Diagnostic accuracy of 18F-FDG PET/CT in muscle-invasive bladder cancer: rationale and design of the MIBC-PET study

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Authors: Luca Urso, Francesco Feletti, Federica Lancia, Francesca Tiozzo Canella, Corrado Cittanti, Ilham Badrane, Sara Adamantiadis, Licia Uccelli, Antonella Iudicello, Alberto Nieri, Matteo Caracciolo, Ilaria Rambaldi
+8 more Riccardo Bisi, Luigi Manco, Ilaria Bagni, Massimo Guidoboni, Luana Calabrò, Carmelo Ippolito, M. Giganti, Mirco Bartolomei
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References: 26

Abstract

Introduction Muscle-invasive bladder cancer (MIBC) is associated with poor prognosis. Current staging relies on CT and MRI, but both show limited sensitivity for nodal and distant metastases. [ 18 F]FDG PET/CT has emerged as a promising tool for staging and response assessment, yet its role remains undefined. Methods and analysis MIBC-PET is a prospective, monocentric, no-profit study with paired imaging comparison enrolling 60 patients with newly diagnosed, histologically confirmed high-grade MIBC. All patients undergo baseline staging with [ 18 F]FDG PET/CT and contrast-enhanced CT (ceCT) of chest, abdomen, and pelvis. A second [ 18 F]FDG PET/CT and CT are performed after two cycles of neoadjuvant therapy. [ 18 F]FDG PET/CT includes both standard delayed imaging and an early dynamic pelvic acquisition to overcome urinary tracer interference. The primary endpoints are (1) diagnostic accuracy of [ 18 F]FDG PET/CT vs. ceCT for baseline staging, and (2) accuracy of [ 18 F]FDG PET/CT in predicting pathological response to neoadjuvant chemotherapy. Secondary endpoints include validation of early dynamic [ 18 F]FDG PET/CT for local staging and radiomic/AI-based predictive modeling. Ethics and dissemination The study complies with the Declaration of Helsinki and Good Clinical Practice guidelines. The study was approved by the local ethical committee (CE-AVEC 109-2024-Oss-AOUFe – P.I. Dr. Luca Urso, MD). Results will inform the integration of [ 18 F]FDG PET/CT into diagnostic algorithms for MIBC. Trial registration ClinicalTrials.gov , identifier: not yet assigned. Local trial registration code: CE-AVEC 109-2024-Oss-AOUFe.

Fields of Study & Subjects

Medical Imaging Techniques and Applications Bladder and Urothelial Cancer Treatments Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Frontiers in Medicine
Volume
13
Pages
1792243–1792243
Publication date
12 March 2026
Language
EN