| Title | Combination of Peri- and Intratumoral Radiomic Features on Baseline CT Scans Predicts Response to Chemotherapy in Lung Adenocarcinoma. |
| Publication Type | Journal Article |
| Year of Publication | 2019 |
| Authors | Khorrami, MH, Khunger M, Zagouras A, Patil P, Thawani R, Bera K, Rajiah P, Fu P, Velcheti V, Madabhushi A |
| Journal | Radiology. Artificial intelligence |
| Volume | 1 |
| Issue | 2 |
| Pagination | e180012 |
| Date Published | 2019 Mar 20 |
| ISSN | 2638-6100 |
| Abstract | To identify the role of radiomics texture features both within and outside the nodule in predicting time to progression (TTP) and overall survival (OS) as well as response to chemotherapy in patients with non-small cell lung cancer (NSCLC). |
| DOI | 10.1148/ryai.2019180012 |
| PDF Link | |
| Alternate Journal | Radiol Artif Intell |
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