Erschienen in:
02.07.2018 | Chest
Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule
verfasst von:
Li Fan, MengJie Fang, ZhaoBin Li, WenTing Tu, ShengPing Wang, WuFei Chen, Jie Tian, Di Dong, ShiYuan Liu
Erschienen in:
European Radiology
|
Ausgabe 2/2019
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Abstract
Objectives
To identify the radiomics signature allowing preoperative discrimination of lung invasive adenocarcinomas from non-invasive lesions manifesting as ground-glass nodules.
Methods
This retrospective primary cohort study included 160 pathologically confirmed lung adenocarcinomas. Radiomics features were extracted from preoperative non-contrast CT images to build a radiomics signature. The predictive performance and calibration of the radiomics signature were evaluated using intra-cross (n=76), external non-contrast-enhanced CT (n=75) and contrast-enhanced CT (n=84) validation cohorts. The performance of radiomics signature and CT morphological and quantitative indices were compared.
Results
355 three-dimensional radiomics features were extracted, and two features were identified as the best discriminators to build a radiomics signature. The radiomics signature showed a good ability to discriminate between invasive adenocarcinomas and non-invasive lesions with an accuracy of 86.3%, 90.8%, 84.0% and 88.1%, respectively, in the primary and validation cohorts. It remained an independent predictor after adjusting for traditional preoperative factors (odds ratio 1.87, p < 0.001) and demonstrated good calibration in all cohorts. It was a better independent predictor than CT morphology or mean CT value.
Conclusions
The radiomics signature showed good predictive performance in discriminating between invasive adenocarcinomas and non-invasive lesions. Being a non-invasive biomarker, it could assist in determining therapeutic strategies for lung adenocarcinoma.
Key Points
• The radiomics signature was a non-invasive biomarker of lung invasive adenocarcinoma.
• The radiomics signature outweighed CT morphological and quantitative indices.
• A three-centre study showed that radiomics signature had good predictive performance.