Citations

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.

Post-transplant lymphoproliferative disorder is a rare and serious complication of organ and stem cell transplant secondary to immunosuppressive therapies, most commonly of monomorphic B-cell subtype. Here we describe the first reported case of a pediatric heart transplant patient who developed both monomorphic B-cell and nondestructive PTLD with plasmacytic hyperplasia followed by an unrelated case of monomorphic T-cell and nondestructive PTLD with plasmacytic hyperplasia, which later relapsed. We detail the patient’s risk factors for development of PTLD and her successful treatment regimens. This case highlights the potential relationship between Epstein-Barr virus and/or cytomegalovirus and PTLD.

PURPOSE Gender bias against girls may affect health-seeking behavior and outcomes of childhood cancer. This study aimed to study the nature and extent of gender bias in health care among caregivers of childhood patients with cancer and also in community. METHODS This cross-sectional mixed-methods study was conducted in a tertiary cancer hospital and an urban community between July 2021 and July 2023. Qualitative component included 26 in-depth interviews (IDI) and four focus group discussions (FGDs) with caregivers of children with cancer. IDIs and FGDs were conducted by a psychologist and continued until thematic saturation was reached. For quantitative part, a gender-bias questionnaire was finalized which was administered to 230 caregivers in hospital and 311 participants from the community, with children in family. RESULTS Most participants did not perceive personal gender bias; however, many acknowledged noticing gender bias in others. This bias was linked to girls being considered financial burdens and having reduced marital prospects due to illness. Reducing treatment costs, improving access, and education targeting societal mindsets were suggested measures to mitigate bias. In community, no significant difference was observed among the respondents based on sex of youngest child in family. However, in hospital, caregivers of male children were less likely to offer similar care to a child of opposite sex than that reported by caregivers of female children ( P = .01) for ailments like fever/diarrhea. Similar difference was not observed for other health care scenarios. CONCLUSION Gender bias against girls, including that in health care access, is influenced by societal norms. Even with little personal perception of bias, there was a significant perceived bias observed in others by the participants. This study identified the existence of gender bias affecting health care choices, including cancer care.

Abstract Objective The objective of this study is to identify social/metabolic risk factors associated with subsequent diagnosis of adrenal adenoma Design The design is a population-based historical case–control study. Methods Cases were adult patients diagnosed with an adrenal adenoma between 2005 and 2017 with no overt hormone excess. Controls were age- and sex-matched individuals with (1) no diagnosis of adrenal adenoma and (2) no diagnosis of adrenal adenoma with cross-sectional imaging of the chest/abdomen performed within 5 years prior to index date. The frequency of various social/metabolic risk factors present 5-10 years prior to index date and odds ratios (ORs) for adrenal adenoma diagnosis were reported. Results Six hundred seventy cases identified (median age 63 years old, 56% women). During the 5-10 years prior to index date, patients with adrenal adenomas had higher prevalence of obesity (56.7% vs 49.3%, P = .007), low socioeconomic status (36.7% vs 31.1%, P = .039), tobacco use (70.2% vs 61.4%, P = .001), and diabetes (17.5% vs 11.7%, P = .003) compared to controls with prior imaging. No difference in prevalence of hypertension, substance use, chronic kidney disease, or combined cardiovascular events was observed. Based on a multivariable analysis, increased body mass index (BMI) and tobacco use were associated with increased odds of adrenal adenoma diagnosis with ORs 1.18 (95% confidence interval [CI] 1.07-1.32) and 1.41 (95% CI 1.06-1.87), respectively. Conclusions Compared to controls with prior imaging, patients with adrenal adenoma had higher prevalence of obesity, low socioeconomic status, tobacco use, and diabetes 5-10 years prior to index date. In particular, increased BMI and tobacco use were independent risk factors associated with increased odds of adrenal adenoma diagnosis.