Artificial intelligence algorithms and 3D volumetric rendering for basal cell carcinoma detection and tumor depth assessment in RCM-OCT images: a pilot study.

The Reflectance Confocal Microscopy - Optical Coherence Tomography (RCM-OCT) device has shown utility in detecting and assessing depth of basal cell carcinoma (BCC) in vivo but is challenging for novices to interpret. Artificial intelligence (AI) applied to RCM-OCT could aid readers. We trained artificial intelligence (AI) models, using OCT rasters of biopsy-confirmed BCC, to detect and create 3D BCC rendering and automatically measure tumor depth. Trained AI models were applied to a separate test set containing rasters of BCC, benign lesions, and normal skin. Blinded reader analysis and tumor depth correlation with histopathology were conducted. BCC detection improved from viewing OCT rasters only (sensitivity 73.3%, specificity 45.5%) to viewing rasters with AI-generated BCC rendering (sensitivity 86.7%, specificity 48.5%). A Pearson Correlation r2 = 0.59 (p=0.02) was achieved for the tumor depth measurement between AI and histologic measured depths. Thus, addition of AI to the RCM-OCT device may expand its utility widely.

High-resolution full-field optical coherence tomography microscope for the evaluation of freshly excised skin specimens during Mohs surgery: A feasibility study.

Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution and potentially facilitates evaluation. Here, we define FF-OCT features of normal and neoplastic skin lesions in fresh ex vivo tissues and assess its diagnostic accuracy for malignancies. For this, normal and neoplastic tissues were obtained from Mohs surgery, imaged using FF-OCT, and their features were described. Two expert OCT readers conducted a blinded analysis to evaluate their diagnostic accuracies, using histopathology as the ground truth. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 basal cell carcinomas [BCCs] and 17 squamous cell carcinomas [SCCs]). The average reader diagnostic accuracy was 88.1%, with a sensitivity of 93.7%, and a specificity of 58.3%. The artificial intelligence (AI) model achieved a diagnostic accuracy of 87.6 ± 5.9%, sensitivity of 93.2 ± 2.1%, and specificity of 81.2 ± 9.2%. A mean intersection-over-union of 60.3 ± 10.1% was achieved when delineating the nodular BCC from normal structures. Limitation of the study was the small sample size for all tumors, especially SCCs. However, based on our preliminary results, we envision FF-OCT to rapidly image fresh tissues, facilitating surgical margin assessment. AI algorithms can aid in automated tumor detection, enabling widespread adoption of this technique.

Training With Uncertain Annotations for Semantic Segmentation of Basal Cell Carcinoma From Full-Field OCT Images.

Semantic segmentation of basal cell carcinoma (BCC) from full-field optical coherence tomography (FF-OCT) images of human skin has received considerable attention in medical imaging. However, it is challenging for dermatopathologists to annotate the training data due to OCT's lack of color specificity. Very often, they are uncertain about the correctness of the annotations they made. In practice, annotations fraught with uncertainty profoundly impact the effectiveness of model training and hence the performance of BCC segmentation. To address this issue, we propose an approach to model training with uncertain annotations. The proposed approach includes a data selection strategy to mitigate the uncertainty of training data, a class expansion to consider sebaceous gland and hair follicle as additional classes to enhance the performance of BCC segmentation, and a self-supervised pre-training procedure to improve the initial weights of the segmentation model parameters. Furthermore, we develop three post-processing techniques to reduce the impact of speckle noise and image discontinuities on BCC segmentation. The mean Dice score of BCC of our model reaches 0.503±0.003, which, to the best of our knowledge, is the best performance to date for semantic segmentation of BCC from FF-OCT images.

Lentigo maligna melanoma mapping using reflectance confocal microscopy correlates with staged excision: A prospective study.

BACKGROUND: Lentigo maligna/lentigo maligna melanoma (LM/LMM) can present with subclinical extension that may be difficult to define preoperatively and lead to incomplete excision and potential recurrence. Preliminarily studies have used reflectance confocal microscopy (RCM) to assess LM/LMM margins. OBJECTIVE: To evaluate the correlation of LM/LMM subclinical extension defined by RCM compared with the gold standard histopathology. METHODS: Prospective study of LM/LMM patients referred for dermatologic surgery. RCM was performed at the clinically defined initial surgical margin followed by margin-controlled staged excision with paraffin-embedded tissue, and histopathology was correlated with RCM results. RESULTS: Seventy-two patients were included. Mean age was 66.8 years (standard deviation, 11.1; range, 38-89); 69.4% were men. Seventy of 72 lesions (97.2%) were located on the head and neck with mean largest clinical diameter of 1.3 cm (range, 0.3-5). Diagnostic accuracy for detection of residual melanoma in the tumor debulk (after biopsy) had a sensitivity of 96.7% and a specificity of 66.7% when compared with histopathology. RCM margin assessment revealed an overall agreement with final histopathology of 85.9% (κ = 0.71; P < .001). LIMITATIONS: No RCM imaging beyond initial planned margins was performed. CONCLUSION: RCM showed moderate to excellent overall agreement between RCM imaging of LM/LMM and histopathology of staged excision margins.

Tertiary lymphoid structures accompanied by fibrillary matrix morphology impact anti-tumor immunity in basal cell carcinomas.

Tertiary lymphoid structures (TLS) are specialized lymphoid formations that serve as local repertoire of T- and B-cells at sites of chronic inflammation, autoimmunity, and cancer. While presence of TLS has been associated with improved response to immune checkpoint blockade therapies and overall outcomes in several cancers, its prognostic value in basal cell carcinoma (BCC) has not been investigated. Herein, we determined the prognostic impact of TLS by relating its prevalence and maturation with outcome measures of anti-tumor immunity, namely tumor infiltrating lymphocytes (TILs) and tumor killing. In 30 distinct BCCs, we show the presence of TLS was significantly enriched in tumors harboring a nodular component and more mature primary TLS was associated with TIL counts. Moreover, assessment of the fibrillary matrix surrounding tumors showed discrete morphologies significantly associated with higher TIL counts, critically accounting for heterogeneity in TIL count distribution within TLS maturation stages. Specifically, increased length of fibers and lacunarity of the matrix with concomitant reduction in density and alignment of fibers were present surrounding tumors displaying high TIL counts. Given the interest in inducing TLS formation as a therapeutic intervention as well as its documented prognostic value, elucidating potential impediments to the ability of TLS in driving anti-tumor immunity within the tumor microenvironment warrants further investigation. These results begin to address and highlight the need to integrate stromal features which may present a hindrance to TLS formation and/or effective function as a mediator of immunotherapy response.

In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response.

Response to immunotherapies can be variable and unpredictable. Pathology-based phenotyping of tumors into 'hot' and 'cold' is static, relying solely on T-cell infiltration in single-time single-site biopsies, resulting in suboptimal treatment response prediction. Dynamic vascular events (tumor angiogenesis, leukocyte trafficking) within tumor immune microenvironment (TiME) also influence anti-tumor immunity and treatment response. Here, we report dynamic cellular-level TiME phenotyping in vivo that combines inflammation profiles with vascular features through non-invasive reflectance confocal microscopic imaging. In skin cancer patients, we demonstrate three main TiME phenotypes that correlate with gene and protein expression, and response to toll-like receptor agonist immune-therapy. Notably, phenotypes with high inflammation associate with immunostimulatory signatures and those with high vasculature with angiogenic and endothelial anergy signatures. Moreover, phenotypes with high inflammation and low vasculature demonstrate the best treatment response. This non-invasive in vivo phenotyping approach integrating dynamic vasculature with inflammation serves as a reliable predictor of response to topical immune-therapy in patients.

Combined PARP1-Targeted Nuclear Contrast and Reflectance Contrast Enhance Confocal Microscopic Detection of Basal Cell Carcinoma.

Reflectance confocal microscopy (RCM) with endogenous backscattered contrast can noninvasively image basal cell carcinomas (BCCs) in skin. However, BCCs present with high nuclear density, and the relatively weak backscattering from nuclei imposes a fundamental limit on contrast, detectability, and diagnostic accuracy. We investigated PARPi-FL, an exogenous nuclear poly(adenosine diphosphate ribose) polymerase (PARP1)-targeted fluorescent contrast agent, and fluorescence confocal microscopy toward improving BCC diagnosis. Methods: We tested PARP1 expression in 95 BCC tissues using immunohistochemistry, followed by PARPi-FL staining in 32 fresh surgical BCC specimens. The diagnostic accuracy of PARPi-FL contrast was evaluated in 83 surgical specimens. The optimal parameters for permeability of PARPi-FL through intact skin was tested ex vivo on 5 human skin specimens and in vivo in 3 adult Yorkshire pigs. Results: We found significantly higher PARP1 expression and PARPi-FL binding in BCCs than in normal skin structures. Blinded reading of RCM-and-fluorescence confocal microscopy images by 2 experts demonstrated a higher diagnostic accuracy for BCCs with combined fluorescence and reflectance contrast than for RCM alone. Optimal parameters (time and concentration) for PARPi-FL transepidermal permeation through intact skin were successfully determined. Conclusion: Combined fluorescence and reflectance contrast may improve noninvasive BCC diagnosis with confocal microscopy.

Classification of Basal Cell Carcinoma in Ex Vivo Confocal Microscopy Images from Freshly Excised Tissues Using a Deep Learning Algorithm.

Ex vivo confocal microscopy (EVCM) generates digitally colored purple-pink images similar to H&E without time-consuming tissue processing. It can be used during Mohs surgery for rapid detection of basal cell carcinoma (BCC); however, reading EVCM images requires specialized training. An automated approach using a deep learning algorithm for BCC detection in EVCM images can aid in diagnosis. A total of 40 BCCs and 28 negative (not-BCC) samples were collected at Memorial Sloan Kettering Cancer Center to create three training datasets: (i) EVCM image dataset (663 images), (ii) H&E image dataset (516 images), and (iii) a combination of the two datasets. A total of seven BCCs and four negative samples were collected to create an EVCM test dataset (107 images). The model trained with the EVCM dataset achieved 92% diagnostic accuracy, similar to the H&E model (93%). The area under the receiver operator characteristic curve was 0.94, 0.95, and 0.94 for EVCM-, H&E-, and combination-trained models, respectively. We developed an algorithm for automatic BCC detection in EVCM images (comparable accuracy to dermatologists). This approach could be used to assist with BCC detection during Mohs surgery. Furthermore, we found that a model trained with only H&E images (which are more available than EVCM images) can accurately detect BCC in EVCM images.

In vivo optical imaging-guided targeted sampling for precise diagnosis and molecular pathology.

Conventional tissue sampling can lead to misdiagnoses and repeated biopsies. Additionally, tissue processed for histopathology suffers from poor nucleic acid quality and/or quantity for downstream molecular profiling. Targeted micro-sampling of tissue can ensure accurate diagnosis and molecular profiling in the presence of spatial heterogeneity, especially in tumors, and facilitate acquisition of fresh tissue for molecular analysis. In this study, we explored the feasibility of performing 1-2 mm precision biopsies guided by high-resolution reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), and reflective metallic grids for accurate spatial targeting. Accurate sampling was confirmed with either histopathology or molecular profiling through next generation sequencing (NGS) in 9 skin cancers in 7 patients. Imaging-guided 1-2 mm biopsies enabled spatial targeting for in vivo diagnosis, feature correlation and depth assessment, which were confirmed with histopathology. In vivo 1-mm targeted biopsies achieved adequate quantity and high quality of DNA for next-generation sequencing. Subsequent mutational profiling was confirmed on 1 melanoma in situ and 2 invasive melanomas, using a 505-gene mutational panel called Memorial Sloan Kettering-Integrated mutational profiling of actionable cancer targets (MSK-IMPACT). Differential mutational landscapes, in terms of number and types of mutations, were found between invasive and in situ melanomas in a single patient. Our findings demonstrate feasibility of accurate sampling of regions of interest for downstream histopathological diagnoses and molecular pathology in both in vivo and ex vivo settings with broad diagnostic, therapeutic and research potential in cutaneous diseases accessible by RCM-OCT imaging.

Optical imaging guided- 'precision' biopsy of skin tumors: a novel approach for targeted sampling and histopathologic correlation.

Dermoscopy and reflectance confocal microscopy (RCM) are two noninvasive, optical imaging tools used to facilitate clinical diagnosis. A biopsy technique that produces exact correlation with optical imaging features is not previously reported. To evaluate the applications of a novel feature-focused 'precision biopsy' technique that correlates clinical-dermoscopy-RCM findings with histopathology. This was a prospective case-series performed during August 2017 and June 2019 at a tertiary care cancer. We included consecutive patients requiring a precise dermoscopy-RCM-histopathologic correlation. We performed prebiopsy dermoscopy and both wide probe and handheld RCM of suspicious lesions. Features of interest were isolated with the aid of paper rings and a 2 mm punch biopsy was performed in the dermoscopy- or RCM-highlighted area. Tissue was processed either en face or with vertical sections. One-to-one correlation with histopathology was obtained. Twenty-three patients with 24 lesions were included in the study. The mean age was 64.6 years (range 22-91 years); there were 16 (69.6%) males, 14 (58.3%) lesions biopsied were on head and neck region. We achieved tissue-conservation diagnosis in 100% (24/24), 13 (54.2%) were clinically equivocal lesions, six (25%) were selected for 'feature correlation' of structures on dermoscopy or RCM, and five (20.8%) for 'correlation of new/unknown' RCM features seen on follow-up. The precision biopsy technique described herein is a novel method that facilitates direct histopathological correlation of dermoscopy and RCM features. With the aids of optical imaging devices, accurate diagnosis may be achieved by minimally invasive tissue extraction.

Angulated small nests and cords: Key diagnostic histopathologic features of infiltrative basal cell carcinoma can be identified using integrated reflectance confocal microscopy-optical coherence tomography.

BACKGROUND: Accurate basal cell carcinoma (BCC) subtyping is requisite for appropriate management, but non-representative sampling occurs in 18% to 25% of biopsies. By enabling non-invasive diagnosis and more comprehensive sampling, integrated reflectance confocal microscopy-optical coherence tomography (RCM-OCT) may improve the accuracy of BCC subtyping and subsequent management. We evaluated RCM-OCT images and histopathology slides for the presence of two key features, angulation and small nests and cords, and calculated (a) sensitivity and specificity of these features, combined and individually, for identifying an infiltrative BCC subtype and (b) agreement across modalities. METHODS: Thirty-three RCM-OCT-imaged, histopathologically-proven BCCs (17 superficial and/or nodular; 16 containing an infiltrative component) were evaluated. RESULTS: The presence of angulation or small nests and cords was sufficient to identify infiltrative BCC on RCM-OCT with 100% sensitivity and 82% specificity, similar to histopathology (100% sensitivity, 88% specificity, kappa = 0.82). When both features were present, the sensitivity for identifying infiltrative BCC was 100% using either modality and specificity was 88% on RCM-OCT vs 94% on histopathology, indicating near-perfect agreement between non-invasive and invasive diagnostic modalities (kappa = 0.94). CONCLUSIONS: RCM-OCT can non-invasively identify key histopathologic features of infiltrative BCC offering a possible alternative to traditional invasive biopsy.

The potential utility of integrated reflectance confocal microscopy-optical coherence tomography for guiding triage and therapy of basal cell carcinomas.

The increasing rate of incidence and prevalence of basal cell carcinomas (BCCs) worldwide, combined with the morbidity associated with conventional surgical treatment has led to the development and use of alternative minimally invasive non-surgical treatments. Biopsy and pathology are used to guide BCC diagnosis and assess margins and subtypes, which then guide the decision and choice of surgical or non-surgical treatment. However, alternatively, a noninvasive optical approach based on combined reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) imaging may be used. Optical imaging may be used to guide diagnosis and margin assessment at the bedside, and potentially facilitate non-surgical management, along with long-term monitoring of treatment response. Noninvasive imaging may also complement minimally invasive treatments and help further reduce morbidity. In this paper, we highlight the current state of an integrated RCM/OCT imaging approach for diagnosis and triage of BCCs, as well as for assessing margins, which therefore may be ultimately used for guiding therapy.

A clinical and genetic study of early-onset and familial parkinsonism in taiwan: An integrated approach combining gene dosage analysis and next-generation sequencing.

BACKGROUND: Recent genetic progress has allowed for the molecular diagnosis of Parkinson's disease. However, genetic causes of PD vary widely in different ethnicities. Mutational frequencies and clinical phenotypes of genes associated with PD in Asian populations are largely unknown. The objective of this study was to identify the mutational frequencies and clinical spectrums of multiple PD-causative genes in a Taiwanese PD cohort. METHODS: A total of 571 participants including 324 patients with early-onset parkinsonism (onset age, <50 years) and 247 parkinsonism pedigrees were recruited at a tertiary referral center in Taiwan from 2002 to 2017. Genetic causes were identified by an integrated approach including gene dosage analysis, a targeted next-generation sequencing panel containing 40 known PD-causative genes, repeat-primed polymerase chain reaction, and whole-exome sequencing analysis. RESULTS: Thirty of the 324 patients with early-onset parkinsonism (9.3%) were found to carry mutations in Parkin, PINK1, or PLA2G6 or had increased trinucleotide repeats in SCA8. Twenty-nine of 109 probands with autosomal-recessive inheritance of parkinsonism (26.6%) were found to carry mutations in Parkin, PINK1, GBA, or HTRA2. The genetic causes for the 138 probands with an autosomal-dominant inheritance pattern of parkinsonism were more heterogeneous. Seventeen probands (12.3%) carried pathogenic mutations in LRRK2, VPS35, MAPT, GBA, DNAJC13, C9orf72, SCA3, or SCA17. A novel missense mutation in the UQCRC1 gene was found in a family with autosomal-dominant inheritance parkinsonism via whole-exome sequencing analysis. CONCLUSIONS: Our findings provide a better understanding of the genetic architecture of PD in eastern Asia and broaden the clinical spectrum of PD-causing mutations. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Topical Aluminum Chloride and Monsel's Solution Block Toluidine Blue Staining in Mohs Frozen Sections: Mechanism and Solution.

BACKGROUND: A diminished-staining artifact is observed in some Mohs frozen sections that are stained in toluidine blue (T-blue). Such an artifact, not yet described in the literature, may interfere with a Mohs surgeon's accurate reading. The authors hypothesize that topical hemostatic agents, aluminum chloride, and Monsel's solution are the causative factors. OBJECTIVE: To evaluate the aforementioned topical hemostatic agents as a potential cause of the nonstaining artifact, to propose the mechanism associated with this phenomenon, and to develop a method to prevent or rectify the problem. MATERIALS AND METHODS: Leftover Mohs frozen sections and specimens were treated with aluminum chloride or Monsel's solution and processed with routine Mohs histology. RESULTS: Nonstaining artifact is reproduced in aluminum chloride or Monsel's solution-treated ex vivo skin specimens. The authors found that ethylenediaminetetraacetic acid (EDTA), a chelating agent, can reverse the staining blockage. Such a finding suggests that aluminum or ferric cations bind to tissue and subsequently inhibit T-blue from interacting with the tissue. Direct binding of ferric cations to the tissue section is demonstrated with Prussian blue iron staining. CONCLUSION: By rinsing Mohs frozen sections in an EDTA solution before T-blue staining, the authors could prevent hemostatic agent-induced nonstaining. Applying an EDTA wash and restaining the slides can correct the same artifact.

Targeted Next-Generation Sequencing Facilitates Genetic Diagnosis and Provides Novel Pathogenetic Insights into Deafness with Enlarged Vestibular Aqueduct.

Enlarged vestibular aqueduct (EVA) is an inner-ear malformation associated with sensorineural hearing impairment. Most EVAs are associated with Pendred syndrome and nonsyndromic autosomal recessive deafness-4 (DFNB4), two autosomal-recessive disorders caused by mutations in SLC26A4. However, many EVA patients cannot have a confirmed diagnosis by screening common SLC26A4 mutations, constituting an enigma in genetic diagnosis. To enable comprehensive genetic examination and explore the etiologies of EVA, we designed a next-generation sequencing panel targeting the entire length of 3 Pendred syndrome/DFNB4 genes (SLC26A4, FOXI1, and KCNJ10) and exons of 10 other genes related to EVA and performed genetic testing in 50 EVA families without confirmative results on screening for SLC26A4 hotspots (c.919-2A>G and p.H723R). Bi-allelic SLC26A4 mutations were identified in 34 families and EYA1 mutations in two families, yielding a diagnostic rate of 72% (36 of 50). In addition, two variants were identified in KCNJ10 and FOXI1, but findings did not support the previous hypothesis that mutations in these two genes are probable contributors to EVA through recessive inheritance or digenic inheritance with SLC26A4. Of note, a large SLC26A4 deletion was confirmed in one step using our panel. These results show the utility of a next-generation sequencing-based panel to address EVA families by identifying various types of gene mutations with satisfactory diagnostic yields and provide novel insights into the pathogenesis of EVA.

Identification of a novel LDLR disease-causing variant using capture-based next-generation sequencing screening of familial hypercholesterolemia patients in Taiwan.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is an autosomal dominant disorder with paramount health impacts. However, less than 1% FH patients in Taiwan were formally diagnosed, partly due to the lack of reliable cost-effective genetic testing. We aimed at using a next-generation sequencing (NGS) platform as the clinical genetic testing method for FH. METHODS: We designed probes to capture the whole LDLR gene and all coding sequences of APOB and PCSK9, and then sequenced with Illumina MiSeq platform (2 × 300 bps). The entire pipeline was tested on 13 DNA samples with known causative variants (including 3 large duplications and 2 large deletions). Then we enrolled a new cohort of 28 unrelated FH patients with Dutch Lipid Clinic Network score ≥5. Relatives were included in the cascade screening. RESULTS: From the 13 DNA samples, we correctly identify all the variants, including big duplications and deletions. From the new cohort, we identified the causative variants in 21 of the 28 unrelated probands; five of them carrying a novel splice site variant c.1186+2T>G in LDLR. Among the family members, the concentration of LDL cholesterol was 7.82 ±â€¯2.13 mmol/l in LDLR c.1186+2T>G carrier group (n = 26), and was significantly higher than 3.18 ± 1.36 mmol/l in the non-carrier group (n = 25). CONCLUSIONS: This is the first capture-based NGS testing for FH to cover the whole LDLR genomic region, and therefore making reliable structural variation detection. This panel can comprehensively detect disease-causing variants in LDLR, APOB, and PCSK9 for FH patients.