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Biodistribution Assessment of a Novel 68Ga-Labeled Radiopharmaceutical in a Cancer Overexpressing CCK2R Mouse Model: Conventional and Radiomics Methods for Analysis

Authors :
Anna Maria Pavone
Viviana Benfante
Paolo Giaccone
Alessandro Stefano
Filippo Torrisi
Vincenzo Russo
Davide Serafini
Selene Richiusa
Marco Pometti
Fabrizio Scopelliti
Massimo Ippolito
Antonino Giulio Giannone
Daniela Cabibi
Mattia Asti
Elisa Vettorato
Luca Morselli
Mario Merone
Marcello Lunardon
Alberto Andrighetto
Antonino Tuttolomondo
Francesco Paolo Cammarata
Marco Verona
Giovanni Marzaro
Francesca Mastrotto
Rosalba Parenti
Giorgio Russo
Albert Comelli
Source :
Life, Vol 14, Iss 3, p 409 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The aim of the present study consists of the evaluation of the biodistribution of a novel 68Ga-labeled radiopharmaceutical, [68Ga]Ga-NODAGA-Z360, injected into Balb/c nude mice through histopathological analysis on bioptic samples and radiomics analysis of positron emission tomography/computed tomography (PET/CT) images. The 68Ga-labeled radiopharmaceutical was designed to specifically bind to the cholecystokinin receptor (CCK2R). This receptor, naturally present in healthy tissues such as the stomach, is a biomarker for numerous tumors when overexpressed. In this experiment, Balb/c nude mice were xenografted with a human epidermoid carcinoma A431 cell line (A431 WT) and overexpressing CCK2R (A431 CCK2R+), while controls received a wild-type cell line. PET images were processed, segmented after atlas-based co-registration and, consequently, 112 radiomics features were extracted for each investigated organ / tissue. To confirm the histopathology at the tissue level and correlate it with the degree of PET uptake, the studies were supported by digital pathology. As a result of the analyses, the differences in radiomics features in different body districts confirmed the correct targeting of the radiopharmaceutical. In preclinical imaging, the methodology confirms the importance of a decision-support system based on artificial intelligence algorithms for the assessment of radiopharmaceutical biodistribution.

Details

Language :
English
ISSN :
20751729
Volume :
14
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Life
Publication Type :
Academic Journal
Accession number :
edsdoj.64a6d1ac13f04ce09cb9e4845723a8d5
Document Type :
article
Full Text :
https://doi.org/10.3390/life14030409