A pilot study of MRI radiomics for high-risk prostate cancer stratification in 1.5 T MR-guided radiotherapy
Yihang Zhou
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorCorresponding Author
Jing Yuan
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Correspondence
Jing Yuan, Research Department, Hong Kong Sanatorium & Hospital, 8/F, Li Shu Fan Block, Hong Kong Sanatorium & Hospital, 2 Village Road, Happy Valley, Hong Kong, Hong Kong SAR, China.
Email: [email protected]
Search for more papers by this authorCindy Xue
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorDarren M. C. Poon
Comprehensive Oncology Center, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorBin Yang
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorSiu Ki Yu
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorKin Yin Cheung
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorYihang Zhou
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorCorresponding Author
Jing Yuan
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Correspondence
Jing Yuan, Research Department, Hong Kong Sanatorium & Hospital, 8/F, Li Shu Fan Block, Hong Kong Sanatorium & Hospital, 2 Village Road, Happy Valley, Hong Kong, Hong Kong SAR, China.
Email: [email protected]
Search for more papers by this authorCindy Xue
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorDarren M. C. Poon
Comprehensive Oncology Center, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorBin Yang
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorSiu Ki Yu
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorKin Yin Cheung
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, People's Republic of China
Search for more papers by this authorClick here for author-reader discussions
Abstract
Purpose
To investigate the potential value of MRI radiomics obtained from a 1.5 T MRI-guided linear accelerator (MR-LINAC) for D'Amico high-risk prostate cancer (PC) classification in MR-guided radiotherapy (MRgRT).
Methods
One hundred seventy-six consecutive PC patients underwent 1.5 T MRgRT treatment were retrospectively enrolled. Each patient received one or two pretreatment T2-weighted MRI scans on a 1.5 T MR-LINAC. The endpoint was to differentiate high-risk from low/intermediate-risk PC based on D'Amico criteria using MRI-radiomics. Totally 1023 features were extracted from clinical target volume (CTV) and planning target volume (PTV). Intraclass correlation coefficient of scan–rescan repeatability, feature correlation, and recursive feature elimination were used for feature dimension reduction. Least absolute shrinkage and selection operator regression was employed for model construction. Receiver operating characteristic area under the curve (AUC) analysis was used for model performance assessment in both training and testing data.
Results
One hundred and eleven patients fulfilled all criteria were finally included: 76 for training and 35 for testing. The constructed MRI-radiomics models extracted from CTV and PTV achieved the AUC of 0.812 and 0.867 in the training data, without significant difference (P = 0.083). The model performances remained in the testing. The sensitivity, specificity, and accuracy were 85.71%, 64.29%, and 77.14% for the PTV-based model; and 71.43%, 71.43%, and 71.43% for the CTV-based model. The corresponding AUCs were 0.718 and 0.750 (P = 0.091) for CTV- and PTV-based models.
Conclusion
MRI-radiomics obtained from a 1.5 T MR-LINAC showed promising results in D'Amico high-risk PC stratification, potentially helpful for the future PC MRgRT. Prospective studies with larger sample sizes and external validation are warranted for further verification.
Supporting Information
| Filename | Description |
|---|---|
| mrm29564-sup-0001-Supinfo.docxWord 2007 document , 236.8 KB | Table S1. The selected features based on CTV and PTV using RFE. The features that were chosen from both PTV and CTV are highlighted in green. Figure S1. The ROC curves of the risk-stratification model based on PTV and CTV, using the radiomics features extracting from 111 patients without data splitting |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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