Academic Journal
A short-term follow-up CT based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer
| العنوان: | A short-term follow-up CT based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer |
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| المؤلفون: | Jing Gong, Xiao Bao, Ting Wang, Jiyu Liu, Weijun Peng, Jingyun Shi, Fengying Wu, Yajia Gu |
| المصدر: | OncoImmunology, Vol 11, Iss 1 (2022) |
| بيانات النشر: | Taylor & Francis Group, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Immunologic diseases. Allergy LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| مصطلحات موضوعية: | radiomics, immunotherapy, non-small-cell lung cancer, response prediction, ct image, Immunologic diseases. Allergy, RC581-607, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| الوصف: | To develop a short-term follow-up CT-based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer (NSCLC) and investigate the prognostic value of radiomics features in predicting progression-free survival (PFS) and overall survival (OS). We first retrospectively collected 224 advanced NSCLC patients from two centers, and divided them into a primary cohort and two validation cohorts respectively. Then, we processed CT scans with a series of image preprocessing techniques namely, tumor segmentation, image resampling, feature extraction and normalization. To select the optimal features, we applied the feature ranking with recursive feature elimination method. After resampling the training dataset with a synthetic minority oversampling technique, we applied the support vector machine classifier to build a machine-learning-based classification model to predict response to immunotherapy. Finally, we used Kaplan-Meier (KM) survival analysis method to evaluate prognostic value of rad-score generated by CT-radiomics model. In two validation cohorts, the delta-radiomics model significantly improved the area under receiver operating characteristic curve from 0.64 and 0.52 to 0.82 and 0.87, respectively (P |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2162-402X 2162402X |
| Relation: | https://doaj.org/toc/2162-402X |
| DOI: | 10.1080/2162402X.2022.2028962 |
| URL الوصول: | https://doaj.org/article/28c751abb92f41e38eafe867bfb63db0 |
| رقم الانضمام: | edsdoj.28c751abb92f41e38eafe867bfb63db0 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 2162402X |
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| DOI: | 10.1080/2162402X.2022.2028962 |