Journal
EUROPEAN RADIOLOGY
Volume 29, Issue 2, Pages 889-897Publisher
SPRINGER
DOI: 10.1007/s00330-018-5530-z
Keywords
Lung; Adenocarcinoma; Tomography; x-ray computed; Computational biology; Solitary pulmonary nodule
Funding
- National Natural Science Foundation of China [81370035, 81230030, 81771924]
- National Key R&D Program of China [2016YFE0103000, 2017YFC1308703, 2017YFA0205200, 2017YFC1309100, 2017YFC1308700]
- Shanghai Pujiang Talent Program [15PJD002]
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ObjectivesTo identify the radiomics signature allowing preoperative discrimination of lung invasive adenocarcinomas from non-invasive lesions manifesting as ground-glass nodules.MethodsThis 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.Results355 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.ConclusionsThe 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 center dot The radiomics signature was a non-invasive biomarker of lung invasive adenocarcinoma.center dot The radiomics signature outweighed CT morphological and quantitative indices.center dot A three-centre study showed that radiomics signature had good predictive performance.
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