Value of CT radiomics in the differential diagnosis of lung nodules

doi:10.3877/cma.j.issn.2095-8773.2024.02.08

Abstract

Abstract:

In the post-COVID era, the application of chest CT has become increasingly widespread, leading to a higher detection rate of pulmonary nodules. Given the substantial variability in treatment and prognosis among different types of nodules, accurate identification and diagnosis are of paramount importance. Traditional clinical features and radiographic assessments for nodule differentiation still bear a significant risk of error. However, the field of radiomics has emerged in the past decade, utilizing computer algorithms to seek high-throughput data from images to aid clinical decision-making, thus enhancing diagnostic efficacy and benefiting patients. This article presents an overview of CT radiomics and its value in the differential diagnosis of pulmonary nodules. It also discusses the advantages, challenges, and limitations of this approach and looks forward to the future directions in the development of radiomics.

Key words: Pulmonary nodule, Computer tomography, Radiomics, Diagnosis

Yunze Liu, Chengrun Li, Hong Ren, Juntang Guo, Yang Liu. Value of CT radiomics in the differential diagnosis of lung nodules[J]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2024, 11(02): 120-129.

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应用领域	文献	样本量	模型表现（AUC值）	发表年份
良恶性鉴别	Aerts等^[29]	42 290	0.944	2014
肿瘤分期	Xu等^[30]	163	0.790	2023
病理亚型	Chen等^[31]	229	0.864	2019
结节侵袭性	Zhao等^[32]	395	0.770	2019
基因分型	Wu等^[33]	18 232	0.813	2023
治疗效果及预后预测	Mattonen等^[34]	188	0.820	2016
作为补充提高其他模型效能	Kammer等^[35]	100	0.944	2021

应用领域	文献	样本量	模型表现（AUC值）	发表年份
良恶性鉴别	Aerts等^[29]	42 290	0.944	2014
肿瘤分期	Xu等^[30]	163	0.790	2023
病理亚型	Chen等^[31]	229	0.864	2019
结节侵袭性	Zhao等^[32]	395	0.770	2019
基因分型	Wu等^[33]	18 232	0.813	2023
治疗效果及预后预测	Mattonen等^[34]	188	0.820	2016
作为补充提高其他模型效能	Kammer等^[35]	100	0.944	2021

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