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作者

Xinxin Yu Shuai Zhang Jingxu Xu Yong Huang Hao Luo Chencui Huang Pei Nie Yan Deng Ning Mao Ran Zhang Lin Gao Sha Li Bing Kang Ximing Wang

作者单位

Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing, China. ⁴ Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China. ⁵ Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, China. ⁶ Department of Radiology, Qilu Hospital, Shandong University, Jinan, China. ⁷ Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China. ⁸ Huiying Medical Technology Co., Ltd., Beijing, China. ⁹ Department of Radiology, Shandong Provincial Hospital, Shandong First Medical University, Shandong University, No. 324, Jingwu Rd, Jinan, 250021, China. Affiliations ¹ Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, China. ² School of Medicine, Shandong First Medical University, Jinan, China. ³ Department of Research Collaboration, R

刊名

AJR. American journal of roentgenology

卷号

Vol.220 No.2

页码

224-234

ISSN

1546-3141

关键词

CT invasive mucinous adenocarcinoma pneumonia radiomics.

摘要

BACKGROUND. Pneumonia-type invasive mucinous adenocarcinoma and pneumonia show overlapping chest CT features as well as overlapping clinical characteristics. OBJECTIVE. The purpose of our study was to develop and validate a nomogram combining clinical and CT-based radiomics features to differentiate pneumonia-type IMA and pneumonia. METHODS. This retrospective study included 314 patients from six hospitals who underwent noncontrast chest CT showing consolidation and were diagnosed with pneumon...更多

BACKGROUND. Pneumonia-type invasive mucinous adenocarcinoma and pneumonia show overlapping chest CT features as well as overlapping clinical characteristics. OBJECTIVE. The purpose of our study was to develop and validate a nomogram combining clinical and CT-based radiomics features to differentiate pneumonia-type IMA and pneumonia. METHODS. This retrospective study included 314 patients from six hospitals who underwent noncontrast chest CT showing consolidation and were diagnosed with pneumonia-type IMA or pneumonia . Patients from three hospitals formed a training set and a validation set , and patients from the other three hospitals formed the external test set . A model for predicting pneumonia-type IMA was built using clinical characteristics that were significant independent predictors of this diagnosis. Radiomics features were extracted from CT images by placing ROIs on areas of consolidation, and a radiomics signature of pneumonia-type IMA was constructed. A nomogram for predicting pneumonia-type IMA was constructed that combined features in the clinical model and the radiomics signature. Two cardiothoracic radiologists independently reviewed CT images in the external test set to diagnose pneumonia-type IMA. Diagnostic performance was compared among models and radiologists. Decision curve analysis was performed. RESULTS. The clinical model included fever and family history of lung cancer. The radiomics signature included 15 radiomics features. DCA showed higher overall net benefit from the nomogram than from the clinical model. In the external test set, AUC was higher for the nomogram than for the clinical model , radiologist 1 , and radiologist 2 . In the external test set, the nomogram had sensitivity of 46.9%, specificity of 94.6%, and accuracy of 72.5%. CONCLUSION. The nomogram combining clinical variables and CT-based radiomics features outperformed the clinical model and two cardiothoracic radiologists in differentiating pneumonia-type IMA from pneumonia. CLINICAL IMPACT. The findings support potential clinical use of the nomogram for diagnosing pneumonia-type IMA in patients with consolidation on chest CT.收起

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