A New Preclinical Decision Support System Based on PET Radiomics: A Preliminary Study on the Evaluation of an Innovative <sup>64</sup>Cu-Labeled Chelator in Mouse Models

oleh: Viviana Benfante, Alessandro Stefano, Albert Comelli, Paolo Giaccone, Francesco Paolo Cammarata, Selene Richiusa, Fabrizio Scopelliti, Marco Pometti, Milene Ficarra, Sebastiano Cosentino, Marcello Lunardon, Francesca Mastrotto, Alberto Andrighetto, Antonino Tuttolomondo, Rosalba Parenti, Massimo Ippolito, Giorgio Russo

Format: Article
Diterbitkan: MDPI AG 2022-03-01

Deskripsi

The <sup>64</sup>Cu-labeled chelator was analyzed in vivo by positron emission tomography (PET) imaging to evaluate its biodistribution in a murine model at different acquisition times. For this purpose, nine 6-week-old female Balb/C nude strain mice underwent micro-PET imaging at three different time points after <sup>64</sup>Cu-labeled chelator injection. Specifically, the mice were divided into group 1 (acquisition 1 h after [<sup>64</sup>Cu] chelator administration, n = 3 mice), group 2 (acquisition 4 h after [<sup>64</sup>Cu]chelator administration, n = 3 mice), and group 3 (acquisition 24 h after [<sup>64</sup>Cu] chelator administration, n = 3 mice). Successively, all PET studies were segmented by means of registration with a standard template space (3D whole-body Digimouse atlas), and 108 radiomics features were extracted from seven organs (namely, heart, bladder, stomach, liver, spleen, kidney, and lung) to investigate possible changes over time in [<sup>64</sup>Cu]chelator biodistribution. The one-way analysis of variance and post hoc Tukey Honestly Significant Difference test revealed that, while heart, stomach, spleen, kidney, and lung districts showed a very low percentage of radiomics features with significant variations (<i>p</i>-value < 0.05) among the three groups of mice, a large number of features (greater than 60% and 50%, respectively) that varied significantly between groups were observed in bladder and liver, indicating a different in vivo uptake of the <sup>64</sup>Cu-labeled chelator over time. The proposed methodology may improve the method of calculating the [<sup>64</sup>Cu]chelator biodistribution and open the way towards a decision support system in the field of new radiopharmaceuticals used in preclinical imaging trials.