Clinician Telemedicine Perceptions During the COVID-19 Pandemic.

Background: Telemedicine utilization increased exponentially due to the coronavirus disease 2019 (COVID-19) pandemic. As a result, most clinicians now have experience with telemedicine. Questions/Purposes: We studied factors independently associated with a clinician desiring to continue telemedicine services after the COVID-19 pandemic. Secondarily, we sought factors independently associated with clinician satisfaction with the quality of care provided through telemedicine and factors associated with telemedicine platform preference by clinicians. Methods: A large multispecialty medical group of physicians were invited to complete a survey, including demographics, telemedicine experience, satisfaction with various elements of telemedicine encounters, desired features in a telemedicine platform, personality traits, and preferences. A total of 220 complete responses were analyzed. Results: A desire to continue offering telemedicine visits after the COVID-19 pandemic was independently associated with a higher satisfaction with the quality of telemedicine care, endorsement of the ease of performing a physical examination with telemedicine, belief that adaptability is an important element of being a clinician, and less preference for in-person work meetings over virtual meetings. Higher satisfaction with the quality of telemedicine care was associated with belief that adaptability is an important element of being a clinician, clinicians who identify as being more perceiving (value flexibility) than judging (value organization), providers from relatively urban counties, and those with less preference for in-person work meetings over virtual meetings. Clinicians ranked ease of use for patients and physicians as the most important features of telemedicine platforms. Conclusions: The observed association of clinician personality and interpersonal preferences with the appeal, satisfaction, and perceived effectiveness of telemedicine merit additional study. Early implementation of telemedicine might be easiest with clinicians that take pride in their adaptability and value a technology-based workstyle.

Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening.

A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a "second opinion" for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

The Other Itch That Rashes: a Clinical and Therapeutic Approach to Pruritus and Skin Picking Disorders.

Patients with skin picking disorders (SPDs) have historically been an under recognized and under treated group. Originally classified an impulse control disorder, skin picking disorder is now considered under the obsessive-compulsive disorder (OCD) and obsessive-compulsive-related disorder (OCRD) spectrum. Workup of SPD concentrates on differentiating this condition from primary skin disorders, systemic conditions associated with pruritus, and psychocutaneous syndromes. It is important to first address any underlying pruritic disorders (if present) that may be a trigger to pick the skin. First-line treatment for SPD is cognitive behavioral therapy. When necessary, pharmacologic therapy can be helpful as well.

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.

Patients labeled with delusions of parasitosis compose a heterogenous group: a retrospective study from a referral center.

BACKGROUND: There are few diagnostic tools available to the dermatologist to help in the diagnosis of patients with delusions of parasitosis (DOP). OBJECTIVE: We sought to find differences in presentation and clinical course between patients who received a final diagnosis of DOP and those who received a final diagnosis of a primary medical condition or other psychiatric disorder. METHODS: We performed a retrospective chart review of patients referred with a diagnosis of DOP. Each patient received a final consensus diagnosis. RESULTS: In all, 47 patients were included in the study. Patients reporting bugs were more likely to be given a final diagnosis of delusional disorder or found to have a medical diagnosis, whereas patients noting fibers were more likely to have a somatoform disorder. A review of systems can be helpful in making a final diagnosis. Patients referred to the clinic for DOP were 300 times more likely to require a physician to contact the hospital's legal counsel compared with other patients in the practice. LIMITATIONS: The retrospective nature of the study resulted in limited laboratory testing and psychiatric evaluation in some patients. Many of the patients may have been inappropriately referred to the DOP clinic because of other psychiatric comorbidities. CONCLUSION: Patients referred to this practice as "delusional" had a heterogeneous final diagnosis. The chief symptom of the patient was predictive of the patient's final diagnosis. The use of written questionnaires may be helpful. These patients have a greatly increased risk of requiring the physician to seek legal counsel.

New world cutaneous leishmaniasis: obstacles in initiating treatment with sodium stibogluconate in 2 travelers from Texas.

New World cutaneous leishmaniasis (CL) is considered in the differential diagnosis for patients with nonhealing ulcers and a history of travel to high-risk areas. For patients at risk for progression to mucocutaneous leishmaniasis, first-line treatment in the United States entails the use of sodium stibogluconate (SSG), which is obtained from the Centers for Disease Control and Prevention (CDC) under an investigational drug protocol. We report 2 cases of New World CL in travelers to endemic areas who were diagnosed and treated with SSG. These cases demonstrate the logistics of coordinating with the CDC to definitively diagnose New World CL and initiate the necessary treatment.

The utility of teledermatology in the evaluation of skin lesions.

INTRODUCTION: Past studies have shown mixed results about the accuracy of store-and-forward (SAF) teledermatology in the evaluation of skin lesions. The objective of this study is to determine the accuracy of SAF teledermatology in the diagnosis of skin lesions and biopsy decision compared to in-person clinical evaluation. METHODS: Histories and photographs of skin lesions gathered at clinic visits were sent as SAF consults to teledermatologists, whose diagnoses and biopsy decisions were recorded and compared statistically to the clinic data.Results and Discussion: We enrolled 206 patients with 308 lesions in the study. The study population was composed of 50% males (n = 104), and most patients were white (n = 179, 87%) and not Hispanic/Latino (n = 167, 81%). There was good concordance for biopsy decision between the clinic dermatologist (CD) and teledermatologist (TD) (Cohen's kappa (κ) = 0.51), which did not significantly differ when melanocytic lesions were excluded (κ = 0.54). The sensitivity and specificity of teledermatology based on biopsy decision was 0.71 and 0.85, respectively. Overall concordance in first diagnosis between the CD and TD was good (κ = 0.60). While there was no difference between CD and TD in proportion of correct diagnoses compared to histopathology, two skin cancers presentations were missed by TD. Study limitations included sample size, enrolment bias and differing amounts of teledermatologist case experience. Teledermatology has good concordance in diagnosis and biopsy decision when compared to clinic dermatology. Teledermatology may be utilized in the evaluation of skin lesions to expand access to dermatologic care.

Successful treatment of patients previously labeled as having "delusions of parasitosis" with antidepressant therapy.

Delusions of parasitosis (DOP) is a somatic subtype of delusional disorder, also known as monosymptomatic hypochondriacal psychosis. The management of DOP has been discussed extensively in the medical literature. Patients with suspected DOP have a broad differential diagnosis, including skin-based or systemic medical conditions and several kinds of psychiatric disease. However, there are many patients who have been labeled with DOP but do not meet the diagnostic criteria or who present with additional somatic complaints. These cases are a unique therapeutic challenge for dermatologists and psychiatrists alike and have not been thoroughly studied or reported. We present a patient referred for DOP who benefited substantially with antidepressant therapy.

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.

Acute methotrexate toxicity seen as plaque psoriasis ulceration and necrosis: A diagnostic clue.

In addition to the well-known signs of methotrexate toxicity, rare cutaneous side effects have been described. These cutaneous signs may provide a diagnostic clue into the diagnosis of toxicity as well as facilitate early and aggressive therapy. We describe the case of a 37-year-old male, with a diagnosis of psoriasis, who developed characteristic signs and symptoms of acute methotrexate toxicity after receiving an unknown amount of intravenous methotrexate. The patient experienced a distinct change in the morphology of his existing psoriatic plaques, which became ulcerated and necrotic in the week following the methotrexate injection. Shortly after the development of cutaneous erosions, the patient developed pancytopenia, which ultimately led to his death. Ulceration and necrosis of cutaneous psoriasis plaques may serve as a herald for the impending development of life-threatening pancytopenia in patients with acute methotrexate toxicity.

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.

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.

Design and validation of a clinical instrument for spectral diagnosis of cutaneous malignancy.

We report a probe-based portable and clinically compatible instrument for the spectral diagnosis of melanoma and nonmelanoma skin cancers. The instrument combines two modalities--diffuse reflectance and intrinsic fluorescence spectroscopy--to provide complementary information regarding tissue morphology, function, and biochemical composition. The instrument provides a good signal-to-noise ratio for the collected reflectance and laser-induced fluorescence spectra. Validation experiments on tissue phantoms over a physiologically relevant range of albedos (0.35-0.99) demonstrate an accuracy of close to 10% in determining scattering, absorption and fluorescence characteristics. We also demonstrate the ability of our instrument to collect in vivo diffuse reflectance and fluorescence measurements from clinically normal skin, dysplastic nevus, and malignant nonmelanoma skin cancer.

Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer.

BACKGROUND: Several research groups have demonstrated the non-invasive diagnostic potential of diffuse optical spectroscopy (DOS) and laser-induced fluorescence (LIF) techniques for early cancer detection. By combining both modalities, one can simultaneously measure quantitative parameters related to the morphology, function and biochemical composition of tissue and use them to diagnose malignancy. The objective of this study was to use a quantitative reflectance/fluorescence spectroscopic technique to determine the optical properties of normal skin and non-melanoma skin cancers and the ability to accurately classify them. An additional goal was to determine the ability of the technique to differentiate non-melanoma skin cancers from normal skin. STUDY DESIGN: The study comprised 48 lesions measured from 40 patients scheduled for a biopsy of suspected non-melanoma skin cancers. White light reflectance and laser-induced fluorescence spectra (wavelength range = 350-700 nm) were collected from each suspected lesion and adjacent clinically normal skin using a custom-built, optical fiber-based clinical instrument. After measurement, the skin sites were biopsied and categorized according to histopathology. Using a quantitative model, we extracted various optical parameters from the measured spectra that could be correlated to the physiological state of tissue. RESULTS: Scattering from cancerous lesions was significantly lower than normal skin for every lesion group, whereas absorption parameters were significantly higher. Using numerical cut-offs for our optical parameters, our clinical instrument could classify basal cell carcinomas with a sensitivity and specificity of 94% and 89%, respectively. Similarly, the instrument classified actinic keratoses and squamous cell carcinomas with a sensitivity of 100% and specificity of 50%. CONCLUSION: The measured optical properties and fluorophore contributions of normal skin and non-melanoma skin cancers are significantly different from each other and correlate well with tissue pathology. A diagnostic algorithm that combines these extracted properties holds promise for the potential non-invasive diagnosis of skin cancer.

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.

Successful Use of the 308-nm Excimer Laser in Early Patch Stage Mycosis Fungoides.

Introduction: Mycosis fungoides (MF), a type of cutaneous T-cell lymphoma, is a rare condition with a variety of treatment options. A frequently utilized method in the treatment of early-stage MF is phototherapy. Full body phototherapy can be associated with photoaging of the skin and an increased risk of developing skin cancer. Targeted phototherapy, with a 308-nm excimer laser, may be just as effective and of a lower risk. This makes it especially useful in the treatment of patients with dysplastic nevi (DN) or other conditions which can put them at a higher risk of developing skin cancer. There are currently limited data on the treatment of early-stage MF with an excimer laser. Case Report: This study reports on a 43-year-old female patient presented to the clinic with early-stage (Ia) MF. Given her history of DN, she wished to pursue targeted phototherapy with an excimer laser. Localized light treatment was performed via a 308-nm excimer laser, 3 times weekly, for a total of 17 treatments to affected lesions. Following excimer laser treatment, she had a clinical resolution of her patches. On the follow-up clinic visits, she maintained her excellent response 12 months out. Conclusion: Targeted phototherapy with a 308-nm excimer laser may be a safer and equally effective alternative to generalized phototherapy in the treatment of early-stage MF. This case report demonstrates its efficacy and advantages over traditional generalized phototherapy.

Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis.

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.

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.