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.

Introduction Software packages for quantification of CT perfusion parameters allow quick visualization of perfusion deficits to support clinical decision making in acute ischemic stroke (AIS). Several packages are now commercially available for automated quantification of ischemic core, penumbra volumes, and mismatch ratios to indicate eligibility for reperfusion therapies. This study explored the agreement between two software packages, Brainomix 360 e‐CTP and Rapid CTP, in prospective, real‐world use. Methods Consecutive patients scanned for suspected stroke at three comprehensive stroke centers over 90 days from May to July 2024 were included in the study. Eligibility for the current analysis was limited to discharge diagnosis of AIS and CTP imaging processed by both Brainomix and Rapid software. Software processing was conducted in real time after image acquisition. The presence of large vessel occlusion (LVO) was determined from review of electronic medical records. CTP core (CBF<30%) and penumbra (Tmax>6s) volumes from Brainomix and Rapid were recorded for each case. Mismatch ratios were calculated (penumbra÷core volume); positive mismatch was defined according to DEFUSE‐3 criteria (core<70ml, penumbra>15ml, mismatch ratio > 1.8). The correlations and linear regressions between Brainomix and Rapid were computed for core, penumbra and mismatch ratios, and their concordance for mismatch positivity was assessed. Results 137 patients were scanned and received a final diagnosis of AIS. Of these, only 38 had imaging processed by both Brainomix and Rapid. Median age was 69 years (interquartile range: 57‐77.5y); 16 (42%) were female; 13 (34%) had LVO. Linear models between Brainomix and Rapid's outputs for CBF and Tmax volumes are shown in Figure 1a and 1b. The correlation between software outputs for CBF volume was r=0.70 (p<.001), and for Tmax volume was r=0.72 (p<.001). Mismatch ratios were calculated for the 13 cases with LVO (Figure 1c). The linear model between mismatch ratios was not significant, with four Rapid outputs showing infinite mismatch ratios (due to having CBF volumes of 0ml). Concordance between software for mismatch positivity was good; 8/13 cases showed mismatch on both softwares; 1 case showed mismatch on Brainomix only; 1 for Rapid only; and 3 cases showed mismatch on neither software. Conclusion This prospective study, despite limited sample size (N=38), showed good correlations between Brainomix 360 e‐CTP and Rapid CTP for calculation of both core and penumbra volumes. Although mismatch ratios showed less agreement, the categorization of mismatch positivity showed good concordance between software platforms. image

ABSTRACT Background Given the Centers for Medicare and Medicaid Services' coverage of screening CT colonography (CTC) beginning in January 2025, we evaluated the cost‐effectiveness of CTC for colorectal cancer (CRC) screening by race (Black and White) and gender, considering real‐world screening adherence. Methods A microsimulation model compared CRC screening strategies in average‐risk adults by race and gender, incorporating 2010–2019 U.S. data on disease progression and real‐world screening adherence for colonoscopy and fecal immunochemical test (FIT). Five strategies were compared: (1) status quo (choice between colonoscopy and FIT); (2) CTC every 5 years; (3) colonoscopy every 10 years; (4) annual FIT; and (5) multitarget stool DNA test every 3 years, plus no screening. Lifetime costs, quality‐adjusted life years gained (QALYG), and incremental cost‐effectiveness ratios were projected. A willingness‐to‐pay threshold of $100,000/QALYG was used. Results Under the status quo, Black adults showed higher CRC cases and greater utilization for FIT over colonoscopy than White adults. Compared to the status quo, the CTC strategy yielded more QALYG and fewer CRC cases among Black adults, but fewer QALYG and more CRC cases among White adults. Both status quo and CTC strategies outperformed other strategies across races. The CTC strategy was the dominant strategy for Black adults. For White adults, the status quo was cost‐effective with incremental cost‐effectiveness ratios of $34,998–$73,428/QALYG, while the CTC strategy was cost saving compared to no screening. Conclusions CTC could be cost‐effective for CRC screening in Black adults under real‐world screening adherence, supporting Medicare coverage to address specific population needs and structural barriers to screening.

Importance Treatment for cognitive dysfunction due to postacute sequelae of long COVID (ie, symptoms of fatigue, malaise, weakness, confusion that persist beyond 12 weeks after an initial COVID infection) remains a significant unmet need. Objective To test evidence-based rehabilitation strategies for improving cognitive symptoms in persons with long COVID. Design, Setting, and Participants This was a 5-arm, multicenter, randomized clinical trial of 3 remotely delivered interventions conducted between August 17, 2023, and June 10, 2024. The study took place at 22 trial sites and included the screening of individuals with cognitive long COVID. Interventions Participants were randomized to 1 of 5 arms: adaptive computerized cognitive training (BrainHQ [Posit Science]), cognitive-behavioral rehabilitation involving both group and individual counseling sessions (PASC-Cognitive Recovery [PASC-CoRE]) paired with BrainHQ, and transcranial direct current stimulation (tDCS) paired with BrainHQ. Two comparator arms were included as follows: unstructured computer puzzles and games (active comparator) and sham tDCS paired with BrainHQ. The interventions occurred 5 times per week over 10 weeks. Main Outcomes and Measures Cognitive and behavioral in-person assessments were performed at baseline, midintervention, at the end of intervention, and 3 months after the end of the intervention. The primary outcome measure was the modified Everyday Cognition Scale 2 (ECog2) completed at the end of the intervention compared to the baseline visit based on participant self-report looking back over the prior 7 days. Results A total of 378 individuals were screened, from which there were 328 participants (median [IQR] age, 48.0 [37.0-58.0] years; 241 female [73.5%]; race: 15 Asian [4.6%], 47 Black [14.3%], and 235 White [71.6%]; ethnicity: 52 Hispanic [15.9%]). None of the 3 active interventions demonstrated benefits on the modified ECog2 in the intention-to-treat population by the end of the intervention period. The adjusted differences in mean change were 0.0 (95% CI, −0.2 to 0.2) for BrainHQ vs active comparator, 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs active comparator, 0.0 (95% CI, −0.2 to 0.2) for tDCS-active + BrainHQ vs tDCS-sham + BrainHQ, and 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs BrainHQ alone. Secondary participant-reported outcomes and neuropsychological tests showed no differential benefits for any treatment arm. All 5 arms demonstrated some improvements over time on the modified ECog2 and on secondary outcomes. There were no serious adverse events attributable to the interventions. Conclusions and Relevance This phase 2 randomized clinical trial failed to demonstrate differential benefits for online cognitive training, a structured cognitive rehabilitation program, and tDCS for cognitive long COVID. Trial Registration ClinicalTrials.gov Identifier: NCT05965739 .

Immune checkpoint inhibitors (ICIs) are an important class of cancer treatment. Endocrine immune-related adverse events (E-irAEs) account for a significant proportion of irAEs in ICI-treated patients. Diagnosing E-irAEs accurately and timely can be challenging in the absence of clear categorization and standardization across oncology, endocrinology and other specialties. While existing guidelines provide some broad directions to diagnosis and management, they lack clarity on irAE-specific symptom evaluation and work-up, as well as assessment of severity. These limitations can then impact triage, time-sensitive management and care escalation to specialists such as oncoendocrinologists. The objective of this study was to develop consensus-based statements on disease definitions for E-irAEs. A core working group of endocrinologists with expertise in the oncoendocrinology field drafted a survey with statements outlining the general approach to E-irAEs, disease definition and management approach of six specific diagnoses: ir-thyroiditis thyrotoxic phase, ir-thyroiditis hypothyroidism, ir-Graves’ disease, ir-hypophysitis, ir-adrenalitis and ir-type 1 diabetes mellitus. Severity grading tables were drafted for three disease categories—“thyroid”, “pituitary and adrenal”, and “diabetes mellitus”. A two-round modified Delphi process, using the RAND/University of California Los Angeles (RAND/UCLA) Appropriateness Method, was employed. In this process, a 25-member voting panel consisting of endocrinologists, oncologists and other specialists and healthcare providers with experience in management of ICI-treated patients and irAEs was recruited. The panel rated anonymously on usability, accuracy, appropriateness or agreement of 41 items on a 9-point scale in Survey 1, after which a meeting was convened. Statements were modified based on voting results from Survey 1 and Meeting 1, and the process was repeated in Survey 2 and Meeting 2. At the end of this process, consensus was achieved for all statements. Our study findings address the gap in standardized nomenclature, clinical, laboratory and radiological evaluations, and management principles of E-irAEs. With consensus achieved from a panel of experts from a variety of disciplines, we anticipate that the statements can form the basis for standardization of the diagnostic process and improvement of patient care.

Abstract INTRODUCTION In multicenter Alzheimer's disease studies, amyloid positron emission tomography (PET) visual reads are typically performed centrally by a few experts. Incorporating a broader reader network enhances scalability and generalizability. METHODS Ten neuroimaging experts from eight Alzheimer's Disease Research Centers (ADRCs) visually read 180 amyloid PET scans (30 scans and 15 duplicate scans for each of four tracers, imaged across a wide variety of scanners), using preferred reading software without anatomical imaging or quantitation. Scans were classified as elevated or non‐elevated per tracer‐specific criteria. Inter‐ and intra‐rater agreement was assessed. RESULTS Inter‐rater agreement was substantial (Fleiss’ κ = 0.78), with full consensus on 69% of scans. Inter‐rater reliability was substantial to perfect across tracers (Fleiss’ κ = 0.70–0.87). Intra‐rater agreement was substantial to perfect (Cohen's κ = 0.79‐1). Scans with intermediate (10–40 Centiloid) quantitation had lower reader agreement. DISCUSSION A multicenter expert network achieved substantial agreement classifying amyloid PET scans. These scans provide a standard for reader training and reliability assurance in future studies. Highlights Calibration methods ensure reliable amyloid positron emission tomography (PET) visual reads across multiple raters. Substantial agreement is possible across readers using their preferred tools. Agreement is also substantial regardless of the amyloid PET tracer used. Scans with intermediate (10–40 Centiloid) quantitation have lower reader agreement. The calibration set will become a training tool for amyloid PET visual read studies.

Abstract Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare, deadly form of ovarian cancer that uniformly harbors mutations in SMARCA4, a member of the SWI/SNF chromatin remodeling complex. SWI/SNF impacts RNA splicing, and dysregulation of splicing can generate immunogenic tumor antigens. Here, we explored the relationship between SMARCA4 loss and RNA splicing dysregulation. SCCOHT primary tumors harbored tumor-associated outlier splicing events compared to normal tissues. Many of the tumor events were retained introns encoding novel peptides predicted to bind to MHC-I complexes. Immune cells were observed in primary SCCOHT tumors, suggesting a potentially immune reactive tumor microenvironment. Mutations in several SWI/SNF subunits were associated with higher rates of outlier retained introns across tumor types in TCGA data. Interestingly, RNA sequencing of isogenic SCCOHT cell lines demonstrated a role for SMARCA4 in intron retention. Distinct protein-protein interactions between splicing factors identified in SCCOHT cell lines supported a role for SMARCA4 in splicing regulation. Further, SWI/SNF localized to genes which were differentially spliced. Mass spectrometry analyses confirmed expression of some of these novel peptides and a subset of these are predicted to bind to MHC-I complexes. A pool of these novel peptides derived from retained introns in SCCOHT triggered proliferation and expression of TNFa and INFb in primary human T cells. Together, these data suggest that SMARCA4 loss in SCCOHT leads to intron retention. Furthermore, T cell activation by novel peptides encoded by these tumor-specific splicing events suggests intron retention could be a source of tumor-associated antigens in SCCOHT. Citation Format: Elizabeth Raupach, Apurva Hegde, Krystine Garcia-Masnfield, Marice Alcantara, David Rose, Rebecca Halperin, Krystal Orlando, Jessica Lang, Ritin Sharma, Victoria David-Dirgo, Salvatore Facista, Rayvon Moore, Rochelle Kofman, Zoe Jensen, Victoria Zismann, Anthony Karnezis, Yemin Wang, Lynda Bennett, Timothy Whitsett, Marcin Kortylewski, William Hendricks, David Huntsman, Lorna Rodriguez-Rodriguez, Bernard Weissman, Jeffrey Trent, Patrick Pirrotte. Loss of SMARCA4 leads to intron retention and generation of tumor-associated antigens in small cell carcinoma of the ovary, hypercalcemic type [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Ovarian Cancer Research; 2025 Sep 19-21; Denver, CO. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl):Abstract nr B065.

Importance Advances in Alzheimer disease (AD) have shifted research focus to earlier disease stages, necessitating more scalable approaches to identify cognitively unimpaired individuals with amyloid β (Aβ) pathology. Objective To assess the utility of plasma phosphorylated tau 217 (p-tau217) for classifying Aβ status in cognitively unimpaired individuals, both as a stand-alone test and in a 2-step approach where positive plasma results were confirmed using a second modality (Aβ positron emission tomography [PET] or cerebrospinal fluid [CSF]). Design, Setting, and Participants This cross-sectional cohort study used data collected between June 2009 and March 2024. We included 2916 cognitively unimpaired participants from 12 international independent observational cohorts in the US, Europe, Australia, and Canada with available plasma p-tau217 levels and CSF or PET Aβ biomarkers. Performance comparisons between mass spectrometry and immunoassay-based p-tau217 measurements were also performed (n = 964). Exposures Plasma p-tau217 levels measured by immunoassay. Main Outcome and Measures Aβ status, determined by CSF or Aβ PET biomarkers. Results Participants had a mean (SD) age of 66.9 (9.9) years; 971 (33.3%) were Aβ positive by either CSF or PET, 1667 (57.2%) were women, and 1108 (38.1%) carried at least 1 APOE ε4 allele. As a stand-alone test, plasma p-tau217 achieved a positive predictive value (PPV) of 79% (95% CI, 74-84) and an overall accuracy of 81% (95% CI, 80-82). In a 2-step workflow, the PPV and accuracy significantly increased to 91% (95% CI, 86-95). While this approach required screening of 677 individuals with plasma p-tau217 to identify 100 Aβ-positive individuals, compared to 536 participants when using PET alone, it reduced the need for PET testing to 124. Immunoassays demonstrated comparable PPVs to mass spectrometry (80% [95% CI, 74-86] vs 85% [95% CI, 81-90]; P = .12) but significantly lower overall accuracy (82% [95% CI, 79-84]% vs 88 [95% CI, 86-90]; P &amp;lt; .001) and true Aβ-positive detection rate (49% [95% CI, 43-55] vs 69% [95% CI, 64-75]; P &amp;lt; .001). Conclusions and Relevance The findings highlight the potential of plasma p-tau217 as a stand-alone test—or when used in a sequential 2-step approach alongside PET or CSF testing—as a cost-effective, scalable, and minimally burdensome strategy for identifying preclinical AD. Tailored screening workflows that incorporate p-tau217 can improve efficiency in participant selection for preclinical AD trials and, in the future, help guide access to disease-modifying treatments.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.