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Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques

C. D. Fu, Bangxing Zhang, T. X. Guo, Junliang Li

2024Korean Journal of Radiology27 citationsDOIOpen Access PDF

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.

Topics & Concepts

MedicineMagnetic resonance imagingMolecular imagingPositron emission tomographyRadiologyRadiomicsMedical imagingMetastasisMedical physicsCancerBiologyInternal medicineIn vivoBiotechnologyIntraperitoneal and Appendiceal MalignanciesRenal cell carcinoma treatmentHepatocellular Carcinoma Treatment and Prognosis
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