Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification.

Aged; Aged, 80 and over; Alzheimer Disease/diagnostic imaging; Brain/diagnostic imaging; Databases, Factual; Female; Humans; Magnetic Resonance Imaging/methods/standards; Male; Middle Aged; Plaque, Amyloid/diagnostic imaging; Positron Emission Tomography Computed Tomography/methods/standards; Positron-Emission Tomography/methods/standards; Prodromal Symptoms; Radiation Dosage; Reproducibility of Results; Tomography, X-Ray Computed/methods/standards; Alzheimer's disease; Amyloid burden; Positron emission tomography/computed tomography; SUVr

Abstract :

[en] The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT ((18)F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global (18)F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVr(CT,) SUVr(MRI)) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVr(CT) and SUVr(MRI) global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis.

Disciplines :

Radiology, nuclear medicine & imaging

Author, co-author :

Presotto, Luca

Iaccarino, Leonardo

Sala, Arianna ; UniSR

Vanoli, Emilia G.

Muscio, Cristina

Nigri, Anna

Bruzzone, Maria Grazia

Tagliavini, Fabrizio

Gianolli, Luigi

Perani, Daniela

Bettinardi, Valentino

Language :

English

Title :

Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification.

Publication date :

2018

Journal title :

NeuroImage: Clinical

eISSN :

2213-1582

Publisher :

Elsevier, Netherlands

Volume :

Pages :

153-160

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 02 June 2021

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