Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A New Tool for Extracting Static and Dynamic Parameters from [18F]F-DOPA PET/CT in Pediatric Gliomas

Michele Mureddu
ORCID logo ,
Thomas Funck
,
Giovanni Morana
,
Andrea Rossi
,
Antonia Ramaglia
,
Claudia Milanaccio
,
Antonio Verrico
ORCID logo ,
Gianluca Bottoni
,
Francesco Fiz
ORCID logo ,
Arnoldo Piccardo
* ORCID logo ,
Marco Massimo Fato
,
Trò Rosella
Version 1 : Received: 3 September 2024 / Approved: 3 September 2024 / Online: 4 September 2024 (18:11:23 CEST)

How to cite: Mureddu, M.; Funck, T.; Morana, G.; Rossi, A.; Ramaglia, A.; Milanaccio, C.; Verrico, A.; Bottoni, G.; Fiz, F.; Piccardo, A.; Fato, M. M.; Rosella, T. A New Tool for Extracting Static and Dynamic Parameters from [18F]F-DOPA PET/CT in Pediatric Gliomas. Preprints 2024, 2024090299. https://doi.org/10.20944/preprints202409.0299.v1 Mureddu, M.; Funck, T.; Morana, G.; Rossi, A.; Ramaglia, A.; Milanaccio, C.; Verrico, A.; Bottoni, G.; Fiz, F.; Piccardo, A.; Fato, M. M.; Rosella, T. A New Tool for Extracting Static and Dynamic Parameters from [18F]F-DOPA PET/CT in Pediatric Gliomas. Preprints 2024, 2024090299. https://doi.org/10.20944/preprints202409.0299.v1

Abstract

PET imaging with [18F]F-DOPA has demonstrated high potential for the evaluation and management of pediatric brain gliomas. Manual extraction of PET parameters is time-consuming, lacks reproducibility, and varies with operator experience. In this study, we tested whether a semi-automated image processing framework could overcome these limitations. Pediatric patients with available static and/or dynamic [18F]F-DOPA PET studies were evaluated retrospectively. We developed a Python software to automate clinical index calculations, including preprocessing to delineate tumor volumes from structural MRI, accounting for lesions with low [18F]F-DOPA uptake. 73 subjects with treatment-naïve low and high-grade gliomas, who underwent brain MRI within two weeks of [18vF]F-DOPA PET, were included and analyzed. Static analysis was conducted on all subjects, while dynamic analysis was performed on 32 patients. For 68 subjects, the Intraclass Correlation Coefficient for T/S between manual and ground truth segmentation was 0.91. Using our tool, ICC improved to 0.94. Our method demonstrated good reproducibility in extracting static tumor-to-striatum ratio (p = 0.357), though significant differences were observed in tumor slope (p < 0.05). No significant differences were found in time-to-peak (p = 0.167) and striatum slope (p = 0.36). Our framework aids in analyzing [18F]F-DOPA PET images of pediatric brain tumors by automating clinical score extraction, simplifying segmentation and Time Activity Curve extraction, reducing user variability, and enhancing reproducibility.

Keywords

automatic pipeline; brain gliomas; [18F]F-DOPA PET imaging; FLAIR MRI; pediatric gliomas

Subject

Engineering, Bioengineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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