Literature DB >> 23585159

Comparison of different methods of spatial normalization of FDG-PET brain images in the voxel-wise analysis of MCI patients and controls.

María Elena Martino1, Juan Guzmán de Villoria, María Lacalle-Aurioles, Javier Olazarán, Isabel Cruz, Eloisa Navarro, Verónica García-Vázquez, José Luis Carreras, Manuel Desco.   

Abstract

OBJECTIVE: One of the most interesting clinical applications of 18F-FDG PET imaging in neurodegenerative pathologies is that of establishing the prognosis of patients with mild cognitive impairment (MCI), some of whom have a high risk of progressing to Alzheimer's disease (AD). One method of analyzing these images is to perform statistical parametric mapping (SPM) analysis. Spatial normalization is a critical step in such an analysis. The purpose of this study was to assess the effect of using different methods of spatial normalization on the results of SPM analysis of 18F-FDG PET images by comparing patients with MCI and controls.
METHODS: We evaluated the results of three spatial normalization methods in an SPM analysis by comparing patients diagnosed with MCI with a group of control subjects. We tested three methods of spatial normalization: MRI-DARTEL and MRI-SPM8, which combine structural and functional images, and FDG-SPM8, which is based on the functional images only.
RESULTS: The results obtained with the three methods were consistent in terms of the main pattern of functional alterations detected; namely, a bilateral reduction in glucose metabolism in the frontal and parietal cortices in the patient group. However, MRI-SPM8 also revealed differences in the left temporal cortex, and MRI-DARTEL revealed further differences in the left temporal cortex, precuneus, and left posterior cingulate.
CONCLUSIONS: The results obtained with MRI-DARTEL were the most consistent with the pattern of changes in AD. When we compared our observations with those of previous reports, MRI-SPM8 and FDG-SPM8 seemed to show an incomplete pattern. Our results suggest that basing the spatial normalization method on functional images only can considerably impair the results of SPM analysis of 18F-FDG PET studies.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23585159     DOI: 10.1007/s12149-013-0723-7

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  12 in total

1.  Validation of 18F-FDG-PET Single-Subject Optimized SPM Procedure with Different PET Scanners.

Authors:  Luca Presotto; Tommaso Ballarini; Silvia Paola Caminiti; Valentino Bettinardi; Luigi Gianolli; Daniela Perani
Journal:  Neuroinformatics       Date:  2017-04

2.  A standardized [18F]-FDG-PET template for spatial normalization in statistical parametric mapping of dementia.

Authors:  Pasquale Anthony Della Rosa; Chiara Cerami; Francesca Gallivanone; Annapaola Prestia; Anna Caroli; Isabella Castiglioni; Maria Carla Gilardi; Giovanni Frisoni; Karl Friston; John Ashburner; Daniela Perani
Journal:  Neuroinformatics       Date:  2014-10

3.  A Spatial Registration Toolbox for Structural MR Imaging of the Aging Brain.

Authors:  Marco Ganzetti; Quanying Liu; Dante Mantini
Journal:  Neuroinformatics       Date:  2018-04

4.  Deformation field correction for spatial normalization of PET images.

Authors:  Murat Bilgel; Aaron Carass; Susan M Resnick; Dean F Wong; Jerry L Prince
Journal:  Neuroimage       Date:  2015-06-30       Impact factor: 6.556

5.  Assessment of brain damage and plasticity in the visual system due to early occipital lesion: comparison of FDG-PET with diffusion MRI tractography.

Authors:  Jeong-won Jeong; Vijay N Tiwari; Joseph Shin; Harry T Chugani; Csaba Juhász
Journal:  J Magn Reson Imaging       Date:  2014-01-06       Impact factor: 4.813

6.  Quantitative SPM Analysis Involving an Adaptive Template May Be Easily Applied to [18F]FDG PET Images of the Rat Brain.

Authors:  Sylvain Poussier; Fatiha Maskali; Gaelle Vexiau; Antoine Verger; Henri Boutley; Gilles Karcher; Emmanuel Raffo; Pierre-Yves Marie
Journal:  Mol Imaging Biol       Date:  2017-10       Impact factor: 3.488

7.  Controls-based denoising, a new approach for medical image analysis, improves prediction of conversion to Alzheimer's disease with FDG-PET.

Authors:  Dominik Blum; Inga Liepelt-Scarfone; Daniela Berg; Thomas Gasser; Christian la Fougère; Matthias Reimold
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-24       Impact factor: 9.236

8.  Unified spatial normalization method of brain PET images using adaptive probabilistic brain atlas.

Authors:  Tianhao Zhang; Binbin Nie; Hua Liu; Baoci Shan
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-03-08       Impact factor: 10.057

9.  Construction and comparative evaluation of different activity detection methods in brain FDG-PET.

Authors:  Hans-Georg Buchholz; Fabian Wenzel; Martin Gartenschläger; Frank Thiele; Stewart Young; Stefan Reuss; Mathias Schreckenberger
Journal:  Biomed Eng Online       Date:  2015-08-18       Impact factor: 2.819

10.  Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Cognitively Unimpaired Individuals Using Multi-feature Kernel Discriminant Dictionary Learning.

Authors:  Qing Li; Xia Wu; Lele Xu; Kewei Chen; Li Yao
Journal:  Front Comput Neurosci       Date:  2018-01-09       Impact factor: 2.380

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.