Zhuang Xiangrong, Wang Jinan, Kang Jianghe, Lin Ziying
Department of Radiology, Zhongshan Hospital, School of Medicine, Xiamen University, No.201-209 Hubinnan Road, Siming District, Xiamen, 361004, Fujian Province, China.
J Imaging Inform Med. 2024 Dec 9. doi: 10.1007/s10278-024-01359-5.
The purpose of this study is to evaluate the performance of radiomic models in acute thoracolumbar vertebral compression fractures (VCFs) and their impact on radiologists. In this monocentre retrospective study, eligible for inclusion were adults who underwent emergent thoracic/lumbar CT between May 2022 and November 2023 in our hospital diagnosed with thoracolumbar VCFs. The lesions were randomly divided at a ratio of 7:3 into a training set and test set. For external validation, consecutive patients who underwent emergent thoracic/lumbar CT between January 2022 and April 2022 were included. MRI and previous imaging were used as reference standard. The vertebral body area was manually segmented. Logistic regression was used to construct a CT radiomic model and a combined model, including Relief-selected radiomic features and clinical information. The radiologists' diagnosis with and without the models was recorded. The performance was assessed using receiver operating characteristic curves (ROC), calibration curves (CC) and decision curve analysis (DCA). Of 235 VCFs in 147 patients (median age, 73 years, 66 male) included, the diagnosis of acute VCFs was confirmed in 126. The area under the ROC of the CT radiomics model and the combined model in the external validation set were 0.883 (95% CI 0.777, 0.998) and 0.875 (95% CI 0.768, 0.982), respectively. CC and DCA showed good clinical application of the models. The less experienced reader achieved a higher accuracy with the help of the models (p = 0.027). The radiomic models showed high accuracy for diagnosing acute VCFs and helped radiologists improve the accuracy of diagnosis.
本研究旨在评估放射组学模型在急性胸腰椎椎体压缩骨折（VCF）中的表现及其对放射科医生的影响。在这项单中心回顾性研究中，纳入标准为2022年5月至2023年11月在我院接受急诊胸/腰椎CT检查且被诊断为胸腰椎VCF的成年人。将病变以7:3的比例随机分为训练集和测试集。对于外部验证，纳入2022年1月至2022年4月期间接受急诊胸/腰椎CT检查的连续患者。以MRI和既往影像学检查作为参考标准。手动分割椎体区域。采用逻辑回归构建CT放射组学模型和联合模型，包括通过 Relief 法选择的放射组学特征和临床信息。记录放射科医生在有模型和无模型情况下的诊断情况。使用受试者操作特征曲线（ROC）、校准曲线（CC）和决策曲线分析（DCA）评估模型性能。在纳入的147例患者（中位年龄73岁，男性66例）的235处VCF中，确诊急性VCF的有126处。外部验证集中CT放射组学模型和联合模型的ROC曲线下面积分别为0.883（95%CI 0.777, 0.998）和0.875（95%CI 0.768, 0.982）。CC和DCA显示模型具有良好的临床应用价值。经验较少的阅片者在模型的帮助下准确性更高（p = 0.027）。放射组学模型在诊断急性VCF方面显示出较高的准确性，并有助于放射科医生提高诊断准确性。
