Department of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Department of Radiology, Yunnan Cancer Hospital/Center, Third Affiliated Hospital of Kunming Medical University, Kunming, China.
BMC Pulm Med. 2023 Nov 21;23(1):454. doi: 10.1186/s12890-023-02727-7.
To establish a preoperative model for the differential diagnosis of benign and malignant pulmonary nodules (PNs), and to evaluate the related factors of overdiagnosis of benign PNs at the time of imaging assessments.
In this retrospective study, 357 patients (median age, 52 years; interquartile range, 46-59 years) with 407 PNs were included, who underwent surgical histopathologic evaluation between January 2020 and December 2020. Patients were divided into a training set (n = 285) and a validation set (n = 122) to develop a preoperative model to identify benign PNs. CT scan features were reviewed by two chest radiologists, and imaging findings were categorized. The overdiagnosis rate of benign PNs was calculated, and bivariate and multivariable logistic regression analyses were used to evaluate factors associated with benign PNs that were over-diagnosed as malignant PNs.
The preoperative model identified features such as the absence of part-solid and non-solid nodules, absence of spiculation, absence of vascular convergence, larger lesion size, and CYFRA21-1 positivity as features for identifying benign PNs on imaging, with a high area under the receiver operating characteristic curve of 0.88 in the validation set. The overdiagnosis rate of benign PNs was found to be 50%. Independent risk factors for overdiagnosis included diagnosis as non-solid nodules, pleural retraction, vascular convergence, and larger lesion size at imaging.
We developed a preoperative model for identifying benign and malignant PNs and evaluating factors that led to the overdiagnosis of benign PNs. This preoperative model and result may help clinicians and imaging physicians reduce unnecessary surgery.
建立术前模型以鉴别良、恶性肺结节(PN),并评估影像学评估时良性 PN 过度诊断的相关因素。
本回顾性研究纳入了 2020 年 1 月至 2020 年 12 月间进行手术病理评估的 357 名患者(中位年龄为 52 岁,四分位距为 46-59 岁),共 407 个 PN。患者分为训练集(n=285)和验证集(n=122),以建立术前模型以识别良性 PN。由两名胸部放射科医生对 CT 扫描特征进行回顾,对影像学表现进行分类。计算良性 PN 的过度诊断率,并进行二变量和多变量逻辑回归分析,以评估与将良性 PN 过度诊断为恶性 PN 相关的因素。
术前模型确定了一些特征,例如不存在部分实性和非实性结节、无分叶征、无血管聚集、更大的病变大小和细胞角蛋白 19 片段 21-1(CYFRA21-1)阳性,这些特征可用于在影像学上识别良性 PN,在验证集中的受试者工作特征曲线下面积(AUC)为 0.88。良性 PN 的过度诊断率为 50%。过度诊断的独立危险因素包括影像学上诊断为非实性结节、胸膜回缩、血管聚集和更大的病变大小。
我们建立了一种术前模型以识别良、恶性 PN,并评估导致良性 PN 过度诊断的因素。该术前模型和结果可能有助于临床医生和影像医师减少不必要的手术。