Citations

AimsCompared to lymphovascular invasion (LVI), hilar soft tissue invasion (HSTI) is a relatively novel pT2 staging parameter in testicular germ cell tumours (GCT), associated with metastasis at the time of diagnosis and a risk factor for disease relapse. Given diagnostic variability in how pathologists interpret HSTI, herein we explore interobserver reproducibility among genitourinary (GU) pathologists.MethodsTwenty haematoxylin and eosin‐stained digitized slides from testicular GCTs were distributed to 30 GU pathologists to classify each as HSTI or not HSTI based on their respective clinical practices; slides with concomitant LVI were excluded. Slides were then evaluated for the following morphologic features: tumour invasion beyond prominent hilar vessels, tumour invasion beyond the rete, tumour invasion beyond the level parallel to hilar adipose tissue and tumour within (directly touching) hilar adipose tissue. Interobserver reproducibility was assessed, and the morphological features were correlated with HSTI. Relationships between pathologists' interpretations, morphological features and HSTI were evaluated using hierarchical clustering.ResultsAlthough the diagnosis of HSTI was relatively uniform with a majority agreement (>67%) reached in 17/20 slides, overall interobserver reproducibility was only moderate (kappa = 0.50). Morphological features such as invasion beyond the level parallel to hilar adipose tissue and invasion into fat were more sensitive and specific for HSTI, while features such as invasion beyond hilar vessels and invasion beyond rete were less useful.ConclusionsThese findings suggest that more specific defined diagnostic criteria for testicular GCT HSTI are needed.

Importance Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin–stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important. Objective To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods. Design, Setting, and Participants This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditional pathologist-read methods and an artificial intelligence (AI)-driven approach. The study was conducted using retrospective cohorts of patients with melanoma between January 2022 and June 2023 across 45 institutions, with tissue evaluated by participants from academic, clinical, and research institutions. Participants were selected to ensure diverse expertise and professional backgrounds. Main Outcomes and Measures Intraclass correlation coefficient (ICC) values were calculated for the manual and AI-assisted arms using log-transformed data. Kendall W values were calculated for Clark scores (brisk = 3, nonbrisk = 2, and sparse = 1). Reliabilities of ICC and W values were classified as moderate (0.40-0.60), good (0.61-0.80), or excellent (>0.80). AI TIL measurements were dichotomized using the 16.6 and median cutoffs. Univariable and multivariable Cox regression analyses assessed the prognostic value of TIL scores adjusted for clinicopathologic variables. Results There were 111 patients with melanoma in the independent testing cohort (median [range] age at diagnosis, 61.0 [25.0-87.0] years; 56 [50.5%] male) who contributed melanoma whole tissue sections. A total of 98 participants evaluated TILs on 60 hematoxylin and eosin–stained melanoma tissue sections. All 40 participants in the manual arm were pathologists, while the AI-assisted arm included 11 pathologists and 47 nonpathologists (scientists). The AI algorithm demonstrated superior reproducibility, with ICCs higher than 0.90 for all machine learning TIL variables, significantly outperforming manual assessments (ICC, 0.61 for AI-derived stromal TILs vs Kendall W , 0.44 for manual Clark TIL scoring). AI-based TIL scores showed prognostic associations with patient outcomes (n = 111) using the median cutoff approach with a hazard ratio (HR) of 0.45 (95% CI, 0.26-0.80; P = .005), and using the cutoff of 16.6, with an HR of 0.56 (95% CI, 0.32-0.98; P = .04). Conclusions and Relevance In this prognostic study of TIL quantification in melanoma, the AI algorithm demonstrated superior reproducibility and prognostic associations compared with traditional methods. Although the retrospective nature of the cohorts limits demonstration of clinical utility, the publicly available dataset and open-source AI tool offer a foundation for future validation and integration into melanoma management.

Objectives Periodic quality control (QC) testing of ultrasound (US) imaging systems is essential to ensure and maintain image quality and safety. The study aims to analyze QC findings from medical physics annual surveys of modern clinical US systems in a multi‐institutional survey. Methods QC results from annual surveys between 2018 and 2021 were retrospectively collected from 12 medical physicists from 11 institutions or consulting companies (hereafter referred to as sites). QC tests were classified as scanner‐ and transducer‐related tests, where scanner‐related tests also included evaluation of diagnostic workstation display monitors and routine QC programs if applicable. Test methodology and pass/fail criteria were established by each site. QC findings were defined as results requiring follow‐up action by service engineers, vendors, or other personnel. The percentage of annual findings was calculated for each site and averaged across the years of data contributed. Furthermore, findings across all sites were aggregated for an overall analysis. Results QC data from a total of 1069 scanner tests and 4542 transducer tests were collected. The average annual percentage of scanner‐related findings varied from 0 to 40.8% among all sites (first quartile 8.7%, median 18.2%, and third quartile 34.1%), while that of transducer‐related findings ranged between 0.5% and 19.9% (first quartile 3.9%, median 7.2%, and third quartile 14.5%). For scanner‐related tests, the top 3 categories of findings were associated with physical and mechanical integrity (171 findings, 74.7%), quantitative testing of the scanner display monitor (40 findings, 17.5%), and scanner port creating artifacts (10 findings, 4.4%). The top 3 findings for transducers related to uniformity and artifact (227 findings, 79.9%), physical and mechanical integrity (44 findings, 15.5%), and sensitivity in fundamental mode (9 findings, 3.2%). Conclusions Medical physics annual surveys revealed considerable actionable findings of modern US systems, which inform the status of current US QC practices in the United States and may guide future standardization and recommendation of QC tests.

Objective: To develop an artificial intelligence–based pipeline to assess and triage patient-submitted postoperative wound images. Background: The rise of outpatient surgeries, remote monitoring, and patient-submitted wound images via online portals has contributed to a growing administrative workload on clinicians. Early identification of surgical site infection (SSI) is essential for reducing postoperative morbidity. Methods: Patients ≥18 years old who underwent surgery at 9 affiliated Mayo Clinic hospitals (2019-2022) and were captured by the National Surgical Quality Improvement Program (NSQIP) were included. Eligibility required submission of one image via the patient portal within 30 days after surgery. Images were independently screened in duplicate to determine the presence of an incision. SSI outcomes were obtained from NSQIP. The developed model consisted of 2 stages: incision detection and SSI detection in images with incisions. Four pretrained architectures were evaluated using 10-fold cross-validation, with upsampling and data augmentation to mitigate class imbalance. An end-to-end pipeline, image quality assessment and sensitivity analysis stratified by race were also performed. Results: Among 6060 patients, the median age was 54 years (interquartile range: 40–65), 61.4% (n=3805) were female, and 92.5% (n=5731) identified as White. SSIs were confirmed in 6.2% (n=386) images. Vision Transformer outperformed all others, achieving an incision detection accuracy of 0.94 (area under the curve=0.98) and an SSI detection accuracy of 0.73 (area under the curve=0.81). In addition, it demonstrated strong performance in assessing image quality. Sensitivity analysis revealed comparable performance across racial subgroups. Conclusion: This artificial intelligence pipeline demonstrates promising performance in automating wound image assessment and SSI detection, reducing clinical workload and improving postoperative care.

Introduction Patients hospitalized for headache treatment pose unique challenges to the healthcare system. Currently, there is a lack of evidence-based guidance on management. This practice advisory aims to fill this critical gap by systematically reviewing the existing literature and providing comprehensive, evidence-based recommendations for managing headache patients during hospitalization. Methods In February 2023, the American Society of Regional Anesthesia and Pain Medicine approved this practice advisory proposal. The steering committee selected committee members based on clinical and research expertise in the field of headache medicine. Nine questions were formulated by the committee, and each question was assigned to a group composed of 3–4 members. A systematic literature search for each question was performed in Medline, Embase, Cochrane Database of Systematic Reviews and Web of Science on June 21, 2023. The results from each search were imported into separate Covidence projects for screening, data extraction, and risk of bias assessment. Additionally, relevant systematic reviews (SR) were screened. Each group submitted a structured narrative review along with statements and recommendations based on the US Preventive Services Task Force (USPSTF) format for grading of evidence. While the USPSTF framework was used, including the language in the recommendations, the formal USPSTF methodology, including the SR with meta-analysis and summary tables with forest plots, was not followed because of low overall evidence quality. The interim draft was shared electronically with each collaborator, who was requested to vote anonymously using two rounds of the modified Delphi approach. A consensus recommendation required >75% agreement. Results The panel generated 12 statements and 17 recommendations, along with their strength and certainty of evidence. Following two rounds of Delphi voting, a high consensus was achieved for all statements and recommendations. Most statements received a low-to-moderate level of certainty, and all but one recommendation received grade B or C, which was consistent with the lack of randomized controlled trials supporting most of the drugs in this document. Conclusions This evidence-based practice advisory provides a foundational step toward standardizing inpatient headache care and highlights existing gaps in the literature that should be addressed through rigorous prospective randomized studies.

PURPOSE Despite international medical graduates (IMGs) accounting for up to one third of all practicing oncologists in the United States, and nearly half of fellowship trainees, little is known about their contributions to presentations at international oncology meetings. Therefore, we investigated the representation of IMGs in invited faculty roles at the ASCO Annual Meeting as a representative example. METHODS Presentation data from ASCO 2022 and 2023 Annual Meetings were obtained from program guides. We collected presentation-level and speaker-level variables of invited faculty roles and original research. Speakers were categorized as American medical graduate (AMG), IMG, non–US-based, or non-MD (Doctor of Medicine). Univariable and multivariable analyses assessed factors influencing selection for invited faculty roles. RESULTS A total of 2,590 presentations by 2,109 unique speakers were reviewed, including primary research presenters and invited faculty. Among the 1,352 presentations by AMGs, 30% were primary research and 70% were invited faculty roles. For the 374 presentations by IMGs, 41% were primary research and 59% were invited faculty roles. Notably, first-author IMGs were significantly less likely to receive invited faculty roles relative to their primary research output compared with first-author AMGs (adjusted odds ratio, 0.69 [95% CI, 0.53 to 0.90]; P = .006), even when accounting for academic rank, presumed sex, and year. CONCLUSION Relative to IMGs' original research output, IMGs appear to receive fewer invitations for ASCO Annual Meeting invited faculty roles compared with AMGs. Our findings suggest potential underrepresentation and under-recognition of IMGs in these roles, despite their contributions to the oncology workforce in the United States.

Abstract Background Dasatinib is an oral inhibitor of the Src kinase family, with preclinical data indicating impact on gliomagenesis, tumor invasion, and radiosensitivity. Methods North Central Cancer Treatment Group N0877 is a phase 1 dose escalation and phase II randomized study evaluating the maximum tolerated dose (MTD), safety, and efficacy of dasatinib with radiation and temozolomide (TMZ) for glioblastoma. Following identification of the MTD, adult patients with a histologic diagnosis of glioblastoma were randomized 2:1 between dasatinib given with standard concurrent and adjuvant TMZ, versus placebo with standard concurrent and adjuvant TMZ. Radiation dose was 60 Gy in 30 fractions. The primary endpoint was overall survival (OS). Secondary endpoints included progression-free survival (PFS), toxicity, and quality of life. Results Thirteen patients were enrolled in the phase I component and established the MTD and phase II dose of 150 mg given daily. A total of 204 patients were enrolled in the phase II component. OS was not different between arms (median OS 15.6 months for dasatinib compared to 19.3 months for placebo, hazard ratio:1.21 favoring placebo, 95% CI: 0.88–1.65, log-rank P-value: .238). Similarly, PFS was not significantly different between the dasatinib and placebo arms. There was a significant increase in anemia, nausea, and creatinine elevation with dasatinib, but significantly more grade 3 lymphopenia with placebo. Conclusions The addition of dasatinib to standard chemoradiation did not improve outcomes for patients with glioblastoma. Clinical Trial Identifier NCT00869401.

Multidisciplinary case conferences have been shown to improve patient outcomes. However, such case conferences may be unavailable in some settings. This multidisciplinary discussion of 4 challenging hepatobiliary cases was presented at the 2023 Society of Advanced Body Imaging Annual Meeting in Dallas, TX. The cases include an “imaging occult” pancreatic tumor, a large pancreatic mass, an intraductal biliary mass, and a polypoid intraluminal gallbladder mass.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

ABSTRACTAlthough current treatment strategies for nonmalignant airway stenosis may offer short‐term relief, their effectiveness is limited by high recurrence rates, often requiring additional procedures. While paclitaxel‐coated balloons (PCB) have demonstrated effectiveness in treating stenosis across various vascular and nonvascular conditions, their evidence in recurrent airway stenosis remains limited. Here, we present the case of a 35‐year‐old female with bronchial stenosis who underwent multiple bronchoscopic interventions, all of which were complicated by restenosis. Following the addition of a PCB to the therapeutic regimen, the patient achieved sustained airway patency.