Impact of Image Reconstruction on Quantitative Analysis of 18F-Fdg Pet in Epilepsy Evaluation: A Preliminary Study Publisher



Firouzi N ; Parach A A ; Tanha K ; Rostami M S ; Geramifar P
Source: Frontiers in Biomedical Technologies Published:2026

Abstract

Purpose: In epilepsy pre-surgical evaluations, semi-automated quantitative analysis of Fluorine-18-fluorodeoxyglucose (18F-FDG) brain PET complements visual assessment for localizing the seizure onset zone. This study evaluates how adjusting reconstruction parameters enhances quantitative accuracy, aiming to identify optimal configurations for reliable clinical decision-making. Materials and Methods: 234 reconstruction methods were applied to 18F-FDG brain PET images of a 47-year-old male with focal epilepsy. The parameters encompassed the 3D-Ordered-Subset Expectation Maximization image reconstruction method, both with Resolution Recovery (RR) and without (non-RR), various numbers of iterations×subset (#it×sub), pixel sizes, and Gaussian filters. The accuracy errors were determined by the Relative Difference Percentage (RDP) in measured maximum standardized uptake value SUVmax and absolute Z-scores from all 234 reconstructed images, compared to reference values from the normal database reconstruction set as the benchmark Results: The study revealed that reconstructed images with 5 mm or 8 mm full width at half maximum (FWHM) Gaussian filters yielded RDP values above 5% for SUVmax and Z-scores, indicating potential inaccuracy with higher values of post-smoothing filters. The recommended reconstruction sets with RDP values below 5% for both RR and non-RR images were those with a 3 mm FWHM Gaussian filter and higher (#it×sub), specifically (5×21, 8×21), (5×21, 6×21), and (7×21, 8×21) for pixel sizes of 1.01 mm, 1.35 mm, and 2.03 mm, respectively. Conclusion: The findings underscore the significant impact of altering the image reconstruction sets on the SUVmax and Z-scores. Furthermore, the inconsistent fluctuations of Z-scores emphasize the importance of using standardized image reconstruction sets to ensure accurate and reliable quantitative outcomes in epilepsy presurgical evaluations. Copyright © 2026 Tehran University of Medical Sciences. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/by-nc/4.0/). Noncommercial uses of the work are permitted, provided the original work is properly cited.