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BioMed Research International
Volume 2015, Article ID 693206, 6 pages
http://dx.doi.org/10.1155/2015/693206
Research Article

Brain Parenchymal Fraction: A Relatively Simple MRI Measure to Clinically Distinguish ALS Phenotypes

1Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Hyderabad 500078, India
2Department of Biomedical Engineering, ND2, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
3Neuromuscular Center and Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
4Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA

Received 19 July 2015; Revised 19 November 2015; Accepted 23 November 2015

Academic Editor: Yukihisa Takayama

Copyright © 2015 Venkateswaran Rajagopalan and Erik P. Pioro. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Even though neuroimaging and clinical studies indicate that amyotrophic lateral sclerosis (ALS) manifests with distinct clinical phenotypes, no objective test exists to assess upper motor degeneration in ALS. There is great interest in identifying biomarkers of ALS to allow earlier diagnosis and to recognize disease subtypes. Current quantitative neuroimaging techniques such as T2 relaxometry and diffusion tensor imaging are time-consuming to use in clinical settings due to extensive postprocessing requirements. Therefore, we aimed to study the potential role of brain parenchymal fraction (BPF) as a relatively simple quantitative measure for distinguishing ALS phenotypes. T1-weighted MR images of brain were obtained in 15 neurological controls and 88 ALS patients categorized into 4 distinct clinical phenotypes, upper motor neuron- (UMN-) predominant ALS patients with/without corticospinal tract (CST) hyperintensity on T2/PD-weighted images, classic ALS, and ALS with frontotemporal dementia (ALS-FTD). BPF was calculated using intracranial grey matter, white matter, and cerebrospinal fluid volumes obtained in control and ALS subgroups using SPM8 software. Only ALS-FTD patients had significant reduction in BPF when compared to controls and nondemented ALS patients. Correlation of clinical measures such as disease duration with BPF further supports the view that the BPF could be a potential biomarker for clinical diagnosis of ALS-FTD patients.