ArticleEJNMMI physics2023
Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan.
Article in EJNMMI physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- P300 Event-Related Potentials as Cognitive Biomarkers in Neurological and Neuropsychiatric Disorders: A Systematic Review.Revista de neurologia · 2026Pooled it
- Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standard for PET imaging of brain metastases: version 1.0.European journal of nuclear medicine and molecular imaging · 2025Guideline
- From image reconstruction to clinical prognosis: A comprehensive analysis of centiloid-based amyloid PET assessment.European journal of nuclear medicine and molecular imaging · 2026Article
- Article
- Ternary classification prediction and heterogeneity quantification for HER2-Zero, -low, and -positive in breast cancer using HER2-targeted PET/CT imaging.European journal of nuclear medicine and molecular imaging · 2026Article
- Reconstruction matters: influence of EARL standards and BSREM in [EJNMMI research · 2026Article
- Comparative performance of semi-quantitative methods for amyloid deposition in preclinical autosomal dominant Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- Self-reported sleep quality and longitudinal amyloid burden in clinically unimpaired adults from the AMYPAD PNHS study.Alzheimer's research & therapy · 2026Article
- Generation of an Age-Dependent and HarmonizedHuman brain mapping · 2026Article
- Long vs. short axial field-of-view PET scanners for brain imaging: a phantom study.Frontiers in nuclear medicine · 2026Article
- Quantification of baseline amyloid PET in individuals with subjective cognitive decline can identify risk of amyloid accumulation and cognitive worsening: the FACEHBI study.European journal of nuclear medicine and molecular imaging · 2025Article
- IRMA: Machine learning-based harmonization ofEuropean journal of nuclear medicine and molecular imaging · 2025Article
- A novel method for harmonization of PET image spatial resolution without phantoms.EJNMMI physics · 2025Article
- Considerations in the clinical use of amyloid PET and CSF biomarkers for Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Digital detector PET/CT increases Centiloid measures of amyloid in Alzheimer's disease: A head-to-head comparison of cameras.Journal of Alzheimer's disease : JAD · 2025Article
- Optimization of penalization function in Bayesian penalized likelihood reconstruction algorithm for [Physical and engineering sciences in medicine · 2024Article
- Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- The impact of tau-PET in a selected memory clinic cohort: rationale and design of the TAP-TAU study.Alzheimer's research & therapy · 2024Article
- StepBrain: A 3-Dimensionally Printed Multicompartmental Anthropomorphic Brain Phantom to Simulate PET Activity Distributions.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
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Abstract
backgroundImage harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial.
methodHoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using "Hoffman 3D brain Analysis tool," indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method's robustness against typical dose-calibrator-based errors was assessed.
resultsThe EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040-0.012), and Contrast SD (0.14-0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR.
conclusionHarmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy.
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