Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
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Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques

  • Chen Fu (The First School of Clinical Medical, Gansu University of Chinese Medicine) ;
  • Bangxing Zhang (School of Clinical Medicine, Ningxia Medical University) ;
  • Tiankang Guo (Department of General Surgery, Gansu Provincial Hospital) ;
  • Junliang Li (The First School of Clinical Medical, Gansu University of Chinese Medicine)
  • Received : 2023.06.22
  • Accepted : 2023.10.08
  • Published : 2024.01.01
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Abstract

Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.

Keywords

Acknowledgement

This research was supported by the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320005, NHCDP2022028), Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province (2020GSZDSYS02), the 14th Five Year Plan of Education Science of Gansu Province (GS (2021) GHB1859), Scientific Research and Innovation Fund of Gansu University of Chinese Medicine (2020KCYB7), Longyuan Youth Innovation and Entrepreneurship Talent Project (111266548053), Teaching Research and Reform comprehensive project of Gansu University of Traditional Chinese Medicine (ZHXM-202207), and Research Fund project of Gansu Provincial Hospital (22GSSYC-1, 22GSSYB-14).

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