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Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT
Published on: January 22, 2018
Diagnostic value of [68Ga]Ga-FAPI-04 PET/CT in peritoneal carcinomatosis
Xiaolin Chen1, Mengjiao Wang1, Yan Zhao2
1Department of Nuclear Medicine, The Fourth Hospital of Hebei Medical University, Shijiazhuang City, China.
Purpose:
Peritoneal carcinomatosis (PC) carries a poor prognosis, making accurate imaging vital for patient selection and treatment optimization. This study aims to evaluate [68Ga]Ga-FAPI-04 PET/CT for its efficacy in the early diagnosis of PC through a systematic comparison with surgical pathology.
Methods:
In this retrospective study, 267 patients (99 males; median age 59 years) suspected of peritoneal malignancies underwent [68Ga]Ga-FAPI-04 PET/CT from February 2022 to October 2024. Diagnostic performance was compared using patient-based and lesion-based analyses. The regions of peritoneal lesion and Peritoneal Cancer Index (PCI) scores were evaluated with surgical pathology as the reference standard. Lesions were categorized into five morphological subtypes for semi-quantitative analysis, and uptake metrics (SUVmax, SUVmean, TBR) were compared across subgroups.
Results:
Of the 267 patients, 251 were confirmed to have peritoneal metastasis. On patient-based versus lesion-based analysis, the modality achieved a sensitivity of 98.8% (248/251) vs. 93.8% (180/192); a specificity of 50% (8/16) vs. 72.7% (8/11); and an accuracy of 95.9% (256/267) vs. 92.6% (188/203). Compared with surgical pathology, [68Ga]Ga-FAPI-04 PET/CT exhibited strong correlations for involved regions [5 (0-13) vs. 6 (1-12)] and PCI scores [10 (0-39) vs. 12 (2-37)] (both P < 0.001), showing good consistency with actual lesion distribution. Furthermore, the cake-like and mass-forming subtypes exhibited significantly higher uptake compared to other subtypes (all P < 0.001).
Conclusions:
[68Ga]Ga-FAPI-04 PET/CT provides high diagnostic performance for early peritoneal carcinomatosis, reliably assessing tumor burden and distribution in correlation with surgical findings and differentiating morphological subtypes to guide preoperative planning.
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