Literature DB >> 9022787

A new computer-assisted method for the quantification of enhancing lesions in multiple sclerosis.

S Samarasekera1, J K Udupa, Y Miki, L Wei, R I Grossman.   

Abstract

PURPOSE: Our goal is to describe a new computerized method for the detection and quantification of enhanced multiple sclerosis (MS) lesions.
METHOD: Gd-DTPA-enhanced, thin section, T1-weighted images of seven patients (involving 336 slice images) with definite MS were analyzed using a new method based on the theory of "fuzzy connected components," developed and implemented on the 3DVIEWNIX software system. Four neuroradiologists selected "true" lesions from the computer-detected potential lesions with a yes/no response to the program query on 2 different days. The enhanced lesion volume and number of enhancing lesions for each image and each observer were subsequently computed. Additional studies involving 720 slices were conducted to determine lesions that were missed by the system.
RESULTS: The intra- and interobserver variability in the system was 0%. It took approximately 1 min of operator time per 3D study. The system output has no false positives and a mean false-negative volume of 1.3%.
CONCLUSION: The novel system calculates enhancing lesion volume and the number of enhancing lesions with very little operator time, inter- and intraoperator variability, or false-positive and false-negative volumes. Computer-based quantification of enhancing lesion volume is an important objective measure of the activity of MS. The system is now in routine use in clinical investigations that study the role of enhancing lesions in the MS disease.

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Year:  1997        PMID: 9022787     DOI: 10.1097/00004728-199701000-00028

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  4 in total

1.  Supervised automatic procedure to identify new lesions in brain MR longitudinal studies of patients with multiple sclerosis.

Authors:  R C Parodi; F Levrero; M P Sormani; A Pilot; G L Mancardi; A Aliprandi; F Sardanelli
Journal:  Radiol Med       Date:  2008-04-02       Impact factor: 3.469

2.  Whole-brain N-acetylaspartate concentration: correlation with T2-weighted lesion volume and expanded disability status scale score in cases of relapsing-remitting multiple sclerosis.

Authors:  Fabrice Bonneville; David M Moriarty; Belinda S Y Li; James S Babb; Robert I Grossman; Oded Gonen
Journal:  AJNR Am J Neuroradiol       Date:  2002-03       Impact factor: 3.825

3.  Magnetization transfer histogram analysis of monosymptomatic episodes of neurologic dysfunction: preliminary findings.

Authors:  J S Kaiser; R I Grossman; M Polansky; J K Udupa; Y Miki; S L Galetta
Journal:  AJNR Am J Neuroradiol       Date:  2000 Jun-Jul       Impact factor: 3.825

4.  Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis.

Authors:  Ivan Coronado; Refaat E Gabr; Ponnada A Narayana
Journal:  Mult Scler       Date:  2020-05-22       Impact factor: 6.312

  4 in total

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