Citations

Purpose To evaluate retear rates, clinical outcomes, and complications of a consecutive series of full‐thickness rotator cuff repair cases augmented with an autograft biceps patch. Methods A retrospective review was performed of patients undergoing rotator cuff repair with autograft biceps patch augmentation. Patients underwent either magnetic resonance imaging or ultrasound to evaluate rotator cuff repair integrity at a minimum of 6 months postoperatively. Patient‐reported outcomes including the American Shoulder and Elbow Surgeons Score and Single Assessment Numeric Evaluation score were also collected and evaluated for clinical significance at a minimum of 12 months postoperatively. Analysis of retear rates was performed by comparing observed retear rates to expected retear rates using the modified Rotator Cuff Healing Index score. Results The final cohort included 25 rotator cuff repair cases. Postoperative imaging was obtained by magnetic resonance imaging in 22 patients at a mean of 9 months postoperatively (range, 6.0‐15.3 months) and ultrasound in 3 patients at a mean of 30.4 months (range, 28.8‐32.2 months). The expected retear rate using the modified Rotator Cuff Healing Index score was 21.5% for the entire cohort. There was 1 retear, resulting in an actual retear rate of 4% at an average of 23.5‐month follow‐up ( P = .0196). The average Single Assessment Numeric Evaluation score was 93 (standard deviation 9), and the average American Shoulder and Elbow Surgeons Score was 96 (standard deviation 6.3) at an average of 23.5‐month follow‐up (range 14‐32). Patient acceptable symptomatic state was achieved by 96% of the cohort for the American Shoulder and Elbow Surgeons Score and 88% of the cohort for the Single Assessment Numeric Evaluation score. There were no cases of reoperation or complications. Conclusions In this consecutive series, the biceps autograft “smash” patch for rotator cuff augmentation resulted in a low rate of retears, favorable patient‐reported outcomes, and no complications. This augmentation option has the potential to be safe and effective for improving rotator cuff repair healing rates. Level of Evidence Level IV, retrospective case series.

Primary central nervous system choriocarcinoma is a non-germinomatous germ cell tumor with a highly malignant character, comprising up to 5% of all central nervous system germ cell tumors. Locations affected can include suprasellar or pineal locations most commonly, with others including the basal ganglia and lateral ventricles. Guidelines do not specify an optimal radiation regimen but recommend proceeding with maximally safe resection if feasible and then chemotherapy before radiotherapy. Radiation is often comprised of craniospinal irradiation with subsequent tumor bed boost. We present a case of an adult male with a primary central nervous system choriocarcinoma who underwent reversed sequence radiation therapy with photon tumor bed boost before proton craniospinal irradiation due to recurrent intracranial hemorrhages with long-term control of cancer and no subsequent hemorrhages. This case highlights the excellent outcome and feasibility of reversed sequence radiotherapy on choriocarcinoma in hemorrhage and tumor control.

Abstract Aims Heart failure (HF), a major global health challenge, affects millions worldwide and poses substantial healthcare and economic burdens. It is estimated that a large proportion of those with early systolic dysfunction remain asymptomatic at a stage when guideline-directed medical therapies have been shown to prevent disease progression. To develop an artificial intelligence (AI) model capable of predicting abnormal left ventricular ejection fraction (EF) directly from static, non-gated, non-contrast chest computed tomography (CT) scans as a form of opportunistic screening, Methods and results Using a multi-institutional dataset of 34 058 paired non- contrast CT images and echocardiogram reports from two academic centres, we trained our model of classification for predicting left-ventricle ejection fraction (LVEF) categories: abnormal EF (EF < 50%) vs. normal on 25 948 studies. We validated the model on 8110 paired chest CT and echocardiogram results from a separate institution. The model achieved an area under the receiver operating characteristic (AUROC) curve of 0.786 on the hold-out test set and 0.762 on external validation to detect an abnormal EF (<50%). Beyond strong predictive performance, the AI model surpassed expert radiologists in both accuracy and efficiency and provided interpretable visualizations highlighting imaging features linked to reduced LVEF. Conclusion In this study, we developed and validated an AI model capable of predicting abnormal LVEF directly from static, non-gated, non-contrast chest CT scans, a novel application for an imaging modality typically used for unrelated indications as a form of opportunistic screening. This technology holds significant promise for early detection of systolic HF, reducing the diagnostic gap, and improving outcomes in asymptomatic HF patients.