PURPOSE: To study the utility of a computer-assisted method of quantitating enhancing multiple sclerosis (MS) lesions and to correlate this quantitation with the type and duration of disease. METHODS: Forty untreated patients with MS were studied. The patients had been classified clinically as having either relapsing-remitting (n = 27) or chronic-progressive (n = 13) disease. Postcontrast contiguous 3-mm-thick MR images of the brain were obtained for up to 3 years. The computer program selected potential lesion sites automatically on the basis of the theory of "fuzzy connectedness," which was incorporated into 3DVIEWNIX software. True lesions were selected from these previously detected potential lesions by means of yes/no responses to the program query. The number of enhancing lesions and the enhancing lesions volume were subsequently computed. RESULTS: The enhancing lesion volume in patients with relapsing-remitting disease was statistically significantly higher than that of patients with chronic-progressive disease. There was a strong positive correlation between the number of enhancing lesions and the enhancing lesion volume. No significant correlation was noted between the change in score on the expanded disability status scale (EDSS) and the change in the number of enhancing lesions, or between the change in EDSS score and the change in enhancing lesion volume. A negative correlation was found between enhancing lesion volume and duration of disease, and between the number of enhancing lesions and duration of disease in the patients who had enhancing lesions. CONCLUSIONS: Our data suggest that enhancing lesion volume reflects differences in the classification of clinical MS and in the disease activity over time. Computer-assisted quantitation of enhancing lesion volume is a robust, practical, and objective measure of MS activity.
PURPOSE: To study the utility of a computer-assisted method of quantitating enhancing multiple sclerosis (MS) lesions and to correlate this quantitation with the type and duration of disease. METHODS: Forty untreated patients with MS were studied. The patients had been classified clinically as having either relapsing-remitting (n = 27) or chronic-progressive (n = 13) disease. Postcontrast contiguous 3-mm-thick MR images of the brain were obtained for up to 3 years. The computer program selected potential lesion sites automatically on the basis of the theory of "fuzzy connectedness," which was incorporated into 3DVIEWNIX software. True lesions were selected from these previously detected potential lesions by means of yes/no responses to the program query. The number of enhancing lesions and the enhancing lesions volume were subsequently computed. RESULTS: The enhancing lesion volume in patients with relapsing-remitting disease was statistically significantly higher than that of patients with chronic-progressive disease. There was a strong positive correlation between the number of enhancing lesions and the enhancing lesion volume. No significant correlation was noted between the change in score on the expanded disability status scale (EDSS) and the change in the number of enhancing lesions, or between the change in EDSS score and the change in enhancing lesion volume. A negative correlation was found between enhancing lesion volume and duration of disease, and between the number of enhancing lesions and duration of disease in the patients who had enhancing lesions. CONCLUSIONS: Our data suggest that enhancing lesion volume reflects differences in the classification of clinical MS and in the disease activity over time. Computer-assisted quantitation of enhancing lesion volume is a robust, practical, and objective measure of MS activity.
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
Authors: Jason S Weinstein; Csanad G Varallyay; Edit Dosa; Seymur Gahramanov; Bronwyn Hamilton; William D Rooney; Leslie L Muldoon; Edward A Neuwelt Journal: J Cereb Blood Flow Metab Date: 2009-09-16 Impact factor: 6.200
Authors: J C Fulton; R I Grossman; J Udupa; L J Mannon; M Grossman; L Wei; M Polansky; D L Kolson Journal: AJNR Am J Neuroradiol Date: 1999 Nov-Dec Impact factor: 3.825
Authors: Minjie Wu; Caterina Rosano; Meryl Butters; Ellen Whyte; Megan Nable; Ryan Crooks; Carolyn C Meltzer; Charles F Reynolds; Howard J Aizenstein Journal: Psychiatry Res Date: 2006-11-13 Impact factor: 3.222