4.7 Article

Towards an Automated Approach to the Semi-Quantification of [18F]F-DOPA PET in Pediatric-Type Diffuse Gliomas

Journal

JOURNAL OF CLINICAL MEDICINE
Volume 12, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/jcm12082765

Keywords

semi-quantification; SUVr; [F-18]F-DOPA PET; pediatric oncology; PDGs

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This study aims to evaluate the use of a computer-aided approach to calculate the tumor-to-background ratio in pediatric-type diffuse gliomas (PDGs) using [F-18]F-DOPA positron emission tomography (PET). The results showed that the computer-aided approach yielded similar diagnostic and prognostic information compared to the manual procedure.
Background: This study aims to evaluate the use of a computer-aided, semi-quantification approach to [F-18]F-DOPA positron emission tomography (PET) in pediatric-type diffuse gliomas (PDGs) to calculate the tumor-to-background ratio. Methods: A total of 18 pediatric patients with PDGs underwent magnetic resonance imaging and [F-18]F-DOPA PET, which were analyzed using both manual and automated procedures. The former provided a tumor-to-normal-tissue ratio (T-N) and tumor-to-striatal-tissue ratio (T-S), while the latter provided analogous scores (t(n), t(s)). We tested the correlation, consistency, and ability to stratify grading and survival between these methods. Results: High Pearson correlation coefficients resulted between the ratios calculated with the two approaches: rho = 0.93 (p < 10(-4)) and rho = 0.814 (p < 10(-4)). The analysis of the residuals suggested that t(n) and t(s) were more consistent than T-N and T-S. Similarly to T-N and T-S, the automatically computed scores showed significant differences between low- and high-grade gliomas (p <= 10(-4), t-test) and the overall survival was significantly shorter in patients with higher values when compared to those with lower ones (p < 10(-3), log-rank test). Conclusions: This study suggested that the proposed computer-aided approach could yield similar results to the manual procedure in terms of diagnostic and prognostic information.

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