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

Abstract

Purpose

The role for [18F]FDG-PET in supporting amyotrophic lateral sclerosis (ALS) diagnosis is not fully established. In this study, we aim at evaluating [18F]FDG-PET hypo- and hyper-metabolism patterns in spinal- and bulbar-onset ALS cases, at the single-subject level, testing the diagnostic value in discriminating the two conditions, and the correlations with core clinical symptoms severity.

Methods

We included 95 probable-ALS patients with [18F]FDG-PET scan and clinical follow-up. [18F]FDG-PET images were analyzed with an optimized voxel-based-SPM method. The resulting single-subject SPM-t maps were used to: (a) assess brain regional hypo- and hyper-metabolism; (b) evaluate the accuracy of regional hypo- and hyper metabolism in discriminating spinal vs. bulbar-onset ALS; (c) perform correlation analysis with motor symptoms severity, as measured by ALS-FRS-R.

Results

Primary motor cortex showed the most frequent hypo-metabolism in both spinal-onset (∼57%) and bulbar-onset (∼64%) ALS; hyper-metabolism was prevalent in the cerebellum in both spinal-onset (∼56.5%) and bulbar-onset (∼55.7%) ALS, and in the occipital cortex in bulbar-onset (∼62.5%) ALS. Regional hypo- and hyper-metabolism yielded a very low accuracy (AUC < 0.63) in discriminating spinal- vs. bulbar-onset ALS, as obtained from single-subject SPM-t-maps. Severity of motor symptoms correlated with hypo-metabolism in sensorimotor cortex in spinal-onset ALS, and with cerebellar hyper-metabolism in bulbar-onset ALS.

Conclusions

The high variability in regional hypo- and hyper-metabolism patterns, likely reflecting the heterogeneous pathology and clinical phenotypes, limits the diagnostic potential of [18F]FDG-PET in discriminating spinal and bulbar onset patients.

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Funding

This study was funded by the Italian Ministry of Health (Ricerca Finalizzata Progetto Reti Nazionale AD NET-2011-02346784) (D.P), EU FP7 INMIND Project (FP7-HEALTH-2011-two-stage “Imaging of Neuroinflammation in Neurodegenerative Diseases”, grant agreement no. 278850)” (D.P.), “IVASCOMAR project “Identificazione, validazione e sviluppo commerciale di nuovi biomarcatori diagnostici prognostici per malattie complesse” (grant agreement no. CTN01_00177_165430)” (D.P.), CARIPLO Project “Evaluation of autonomic, genetic, imaging and biochemical markers for Parkinson-related dementia: longitudinal assessment of a PD cohort” 2016–2020 (grant agreement no. 2014–0832)” (D.P.), Fondazione Eli-Lilly (Eli-Lilly grant 2011 “Imaging of neuroinflammation and neurodegeneration in prodromal and presymptomatic Alzheimer’s disease phases”)(C.C.), Ministero dell’Istruzione, dell’Università e della Ricerca – MIUR project “Dipartimenti di Eccellenza 2018–2022″ to Department of Neuroscience “Rita Levi Montalcini”(Ad.C, And.C, Ant.C.). This work was in part supported by the Italian Ministry of Health (Ricerca Sanitaria Finalizzata 2010, grant RF-2010e2309849) (Ad.C), the European Community’s Health Seventh Framework Programme (FP7/2007–2013 under grant agreement 259867) (Ad.C), the Joint Programme - Neurodegenerative Disease Research (Italian Ministry of Education, University and Research) (Sophia) (Ad.C.), Fondazione Vialli e Mauro (And.C.); and Fondazione Magnetto (Ant.C.).

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Correspondence to Daniela Perani.

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A. Chiò reports grants from the Italian Ministry of Health (Ricerca Finalizzata), EU JPND through the Ministry of Education, University, and Research, and the Italy-Israel Scientific Collaboration through the Italian Foreign Ministry, as well as personal fees from Biogen Idec, Cytokinetics, Italfarmaco, Mitsubishi Tanabe, and Neuraltus. All other authors declare that they have no conflict of interest.

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Sala, A., Iaccarino, L., Fania, P. et al. Testing the diagnostic accuracy of [18F]FDG-PET in discriminating spinal- and bulbar-onset amyotrophic lateral sclerosis. Eur J Nucl Med Mol Imaging 46, 1117–1131 (2019). https://doi.org/10.1007/s00259-018-4246-2

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Keywords

  • Amyotrophic lateral sclerosis
  • Biomarkers
  • Diagnosis
  • [18F]FDG-PET
  • Brain metabolism