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Multimodal MRI as a diagnostic biomarker for amyotrophic lateral sclerosis
Author(s) -
Foerster Bradley R.,
Carlos Ruth C.,
Dwamena Ben A.,
Callaghan Brian C.,
Petrou Myria,
Edden Richard A. E.,
Mohamed Mona A.,
Welsh Robert C.,
Barker Peter B.,
Feldman Eva L.,
Pomper Martin G.
Publication year - 2014
Publication title -
annals of clinical and translational neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.824
H-Index - 42
ISSN - 2328-9503
DOI - 10.1002/acn3.30
Subject(s) - medicine , receiver operating characteristic , amyotrophic lateral sclerosis , diffusion mri , fractional anisotropy , magnetic resonance imaging , biomarker , likelihood ratios in diagnostic testing , neuroimaging , imaging biomarker , corticospinal tract , nuclear medicine , logistic regression , radiology , disease , biochemistry , chemistry , psychiatry
Objective Reliable biomarkers for amyotrophic lateral sclerosis ( ALS ) are needed, given the clinical heterogeneity of the disease. Here, we provide proof‐of‐concept for using multimodal magnetic resonance imaging ( MRI ) as a diagnostic biomarker for ALS . Specifically, we evaluated the added diagnostic utility of proton magnetic resonance spectroscopy ( MRS ) to diffusion tensor imaging ( DTI ). Methods Twenty‐nine patients with ALS and 30 age‐ and gender‐matched healthy controls underwent brain MRI which used proton MRS including spectral editing techniques to measure γ‐aminobutyric acid ( GABA ) and DTI to measure fractional anisotropy of the corticospinal tract. Data were analyzed using logistic regression, t ‐tests, and generalized linear models with leave‐one‐out analysis to generate and compare the resulting receiver operating characteristic ( ROC ) curves. Results The diagnostic accuracy is significantly improved when the MRS data were combined with the DTI data as compared to the DTI data only (area under the ROC curves ( AUC ) = 0.93 vs. AUC  = 0.81; P  = 0.05). The combined MRS and DTI data resulted in sensitivity of 0.93, specificity of 0.85, positive likelihood ratio of 6.20, and negative likelihood ratio of 0.08 whereas the DTI data only resulted in sensitivity of 0.86, specificity of 0.70, positive likelihood ratio of 2.87, and negative likelihood ratio of 0.20. Interpretation Combining multiple advanced neuroimaging modalities significantly improves disease discrimination between ALS patients and healthy controls. These results provide an important step toward advancing a multimodal MRI approach along the diagnostic test development pathway for ALS.

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