Use of Digital Whole Slide Imaging in Dermatopathology

Dermatopathology of Malignant Melanoma in the Era of Artificial Intelligence: A Single Institutional Experience

The application of artificial intelligence (AI) algorithms in medicine could support diagnostic and prognostic analyses and decision making. In the field of dermatopathology, there have been various papers that have trained algorithms for the recognition of different types of skin lesions, such as basal cell carcinoma (BCC), seborrheic keratosis (SK) and dermal nevus. Furthermore, the difficulty in diagnosing particular melanocytic lesions, such as Spitz nevi and melanoma, considering the grade of interobserver variability among dermatopathologists, has led to an objective difficulty in training machine learning (ML) algorithms to a totally reliable, reportable and repeatable level. In this work we tried to train a fast random forest (FRF) algorithm, typically used for the classification of clusters of pixels in images, to highlight anomalous areas classified as melanoma “defects” following the Allen–Spitz criteria. The adopted image vision diagnostic protocol was structured in the following steps: image acquisition by selecting the best zoom level of the microscope; preliminary selection of an image with a good resolution; preliminary identification of macro-areas of defect in each preselected image; identification of a class of a defect in the selected macro-area; training of the supervised machine learning FRF algorithm by selecting the micro-defect in the macro-area; execution of the FRF algorithm to find an image vision performance indicator; and analysis of the output images by enhancing lesion defects. The precision achieved by the FRF algorithm proved to be appropriate with a discordance of 17% with respect to the dermatopathologist, allowing this type of supervised algorithm to be nominated as a help to the dermatopathologist in the challenging diagnosis of malignant melanoma.

Characterization of multiple diagnostic terms in melanocytic skin lesion pathology reports

BACKGROUND

Histopathologically ambiguous melanocytic lesions lead some pathologists to list multiple diagnostic considerations in the pathology report. The frequency and circumstance of multiple diagnostic considerations remain poorly characterized.

METHODS

Two hundred and forty skin biopsy samples were interpreted by 187 pathologists (8976 independent diagnoses) and classified according to a diagnostic/treatment stratification (MPATH-Dx).

RESULTS

Multiple diagnoses in different MPATH-Dx classes were used in n = 1320 (14.7%) interpretations, with 97% of pathologists and 91% of cases having at least one such interpretation. Multiple diagnoses were more common for intermediate risk lesions and are associated with greater subjective difficulty and lower confidence. We estimate that 6% of pathology reports for melanocytic lesions in the United States contain two diagnoses of different MPATH-Dx prognostic classes, and 2% of cases are given two diagnoses with significant treatment implications.

CONCLUSIONS

Difficult melanocytic diagnoses in skin may necessitate multiple diagnostic considerations; however, as patients increasingly access their health records and retrieve pathology reports (as mandated by US law), uncertainty should be expressed unambiguously.

Artificial Intelligence in Dermatopathology: New Insights and Perspectives

In recent years, an increasing enthusiasm has been observed towards artificial intelligence and machine learning, involving different areas of medicine. Among these, although still in the embryonic stage, the dermatopathological field has also been partially involved, with the attempt to develop and train algorithms that could assist the pathologist in the differential diagnosis of complex melanocytic lesions. In this article, we face this new challenge of the modern era, carry out a review of the literature regarding the state of the art and try to determine promising future perspectives.

Multiplexed Immunohistochemistry and Digital Pathology as the Foundation for Next-Generation Pathology in Melanoma: Methodological Comparison and Future Clinical Applications

The state-of-the-art for melanoma treatment has recently witnessed an enormous revolution, evolving from a chemotherapeutic, "one-drug-for-all" approach, to a tailored molecular- and immunological-based approach with the potential to make personalized therapy a reality. Nevertheless, methods still have to improve a lot before these can reliably characterize all the tumoral features that make each patient unique. While the clinical introduction of next-generation sequencing has made it possible to match mutational profiles to specific targeted therapies, improving response rates to immunotherapy will similarly require a deep understanding of the immune microenvironment and the specific contribution of each component in a patient-specific way. Recent advancements in artificial intelligence and single-cell profiling of resected tumor samples are paving the way for this challenging task. In this review, we provide an overview of the state-of-the-art in artificial intelligence and multiplexed immunohistochemistry in pathology, and how these bear the potential to improve diagnostics and therapy matching in melanoma. A major asset of in-situ single-cell profiling methods is that these preserve the spatial distribution of the cells in the tissue, allowing researchers to not only determine the cellular composition of the tumoral microenvironment, but also study tissue sociology, making inferences about specific cell-cell interactions and visualizing distinctive cellular architectures - all features that have an impact on anti-tumoral response rates. Despite the many advantages, the introduction of these approaches requires the digitization of tissue slides and the development of standardized analysis pipelines which pose substantial challenges that need to be addressed before these can enter clinical routine.

Attitudes Toward Artificial Intelligence Within Dermatopathology: An International Online Survey

Background: Artificial intelligence (AI) has recently surfaced as a research topic in dermatology and dermatopathology. In a recent survey, dermatologists were overall positive toward a development with an increased use of AI, but little is known about the corresponding attitudes among pathologists working with dermatopathology. The objective of this investigation was to make an inventory of these attitudes.

Participants and Methods: An anonymous and voluntary online survey was prepared and distributed to pathologists who regularly analyzed dermatopathology slides/images. The survey consisted of 39 question divided in five sections; (1) AI as a topic in pathology; (2) previous exposure to AI as a topic in general; (3) applications for AI in dermatopathology; (4) feelings and attitudes toward AI and (5) self-reported tech-savviness and demographics. The survey opened on March 13, 2020 and closed on May 5, 2020.

Results: Overall, 718 responders (64.1% females) representing 91 countries were analyzed. While 81.5% of responders were aware of AI as an emerging topic in pathology, only 18.8% had either good or excellent knowledge about AI. In terms of diagnosis classification, 42.6% saw strong or very strong potential for automated suggestion of skin tumor diagnoses. The corresponding figure for inflammatory skin diseases was 23.0% (P_adj < 0.0001). For specific applications, the highest potential was considered for automated detection of mitosis (79.2%), automated suggestion of tumor margins (62.1%) and immunostaining evaluation (62.7%). The potential for automated suggestion of immunostaining (37.6%) and genetic panels (48.3%) were lower. Age did not impact the overall attitudes toward AI. Only 6.0% of the responders agreed or strongly agreed that the human pathologist will be replaced by AI in the foreseeable future. For the entire group, 72.3% agreed or strongly agreed that AI will improve dermatopathology and 84.1% thought that AI should be a part of medical training.

Conclusions: Pathologists are generally optimistic about the impact and potential benefit of AI in dermatopathology. The highest potential is expected for narrow specified tasks rather than a global automated suggestion of diagnoses. There is a strong need for education about AI and its use within dermatopathology.

Pathologists' agreement on treatment suggestions for melanocytic skin lesions

BACKGROUND

Although treatment guidelines exist for melanoma in situ and invasive melanoma, guidelines for other melanocytic skin lesions do not exist.

OBJECTIVE

To examine pathologists' treatment suggestions for a broad spectrum of melanocytic skin lesions and compare them with existing guidelines.

METHODS

Pathologists (N = 187) completed a survey and then provided diagnoses and treatment suggestions for 240 melanocytic skin lesions. Physician characteristics associated with treatment suggestions were evaluated with multivariable modeling.

RESULTS

Treatment suggestions were concordant with National Comprehensive Cancer Network guidelines for the majority of cases interpreted as melanoma in situ (73%) and invasive melanoma (86%). Greater variability of treatment suggestions was seen for other lesion types without existing treatment guidelines. Characteristics associated with provision of treatment suggestions discordant with National Comprehensive Cancer Network guidelines were low caseloads (invasive melanoma), lack of fellowship training or board certification (melanoma in situ), and more than 10 years of experience (invasive melanoma and melanoma in situ).

LIMITATIONS

Pathologists could not perform immunohistochemical staining or other diagnostic tests; only 1 glass side was provided per biopsy case.

CONCLUSIONS

Pathologists' treatment suggestions vary significantly for melanocytic lesions, with lower variability for lesion types with national guidelines. Results suggest the need for standardization of treatment guidelines for all melanocytic lesion types.

Validation of Whole-slide Digitally Imaged Melanocytic Lesions: Does Z-Stack Scanning Improve Diagnostic Accuracy?

Background

Accurate diagnosis of melanocytic lesions is challenging, even for expert pathologists. Nowadays, whole-slide imaging (WSI) is used for routine clinical pathology diagnosis in several laboratories. One of the limitations of WSI, as it is most often used, is the lack of a multiplanar focusing option. In this study, we aim to establish the diagnostic accuracy of WSI for melanocytic lesions and investigate the potential accuracy increase of z-stack scanning. Z-stack enables pathologists to use a software focus adjustment, comparable to the fine-focus knob of a conventional light microscope.

Materials and Methods

Melanocytic lesions (n = 102) were selected from our pathology archives: 35 nevi, 5 spitzoid tumors of unknown malignant potential, and 62 malignant melanomas, including 10 nevoid melanomas. All slides were scanned at a magnification comparable to use of a ×40 objective, in z-stack mode. A ground truth diagnosis was established on the glass slides by four academic dermatopathologists with a special interest in the diagnosis of melanoma. Six nonacademic surgical pathologists subspecialized in dermatopathology examined the cases by WSI.

Results

An expert consensus diagnosis was achieved in 99 (97%) of cases. Concordance rates between surgical pathologists and the ground truth varied between 75% and 90%, excluding nevoid melanoma cases. Concordance rates of nevoid melanoma varied between 10% and 80%. Pathologists used the software focusing option in 7%-28% of cases, which in 1 case of nevoid melanoma resulted in correcting a misdiagnosis after finding a dermal mitosis.

Conclusion

Diagnostic accuracy of melanocytic lesions based on glass slides and WSI is comparable with previous publications. A large variability in diagnostic accuracy of nevoid melanoma does exist. Our results show that z-stack scanning, in general, does not increase the diagnostic accuracy of melanocytic.

Pathologist characteristics associated with accuracy and reproducibility of melanocytic skin lesion interpretation

BACKGROUND

Diagnostic interpretations of melanocytic skin lesions vary widely among pathologists, yet the underlying reasons remain unclear.

OBJECTIVE

Identify pathologist characteristics associated with rates of accuracy and reproducibility.

METHODS

Pathologists independently interpreted the same set of biopsy specimens from melanocytic lesions on 2 occasions. Diagnoses were categorized into 1 of 5 classes according to the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis system. Reproducibility was determined by pathologists' concordance of diagnoses across 2 occasions. Accuracy was defined by concordance with a consensus reference standard. Associations of pathologist characteristics with reproducibility and accuracy were assessed individually and in multivariable logistic regression models.

RESULTS

Rates of diagnostic reproducibility and accuracy were highest among pathologists with board certification and/or fellowship training in dermatopathology and in those with 5 or more years of experience. In addition, accuracy was high among pathologists with a higher proportion of melanocytic lesions in their caseload composition and higher volume of melanocytic lesions.

LIMITATIONS

Data gathered in a test set situation by using a classification tool not currently in clinical use.

CONCLUSION

Diagnoses are more accurate among pathologists with specialty training and those with more experience interpreting melanocytic lesions. These findings support the practice of referring difficult cases to more experienced pathologists to improve diagnostic accuracy, although the impact of these referrals on patient outcomes requires additional research.

Pathologists' Use of Second Opinions in Interpretation of Melanocytic Cutaneous Lesions: Policies, Practices, and Perceptions

BACKGROUND

Research examining the role of second opinions in pathology for diagnosis of melanocytic lesions is limited.

OBJECTIVE

To assess current laboratory policies, clinical use of second opinions, and pathologists' perceptions of second opinions for melanocytic lesions.

MATERIALS AND METHODS

Cross-sectional data collected from 207 pathologists in 10 US states who diagnose melanocytic lesions. The web-based survey ascertained pathologists' professional information, laboratory second opinion policy, use of second opinions, and perceptions of second opinion value for melanocytic lesions.

RESULTS

Laboratory policies required second opinions for 31% of pathologists and most commonly required for melanoma in situ (26%) and invasive melanoma (30%). In practice, most pathologists reported requesting second opinions for melanocytic tumors of uncertain malignant potential (85%) and atypical Spitzoid lesions (88%). Most pathologists perceived that second opinions increased interpretive accuracy (78%) and protected them from malpractice lawsuits (62%).

CONCLUSION

Use of second opinions in clinical practice is greater than that required by laboratory policies, especially for melanocytic tumors of uncertain malignant potential and atypical Spitzoid lesions. Quality of care in surgical interventions for atypical melanocytic proliferations critically depends on the accuracy of diagnosis in pathology reporting. Future research should examine the extent to which second opinions improve accuracy of melanocytic lesion diagnosis.

Daily Biopsy Diagnosis in Surgical Pathology: Concordance Between Light Microscopy and Whole-Slide Imaging in Real-Life Conditions

OBJECTIVES

The current challenge for the various digital whole-slide imaging (WSI) systems is to be definitively validated for diagnostic purposes. We designed a concordance study between glass slide and digital slide diagnosis in real-life conditions, coupled with an ergonomic study.

METHODS

Three senior pathologists evaluated, first in glass slides and then in digital slides, 119 biopsy cases, including 749 slides, with 332 H&E saffron stains and 417 additional techniques, mainly immunohistochemistry.

RESULTS

All digital slides, including specially stained slides, were interpretable. Concordance between glass slides and digital slides was observed in 87.4% of cases. Minor discordances were observed in 12 (10.1%) cases and major discordances, with therapeutic impact, in three (2.5%), including one related to WSI. The satisfaction of participants was high and increased with time.

CONCLUSIONS

Our study confirms the feasibility and accuracy of WSI diagnosis, even for cases having multiple samples and requiring special staining techniques, such as immunohistochemistry and in situ hybridization.

Pathologists' diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study

Objective To quantify the accuracy and reproducibility of pathologists' diagnoses of melanocytic skin lesions.Design Observer accuracy and reproducibility study.Setting 10 US states.Participants Skin biopsy cases (n=240), grouped into sets of 36 or 48. Pathologists from 10 US states were randomized to independently interpret the same set on two occasions (phases 1 and 2), at least eight months apart.Main outcome measures Pathologists' interpretations were condensed into five classes: I (eg, nevus or mild atypia); II (eg, moderate atypia); III (eg, severe atypia or melanoma in situ); IV (eg, pathologic stage T1a (pT1a) early invasive melanoma); and V (eg, ≥pT1b invasive melanoma). Reproducibility was assessed by intraobserver and interobserver concordance rates, and accuracy by concordance with three reference diagnoses.Results In phase 1, 187 pathologists completed 8976 independent case interpretations resulting in an average of 10 (SD 4) different diagnostic terms applied to each case. Among pathologists interpreting the same cases in both phases, when pathologists diagnosed a case as class I or class V during phase 1, they gave the same diagnosis in phase 2 for the majority of cases (class I 76.7%; class V 82.6%). However, the intraobserver reproducibility was lower for cases interpreted as class II (35.2%), class III (59.5%), and class IV (63.2%). Average interobserver concordance rates were lower, but with similar trends. Accuracy using a consensus diagnosis of experienced pathologists as reference varied by class: I, 92% (95% confidence interval 90% to 94%); II, 25% (22% to 28%); III, 40% (37% to 44%); IV, 43% (39% to 46%); and V, 72% (69% to 75%). It is estimated that at a population level, 82.8% (81.0% to 84.5%) of melanocytic skin biopsy diagnoses would have their diagnosis verified if reviewed by a consensus reference panel of experienced pathologists, with 8.0% (6.2% to 9.9%) of cases overinterpreted by the initial pathologist and 9.2% (8.8% to 9.6%) underinterpreted.Conclusion Diagnoses spanning moderately dysplastic nevi to early stage invasive melanoma were neither reproducible nor accurate in this large study of pathologists in the USA. Efforts to improve clinical practice should include using a standardized classification system, acknowledging uncertainty in pathology reports, and developing tools such as molecular markers to support pathologists' visual assessments.

RecutClub.com: An Open Source, Whole Slide Image-based Pathology Education System

BACKGROUND

Our institution's pathology unknown conferences provide educational cases for our residents. However, the cases have not been previously available digitally, have not been collated for postconference review, and were not accessible to a wider audience. Our objective was to create an inexpensive whole slide image (WSI) education suite to address these limitations and improve the education of pathology trainees.

MATERIALS AND METHODS

We surveyed residents regarding their preference between four unique WSI systems. We then scanned weekly unknown conference cases and study set cases and uploaded them to our custom built WSI viewer located at RecutClub.com. We measured site utilization and conference participation.

RESULTS

Residents preferred our OpenLayers WSI implementation to Ventana Virtuoso, Google Maps API, and OpenSlide. Over 16 months, we uploaded 1366 cases from 77 conferences and ten study sets, occupying 793.5 GB of cloud storage. Based on resident evaluations, the interface was easy to use and demonstrated minimal latency. Residents are able to review cases from home and from their mobile devices. Worldwide, 955 unique IP addresses from 52 countries have viewed cases in our site.

CONCLUSIONS

We implemented a low-cost, publicly available repository of WSI slides for resident education. Our trainees are very satisfied with the freedom to preview either the glass slides or WSI and review the WSI postconference. Both local users and worldwide users actively and repeatedly view cases in our study set.

Variation among pathologists' treatment suggestions for melanocytic lesions: A survey of pathologists

BACKGROUND

The extent of variability in treatment suggestions for melanocytic lesions made by pathologists is unknown.

OBJECTIVE

We investigated how often pathologists rendered suggestions, reasons for providing suggestions, and concordance with national guidelines.

METHODS

We conducted a cross-sectional survey of pathologists. Data included physician characteristics, experience, and treatment recommendation practices.

RESULTS

Of 301 pathologists, 207 (69%) from 10 states (California, Connecticut, Hawaii, Iowa, Kentucky, Louisiana, New Jersey, New Mexico, Utah, and Washington) enrolled. In all, 15% and 7% reported never and always including suggestions, respectively. Reasons for offering suggestions included improved care (79%), clarification (68%), and legal liability (39%). Reasons for not offering suggestions included referring physician preference (48%), lack of clinical information (44%), and expertise (29%). Training and caseload were associated with offering suggestions (P < .05). Physician suggestions were most consistent for mild/moderate dysplastic nevi and melanoma. For melanoma in situ, 18 (9%) and 32 (15%) pathologists made suggestions that undertreated or overtreated lesions based on National Comprehensive Cancer Network (NCCN) guidelines, respectively. For invasive melanoma, 14 (7%) pathologists made treatment suggestions that undertreated lesions based on NCCN guidelines.

LIMITATIONS

Treatment suggestions were self-reported.

CONCLUSIONS

Pathologists made recommendations ranging in consistency. These findings may inform efforts to reduce treatment variability and optimize patterns of care delivery for patients.

The self-reported use of immunostains and cytogenetic testing in the diagnosis of melanoma by practicing U.S. pathologists of 10 selected states

BACKGROUNDS

The diagnosis of melanoma can be challenging, especially in lesions for which the histopathologic criteria bridge two or more taxonomic categories. Newer genomic analytical methods of fluorescence in situ hybridization (FISH) and comparative genomic hybridization (CGH) have been introduced as ancillary techniques to differentiate benign and malignant melanocytic proliferations.

METHODS

We evaluated how pathologists perceive and are incorporating these new cytogenetic testing technologies into their practices. We conducted a study of 207 U.S. pathologists who interpret melanocytic lesions in clinical practice in 10 SEER states. Pathologists were surveyed regarding perceptions and utilization of FISH and/or CGH in their clinical practices.

RESULTS

Results showed that 38% of pathologists use FISH and/or CGH in interpreting melanocytic lesions. Pathologists reporting FISH and/or CGH use were significantly younger (p < 0.05), were fellowship trained or board certified in dermatopathology (p < 0.001) and were affiliated with an academic institute (p < 0.001). Pathologists reporting that their colleagues consider them an expert in the assessment of melanocytic lesions were more likely to employ FISH and/or CGH in their practices than non-experts.

CONCLUSIONS

Early users of cytogenetic testing technologies in cutaneous pathology are more likely to be younger, affiliated with an academic institution and fellowship trained or board certified in dermatopathology.