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J Neurol Sci. 2003 Dec 15;216(1):169-77.

Whole-brain atrophy in multiple sclerosis measured by two segmentation processes from various MRI sequences.

Author information

1
Division of Medical Physics, University of Leicester, Leicester Royal Infirmary, Leicester, LE1 5WW, UK. mah5@le.ac.uk

Abstract

Recent MRI and pathologic studies have drawn attention to the destructive nature of the multiple sclerosis (MS) disease process, including the early occurrence of axonal and neuronal loss, leading to macroscopic brain and spinal cord atrophy. Measurement of brain atrophy from MRI has emerged as a potential outcome measure and marker of disease severity in MS and neurodegenerative diseases such as Alzheimer's. However, the optimal method for quantifying atrophy has not been established, including the choice of pulse sequence and segmentation algorithm employed. Using two different MRI scanners to ensure generalizability of results, we compared the reproducibility of four pulse sequences and two analysis methods (fully automated [FA] and semi-automated [SA]) when obtaining brain parenchymal fraction (BPF), a normalized measure of whole-brain atrophy, in patients with MS (n=13) and normal controls (n=2). In order to ensure the validity of our fully automated analysis technique, we also used it to evaluate the atrophy rate over nine months in 57 MS patients from the placebo arm of a clinical trial. All pulse sequences were capable of yielding reproducibility of around 1% coefficient of variation (CoV) or better. The best reproducibility was obtained using 2D multi-slice sequences (conventional spin echo [SE] and fluid-attenuated inversion recovery [FLAIR]), with fully automated analysis. Fully automated analysis of the longitudinal data (conventional spin echo) showed an atrophy rate of -0.5% change in BPF per year, in line with previous findings from a similar cohort of patients. In conclusion, BPF measurement is affected by both pulse sequence and segmentation method. Automated measurement has high reproducibility especially when 2D sequences are used. Semi-automated measurement may have increased accuracy, but with a decreased efficiency and reliability.

PMID:
14607319
[Indexed for MEDLINE]

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