文献类型：期刊文献

英文题名：Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques

作者：Fu, Chen[1];Zhang, Bangxing[2];Guo, Tiankang[3,4,5];Li, Junliang[1,3,4,5]

第一作者：Fu, Chen

通信作者：Li, JL[1]

机构：[1]Gansu Univ Chinese Med, Sch Clin Med 1, Lanzhou, Gansu, Peoples R China;[2]Ningxia Med Univ, Sch Clin Med, Yinchuan, Ningxia, Peoples R China;[3]Gansu Prov Hosp, Dept Gen Surg, 204 Donggang West Rd, Lanzhou 730030, Gansu, Peoples R China;[4]Gansu Prov Hosp, Key Lab Mol Diagnost & Precis Med Surg Oncol Gansu, Lanzhou, Gansu, Peoples R China;[5]Gansu Prov Hosp, NHC Key Lab Diag & Therapy Gastrointestinal Tumor, Lanzhou, Gansu, Peoples R China

第一机构：甘肃中医药大学

通信机构：[1]corresponding author), Gansu Prov Hosp, Dept Gen Surg, 204 Donggang West Rd, Lanzhou 730030, Gansu, Peoples R China.

年份：2024

卷号：25

期号：1

起止页码：86

外文期刊名：KOREAN JOURNAL OF RADIOLOGY

收录：;Scopus(收录号：2-s2.0-85181788675);WOS:【SCI-EXPANDED(收录号:WOS:001222833600007)】；

基金：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 (2020KCYB-7), 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).

语种：英文

外文关键词：Peritoneal neoplasms; Diagnostic imaging; Molecular imaging; Optical imaging; Radiomics; Artificial intelligence; Deep learning; Machine learning

摘要：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.