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27.04.2023 | Original Communication

Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis

verfasst von: M. Khamaysa, M. Lefort, M. Pélégrini-Issac, A. Lackmy-Vallée, A. Preuilh, D. Devos, A.-S. Rolland, C. Desnuelle, M. Chupin, V. Marchand-Pauvert, G. Querin, Pierre-François Pradat, the Pulse study group

Erschienen in: Journal of Neurology | Ausgabe 8/2023

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Abstract

Background

Motor capacity is crucial in amyotrophic lateral sclerosis (ALS) clinical trial design and patient care. However, few studies have explored the potential of multimodal MRI to predict motor capacity in ALS. This study aims to evaluate the predictive value of cervical spinal cord MRI parameters for motor capacity in ALS compared to clinical prognostic factors.

Methods

Spinal multimodal MRI was performed shortly after diagnosis in 41 ALS patients and 12 healthy participants as part of a prospective multicenter cohort study, the PULSE study (NCT 2013-A00969-36). Motor capacity was assessed using ALSFRS-R scores. Multiple stepwise linear regression models were constructed to predict motor capacity at 3 and 6 months from diagnosis, based on clinical variables, structural MRI measurements, including spinal cord cross-sectional area (CSA), anterior–posterior, and left-to-right cross-section diameters at vertebral levels from C1 to T4, and diffusion parameters in the lateral corticospinal tracts (LCSTs) and dorsal columns.

Results

Structural MRI measurements were significantly correlated with the ALSFRS-R score and its sub-scores. And as early as 3 months from diagnosis, structural MRI measurements fit the best multiple linear regression model to predict the total ALSFRS-R (R² = 0.70, p value = 0.0001) and arm sub-score (R² = 0.69, p value = 0.0002), and combined with DTI metric in the LCST and clinical factors fit the best multiple linear regression model to predict leg sub-score (R² = 0.73, p value = 0.0002).

Conclusions

Spinal multimodal MRI could be promising as a tool to enhance prognostic accuracy and serve as a motor function proxy in ALS.

Robberecht W, Philips T (2013) The changing scene of amyotrophic lateral sclerosis. Nat Rev Neurosci 14:248–264. https://doi.org/10.1038/nrn3430CrossRefPubMed

Rowland LP, Shneider NA (2001) Amyotrophic lateral sclerosis. N Engl J Med 344:1688–1700. https://doi.org/10.1056/nejm200105313442207CrossRefPubMed

Turner MR, Bowser R, Bruijn L, Dupuis L, Ludolph A, McGrath M, Manfredi G, Maragakis N, Miller RG, Pullman SL, Rutkove SB, Shaw PJ, Shefner J, Fischbeck KH (2013) Mechanisms, models and biomarkers in amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener 14:19–32. https://doi.org/10.3109/21678421.2013.778554CrossRefPubMedPubMedCentral

Turner MR, Benatar M (2015) Ensuring continued progress in biomarkers for amyotrophic lateral sclerosis. Muscle Nerve 51:14–18. https://doi.org/10.1002/mus.24470CrossRefPubMed

Ravits J, Paul P, Jorg C (2007) Focality of upper and lower motor neuron degeneration at the clinical onset of ALS. Neurology 68:1571–1575. https://doi.org/10.1212/01.wnl.0000260965.20021.47CrossRefPubMed

Gordon PH, Cheng B, Katz IB, Pinto M, Hays AP, Mitsumoto H, Rowland LP (2006) The natural history of primary lateral sclerosis. Neurology 66:647–653. https://doi.org/10.1212/01.wnl.0000200962.94777.71CrossRefPubMed

Kraemer M, Buerger M, Berlit P (2010) Diagnostic problems and delay of diagnosis in amyotrophic lateral sclerosis. Clin Neurol Neurosurg 112:103–105. https://doi.org/10.1016/j.clineuro.2009.10.014CrossRefPubMed

Witzel S, Frauhammer F, Steinacker P, Devos D, Pradat PF, Meininger V, Halbgebauer S, Oeckl P, Schuster J, Anders S, Dorst J, Otto M, Ludolph AC (2021) Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials. Transl Neurodegener 10:31. https://doi.org/10.1186/s40035-021-00257-yCrossRefPubMedPubMedCentral

Cai Z, Liu Q, Liu M, Yang X, Shen D, Sun X, He D, Zhang K, Shang L, Zhang X, Cui L (2022) Survival analysis of clinical and genetic factors in an amyotrophic lateral sclerosis cohort from China. Neurol Res 44:651–658. https://doi.org/10.1080/01616412.2022.2029292CrossRefPubMed

10.

Westeneng HJ, Debray TPA, Visser AE, van Eijk RPA, Rooney JPK, Calvo A, Martin S, McDermott CJ, Thompson AG, Pinto S, Kobeleva X, Rosenbohm A, Stubendorff B, Sommer H, Middelkoop BM, Dekker AM, van Vugt J, van Rheenen W, Vajda A, Heverin M, Kazoka M, Hollinger H, Gromicho M, Körner S, Ringer TM, Rödiger A, Gunkel A, Shaw CE, Bredenoord AL, van Es MA, Corcia P, Couratier P, Weber M, Grosskreutz J, Ludolph AC, Petri S, de Carvalho M, Van Damme P, Talbot K, Turner MR, Shaw PJ, Al-Chalabi A, Chiò A, Hardiman O, Moons KGM, Veldink JH, van den Berg LH (2018) Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model. Lancet Neurol 17:423–433. https://doi.org/10.1016/s1474-4422(18)30089-9CrossRefPubMed

11.

Trojsi F, Siciliano M, Femiano C, Santangelo G, Lunetta C, Calvo A, Moglia C, Marinou K, Ticozzi N, Ferro C, Scialò C, Sorarù G, Conte A, Falzone YM, Tortelli R, Russo M, Sansone VA, Chiò A, Mora G, Silani V, Volanti P, Caponnetto C, Querin G, Sabatelli M, Riva N, Logroscino G, Messina S, Fasano A, Monsurrò MR, Tedeschi G, Mandrioli J (2019) Comparative analysis of C9orf72 and sporadic disease in a large multicenter ALS population: the effect of male sex on survival of C9orf72 positive patients. Front Neurosci. https://doi.org/10.3389/fnins.2019.00485CrossRefPubMedPubMedCentral

12.

Ahmed RM, Devenney EM, Strikwerda-Brown C, Hodges JR, Piguet O, Kiernan MC (2020) Phenotypic variability in ALS-FTD and effect on survival. Neurology 94:e2005–e2013. https://doi.org/10.1212/wnl.0000000000009398CrossRefPubMed

13.

Zhou YN, Chen YH, Dong SQ, Yang WB, Qian T, Liu XN, Cheng Q, Wang JC, Chen XJ (2021) Role of blood neurofilaments in the prognosis of amyotrophic lateral sclerosis: a meta-analysis. Front Neurol. https://doi.org/10.3389/fneur.2021.712245CrossRefPubMedPubMedCentral

14.

El Mendili MM, Cohen-Adad J, Pelegrini-Issac M, Rossignol S, Morizot-Koutlidis R, Marchand-Pauvert V, Iglesias C, Sangari S, Katz R, Lehericy S, Benali H, Pradat PF (2014) Multi-parametric spinal cord MRI as potential progression marker in amyotrophic lateral sclerosis. PLoS ONE 9:e95516. https://doi.org/10.1371/journal.pone.0095516CrossRefPubMedPubMedCentral

15.

European Medicines Agency. Guideline on clinical investigation of medicinal products for the treatment of amyotrophic lateral sclerosis 2016 [Available from: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-clinical-investigation-medicinal-products-treatment-amyotrophic-lateral-sclerosis_en.pdf. Accessed 06 Oct 2022.

16.

U.S. Food and Drug Administration. Guidance for industry: amyotrophic lateral sclerosis: developing drugs for treatment 2019 [Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/amyotrophic-lateral-sclerosis-developing-drugs-treatment-guidance-industry.

17.

Steering committee members of The ALS CNTF Treatment Study Phase I-II Study Group (1996) The Amyotrophic Lateral Sclerosis Functional Rating Scale. Assessment of activities of daily living in patients with amyotrophic lateral sclerosis. The ALS CNTF treatment study (ACTS) phase I-II Study Group. Arch Neurol 53:141–147. https://doi.org/10.1001/archneur.1996.00550020045014CrossRef

18.

van Eijk R, Kliest T, van den Berg L (2020) Current trends in the clinical trial landscape for amyotrophic lateral sclerosis. Curr Opin Neurol 33:655–661. https://doi.org/10.1097/WCO.0000000000000861CrossRefPubMed

19.

Kiernan MC, Vucic S, Cheah BC, Turner MR, Eisen A, Hardiman O, Burrell JR, Zoing MC (2011) Amyotrophic lateral sclerosis. Lancet 377:942–955. https://doi.org/10.1016/s0140-6736(10)61156-7CrossRefPubMed

20.

El Mendili MM, Querin G, Bede P, Pradat P-F (2019) Spinal cord imaging in amyotrophic lateral sclerosis: historical concepts—novel techniques. Front Neurol 10:350. https://doi.org/10.3389/fneur.2019.00350CrossRefPubMedPubMedCentral

21.

Cohen-Adad J, El Mendili MM, Morizot-Koutlidis R, Lehéricy S, Meininger V, Blancho S, Rossignol S, Benali H, Pradat PF (2013) Involvement of spinal sensory pathway in ALS and specificity of cord atrophy to lower motor neuron degeneration. Amyotroph Lateral Scler Frontotemporal Degener 14:30–38. https://doi.org/10.3109/17482968.2012.701308CrossRefPubMed

22.

Branco LM, De Albuquerque M, De Andrade HM, Bergo FP, Nucci A, França MC Jr (2014) Spinal cord atrophy correlates with disease duration and severity in amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener 15:93–97. https://doi.org/10.3109/21678421.2013.852589CrossRefPubMed

23.

Nair G, Carew JD, Usher S, Lu D, Hu XP, Benatar M (2010) Diffusion tensor imaging reveals regional differences in the cervical spinal cord in amyotrophic lateral sclerosis. Neuroimage 53:576–583. https://doi.org/10.1016/j.neuroimage.2010.06.060CrossRefPubMed

24.

Querin G, El Mendili MM, Lenglet T, Delphine S, Marchand-Pauvert V, Benali H, Pradat PF (2017) Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis. Eur J Neurol 24:1040–1046. https://doi.org/10.1111/ene.13329CrossRefPubMed

25.

Grolez G, Kyheng M, Lopes R, Moreau C, Timmerman K, Auger F, Kuchcinski G, Duhamel A, Jissendi-Tchofo P, Besson P, Laloux C, Petrault M, Devedjian JC, Pérez T, Pradat PF, Defebvre L, Bordet R, Danel-Brunaud V, Devos D (2018) MRI of the cervical spinal cord predicts respiratory dysfunction in ALS. Sci Rep 8:1828. https://doi.org/10.1038/s41598-018-19938-2CrossRefPubMedPubMedCentral

26.

Querin G, El Mendili MM, Bede P, Delphine S, Lenglet T, Marchand-Pauvert V, Pradat PF (2018) Multimodal spinal cord MRI offers accurate diagnostic classification in ALS. J Neurol Neurosurg Psychiatry 89:1220–1221. https://doi.org/10.1136/jnnp-2017-317214CrossRefPubMed

27.

Brooks BR, Miller RG, Swash M, Munsat TL (2000) El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord 1:293–299. https://doi.org/10.1080/146608200300079536CrossRefPubMed

28.

Cedarbaum JM, Stambler N, Malta E, Fuller C, Hilt D, Thurmond B, Nakanishi A (1999) The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function. BDNF ALS Study Group (Phase III). J Neurol Sci 169:13–21. https://doi.org/10.1016/s0022-510x(99)00210-5CrossRefPubMed

29.

Gros C, De Leener B, Dupont SM, Martin AR, Fehlings MG, Bakshi R, Tummala S, Auclair V, McLaren DG, Callot V, Cohen-Adad J, Sdika M (2018) Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Med Image Anal 44:215–227. https://doi.org/10.1016/j.media.2017.12.001CrossRefPubMed

30.

Fonov VS, Le Troter A, Taso M, De Leener B, Lévêque G, Benhamou M, Sdika M, Benali H, Pradat PF, Collins DL, Callot V, Cohen-Adad J (2014) Framework for integrated MRI average of the spinal cord white and gray matter: the MNI-Poly-AMU template. Neuroimage 102:2817–2827. https://doi.org/10.1016/j.neuroimage.2014.08.057CrossRef

31.

Lévy S, Benhamou M, Naaman C, Rainville P, Callot V, Cohen-Adad J (2015) White matter atlas of the human spinal cord with estimation of partial volume effect. Neuroimage 119:262–271. https://doi.org/10.1016/j.neuroimage.2015.06.040CrossRefPubMed

32.

Jiao Y, Lin F, Wu J, Li H, Wang L, Jin Z, Wang S, Cao Y (2018) A supplementary grading scale combining lesion-to-eloquence distance for predicting surgical outcomes of patients with brain arteriovenous malformations. J Neurosurg 128:530–540. https://doi.org/10.3171/2016.10.Jns161415CrossRefPubMed

33.

Sabatelli M, Madia F, Conte A, Luigetti M, Zollino M, Mancuso I, Lo Monaco M, Lippi G, Tonali P (2008) Natural history of young-adult amyotrophic lateral sclerosis. Neurology 71:876–881. https://doi.org/10.1212/01.wnl.0000312378.94737.45CrossRefPubMed

34.

Chen L, Zhang B, Chen R, Tang L, Liu R, Yang Y, Yang Y, Liu X, Ye S, Zhan S, Fan D (2015) Natural history and clinical features of sporadic amyotrophic lateral sclerosis in China. J Neurol Neurosurg Psychiatry 86:1075–1081. https://doi.org/10.1136/jnnp-2015-310471CrossRefPubMed

35.

Paquin M, El Mendili MM, Gros C, Dupont SM, Cohen-Adad J, Pradat PF (2018) Spinal cord gray matter atrophy in amyotrophic lateral sclerosis. AJNR Am J Neuroradiol 39:184–192. https://doi.org/10.3174/ajnr.A5427CrossRefPubMedPubMedCentral

36.

Barry RL, Torrado-Carvajal A, Kirsch JE, Arabasz GE, Albrecht DS, Alshelh Z, Pijanowski O, Lewis AJ, Keegan M, Reynolds B, Knight PC, Morrissey EJ, Loggia ML, Atassi N, Hooker JM, Babu S (2022) Selective atrophy of the cervical enlargement in whole spinal cord MRI of amyotrophic lateral sclerosis. NeuroImage Clin 36:103199. https://doi.org/10.1016/j.nicl.2022.103199CrossRefPubMedPubMedCentral

37.

Bede P, Hardiman O (2014) Lessons of ALS imaging: Pitfalls and future directions—a critical review. NeuroImage Clin 4:436–443. https://doi.org/10.1016/j.nicl.2014.02.011CrossRefPubMedPubMedCentral

38.

Cao B, Wei Q, Ou R, Zhang L, Hou Y, Chen Y, Shang H (2019) Neurophysiological index is associated with the survival of patients with amyotrophic lateral sclerosis. Clin Neurophysiol 130:1730–1733. https://doi.org/10.1016/j.clinph.2019.05.012CrossRefPubMed

Titel: Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis
verfasst von: M. Khamaysa
M. Lefort
M. Pélégrini-Issac
A. Lackmy-Vallée
A. Preuilh
D. Devos
A.-S. Rolland
C. Desnuelle
M. Chupin
V. Marchand-Pauvert
G. Querin
Pierre-François Pradat
the Pulse study group
Publikationsdatum: 27.04.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Neurology / Ausgabe 8/2023
Print ISSN: 0340-5354
Elektronische ISSN: 1432-1459
DOI: https://doi.org/10.1007/s00415-023-11727-w

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