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European Journal of Nuclear Medicine and Molecular Imaging
Erschienen in:

07.01.2019 | Original Article

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

verfasst von: 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

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 5/2019

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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.
Literatur
1.
Chiò A, Pagani M, Agosta F, Calvo A, Cistaro A, Filippi M. Neuroimaging in amyotrophic lateral sclerosis: insights into structural and functional changes. Lancet Neurol. 2014;13:1228–40.CrossRefPubMed
2.
Ludolph A, Drory V, Hardiman O, Nakano I, Ravits J, Robberecht W, et al. A revision of the El Escorial criteria - 2015. Amyotroph Lateral Scler Front Degener. 2015;16:291–2.
3.
Brooks BR, Miller RG, Swash M, Munsat TL. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1:293–9.CrossRefPubMed
4.
Zoccolella S, Beghi E, Palagano G, Fraddosio A, Samarelli V, Lamberti P, et al. Predictors of delay in the diagnosis and clinical trial entry of amyotrophic lateral sclerosis patients: a population-based study. J Neurol Sci. 2006;250:45–9.CrossRefPubMed
5.
Turner MR, Kiernan MC, Leigh PN, Talbot K. Biomarkers in amyotrophic lateral sclerosis. Lancet Neurol. Elsevier Ltd. 2009;8:94–109.CrossRef
6.
Swinnen B, Robberecht W. The phenotypic variability of amyotrophic lateral sclerosis. Nat. Rev. Neurol. Nature Publishing Group. 2014;10:661–70.CrossRef
7.
Chiò AISIS. Survey: an international study on the diagnostic process and its implications in amyotrophic lateral sclerosis. J Neurol. 1999;246:1–5.CrossRef
8.
Belsh JM, Schiffman PL. The amyotrophic lateral sclerosis (ALS) patient perspective on misdiagnosis and its repercussions. J Neurol Sci. 1996;139:110–6.CrossRefPubMed
9.
Nzwalo H, De Abreu D, Swash M, Pinto S, De Carvalho M. Delayed diagnosis in ALS: the problem continues. J Neurol Sci. 2014;343:173–5.CrossRefPubMed
10.
Hardiman O, van den Berg LH, Kiernan MC. Clinical diagnosis and management of amyotrophic lateral sclerosis. Nat Rev Neurol Nature Publishing Group. 2011;7:639–49.CrossRef
11.
Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol. 2014;13:614–29.CrossRefPubMed
12.
McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s dement. Elsevier Ltd. 2011;7:263–9.
13.
McKeith I, Boeve B, Dickson D, Lowe J, Emre M, Al E. Diagnosis and management of dementia with Lewy bodies: fourth consensus report of the DLB consortium. Neurology. 2017;89:88–100.CrossRefPubMedPubMedCentral
14.
Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging and Alzheimer’s association workgroup. Alzheimers Dement. 2011;7:270–9.CrossRefPubMedPubMedCentral
15.
Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, et al. Classification of primary progressive aphasia and its variants. Neurology. 2011;76:1006–14.CrossRefPubMedPubMedCentral
16.
Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011;134:2456–77.CrossRefPubMedPubMedCentral
17.
Stoessl AJ. Glucose utilization: still in the synapse. Nat Neurosci Nature Publishing Group. 2017;20:382–4.CrossRef
18.
Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s dement. Elsevier Ltd. 2011;7:280–92.
19.
Armstrong MJ, Litvan I, Lang AE, Bak TH, Bhatia KP, Borroni B, et al. Criteria for the diagnosis of corticobasal degeneration. Neurology. 2013;80:496–503.CrossRefPubMedPubMedCentral
20.
Caminiti SP, Alongi P, Majno L, Volontè MA, Cerami C, Gianolli L, et al. Evaluation of an optimized [18F]fluoro-deoxy-glucose positron emission tomography voxel-wise method to early support differential diagnosis in atypical Parkinsonian disorders. Eur J Neurol. 2017;24:687–e26.CrossRefPubMed
21.
Cerami C, Dodich A, Greco L, Iannaccone S, Magnani G, Marcone A, et al. The role of single-subject brain metabolic patterns in the early differential diagnosis of primary progressive aphasias and in prediction of progression to dementia. J Alzheimers Dis. 2016;55:183–97.CrossRefPubMedCentral
22.
Perani D, Della Rosa PA, Cerami C, Gallivanone F, Fallanca F, Vanoli EG, et al. Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting. NeuroImage. Clin. Elsevier BV. 2014;6:445–54.
23.
Perani D, Cerami C, Caminiti SP, Santangelo R, Coppi E, Ferrari L, et al. Cross-validation of biomarkers for the early differential diagnosis and prognosis of dementia in a clinical setting. Eur J Nucl Med Mol Imaging. 2016;43:499–508.CrossRefPubMed
24.
Cerami C, Della Rosa PA, Magnani G, Santangelo R, Marcone A, Cappa SF, et al. Brain metabolic maps in mild cognitive impairment predict heterogeneity of progression to dementia. NeuroImage Clin Elsevier BV. 2015;7:187–94.CrossRef
25.
Caminiti SP, Ballarini T, Sala A, Cerami C, Presotto L, Santangelo R, et al. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort. NeuroImage Clin Elsevier. 2018;18:167–77.CrossRef
26.
Pilotto A, Premi E, Caminiti SP, Presotto L, Alberici A, Paghera B, et al. Single-subject SPM FDG-PET patterns predict risk of dementia progression in Parkinson’s disease. Neurology. 2018;90:e1029–37.CrossRefPubMed
27.
Iaccarino L, Chiotis K, Alongi P, Almkvist O, Wall A, Cerami C, et al. A cross-validation of FDG- and amyloid-PET biomarkers in mild cognitive impairment for the risk prediction to dementia due to Alzheimer’s disease in a clinical setting. J Alzheimers Dis. 2017:1–12.
28.
Pagani M, Chiò A, Valentini MC, Öberg J, Nobili F, Calvo A, et al. Functional pattern of brain FDG-PET in amyotrophic lateral sclerosis. Neurology. 2014;83:1067–74.CrossRefPubMed
29.
Cistaro A, Valentini MC, Chiò A, Nobili F, Calvo A, Moglia C, et al. Brain hypermetabolism in amyotrophic lateral sclerosis: a FDG PET study in ALS of spinal and bulbar onset. Eur J Nucl Med Mol Imaging. 2012;39:251–9.CrossRefPubMed
30.
Van LK, Vanhee A, Verschueren J, De CL, Driesen A, Dupont P, et al. Value of 18fluorodeoxyglucose-positron-emission tomography in amyotrophic lateral sclerosis a prospective study. JAMA Neurol. 2014;71:553–61.CrossRef
31.
Matías-Guiu JA, Pytel V, Cabrera-Martín MN, Galán L, Valles-Salgado M, Guerrero A, et al. Amyloid- and FDG-PET imaging in amyotrophic lateral sclerosis. Eur J Nucl Med Mol Imaging. 2016;43:2050–60.CrossRefPubMed
32.
Canosa A, Pagani M, Cistaro A, Montuschi A, Iazzolino B, Fania P, et al. 18F-FDG-PET correlates of cognitive impairment in ALS. Neurology. 2015;86:44–9.CrossRefPubMed
33.
Agosta F, Altomare D, Festari C, Orini S, Gandolfo F, Boccardi M, et al. Clinical utility of FDG-PET in amyotrophic lateral sclerosis and Huntington disease. Eur J Nucl Med Mol Imaging. 2018;45:1546–56.CrossRefPubMed
34.
Varrone A, Asenbaum S, Vander Borght T, Booij J, Nobili F, Någren K, et al. EANM procedure guidelines for PET brain imaging using [18F] FDG, version 2. Eur J Nucl Med Mol Imaging Springer. 2009;36:2103–10.CrossRef
35.
Della Rosa PA, Cerami C, Gallivanone F, Prestia A, Caroli A, Castiglioni I, et al. A standardized [(18)F]-FDG-PET template for spatial normalization in statistical parametric mapping of dementia. Neuroinformatics. 2014;12:575–93.CrossRefPubMed
36.
Gallivanone F, Della Rosa P, Perani D, Gilardi MC, Castiglioni I. The impact of different 18FDG PET healthy subject scans for comparison with single patient in SPM analysis. Q J Nucl Med Mol Imaging. 2017;6(1):115–32.
37.
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage. 2002;15:273–89.CrossRefPubMed
38.
Sallet J, Mars RB, Noonan MP, Neubert F-X, Jbabdi S, O’Reilly JX, et al. The organization of dorsal frontal cortex in humans and macaques. J Neurosci. 2013;33:12255–74.CrossRefPubMedPubMedCentral
39.
Mayka MA, Corcos DM, Leurgans SE, Vaillancourt DE. Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: a meta-analysis. NeuroImage. 2006;31:1453–74.CrossRefPubMed
40.
Tziortzi AC, Searle GE, Tzimopoulou S, Salinas C, Beaver JD, Jenkinson M, et al. Imaging dopamine receptors in humans with [11C]-(+)-PHNO: dissection of D3 signal and anatomy. NeuroImage. 2011;54:264–77.CrossRefPubMed
41.
Lancaster J, Rainey L, Summerlin J, Freitas C. Automated labeling of the human brain: a preliminary report on the development and evaluation of a forward-transform method. Hum Brain Mapp. 1997;5:238–42.CrossRefPubMed
42.
Lancaster JL, Woldorff MG, Parsons LM, Liotti M, Freitas CS, Rainey L, et al. Automated Talairach atlas labels for functional brain mapping. Hum Brain Mapp. 2000;10:120–31.CrossRefPubMedPubMedCentral
43.
Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH. An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. NeuroImage. 2003;19:1233–9.CrossRefPubMed
44.
Diedrichsen J, Maderwald S, Küper M, Thürling M, Rabe K, Gizewski ER, et al. Imaging the deep cerebellar nuclei: a probabilistic atlas and normalization procedure. NeuroImage. 2011;54:1786–94.CrossRefPubMed
45.
Pagani M, Öberg J, De Carli F, Calvo A, Moglia C, Canosa A, et al. Metabolic spatial connectivity in amyotrophic lateral sclerosis as revealed by independent component analysis. Hum Brain Mapp. 2016;37:942–53.CrossRefPubMed
46.
Cauda F, Giuliano G, Federico D, Sergio D, Katiuscia S. Discovering the somatotopic organization of the motor areas of the medial wall using low-frequency bold fluctuations. Hum Brain Mapp. 2011;32:1566–79.CrossRefPubMed
47.
48.
Endo H, Sekiguchi K, Ueda T, Kowa H, Kanda F, Toda T. Regional glucose hypometabolic spread within the primary motor cortex is associated with amyotrophic lateral sclerosis disease progression: a fluoro-deoxyglucose positron emission tomography study. eNeurologicalSci. 2017;6:74–9.CrossRefPubMedPubMedCentral
49.
Verstraete E, Veldink JH, Hendrikse J, Schelhaas HJ, Van Den Heuvel MP, Van Den Berg LH. Structural MRI reveals cortical thinning in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2012;83:383–8.CrossRefPubMed
50.
Genç B, Jara JH, Lagrimas AKB, Pytel P, Roos RP, Mesulam MM, et al. Apical dendrite degeneration, a novel cellular pathology for Betz cells in ALS. Sci Rep Nature Publishing Group. 2017;7:41765.
51.
Baker MR. ALS—dying forward, backward or outward? Nat Rev Neurol. 2014;10:660–0.
52.
Chou SM, Norris FH. Amyotrophic lateral sclerosis: lower motor neuron disease spreading to upper motor neurons. Muscle Nerve. 1993;16:864–9.CrossRefPubMed
53.
Eisen A, Weber M. The motor cortex and amyotrophic lateral sclerosis. Muscle Nerve. 2001;24:564–73.CrossRefPubMed
54.
Yamanaka K, Chun SJ, Boillee S, Fujimori-Tonou N, Yamashita H, Gutmann DH, et al. Astrocytes as determinants of disease progression in inherited amyotrophic lateral sclerosis. Nat Neurosci. 2008;11:251–3.CrossRefPubMedPubMedCentral
55.
Philips T, Robberecht W. Neuroinflammation in amyotrophic lateral sclerosis: role of glial activation in motor neuron disease. Lancet Neurol Elsevier Ltd. 2011;10:253–63.CrossRef
56.
Turner MR, Cagnin A, Turkheimer FE, Miller CCJ, Shaw CE, Brooks DJ, et al. Evidence of widespread cerebral microglial activation in amyotrophic lateral sclerosis: an [11C](R)-PK11195 positron emission tomography study. Neurobiol Dis. 2004;15:601–9.CrossRefPubMed
57.
Schroeter M, Dennin MA, Walberer M, Backes H, Neumaier B, Fink GR, et al. Neuroinflammation extends brain tissue at risk to vital peri-infarct tissue: a double tracer [11C]PK11195- and [18F]FDG-PET study. J Cereb Blood Flow Metab. 2009;29:1216–25.CrossRefPubMed
58.
Turner MR, Kiernan MC. Does interneuronal dysfunction contribute to neurodegeneration in amyotrophic lateral sclerosis? Amyotroph Lateral Scler. 2012;13:245–50.CrossRefPubMed
59.
Sibson NR, Dhankhar A, Mason GF, Rothman DL, Behar KL, Shulman RG. Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity. Neurobiology. 1998;95:316–21.
60.
Schreiber H, Gaigalat T, Wiedemuth-Catrinescu U, Graf M, Uttner I, Muche R, et al. Cognitive function in bulbar- and spinal-onset amyotrophic lateral sclerosis: a longitudinal study in 52 patients. J Neurol. 2005;252:772–81.CrossRefPubMed
61.
62.
Takeuchi R, Tada M, Shiga A, Toyoshima Y, Konno T, Sato T, et al. Heterogeneity of cerebral TDP-43 pathology in sporadic amyotrophic lateral sclerosis: evidence for clinico-pathologic subtypes. Acta Neuropathol Commun Acta Neuropathologica Communications. 2016;4:61.CrossRefPubMed
63.
Nishihira Y, Tan CF, Onodera O, Toyoshima Y, Yamada M, Morita T, et al. Sporadic amyotrophic lateral sclerosis: two pathological patterns shown by analysis of distribution of TDP-43-immunoreactive neuronal and glial cytoplasmic inclusions. Acta Neuropathol. 2008;116:169–82.CrossRefPubMed
64.
Sabatelli M, Conte A, Zollino M. Clinical and genetic heterogeneity of amyotrophic lateral sclerosis. Clin Genet. 2013;83:408–16.CrossRefPubMed
65.
Willekens SMA, Van Weehaeghe D, Van Damme P, Van Laere K. Positron emission tomography in amyotrophic lateral sclerosis: towards targeting of molecular pathological hallmarks. Eur J Nucl Med Mol Imaging. 2016:1–15.
66.
Hoffman JM, Mazziotta JC, Hawk TC, Sumida R. Cerebral glucose utilization in motor neuron disease. Arch Neurol. 1992;49:849–54.CrossRefPubMed
67.
Buckner RL. The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron. 2013;80:807–15.CrossRefPubMed
68.
Mottolese C, Richard N, Harquel S, Szathmari A, Sirigu A, Desmurget M. Mapping motor representations in the human cerebellum. Brain. 2013;136:330–42.CrossRefPubMed
69.
Prell T, Grosskreutz J. The involvement of the cerebellum in amyotrophic lateral sclerosis. Amyotroph Lateral Scler Front Degener. 2013;14:507–15.CrossRef
Metadaten
Titel
Testing the diagnostic accuracy of [18F]FDG-PET in discriminating spinal- and bulbar-onset amyotrophic lateral sclerosis
verfasst von
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
Publikationsdatum
07.01.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 5/2019
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI
https://doi.org/10.1007/s00259-018-4246-2

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