Data-driven image-based protocol for brain PET image harmonization

Eva Rebec (Author), Urban Simončič (Author)

Abstract

Quantitative FDG-PET brain imaging across multiple centers is challenged by inter-scanner variability, impacting the comparability of neuroimaging data. This study proposes a data-driven image-based harmonization protocol to address these discrepancies without relying on traditional phantom scans. The protocol uses spatially normalized FDG-PET brain images to estimate scanner-specific Gaussian smoothing filters, optimizing parameters via the structural similarity index (SSIM). Validation was performed using images from cognitively normal individuals and Alzheimer’s disease patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Results demonstrated robust harmonization at moderate target resolutions (8 and 10 mm FWHM), with filter estimates consistently within 1.2 mm of phantom-derived ground truths. However, at higher resolutions (6 mm FWHM), discrepancies reached up to 3 mm, reflecting reduced accuracy. These deviations were particularly evident for high-resolution scanners like HRRT, likely due to elevated noise levels and smaller sample sizes. The presented harmonization method effectively reduces inter-scanner variability in retrospective FDG-PET studies, especially valuable when phantom scans are unavailable. Nonetheless, the current limitations at finer resolutions underline the necessity for methodological refinements to meet the demands of evolving high-resolution PET imaging technologies.

Keywords

medicinska fizika;medicinsko slikanje;FDG-PET;slikanje možganov;medical physics;medical imaging;positron emission tomography;brain imaging;

Data

Language:	English
Year of publishing:	2025
Typology:	1.01 - Original Scientific Article
Organization:	UL FMF - Faculty of Mathematics and Physics
UDC:	616-073:53
COBISS:	243679491
ISSN:	1424-8220
Views:	102
Downloads:	44
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	medicinska fizika;medicinsko slikanje;FDG-PET;slikanje možganov;
Type (COBISS):	Article
Pages:	17 str.
Volume:	ǂVol. ǂ25
Issue:	ǂiss. ǂ13, art. no. 4230
Chronology:	Jul. 2025
DOI:	10.3390/s25134230
ID:	26875272