Published 2025-01-01
“…Wenjun Liu,1 Jin Wang,2 Yiting Lei,1 Peng Liu,3 Zhenghan Han,1 Shichu Wang,1 Bo Liu1 1Department of Orthopedics, First Affiliated Hospital, Chongqing Medical University, Chongqing, People’s Republic of China; 2College of
Medical Informatics, Chongqing Medical University, Chongqing, People’s Republic of China; 3Department of Orthopedics, Daping Hospital, Army Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Bo Liu, Department of Orthopedics, First Affiliated Hospital, Chongqing Medical University, Chongqing, People’s Republic of China, Tel +8613996065698, Email boliu@hospital.cqmu.edu.cnBackground: Early differentiation between spinal tuberculosis (STB) and acute osteoporotic vertebral compression fracture (OVCF) is crucial for determining the appropriate clinical management and treatment pathway, thereby significantly impacting patient outcomes.Objective: To evaluate the efficacy of deep learning (DL) models using reconstructed sagittal CT images in the differentiation of early STB from acute OVCF, with the aim of enhancing diagnostic precision, reducing reliance on MRI and biopsies, and minimizing the risks of misdiagnosis.Methods: Data were collected from 373 patients, with 302 patients recruited from a university-affiliated hospital serving as the training and internal validation sets, and an additional 71 patients from another university-affiliated hospital serving as the external validation set. …”
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