Citations

Abstract Background Dose‐driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness. Purpose This study introduces a Break Spot‐Guided (BSG) method, combined with two acceleration strategies—dose rate skipping and bounding—to optimize beam intensity while minimizing beam delivery time (BDT). In addition, a ‐method is proposed for efficient move spot generation, aiming to balance computational efficiency and dose calculation accuracy. Methods The BSG framework simplifies the original mixed‐integer nonlinear programming (MINLP) problem by transforming it into a series of TSP evaluations using break‐spot dose rates. The two acceleration strategies are integrated to reduce computational complexity. The ‐method is introduced to efficiently generate move spots without compromising dose fidelity. The performance of the BSG method, with and without the acceleration strategies, and the ‐method, was evaluated across multiple clinical cases. Results By jointly optimizing the scan path and dose rate, the proposed BSG‐S‐B method offered the most efficient delivery, achieving a 64% reduction in BDT compared to DSS and a 57% reduction compared to Liu's method in the prostate case. These gains were consistently observed across all cases. Utilizing acceleration strategies, BSG‐S‐B significantly reduced computation time from hours to minutes (e.g., from 10 525.7 to 108.5 s in the prostate case, and from 6202.4 to 129.8 s in the head‐and‐neck case). When combined with the ‐method, it reduced the number of move spots by more than 50%, while still ensuring dosimetric quality. Conclusions The proposed framework significantly improves computational efficiency, making scan path optimization with dose rate selection feasible for clinical DDCS delivery. The ‐method effectively reduces computational complexity while maintaining dose calculation accuracy, demonstrating strong potential for clinical adoption in proton therapy treatment planning.

ABSTRACT Introduction Children with hepatoblastoma (HB) and other solid tumors frequently undergo intraoperative blood transfusion (IBT) with unknown impact on oncologic outcomes and scant data to guide transfusion in this population. This study tested the hypothesis that IBT is associated with poorer survival in children with HB. Methods A multicenter retrospective observational study of patients aged <18 years with HB who underwent primary tumor resection, including liver transplantation, from 2010 to 2019 was performed at 19 institutions. The association of IBT with risk of recurrence and death were determined using propensity score reweighted (PSR) Cox proportional hazards regression analyses. Results There were 338 patients identified who met inclusion criteria and had sufficient data for inclusion. Of those, 257 (76%) received IBT, including 253 (98%) who received packed red blood cells (pRBC), 84 (33%) who received plasma, and 28 (11%) who received platelets. IBT was associated with higher pretreatment extent of disease ( p < 0.001), presence of annotation factors (+VPEFR: 50%, n = 129 vs. 37%, n = 30, p = 0.035), and complex resections (extended, meso‐, or total hepatectomy: 54%, n = 139 vs. 27%, n = 22, p < 0.001); these differences were mitigated after applying propensity score weighting. Patients who received IBT had greater postoperative hemoglobin (g/dL) (median 10 (I8–11) vs. 9 (8–10), p = 0.013) and required more postoperative plasma and platelet transfusions ( p < 0.05). Median follow‐up was 4.4 (2.0–8.3) years. Compared with non‐IBT patients, those with IBT had higher incidence of death (PSR HR 2.35, 95% CI 1.10–5.02). Recurrence did not significantly differ across groups (PSR HR = 0.82, 95% CI 0.45–1.48). Conclusion IBT was associated with greater hazard of death. Postoperative hemoglobin levels suggested that unnecessary transfusions occurred and a pRBC‐focused approach to IBT led to coagulopathy. Development of optimal transfusion strategies for HB are needed to minimize unnecessary transfusions.

Abstract Despite significant therapeutic advances in multiple myeloma (MM), outcomes in patients with plasma cell leukemia (PCL) remain dismal. We conducted a multicenter retrospective analysis of patients with PCL who were treated with the B-cell maturation antigen–directed chimeric antigen receptor T-cell (CAR-T) products idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel). We identified 34 patients; 19 patients received ide-cel and 15 received cilta-cel. With a median follow-up of 11.9 months, the overall median progression-free survival (mPFS) was 9.0 months (95% confidence interval [CI], 4-15) and the median overall survival (mOS) was 13.0 months (95% CI, 8 to not estimable [NE]). The 1-year cumulative incidence of progression or death was 72%, and the 1-year cumulative incidence of death was 47%. Patients who received cilta-cel had a longer mPFS (19.0 months vs 6.0 months) and mOS (&gt;23 months [NE] vs 9.0 months) when compared with those treated with ide-cel. Similarly, the 1-year cumulative incidence of disease progression or death was 37.5% (95% CI, 17.4-68.5) with cilta-cel, whereas all patients treated with ide-cel progressed or died within 12 months of infusion. The rates of hematologic and nonhematologic toxicities were similar between patients treated with cilta-cel and those treated with ide-cel and were consistent with those reported in patients with MM. In this first multicenter study that evaluated patients with PCL who were treated with standard-of-care CAR-T products, we show that CAR-T is safe, feasible, and associated with improved outcomes when compared with historic standards.

Introduction: Endovascular thrombectomy (EVT) is an effective treatment for basilar artery occlusion (BAO) stroke in select patients. While there is a growing body of literature suggesting that advanced imaging modalities such as computed tomography perfusion (CTP) and magnetic resonance (MR) may not be necessary for selecting anterior circulation large vessel occlusion stroke patients for EVT, whether advanced imaging may be superior to conventional imaging (non-contrast CT and CT angiography) in identifying good treatment candidates among BAO patients is less clear. Patients and methods: This was a multicenter retrospective cohort study of BAO EVT patients treated from 2013 to 2022 in the Stroke Thrombectomy and Aneurysm Registry. Patients selected for EVT by advanced imaging (CTP or MR) were matched with those selected by conventional imaging using propensity score matching (PSM) accounting for possible confounders. Primary outcome was functional independence at 90 days. Other outcomes include bedridden state or death at 90-days and symptomatic intracranial hemorrhage (sICH). Results: 268 patients were included. 150 patients were selected for BAO EVT by conventional imaging, 86 by CTP, and 32 by MR. Patients selected by advanced imaging were significantly older than those selected by conventional imaging (median age 71 vs 64 years, p = 0.001); patient characteristics were otherwise similar between cohorts. After PSM, 90-day outcomes were similar between the two cohorts ( p = 0.56), with similar rates of functional independence (39.4% vs 35.1%, p = 0.65), bedridden state or death (40.4% vs 44.7%, p = 0.66), and sICH (3.3% vs 5.7%, p = 0.49) for conventional and advanced imaging groups, respectively. Results were similar across treatment time windows (all p > 0.05). Conclusions: Selecting patients for basilar EVT using conventional versus advanced imaging did not result in different clinical outcomes, regardless of treatment time windows. Conventional imaging appears sufficient as a first-line tool for selecting basilar EVT patients in routine clinical practice.

Abstract Background Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. Methods We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. Results The logit-scale heritability of breast cancer ranged from ℎ 2 =0.47 (SE = 0.07) in EAS to AFR ℎ 2 =0.61 (SE = 0.10), with no significant differences across ancestries (p=0.63). The estimated number of susceptibility markers in a sparse normal-mixture effects model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p=0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (𝜌 = 0.79, SE = 0.08) and weakest between AFR and H/L (𝜌 = 0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. Conclusion These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.

Background and objectives Arteriovenous malformations (AVMs) with perinidal aneurysms and single draining vein are associated with an elevated risk of rupture and increased procedural complexity. The role of preoperative embolization in this high-risk anatomical subset remains unclear. This study aimed to evaluate the safety and efficacy of microsurgery with preoperative embolization, compared with microsurgery alone in patients with such AVMs. Methods We conducted a multicenter retrospective analysis of an AVM registry from the MISTA (Multicenter International Study for Treatment of Brain AVMs) consortium and included AVMs with perinidal aneurysms and a single draining vein. Baseline characteristics, angiographic outcomes, functional outcomes, and complication rates were compared. Propensity score weighting (PSW) using the covariate balancing method was applied to adjust for baseline differences. Results Out of a total of 1919 patients, 65 met the inclusion criteria; 45 patients underwent preoperative embolization followed by microsurgery, and 20 underwent microsurgery alone. After adjustment, complete obliteration rates were similar between groups (OR 0.87, 95% CI 0.04 to 16.33, P=0.92), as were rates of functional independence at discharge and follow-up. Overall complication, symptomatic complication, and mortality rates did not differ significantly between groups. However, permanent complications were significantly lower in patients with preoperative embolization (OR 0.06, 95% CI 0.004 to 0.84, P=0.03). Discussion In patients with AVMs featuring perinidal aneurysms and single draining vein, preoperative embolization followed by microsurgery was associated with fewer permanent complications and no increase in adverse outcomes compared with microsurgery alone. However, given the small number of events, this finding should be interpreted cautiously.

Abstract Objective: Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network. Methods: We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit. Results: The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility. Conclusion: This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.

Abstract The cumulative impact of baseline comorbidities on outcomes of chimeric antigen receptor T-cell (CAR-T) therapy is not well established. Therefore, we developed and validated a Cellular Therapy Comorbidity Index (CT-CI) to predict outcomes following CD19-directed CAR-T therapy for large B-cell lymphoma (LBCL). Patients aged 18 or older receiving commercial CAR-T therapy for LBCL during 2017 to 2020 were selected from the Center for International Blood and Marrow Transplant Research registry. Patients were randomly assigned to training or validation cohorts. Comorbidities given weighted scores comprised the CT-CI, which was then validated for overall survival (OS) prognostication. A total of 1916 patients from 97 medical centers were included, with a median age of 64 years (19-91 years). About 70% of patients had comorbidities, such as cardiac disease (12%); diabetes (14%); hepatic dysfunction (mild, 8%; moderate to severe, 2%); psychiatric disturbance (18%); and pulmonary dysfunction (moderate, 15%; severe, 12%). The CT-CI was calculated, stratified patients in 3 categories, and was associated with increased mortality. Patients with higher CT-CI scores had worse OS (CT-CI 1: hazard ratio [HR], 1.37 [95% confidence interval [CI], 1.16-1.62; P&lt; .001]; CT-CI 2: HR, 1.49 [95% CI, 1.17-1.89; P = .001]; CT-CI ≥ 3: HR, 2.55 [95% CI, 1.90-3.42; P&lt; .001]). Higher CT-CI scores predicted treatment-related mortality and relapse. There was no correlation between the CT-CI score and CAR-T–related toxicities. The novel CT-CI score stratifies the effect of patient comorbidities on survival after CAR-T therapy and can be used for clinical decision-making and treatment selection in high-risk populations. However, comorbidities and fear of increased toxicity should not preclude patients from this effective therapy.