Citations

Objective The objective of this study was to determine the predictive value of amyloid‐positron emission tomography (PET) versus the plasma ratio of phosphorylated tau at threonine 217 (p‐tau217) to non‐phosphorylated tau217 (%p‐tau217) for tau‐PET transitions (T− to T+). The added value of combining plasma amyloid‐β 42 and amyloid‐β 40 (Aβ42/40) and %p‐tau217 into an amyloid probability score (APS2) was also assessed. Methods Mayo Clinic Study of Aging (MCSA) participants had plasma markers measured at via mass spectrometry (MS), an amyloid‐PET scan, and a tau‐PET (meta‐temporal region of interest [ROI]) negative scan (standardized uptake value ratio [SUVR] <1.29) at the index (baseline) date, along with one or more follow‐up tau‐PET scans. The BioFINDER‐2 cohort was used for validation. Cox proportional hazards models adjusted for age, sex, and apolipoprotein ( APOE ) ε4 were used to assess predictors, with scaling to the interquartile range (IQR) for comparability of hazard ratios (HR). Results Among 255 tau‐PET negative MCSA participants (median age: 71.9 years), 37 converted to tau‐PET positive (median follow‐up time: 3.81 years). Higher %p‐tau217 (HR: 1.52 [95% CI: 1.28–1.80]), amyloid‐PET centiloid (HR: 1.47 [95% CI: 1.20–1.79]), and APS2 (HR: 1.62 [95% CI: 1.22–2.16]) predicted tau‐PET conversion. However, Aβ42/40 (HR: 0.94 [95% CI: 0.54–1.66]) was not associated with tau‐PET conversion. In the BioFINDER‐2 cohort (605 tau‐negative, median age: 70.2), 33 converted to tau‐positive (median follow‐up time: 2 years), with higher %p‐tau217 (HR: 1.80 [95% CI: 1.50–2.17]), amyloid‐PET centiloid (HR: 2.29 [95% CI: 1.77–2.97]), and lower Aβ42/40 (HR: 2.38 [95% CI: 1.17–4.83]) predicting conversion. Interpretation In two cohorts, %p‐tau217 was associated with tau‐PET conversion, comparable to amyloid‐PET. APS2 also predicted conversion in the MCSA cohort, whereas Aβ42/40 predicted conversion in the BioFINDER‐2 cohort, which had more individuals with cognitive impairment. ANN NEUROL 2025;98:1249–1260

With continued improvements in systemic cancer therapies, there has been an increase in the survivorship of patients with spinal metastases. However, many patients with spinal metastases are frail and may not be able to tolerate the morbidity of open surgery. For these patients, percutaneous ablation techniques offer a minimally invasive approach that can facilitate local tumor control and pain relief. Here we describe the currently employed modalities—radiofrequency ablation (RFA), microwave ablation (MWA), cryoablation, and laser interstitial thermal therapy (LITT)—summarize the clinical support for their use, and overview the relative risks and benefits for each. All these technologies offer to help improve local tumor control and improve oncologic pain associated with vertebral metastases, and they have become a staple of multidisciplinary spine metastasis care at many centers. As clinical experience with these technologies continues to grow, their use will likely become more widely adopted, and so understanding of their indications, risks, and benefits will become increasingly important to the practicing spine oncologist.

Introduction: We aimed to prove integration of advanced machine learning methods within a robust ensemble framework can enhance clinical decision-support for neurologists managing patients in the emergency department (ED). Methods: We engineered an ensemble framework leveraging the capabilities of the Gemini 1.5-pro-002 large language model (LLM). The model was enhanced using prompt engineering and retrieval-augmented generation (RAG). Predictive modeling achieved by combining eXtreme Gradient Boosting (XGBoost) and logistic regression for optimal accuracy in clinical decision-making. Key clinical outcomes, such as admission and mortality, were assessed. A random subset of 100 cases was reviewed by three senior neurologists to evaluate the alignment of the AI’s predictions with expert clinical judgment. Results: We retrospectively analyzed 1368 consecutive ED patients who underwent neurological consultations, assessing their clinical features, diagnostic tests, and admission outcomes. Patients admitted were typically older and had higher mortality rates, shorter intervals to neurological evaluation, and a higher incidence of acute stroke compared to those discharged. For the primary analysis (n = 250), the Neuro artificial intelligence (AI) model demonstrated significant performance metrics, achieving an area under the curve (AUC) of 0.88 for general admission predictions in comparison to actual outcomes, an AUC of 0.86 for neurological department admissions, 0.93 for long-term mortality risk, and 1 for 48 h mortality risk. Our Neuro AI model predictions showed a strong correlation with expert consensus (Pearson correlation 0.79, p < 0.001), indicating its ability to provide consistent support amid divergent clinical opinions. Conclusions: Our Neuro AI model accurately predicted hospital admissions (AUC = 0.88) and neurological department admissions (AUC = 0.86), demonstrating strong alignment with expert clinical judgment.

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 Isatuximab is an immunoglobulin G1κ monoclonal antibody that binds with high affinity to CD38 expressed on plasma cells. Anti-CD38 antibodies have shown efficacy as monotherapy and in combination in a variety of settings for patients with multiple myeloma and light chain (AL) amyloidosis. This multicenter, cooperative group phase 2 trial was designed to evaluate hematologic response, organ response, and safety of isatuximab monotherapy for the treatment of relapsed AL amyloidosis. Isatuximab at 20 mg/kg was administered IV weekly during the first 28-day cycle, and then every other week during cycles 2 to 24. Forty-three patients were registered, with 35 patients being evaluable for response. The overall hematologic response rate was 77.1%, with 57% of patients achieving a very good partial response (VGPR) or better. The median time to partial response (PR) or better was 1.1 months. Renal response occurred in 50% (7/14) of patients with renal involvement, and cardiac response occurred in 57% (8/14) of patients who were evaluable utilizing N-terminal pro b-type natriuretic peptide (NT-proBNP) with cardiac involvement. The most common treatment-related grade ≥3 adverse events included lymphopenia (n = 3, 8.5%) and infection (n = 2, 6%). Isatuximab demonstrated substantial efficacy in previously treated patients with AL amyloidosis, and was associated with a good safety profile. This trial was registered at www.clinicaltrials.gov as #NCT03499808.