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KMID : 1137820230440010011
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의공학회지
2023 Volume.44 No. 1 p.11 ~ p.18
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A Study on MRI Semi-Automatically Selected Biomarkers for Predicting Risk of Rectal Cancer Surgery Based on Radiomics
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Baik Young-Seo
Yoon Ji-Seon
Jeon Young-Bae
Hwang Tae-Sik
Baek Jeong-Heum
Kim Kwang-Gi
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Abstract
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Currently, studies to predict the risk of rectal cancer surgery select MRI image slices based on the clinical experience of surgeons. The purpose of this study is to semi-automatically select and classify 2D MRI image slides to predict the risk of rectal cancer surgery using biomarkers. The data used were retrospectively collected MRI imag- ing data of 50 patients who underwent laparoscopic surgery for rectal cancer at Gachon University Gil Medical Center.
Expert-selected MRI image slices and non-selected slices were screened and radiomics was used to extract a total of 102 features. A total of 16 approaches were used, combining 4 classifiers and 4 feature selection methods. The combination of Random Forest and Ridge performed with a sensitivity of 0.83, a specificity of 0.88, an accuracy of 0.85, and an AUC of 0.89±0.09. Differences between expert-selected MRI image slices and non-selected slices were analyzed by extracting the top five significant features. Selected quantitative features help expedite decision making and improve efficiency in studies to predict risk of rectal cancer surgery.
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KEYWORD
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Rectal cancer, Radiomics, Biomarker, Quantitative
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