라디오믹스 기반 직장암 수술 위험도 예측을 위한 MRI 반자동 선택 바이오마커 검증 연구A Study on MRI Semi-Automatically Selected Biomarkers for Predicting Risk of Rectal Cancer Surgery Based on Radiomics
- Other Titles
- A Study on MRI Semi-Automatically Selected Biomarkers for Predicting Risk of Rectal Cancer Surgery Based on Radiomics
- Authors
- 백영서; 김영재; 전영배; 황태식; 백정흠; 김광기
- Issue Date
- Feb-2023
- Publisher
- 대한의용생체공학회
- Keywords
- Rectal cancer; Radiomics; Biomarker; Quantitative
- Citation
- 의공학회지, v.44, no.1, pp.11 - 18
- Journal Title
- 의공학회지
- Volume
- 44
- Number
- 1
- Start Page
- 11
- End Page
- 18
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/86932
- DOI
- 10.9718/JBER.2023.44.1.11
- ISSN
- 1229-0807
- Abstract
- 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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Collections - 의과대학 > 의학과 > 1. Journal Articles
- 보건과학대학 > 의용생체공학과 > 1. Journal Articles
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