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Abstract #2824

Improve Model Performance Rectal Cancer Staging by Radiomics Analysis of Diffusion-weighted Imaging and T2-weighted Imaging

Yen-Chun Chen1, Chi-Feng Hsieh2, Shao-Chieh Lin2, Chia-Ching Chang2, Chun-Jung Juan2, Yi-Jui Liu3, and Hsu-Hsia Peng1
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, 2Department of Radiology, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, 3Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan

Synopsis

Keywords: Cancer, Radiomics

Motivation: Accurate preoperative tumor staging is important for treatment decisions of rectal cancer (RC). Radiomics can be helpful in identifying tumor stages.

Goal(s): To improve model performance of tumor staging (≥T3 or <T3) in RC patients by radiomics.

Approach: Five image contrasts, including diffusion-weighted, apparent diffusion coefficient, T2-weighted, and their combinations, were analyzed. The targeting regions were determined by five strategies: bounding box, manually determined tumor region of interest (ROI), and ROIs with dilation of 1, 3, and 5 pixels.

Results: The DWI_b800+T2WI and DWI+FS-T2WI with bounding box and CatBoost achieved an accurate AUC=0.889 for identifying RC patients ≥T3.

Impact: Compared to extracting features from DWI or T2WI solely, radiomics analysis of combinations of DWI_b800+T2WI or DWI_b800+FS-T2WI exhibited better AUC and TNR in identifying rectal cancer patients ≥T3. A bounding-box was the best strategy for determining the analyzed region.

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Keywords