Image-based artificial intelligence for the prediction of pathological complete response to neoadjuvant chemoradiotherapy in patients with rectal cancer: a systematic review and meta-analysis.

Journal: La Radiologia medica
PMID: 38512622

Abstract

OBJECTIVE: Artificial intelligence (AI) holds enormous potential for noninvasively identifying patients with rectal cancer who could achieve pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT). We aimed to conduct a meta-analysis to summarize the diagnostic performance of image-based AI models for predicting pCR to nCRT in patients with rectal cancer.

Authors

  • Hui Shen
    College of Mechatronics and Automation, National University of Defense Technology, Changsha, China.
  • Zhe Jin
    Zhejiang University, College of Computer Science and Technology, Hangzhou, China.
  • Qiuying Chen
    Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
  • Lu Zhang
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Jingjing You
    Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Shuixing Zhang
    Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, PR China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, Guangdong, PR China. Electronic address: shui7515@126.com.
  • Bin Zhang
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

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