A Prospective Double-Blinded Comparison of Reflectance Confocal Microscopy with Conventional Histopathology for In Vivo Assessment in Oral Cancer

PURPOSE

We investigated reflectance confocal microscopy (RCM) as a possible non-invasive approach for the diagnosis of cancer and real-time assessment of surgical margins.

PATIENTS AND METHODS

In a phase I study on 20 patients, we established the RCM imaging morphological features that distinguish OSCC from normal tissue with a newly developed intra-oral RCM probe. Our subsequent phase II prospective double-blinded study in 60 patients tested the diagnostic accuracy of RCM against histopathology. Five RCM videos from the tumor and five from normal surrounding mucosa were collected on each patient, followed by a 3-mm punch biopsy of the imaged area. An experienced RCM reader, who was blinded to biopsy location and histological diagnosis, examined the videos from both regions and classified each as "tumor" or "not-tumor" based on RCM features established in phase I. Hematoxylin and eosin slides from the biopsies were read by a pathologist who was blinded to RCM results. Using histology as the gold standard, we calculated the sensitivity and specificity of RCM.

RESULTS

We report a high agreement between the blinded readers (95% for normal tissue and 81.7% for tumors), high specificity (98.3%) and negative predictive values (96.6%) for normal tissue identification, and high sensitivity (90%) and positive predictive values (88.2%) for tumor detection.

CONCLUSIONS

RCM imaging is a promising technology for non-invasive in vivo diagnosis of OSCC and for real-time intraoperative evaluation of mucosal surgical margins. Its inherent constraint, however, stems from the diminished capability to evaluate structures located at more substantial depths within the tissue.

Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy

Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments.

Paradoxical effect of epinephrine on lesion redness and vascularity

INTRODUCTION

Epinephrine is commonly used in combination with local anesthetic (lidocaine/epinephrine) due to its beneficial vasoconstrictive properties. Typically, pallor is appreciated after injection as a sign of effect; however, we observed that some cutaneous malignancies paradoxically revealed increased redness and vascularity after injection of lidocaine/epinephrine. In this study, we investigate this phenomenon among a series of biopsied lesions to identify characteristics of lesions associated with increased redness and/or vascularity.

OBJECTIVES

To determine characteristics of lesions which become redder or more vascular after injection with lidocaine/epinephrine prior to biopsy.

METHODS

This cross-sectional study consisted of a convenience sample of lesions scheduled for biopsy. Lesions were photographed prior to and 7 min after injection of lidocaine/epinephrine as a part of standard care. Two readers blinded to study objectives and histopathological diagnosis assessed lesions for changes in redness and vascular features.

RESULTS

Fifty-four lesions from 47 patients-61.7% male, mean age 64.8 years, age-range 24-91 were included. Thirty-six lesions were biopsy confirmed malignant, with 5 in situ and 31 invasive malignancies; the remaining 18 lesions were benign. In comparison with non-malignant lesions, malignant lesions were associated with an increase in clinically appreciable vascular features after injection of lidocaine/epinephrine, X2 (1) = 21.600, p < 0.001. Further stratification into benign, in situ, and invasive lesions strengthened the association, X2 (1) = 23.272, p < 0.001.

CONCLUSIONS

Combination lidocaine/epinephrine has been shown to paradoxically increase the visibility of vessels seen in cutaneous malignancies. This is consistent with prior literature suggesting aberrant adrenergic signaling in neoangiogenic vessels.

Improving Artificial Intelligence-Based Diagnosis on Pediatric Skin Lesions

Artificial intelligence algorithms to classify melanoma are dependent on their training data, which limits generalizability. The objective of this study was to compare the performance of an artificial intelligence model trained on a standard adult-predominant dermoscopic dataset before and after the addition of additional pediatric training images. The performances were compared using held-out adult and pediatric test sets of images. We trained two models: one (model A) on an adult-predominant dataset (37,662 images from the International Skin Imaging Collaboration) and the other (model A+P) on an additional 1,536 pediatric images. We compared performance between the two models on adult and pediatric held-out test images separately using the area under the receiver operating characteristic curve. We then used Gradient-weighted Class Activation Maps and background skin masking to understand the contributions of the lesion versus background skin to algorithm decision making. Adding images from a pediatric population with different epidemiological and visual patterns to current reference standard datasets improved algorithm performance on pediatric images without diminishing performance on adult images. This suggests a way that dermatologic artificial intelligence models can be made more generalizable. The presence of background skin was important to the pediatric-specific improvement seen between models. Our study highlights the importance of carefully curated and labeled data from diverse inputs to improve the generalizability of AI models for dermatology, in this case applied to dermoscopic images of adult and pediatric lesions to improve melanoma detection.

Quantitative collagen analysis using second harmonic generation images for the detection of basal cell carcinoma with ex vivo multiphoton microscopy

Basal cell carcinoma (BCC) is the most common skin cancer, and its incidence is rising. Millions of benign biopsies are performed annually for BCC diagnosis, increasing morbidity, and healthcare costs. Non-invasive in vivo technologies such as multiphoton microscopy (MPM) can aid in diagnosing BCC, reducing the need for biopsies. Furthermore, the second harmonic generation (SHG) signal generated from MPM can classify and prognosticate cancers based on extracellular matrix changes, especially collagen type I. We explored the potential of MPM to differentiate collagen changes associated with different BCC subtypes compared to normal skin structures and benign lesions. Quantitative analysis such as frequency band energy analysis in Fourier domain, CurveAlign and CT-FIRE fibre analysis was performed on SHG images from 52 BCC and 12 benign lesions samples. Our results showed that collagen distribution is more aligned surrounding BCCs nests compared to the skin's normal structures (p < 0.001) and benign lesions (p < 0.001). Also, collagen was orientated more parallelly surrounding indolent BCC subtypes (superficial and nodular) versus those with more aggressive behaviour (infiltrative BCC) (p = 0.021). In conclusion, SHG signal from type I collagen can aid not only in the diagnosis of BCC but could be useful for prognosticating these tumors. Our initial results are limited to a small number of samples, requiring large-scale studies to validate them. These findings represent the groundwork for future in vivo MPM for diagnosis and prognosis of BCC.

Self-supervised denoising of Nyquist-sampled volumetric images via deep learning

Purpose

Deep learning has demonstrated excellent performance enhancing noisy or degraded biomedical images. However, many of these models require access to a noise-free version of the images to provide supervision during training, which limits their utility. Here, we develop an algorithm (noise2Nyquist) that leverages the fact that Nyquist sampling provides guarantees about the maximum difference between adjacent slices in a volumetric image, which allows denoising to be performed without access to clean images. We aim to show that our method is more broadly applicable and more effective than other self-supervised denoising algorithms on real biomedical images, and provides comparable performance to algorithms that need clean images during training.

Approach

We first provide a theoretical analysis of noise2Nyquist and an upper bound for denoising error based on sampling rate. We go on to demonstrate its effectiveness in denoising in a simulated example as well as real fluorescence confocal microscopy, computed tomography, and optical coherence tomography images.

Results

We find that our method has better denoising performance than existing self-supervised methods and is applicable to datasets where clean versions are not available. Our method resulted in peak signal to noise ratio (PSNR) within 1 dB and structural similarity (SSIM) index within 0.02 of supervised methods. On medical images, it outperforms existing self-supervised methods by an average of 3 dB in PSNR and 0.1 in SSIM.

Conclusion

noise2Nyquist can be used to denoise any volumetric dataset sampled at at least the Nyquist rate making it useful for a wide variety of existing datasets.

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.

Analyzing the Spatial Randomness in the Distribution of Acquired Melanocytic Neoplasms

On the basis of the clinical impression and current knowledge, acquired melanocytic nevi and melanomas may not occur in random localizations. The goal of this study was to identify whether their distribution on the back is random and whether the location of melanoma correlates with its adjacent lesions. Therefore, patient-level and lesion-level spatial analyses were performed using the Clark‒Evans test for complete spatial randomness. A total of 311 patients with three-dimensional total body photography (average age of 40.08 [30‒49] years; male/female ratio: 128/183) with 5,108 eligible lesions in total were included in the study (mean sum of eligible lesions per patient of 16.42 [3‒199]). The patient-level analysis revealed that the distributions of acquired melanocytic neoplasms were more likely to deviate toward clustering than dispersion (average z-score of ‒0.55 [95% confidence interval = ‒0.69 to ‒0.41; P < 0.001]). The lesion-level analysis indicated a higher portion of melanomas (n = 57 of 72, 79.2% [95% confidence interval = 69.4‒88.9%]) appearing in proximity to neighboring melanocytic neoplasms than to nevi (n = 2,281 of 5,036, 45.3% [95% confidence interval = 43.9‒46.7%]). In conclusion, the nevi and melanomas' distribution on the back tends toward clustering as opposed to dispersion. Furthermore, melanomas are more likely to appear proximally to their neighboring neoplasms than to nevi. These findings may justify various oncogenic theories and improve diagnostic methodology.

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.

Standard assessment of immune infiltration of biopsies is not sufficient to accurately predict response to immunotherapy. Here, the authors show that reflectance confocal microscopy can be used to quantify dynamic vasculature and inflammatory features to better predict treatment response in skin cancers.

Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group

IMPORTANCE

The use of artificial intelligence (AI) is accelerating in all aspects of medicine and has the potential to transform clinical care and dermatology workflows. However, to develop image-based algorithms for dermatology applications, comprehensive criteria establishing development and performance evaluation standards are required to ensure product fairness, reliability, and safety.

OBJECTIVE

To consolidate limited existing literature with expert opinion to guide developers and reviewers of dermatology AI.

EVIDENCE REVIEW

In this consensus statement, the 19 members of the International Skin Imaging Collaboration AI working group volunteered to provide a consensus statement. A systematic PubMed search was performed of English-language articles published between December 1, 2008, and August 24, 2021, for "artificial intelligence" and "reporting guidelines," as well as other pertinent studies identified by the expert panel. Factors that were viewed as critical to AI development and performance evaluation were included and underwent 2 rounds of electronic discussion to achieve consensus.

FINDINGS

A checklist of items was developed that outlines best practices of image-based AI development and assessment in dermatology.

CONCLUSIONS AND RELEVANCE

Clinically effective AI needs to be fair, reliable, and safe; this checklist of best practices will help both developers and reviewers achieve this goal.

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy

Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied for histopathological confirmation, thus lowering the specificity of noninvasive BCC diagnosis. Recently, reflectance confocal microscopy, a noninvasive diagnostic technique that can image skin lesions at cellular level resolution, has shown to improve specificity in BCC diagnosis and reduced the number needed to biopsy by 2-3 times. In this study, we developed and evaluated a deep learning-based artificial intelligence model to automatically detect BCC in reflectance confocal microscopy images. The proposed model achieved an area under the curve for the receiver operator characteristic curve of 89.7% (stack level) and 88.3% (lesion level), a performance on par with that of reflectance confocal microscopy experts. Furthermore, the model achieved an area under the curve of 86.1% on a held-out test set from international collaborators, demonstrating the reproducibility and generalizability of the proposed automated diagnostic approach. These results provide a clear indication that the clinical deployment of decision support systems for the detection of BCC in reflectance confocal microscopy images has the potential for optimizing the evaluation and diagnosis of patients with skin cancer.

Combined PARP1-targeted nuclear contrast and reflectance contrast enhances 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 impose a fundamental limit on contrast, detectability, and diagnostic accuracy. We investigated PARPi-FL, an exogenous nuclear poly (ADP-ribose) polymerase (PARP1)-targeted fluorescent contrast agent and fluorescence confocal microscopy (FCM) towards 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. Diagnostic accuracy of PARPi-FL contrast was evaluated in 83 surgical specimens. Optimal parameters for trans-epidermal 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, as compared to normal skin structures. Blinded reading of RCM-and-FCM images by two experts demonstrated a higher diagnostic accuracy for BCCs with combined fluorescence and reflectance contrast, as compared to RCM-alone. Optimal parameters (time and concentration) for PARPi-FL trans-epidermal permeation through intact skin were successfully determined. Conclusion: Combined fluorescence and reflectance contrast may improve noninvasive BCC diagnosis with confocal microscopy.

Abstract 2814: Dynamic imaging of tumor-immune microenvironment (TiME) and microvasculature identifies ‘hot' and ‘cold' tumor phenotypes in vivo in patients

Investigating the dynamic crosstalk between the tumor-immune microenvironment (TiME) and microvasculature in vivo in patients can lead to important insights into the underlying biology, help identify tumor phenotypes and reveal attractive druggable targets.

Dynamic non-invasive label-free imaging of TiME and microvasculature in real-time directly in patients using reflectance confocal microscopy (RCM) was investigated on 60 skin cancer patients (basal cell carcinoma, BCC; squamous cell carcinoma, SCC), followed by automated and machine-learning based quantification of TiME and microvasculature features such as vascular density, leukocyte trafficking and immune cell density. Manual (two readers) and histopathological evaluation (dermatopathologist) of these features was also performed. Molecular correlation of imaging features and phenotypes was performed using anti-CD3/anti-CD20 IHC staining for tertiary lymphoid structures (TLS) and total lymphocyte density (n=33), flow cytometry for immune cells (n=3), and differential RNA expression (n=14). Correlation of RCM features and phenotypes at baseline (before treatment) with treatment response was also evaluated on 9 cancer lesions undergoing topical immunotherapy imiquimod. High agreement for feature presence on RCM and Histology, and manual and automated RCM features was observed. Unsupervised clustering on total TiME and microvasculature features on RCM using principal component analysis (PCA) indicates four distinct tumor phenotypes (PCA 1). The phenotype with high inflammation, high trafficking and higher density of vessels or the denoted ‘hot' phenotype correlated with higher activated CD8+ Granzyme B+ cells (67% of total CD8+cells). The clustering pattern on RCM was compared to TLS and lymphocyte density (PCA 2) and gene expression following CIBERSORT analysis (PCA 3). The clustering in RCM correlated better with gene expression (PCA 1 and 3, 100% agreement) than TLS and lymphocyte density (PCA 1 and 2, 86% agreement). The ‘hot' phenotype in RCM correlated with higher immune gene signatures and higher TLS/lymphocyte density. Increased plasma, CD8, activated CD4 memory and activated NK cells, M1 macrophages and monocytes, along with up-regulation of JAK-STAT, chemokine and cell adhesion signaling cascade were found in the ‘hot' RCM phenotype. Statistical modeling for correlating phenotypes with treatment outcomes was performed using principal component-linear discriminant analysis (PC-LDA). Two responders with tumor regression were predicted as ‘hot' phenotype while the non-responding patients (remaining 7) were classified as cold phenotype; suggesting that RCM 'hot' phenotype correlates with better treatment response. Thus, we demonstrate the potential utility of noninvasive RCM imaging in identifying ‘hot' and ‘cold' tumor phenotypes directly in patients.

Citation Format: Aditi Sahu, Melissa Gill, Miguel Cordova, Anthony Santella, Kivanc Kose, Teguru Tembo, Anabel Alfonso, Pratik Chandrani, Christi Fox, Salvador Gonzalez, Nicholas Kurtansky, Melissa Pulitzer, William Phillips, Madison Li, Kimeil King, Stephen Dusza, Shuaitong Liu, Ning Yang, Haaris Jilani, Paras Mehta, Ashfaq Marghoob, Allan Halpern, Anthony Rossi, Liang Deng, Chih-Shan Jason Chen, Milind Rajadhyaksha. Dynamic imaging of tumor-immune microenvironment (TiME) and microvasculature identifies ‘hot' and ‘cold' tumor phenotypes in vivo in patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2814.

Skin strata delineation in reflectance confocal microscopy images using recurrent convolutional networks with attention

Reflectance confocal microscopy (RCM) is an effective non-invasive tool for cancer diagnosis. However, acquiring and reading RCM images requires extensive training and experience, and novice clinicians exhibit high discordance in diagnostic accuracy. Quantitative tools to standardize image acquisition could reduce both required training and diagnostic variability. To perform diagnostic analysis, clinicians collect a set of RCM mosaics (RCM images concatenated in a raster fashion to extend the field view) at 4-5 specific layers in skin, all localized in the junction between the epidermal and dermal layers (dermal-epidermal junction, DEJ), necessitating locating that junction before mosaic acquisition. In this study, we automate DEJ localization using deep recurrent convolutional neural networks to delineate skin strata in stacks of RCM images collected at consecutive depths. Success will guide to automated and quantitative mosaic acquisition thus reducing inter operator variability and bring standardization in imaging. Testing our model against an expert labeled dataset of 504 RCM stacks, we achieved [Formula: see text] classification accuracy and nine-fold reduction in the number of anatomically impossible errors compared to the previous state-of-the-art.

Deep Learning-Based Denoising in High-Speed Portable Reflectance Confocal Microscopy

BACKGROUND AND OBJECTIVE

Portable confocal microscopy (PCM) is a low-cost reflectance confocal microscopy technique that can visualize cellular details of human skin in vivo. When PCM images are acquired with a short exposure time to reduce motion blur and enable real-time 3D imaging, the signal-to-noise ratio (SNR) is decreased significantly, which poses challenges in reliably analyzing cellular features. In this paper, we evaluated deep learning (DL)-based approach for reducing noise in PCM images acquired with a short exposure time.

STUDY DESIGN/MATERIALS AND METHODS

Content-aware image restoration (CARE) network was trained with pairs of low-SNR input and high-SNR ground truth PCM images obtained from 309 distinctive regions of interest (ROIs). Low-SNR input images were acquired from human skin in vivo at the imaging speed of 180 frames/second. The high-SNR ground truth images were generated by registering 30 low-SNR input images obtained from the same ROI and summing them. The CARE network was trained using the Google Colaboratory Pro platform. The denoising performance of the trained CARE network was quantitatively and qualitatively evaluated by using image pairs from 45 unseen ROIs.

RESULTS

CARE denoising improved the image quality significantly, increasing similarity with the ground truth image by 1.9 times, reducing noise by 2.35 times, and increasing SNR by 7.4 dB. Banding noise, prominent in input images, was significantly reduced in CARE denoised images. CARE denoising provided quantitatively and qualitatively better noise reduction than non-DL filtering methods. Qualitative image assessment by three confocal readers showed that CARE denoised images exhibited negligible noise more often than input images and non-DL filtered images.

CONCLUSIONS

Results showed the potential of using a DL-based method for denoising PCM images obtained at a high imaging speed. The DL-based denoising method needs to be further trained and tested for PCM images obtained from disease-suspicious skin lesions.

Exploring the utility of Deep Red Anthraquinone 5 for digital staining of ex vivo confocal micrographs of optically sectioned skin

We investigated the utility of the fluorescent dye Deep Red Anthraquinone 5 (DRAQ5) for digital staining of optically sectioned skin in comparison to acridine orange (AO). Eight fresh-frozen thawed Mohs discard tissue specimens were stained with AO and DRAQ5, and imaged using an ex vivo confocal microscope at three wavelengths (488 nm and 638 nm for fluorescence, 785 nm for reflectance). Images were overlaid (AO + Reflectance, DRAQ5 + Reflectance), digitally stained, and evaluated by three investigators for perceived image quality (PIQ) and histopathological feature identification. In addition to nuclear staining, AO seemed to stain dermal fibers in a subset of cases in digitally stained images, while DRAQ5 staining was more specific to nuclei. Blinded evaluation showed substantial agreement, favoring DRAQ5 for PIQ (82%, Cl 75%-90%, Gwet's AC 0.74) and for visualization of histopathological features in (81%, Cl 73%-89%, Gwet's AC 0.67), supporting its use in digital staining of multimodal confocal micrographs of skin.

An international 3-center training and reading study to assess basal cell carcinoma surgical margins with ex vivo fluorescence confocal microscopy

BACKGROUND

Novel solutions are needed for expediting margin assessment to guide basal cell carcinoma (BCC) surgeries. Ex vivo fluorescence confocal microscopy (FCM) is starting to be used in freshly excised surgical specimens to examine BCC margins in real time. Training and educational process are needed for this novel technology to be implemented into clinic.

OBJECTIVE

To test a training and reading process, and measure diagnostic accuracy of clinicians with varying expertise level in reading ex vivo FCM images.

METHODS

An international three-center study was designed for training and reading to assess BCC surgical margins and residual subtypes. Each center included a lead dermatologic/Mohs surgeon (clinical developer of FCM) and three additional readers (dermatologist, dermatopathologist, dermatologic/Mohs surgeon), who use confocal in clinical practice. Testing was conducted on 30 samples.

RESULTS

Overall, the readers achieved 90% average sensitivity, 78% average specificity in detecting residual BCC margins, showing high and consistent diagnostic reading accuracy. Those with expertise in dermatologic surgery and dermatopathology showed the strongest potential for learning to assess FCM images.

LIMITATIONS

Small dataset, variability in mosaic quality between centers.

CONCLUSION

Suggested process is feasible and effective. This process is proposed for wider implementation to facilitate wider adoption of FCM to potentially expedite BCC margin assessment to guide surgery in real time.

Association of Multiple Aggregated Yellow-White Globules With Nonpigmented Basal Cell Carcinoma

Importance

Basal cell carcinoma (BCC) is the most common skin cancer. Dermoscopic imaging has improved diagnostic accuracy; however, diagnosis of nonpigmented BCC remains limited to arborizing vessels, ulceration, and shiny white structures.

Objective

To assess multiple aggregated yellow-white (MAY) globules as a diagnostic feature for BCC.

Design, Setting, and Participants

In this retrospective, single-center, case-control study, nonpigmented skin tumors, determined clinically, were identified from a database of lesions consecutively biopsied during a 7-year period (January 1, 2009, to December 31, 2015). A subset of tumors was prospectively diagnosed, and reflectance confocal microscopy, optical coherence tomography, and histopathologic correlation were performed. Data analysis was conducted from July 1 to September 31, 2019.

Exposures

Investigators evaluated for the presence or absence of known dermoscopic criteria. MAY globules were defined as aggregated, white-yellow structures visualized in polarized and nonpolarized light.

Main Outcomes and Measures

The primary outcome was the diagnostic accuracy of MAY globules for the diagnosis of BCC. Secondary objectives included the association with BCC location and subtype. Interrater agreement was estimated.

Results

A total of 656 nonpigmented lesions from 643 patients (mean [SD] age, 63.1 [14.9] years; 381 [58.1%] male) were included. In all, 194 lesions (29.6%) were located on the head and neck. A total of 291 (44.4%) were BCCs. MAY globules were seen in 61 of 291 BCC cases (21.0%) and in 3 of 365 other diagnoses (0.8%) (P < .001). The odds ratio for diagnosis of BCC was 32.0 (96% CI, 9.9-103.2). The presence of MAY globules was associated with a diagnosis of histologic high-risk BCC (odds ratio, 6.5; 95% CI, 3.1-14.3). The structure was never seen in cases of superficial BCCs.

Conclusions and Relevance

The findings suggest that MAY globules may have utility as a new BCC dermoscopic criterion with a high specificity. MAY globules were negatively associated with superficial BCC and positively associated with deeper-seated, histologic, higher-grade tumor subtypes.

A patient-centric dataset of images and metadata for identifying melanomas using clinical context

Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algorithms have achieved expert-level performance in controlled studies examining single images, in practice dermatologists base their judgment holistically from multiple lesions on the same patient. The 2020 SIIM-ISIC Melanoma Classification challenge dataset described herein was constructed to address this discrepancy between prior challenges and clinical practice, providing for each image in the dataset an identifier allowing lesions from the same patient to be mapped to one another. This patient-level contextual information is frequently used by clinicians to diagnose melanoma and is especially useful in ruling out false positives in patients with many atypical nevi. The dataset represents 2,056 patients (20.8% with at least one melanoma, 79.2% with zero melanomas) from three continents with an average of 16 lesions per patient, consisting of 33,126 dermoscopic images and 584 (1.8%) histopathologically confirmed melanomas compared with benign melanoma mimickers.

Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net)

In-vivo optical microscopy is advancing into routine clinical practice for non-invasively guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce the need for traditional biopsy. However, reading and analysis of the optical microscopic images are generally still qualitative, relying mainly on visual examination. Here we present an automated semantic segmentation method called "Multiscale Encoder-Decoder Network (MED-Net)" that provides pixel-wise labeling into classes of patterns in a quantitative manner. The novelty in our approach is the modeling of textural patterns at multiple scales (magnifications, resolutions). This mimics the traditional procedure for examining pathology images, which routinely starts with low magnification (low resolution, large field of view) followed by closer inspection of suspicious areas with higher magnification (higher resolution, smaller fields of view). We trained and tested our model on non-overlapping partitions of 117 reflectance confocal microscopy (RCM) mosaics of melanocytic lesions, an extensive dataset for this application, collected at four clinics in the US, and two in Italy. With patient-wise cross-validation, we achieved pixel-wise mean sensitivity and specificity of 74% and 92%, respectively, with 0.74 Dice coefficient over six classes. In the scenario, we partitioned the data clinic-wise and tested the generalizability of the model over multiple clinics. In this setting, we achieved pixel-wise mean sensitivity and specificity of 77% and 94%, respectively, with 0.77 Dice coefficient. We compared MED-Net against the state-of-the-art semantic segmentation models and achieved better quantitative segmentation performance. Our results also suggest that, due to its nested multiscale architecture, the MED-Net model annotated RCM mosaics more coherently, avoiding unrealistic-fragmented annotations.

FRI0490 INVESTIGATING THE ROLE OF IL-1THETA IN PATHOGENESIS OF BEHÇET’S DISEASE

Background:

Behçet’s disease (BD) is a chronic inflammatory disease that may involve many systems including mucocutaneous, vascular, articular, gastrointestinal, neurological and cardiopulmonary systems. Although the pathogenic mechanisms of BD remain unclear, increased release of proinflammatory cytokines and chemokines may play a role in inflammatory stages of the disease.

Objectives:

IL-1 theta is a member of IL-1 family. A variety of tissue cells, such as endothelial cells, keratinocytes, dendritic cells macrophages, B cells can produce IL-1 theta under the stimulation of pro-inflammatory factors. Several studies have shown that IL-1 theta can promote the production of proinflammatory cytokines. In this study, we investigated the relationship between serum IL- 1 theta levels and disease activity and clinical findings of BD.

Methods:

59 patients with BD (48 female, 11 male) and 20 healthy controls (17 female, 3 male; mean age 41.0 ± 9.3 years) were enrolled in this study. Thirty five patients were in active stage (mean age; 40.3 ± 11.0 years, median disease duration 7 years) and 24 patients were in inactive stage (mean age; 42.9 ± 13.2 years, median disease duration; 8 years). Serum IL-1 theta levels were evaluated by ELISA.

Results:

The mean serum IL-1 theta levels were 8.65 ± 4.41 pg/ml in patients with BD and 3.9 ± 2.54 pg/ml in healthy controls. The mean serum IL-1 theta levels were 10.34 ± 5.52 pg/ml in active patients with BD and 6.92 ± 2.43 pg/ml in inactive patients with BD. Serum IL-1 theta levels were significantly high in active Behçet’s patients compared with in inactive Behçet’s patients (p<0.01) and the controls (P<0.001).

Serum IL-1 theta levels were significantly higher in the presence of neurological, vascular and mucocutaneous involvement in subgroup analysis according to the clinical findings of Behçet’s patients. IL-1 theta levels were negatively correlation with Platelet count and ESR (r=0.332 p=0.050, r=0.382 p=0.024 respectively). There was no statistically significant difference between IL-1 theta levels disease duration, and CRP.

Conclusion:

In this study, we demonstrated that serum IL-1 theta levels were significantly elevated in patients with BD. The high levels of serum IL-1 theta, in active and inactive patients with BD suggest that IL-1 theta may play a significant role of in the pathogenesis of BD.

References:

[1]Salmaninejad, A., et al. Genetics and immunodysfunction underlying Behçet’s disease and immunomodulant treatment approaches. Journal of immunotoxicology, 2017.14(1): 137-151.

[2]Nara, K., et al. Involvement of innate immunity in the pathogenesis of intestinal Behcet’s disease. Clin Exp Immunol, 2008.152(2): 245-51.

[3]Dalghous, A.M., et al. Expression of cytokines, chemokines, and chemokine receptors in oral ulcers of patients with Behcet’s disease (BD) and recurrent aphthous stomatitis is Th1-associated, although Th2-association is also observed in patients with BD. Scand J Rheumatol, 2006.35(6):472-5.

[4]Uzkeser, H., et al. Is mean platelet volume a new activity criteria in Behçet’s disease? Blood Coagulation & Fibrinolysis, 2015.26(7): 836-839.

Disclosure of Interests:

None declared

Utilizing Machine Learning for Image Quality Assessment for Reflectance Confocal Microscopy

In vivo reflectance confocal microscopy (RCM) enables clinicians to examine lesions' morphological and cytological information in epidermal and dermal layers while reducing the need for biopsies. As RCM is being adopted more widely, the workflow is expanding from real-time diagnosis at the bedside to include a capture, store, and forward model with image interpretation and diagnosis occurring offsite, similar to radiology. As the patient may no longer be present at the time of image interpretation, quality assurance is key during image acquisition. Herein, we introduce a quality assurance process by means of automatically quantifying diagnostically uninformative areas within the lesional area by using RCM and coregistered dermoscopy images together. We trained and validated a pixel-level segmentation model on 117 RCM mosaics collected by international collaborators. The model delineates diagnostically uninformative areas with 82% sensitivity and 93% specificity. We further tested the model on a separate set of 372 coregistered RCM-dermoscopic image pairs and illustrate how the results of the RCM-only model can be improved via a multimodal (RCM + dermoscopy) approach, which can help quantify the uninformative regions within the lesional area. Our data suggest that machine learning-based automatic quantification offers a feasible objective quality control measure for RCM imaging.

Real-time video mosaicking to guide handheld in vivo microscopy

Handheld and endoscopic optical-sectioning microscopes are being developed for noninvasive screening and intraoperative consultation. Imaging a large extent of tissue is often desired, but miniature in vivo microscopes tend to suffer from limited fields of view. To extend the imaging field during clinical use, we have developed a real-time video mosaicking method, which allows users to efficiently survey larger areas of tissue. Here, we modified a previous post-processing mosaicking method so that real-time mosaicking is possible at >30 frames/second when using a device that outputs images that are 400 × 400 pixels in size. Unlike other real-time mosaicking methods, our strategy can accommodate image rotations and deformations that often occur during clinical use of a handheld microscope. We perform a feasibility study to demonstrate that the use of real-time mosaicking is necessary to enable efficient sampling of a desired imaging field when using a handheld dual-axis confocal microscope.

The effects of N-acetylcysteine on cisplatin induced cardiotoxicity

OBJECTIVES

Recent studies reported that oxidative stress is an important mechanism that contributes to cisplatin induced cardiotoxicity. In the present study, the effects of N-acetylcysteine (NAC), which is an antioxidant, on cisplatin induced cardiotoxicity were investigated in a rat model.

METHODS

Thirty two rats were separated into 4 equal groups: Control, NAC-250, CP (cisplatin), CP+NAC. Rats in the experimental groups were treated with a single dose of cisplatin intraperitoneally (ip) (10 mg/kg) and NAC (ip, 250 mg/kg) for 3 consecutive days. At the end of the experiment, cardiotoxicity was determined from plasma CK-MB, LDH, cTnI and cardiac myosin light chain-1 (CMLC-1) levels. In the tissue samples, total oxidant capacity (TOC), total antioxidant capacity (TAC), lipid hydroperoxide (ROOH) and thiol levels were measured. The hearts were also analyzed histopathologically.

RESULTS

It was determined that cisplatin increased the tissue TOC, ROOH levels and decreased TAC and thiol levels. NAC administration after cisplatin treatment was observed to have ameliorated histological and functional changes in heart.

CONCLUSIONS

In conclusion, the results of this experimental study suggested that oxidative stress had a serious effect on cisplatin cardiotoxicity, and NAC could be used as a therapeutic agent in addition to standard cisplatin treatment protocols (Tab. 3, Fig. 1, Ref. 35).

Artifacts and landmarks: pearls and pitfalls for in vivo reflectance confocal microscopy of the skin using the tissue-coupled device

Reflectance confocal microscopy (RCM) is a non-invasive imaging tool for cellular-level examination of skin lesions, typically from the epidermis to the superficial dermis. Clinical studies show RCM imaging is highly sensitive and specific in the diagnosis of skin diseases. RCM is disseminating from academic tertiary care centers with early adopter "experts" into diverse clinical settings, with image acquisition performed by technicians and image interpretation by physicians. In the hands of trained users, RCM serves an aid to accurately diagnose and monitor skin tumors and inflammatory processes. However, exogenous and endogenous artifacts introduced during imaging can obscure RCM images, limiting or prohibiting interpretation. Herein we review the types of artifacts that may occur and techniques for mitigating them during image acquisition, to assist technicians with qualitative image assessment and provide physicians guidance on identifying artifacts that may confound interpretation. Finally, we discuss normal skin "landmarks" and how they can (i) obscure images, (ii) be exploited for additional diagnostic information, and (iii) simulate pathological structures. A deeper understanding of the principles and methods behind RCM imaging and the varying appearance of normal skin structures in the acquired images aids technicians in capturing higher quality image sets and enables physicians to increase interpretation accuracy.

Melanoma risk stratification of individuals with a high-risk naevus phenotype - A pilot study

BACKGROUND/OBJECTIVES

High a naevus counts and atypical naevi are risk factors for cutaneous melanoma. However, many individuals with a high-risk naevus phenotype do not develop melanoma. In this study, we describe the clinical and dermoscopic attributes of naevi associated with melanoma in a high-risk naevus phenotype population.

METHODS

This single-centre, hospital-based case-control study included 54 prospectively enrolled adult patients ≥18 years old with a high-risk naevus phenotype (18 cases with a history of melanoma and 36 age- and gender-matched controls without a history of melanoma). We analysed clinical and dermoscopic images of the 20 largest naevi for each participant.

RESULTS

Cases had a higher mean age than controls (48.2 vs. 39.1 years, P = 0.007) but there was no difference in the male-to-female ratio between groups. Nearly, all participants (97%) were Fitzpatrick skin type II or III. Naevi in cases were more likely to be truncal, (72.6% vs. 53.6%, P = 0.01), particularly anterior truncal, (29.2% vs. 14.4%, P < 0.001) and larger than 8 mm (17.4% vs. 7.8%%, P = 0.01) compared to controls. CASH score of naevi did not differ between groups. Naevi in cases were more likely to have a multicomponent dermoscopic pattern than in controls (18.4% vs. 12.6%, P = 0.02).

CONCLUSION

Larger naevi, truncal naevi, and naevi, with a multicomponent dermoscopic pattern may be risk factors for melanoma among individuals with a high-risk naevus phenotype. Further studies are needed to validate these findings.

Peri-operative delineation of non-melanoma skin cancer margins in vivo with handheld reflectance confocal microscopy and video-mosaicking

BACKGROUND

The surgical removal of non-melanoma skin cancers (NMSCs) is guided by the pathologic examination of margins. However, the preparation of histopathology is time consuming, labour-intensive and requires separate laboratory infrastructure. Furthermore, when histopathology indicates positive margins, patients must return for re-excisions. Reflectance confocal microscopy (RCM) with a new video-mosaicking approach can noninvasively delineate margins directly on patients and potentially guide surgery in real-time, augmenting the traditional approaches of histopathology.

OBJECTIVE

To assess a new peri-operative RCM video-mosaicking approach for comprehensive delineation of NMSC margins on patients in vivo.

METHODS

Thirty-five patients undergoing Mohs micrographic surgery (MMS) in the Mohs surgery unit at Memorial Sloan Kettering Cancer Center, New York, NY were included in the study. RCM imaging was performed before and after the first staged excision by acquiring videos along the surgical margins (epidermal, peripheral and deep dermal) of each wound, which were subsequently processed into video-mosaics. Two RCM evaluators read and assessed video-mosaics, and subsequently compared to the corresponding Mohs frozen histopathology.

RESULTS

Reflectance confocal microscopy videos and video-mosaics displayed acceptable imaging quality (resolution and contrast), pre-operatively in 32/35 (91%) NMSC lesions and intra-operatively in 29/35 lesions (83%). Pre-operative delineation of margins correlated with the histopathology in 32/35 (91%) lesions. Intra-operative delineation correlated in 10/14 (71%) lesions for the presence of residual tumour and in 18/21 (86%) lesions for absence. Sensitivity/specificity were 71%/86% and 86%/81% for two RCM video-mosaic evaluators, and overall agreement was 80% and 83% with histopathology, with moderate inter-evaluator agreement (k = 0.59, P ≤ 0.0002).

CONCLUSIONS

Peri-operative RCM video-mosaicking of NMSC margins directly on patients may potentially guide surgery in real-time, serve as an adjunct to histopathology, reduce time spent in clinic and reduce the need for re-excisions. Further testing in larger studies is needed.

Correlation of Handheld Reflectance Confocal Microscopy With Radial Video Mosaicing for Margin Mapping of Lentigo Maligna and Lentigo Maligna Melanoma

Importance

The management of lentigo maligna (LM) and LM melanoma (LMM) is challenging because of extensive subclinical spread and its occurrence on cosmetically sensitive areas. Reflectance confocal microscopy (RCM) improves diagnostic accuracy for LM and LMM and can be used to delineate their margins.

Objectives

To evaluate whether handheld RCM with radial video mosaicing (HRCM-RV) offers accurate presurgical assessment of LM and LMM margins.

Design, Setting, and Participants

This prospective study included consecutive patients with biopsy-proven LM and LMM located on the head and neck area who sought consultation for surgical management from March 1, 2016, through March 31, 2017, at the Dermatology Service of the Memorial Sloan Kettering Cancer Center. Thirty-two patients underwent imaging using HRCM-RV, and 22 patients with 23 LM or LMM lesions underwent staged surgery and contributed to the analysis.

Main Outcomes and Measures

Clinical lesion size and area, LM and LMM area based on HRCM-RV findings, surgical defect area estimated by HRCM-RV, and observed surgical defect area. In addition, the margins measured in millimeters estimated for tumor clearance in each quadrant based on HRCM-RV findings were calculated and compared with the surgical margins.

Results

Among the 22 patients (12 men and 10 women; mean [SD] age, 69.0 [8.6] years [range, 46-83 years]) with 23 lesions included in the final analysis, the mean (SD) surgical defect area estimated with HRCM-RV was 6.34 (4.02) cm2 and the mean (SD) area of surgical excision with clear margins was 7.74 (5.28) cm2. Overall, controlling for patient age and previous surgery, surgical margins were a mean of 0.76 mm (95% CI, 0.67-0.84 mm; P < .001) larger than the HRCM-RV estimate.

Conclusions and Relevance

Mapping of LM and LMM with HRCM-RV estimated defects that were similar to but slightly smaller than those found in staged excision. Thus, mapping of LM using HRCM-RV can help spare healthy tissue by reducing the number of biopsies needed in clinically uncertain areas and may be used to plan treatment of LM and LMM and counsel patients appropriately.

Handheld Reflectance Confocal Microscopy for the Detection of Recurrent Extramammary Paget Disease

Importance

Extramammary Paget disease (EMPD) is commonly refractory to surgical and nonsurgical therapies. Identifying recurrent or persistent EMPD is challenging because the disease is multifocal, and multiple blind scouting biopsies are usually performed in this setting. Handheld reflectance confocal microscopy (HRCM) has been used to diagnose and map primary EMPD and therefore may be used to identify EMPD recurrences.

Objective

To evaluate HRCM's diagnostic accuracy in the setting of recurrent or persistent EMPD as well as its potential diagnostic pitfalls.

Design, Setting, and Participants

This prospective case series study included patients referred to the Dermatology Service at Memorial Sloan Kettering Cancer Center between January 1, 2014, and December 31, 2016, with biopsy-proven EMPD in whom HRCM was used to monitor treatment response. Five patients were included, and 22 sites clinically concerning for recurrent or persistent disease were evaluated using HRCM and histopathologic examination. In 2 patients, video mosaics were created to evaluate large areas.

Main Outcomes and Measures

Sensitivity and specificity of HRCM in identifying recurrent or persistent EMPD; causes for false-negative results according to their location, histopathologic findings, and previous treatments.

Results

Of the 22 clinically suspicious sites evaluated in 5 patients (4 men, 1 woman; median [range] age, 70 [56-77] years), 9 (40.9%) were positive for recurrent disease on HRCM and histopathologically confirmed, and 13 (59.1%) sites were negative on HRCM, but 3 of the 13 were positive for EMPD on histopathological examination. In general, HRCM had a sensitivity of 75% and a specificity of 100% in identifying recurrent or persistent EMPD. False-negative results were found in 2 patients and occurred at the margins of EMPD, close to previous biopsy sites. Creating video mosaics (or video mosaicking) seemed to improve the detection of EMPD.

Conclusions and Relevance

Handheld reflectance confocal microscopy is a useful auxiliary tool for diagnosing EMPD recurrences and can be used to guide scouting biopsies, thus reducing the number of biopsies needed to render a correct diagnosis.

The Role of Color and Morphologic Characteristics in Dermoscopic Diagnosis

IMPORTANCE

Both colors and structures are considered important in the dermoscopic evaluation of skin lesions but their relative significance is unknown.

OBJECTIVE

To determine if diagnostic accuracy for common skin lesions differs between gray-scale and color dermoscopic images.

DESIGN, SETTING, AND PARTICIPANTS

A convenience sample of 40 skin lesions (8 nevi, 8 seborrheic keratoses, 7 basal cell carcinomas, 7 melanomas, 4 hemangiomas, 4 dermatofibromas, 2 squamous cell carcinomas [SCCs]) was selected and shown to attendees of a dermoscopy course (2014 Memorial Sloan Kettering Cancer Center dermoscopy course). Twenty lesions were shown only once, either in gray-scale (n = 10) or color (n = 10) (nonpaired). Twenty lesions were shown twice, once in gray-scale (n = 20) and once in color (n = 20) (paired). Participants provided their diagnosis and confidence level for each of the 60 images. Of the 261 attendees, 158 participated (60.5%) in the study. Most were attending physicians (n = 76 [48.1%]). Most participants were practicing or training in dermatology (n = 144 [91.1%]). The median (interquartile range) experience evaluating skin lesions and using dermoscopy of participants was 6 (13.5) and 2 (4.0) years, respectively.

MAIN OUTCOMES AND MEASURES

Diagnostic accuracy and confidence level of participants evaluating gray-scale and color images. Two separate analyses were performed: (1) an unpaired evaluation comparing gray-scale and color images shown either once or for the first time, and (2) a paired evaluation comparing pairs of gray-scale and color images of the same lesion.

RESULTS

In univariate analysis of unpaired images, color images were less likely to be diagnosed correctly compared with gray-scale images (odds ratio [OR], 0.8; P < .001). Using gray-scale images as the reference, multivariate analyses of both unpaired and paired images found no association between correct lesion diagnosis and use of color images (OR, 1.0; P = .99, and OR, 1.2; P = .82, respectively). Stratified analysis of paired images using a color by diagnosis interaction term showed that participants were more likely to make a correct diagnosis of SCC and hemangioma in color (P < .001 for both comparisons) and dermatofibroma in gray-scale (P < .001).

CONCLUSIONS AND RELEVANCE

Morphologic characteristics (ie, structures and patterns), not color, provide the primary diagnostic clue in dermoscopy. Use of gray-scale images may improve teaching of dermoscopy to novices by emphasizing the evaluation of morphology.

Investigating the physiological effects of 10.5 Tesla static field exposure on anesthetized swine

PURPOSE

In this work, we investigated the relative effects of static magnetic field exposure (10.5 Tesla [T]) on two physiological parameters; blood pressure (BP) and heart rate (HR).

METHODS

In vivo, we recorded both BP and HR in 4 swine (3 female, 1 male) while they were positioned within a 10.5T magnet. All measurements were performed invasively within these anesthetized animals by the placement of pressure catheters into their carotid arteries.

RESULTS

We measured average increases of 2.0 mm Hg (standard deviation [SD], 6.9) in systolic BP and an increase of 4.5 mm Hg (SD, 13.7) in the diastolic BPs: We also noted an average increase of 1.2 beats per minute (SD, 2.5) in the HRs during such.

CONCLUSION

Data regarding changes in BP and HR in anesthetized swine attributed to whole-body 10.5T exposure are reported. Magn Reson Med 79:511-514, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin

Segmenting objects of interest from 3D data sets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution, and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, the shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance, and unknown locations. The driving application that inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear, and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease, and cancer usually start. Detecting the DEJ is challenging, because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped "peaks and valleys." In addition, RCM imaging resolution, contrast, and intensity vary with depth. Thus, a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process with shape priors and performs inference using Gibbs sampling. Experimental results show that the proposed unsupervised model is able to automatically detect the DEJ with physiologically relevant accuracy in the range 10- 20 μm .

Unsupervised delineation of stratum corneum using reflectance confocal microscopy and spectral clustering

BACKGROUND

Measuring the thickness of the stratum corneum (SC) in vivo is often required in pharmacological, dermatological, and cosmetological studies. Reflectance confocal microscopy (RCM) offers a non-invasive imaging-based approach. However, RCM-based measurements currently rely on purely visual analysis of images, which is time-consuming and suffers from inter-user subjectivity.

METHODS

We developed an unsupervised segmentation algorithm that can automatically delineate the SC layer in stacks of RCM images of human skin. We represent the unique textural appearance of SC layer using complex wavelet transform and distinguish it from deeper granular layers of skin using spectral clustering. Moreover, through localized processing in a matrix of small areas (called 'tiles'), we obtain lateral variation of SC thickness over the entire field of view.

RESULTS

On a set of 15 RCM stacks of normal human skin, our method estimated SC thickness with a mean error of 5.4 ± 5.1 μm compared to the 'ground truth' segmentation obtained from a clinical expert.

CONCLUSION

Our algorithm provides a non-invasive RCM imaging-based solution which is automated, rapid, objective, and repeatable.

Thyroid Hormone Withdrawal Further Exacerbates Oxidative Stress in Patients with Thyroid Carcinoma

PURPOSE

Hypothyroidism has profound effects on multiple organs and systems including cellular oxidative damage. Thus, we aimed to investigate the effects of acute hypothyroidism on oxidative stress in patients with differentiated thyroid carcinoma (DTC).

PATIENTS

33 patients with DTC were involved in the study. 23 healthy subjects matched for age and body mass index (BMI) served as control group. Fasting blood sample was obtained for the determination of blood chemistry, lipids, myeloperoxidase (MPO) activity, total lipid hydroperoxide (LHP), pyrrolized protein, protein carbonyl compounds (PCC), advanced oxidation protein products (AOPP) and thiol levels before and after thyroid hormone withdrawal (THW) in patients with DTC.

RESULTS

MPO activity, total LHP, pyrrolized protein, PCC and AOPP levels were significantly higher, but thiol levels were significantly lower in patients with DTC while on L-thyroxine treatment than those of healthy subjects. At acute hypothyroid status after THW, MPO activity, total LHP, pyrrolized protein, PCC and AOPP levels further increased, thiol levels further decreased in patients with DTC as compared to healthy subjects and to their on L-thyroxine treatment period.

CONCLUSIONS

This study showed an increased oxidative stress in patients with DTC which is further exacerbated with acute hypothyroidism upon THW. This situation may have treatment implications such as antioxidant therapy, at least during THW.

Growth-Curve Modeling of Nevi With a Peripheral Globular Pattern

Importance

Although nevi with a peripheral rim of globules (peripheral globular nevi [PGN]) observed with dermoscopy are associated with enlarging melanocytic nevi, their actual growth dynamics remain unknown. Because change is a sensitive but nonspecific marker for melanoma, beginning to understand the growth patterns of nevi may improve the ability of physicians to differentiate normal from abnormal growth and reduce unnecessary biopsies.

Objective

To study the growth dynamics and morphologic evolution of PGN on dermoscopy.

Design, Setting, and Participants

A total of 84 participants with 121 PGN from September 1, 1999, through May 1, 2013, were identified retrospectively. Cohorts were recruited from the Memorial Sloan Kettering Cancer Center; Melanoma Unit of the Hospital Clinic, University of Barcelona; and Study of Nevi in Children. All 3 cohorts underwent longitudinal monitoring with serial dermoscopic imaging of their PGN. Data analysis was performed from May 1, 2014, through April 1, 2015.

Main Outcomes and Measures

Establishment of the natural growth curve of PGN. The secondary aim was to establish the median time to growth cessation in those PGN for which the size eventually stabilized and/or had begun to decrease during the study period.

Results

The median duration of follow-up was 25.1 (range, 2.0-114.4) months. Most of the nevi (116 [95.9%]) enlarged at some point during sequential monitoring. The rate of increase in the surface area of PGN varied among cohorts and ranged from -0.47 to 2.26 mm2/mo (mean rate, 0.25 [95% CI, 0.14-0.36] mm2/mo). The median time to growth cessation in the 26 PGN that stabilized or decreased in size (21.5%) was 58.6 months. All lesions changed in a symmetric manner and 91 (75.2%) displayed a decrease in the density of peripheral globules over time.

Conclusions and Relevance

Nevi displaying a peripheral globular pattern enlarged symmetrically with apparent growth cessation occurring during a span of 4 to 5 years. Our results reiterate the important concept that not all growth is associated with malignancy.

Intraoperative imaging during Mohs surgery with reflectance confocal microscopy: initial clinical experience

Mohs surgery for the removal of nonmelanoma skin cancers (NMSCs) is performed in stages, while being guided by the examination for residual tumor with frozen pathology. However, preparation of frozen pathology at each stage is time consuming and labor intensive. Real-time intraoperative reflectance confocal microscopy(RCM), combined with video mosaicking, may enable rapid detection of residual tumor directly in the surgical wounds on patients. We report our initial experience on 25 patients, using aluminum chloride for nuclear contrast. Imaging was performed in quadrants in the wound to simulate the Mohs surgeon’s examination of pathology. Images and videos of the epidermal and dermal margins were found to be of clinically acceptable quality. Bright nuclear morphology was identified at the epidermal margin and detectable in residual NMSC tumors. The presence of residual tumor and normal skin features could be detected in the peripheral and deep dermal margins. Intraoperative RCM imaging may enable detection of residual tumor directly on patients during Mohs surgery, and may serve as an adjunct for frozen pathology. Ultimately, for routine clinical utility, a stronger tumor-to-dermis contrast may be necessary, and also a smaller microscope with an automated approach for imaging in the entire wound in a rapid and controlled manner.

Morphogenesis and three-dimensional movement of the stomach during the human embryonic period

The stomach develops as the local widening of the foregut after Carnegie stage (CS) 13 that moves in a dramatic and dynamic manner during the embryonic period. Using the magnetic resonance images of 377 human embryos, we present the morphology, morphometry, and three-dimensional movement of the stomach during CS16 and CS23. The stomach morphology revealed stage-specific features. The angular incisura and the cardia were formed at CS18. The change in the angular incisura angle was approximately 90° during CS19 and CS20, and was <90° after CS 21. The prominent formations of the fundus and the pylorus differentiate at around CS20. Morphometry of the stomach revealed that the stomach gradually becomes "deflected" during development. The stomach may appear to move to the left laterally and caudally due to its deflection and differential growth. The track of the reference points in the stomach may reflect the visual three-dimensional movement. The movement of point M, representing the movement of the greater curvature, was different from that of points C (cardia) and P (pyloric antrum). The P and C were located just around the midsagittal plane in all the stages observed. Point M moved in the caudal-left lateral direction until CS22. Moreover, the vector CP does not rotate around the dorsoventral axis, as widely believed, but around the transverse axis. The plane CPM rotated mainly around the longitudinal axis. The data obtained will be useful for prenatal diagnosis in the near future.