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Validation of a Deep Learning Tool for Detection of Incidental Vertebral Compression Fractures.
J Comput Assist Tomogr
January 2025
Department of Radiological Sciences.
Objective: This study evaluated the performance of a deep learning-based vertebral compression fracture (VCF) detection tool in patients with incidental VCF. The purpose of this study was to validate this tool across multiple sites and multiple vendors.
Methods: This was a retrospective, multicenter, multinational blinded study using anonymized chest and abdominal CT scans performed for indications other than VCF in patients ≥50 years old.
The use of large language models in detecting Chinese ultrasound report errors.
NPJ Digit Med
January 2025
Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China.
This retrospective study evaluated the efficacy of large language models (LLMs) in improving the accuracy of Chinese ultrasound reports. Data from three hospitals (January-April 2024) including 400 reports with 243 errors across six categories were analyzed. Three GPT versions and Claude 3.
View Article and Find Full Text PDFExperience with the implementation of central venous catheters by medical oncologists in a non-surgical setting.
Sci Rep
January 2025
Medical Oncology Department, Central University Hospital of Asturias, Oviedo, Spain.
Totally implantable central venous catheters (CVCs) are widely used in the management of patients with malignant diseases. Conventionally, port implantations were carried out by general surgeons and vascular radiologists. In recent years, the medical staff of the Medical Oncology department at the Central University Hospital of Asturias (HUCA) has developed a simplified methodology for the routine implantation of these devices.
View Article and Find Full Text PDFImaging-based prediction of early recurrence and neoadjuvant therapy outcomes for resectable beyond Milan HCC.
Eur J Radiol
January 2025
Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China. Electronic address:
Purpose: To develop and validate an MRI-based model for predicting postoperative early (≤2 years) recurrence-free survival (RFS) in patients receiving upfront surgical resection (SR) for beyond Milan hepatocellular carcinoma (HCC) and to assess the model's performance in separate patients receiving neoadjuvant therapy for similar-stage tumors.
Method: This single-center retrospective study included consecutive patients with resectable BCLC A/B beyond Milan HCC undergoing upfront SR or neoadjuvant therapy. All images were independently evaluated by three blinded radiologists.
Combining Multifrequency Magnetic Resonance Elastography With Automatic Segmentation to Assess Renal Function in Patients With Chronic Kidney Disease.
J Magn Reson Imaging
January 2025
Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, China.
Background: Multifrequency MR elastography (mMRE) enables noninvasive quantification of renal stiffness in patients with chronic kidney disease (CKD). Manual segmentation of the kidneys on mMRE is time-consuming and prone to increased interobserver variability.
Purpose: To evaluate the performance of mMRE combined with automatic segmentation in assessing CKD severity.
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