Literature DB >> 24028871

Multiple Sclerosis Lesions in the Brain: Computer-Assisted Assessment of Lesion Load Dynamics on 3D FLAIR MR Images.

M Bilello1, M Arkuszewski, I Nasrallah, X Wu, G Erus, J Krejza.   

Abstract

The detection and monitoring of brain lesions caused by multiple sclerosis is commonly performed with the use of magnetic resonance imaging. Analysis of a large number of images is a time-consuming challenge to the neuroradiologist, that can be accelerated with the assistance of computer-detection software. In 98 baseline and follow-up brain magnetic resonance studies from 88 patients with a diagnosis of multiple sclerosis, we employed locally developed lesion-detection software to assess temporal change in the load of brain lesions and compared its results to routine clinical reports. Analyzing the differences between the follow-up study and the baseline study, the software displays the results in the form of a scrollable axial volume, with the changed lesions highlighted in different colors and superimposed on the baseline reference scan. Disagreements between the software and the clinical readers in the detection of changed lesions were observed only in 11 (11.2%) cases, and the difference did not reach statistical significance (p=0.07). The mean interpretation time with assistance of the software was 2.7±2.2 minutes. We conclude that the performance of the software-assisted interpretation in the analysis of change over time in multiple sclerosis brain lesions is comparable to the performance of clinical readers, with a possibly shorter assessment time. Our study demonstrates the potential of including lesion-detection software in the workflow of neuroradiology practice.

Entities:  

Year:  2012        PMID: 24028871     DOI: 10.1177/197140091202500102

Source DB:  PubMed          Journal:  Neuroradiol J        ISSN: 1971-4009


  3 in total

1.  Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

Authors:  A Galletto Pregliasco; A Collin; A Guéguen; M A Metten; J Aboab; R Deschamps; O Gout; L Duron; J C Sadik; J Savatovsky; A Lecler
Journal:  AJNR Am J Neuroradiol       Date:  2018-06-07       Impact factor: 3.825

2.  Multiple sclerosis: identification of temporal changes in brain lesions with computer-assisted detection software.

Authors:  M Bilello; M Arkuszewski; P Nucifora; I Nasrallah; E R Melhem; L Cirillo; J Krejza
Journal:  Neuroradiol J       Date:  2013-05-10

3.  Improving Multiple Sclerosis Plaque Detection Using a Semiautomated Assistive Approach.

Authors:  J van Heerden; D Rawlinson; A M Zhang; R Chakravorty; M A Tacey; P M Desmond; F Gaillard
Journal:  AJNR Am J Neuroradiol       Date:  2015-06-18       Impact factor: 3.825

  3 in total

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