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Abstract BACKGROUND Post-operative prognostication in glioma patients remains a clinical challenge, particularly given the heterogeneity in tumor biology and patient outcomes. We evaluated whether image-derived features from post-operative imaging improve survival modeling beyond established clinicopathologic factors. METHODS We analyzed a cohort of 71 post-surgical glioma patients treated at Princess Margaret Cancer Centre with known clinicopathologic features including age, histological classification, IDH mutation status, MGMT methylation status, extent of resection, and performance status. A baseline Cox proportional hazards model was fit to clinical variables. Radiomic features were extracted using PyRadiomics from post-operative CT and MRI across three regions of interest: whole brain, tumor bed, and peritumoral ring. Features underwent stepwise unsupervised reduction (variance filtering, exclusion of volume-correlated features, and removal of remaining collinear features), followed by dimensionality reduction via principal component analysis. Combined clinical and imaging models were evaluated in the overall cohort and stratified by IDH mutation status. RESULTS In the overall cohort, the clinical model was highly prognostic (C-index 0.74, p ~ 3.2×10⁻⁶). Adding imaging features improved performance (C-index 0.79) but was not significant (p ~ 0.31). Subset analysis revealed differential effects by IDH status. In IDH-mutant gliomas (n=24), neither clinical nor combined models were significant. In IDH wild-type glioblastoma (n=47), the clinical model achieved C-index 0.75 (p=0.04). The addition of imaging features significantly improved model performance (C-index 0.83, p=0.03), with selected imaging components contributing independent prognostic value after adjustment for clinical variables. Post-hoc analysis of radiomic feature importance (random forest ranking) revealed that top contributing features were drawn from both CT and MRI modalities, with most sourced from the whole brain region. CONCLUSIONS In post-surgical patients with IDH wild-type glioblastoma, image-derived features from post-operative imaging can significantly enhance prognostic modeling beyond known clinicopathologic factors. These preliminary findings support the potential role of radiomic biomarkers in refining risk stratification for this patient subgroup.

Importance Transthyretin amyloid cardiomyopathy (ATTR-CM) is underdiagnosed despite expanding treatment options. Objective To develop and evaluate an artificial intelligence (AI)–augmented clinical program for ATTR-CM detection. Design, Setting, and Participants This nonrandomized clinical trial involved constructing an AI model, ATTRACTnet, using electrocardiogram waveforms, echocardiographic measurements, demographics, and diagnosis codes for orthopedic manifestations of amyloidosis. A single-system, multisite, single-arm, open-label trial was conducted to evaluate its real-world performance. The model was trained and validated at a large academic referral site for ATTR-CM with external validation at an academic site. The trial was conducted as a single-system, multisite trial. Patients with left ventricular (LV) wall thickness 12 mm or more and an ATTRACTnet score 0.5 or higher were eligible. Exclusions included prior ATTR-CM testing, hypertrophic cardiomyopathy, expected life span less than 1 year, nursing home residence, advanced dementia, or LV wall thickness less than 14 mm explained by uncontrolled hypertension or moderate/severe aortic stenosis. Intervention Eligible patients were notified and offered nuclear scintigraphy testing, monoclonal protein testing, and follow-up care on agreement from the treating physician. Main Outcomes and Measure The primary outcome was a diagnosis of ATTR-CM by consensus criteria. ATTR-CM testing positivity was compared with historical and contemporary controls. Results ATTRACTnet was developed in an internal test set of 799 patients (mean [SD] age, 75.1 [11.1] years; 516 [64.7%] male and 283 [35.3%] female) using 5-fold cross-validation with an additional external test set of 422 patients. It had good discrimination for ATTR-CM detection with an area under the receiver operator characteristic curve of 0.85 (5-fold cross-validation, 0.77-0.85) in the internal set and 0.82 (95% CI, .81-0.83) in the external test set with similar performance in Hispanic, non-Hispanic Black, and non-Hispanic White patients. A total of 1471 patients were identified with positive AI model scores 0.5 or more during the study period, with 256 eligible patients who met study criteria. Of these patients, 50 underwent amyloidosis testing after physician and patient approval; 24 (48%) were diagnosed with ATTR-CM, and 21 (88%) initiated treatment within 3 months. The positivity rate was more than 2.8 times higher than historical controls (15.3%; 95% CI, 13.1%-17.9%; P < .001), with an 18% relative increase in new diagnoses vs the prior year. Conclusions and Relevance AI-augmented screening may improve ATTR-CM detection and identify patients who are missed by usual care. Prospective randomized trials are needed to determine if outcomes are improved. Trial Registration ClinicalTrials.gov Identifier: NCT06469372

BACKGROUND AND OBJECTIVES: The Patient-Generated Subjective Global Assessment (PG-SGA) is a standardized tool for assessing malnutrition in patients with cancer. The primary aim of this study was to assess the impact of preoperative nutritional status as measured by PG-SGA on survival in patients requiring surgical intervention and/or radiotherapy for spinal metastases. METHODS: Patients with spinal metastases who underwent surgery and/or radiation therapy for symptomatic spinal metastases were enrolled in the AO Spine Metastatic Tumor Research and Outcomes Network, a prospective international multicenter research registry, between September 2017 and August 2022. Using the PG-SGA, nutritional status was classified into 3 categories: A, well nourished; B, moderately malnourished; and C, severely malnourished. RESULTS: A total of 589 patients met the inclusion criteria; 362 were classified as well nourished (61%), 159 were moderately malnourished (27%), and 68 were severely malnourished (12%). The median survival was 491 days, 328 days, and 117 days for well-nourished, moderately malnourished, and severely malnourished patients, respectively. In the multivariate analyses, severe malnourishment (HR 2.5 95% CI 1.4-4.3, P < .01) and an ECOG performance status of 3 or 4 (HR 2.7 95% CI 1.2-6.0) remained associated with significantly worse survival. CONCLUSION: Malnutrition as measured by the PG-SGA demonstrated to be significantly and independently associated with postoperative survival. The PG-SGA is a simple and useful tool to identify spinal metastases patients at risk of early postoperative mortality, and inclusion in the preoperative evaluation of these patients should be considered.

Background: Pre-clinical animal studies have demonstrated improved cerebral blood flow and neurological survival with Automated Head Up Position (AHUP) cardiopulmonary resuscitation (CPR) as compared to flat conventional (C) CPR. AHUP CPR consists of 1) automated head and thorax elevation 2) active compression decompression CPR and 3) an impedance threshold device. Subsequently, observational propensity-matched studies of out-of-hospital cardiac arrest (OHCA) patients demonstrated a time-dependent association between survival with intact neurological function (SNF) and application of AHUP CPR. However, comparison of AHUP CPR outcomes with contemporaneous C-CPR controls is lacking. Hypothesis: Use of AHUP CPR for OHCA by first responder agencies will demonstrate a higher incidence of SNF compared to C-CPR outcomes from a national registry Methods: Data from the previous 5 years (2020-2024) from an AHUP-CPR Registry comprised of OHCA patients routinely treated by first responders with AHUP CPR were compared with data from the Cardiac Arrest Registry to Enhance Survival (CARES). Patient demographics, arrest characteristics, ROSC, SHD, and SNF were recorded. SNF was defined as a Cerebral Performance Category 1 or 2 at hospital discharge. A two-sample test of proportions was used for outcome comparisons. Results: Nine AHUP registry sites (MN, FL, TN, IL, OK, VA, AL, IA, MI) were included. Summary 5-year demographics (Table 1) and clinical outcomes (Table 2) are presented. For 2020-2024 AHUP sites, the average time (mm:ss, SD) from 9-1-1 call to start of CPR was 9:09 (4:37) and time to start of AHUP CPR was 12:46 (5:57). The AHUP registry had a higher 5-yr incidence of SNF versus the CARES registry (difference 2.8%, 95% CI 1.8-3.8, p < 0.00001). This difference was consistent year over year (Figure 1). Secondary outcomes of sustained return of spontaneous circulation and survival to hospital discharge in the AHUP registry were also significantly higher than CARES registry data (Table 2). Conclusions: Over a 5-year period, an unadjusted analysis of aggregate data from two OHCA patient registries demonstrated that the incidence of survival with intact neurological function was higher in patients treated with AHUP CPR as part of first responder care versus patients treated with more conventional CPR methods.

ABSTRACT Purpose Abnormal restrictions at myofascial interfaces are a key factor in chronic low back pain (CLBP) with myofascial pain syndrome (MPS), but no established imaging method exists for quantitative assessment. This pilot study evaluated the clinical feasibility of MR elastography (MRE)‐based slip interface imaging (SII) for visualizing myofascial mobility in CLBP‐MPS patients versus age−/sex‐/BMI‐matched healthy participants. A new SII biomarker, maximal normalized displacement discontinuity (), was introduced, and the previously developed normalized octahedral shear strain (NOSS) map was used for comparison. Preliminary assessments of vibration‐frequency effects, repeatability, and group differences in inter‐muscular mobility were conducted. Methods MRE was conducted at 30, 60, and 90 Hz to compare with NOSS for visualizing inter‐muscular slip interfaces at the quadratus lumborum‐erector spinae (QL‐ES) and erector spinae‐multifidus (ES‐M) muscle boundaries at L3‐L4. Repeatability of and NOSS was assessed at 30 Hz (identified as the best‐performing frequency) using within‐subject coefficients of variation and a linear mixed‐effects model from within‐ and between‐day scans. Clinical feasibility was then assessed via Wilcoxon rank‐sum tests in six CLBP‐MPS patients and matched controls. Results at 30 Hz exhibited superior delineation of slip interfaces compared to higher frequencies and NOSS. demonstrated significantly lower variation and better repeatability than NOSS. Healthy participants showed continuous, well‐defined slip interfaces, whereas CLBP‐MPS patients displayed disrupted interfaces with significant mobility reduction at L4 ES‐M. Conclusion SII with lower vibration frequency and map enhances visualization of lower back myofascial mobility and shows potential for assessing differences between healthy individuals and CLBP‐MPS patients.

Abstract With the goal of preventing more hip fractures, a next generation of the VirtuOst Biomechanical Computed Tomography (BCT) test was developed that integrates measurements from a clinical CT scan related to fall risk, impact force, and femoral strength, the three main determinants of hip fracture. Here, we introduce the test and validate it against BMD and FRAX. Our source population from a large healthcare system comprised of 341364 patients (≥65 yr) with an abdominal-pelvic CT during care. Using data from 3035 patients (1790 with hip fracture), we developed a “BCT Risk Score” (range: 0-100) having input risk factors of age, femoral strength, ratio of trabecular/cortical BMD, muscle area, intramuscular fat, FN volume, hip width, and posterior fat thickness. In a geographically distinct set of 2124 patients (1293 with hip fracture), we then compared the BCT Risk Score against a DXA-equivalent hip BMD T-score (lowest hip value, measured from the CT scan by VirtuOst) and FRAX hip fracture risk (with BMD but without parental fracture history) for predicting a first incident hip fracture within 5 yr. For the women, the c-statistic for predicting fracture was higher for BCT (0.89, 95% CI: 0.87-0.90) than for BMD (0.81, 0.79-0.84) or FRAX (0.85, 0.83-0.87). Using binary thresholds to identify high-risk patients, sensitivity for BCT (Risk Score ≥ 75) was higher than for BMD (T-score ≤ −2.5) and FRAX (hip risk ≥ 3.0%): 81.4% vs 47.8% vs 75.9%, respectively; positive predictive values confirmed comparable high-risk status (BCT 13.6% vs BMD 15.3% vs FRAX 12.7%). Similar trends were observed for the men, 2-yr outcomes, and identifying very-high-risk patients. We conclude that, compared to both BMD and FRAX, the integrative BCT test better predicted hip fracture and its high sensitivity should improve fracture prevention.

PURPOSE Public reporting of health care outcomes can have unintended effects such as inappropriate risk aversion in patient selection. METHODS The center-specific survival analysis annually assigns all hematopoietic cell transplantation (HCT) centers in the United States a +1, −1, or 0 score for observed outcomes that are above, below, or within a center-specific predicted range of outcome. For each index year (2012-2016), centers receiving a −1 score after 0 scores in the preceding 2 years were compared with contemporaneous centers with as-predicted outcomes (0 score). Changes in the patient population characteristics in the 3 years before versus the 3 years after the index years were compared between the newly below-expected centers (NBCs) and the controls. A multivariate model adjusted for baseline patient population characteristics and center volume. RESULTS No differences in patient selection behavior were identified when comparing the NBCs with the controls across eight key patient population characteristics. For the statistically modeled (predicted) 1-year overall survival (OS), reflecting a holistic measure of centers' patient population risk, we observed no statistically significant difference in change (−0.23% [95% CI, −1.4 to 0.9]; P = .70). The observed OS increased in both NBCs and controls by 0.9% and 4.5%, respectively, without statistically significant difference in change. CONCLUSION Centers receiving a −1 score were not observed to deviate significantly from patient selection trends in the HCT field. These findings suggest that public reporting of HCT outcomes in the United States does not result in unintended bias against HCT for high-risk patients.

ABSTRACT Background Flap complications following maxillectomy, reconstruction, and adjuvant proton beam therapy (PBT) for primary maxillary and sinonasal malignancies are not well described. Methods This retrospective cohort study included consecutive patients treated between 2016 and 2023 from a single‐institutional database. Results Thirteen patients were identified with a median follow‐up of 26 months. No immediate post‐operative complications occurred, with a median time between surgery and PBT of 61 days. Nine patients (69.2%) had high‐risk postoperative pathology and required 66+ Gy(RBE), including five (38.5%) with gross disease receiving 70 Gy(RBE). Flap necrosis and fistulization occurred in three patients (23.1%) following PBT (median time from PBT to complication, 112 days). Higher flap mean and minimum dose, flap volume receiving at least 66 Gy[RBE], and minimum dose to 50% flap volume were associated with complications. Conclusions Careful patient selection and planning strategies should be considered to mitigate flap complication risk following adjuvant PBT for high‐risk post‐operative pathology.