Bibliographic Details
| Title: |
DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer |
| Authors: |
Jinrong Qu, Ling Ma, Yanan Lu, Zhaoqi Wang, Jia Guo, Hongkai Zhang, Xu Yan, Hui Liu, Ihab R. Kamel, Jianjun Qin, Hailiang Li |
| Source: |
Discover Oncology, Vol 13, Iss 1, Pp 1-13 (2022) |
| Publisher Information: |
Springer, 2022. |
| Publication Year: |
2022 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
Esophageal cancer, Magnetic Resonance Imaging, Adjuvant chemotherapy, Nomograms, Precision medicine, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Abstract Objectives To assess volumetric DCE-MRI radiomics nomogram in predicting response to neoadjuvant chemotherapy (nCT) in EC patients. Methods This retrospective analysis of a prospective study enrolled EC patients with stage cT1N + M0 or cT2-4aN0-3M0 who received DCE-MRI within 7 days before chemotherapy, followed by surgery. Response assessment was graded from 1 to 5 according to the tumor regression grade (TRG). Patients were stratified into responders (TRG1 + 2) and non-responders (TRG3 + 4 + 5). 72 radiomics features and vascular permeability parameters were extracted from DCE-MRI. The discriminating performance was assessed with ROC. Decision curve analysis (DCA) was used for comparing three different models. Results This cohort included 82 patients, and 72 tumor radiomics features and vascular permeability parameters acquired from DCE-MRI. mRMR and LASSO were performed to choose the optimized subset of radiomics features, and 3 features were selected to create the radiomics signature that were significantly associated with response (P |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2730-6011 |
| Relation: |
https://doaj.org/toc/2730-6011 |
| DOI: |
10.1007/s12672-022-00464-7 |
| Access URL: |
https://doaj.org/article/97dc267bbcdb4b1cbd5b1e60f8feb69d |
| Accession Number: |
edsdoj.97dc267bbcdb4b1cbd5b1e60f8feb69d |
| Database: |
Directory of Open Access Journals |
