MRI‐Based Artificial Intelligence in Rectal Cancer. Issue 1 (22nd August 2022)

• Record Type: Journal Article
• Authors: Wong, Chinting; Fu, Yu; Li, Mingyang; Mu, Shengnan; Chu, Xiaotong; Fu, Jiahui; Lin, Chenghe; Zhang, Huimao
• Is Part Of: Journal of magnetic resonance imaging. Volume 57:Issue 1(2023)
• Page Start: 45
• Page End: 56
• Publication Date: 2022-08-22
• Subjects: MRI -- artificial intelligence -- rectal cancer; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.28381
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Rectal cancer (RC) accounts for approximately one‐third of colorectal cancer (CRC), with death rates increasing in patients younger than 50 years old. Magnetic resonance imaging (MRI) is routinely performed for tumor evaluation. However, the semantic features from images alone remain insufficient to guide treatment decisions. Functional MRIs are useful for revealing microstructural and functional abnormalities and nevertheless have low or modest repeatability and reproducibility. Therefore, during the preoperative evaluation and follow‐up treatment of patients with RC, novel noninvasive imaging markers are needed to describe tumor characteristics to guide treatment strategies and achieve individualized diagnosis and treatment. In recent years, the development of artificial intelligence (AI) has created new tools for RC evaluation based on MRI. In this review, we summarize the research progress of AI in the evaluation of staging, prediction of high‐risk factors, genotyping, response to therapy, recurrence, metastasis, prognosis, and segmentation with RC. We further discuss the challenges of clinical application, including improvement in imaging, model performance, and the biological meaning of features, which may also be major development directions in the future. Evidence Level: 5 Technical Efficacy: Stage 2