Citations

Objective: This study aims to identify the perceived barriers and factors contributing to the slow adoption of robotic technology among coronary surgeons. Methods: We administered an anonymous online survey during the 2023 Society for Thoracic Surgeons (STS) Coronary Conference and included questions about factors associated with the lack of, or slow adoption of, robotics in coronary artery bypass surgery. Results: A total of 75 coronary surgeons completed the anonymous online survey. Of these respondents, 30 surgeons (39.4%) reported having more than 15 years of experience as independent coronary surgeons. Among the 71 surgeons (95%) who were not using robotic technology, the barriers to adoption (from most important to less important) were lack of skill or experience with robotic technology (mean score, 2.56 ± 1.84), followed by the lack of referral of patients with hybrid or single-vessel disease from cardiologists (2.81 ± 1.76), the need for more support and learning opportunities (e.g., hands-on courses, online courses; 3.44 ± 1.98), and more data to support the efficacy and safety of robotic coronary surgery (3.63 ± 2.22). Moreover, 38 surgeons (50%) expressed a willingness to consider robotic coronary surgery if industry provided appropriate devices such as stabilizers and automated anastomotic devices. Finally, 53 surgeons (69.7%) reported being unaware of the Thoracic Surgery Foundation and STS Advanced Robotic Cardiac Surgery Fellowship award with a coronary track. Conclusions: The findings from this survey identify the barriers to adopting robotic technology in coronary surgery. Addressing these barriers through targeted interventions could foster wider acceptance and use of robotic technology in coronary bypass surgery.

Objective: Cervical artery dissection (CeAD) was previously thought to be more common in men, but recent epidemiology studies show a disproportionate increase in the incidence of CeAD in women. In addition to sex-based differences in clinical presentation, there are unique biological risk factors for CeAD in women. Identifying risk factors for ischemic stroke in CeAD is crucial in individualizing treatment options. Herein, we utilized an inpatient cohort to investigate whether noncancerous gynecologic conditions or pregnancy are risk factors for ischemic stroke in CeAD. Methods: The National Inpatient Sample was queried from 2016 to 2020 for patients diagnosed with CeAD using the International Classification of Diseases, 10th edition, correction of the mean codes. Diagnoses of pregnancy/puerperium and noncancerous gynecologic conditions were identified. Among CeAD admissions, acute ischemic stroke (AIS) was also identified. Hierarchical, multivariable regression, adjusted for patient demographics and medical comorbidities, was conducted to assess factors associated with AIS. Results: A total of 34,925 women with CeAD were identified. Of these women, 2.1% were pregnant or up to six weeks postpartum, 1.3% had a noncancerous gynecologic condition, and 0.09% had both active pregnancy/puerperium and a noncancerous gynecologic condition. Noncancerous gynecologic conditions (odds ratio = 1.86, P = 0.012) were found to be an independent risk factor for AIS in CeAD but not active pregnancy/puerperium (odds ratio = 0.84, P = 0.34). Conclusion: In this national inpatient sample of female patients with CeAD, the presence of noncancerous gynecologic conditions is associated with an increased risk of AIS. Further studies are needed to validate this observation and help guide the best antithrombotic treatment decisions in this patient population.

ABSTRACT HLA‐B*07:528 differs from HLA‐B*07:02:01:26 by one nucleotide substitution in codon 286 (GGC>GAC) in exon 5.

Background and Objectives: Stroke is a leading cause of disability worldwide. Recent studies have suggested the feasibility and potential utility of remotely supervised transcranial direct current stimulation (RS-tDCS) to improve different types of impairments in various neurological conditions. This scoping review provides a critical appraisal of RS-tDCS as an adjunct therapy to enhance recovery after stroke. Materials and Methods: A comprehensive literature review was systematically conducted using PubMed through Nested Knowledge software. A supplementary search was conducted in Google Scholar. Two independent authors screened and identified related studies investigating RS-tDCS in patients with stroke from inception to February 2025. Results: Studies showed that RS-tDCS was safe, with only mild side effects. Additionally, it was feasible, with high adherence rates likely due to ease of use. Regarding efficacy, RS-tDCS preliminarily yielded improvements in upper- and lower-limb motor functions and increased language and cognitive performance. However, the studies were underpowered and heterogeneous, limiting generalization of findings. Conclusions: RS-tDCS is safe and feasible, affording beneficial effects in the motor, language, and cognitive functions of patients with post-stroke impairments. RS-tDCS has the potential to improve access and reduce disparities for post-stroke experimental treatments. However, adequately powered randomized trials are needed to further investigate the efficacy.

Background/Objectives: Pediatric rhabdomyosarcoma is a rare and poorly understood disease. Patients and parents can have varying experiences including barriers to care, time to treatment, and treatments offered. Here, we report on patient experiences regarding their care of pediatric rhabdomyosarcoma. Methods: Two separate online parent support groups were invited to participate in a survey. The survey included questions that sought to collect patient demographics, history of rhabdomyosarcoma, treatment timelines, and barriers to care. Results: A total of 215 surveys were completed. The average time from diagnosis to treatment was 12 days (SD = 14). Only 26% were offered fertility preservation prior to treatment. For patients with recurrence, an average of 75 days passed between detection of recurrence and treatment re-initiation. Patients traveled to centers with a dedicated sarcoma program in 52% of the cases. A total of 42% of parents sought a second opinion. Of those, the majority had to wait between one week and one month to be seen by another expert. Conclusions: The data collected from the survey suggests there are several opportunities to improve care among patients with pediatric rhabdomyosarcoma. Many patients may benefit from more efficient rhabdomyosarcoma referral networks, delivering patients to experts who can quickly begin multidisciplinary treatment.

Abstract Background Conventional proton dose calculation methods are either time‐ and resource‐intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade‐off between computational efficiency and accuracy highlights the need for improved dose calculation approaches in clinical settings. Purpose This study aims to develop a deep‐learning‐based model that calculates dose‐to‐water ( D W ) and dose‐to‐medium ( D M ) using patient anatomy and proton spot map (PSM), achieving approaching MC‐level accuracy with significantly reduced computation time. Additionally, the study seeks to generalize the model to different treatment sites using transfer learning. Methods A SwinUNetr model was developed using 259 four‐field prostate proton stereotactic body radiation therapy (SBRT) plans to calculate patient‐specific D W and D M distributions from CT and projected PSM (PPSM). The PPSM was created by projecting PSM into the CT scans using spot coordinates, stopping power ratio, beam divergence, and water‐equivalent thickness. Fine‐tuning was then performed for the central nervous system (CNS) site using 84 CNS plans. The model's accuracy was evaluated against MC simulation benchmarks using mean absolute error (MAE), gamma analysis (2% local dose difference, 2‐mm distance‐to‐agreement, 10% low dose threshold), and relevant clinical indices on the test dataset. Results The trained model achieved a single‐field dose calculation time of 0.07 s on a Nvidia‐A100 GPU, over 100 times faster than MC simulators. For the prostate site, the best‐performing model showed an average MAE of 0.26 ± 0.17 Gy and a gamma index of 92.2% ± 3.1% in dose regions above 10% of the maximum dose for D W calculations, and an MAE of 0.30 ± 0.19 Gy with a gamma index of 89.7% ± 3.9% for D M calculations. After transfer learning for CNS plans, the model achieved an MAE of 0.49 ± 0.24 Gy and a gamma index of 90.1% ± 2.7% for D W computations, and an MAE of 0.47 ± 0.25 Gy with a gamma index of 85.4% ± 7.1% for D M computations. Conclusions The SwinUNetr model provides an efficient and accurate method for computing dose distributions in proton therapy. It also opens the possibility of reverse‐engineering PSM from D W , potentially speeding up treatment planning while maintaining accuracy.

Abstract Background Patients’ self-report of their symptoms can provide important data for the evaluation of treatment benefit and tolerability of oncology drugs. Contemporary treatment approaches, including immunotherapy and molecular targeted therapies, have unique toxicities based on their novel mechanisms of action. This scoping review aimed to summarize evidence from existing reviews and clinical practice guidelines to examine the type and prevalence of toxicities including symptomatic adverse events (sympAEs) for adult cancer patients to inform clinical care and therapeutic trials. Methods A systematic search of PubMed, Web of Science, and Embase was performed using predefined eligibility criteria. Thirty-one literature reviews and 3 clinical practice guidelines met inclusion criteria and were selected for review and data abstraction. Results Findings from this scoping review demonstrated several leading sympAEs that were reported across immunotherapy and targeted therapy drugs, including fatigue, diarrhea, and rash. In addition to these more prevalent sympAEs, there were some less frequently reported class-specific sympAEs, which had potential for significant harm or disability to the patient if not properly identified and treated. Many studies reported toxicities as AEs or syndromes solely using data reported by clinicians without additional self-report from patients. Conclusion We identified several core sympAEs experienced by patients participating in oncology trials using immunotherapy and targeted therapy agents, which has implications for future trial design and drug labeling. Future cancer trials should assess patient-reported sympAEs based on the identified drug mechanism to inform the tolerability of these newer agents and enhance patient safety during trial participation and clinical care.

Neuropilin-1 (NRP1), initially identified as a neuronal guidance protein, has emerged as a multifaceted regulator in cancer biology. Beyond its role in axonal guidance and angiogenesis, NRP1 is increasingly recognized for its significant impact on tumor progression and therapeutic outcomes. This review explores the diverse functions of NRP1 in cancer, encompassing its influence on tumor cell proliferation, migration, invasion, and metastasis. NRP1 interacts with several key signaling pathways, including vascular endothelial growth factor (VEGF), semaphorins, and transforming growth factor-beta (TGF-β), modulating the tumor microenvironment and promoting angiogenesis. Moreover, NRP1 expression correlates with poor prognosis in various malignancies, underscoring its potential as a prognostic biomarker. Therapeutically, targeting NRP1 holds promise as a novel strategy to inhibit tumor growth and enhance the efficacy of regular treatments such as chemotherapy and radiotherapy. Strategies involving NRP1-targeted therapies, including monoclonal antibodies, small molecule inhibitors, and gene silencing techniques, are being actively investigated in preclinical and clinical settings. Despite challenges in specificity and delivery, advances in understanding NRP1 biology offer new avenues for personalized cancer therapy. Although several types of cancer cells can express NRPs, the role of NRPs in tumor pathogenesis is largely unknown. Future investigations are needed to enhance our understanding of the effects and mechanisms of NRPs on the proliferation, apoptosis, and migration of neuronal, endothelial, and cancer cells. The novel frameworks or multi-omics approaches integrate data from multiple databases to better understand cancer’s molecular and clinical features, develop personalized therapies, and help identify biomarkers. This review highlights the pivotal role of NRP1 in cancer pathogenesis and discusses its implications for developing targeted therapeutic approaches to improve patient outcomes, highlighting the role of OMICS in targeting cancer patients for personalized therapy.

Background/Objectives: Acute myeloid leukemia (AML) is a biologically heterogeneous malignancy with a variable prognosis. Despite many patients achieving complete remission, relapse remains common, underscoring the need for effective prognostic markers. Measurable residual disease (MRD) has emerged as a critical prognostic indicator, associated with higher relapse risk and shorter survival. This study reports on our initial experience of MRD detection by flow cytometry in 385 bone marrow samples from 126 AML patients. Methods: The flow cytometry MRD assay, validated according to stringent consensus recommendations, consists of a 3-tube, 10-color panel incorporating a broad spectrum of lineage differentiation markers. Analytical specificity, sensitivity, precision, and reproducibility were evaluated, demonstrating the assay’s robustness. Results: The results reveal distinct immunophenotypic aberrancies in all AML cases, with consistent identification of aberrant immunophenotypes in follow-up specimens. AML MRD was detected in 32 out of 126 patients (25%) and in 77 out of 385 analyses (20%), with a median aberrant blast percentage of 1.87% (range, 0.01–12). A change in immunophenotype was documented in 21% of the MRD-positive cases. MRD positivity detected in the first sample studied was associated with reduced overall survival (HR: 5.153; p < 0.0001). Conclusions: Our findings support the integration of flow cytometric MRD analysis into routine clinical practice to enhance risk stratification and treatment planning for AML patients, as currently recommended by professional guidelines.