Citations

Importance Ischemia-reperfusion injury contributes to graft dysfunction after liver transplant. Hypothermic oxygenated perfusion (HOPE) has been shown to improve liver function, but its benefit in extended criteria donors in a US population remains unclear. Objective To assess whether back-to-base portal-venous HOPE impacts outcomes after liver transplant in the US. Design, Setting, and Participants The Bridge to HOPE Trial is a multicenter, randomized, open-label trial with 1-year follow-up. The study took place at 15 US liver transplant centers and patients were enrolled between January 2021 and May 2023. Central assessment of complications and cholangiograms for nonanastomotic biliary strictures (NAS) was blinded to treatment arm. Participants included 219 recipients of extended-criteria donor livers after brain death (DBD) and after circulatory death (DCD) who were randomized 1:1 to HOPE after static cold storage (SCS) (n = 109) or SCS only (n = 110). Randomization was performed after liver inspection and acceptance for transplant. Data were analyzed from December 2024 to July 2025. Intervention After SCS and transport, livers underwent portal-venous HOPE until implant, using the VitaSmart HOPE System. Main Outcomes and Measures The primary efficacy end point was early allograft dysfunction (EAD). Other main outcomes included model for early allograft function (MEAF) score, hospital length of stay (LOS), patient and graft survival, and biliary complications. Additional post hoc analyses were performed. Results Overall, 219 patients (82 female [37.4%] and 137 male[62.6%]) were included (DCD, 57 of 219 [26%]) with 97% (212 of 219) completing 12-month follow-up. EAD incidence was 20.2% (22 of 109) with HOPE vs 37.3% (41 of 110) with SCS (rate difference, −17.1%; 95% CI, −27.2 to −7.0; noninferiority P < .001; superiority P = .005). HOPE treatment led to significantly lower MEAF mean (SD) scores (HOPE group, 4.28 [1.75]; control group, 4.82 [1.85]; mean difference, −0.54; 95% CI, −1.02 to −0.06; P = .03) and shorter median LOS (hazard ratio, 1.32; 95% CI, 1.01-1.73; P = .04). NAS on imaging and 1-year survivals were comparable between groups (patients: HOPE group, 106 of 109 [97.2%] vs SCS, 106 of 110 [96.4%]; graft: HOPE group, 104 of 109 [95.4%] vs SCS, 102 of 110 [92.7%]). Post hoc analyses showed numerically less graft loss due to NAS after HOPE (4 vs 1) and less major complications (Clavien-Dindo classification ≥IIIa) per patient, respectively. Conclusions and Relevance Back-to-base portal-venous HOPE was compared with SCS alone for extended risk DBD and DCD livers. The HOPE approach was safe and associated with reduced EAD, MEAF score, and LOS. These findings support the use of HOPE as a pragmatic strategy to improve early posttransplant outcomes. Trial Registration ClinicalTrials.gov Identifier: NCT05045794 .

Abstract Background Accurate and efficient dose calculation is essential for online adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results for pencil beam scanning proton therapy (PBSPT) in recent years, but existing DL‐based dose prediction methods still suffer from limited generalizability and an inability to effectively handle outlier clinical cases. This may lead to inaccurate dose delivery to targets or excessive irradiation to organs at risk (OARs), thereby compromising the safety and efficacy of online adaptive proton therapy. Purpose To design a physics‐aware and generalizable AI‐based PBSPT dose prediction method that incorporates underlying physics to enhance generalizability, particularly in handling outlier clinical cases. Methods This study analyzed PBSPT plans of 103 prostate (93 for training and 10 for testing) and 78 lung cancer patients (68 for training and 10 for testing) from our institution, with each case comprising CT images and structure sets. Using the doses generated by our Monte Carlo‐based dose engine as the reference standard, we compared three methods: the region of interest (ROI)‐based method, the beam mask and sliding window method, and the proposed noisy probing dose method, which rapidly generates a low‐statistics dose via uniformly weighted spots on an expanded spot‐placement target volume without optimization. To evaluate the generalizability of these methods to rare treatment planning scenarios, 12 cases with uncommon beam angles or prescription doses were used to assess their performance, which was evaluated using dose‐volume histogram (DVH) indices, 3D Gamma passing rates (3%/2 mm/10%), and Dice coefficients for dose agreement, while prediction times were measured to gauge model efficiency. Results The proposed noisy probing dose method consistently outperformed the ROI‐based and beam mask baselines across all evaluated metrics, with more accurate dose agreement and superior generalizability. For DVH indices, the noisy probing dose method achieved the smallest deviation in clinical target volume (CTV) dose coverage: in prostate cancer, CTV D98 deviation was reduced by 45% (from 0.53 ± 0.22 Gy [RBE] for ROI‐based) and 29% (from 0.41 ± 0.28 Gy [RBE] for beam mask) to 0.29 ± 0.06 Gy [RBE]; in lung cancer, similar improvements were observed, with CTV D98 deviations reduced to 0.34 ± 0.12 Gy [RBE]. The 3D Gamma passing rates improved to 99.65% ± 1.15% for prostate targets and 97.04% ± 1.17% for lung targets. The dice coefficients of the 90% iso‐dose lines were also the highest with the noisy probing dose method (prostate: 0.983 ± 0.005; lung: 0.967 ± 0.01). For the 12 outlier cases, the noisy probing dose method maintained superior generalizability, yielding higher 3D Gamma passing rates (prostate targets: 96.79% ± 0.83%, OARs: 94.29% ± 1.01%; lung targets: 93.38% ± 1.34%, OARs: 93.95% ± 1.32%), demonstrating robust generalizability to rare clinical scenarios. The dose predictions for all testing cases were completed within 0.3 seconds. Conclusions A novel noisy probing dose method was proposed for PBSPT dose prediction in prostate and lung cancer patients. By embedding more proton‐specific physics, this method demonstrated an improvement in the generalizability of dose prediction.

OBJECTIVE Historically, craniopharyngioma (CP) was divided into adamantinomatous CP (ACP) and papillary CP (PCP) subtypes based on histopathological features. However, each harbors a unique genetic profile and progressively differing treatment paradigms, leading to their reclassification by the WHO in 2016 as two distinct entities. Descriptive in nature, this large multi-institutional study aimed to establish current differences between the presentation, treatment patterns, and clinical course of these pathologies to serve as a baseline for future studies as new treatment paradigms emerge. METHODS The authors queried the Registry for Adenomas of the Pituitary and Related Disorders (RAPID) database, which encompassed patients from 14 participating institutions across the United States between 2000 and 2024. The database was screened for adult patients who underwent initial CP treatment with a confirmed histopathological diagnosis of ACP or PCP. Patient demographic characteristics, clinical course, tumor treatment, and outcomes data were collected and compared by CP type. RESULTS The final analysis included 273 ACP and 99 PCP adult patients who underwent initial surgical treatment. ACP patients presented younger on average (mean 48.3 vs 52.8 years, p = 0.034). PCP patients were more likely to present with hypothyroidism (33.3% vs 20.5%, p = 0.010), hyperlipidemia (25.3% vs 15.8%, p = 0.036), fatigue (28.3% vs 17.6%, p = 0.024), temperature intolerance (9.1% vs 1.5%, p < 0.001), and cardiac arrhythmia (6.1% vs 1.1%, p = 0.006). The groups demonstrated similar postsurgical and neuroendocrinological outcomes. Postoperative median (IQR) progression-free survival did not significantly differ between groups (19.0 [7.0–37.0] for ACP vs 5.0 [3.5–7.5] months for PCP, p = 0.972). ACP patients were more likely to receive radiation after surgery (27.8% vs 15.2%, p = 0.012). CONCLUSIONS This large multicenter descriptive study aimed to characterize similarities and differences between the clinical courses of molecularly distinct ACP and PCP, which has not previously been described. The findings should serve as a baseline to inform future studies, particularly with the recent introduction of targeted therapy for PCP.

OBJECTIVE Frailty is a known predictor of adverse outcomes in pituitary surgery, yet its impact regarding craniopharyngioma remains unclear. The authors assessed preoperative frailty, measured by the 11-factor modified frailty index (mFI-11), and its association with perioperative morbidity among adult patients undergoing craniopharyngioma surgery. METHODS Using the Registry for Adenomas of the Pituitary and Related Disorders (RAPID) database, the authors performed a retrospective cohort study of the records of patients ≥ 18 years of age who underwent craniopharyngioma surgery between June 2007 and November 2024. Patients were stratified into the following categories according to their numeric mFI-11 score: fit (scores 0 and 1), managing well (scores 2 and 3), and mildly frail (scores 4–6). Primary outcomes included hospital length of stay (LOS) and discharge disposition. Secondary outcomes included 90-day readmission, surgical outcomes, and complications. Multivariable analyses were performed to identify independent predictors of hospital LOS and non-home discharge, adjusting for age, surgeon experience, American Society of Anesthesiologists class, complications, and surgical approach. RESULTS Among 278 patients (221 fit, 43 managing well, 14 mildly frail), higher-frailty patients were older (mean age 47.8 ± 16.1 years in fit vs 60.1 ± 12.5 years in managing well vs 67.6 ± 8 years in mildly frail, p < 0.001) and more likely to present urgently (24.2% vs 36.4% vs 78.6%, p = 0.001). Gross-total resection was achieved less frequently in frail patients (44.8% vs 24.3% vs 23.1%, p = 0.030). Overall complication rates were similar; however, increasing frailty was associated with higher rates of postoperative mortality (0% vs 2.8% [1/36] vs 7.7% [1/13], p = 0.018), pneumonia (0.5% [1/195] vs 2.8% [1/36] vs 15.4% [2/13], p = 0.006), and reintubation (2.6% [5/195] vs 2.8% [1/36] vs 30.8% [4/13], p = 0.002). Higher frailty was associated with a stepwise rise in median [IQR] LOS (5 [3–8] days vs 7 [4–12] days vs 13 [6.5–21.8] days, p < 0.001) and remained an independent predictor of extended LOS on multivariable analysis (β = 1.729 per point, p = 0.006). Rates of non-home discharge showed a similar pattern (9.2% vs 30.0% vs 64.3%, p < 0.001), with frailty independently predicting non-home discharge (OR 2.352, 95% CI 1.527–3.822). Unplanned 90-day readmission rates were significantly higher in the mildly frail cohorts (22.5% vs 45.7% vs 53.8%, p = 0.002). CONCLUSIONS The mFI-11 scores independently predicted perioperative morbidity following craniopharyngioma resection. Incorporating frailty screening into preoperative screening may improve risk stratification, family and patient counseling, and discharge planning.

OBJECTIVE Craniopharyngiomas are benign intracranial tumors that can be difficult to manage operatively and often result in postoperative complications and prolonged recovery. Understanding the factors that influence length of stay (LOS), discharge disposition, and readmission can guide perioperative planning and patient counseling. The authors examined the clinical, radiographic, and surgical predictors of extended LOS (eLOS), nonhome discharge, 90-day readmission, and hospitalization ratio (HR) after craniopharyngioma resection using a large, multicenter cohort. METHODS A retrospective analysis was conducted using the Registry of Adenomas of the Pituitary and Related Disorders database, encompassing 469 patients who underwent craniopharyngioma resection at 14 US academic centers from 2011 to 2025. Patients were stratified by 4 outcomes: eLOS (> 75th percentile), discharge to home versus skilled nursing facility/rehabilitation, 90-day hospital readmission, and hospitalization ratio (i.e., integration of initial and readmission LOS). Multivariable logistic regression models identified independent predictors for each outcome among patient and surgical variables. RESULTS An eLOS (> 10 days) was independently associated with preoperative memory loss (OR 3.75, 95% CI 1.95–7.21), gait imbalance (OR 5.90, 95% CI 1.53–22.70), and postoperative complications (OR 4.07, 95% CI 2.34–7.06). The use of a nasoseptal flap was protective against an eLOS (OR 0.52, 95% CI 0.28–0.93). Discharge to home was predicted by an endoscopic approach (OR 3.87, 95% CI 1.78–8.44) and postoperative intact thirst (OR 2.22, 95% CI 1.05–4.66) and negatively predicted by preoperative diabetes mellitus (OR 0.21, 95% CI 0.09–0.50), LOS (OR 0.87, 95% CI 0.84–0.91), and postoperative cognitive dysfunction (OR 0.30, 95% CI 0.13–0.72). Among 385 patients with follow-up data, a 90-day readmission was independently associated with postoperative complications (OR 5.62, 95% CI 3.12–10.13), preexisting coronary artery disease (OR 4.30, 95% CI 1.46–12.69), and postoperative cognitive dysfunction (OR 3.33, 95% CI 1.76–6.44). A higher HR was associated with diabetes mellitus (unstandardized B 0.059, 95% CI 0.010–0.108, p = 0.02), postoperative complications (unstandardized B 0.054, 95% CI 0.021–0.086, p = 0.001), and postoperative cognitive dysfunction (unstandardized B 0.049, 95% CI 0.006–0.092, p = 0.02). Tumor pathologic subtype and size, prior treatment, extent of resection, and surgeon experience were not directly predictive of outcomes. CONCLUSIONS Cognitive and functional status, systemic comorbidities, and postoperative complications, in addition to surgical approach, are important predictors of the early clinical course after craniopharyngioma surgery. Early identification of high-risk patients may help to guide treatment decisions, improve discharge planning, and reduce healthcare utilization.

Artificial intelligence (AI) has emerged as a transformative force in liver transplantation (LT), spanning patient selection, donor–recipient matching, intraoperative management, and post-transplant care. Historically, applications have relied on traditional machine learning (ML) and deep learning (DL) techniques trained on structured clinical datasets to improve risk stratification and outcome prediction. Since 2023, however, advances in generative AI (GenAI) and large language models (LLMs) have expanded the scope of AI in LT, enabling multimodal reasoning and the extraction of clinically meaningful information from unstructured data. This review synthesizes recent AI-driven developments across the LT patient journey, from advanced chronic liver disease management to long-term post-transplant outcomes. Representative applications include ML-based models to optimize treatment selection and waitlist prioritization for hepatocellular carcinoma, random forest and gradient-boosting approaches to improve donor utilization and predict graft survival, and DL-based imaging models for graft volumetry and steatosis assessment. Post-transplant innovations encompass neural network models for graft injury classification, recurrent architectures for immunosuppression dosing and fibrosis prediction, multi-task frameworks for complication risk stratification, and integrative omics-based approaches to detect rejection and dysfunction. Emerging GenAI applications include LLM-enabled digital phenotyping of social determinants of health and multi-agent simulations of transplant selection committees. Despite rapid progress, translation into routine practice remains limited by challenges in local validation, workflow integration, and infrastructure requirements. Future opportunities lie in incorporating underutilized data domains, such as psychosocial factors, -omics, and intraoperative physiologic streams, and leveraging GenAI to enhance clinical decision support, research scalability, and patient–clinician communication. AI is poised not only to refine prediction but to reshape the conceptual and operational landscape of liver transplantation.

Objectives: To summarize current evidence for radiotherapy in the treatment of OA. The population, intervention, comparator, and outcome questions included: What is the role of LDRT for treatment of OA?; What are risks of LDRT?; and What are the optimal RT techniques for OA? Methods: This multispecialty-led committee includes radiation oncologists, rheumatologists, orthopedic surgeons, and a patient advocate. Using the population, intervention, comparator, outcome, timing and study design (PICOTS) framework, evidence regarding treatment outcomes was assessed using Cochrane and PRISMA methodology. Eligible studies included prospective and retrospective (n≥50) studies published between January 1, 2010, and May 10, 2025, from Embase, Medline, and PubMed databases. Study type and quality were assessed. Well-established RAND-UCLA consensus methodology (modified Delphi) was used to rate the appropriateness of the treatment options. Results: Of the 548 articles identified using the search strategy, 44 were selected for inclusion. Eight additional studies were identified through backward citation searching. Ten well-designed studies accounting for biases, 15 moderately well-designed studies accounting for the most common biases, 18 studies with design limitations, 8 supplemental studies not useful as primary evidence, and 1 meta-analysis were included. Additional studies were included to provide context and were not used to guide recommendations. The results of this analysis demonstrate that LDRT results in an overall treatment response rate of 60% to 90%, with significant clinical benefits including pain reduction, increased joint mobility, and improved quality of life. Conclusions: This systematic review and consensus guidelines for LDRT treatment of OA are based on current evidence. Further high-quality studies are warranted.

Abstract Background Vorasidenib is Food and Drug Administration‐approved for treatment of grade 2 isocitrate dehydrogenase (IDH)–mutant gliomas and has demonstrated a benefit in progression‐free survival compared to a placebo. This study assessed the cost‐effectiveness of this treatment strategy compared to standard treatment: observation or chemoradiation (CRT). Methods The authors used an integrated Markov model to compare quality‐adjusted life‐years (QALY) gained and cost‐effectiveness of patients with IDH‐mutated low‐grade glioma (LGG) treated with vorasidenib, observation, or CRT. Outcomes were expressed as incremental cost‐effectiveness ratios (ICERs) per QALY gained. Treatment is considered cost‐effective if it meets the commonly accepted willingness‐to‐pay threshold of $100,000 per QALY gained. Results Based on model parameters, vorasidenib demonstrated an ICER of $356,756 per QALY when compared to CRT. When compared to observation, vorasidenib demonstrated an improved ICER of $215,191 per QALY. On one‐way sensitivity analysis compared to observation, median cost of vorasidenib and median overall survival were most likely to affect ICER with only marginal changes on analysis of other model factors. For ICER to become ≤$100,000 compared to observation, the cost of vorasidenib would need to drop to below $14,072 monthly or have a median survival gain of at least 11.9 years. The probabilistic sensitivity analysis demonstrated that vorasidenib was favored in none of 5000 Monte Carlo iterations. Conclusion Using the best available data, the current price of vorasidenib does not meet commonly accepted cost‐effectiveness thresholds in treatment of IDH‐mutated LGGs.

ABSTRACT Age‐related changes in human hematopoietic stem cells (HSCs) often form the basis for clonal hematopoiesis (CH), which presages the development of overt myeloid neoplasm with variable risk. CH can also arise after exposure to chemotherapy, radiotherapy, or immune interventions. In this study, we performed clinico‐genomic profiling of therapy‐related CH (t‐CH) ( n = 67) versus de novo CH ( n = 123) from a multidisciplinary CHIP Clinic. The most enriched mutations in t‐CH were TET2 (26.2%), DNMT3A (22.4%), and TP53 (8.4%). Median latency period from the time of initial exposure to the diagnosis of t‐CH was 6.96 ± 1.10 years. Patients with t‐CH had inferior event‐free survival compared to de novo CH (median 29.9 months versus 122.1 months, p = 0.0045). Overall survival was also shorter in t‐CH versus de novo CH (median 55.3 months vs. 129.2 months, p = 0.043). Genes that imparted significantly increased risk for progression from t‐CH to overt therapy‐related myeloid neoplasm (t‐MN) included JAK2 (relative risk (RR) 9.42, p = 0.0001), RUNX1 (RR 7.11, p = 0.001), EZH2 (RR 7.11, p = 0.001), and TET2 (RR 13.4, p = 0.01). Clonal dynamic modeling of patients with t‐CH who progressed to overt t‐MN showed an increase in the relative clonal fraction and new clonal outgrowth. In the t‐CH cohort, higher mean variant allele frequency was observed in progressors versus non‐progressors (77.1% vs. 30.6%, p = 0.017). This study sheds light onto outcomes for CH based on differing clinical ontogeny and has implications for previvorship for secondary malignancies.