Citations

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Evaluation of T-cell receptor (TCR) β-chain constant region 1 (TRBC1) expression is an alternative T-cell clonality assessment method. However, evaluation of TRBC1 immunohistochemistry (IHC) for distinguishing mycosis fungoides (MF)/Sezary syndrome (SS) from reactive inflammatory infiltrates in skin is incomplete. We evaluated the utility of a novel dual TRBC1-CD3 IHC stain in skin biopsies with MF/SS (n=40), reactive (n=24), or atypical T-cell infiltrates indeterminant for MF/SS (n=9). Twenty of 24 reactive cases showed clear polytypic TRBC1 expression (median percent TRBC1 positivity among CD3-positive T cells [%TRBC1+] 50% in dermis, 42.5% in epidermis among all cases), while 34/40 MF/SS were clearly monotypic (%TRBC1+ either ≤20% or ≥85%) (sensitivity 85.0%, specificity 91.7%, positive predictive value 94.4%, negative predictive value 78.6%). Discordance between TRBC1 expression and diagnosis was associated with few neoplastic/monotypic T cells and/or lack of physical separation between neoplastic and non-neoplastic populations. Among patch/plaque MF/SS, TRBC1 showed similar diagnostic sensitivity (80.0% vs. 86.7%) and high categorical correlation (monotypic vs. not monotypic, 80%) with TCR gene rearrangement results. TRBC1 interpretation was reproducible, with ≥2/3 and 3/3 pathologists rendering identical interpretations in 100% and 86% of cases, respectively, after independent review and 100% agreement following collective review. Digital image analysis confirmed visual %TRBC1+ accuracy ( r =0.9749, P <0.0001). On the basis of these results, we propose %TRBC1+ cutoffs of <25% or >75% for establishing T-cell monotypia in skin. Considering such thresholds, TRBC1-CD3 evaluation facilitated diagnostic refinement in 7/9 (78%) atypical cases. Overall, TRBC1-CD3 IHC clearly and rapidly aids diagnosis of cutaneous T-cell proliferations.

OBJECTIVE The Centers for Medicare & Medicaid Services (CMS) requires a low C-peptide level for insulin pump coverage unless the individual is β-cell autoantibody positive, which precludes coverage of automated insulin delivery (AID) systems for many people with type 2 diabetes. RESEARCH DESIGN AND METHODS In the Randomized Trial Evaluating the Efficacy and Safety of Control-IQ+ Technology in Adults With Type 2 Diabetes Using Basal-Bolus Insulin Therapy study evaluating the t:slim X2 insulin pump with Control-IQ+ technology, adults with insulin-treated type 2 diabetes were categorized into high C-peptide (n = 195) and low C-peptide (n = 59) groups based on CMS criteria. RESULTS In the AID group, mean HbA1c decreased from baseline by 0.8%, which was significantly greater than in the control group with both high (P &lt; 0.001) and low (P = 0.02) C-peptide levels. Results were similar in participants ≥65 years old. CONCLUSIONS The benefit of AID is present with high and low C-peptide levels. Thus, requiring a low C-peptide level as a prerequisite for AID therapy is not warranted.

Abstract Objective The aim of this study was to evaluate a large cohort of gallbladder amyloid cases to determine clinical and morphologic features. Methods Cholecystectomy specimens (N = 118) typed using proteomics-based techniques between 2008 and 2023 were identified. Clinical and morphologic features were reviewed. Results Six amyloid types were identified: ATTR (n = 63, 53.4%), AL (n = 46, 39.0%), AA (n = 4, 3.4%), AApoA1 (n = 2, 1.7%), ALECT2 (n = 2, 1.7%), and AEFEMP1 (n = 1, 0.8%). Amyloidogenic mutations were detected in 3 ATTR cases and 2 AApoA1 cases. Morphologic review (n = 26) revealed perimuscular vessel involvement in all cases. Amyloidosis was an unexpected diagnosis first made on the cholecystectomy specimen in half of the patients with clinical information (n = 10). All 9 patients with follow-up had evidence of systemic disease. In 2 patients, cholecystic involvement was initially missed and only retrospectively identified after the diagnosis of cardiac amyloidosis. Conclusions In patients with clinical data, amyloidosis was often unexpected, the gallbladder was commonly the first tissue sampled with amyloidosis, and all patients had systemic disease. Thorough review of cholecystectomy specimens with careful inspection of perimuscular vessels, coupled with a low threshold for ordering Congo red stain in elderly individuals and amyloid typing using a robust method such as proteomics, can prevent a delay in amyloid diagnosis and management.

ABSTRACTPurposeThis study aimed to assess whether kidney stone burden and risk factors at the time of kidney donor evaluation were associated with a symptomatic stone event post‐donor evaluation.MethodsWe identified adults evaluated at Mayo Clinic (two sites) (2000–2011) for living kidney donation and had either a personal history or radiological evidence of kidney stone disease. We analyzed demographics, stone risk factors, stone number/size, and the committee's donation decision and reasons. A follow‐up survey (2022–2023) assessed post‐evaluation symptomatic kidney stones and related morbidity.ResultsAmong 412 potential donors with kidney stone disease, 258 donated, 75 did not donate due to kidney stones, and 79 did not donate for other reasons. Multivariable analysis showed that candidates not donating due to stones had higher body mass index (BMI), prior symptomatic kidney stones, multiple stones on imaging, bilateral kidney stones, and diameter of largest stone ≥3 mm. Of 147 who completed the survey, 26 (18%) had a symptomatic kidney stone post‐donor evaluation. Younger age (p = 0.031) and multiple stones on imaging (p = 0.02) were significant predictors of post‐evaluation symptomatic stones regardless of donation status (p = 0.41).ConclusionsStone burden on imaging and prior symptomatic stone events were associated with not donating. Younger age and stone burden on imaging were the primary risk factors for a symptomatic kidney stone event after donor evaluation.

Introduction: Outcomes from multidisciplinary lymphoma tumor boards in the molecular era are limited, and the effects of transitioning to virtual formats during the COVID-19 pandemic are not well-documented. This study evaluates how the transition of the Mayo Clinic Lymphoma Tumor Board to a virtual format has impacted its effectiveness and operations. The board, part of the International Mayo Clinic Care Network (MCCN), involves case presentations, subspecialist reviews, and collaborative recommendations. Methods: The Mayo Clinic Lymphoma Tumor Board, an integral part of the Mayo Clinic Care Network (MCCN), conducted a comprehensive review of lymphoma cases from 2014 to 2024. The board's review process involves a structured approach including the presentation of clinical case details, radiology and hematopathology findings, proposed treatment options, relevant literature review, and discussions. From 2014 to 2024, the Mayo Clinic Lymphoma Tumor Board reviewed a total of 722 patients. The review process involves a multidisciplinary team, including physicians, pharmacists, clinical research associates, and trainees. Recommendations and changes related to radiology interpretation, pathologic diagnosis, and treatment approaches were documented and tracked prospectively. In March 2020, the board transitioned to a virtual format due to the COVID-19 pandemic. This shift allowed for remote participation and continued collaborative review while maintaining the board's structured approach and documentation practices. Results: In a total of 722 patients, changes in care were identified in 423 patients, including 287 with newly diagnosed lymphoma and 136 with relapse or refractory disease. Among those who experienced changes, 94 had diffuse large B-cell lymphoma, 49 had follicular lymphoma, 39 had marginal zone lymphoma, 36 had classical Hodgkin lymphoma, and 29 had mantle cell lymphoma. Prior to the COVID-19 pandemic, 431 patients were analyzed, with 217 (50.3%) experiencing changes. A total of 268 changes were documented among these patients. Changes in radiologic interpretation occurred in 9 patients (2.1% of 431 total patients). Pathologic diagnosis changes were noted in 42 patients (9.7%). Additional testing was recommended for 73 patients (16.9%), and clinical management was altered for 144 patients (33.4%). After transitioning to a virtual format, 291 patients were reviewed post-COVID, with 206 (70.8%) having recommended changes. The total number of change recommendations was 322, reflecting increases across all components compared to previous data, with adjustments for varying numbers of patients reviewed. Specifically, radiologic interpretation changes occurred in 21 patients (7.2%), pathologic diagnosis changes in 57 patients (19.6%), additional testing recommendations for 85 patients (29.2%), and clinical management alterations in 159 patients (54.7%). Conclusion: Transitioning to a virtual format in the Mayo Clinic Lymphoma Tumor Board's continued to demonstrate the effectiveness, with increased changes in diagnostic interpretations and clinical management. These results illustrate the potential of virtual tumor boards to improve collaborative decision-making and adapt to evolving clinical needs.