Estimating Brain Lesion Volume Change in Multiple Sclerosis by Subtraction of Magnetic Resonance Images

Mark A. Horsfield, Maria A. Rocca, Elisabetta Pagani, Loredana Storelli, Paolo Preziosa, Roberta Messina, Fabiano Camesasca, Massimiliano Copetti, Massimo Filippi

Research output: Contribution to journalArticle

Abstract

BACKGROUND: Change in lesion volume over time, measured on brain magnetic resonance imaging (MRI) scans, is an important outcome measure for natural history studies and clinical trials in multiple sclerosis (MS). PURPOSE: To develop and test image analysis methods for quantification of lesion volume change in order to improve reliability. METHODS: The technique is based on registration and subtraction, and was evaluated in a cohort of 20 MS patients with dual-echo images acquired annually over a period of four years. The study protocol was approved by the local ethics review boards of participating centers, and all subjects gave written informed consent. The repeatability was compared to that obtained by the standard method for obtaining lesion volume change by evaluating the total volume at each time point, and then subtracting the volumes to obtain the difference. RESULTS: Compared to the standard method, the subtraction method had improved intrarater correlation (0.95 and 0.72 for the subtraction method and the standard method, respectively) and interrater correlation (0.51 and 0.28, respectively). Furthermore, the mean time required to analyze the scans from one patient was 41 minutes for the subtraction method compared to 125 minutes for the standard method. CONCLUSION: Use of the subtraction algorithm leads to improved reliability and lower operator fatigue in clinical trials and studies of the natural history of MS.

Original languageEnglish
Pages (from-to)395-402
Number of pages8
JournalJournal of Neuroimaging
Volume26
Issue number4
DOIs
Publication statusPublished - Jul 1 2016

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Keywords

  • Lesion volume
  • longitudinal
  • MRI
  • multiple sclerosis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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