Single color virtual H&E staining with In-and-Out Net.

Virtual staining streamlines traditional staining procedures by digitally generating stained images from unstained or differently stained images. While conventional staining methods involve time-consuming chemical processes, virtual staining offers an efficient and low infrastructure alternative. Leveraging microscopy-based techniques, such as confocal microscopy, researchers can expedite tissue analysis without the need for physical sectioning. However, interpreting grayscale or pseudo-color microscopic images remains a challenge for pathologists and surgeons accustomed to traditional histologically stained images. To fill this gap, various studies explore digitally simulating staining to mimic targeted histological stains. This paper introduces a novel network, In-and-Out Net, specifically designed for virtual staining tasks. Based on Generative Adversarial Networks (GAN), our model efficiently transforms Reflectance Confocal Microscopy (RCM) images into Hematoxylin and Eosin (H&E) stained images. We enhance nuclei contrast in RCM images using aluminum chloride preprocessing for skin tissues. Training the model with virtual H\&E labels featuring two fluorescence channels eliminates the need for image registration and provides pixel-level ground truth. Our contributions include proposing an optimal training strategy, conducting a comparative analysis demonstrating state-of-the-art performance, validating the model through an ablation study, and collecting perfectly matched input and ground truth images without registration. In-and-Out Net showcases promising results, offering a valuable tool for virtual staining tasks and advancing the field of histological image analysis.

CAPABLE: A Scoring System Utilizing Patient-Reported Measures to Evaluate Patient Experience After Mohs Surgery.

BACKGROUND: Patient experience metrics are gaining prominence in health care. We introduce the CAPABLE survey to assess postoperative experiences of Mohs surgery patients. OBJECTIVE: We sought to determine whether CAPABLE scores aligned with overall patient satisfaction in Mohs surgery. METHODS: This was a cross-sectional, survey-based study of patients presenting for their first postoperative visit after Mohs surgery. The CAPABLE survey included questions on postoperative instructions, activity limitations, pain control, provider accessibility, and bleeding, followed by 2 overall satisfaction questions taken from the Outpatient and Ambulatory Surgery Consumer Assessment of Healthcare Providers and Systems survey. The pilot study took place at the University of Texas Dell Medical School (DMS), followed by a validation study ( n = 206) at DMS and Oregon Health and Science University (OHSU). We assessed for correlations between CAPABLE scores and overall satisfaction. RESULTS: In the pilot study ( n = 137), overall CAPABLE scores and scores of individual CAPABLE components correlated positively with overall satisfaction.In the multisite validation study ( n = 206) spanning DMS and OHSU, CAPABLE scores correlated positively with overall satisfaction. CONCLUSION: The CAPABLE survey is a concise tool for assessing specific, actionable components of the postoperative patient experience in Mohs surgery, while correlating with overall patient satisfaction.

Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma.

SIGNIFICANCE: Raman spectroscopy (RS) provides an automated approach for assisting Mohs micrographic surgery for skin cancer diagnosis; however, the specificity of RS is limited by the high spectral similarity between tumors and normal tissues structures. Reflectance confocal microscopy (RCM) provides morphological and cytological details by which many features of epidermis and hair follicles can be readily identified. Combining RS with deep-learning-aided RCM has the potential to improve the diagnostic accuracy of RS in an automated fashion, without requiring additional input from the clinician. AIM: The aim of this study is to improve the specificity of RS for detecting basal cell carcinoma (BCC) using an artificial neural network trained on RCM images to identify false positive normal skin structures (hair follicles and epidermis). APPROACH: Our approach was to build a two-step classification model. In the first step, a Raman biophysical model that was used in prior work classified BCC tumors from normal tissue structures with high sensitivity. In the second step, 191 RCM images were collected from the same site as the Raman data and served as inputs for two ResNet50 networks. The networks selected the hair structure and epidermis images, respectively, within all images corresponding to the positive predictions of the Raman biophysical model with high specificity. The specificity of the BCC biophysical model was improved by moving the Raman spectra corresponding to these selected images from false positive to true negative. RESULTS: Deep-learning trained on RCM images removed 52% of false positive predictions from the Raman biophysical model result while maintaining a sensitivity of 100%. The specificity was improved from 84.2% using Raman spectra alone to 92.4% by integrating Raman spectra with RCM images. CONCLUSIONS: Combining RS with deep-learning-aided RCM imaging is a promising tool for guiding tumor resection surgery.

Association of Tumor Characteristics With Insurance Type Among Patients Undergoing Mohs Micrographic Surgery for Nonmelanoma Skin Cancer.

Importance: Little is known about the association between insurance type and tumor or treatment characteristics among patients undergoing Mohs micrographic surgery (MMS) for nonmelanoma skin cancer (NMSC). Objective: To investigate whether there are differences in tumor and treatment characteristics among patients undergoing MMS for NMSC by insurance type. Design, Setting, and Participants: This retrospective cohort study included patients with NMSC who presented for surgery at an academic MMS practice between May 2017 and May 2019. Main Outcomes and Measures: Preoperative and postoperative tumor diameters, number of MMS stages, type of closure, and number of high-risk tumors were compared based on insurance type among uninsured and underinsured patients and those with private insurance, Medicare, and Veterans Affairs (VA) insurance. Results: A total of 1397 patients with NMSC (978 [70%] male; mean [SD] age, 68.5 [12.4] years) underwent 1916 MMS procedures. Of these patients, 868 (45%) had Medicare, 570 (30%) had private insurance, 299 (16%) had VA insurance, and 179 (9%) were treated at a safety net clinic or were uninsured. Compared with patients with private insurance, uninsured and underinsured patients had significantly larger preoperative tumor bed diameters (difference, 28%; 95% CI, 14%-43%; P < .001) and postoperative defect sizes (difference, 28%, 95% CI, 16%-41%; P < .001). Patients with Medicare and VA insurance did not have significantly different preoperative tumor bed diameters compared with patients with private insurance. Patients with VA insurance had larger postoperative defect sizes than patients with private insurance (difference, 12%; 95% CI, 2%-23%; P = .02). The number of MMS stages and type of closure did not significantly differ based on insurance type. Conclusions and Relevance: In this cohort study of patients undergoing MMS for NMSC, larger preoperative tumor and postoperative defect sizes were associated with being uninsured or underinsured compared with privately insured. Future studies are required to determine why these differences exist to deliver optimal care to all patients.

Consensus-Based Recommendations on the Prevention of Squamous Cell Carcinoma in Solid Organ Transplant Recipients: A Delphi Consensus Statement.

IMPORTANCE: There is a paucity of evidence to guide physicians regarding prevention strategies for cutaneous squamous cell carcinoma (CSCC) in solid organ transplant recipients (SOTRs). OBJECTIVE: To examine the development and results of a Delphi process initiated to identify consensus-based medical management recommendations for prevention of CSCC in SOTRs. EVIDENCE REVIEW: Dermatologists with more than 5 years' experience treating SOTRs were invited to participate. A novel actinic damage and skin cancer index (AD-SCI), consisting of 6 ordinal stages corresponding to an increasing burden of actinic damage and CSCC, was used to guide survey design. Three sequential web-based surveys were administered from January 1, 2019, to December 31, 2020. Pursuant to Delphi principles, respondents thoroughly reviewed all peer responses between rounds. Supplemental questions were also asked to better understand panelists' rationale for their responses. FINDINGS: The Delphi panel comprised 48 dermatologists. Respondents represented 13 countries, with 27 (56%) from the US. Twenty-nine respondents (60%) were Mohs surgeons. Consensus was reached with 80% or higher concordance among respondents when presented with a statement, question, or management strategy pertaining to prevention of CSCC in SOTRs. A near-consensus category of 70% to less than 80% concordance was also defined. The AD-SCI stage-based recommendations were established if consensus or near-consensus was achieved. The panel was able to make recommendations for 5 of 6 AD-SCI stages. Key recommendations include the following: cryotherapy for scattered actinic keratosis (AK); field therapy for AK when grouped in 1 anatomical area, unless AKs are thick in which case field therapy and cryotherapy were recommended; combination lesion directed and field therapy with fluorouracil for field cancerized skin; and initiation of acitretin therapy and discussion of immunosuppression reduction or modification for patients who develop multiple skin cancers at a high rate (10 CSCCs per year) or develop high-risk CSCC (defined by a tumor with approximately ≥20% risk of nodal metastasis). No consensus recommendation was achieved for SOTRs with a first low risk CSCC. CONCLUSIONS AND RELEVANCE: Physicians may consider implementation of panel recommendations for prevention of CSCC in SOTRs while awaiting high-level-of-evidence data. Additional clinical trials are needed in areas where consensus was not reached.

Imaging sub-diffuse optical properties of cancerous and normal skin tissue using machine learning-aided spatial frequency domain imaging.

SIGNIFICANCE: Sub-diffuse optical properties may serve as useful cancer biomarkers, and wide-field heatmaps of these properties could aid physicians in identifying cancerous tissue. Sub-diffuse spatial frequency domain imaging (sd-SFDI) can reveal such wide-field maps, but the current time cost of experimentally validated methods for rendering these heatmaps precludes this technology from potential real-time applications. AIM: Our study renders heatmaps of sub-diffuse optical properties from experimental sd-SFDI images in real time and reports these properties for cancerous and normal skin tissue subtypes. APPROACH: A phase function sampling method was used to simulate sd-SFDI spectra over a wide range of optical properties. A machine learning model trained on these simulations and tested on tissue phantoms was used to render sub-diffuse optical property heatmaps from sd-SFDI images of cancerous and normal skin tissue. RESULTS: The model accurately rendered heatmaps from experimental sd-SFDI images in real time. In addition, heatmaps of a small number of tissue samples are presented to inform hypotheses on sub-diffuse optical property differences across skin tissue subtypes. CONCLUSION: These results bring the overall process of sd-SFDI a fundamental step closer to real-time speeds and set a foundation for future real-time medical applications of sd-SFDI such as image guided surgery.

Toward automated assessment of mole similarity on dermoscopic images.

Purpose: Current skin cancer detection relies on dermatologists' visual assessments of moles directly or dermoscopically. Our goal is to show that our similarity assessment algorithm on dermoscopic images can perform as well as a dermatologist's assessment. Approach: Given one target mole and two other moles from the same patient, our model determines which mole is more similar to the target mole. Similarity was quantified as the Euclidean distance in a feature space designed to capture mole properties such as size, shape, and color. We tested our model on 18 patients, each of whom had at least five moles, and compared the model assessments of mole similarity with that of three dermatologists. Fleiss' Kappa agreement coefficients and iteration tests were used to evaluate the agreement in similarity assessment among dermatologists and our model. Results: With the selected features of size, entropy (color variation), and cluster prominence (asymmetry), our algorithm's similarity assessments agreed moderately with the similarity assessments of dermatologists. The mean Kappa of 1000 iteration tests was 0.49 ( confidence interval ( CI ) = [ 0.23 , 0.74 ] ) when comparing three dermatologists and our model, which is comparable to the agreement in similarity assessment among the dermatologists themselves (the mean Kappa of 1000 iteration tests for three dermatologists was 0.48, CI = [ 0.19 , 0.77 ] .) By contrast, the mean Kappa was 0.22 ( CI = [ - 0.00 , 0.43 ] ) when comparing the similarity assessments of three dermatologists and random guesses. Conclusions: Our study showed that our image feature-engineering-based algorithm can effectively assess the similarity of moles as dermatologists do. Such a similarity assessment could serve as the foundation for computer-assisted intra-patient evaluation of moles.

Successful treatment of recurrent advanced cutaneous squamous cell carcinoma with cemiplimab.

A 90-year-old man presented for evaluation of an incompletely excised squamous cell carcinoma above the right brow, with pathology demonstrating tumor extending to resection margins with perineural invasion. A cord of tumor was noted to extend past the orbital rim and towards the posterior orbit. Mohs excision versus coordinated resection and reconstruction with colleagues in the head and neck surgery and craniofacial plastic surgery departments were considered. Multidisciplinary consensus was to proceed with radical resection in the operating room followed by adjuvant radiation therapy. One year later, the patient presented to our Mohs unit with a 3cm eroded multinodular plaque. Following an in-depth discussion regarding the options of further surgery versus systemic treatment, the patient and his family opted to pursue consultation with a medical oncology consultant to discuss restaging and potential systemic therapy. A PET scan with concurrent CT revealed a hypermetabolic right temporal scalp mass without evidence of bony invasion or extension into the nodal basin. Immunotherapy with cemiplimab was started at a dose of 350mg IV every three weeks. After 7 cycles, the patient demonstrated complete clinical resolution with a repeat PET scan showing interval near resolution of abnormal metabolic activity.

Safety of Intradermal/Subcutaneous Lidocaine With Epinephrine Use in Dermatologic Surgery.

BACKGROUND: Recently, the safety of lidocaine plus epinephrine use in outpatient surgery has come under scrutiny despite its long history of use in outpatient dermatologic procedures and surgeries. OBJECTIVE: To assess the frequency of crash cart and other emergency interventions during Mohs micrographic surgery when lidocaine plus epinephrine is used as a local anesthetic and evaluate patient comorbidities associated with these events. MATERIALS AND METHODS: A retrospective chart review was conducted in an outpatient Mohs micrographic surgery clinic. RESULTS: One thousand one hundred twenty-seven Mohs cases were reviewed from the period of March 2015 to June 2016 with 864 meeting the inclusion criteria of patient weight, medical history, and amount of lidocaine administered recorded. No adverse events requiring emergency intervention with a crash cart or transfer to the emergency department occurred despite a patient population with advanced age and a wide range of comorbidities. CONCLUSION: No serious adverse events requiring emergency intervention were associated with lidocaine with epinephrine doses administered below the Food and Drug Administration recommended maximum. The authors did not find evidence from this study or after a literature search to support the requirement for a crash cart and other emergency equipment to be present during procedures.

Superpixel Raman spectroscopy for rapid skin cancer margin assessment.

Spontaneous Raman micro-spectroscopy has been demonstrated great potential in delineating tumor margins; however, it is limited by slow acquisition speed. We describe a superpixel acquisition approach that can expedite acquisition between ~×100 and ×10 000, as compared to point-by-point scanning by trading off spatial resolution. We present the first demonstration of superpixel acquisition on rapid discrimination of basal cell carcinoma tumor from eight patients undergoing Mohs micrographic surgery. Results have been demonstrated high discriminant power for tumor vs normal skin based on the biochemical differences between nucleus, collagen, keratin and ceramide. We further perform raster-scanned superpixel Raman imaging on positive and negative margin samples. Our results indicate superpixel acquisition can facilitate the use of Raman microspectroscopy as a rapid and specific tool for tumor margin assessment.

Initial skin cancer screening for solid organ transplant recipients in the United States: Delphi method development of expert consensus guidelines.

Skin cancer is the most common malignancy affecting solid organ transplant recipients (SOTR), and SOTR experience increased skin cancer-associated morbidity and mortality. There are no formal multidisciplinary guidelines for skin cancer screening after transplant, and current practices are widely variable. We conducted three rounds of Delphi method surveys with a panel of 84 U.S. dermatologists and transplant physicians to establish skin cancer screening recommendations for SOTR. The transplant team should risk stratify SOTR for screening, and dermatologists should perform skin cancer screening by full-body skin examination. SOTR with a history of skin cancer should continue regular follow-up with dermatology for skin cancer surveillance. High-risk transplant patients include thoracic organ recipients, SOTR age 50 and above, and male SOTR. High-risk Caucasian patients should be screened within 2 years after transplant, all Caucasian, Asian, Hispanic, and high-risk African American patients should be screened within 5 years after transplant. No consensus was reached regarding screening for low-risk African American SOTR. We propose a standardized approach to skin cancer screening in SOTR based on multidisciplinary expert consensus. These guidelines prioritize and emphasize the need for screening for SOTR at greatest risk for skin cancer.

Biophysical basis of skin cancer margin assessment using Raman spectroscopy.

Achieving adequate margins during tumor margin resection is critical to minimize the recurrence rate and maximize positive patient outcomes during skin cancer surgery. Although Mohs micrographic surgery is by far the most effective method to treat nonmelanoma skin cancer, it can be limited by its inherent required infrastructure, including time-consuming and expensive on-site histopathology. Previous studies have demonstrated that Raman spectroscopy can accurately detect basal cell carcinoma (BCC) from surrounding normal tissue; however, the biophysical basis of the detection remained unclear. Therefore, we aim to explore the relevant Raman biomarkers to guide BCC margin resection. Raman imaging was performed on skin tissue samples from 30 patients undergoing Mohs surgery. High correlations were found between the histopathology and Raman images for BCC and primary normal structures (including epidermis, dermis, inflamed dermis, hair follicle, hair shaft, sebaceous gland and fat). A previously developed model was used to extract the biochemical changes associated with malignancy. Our results showed that BCC had a significantly different concentration of nucleus, keratin, collagen, triolein and ceramide compared to normal structures. The nucleus accounted for most of the discriminant power (90% sensitivity, 92% specificity - balanced approach). Our findings suggest that Raman spectroscopy is a promising surgical guidance tool for identifying tumors in the resection margins.

Raman biophysical markers in skin cancer diagnosis.

Raman spectroscopy (RS) has demonstrated great potential for in vivo cancer screening; however, the biophysical changes that occur for specific diagnoses remain unclear. We recently developed an inverse biophysical skin cancer model to address this issue. Here, we presented the first demonstration of in vivo melanoma and nonmelanoma skin cancer (NMSC) detection based on this model. We fit the model to our previous clinical dataset and extracted the concentration of eight Raman active components in 100 lesions in 65 patients diagnosed with malignant melanoma (MM), dysplastic nevi (DN), basal cell carcinoma, squamous cell carcinoma, and actinic keratosis. We then used logistic regression and leave-one-lesion-out cross validation to determine the diagnostically relevant model components. Our results showed that the biophysical model captures the diagnostic power of the previously used statistical classification model while also providing the skin's biophysical composition. In addition, collagen and triolein were the most relevant biomarkers to represent the spectral variances between MM and DN, and between NMSC and normal tissue. Our work demonstrates the ability of RS to reveal the biophysical basis for accurate diagnosis of different skin cancers, which may eventually lead to a reduction in the number of unnecessary excisional skin biopsies performed.

Raman active components of skin cancer.

Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.