were particularly problematic.  Studies may not be representative of populations eligible for RCM, and test interpretation was often undertaken remotely from the patient and blinded to clinical information.  Meta-analysis found RCM to be more accurate than dermoscopy in studies of participants with any lesion suspicious for melanoma and in participants with lesions that were more difficult to diagnose (equivocal lesion populations).  Assuming a fixed sensitivity of 90 % for both tests, specificities were 82 % for RCM and 42 % for dermoscopy for any lesion suspicious for melanoma (9 RCM datasets; 1,452 lesions and 370 melanomas).  For a hypothetical population of 1,000 lesions at the median observed melanoma prevalence of 30 %, this equated to a reduction in unnecessary excisions with RCM of 280 compared to dermoscopy, with 30 melanomas missed by both tests.  For studies in equivocal lesions, specificities of 86 % would be observed for RCM and 49 % for dermoscopy (7 RCM datasets; 1,177 lesions and 180 melanomas).  At the median observed melanoma prevalence of 20 %, this reduced unnecessary excisions by 296 with RCM compared with dermoscopy, with 20 melanomas missed by both tests.  Across all populations, algorithms and thresholds assessed, the sensitivity and specificity of the Pellacani RCM score at a threshold of 3 or greater were estimated at 92 % (95 % CI: 87 to 95) for RCM and 72% (95 % CI 62 to 81) for dermoscopy.  The authors concluded that RCM may have a potential role in clinical practice, particularly for the assessment of lesions that are difficult to diagnose using visual inspection and dermoscopy alone, where the evidence suggested that RCM may be both more sensitive and specific in comparison to dermoscopy.  Moreover, these researchers stated that given the paucity of data to allow comparison with dermoscopy, the results presented require further confirmation in prospective studies comparing RCM with dermoscopy in a real-world setting in a representative population.

In a Cochrane review, Dinnes and colleagues (2018c) determined the diagnostic accuracy of RCM for the detection of BCC, cSCC, or any skin cancer in adults with any suspicious lesion and lesions that are difficult to diagnose (equivocal); and compared its accuracy with that of usual practice (visual inspection or dermoscopy, or both).  These researchers undertook a comprehensive search of the following databases from inception to August 2016: Cochrane Central Register of Controlled Trials; Medline; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform.  They studied reference lists and published systematic review articles.  Studies of any design that evaluated the accuracy of RCM alone, or RCM in comparison to visual inspection or dermoscopy, or both, in adults with lesions suspicious for skin cancer compared with a reference standard of either histological confirmation or clinical follow-up, or both were selected for analysis.  Two review authors independently extracted data using a standardized data extraction and quality assessment form (based on QUADAS-2).  These investigators contacted authors of included studies where information related to the target condition or diagnostic threshold were missing.  They estimated summary sensitivities and specificities using the bi-variate hierarchical model.  For computation of likely numbers of true-positive, false-positive, false-negative, and true-negative findings in the "Summary of findings" tables, they applied summary sensitivity and specificity estimates to lower quartile, median and upper quartiles of the prevalence observed in the study groups.  They also examined the impact of observer experience.  The review included 10 studies reporting on 11 study cohorts.  All 11 cohorts reported data for the detection of BCC, including 2,037 lesions (464 with BCC); and 4 cohorts reported data for the detection of cSCC, including 834 lesions (71 with cSCC).  Only 1 study also reported data for the detection of BCC or cSCC using dermoscopy, limiting comparisons between RCM and dermoscopy.  Studies were at high or unclear risk of bias across almost all methodological quality domains, and were of high or unclear concern regarding applicability of the evidence.  Selective participant recruitment, unclear blinding of the reference test, and exclusions due to image quality or technical difficulties were observed.  It was unclear whether studies were representative of populations eligible for testing with RCM, and test interpretation was often undertaken using images, remotely from the participant and the interpreter blinded to clinical information that would normally be available in practice.  Meta-analysis found RCM to be more sensitive but less specific for the detection of BCC in studies of participants with equivocal lesions (sensitivity 94 %, 95 % CI: 79 % to 98 %; specificity 85 %, 95 % CI: 72 % to 92 %; 3 studies) compared to studies that included any suspicious lesion (sensitivity 76 %, 95 % CI: 45 % to 92 %; specificity 95 %, 95 % CI: 66 % to 99 %; 4 studies), although CIs were wide.  At the median prevalence of disease of 12.5 % observed in studies including any suspicious lesion, applying these results to a hypothetical population of 1,000 lesions results in 30 BCCs missed with 44 false-positive results (lesions misdiagnosed as BCCs).  At the median prevalence of disease of 15 % observed in studies of equivocal lesions, 9 BCCs would be missed with 128 false-positive results in a population of 1,000 lesions.  Across both sets of studies, up to 15 % of these false-positive lesions were observed to be melanomas mistaken for BCCs.  There was some suggestion of higher sensitivities in studies with more experienced observers.  Summary sensitivity and specificity could not be estimated for the detection of cSCC due to paucity of data.  The authors concluded that there is insufficient evidence for the use of RCM for the diagnosis of BCC or cSCC in either population group.  A possible role for RCM in clinical practice is as a tool to avoid diagnostic biopsies in lesions with a relatively high clinical suspicion of BCC.  These investigators stated that the potential for, and consequences of, misclassification of other skin cancers such as melanoma as BCCs requires further research; and more importantly, data are lacking that compare RCM to standard clinical practice (with or without dermoscopy).

The American Academy of Dermatology (AAD)’s guideline on "Care for the management of primary cutaneous melanoma" (Swetter et al, 2019) lists RCM as one of the "emerging" diagnostic technologies.  The guideline states that "Currently, there are limited data to support the use of in vivo imaging technologies for intraoperative, surgical margin assessment of melanoma in-situ (MIS), lentigo maligna (LM) type.  Some preliminary data suggest that in vivo RCM can be helpful in identifying the tumor’s peripheral margin and therefore guide surgical removal, and this approach remains an active area of investigation".

Teledermatology / Teledermoscopy

In a Cochrane review, Chuchu and colleagues (2018) determined the diagnostic accuracy of teledermatology for the detection of any skin cancer (melanoma, BCC or cSCC) in adults, and compared its accuracy with that of in-person diagnosis.  These researchers undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials, Medline, Embase, CINAHL, CPCI, Zetoc, Science Citation Index, US National Institutes of Health Ongoing Trials Register, NIHR Clinical Research Network Portfolio Database and the World Health Organization International Clinical Trials Registry Platform.  They studied reference lists and published systematic review articles.  Studies evaluating skin cancer diagnosis for teledermatology alone, or in comparison with face-to-face diagnosis by a specialist clinician, compared with a reference standard of histological confirmation or clinical follow-up and expert opinion were selected for analysis.  They also included studies evaluating the referral accuracy of teledermatology compared with a reference standard of face-to-face diagnosis by a specialist clinician.  Two review authors independently extracted all data using a standardized data extraction and quality assessment form (based on QUADAS-2).  They contacted authors of included studies where there were information related to the target condition of any skin cancer missing.  Data permitting, these investigators estimated summary sensitivities and specificities using the bi-variate hierarchical model.  Due to the scarcity of data, these researchers undertook no co-variate investigations for this review.  For illustrative purposes, they plotted estimates of sensitivity and specificity on coupled forest plots for diagnostic threshold and target condition under consideration.  The review included 22 studies reporting diagnostic accuracy data for 4,057 lesions and 879 malignant cases (16 studies) and referral accuracy data for reported data for 1,449 lesions and 270 "positive" cases as determined by the reference standard face-to-face decision (6 studies).  Methodological quality was variable with poor reporting hindering assessment.  The overall risk of bias was high or unclear for participant selection, reference standard, and participant flow and timing in at least 50 % of all studies; the majority were at low risk of bias for the index test.  The applicability of study findings were of high or unclear concern for most studies in all domains assessed due to the recruitment of participants from secondary care settings or specialist clinics rather than from primary or community-based settings in which teledermatology was more likely to be used and due to the acquisition of lesion images by dermatologists or in specialist imaging units rather than by primary care clinicians; 7 studies provided data for the primary target condition of any skin cancer (1,588 lesions and 638 malignancies).  For the correct diagnosis of lesions as malignant using photographic images, summary sensitivity was 94.9 % (95 % CI: 90.1 % to 97.4 %) and summary specificity was 84.3 % (95 % CI: 48.5 % to 96.8 %) (from 4 studies).  Individual study estimates using dermoscopic images or a combination of photographic and dermoscopic images generally suggested similarly high sensitivities with highly variable specificities.  Limited comparative data suggested similar diagnostic accuracy between teledermatology assessment and in-person diagnosis by a dermatologist; however, data were too scarce to draw firm conclusions.  For the detection of invasive melanoma or atypical intra-epidermal melanocytic variants both sensitivities and specificities were more variable.  Sensitivities ranged from 59 % (95 % CI: 42 % to 74 %) to 100 % (95 % CI: 48 % to 100 %) and specificities from 30 % (95 % CI: 22 % to 40 %) to 100 % (95 % CI: 93 % to 100 %), with reported diagnostic thresholds including the correct diagnosis of melanoma, classification of lesions as "atypical" or "typical", and the decision to refer or to excise a lesion.  Referral accuracy data comparing teledermatology against a face-to-face reference standard suggested good agreement for lesions considered to require some positive action by face-to-face assessment (sensitivities of over 90 %).  For lesions considered of less concern when assessed face-to-face (e.g., for lesions not recommended for excision or referral), agreement was more variable with teledermatology specificities ranging from 57 % (95 % CI: 39 % to 73 %) to 100 % (95 % CI: 86 % to 100 %), suggesting that remote assessment is more likely recommend excision, referral or follow-up compared to in-person decisions.  The authors concluded that studies were generally small and heterogeneous and methodological quality was difficult to judge due to poor reporting.  Bearing in mind concerns regarding the applicability of study participants and of lesion image acquisition in specialist settings, these findings suggested that teledermatology could correctly identify the majority of malignant lesions.  Using a more widely defined threshold to identify "possibly" malignant cases or lesions that should be considered for excision is likely to appropriately triage those lesions requiring face-to-face assessment by a specialist.  These investigators stated that despite the increasing use of teledermatology on an international level, the evidence base to support its ability to accurately diagnose lesions and to triage lesions from primary to secondary care is lacking and further prospective and pragmatic evaluation is needed.

Bruce and associates (2018) noted that the use of teledermoscopy in the diagnostic management of pre-cancerous and cancerous skin lesions involves digital dermoscopic images transmitted over telecommunication networks via email or web applications.  Teledermoscopy may improve the accuracy in clinical diagnoses of melanoma skin cancer if integrated into electronic medical records and made available to rural communities, potentially leading to decreased morbidity and mortality.  These investigators presented a systematic review of evidence on the use of teledermoscopy to improve the accuracy of skin lesion identification in adult populations.  The PRISMA method guided the development of this systematic review.  A total of 7 databases were searched for articles published between the years of 2000 and 2015.  All studies were critically appraised using the Rosswurm and Larrabee critique worksheet, placed in a matrix for comparison evaluating internal and external validity and inspected for homogeneity of findings.  A total of 16 articles met inclusion criteria for this review.  A majority of the studies were cross-sectional and non-experimental; 10 of the 16 focused on inter-observer concordance and diagnostic agreement between teledermoscopy and another comparator.  Instrumentation in conducting the studies showed inconsistency with reported results.  The authors concluded that higher level evidence is needed to support clinical application of teledermoscopy for accuracy of diagnostic measurement in the treatment of pre-cancerous and cancerous skin lesions in adults.  They stated that future research is needed to develop a standardized, reliable and valid measurement tool for implementation in clinical practice.

Emerging Diagnostic Techniques

The American Academy of Dermatology (AAD)’s "Guidelines of care for the management of primary cutaneous melanoma" (Swetter et al, 2019) states that "In review of the currently available highest-level evidence, the expert WG acknowledges that although much is known about the management of primary CM, much has yet to be learned.  Bedside diagnosis will continue to improve with further investigation of existing, noninvasive imaging/electrical data acquisition and evaluation tools (e.g., RCM, electrical impedance spectroscopy combined with digital dermoscopy, optical coherence tomography, cross-polarized light and fluorescence photography, and high-frequency ultrasound, some of which are already FDA approved) and novel software technologies (e.g., artificial intelligence-based deep learning algorithms) that can inform and target those lesions most concerning for malignancy.  Noninvasive genomic methods (e.g., adhesive patch ‘‘biopsy’’) are being investigated to further classify melanocytic lesions as either benign or malignant to guide the need for further biopsy.  The uptake of 1 or more of these technologies will eventually depend on cumulative evidence regarding their effectiveness, clinical utility, cost versus benefit, and competing strategies".

Table: CPT Codes / HCPCS Codes / ICD-10 Codes

Code	Code Description
Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":
CPT codes covered if selection criteria are met:
96904	Whole body integumentary photography, for monitoring of high-risk patients with dysplastic nevus syndrome or a history of dysplastic nevi, or patients with a personal or family history of melanoma
CPT codes not covered for indications listed in the CPB:
Computerized TBP systems - MelaFind, MoleMapCD, MoleMate, MoleSafe, Confocal Scanning Laser Microscopy, Electrical impedance devices, High-resolution ultrasonography, Multi-photon laser scanning microscopy (also known as multi-photon fluorescence microscopy or multi-photon excitation microscopy), Multi-spectral image analysis, Spectroscopy, Visual image analysis - no specific code
0089U	Oncology (melanoma), gene expression profiling by RTqPCR, PRAME and LINC00518, superficial collection using adhesive patch(es)
0470T	Optical coherence tomography (OCT) for microstructural and morphological imaging of skin, image acquisition, interpretation, and report; first lesion
0471T	each additional lesion (List separately in addition to code for primary procedure)
96931 - 96936	Reflectance confocal microscopy (RCM) for cellular and sub-cellular imaging of skin
ICD-10 codes covered if selection criteria are met:
C43.0 - C43.9	Malignant melanoma of the skin [not covered for multi-photon laser scanning] [not covered for DermTech Pigmented Lesion Assay]
D22.0 - D23.9	Melanocytic nevi and other benign neoplasms of the skin
Z80.8	Family history of malignant neoplasm of other organs or systems [close family history of non-melanoma skin cancers]
Z85.820	Personal history of malignant melanoma of skin
Z85.828	Personal history of other malignant neoplasm of skin
Z86.018	Personal history of other benign neoplasm [dysplastic nevus]
Z87.2	Personal history of diseases of the skin and subcutaneous tissue [atypical and dysplastic nevus]

The above policy is based on the following references: