1. A New Preclinical Decision Support System Based on PET Radiomics: A Preliminary Study on the Evaluation of an Innovative 64 Cu-Labeled Chelator in Mouse Models.
- Author
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Benfante, Viviana, Stefano, Alessandro, Comelli, Albert, Giaccone, Paolo, Cammarata, Francesco Paolo, Richiusa, Selene, Scopelliti, Fabrizio, Pometti, Marco, Ficarra, Milene, Cosentino, Sebastiano, Lunardon, Marcello, Mastrotto, Francesca, Andrighetto, Alberto, Tuttolomondo, Antonino, Parenti, Rosalba, Ippolito, Massimo, and Russo, Giorgio
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CLINICAL decision support systems ,LUNGS ,RADIOMICS ,HEART ,POSITRON emission tomography ,LABORATORY mice ,FEATURE extraction - Abstract
The
64 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 after64 Cu-labeled chelator injection. Specifically, the mice were divided into group 1 (acquisition 1 h after [64 Cu] chelator administration, n = 3 mice), group 2 (acquisition 4 h after [64 Cu]chelator administration, n = 3 mice), and group 3 (acquisition 24 h after [64 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 [64 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 (p-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 the64 Cu-labeled chelator over time. The proposed methodology may improve the method of calculating the [64 Cu]chelator biodistribution and open the way towards a decision support system in the field of new radiopharmaceuticals used in preclinical imaging trials. [ABSTRACT FROM AUTHOR]- Published
- 2022
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