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ADvanced IMage Algebra (ADIMA): a novel method for depicting multiple sclerosis lesion heterogeneity, as demonstrated by quantitative MRI.
- Source :
-
Multiple sclerosis (Houndmills, Basingstoke, England) [Mult Scler] 2013 May; Vol. 19 (6), pp. 732-41. Date of Electronic Publication: 2012 Oct 04. - Publication Year :
- 2013
-
Abstract
- Background: There are modest correlations between multiple sclerosis (MS) disability and white matter lesion (WML) volumes, as measured by T2-weighted (T2w) magnetic resonance imaging (MRI) scans (T2-WML). This may partly reflect pathological heterogeneity in WMLs, which is not apparent on T2w scans.<br />Objective: To determine if ADvanced IMage Algebra (ADIMA), a novel MRI post-processing method, can reveal WML heterogeneity from proton-density weighted (PDw) and T2w images.<br />Methods: We obtained conventional PDw and T2w images from 10 patients with relapsing-remitting MS (RRMS) and ADIMA images were calculated from these. We classified all WML into bright (ADIMA-b) and dark (ADIMA-d) sub-regions, which were segmented. We obtained conventional T2-WML and T1-WML volumes for comparison, as well as the following quantitative magnetic resonance parameters: magnetisation transfer ratio (MTR), T1 and T2. Also, we assessed the reproducibility of the segmentation for ADIMA-b, ADIMA-d and T2-WML.<br />Results: Our study's ADIMA-derived volumes correlated with conventional lesion volumes (p < 0.05). ADIMA-b exhibited higher T1 and T2, and lower MTR than the T2-WML (p < 0.001). Despite the similarity in T1 values between ADIMA-b and T1-WML, these regions were only partly overlapping with each other. ADIMA-d exhibited quantitative characteristics similar to T2-WML; however, they were only partly overlapping. Mean intra- and inter-observer coefficients of variation for ADIMA-b, ADIMA-d and T2-WML volumes were all < 6 % and < 10 %, respectively.<br />Conclusion: ADIMA enabled the simple classification of WML into two groups having different quantitative magnetic resonance properties, which can be reproducibly distinguished.
- Subjects :
- Female
Humans
Male
Middle Aged
Multiple Sclerosis, Relapsing-Remitting classification
Multiple Sclerosis, Relapsing-Remitting pathology
Observer Variation
Predictive Value of Tests
Reproducibility of Results
Algorithms
Image Processing, Computer-Assisted methods
Magnetic Resonance Imaging
Multiple Sclerosis, Relapsing-Remitting diagnosis
White Matter pathology
Subjects
Details
- Language :
- English
- ISSN :
- 1477-0970
- Volume :
- 19
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Multiple sclerosis (Houndmills, Basingstoke, England)
- Publication Type :
- Academic Journal
- Accession number :
- 23037551
- Full Text :
- https://doi.org/10.1177/1352458512462074