Integration of a deep learning basal cell carcinoma detection and tumor mapping algorithm into the Mohs micrographic surgery workflow and effects on clinical staffing: A simulated, retrospective study.

Background: Artificial intelligence (AI) enabled tools have been proposed as 1 solution to improve health care delivery. However, research on downstream effects of AI integration into the clinical workflow is lacking. Objective: We aim to analyze how integration of an automated basal cell carcinoma detection and tumor mapping algorithm in a Mohs micrographic surgery unit impacts the work efficiency of clinical and laboratory staff. Methods: Slide, staff, and histotechnician waiting times were analyzed over a 20-day period in a Mohs micrographic surgery unit. A simulated AI workflow was created and the time differences between the real and simulated workflows were compared. Results: Simulated nonautonomous algorithm integration led to savings of 35.6% of slide waiting time, 18.4% of staff waiting time, and 18.6% of histotechnician waiting time per day. Algorithm integration on days with increased reconstruction complexity resulted in the greatest time savings. Limitations: One Mohs micrographic surgery unit was analyzed and simulated AI integration was performed retrospectively. Conclusions: AI integration results in reduced staff waiting times, enabling increased productivity and a streamlined clinical workflow. Schedules containing surgical cases with either increased repair complexity or numerous tumor removal stages stand to benefit most. However, significant logistical challenges must be addressed before broad adoption into clinical practice is realistic.

Nonequilibrium Transport in a Superfluid Josephson Junction Chain: Is There Negative Differential Conductivity?

We consider the far-from-equilibrium quantum transport dynamics in a 1D Josephson junction chain of multimode Bose-Einstein condensates. We develop a theoretical model to examine the experiment of Labouvie et al. [Phys. Rev. Lett. 115, 050601 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.050601], wherein the phenomenon of negative differential conductivity (NDC) was reported in the refilling dynamics of an initially depleted site within the chain. We demonstrate that a unitary c-field description can quantitatively reproduce the experimental results over the full range of tunnel couplings, and requires no fitted parameters. With a view toward atomtronic implementations, we further demonstrate that the filling is strongly dependent on spatial phase variations stemming from quantum fluctuations. Our findings suggest that the interpretation of the device in terms of NDC is invalid outside of the weak coupling regime. Within this restricted regime, the device exhibits a hybrid behavior of NDC and the ac Josephson effect. A simplified circuit model of the device will require an approach tailored to atomtronics that incorporates quantum fluctuations.

A shared neoantigen vaccine combined with immune checkpoint blockade for advanced metastatic solid tumors: phase 1 trial interim results.

Therapeutic vaccines that elicit cytotoxic T cell responses targeting tumor-specific neoantigens hold promise for providing long-term clinical benefit to patients with cancer. Here we evaluated safety and tolerability of a therapeutic vaccine encoding 20 shared neoantigens derived from selected common oncogenic driver mutations as primary endpoints in an ongoing phase 1/2 study in patients with advanced/metastatic solid tumors. Secondary endpoints included immunogenicity, overall response rate, progression-free survival and overall survival. Eligible patients were selected if their tumors expressed one of the human leukocyte antigen-matched tumor mutations included in the vaccine, with the majority of patients (18/19) harboring a mutation in KRAS. The vaccine regimen, consisting of a chimp adenovirus (ChAd68) and self-amplifying mRNA (samRNA) in combination with the immune checkpoint inhibitors ipilimumab and nivolumab, was shown to be well tolerated, with observed treatment-related adverse events consistent with acute inflammation expected with viral vector-based vaccines and immune checkpoint blockade, the majority grade 1/2. Two patients experienced grade 3/4 serious treatment-related adverse events that were also dose-limiting toxicities. The overall response rate was 0%, and median progression-free survival and overall survival were 1.9 months and 7.9 months, respectively. T cell responses were biased toward human leukocyte antigen-matched TP53 neoantigens encoded in the vaccine relative to KRAS neoantigens expressed by the patients' tumors, indicating a previously unknown hierarchy of neoantigen immunodominance that may impact the therapeutic efficacy of multiepitope shared neoantigen vaccines. These data led to the development of an optimized vaccine exclusively targeting KRAS-derived neoantigens that is being evaluated in a subset of patients in phase 2 of the clinical study. ClinicalTrials.gov registration: NCT03953235 .

Intraoperative margin assessment for basal cell carcinoma with deep learning and histologic tumor mapping to surgical site.

Successful treatment of solid cancers relies on complete surgical excision of the tumor either for definitive treatment or before adjuvant therapy. Intraoperative and postoperative radial sectioning, the most common form of margin assessment, can lead to incomplete excision and increase the risk of recurrence and repeat procedures. Mohs Micrographic Surgery is associated with complete removal of basal cell and squamous cell carcinoma through real-time margin assessment of 100% of the peripheral and deep margins. Real-time assessment in many tumor types is constrained by tissue size, complexity, and specimen processing / assessment time during general anesthesia. We developed an artificial intelligence platform to reduce the tissue preprocessing and histological assessment time through automated grossing recommendations, mapping and orientation of tumor to the surgical specimen. Using basal cell carcinoma as a model system, results demonstrate that this approach can address surgical laboratory efficiency bottlenecks for rapid and complete intraoperative margin assessment.

A deep learning algorithm to detect cutaneous squamous cell carcinoma on frozen sections in Mohs micrographic surgery: A retrospective assessment.

Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carcinomas (cSCC). Artificial intelligence technologies (AI) have previously demonstrated potential for facilitating rapid and complete tumour removal using intraoperative margin assessment for basal cell carcinoma. However, the varied morphologies of cSCC present challenges for AI margin assessment. The aim of this study was to develop and evaluate the accuracy of an AI algorithm for real-time histologic margin analysis of cSCC. To do this, a retrospective cohort study was conducted using frozen cSCC section slides. These slides were scanned and annotated, delineating benign tissue structures, inflammation and tumour to develop an AI algorithm for real-time margin analysis. A convolutional neural network workflow was used to extract histomorphological features predictive of cSCC. This algorithm demonstrated proof of concept for identifying cSCC with high accuracy, highlighting the potential for integration of AI into the surgical workflow. Incorporation of AI algorithms may improve efficiency and completeness of real-time margin assessment for cSCC removal, particularly in cases of moderately and poorly differentiated tumours/neoplasms. Further algorithmic improvement incorporating surrounding tissue context is necessary to remain sensitive to the unique epidermal landscape of well-differentiated tumours, and to map tumours to their original anatomical position/orientation.

Potential to Enhance Large Scale Molecular Assessments of Skin Photoaging through Virtual Inference of Spatial Transcriptomics from Routine Staining.

The advent of spatial transcriptomics technologies has heralded a renaissance in research to advance our understanding of the spatial cellular and transcriptional heterogeneity within tissues. Spatial transcriptomics allows investigation of the interplay between cells, molecular pathways, and the surrounding tissue architecture and can help elucidate developmental trajectories, disease pathogenesis, and various niches in the tumor microenvironment. Photoaging is the histological and molecular skin damage resulting from chronic/acute sun exposure and is a major risk factor for skin cancer. Spatial transcriptomics technologies hold promise for improving the reliability of evaluating photoaging and developing new therapeutics. Challenges to current methods include limited focus on dermal elastosis variations and reliance on self-reported measures, which can introduce subjectivity and inconsistency. Spatial transcriptomics offers an opportunity to assess photoaging objectively and reproducibly in studies of carcinogenesis and discern the effectiveness of therapies that intervene in photoaging and preventing cancer. Evaluation of distinct histological architectures using highly-multiplexed spatial technologies can identify specific cell lineages that have been understudied due to their location beyond the depth of UV penetration. However, the cost and interpatient variability using state-of-the-art assays such as the 10x Genomics Spatial Transcriptomics assays limits the scope and scale of large-scale molecular epidemiologic studies. Here, we investigate the inference of spatial transcriptomics information from routine hematoxylin and eosin-stained (H&E) tissue slides. We employed the Visium CytAssist spatial transcriptomics assay to analyze over 18,000 genes at a 50-micron resolution for four patients from a cohort of 261 skin specimens collected adjacent to surgical resection sites for basal cell and squamous cell keratinocyte tumors. The spatial transcriptomics data was co-registered with 40x resolution whole slide imaging (WSI) information. We developed machine learning models that achieved a macro-averaged median AUC and F1 score of 0.80 and 0.61 and Spearman coefficient of 0.60 in inferring transcriptomic profiles across the slides, and accurately captured biological pathways across various tissue architectures.

Concurrent Langerhans cell histiocytosis and acute myeloid leukemia: A rare presentation of a rare case.

A 72-year-old woman with no significant past medical history was admitted to the hospital for new-onset of leukocytosis with neutropenia, anemia, and thrombocytopenia, as well as a pruritic skin eruption. She was found to have acute myeloid leukemia (AML) with myelomonocytic differentiation. Her skin eruption consisted of widespread hemorrhagic crusted papules on the scalp and trunk. A skin biopsy was performed, which revealed a proliferation of mononuclear cells in the dermis with prominent epidermotropism and positive expression of CD1a and langerin (CD207), supporting a diagnosis of Langerhans cell histiocytosis (LCH). LCH is an uncommon proliferative disorder of activated Langerhans cells, which generally presents in children. In adults, it is exceptionally infrequent. Associated malignancies and rare reports of AML developing in subsequent years after an initial presentation of LCH have been described. Here we present an unusual concurrent presentation of LCH and AML in an adult.

Velopharyngeal Insufficiency Following Furlow Versus Straight Line Repair With Intravelar Veloplasty: A Single-institution Experience.

BACKGROUND: Measurements of postoperative velopharyngeal dysfunction (VPD) can be used to determine the efficacy of a palatoplasty operation. Hypernasality and audible nasal air emission are typical manifestations of VPD during speech. We aimed to longitudinally compare VPD outcomes in postpalatoplasty patients who underwent Furlow repair versus straight line repair with intravelar veloplasty (IVVP). Additionally, we examined the relationship between VPD outcomes and select pre-existing patient characteristics. METHODS: Retrospective chart review was performed to identify primary palatoplasty patients treated from April 2012 to March 2021. Variables collected included gender, syndromic status, primary language, Veau cleft type, type of speech assessment, age at time of surgery, degree of hypernasality, presence of audible nasal air emission, and overall adequacy of velopharyngeal function. Pearson χ2 test and multivariable t tests were used to analyze variables. Logistic regression was used to control for statistically significant variables. RESULTS: Of the 118 patients included, 38 received a Furlow procedure and 80 received a straight line with IVVP procedure. Audible nasal air emission was present in 57.3% of straight line with IVVP patients and 42.9% of Furlow patients, with no statistically significant difference between groups. Clinically significant hypernasality was present in 42.1% of straight line with IVVP patients and 22.9% of Furlow patients (P=0.05). Velopharyngeal function was classified as adequate in 63.5% of straight line with IVVP patients and 83.3% of Furlow patients (P=0.03). However, after stratifying by syndromic versus nonsyndromic status, there was no statistically significant difference between straight line with IVVP and Furlow patients for postoperative hypernasality and velopharyngeal function. CONCLUSIONS: This study suggests that there are no statistically significant differences between straight line with IVVP and Furlow palatoplasty techniques regarding speech outcomes including hypernasality, audible nasal air emission, and overall VP function. Furthermore, select patient characteristics such as gender, primary language, syndromic status, age at repair, and Veau cleft type do not significantly impact postoperative speech outcomes.

Exploring the Potential and Limitations of Chat Generative Pre-trained Transformer (ChatGPT) in Generating Board-Style Dermatology Questions: A Qualitative Analysis.

This article investigates the limitations of Chat Generative Pre-trained Transformer (ChatGPT), a language model developed by OpenAI, as a study tool in dermatology. The study utilized ChatPDF, an application that integrates PDF files with ChatGPT, to generate American Board of Dermatology Applied Exam (ABD-AE)-style questions from continuing medical education articles from the Journal of the American Board of Dermatology. A qualitative analysis of the questions was conducted by two board-certified dermatologists, assessing accuracy, complexity, and clarity. Out of 40 questions generated, only 16 (40%) were deemed accurate and appropriate for ABD-AE study preparation. The remaining questions exhibited limitations, including low complexity, lack of clarity, and inaccuracies. The findings highlight the challenges faced by ChatGPT in understanding the domain-specific knowledge required in dermatology. Moreover, the model's inability to comprehend the context and generate high-quality distractor options, as well as the absence of image generation capabilities, further hinders its usefulness. The study emphasizes that while ChatGPT may aid in generating simple questions, it cannot replace the expertise of dermatologists and medical educators in developing high-quality, board-style questions that effectively evaluate candidates' knowledge and reasoning abilities.

A deep learning algorithm to detect cutaneous squamous cell carcinoma on frozen sections in Mohs micrographic surgery: a retrospective assessment.

Importance: Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carcinomas (cSCC). Artificial intelligence technologies (AI) have previously demonstrated potential for facilitating rapid and complete tumor removal using intraoperative margin assessment for basal cell carcinoma. However, the varied morphologies of cSCC present challenges for AI margin assessment. Objective: To develop and evaluate the accuracy of an AI algorithm for real-time histologic margin analysis of cSCC. Design: A retrospective cohort study was conducted using frozen cSCC section slides and adjacent tissues. Setting: This study was conducted in a tertiary care academic center. Participants: Patients undergoing Mohs micrographic surgery for cSCC between January and March 2020. Exposures: Frozen section slides were scanned and annotated, delineating benign tissue structures, inflammation, and tumor to develop an AI algorithm for real-time margin analysis. Patients were stratified by tumor differentiation status. Epithelial tissues including epidermis and hair follicles were annotated for moderate-well to well differentiated cSCC tumors. A convolutional neural network workflow was used to extract histomorphological features predictive of cSCC at 50-micron resolution. Main Outcomes and Measures: The performance of the AI algorithm in identifying cSCC at 50-micron resolution was reported using the area under the receiver operating characteristic curve. Accuracy was also reported by tumor differentiation status and by delineation of cSCC from epidermis. Model performance using histomorphological features alone was compared to architectural features (i.e., tissue context) for well-differentiated tumors. Results: The AI algorithm demonstrated proof of concept for identifying cSCC with high accuracy. Accuracy differed by differentiation status, driven by challenges in separating cSCC from epidermis using histomorphological features alone for well-differentiated tumors. Consideration of broader tissue context through architectural features improved the ability to delineate tumor from epidermis. Conclusions and Relevance: Incorporating AI into the surgical workflow may improve efficiency and completeness of real-time margin assessment for cSCC removal, particularly in cases of moderately and poorly differentiated tumors/neoplasms. Further algorithmic improvement is necessary to remain sensitive to the unique epidermal landscape of well-differentiated tumors, and to map tumors to their original anatomical position/orientation. Future studies should assess the efficiency improvements and cost benefits and address other confounding pathologies such as inflammation and nuclei. Funding sources: JL is supported by NIH grants R24GM141194, P20GM104416 and P20GM130454. Support for this work was also provided by the Prouty Dartmouth Cancer Center development funds. Key Points: Question: How can the efficiency and accuracy of real-time intraoperative margin analysis for the removal of cutaneous squamous cell carcinoma (cSCC) be improved, and how can tumor differentiation be incorporated into this approach?Findings: A proof-of-concept deep learning algorithm was trained, validated, and tested on frozen section whole slide images (WSI) for a retrospective cohort of cSCC cases, demonstrating high accuracy in identifying cSCC and related pathologies. Histomorphology alone was found to be insufficient to delineate tumor from epidermis in histologic identification of well-differentiated cSCC. Incorporation of surrounding tissue architecture and shape improved the ability to delineate tumor from normal tissue.Meaning: Integrating artificial intelligence into surgical procedures has the potential to enhance the thoroughness and efficiency of intraoperative margin analysis for cSCC removal. However, accurately accounting for the epidermal tissue based on the tumor's differentiation status requires specialized algorithms that consider the surrounding tissue context. To meaningfully integrate AI algorithms into clinical practice, further algorithmic refinement is needed, as well as the mapping of tumors to their original surgical site, and evaluation of the cost and efficacy of these approaches to address existing bottlenecks.

Conditional survival does not improve over time in metastatic castration-resistant prostate cancer patients undergoing docetaxel.

PURPOSE: To investigate the conditional overall survival (OS) of metastatic castration-resistant prostate cancer (mCRPC) patients receiving docetaxel chemotherapy. METHODS: We used deidentified patient-level data from the Prostate Cancer DREAM Challenge database and the control arm of the ENTHUSE 14 trial. We identified 2158 chemonaïve mCRPC patients undergoing docetaxel chemotherapy in the five randomized clinical trials. The 6-month conditional OS was calculated at times 0, 6, 12, 18, and 24 months from randomization. Survival curves of each group were compared using the log-rank test. Patients were then stratified into low- and high-risk groups based on the median predicted value of our recently published nomogram predicting OS in mCRPC patients. RESULTS: Nearly half (45%) of the study population was aged between 65 and 74 years. Median interquartile range prostate-specific antigen for the overall cohort was 83.2 (29.6-243) ng/mL, and 59% of patients had bone metastasis with or without lymph node involvement. The 6-month conditional survival rates at 0, 6, 12, 18, and 24 months for the entire cohort were 93% (95% confidence interval [CI]: 92-94), 82% (95% CI: 81-84), 76% (95% CI: 73-78), 75% (95% CI: 71-78), and 71% (95% CI: 65-76). These rates were, respectively, 96% (95% CI: 95-97), 92% (95% CI: 90-93), 84% (95% CI: 81-87), 81% (95% CI: 77-85), and 79% (95% CI: 72-84) in the low-risk group and 89% (95% CI: 87-91), 73% (95% CI: 70-76), 65% (95% CI: 60-69), 64% (95% CI: 58-70), and 58% (95% CI: 47-67) in the high-risk group. CONCLUSION: The conditional OS for patients undergoing docetaxel chemotherapy tends to plateau over time, with the main drop in conditional OS happening during the first year from initiating docetaxel treatment. That is the longer a patient survives, the more likely they are to survive further. This prognostic information could be a useful tool for a more accurate tailoring of both follow-up and therapies. PATIENT SUMMARY: In this report, we looked at the future survival in months of patients with metastatic castration resistant prostate cancer on chemotherapy who have already survived a certain period. We found that the longer time that a patient survives, the more likely they will continue to survive. We conclude that this information will help physicians tailor follow-ups and treatments for patients for a more accurate personalized medicine.

GRT-R910: a self-amplifying mRNA SARS-CoV-2 vaccine boosts immunity for ≥6 months in previously-vaccinated older adults.

SARS-CoV-2 has resulted in high levels of morbidity and mortality world-wide, and severe complications can occur in older populations. Humoral immunity induced by authorized vaccines wanes within 6 months, and frequent boosts may only offer transient protection. GRT-R910 is an investigational self-amplifying mRNA (samRNA)-based SARS-CoV-2 vaccine delivering full-length Spike and selected conserved non-Spike T cell epitopes. This study reports interim analyses for a phase I open-label dose-escalation trial evaluating GRT-R910 in previously vaccinated healthy older adults (NCT05148962). Primary endpoints of safety and tolerability were assessed. Most solicited local and systemic adverse events (AEs) following GRT-R910 dosing were mild to moderate and transient, and no treatment-related serious AEs were observed. The secondary endpoint of immunogenicity was assessed via IgG binding assays, neutralization assays, interferon-gamma ELISpot, and intracellular cytokine staining. Neutralizing antibody titers against ancestral Spike and variants of concern were boosted or induced by GRT-R910 and, contrasting to authorized vaccines, persisted through at least 6 months after the booster dose. GRT-R910 increased and/or broadened functional Spike-specific T cell responses and primed functional T cell responses to conserved non-Spike epitopes. This study is limited due to small sample size, and additional data from ongoing studies will be required to corroborate these interim findings.

Triggering multiple sclerosis at conception and early gestation: The variation in ultraviolet radiation is as important as its intensity.

Background and objectives: Medical science needs to further elucidate the role of ultraviolet radiation (UVR), geographic latitude, and the role of vitamin D in the autoimmune disease multiple sclerosis (MS). We separated several papers into categories out of the thousands published and used their conclusions to explore the relationship between UVR and MS. Relevance: MS is increasing in incidence, particularly in women where MS is two to three times that in men and particularly severe in African Americans. Methods: We collected UVR data at our observatory in Central Maine and calculated the average coefficient of variation (CVUVR) for each month for 15 years (2007-2021, inclusive). Results: The month of conception (MOC) is more important than the month of birth (MOB) in explaining how UVR triggers the variable genetic predisposition to MS. We hypothesize that the rapidly increasing CVUVR is important in preventing an increase in the activity of the vitamin D receptor (VDR) from August to December, which then requires a higher intensity of UVR later in life to suppress the immune system, therefore predisposing to more MS. Limitations: One observatory at about 44° latitude. Conclusions: While variation in UVR is important at the MOC if UVR exceeds a threshold (e.g., if the sunspot number equals or is greater than 90, usually at a solar cycle MAX, or at elevations above approximately 3,000 feet above sea level), the MS mitigating vitamin D-VDR mechanism is overwhelmed and the genotoxic effects of higher-intensity UVR promote MS in those with a genetic predisposition. What is new in this research: This paper offers a new concept in MS research.

Impact of preexisting opioid dependence on morbidity, length of stay, and inpatient cost of urological oncological surgery.

OBJECTIVES: To determine the incidence of preexisting opioid dependence in patients undergoing elective urological oncological surgery. In addition, to quantify the impact of preexisting opioid dependence on outcomes and cost of common urologic oncological procedures at a national level in the USA. METHODS: We used the National Inpatient Sample (NIS) to study 1,609,948 admissions for elective partial/radical nephrectomy, radical prostatectomy, and cystectomy procedures. Trends of preexisting opioid dependence were studied over 2003-2014. We use multivariable-adjusted analysis to compare opioid-dependent patients to those without opioid dependence (reference group) in terms of outcomes, namely major complications, length of stay (LOS), and total cost. RESULTS: The incidence of opioid dependence steadily increased from 0.6 per 1000 patients in 2003 to 2 per 1000 in 2014. Opioid-dependent patients had a significantly higher rate of major complications (18 vs 10%; p < 0.001) and longer LOS (4 days (IQR 2-7) vs 2 days (IQR 1-4); p < 0.001), when compared to the non-opioid-dependent counterparts. Opioid dependence also increased the overall cost by 48% (adjusted median cost $18,290 [IQR 12,549-27,715] vs. $12,383 [IQR 9225-17,494] in non-opioid-dependent, p < 0.001). Multivariable analysis confirmed the independent association of preexisting opioid dependence with major complications, length of stay in 4th quartile, and total cost in 4th quartile. CONCLUSIONS: The incidence of preexisting opioid dependence before elective urological oncology is increasing and is associated with adverse outcomes after surgery. There is a need to further understand the challenges associated with opioid dependence before surgery and identify and optimize these patients to improve outcomes.