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平扫 CT 联合增强 CT 基础模型在预测孤立性实性肺结节良恶性中的研究。

The study of plain CT combined with contrast-enhanced CT-based models in predicting malignancy of solitary solid pulmonary nodules.

机构信息

Department of Medical Imaging, Shanxi Medical University, NO.56 Xinjian Road, Taiyuan, 030000, Shanxi, The People's Republic of China.

National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Department of Radiology, Tianjin Medical University Cancer Institute & Hospital, Tianjin, The People's Republic of China.

出版信息

Sci Rep. 2024 Sep 19;14(1):21871. doi: 10.1038/s41598-024-72592-9.

Abstract

To compare the diagnostic performance between plain CT-based model and plain plus contrast CT-based modelin the classification of malignancy for solitary solid pulmonary nodules. Between January 2012 and July 2021, 527 patients with pathologically confirmed solitary solid pulmonary nodules were collected at dual centers with similar CT examinations and scanning parameters. Before surgery, all patients underwent both plain and contrast-enhanced chest CT scans. Two clinical characteristics, fifteen plain CT characteristics, and four enhanced characteristics were used to develop two logistic regression models: model 1 (plain CT only) and model 2 (plain + contrast CT). The diagnostic performance of the two models was assessed separately in the development and external validation cohorts using the AUC. 392 patients from Center A were included in the training cohort (median size, 20.0 [IQR, 15.0-24.0] mm; mean age, 55.8 [SD, 9.9] years; male, 53.3%). 135 patients from Center B were included in the external validation cohort (median size, 20.0 [IQR, 16.0-24.0] mm; mean age, 56.4 [SD, 9.6] years; male, 51.9%). Preoperative patients with 201 malignant (adenocarcinoma, 148 [73.6%]; squamous cell carcinoma, 35 [17.4%]; large cell carcinoma,18 [9.0%]) and 326 benign (pulmonary hamartoma, 118 [36.2%]; sclerosing pneumocytoma, 35 [10.7%]; tuberculosis, 104 [31.9%]; inflammatory pseudonodule, 69 [21.2%]) solitary solid pulmonary nodules were gathered from two independent centers. The mean sensitivity, specificity, accuracy, PPV, NPV, and AUC (95%CI) of model 1 (Plain CT only) were 0.79, 0.78, 0.79, 0.67, 0.87, and 0.88 (95%CI, 0.82-0.93), the model 2 (Plain + Contrast CT) were 0.88, 0.91, 0.90, 0.84, 0.93, 0.93 (95%CI, 0.88-0.98) in external validation cohort, respectively. A logistic regression model based on plain and contrast-enhanced CT characteristics showed exceptional performance in the evaluation of malignancy for solitary solid lung nodules. Utilizing this contrast-enhanced CT model would provide recommendations concerning follow-up or surgical intervention for preoperative patients presenting with solid lung nodules.

摘要

比较单纯 CT 基础模型和单纯 CT 加对比增强 CT 基础模型在孤立性实性肺结节良恶性分类中的诊断性能。2012 年 1 月至 2021 年 7 月,在两个具有相似 CT 检查和扫描参数的中心共收集了 527 例经病理证实的孤立性实性肺结节患者。所有患者均在术前接受了平扫和增强胸部 CT 扫描。建立了两个基于两种临床特征、十五个平扫 CT 特征和四个增强特征的逻辑回归模型:模型 1(仅平扫 CT)和模型 2(平扫+对比增强 CT)。分别在开发和外部验证队列中使用 AUC 评估两个模型的诊断性能。来自中心 A 的 392 例患者被纳入训练队列(中位大小为 20.0 [IQR,15.0-24.0]mm;平均年龄为 55.8 [SD,9.9]岁;男性占 53.3%)。来自中心 B 的 135 例患者被纳入外部验证队列(中位大小为 20.0 [IQR,16.0-24.0]mm;平均年龄为 56.4 [SD,9.6]岁;男性占 51.9%)。术前患者有 201 例恶性病变(腺癌 148 例[73.6%];鳞状细胞癌 35 例[17.4%];大细胞癌 18 例[9.0%])和 326 例良性病变(肺错构瘤 118 例[36.2%];硬化性细支气管肺泡细胞瘤 35 例[10.7%];肺结核 104 例[31.9%];炎性假瘤 69 例[21.2%]),来自两个独立的中心。模型 1(单纯 CT )的平均敏感度、特异度、准确度、PPV、NPV 和 AUC(95%CI)分别为 0.79、0.78、0.79、0.67、0.87 和 0.88(95%CI,0.82-0.93),模型 2(单纯 CT + 对比增强 CT)分别为 0.88、0.91、0.90、0.84、0.93 和 0.93(95%CI,0.88-0.98)。在外部验证队列中,基于平扫和增强 CT 特征的逻辑回归模型在评估孤立性实性肺结节的恶性程度方面表现出色。对于术前表现为实性肺结节的患者,使用这种增强 CT 模型将有助于推荐后续随访或手术干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03b7/11412969/3df819948ecd/41598_2024_72592_Fig1_HTML.jpg

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