Development and validation of an MRI spatiotemporal interaction model for early noninvasive prediction of neoadjuvant chemotherapy response in breast cancer: a multicentre study.

Journal: EClinicalMedicine
Published Date:

Abstract

BACKGROUND: The accurate and early evaluation of response to neoadjuvant chemotherapy (NAC) in breast cancer is crucial for optimizing treatment strategies and minimizing unnecessary interventions. While deep learning (DL)-based approaches have shown promise in medical imaging analysis, existing models often fail to comprehensively integrate spatial and temporal tumor dynamics. This study aims to develop and validate a spatiotemporal interaction (STI) model based on longitudinal MRI data to predict pathological complete response (pCR) to NAC in breast cancer patients.

Authors

  • Wenjie Tang
    Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, Guangdong, 510180, China.
  • Chen Jin
    College of Computer Science, Nankai University, Tianjin 300350, China.
  • Qingcong Kong
    Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Chunling Liu
    Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
  • Siyi Chen
    Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, Guangdong, 510180, China.
  • Shishen Ding
    Department of Radiology, Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, 545006, China.
  • Bihua Liu
    Department of Radiology, The Tenth Affiliated Hospital of Southern Medical University (Gongguan People's Hospital), China.
  • Zaihui Feng
    Department of Radiology, The Third People's Hospital of Honghe Hani and Yi Autonomous Prefecture, Honghe, 661000, China.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Yi Dai
    Department of Computer Science, University of California, Irvine, CA 92617, USA.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yongxin Chen
    Department of Radiology, Guangzhou First People's Hospital, No. 1 Panfu Rd, Guangzhou, 510180 China.
  • Xiaorui Han
    Department of Radiology, School of Medicine, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China.
  • Shuang Liu
    Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China.
  • Dandan Chen
    College of Electronic Engineering, Guangxi Normal University, Guilin, Guangxi, China. Electronic address: chenddan0912@163.com.
  • Zijin Weng
    Department of Pathology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Weifeng Liu
    Guangxi Key Laboratory of Pharmaceutical Precision Detection and Screening, Key Laboratory of Micro-Nanoscale Bioanalysis and Drug Screening of Guangxi Education Department, Pharmaceutical College, State Key Laboratory of Targeting Oncology, Guangxi Medical University, Nanning 530021, China.
  • Xinhua Wei
    Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou 510180, China.
  • Xinqing Jiang
    Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou 510180, China.
  • Qianwei Zhou
    College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, PR China; Key Laboratory of Visual Media Intelligent Processing Technology of Zhejiang Province, Hangzhou 310023, PR China.
  • Ning Mao
    Department of Radiology, Peking University People's Hospital, 11 Xizhimen Nandajie, Xicheng District, Beijing, 100044, People's Republic of China.
  • Yuan Guo
    Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

Keywords

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