Citations

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.

Background/Objectives: Modeling analyses for colorectal cancer (CRC) screening focusing solely on the costs of screening do not fully capture the value of screening programs. We evaluated the clinical and economic effects of CRC stool-based screening tests, including impacts on cancer-related outcomes. Methods: A cohort-based decision-analytic cost-estimator model estimated outcomes for a single round of screening with next-generation multi-target stool DNA (ng mt-sDNA) test or fecal immunochemical test (FIT) from a US payer perspective. Undiagnosed cancers were assumed to become symptomatic (and detected) within 10 years. Clinical assumptions, advanced precancerous lesion and CRC prevalence, and test performance inputs were from clinical trial data. Adherence rates for initial screening and follow-up colonoscopy after a positive result were from real-world data. Input costs included the screening tests, follow-up colonoscopy (with and without polypectomy), and CRC treatment. Results: Compared with FIT, more individuals completed ng mt-sDNA (321,000 vs. 713,000, respectively), leading to the detection of more CRC cases (436 with FIT vs. 2235 with ng mt-sDNA), more advanced precancerous lesions, and more CRC at earlier stages. The cost of screening per patient screened was USD 801 for ng mt-sDNA and USD 124 for FIT. Follow-up colonoscopy cost was USD 149 million with ng mt-sDNA versus USD 22 million with FIT, whereas CRC treatment costs were lower for ng mt-sDNA (USD 1423 million versus USD 1474 million, respectively). When accounting for both direct and CRC averted costs, the total cost of screening and treatment was USD 1383 million with ng mt-sDNA versus USD 1427 million with FIT. Conclusions: Higher screening costs with ng mt-sDNA versus FIT are counterbalanced by savings realized from enhanced CRC prevention and earlier detection due to the superior test performance and better adherence with ng mt-sDNA.

Abstract INTRODUCTION New methods estimate amyloid positivity onset age (EAOA) from amyloid positron emission tomography (PET). We explore the genetics of EAOA to identify molecular factors underlying the earliest Alzheimer's disease (AD) changes. METHODS Harmonized amyloid PET data from 4216 participants were used in genome‐wide survival, tissue‐specific gene expression, and genetic covariance analyses of EAOA. RESULTS Variants in apolipoprotein E ( APOE ), ABCA7 , and RASGEF1C associated with earlier EAOA. APOE ε4/ε4 and ε3/ε4 converted 6.3 and 5 years earlier than ε3/ε3, respectively. ε2 was protective against earlier EAOA. rs4147929, an expression quantitative trait locus for ABCA7 , associated with a 4 year earlier EAOA. This variant was associated with lower brain expression of ABCA7 , which was associated with increased amyloid pathology at autopsy. Multiple immune‐related diseases shared genetic covariance with EAOA. DISCUSSION APOE , ABCA7 , and RASGEF1C associated with earlier EAOA, with supporting evidence from tissue‐specific expression analyses, offering insights into intervenable targets at early stages of AD. Highlights Novel methods estimate how long ago a patient converted to amyloid positivity. Estimating this amyloid clock allows us to determine the onset of the earliest Alzheimer's disease changes. We evaluated what genes influence when someone converts to amyloid positivity. Apolipoprotein E ( APOE ) , ABCA7 , and RASGEF1C associated with earlier age of amyloid positivity. Genetic results were supported by tissue‐specific expression analyses.

INTRODUCTION: Colorectal cancer remains a leading cause of cancer associated death in the United States and colonoscopy the primary screening strategy for prevention. Rates of adenomatous and serrated neoplasia detection are inversely associated with postcolonoscopy colorectal cancer. This crucial quality metric depends on accurate ascertainment of colorectal neoplasia findings from both endoscopy and histopathology records. We aimed to assess the feasibility of a random forest machine learning model to rapidly and accurately categorize colorectal neoplasia from electronic health record data. METHODS: A retrospective cohort study compared neoplasia detection rates among individuals undergoing colonoscopy at a large academic institution to develop a rule-based algorithm to categorize colorectal neoplasia from endoscopy reports and pathology systematized nomenclature of medicine – clinical terms. This cohort provided a large training set to develop a natural language processing system using a random forest approach to automatically classify unstructured pathology findings into adenoma, serrated, or advanced neoplasms. This system was manually validated through an independent holdout set. RESULTS: The training set comprised 35,953 unstructured pathology reports with matched systematized nomenclature of medicine – clinical terms from 95,188 unstructured colonoscopy reports. The final model was assessed on an independent holdout set of 337 manually annotated procedures obtaining an area under the receiver operating characteristic curve of 0.997 (confidence interval [CI] 0.994–1), 0.99 (CI 0.98–1), and 0.99 (CI 0.98–0.99) for prediction of adenoma, serrated, and advanced lesions, respectively. DISCUSSION: The random forest-based hybrid natural language processing system for classification of colonoscopy results was both accurate and explainable. NLP combined with effective machine learning algorithms can provide a scalable strategy for colonoscopy quality monitoring.

Abstract The current European Leukemia Net guidelines (ELN22) classify AML patients with intermediate-risk cytogenetics and MDS-associated mutations (MDSm, mutations in ASXL1, BCOR, EZH2, RUNX1, SF3B1, SRSF2, STAG2, U2AF1, ZRSR2) as adverse-risk but do not use MDSm+ to alter the risk stratification of patients who otherwise classify as favorable-risk. NPM1 mutations (NPM1+) are one of the most common alterations in AML and remain a favorable-risk biomarker for patients without co-occurring FLT3-ITD mutations or adverse-risk cytogenetics (NPM1+/ITD-/ARcyto-). However, prior studies have shown that older patients (≥65 years) with favorable-risk AML, including NPM1+/ITD-/ARcyto- genotype, have significantly higher relapse rates and decreased survival despite receiving comparable intensive chemotherapy regimens to their younger counterparts. Given that MDSm frequency increases with age in patients with NPM1+ AML, it raises the question as to whether MDSm contribute to poorer outcomes in older patients. To date, there have been differing results in retrospective studies examining the effect of MDSm on NPM1+ AML. Some cohorts demonstrate worse outcomes in those that have NPM1+/MDSm+ AML (Chan et al., Blood Adv. 2024), whereas others do not show a significant difference in NPM1+ AML with or without MDSm (Eckardt et al., Leukemia 2023; Othman et al., Blood 2024; Ruhnke et al., Blood Adv. 2025). We examined the mutational landscape in a large group of pre-treatment, diagnostic specimens from 271 patients, which included 119 patients enrolled in SWOG clinical trials (SWOG-9031, SWOG-9333, S0106, and S0112), 96 patients from the UW/FHCC Hematopoietic Repository, and 56 patients from the BeatAML cohort. All patients were treated with curative intent as per standard practice or on clinical trials and had adequate cytogenetic information and long-term follow-up data. Event-free and overall survival (EFS, OS) were estimated using the Kaplan-Meier method and compared using Cox regression models stratified by cohort. MDSm+ occurred in 17% of patients, with the most common mutations being in SRSF2 (7%) and SF3B1 (3%). To assess the impact of MDSm on outcomes of favorable-risk NPM1+ AML, we performed univariate analyses comparing OS and EFS for NPM1+ AML grouped by ELN22 favorable risk/MDSm-, ELN22 favorable/MDSm+, and ELN22 intermediate/adverse risk. Compared to NPM1+/MDSm- (n=116), favorable-risk NPM1+/MDSm+ (n=33) had worse OS with HR 2.0 [95% CI (1.1, 3.3), p=0.008] and had similar OS to those that are classified as ELN22 intermediate/adverse risk (n=122). There was no significant difference in EFS or complete remission rates between NPM1+ favorable risk with and without MDSm (p=0.36 and p=0.6, respectively). When we grouped the ELN22 favorable risk patients by age (&lt;65 years vs. 65+ years), MDSm+ in younger patients did not show a difference for OS (HR 0.99, p=0.98). Older ELN22 favorable-risk patients (≥65) had poor OS regardless of presence of MDSm compared to younger MDSm- patients: older MDSm- (n=91) with HR 2.4, 95% CI (1.3, 4.6), p=0.005 and older MDSm+ (n=25) with HR 3.5, 95% CI (1.9, 6.3), p&lt;0.0001. There was a trend toward worse OS in MDSm+ compared to MDSm- older patients, but this was not statistically significant (HR 1.42, p=0.33). Since most MDSm are in splicing factor genes (SF3B1, SRSF2, U2AF1, ZRSR2), we examined the effect of splicing factor mutations vs. other MDSm+ in ELN22 favorable risk and did not find a significant difference in OS (HR=1.01, p=0.97). Those with non-splicing MDSm+ had worse EFS compared to MDSm- and splicing MDSm+ (HR 4.12, p=0.0037), although no difference in OS. In this study, MDSm+ in the context of favorable-risk NPM1+ AML are associated with worse OS in a univariate analysis. However, this difference is likely due to the increased prevalence of MDSm with increasing age and overall worse outcomes of NPM1+ AML in older patients. When stratified by age, older NPM1+ AML patients had worse OS than younger NPM1+ patients overall, although presence of MDSm trended toward even worse OS in older patients. In younger patients, MDSm+ are not associated with a significant difference in OS, which is a similar finding compared to prior studies. Our findings suggest that NPM1+ AML is not necessarily “favorable-risk” in older patients, particularly with concurrent MDSm. Therefore, further understanding of the underlying biology of age in the context of NPM1+ AML is needed to improve outcomes for older patients.

Abstract Background: Recent advances in computer vision have given rise to image foundation models (FMs), large-scale neural networks pre-trained on millions of unlabeled histopathology patches, which can learn generalizable representations of tissue morphology. In many cancers, these FMs have predicted genetic mutations and prognoses directly from histology, suggesting that morphology encodes “hidden” molecular information. In lymphoma, this field is nascent but growing.General-purpose histopathology FMs have limited representation of lymphoid morphology. We developed and evaluated LymphoVision, a lymphoma-specialized image foundation model pretrained with self-supervised learning, to extract clinically meaningful features from routine hematoxylin and eosin (H&E) histology. Methods: LymphoVision was pre-trained using knowledge distillation and consistency (DINOv2) on over 37 million multi-resolution patches (5x, 10x, 20x, 40x) sampled using a density-aware strategy from 31,211 H&E whole slide images (WSIs) from 9,155 archival lymphoma and reactive lymphoproliferative cases. To ensure diverse, representative samples, our patch sampling method uses an efficient graph-based clustering algorithm and prioritizes morphologically informative regions by clustering patch embeddings and performing density sampling within each cluster. The pretrained encoder was evaluated using a clustering-constrained attention multiple instance learning (MIL) framework on three diagnostic tasks: (1) cell-of-origin (COO) classification in diffuse large B-cell lymphoma (DLBCL), distinguishing germinal center B-cell (GCB) from non-GCB subtypes based on the Hans immunohistochemistry algorithm; (2) follicular lymphoma (FL) grading, differentiating low-grade (grades 1–2) from high-grade (grade 3); and (3) multiclass lymphoma subtype classification across six categories: DLBCL, FL, marginal zone lymphoma (MZL), mantle cell lymphoma (MCL), classical Hodgkin lymphoma (CHL), and benign/reactive lymphoid conditions. WSI-level labels were derived from pathology reports, and none of the evaluation cases were included in pretraining. Models used a ViT-Giant LymphoVision backbone to generate 20x patch embeddings, followed by MIL using 50% training data and 2-fold cross-validation (25% validation, 25% test). Performance was assessed using area under the receiver operating characteristic curve (AUC), accuracy, recall (sensitivity) and F1 score. Results: For DLBCL COO classification (total n=358 cases), LymphoVision achieved a mean test AUC of 0.93 (range 0.92–0.94), accuracy of 84.5% and F1 of 0.85 across two independent test folds (n=91 per fold, 50% GCB). These results outperformed general-purpose FMs on the same task and cases, including Virchow-v2 (AUC 0.85) and UNI-v2 (AUC 0.88), despite those models being pretrained on 10–100 times more images. For FL grading (total n=660 cases), the test set in each fold included 166 cases (18% grade 3), yielding a mean test AUC of 0.88 (range 0.87–0.90), accuracy of 89.2% and F1 of 0.80. In multiclass lymphoma subtype classification (total n=1,176 cases), the test set included 296 cases per fold. LymphoVision achieved a mean test AUC of 0.98 (range 0.97-0.99), mean test accuracy of 87.1% and mean F1 of 0.84. Class-wise recall was 92.0% for DLBCL (n=112), 88.2% for FL (n=72), 77.2% for MZL (n=29), 70.8% for MCL (n=35), 87.5% for CHL (n=24), and 95.8% for benign/reactive lymphoid conditions (n=24). Conclusion: LymphoVision is a lymphoma-specialized FM trained using self-supervision that achieves high diagnostic accuracy across multiple clinically meaningful tasks using weak supervision and standard H&E images, suggesting the encoder has learned fine-grained lymphoma morphology. Based on historical benchmarks from the 1997 International Lymphoma Study Group classification project, expert hematopathologists achieved diagnostic agreement rates of 55% to 84% using H&E morphology alone for the non-Hodgkin lymphoma (NHL) entities included in our multiclass task. LymphoVision approached or exceeded these benchmarks. These findings underscore the value of our approach using disease-specialized pretraining and intelligent patch sampling for data-efficient histopathology learning. LymphoVision has the potential to augment diagnostics, enable scalable AI-powered classification in real-world workflows, and serve as a foundation for prognostic and theragnostic applications. External validation and multimodal integration are ongoing.

Abstract Background: Systemic mastocytosis (SM) comprises a spectrum of subtypes characterized by neoplastic mast cell (MC) infiltration of tissues and release of MC mediators. Non-advanced SM (NonAdvSM), including indolent SM (ISM), smoldering SM (SSM), and bone marrow mastocytosis (BMM) subtypes, is the most prevalent form of SM. NonAdvSM can be associated with debilitating symptomology which can significantly impair quality of life. The gain-of-function somatic KIT c.2447 C&gt;T (p.D816V) mutation is found in up to 95% of patients with SM. Bezuclastinib (CGT9486) is an oral, potent, and selective type 1 tyrosine kinase inhibitor with activity against KIT D816V. Results from Summit (NCT05186753) Part 1 informed the recommended phase 2 dose (100 mg QD bezuclastinib) for Part 2. We report topline results from the 24-week assessment of Summit Part 2. Methods: Summit is a multi-center, randomized, double-blind, placebo (PBO)-controlled Phase 2 trial of bezuclastinib in patients with NonAdvSM who had inadequate symptom control despite best supportive care (BSC) medications. The primary endpoint was 24-week mean change from baseline in Mastocytosis Symptom Severity Daily Diary (MS2D2) total symptom score (TSS) (range 0–110), which is a fit-for-purpose patient-reported outcome measure of NonAdvSM symptom severity. Key secondary endpoints included the proportion of patients with ≥50% reduction in serum tryptase, KIT p.D816V variant allele frequency (VAF), bone marrow (BM) MC burden, and MS2D2 TSS, ≥30% TSS reduction. Patients were randomized 2:1 to receive 100mg QD bezuclastinib + BSC or PBO + BSC. Results: As of May 22, 2025, 179 patients were enrolled in Part 2: 119 were randomized to receive bezuclastinib and 60 to placebo. Patients enrolled were representative of the NonAdvSM population with moderate to severe symptoms. Median age (range) was 51 (23-78) years; 65.9% female; mean (SD) baseline MS2D2 TSS 55.6 (19.8); 82% of patients had ISM, 11% had BMM, and 7% had smoldering SSM. At baseline, median (range) KIT p.D816V VAF in whole blood, BM MC burden, and serum tryptase was 0.25% (0-34%), 10% (1-75%), and 40 (6-692) ng/mL, respectively. Bezuclastinib demonstrated statistically significant superiority to placebo on all primary and key secondary endpoints. At Week 24, bezuclastinib led to significantly greater symptom improvement vs placebo (LS mean [95% CI] MS2D2 TSS change: –24.3 [–27.6 to –21.1] vs –15.4 [–19.6 to –11.2]; placebo-adjusted difference: –8.9 points; P=0.0002). A ≥50% reduction in serum tryptase was achieved in 87.4% of bezuclastinib-treated patients vs 0% on placebo (P&lt;0.0001). Significantly more patients receiving bezuclastinib achieved ≥50% reductions in KIT D816V VAF, serum tryptase, BM MCs (P&lt;0.0001), MS2D2 TSS (P=0.01), and ≥30% reduction in MS2D2 TSS (P=0.0004). Most treatment-emergent adverse events (TEAEs) were low grade (gr; 70% Gr 1) and reversible. The most common TEAEs (≥10%) in any treatment group and occurring in greater frequency in the bezuclastinib arm were hair color changes (69.5% vs 5.0%), altered taste (23.7% vs 0%), nausea (22.0% vs 13.3%), increased ALT/AST (22.0% vs 6.6%), headache (17.8% vs 11.7%), alopecia (11.9% vs 3.3%), and increased ALP (10.2% vs 3.3%). TEAEs (≥10%) that occurred more often in the placebo group were diarrhea (13% vs 18%), dizziness (10% vs 12%), fatigue (7% vs 12%), and arthralgia (6% vs 15%). ALT/AST elevations ≥Gr 3 were experienced by 5.9% of patients. The only hepatic adverse events (AEs) reported were transient lab abnormalities; none required hospitalization. Treatment-related AEs requiring dose reductions occurred in 11% of patients receiving bezuclastinib. All discontinuations (5.9%) due to treatment-related AEs were due to transaminase elevations; all fully resolved. Conclusions: At 24-weeks, bezuclastinib 100 mg QD demonstrated statistically and clinically significant improvements in symptom burden and biomarkers of disease vs placebo in patients with NonAdvSM. The treatment was generally well-tolerated and effective across a population that is representative of the real-world NonAdvSM population, including SSM. These results support the use of bezuclastinib to reduce SM burden and symptoms in pts with NonAdvSM, and a potentially disease-modifying impact.

Background Patients with single-ventricle physiology are often palliated with the Fontan operation, which may involve the creation of a fenestration. We aimed to evaluate differences in cardiopulmonary exercise test (CPET) performance between patients with fenestrated and non-fenestrated Fontan circulation. Methods Patients with a Fontan circulation referred to CPET between 2006 and 2024 were included and were categorised based on their fenestration status at the time of CPET. Logistic regression analyses were performed to assess the impact of fenestration on peak oxygen consumption (VO 2 ), and Cox proportional hazard to evaluate the impact of fenestration on cardiovascular outcomes (death, heart transplant and Fontan-related hospitalisation). Results Of the 184 patients, 141 were classified as non-fenestrated and 43 as fenestrated. The minute ventilation-carbon dioxide production (V E /VCO 2 slope) was higher in the fenestrated (36.9±7.9) versus (33.2±6.2; p=0.009) in the non-fenestrated group. There was no significant difference in predicted VO 2 between groups (non-fenestrated 51.9%±14.4 vs 51.3%±15.6; p=0.7). Resting oxygen saturation was higher in the non-fenestrated group (93%±4.7 compared with fenestrated group 90.1%±5; p<0.001). Fontan fenestration was not significantly associated with the composite outcome; older patient age at the time of the CPET, cirrhosis and ventricular ejection fraction <40% were significantly associated with higher risk, while higher resting systolic blood pressure, left ventricular morphology and higher predicted peak VO 2 were protective. Conclusions The increased hypoxia and reduced ventilatory efficiency associated with Fontan fenestration offset any potential benefits, resulting in similar exercise performance between the groups. Fontan fenestration was not significantly associated with cardiovascular outcomes.

Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies.

Background Spontaneous intracranial hypotension (SIH) results from cerebrospinal fluid (CSF) leakage due to spinal dural tears or CSF–venous fistulas. Orthostatic headache is the hallmark presentation, though severe downward displacement of the brainstem may lead to altered consciousness or coma. Definitive treatments include targeted epidural blood patches, venous embolization, or surgical repair. Methods This article reviews the role of the Trendelenburg position as a temporizing measure in the acute management of SIH. We describe the correct technique, physiologic rationale, and practical considerations for its application, with attention to both therapeutic and diagnostic utility. Discussion Positioning the patient with the feet elevated above the head can reduce brain sag and provide short-term symptomatic relief while awaiting definitive treatment. Although the Trendelenburg position is widely used in practice, supporting evidence remains limited, and clinicians must be aware of its benefits, indications, and inherent limitations. Its appropriate application may assist in stabilizing patients with acute or severe SIH, particularly those with impaired consciousness, until more definitive interventions are pursued.