Literature DB >> 25122207

Functional pattern of brain FDG-PET in amyotrophic lateral sclerosis.

Marco Pagani1, Adriano Chiò2, Maria Consuelo Valentini2, Johanna Öberg2, Flavio Nobili2, Andrea Calvo2, Cristina Moglia2, Davide Bertuzzo2, Silvia Morbelli2, Fabrizio De Carli2, Piercarlo Fania2, Angelina Cistaro2.   

Abstract

OBJECTIVE: We investigated a large sample of patients with amyotrophic lateral sclerosis (ALS) at rest in order to assess the value of (18)F-2-fluoro-2-deoxy-d-glucose ((18)F-FDG) PET as a biomarker to discriminate patients from controls.
METHODS: A total of 195 patients with ALS and 40 controls underwent brain (18)F-FDG-PET, most within 5 months of diagnosis. Spinal and bulbar subgroups of ALS were also investigated. Twenty-five bilateral cortical and subcortical volumes of interest and cerebellum were taken into account, and (18)F-FDG uptakes were individually normalized by whole-brain values. Group analyses investigated the ALS-related metabolic changes. Discriminant analysis investigating sensitivity and specificity was performed using the 51 volumes of interest as well as age and sex. Metabolic connectivity was explored by voxel-wise interregional correlation analysis.
RESULTS: Hypometabolism was found in frontal, motor, and occipital cortex and hypermetabolism in midbrain, temporal pole, and hippocampus in patients with ALS compared to controls. A similar metabolic pattern was also found in the 2 subgroups. Discriminant analysis showed a sensitivity of 95% and a specificity of 83% in separating patients from controls. Connectivity analysis found a highly significant positive correlation between midbrain and white matter in corticospinal tracts in patients with ALS.
CONCLUSIONS: (18)F-FDG distribution changes in ALS showed a clear pattern of hypometabolism in frontal and occipital cortex and hypermetabolism in midbrain. The latter might be interpreted as the neurobiological correlate of diffuse subcortical gliosis. Discriminant analysis resulted in high sensitivity and specificity in differentiating patients with ALS from controls. Once validated by diseased-control studies, the present methodology might represent a potentially useful biomarker for ALS diagnosis. CLASSIFICATON OF EVIDENCE: This study provides Class III evidence that (18)F-FDG-PET accurately distinguishes patients with ALS from normal controls (sensitivity 95.4%, specificity 82.5%).
© 2014 American Academy of Neurology.

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Year:  2014        PMID: 25122207     DOI: 10.1212/WNL.0000000000000792

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  61 in total

1.  (11)C-PBR28 imaging in multiple sclerosis patients and healthy controls: test-retest reproducibility and focal visualization of active white matter areas.

Authors:  Eunkyung Park; Jean-Dominique Gallezot; Aracely Delgadillo; Shuang Liu; Beata Planeta; Shu-Fei Lin; Kevin C O'Connor; Keunpoong Lim; Jae-Yun Lee; Anne Chastre; Ming-Kai Chen; Nicholas Seneca; David Leppert; Yiyun Huang; Richard E Carson; Daniel Pelletier
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-04-02       Impact factor: 9.236

2.  Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease.

Authors:  Nicolai Franzmeier; Anna Rubinski; Julia Neitzel; Yeshin Kim; Alexander Damm; Duk L Na; Hee Jin Kim; Chul Hyoung Lyoo; Hana Cho; Sofia Finsterwalder; Marco Duering; Sang Won Seo; Michael Ewers
Journal:  Brain       Date:  2019-04-01       Impact factor: 13.501

3.  Brain 18F-FDG PET/CT findings in a case of genetic Creutzfeldt-Jakob disease due to V203I heterozygous mutation in the PRNP gene.

Authors:  A Cistaro; L Cassalia; C Ferrara; C Atzori; D Vai; N Quartuccio; P Fania; G P Vaudano; D Imperiale
Journal:  J Neurol       Date:  2016-11-14       Impact factor: 4.849

4.  Cerebellar metabolic involvement and its correlations with clinical parameters in vestibular neuritis.

Authors:  Marco Alessandrini; Alessandro Micarelli; Agostino Chiaravalloti; Matteo Candidi; Ernesto Bruno; Barbara Di Pietro; Johanna Öberg; Orazio Schillaci; Marco Pagani
Journal:  J Neurol       Date:  2014-08-01       Impact factor: 4.849

Review 5.  Positron emission tomography in amyotrophic lateral sclerosis: Towards targeting of molecular pathological hallmarks.

Authors:  Stefanie M A Willekens; Donatienne Van Weehaeghe; Philip Van Damme; Koen Van Laere
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-12-08       Impact factor: 9.236

Review 6.  Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis.

Authors:  Suvi Häkkinen; Stephanie A Chu; Suzee E Lee
Journal:  Neurobiol Dis       Date:  2020-09-02       Impact factor: 5.996

7.  Precentral degeneration and cerebellar compensation in amyotrophic lateral sclerosis: A multimodal MRI analysis.

Authors:  Ting Qiu; Yuanchao Zhang; Xie Tang; Xiaoping Liu; Yue Wang; Chaoyang Zhou; Chunxia Luo; Jiuquan Zhang
Journal:  Hum Brain Mapp       Date:  2019-04-24       Impact factor: 5.038

8.  Testing the diagnostic accuracy of [18F]FDG-PET in discriminating spinal- and bulbar-onset amyotrophic lateral sclerosis.

Authors:  Arianna Sala; Leonardo Iaccarino; Piercarlo Fania; Emilia G Vanoli; Federico Fallanca; Caterina Pagnini; Chiara Cerami; Andrea Calvo; Antonio Canosa; Marco Pagani; Adriano Chiò; Angelina Cistaro; Daniela Perani
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-01-07       Impact factor: 9.236

Review 9.  Motor neuron disease in 2014. Biomarkers for ALS--in search of the Promised Land.

Authors:  Adriano Chiò; Bryan J Traynor
Journal:  Nat Rev Neurol       Date:  2014-12-23       Impact factor: 42.937

Review 10.  ALS biomarkers for therapy development: State of the field and future directions.

Authors:  Michael Benatar; Kevin Boylan; Andreas Jeromin; Seward B Rutkove; James Berry; Nazem Atassi; Lucie Bruijn
Journal:  Muscle Nerve       Date:  2015-12-29       Impact factor: 3.217

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