| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Stroke. 2002;33:2827.)
© 2002 American Heart Association, Inc.
Original Contributions |
From the Department of Neurological and Psychiatric Sciences, University of Florence, Florence, Italy (L.P., M.S., G.P., D.I.); Department of Neurology, Karl-Franzens University of Graz, Graz, Austria (R.S.); and MR-MS Centre, VU Medical Centre, Amsterdam, the Netherlands (F.B.).
Correspondence to Leonardo Pantoni, MD, PhD, Department of Neurological and Psychiatric Sciences, University of Florence, Viale Morgagni 85, 50134 Firenze, Italy. E-mail pantoni{at}neuro.unifi.it
Background and Purpose It has been hypothesized that the use of different visual rating scales partly explains the discordant results of studies investigating risk factors and clinical correlates of age-related cerebral white matter changes (leukoaraiosis). We aimed to compare 6 widely used rating scales for leukoaraiosis and to calculate conversion coefficients of the score of 1 scale in the score of a second scale.
Methods Two trained raters evaluated 80 pairs of CT and MRI scans using 2 CT and 4 MRI rating scales for white matter changes. Correlations among the scales were evaluated and regression lines were constructed with each of the CT and MRI scale scores as variables.
Results A high correlation was observed in all the paired comparisons of the 6 scales (Spearmans
ranging from 0.85 to 0.96, P<0.0001). Using regression analysis, we determined numeric parameters to transform the score of 1 scale to the corresponding score for each of the remaining scales and relative confidence intervals. The predictive values of these conversions expressed as R2 ranged from 0.75 to 0.92.
Conclusions The present findings support the view that a good correlation exists among the considered visual rating scales for white matter changes. With the limitation that conversion parameters are calculated by applying a linear regression to partly nonlinear scales, their use allows comparison of the results of previous studies that used different scales and to pool data from past and ongoing clinical trials.
Key Words: leukoaraiosis magnetic resonance imaging tomography, x-ray computed white matter
This article has been cited by other articles:
![]() |
A. Jaillard, B. Naegele, S. Trabucco-Miguel, J. F. LeBas, and M. Hommel Hidden Dysfunctioning in Subacute Stroke * Supplemental Appendix Stroke, July 1, 2009; 40(7): 2473 - 2479. [Abstract] [Full Text] [PDF] |
||||
![]() |
N. Levy-Cooperman, J. Ramirez, N. J. Lobaugh, and S. E. Black Misclassified Tissue Volumes in Alzheimer Disease Patients With White Matter Hyperintensities: Importance of Lesion Segmentation Procedures for Volumetric Analysis Stroke, April 1, 2008; 39(4): 1134 - 1141. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. L.C. Vogels, W. M. van der Flier, B. van Harten, A. A. Gouw, P. Scheltens, J. M. Schroeder-Tanka, and H. C. Weinstein Brain magnetic resonance imaging abnormalities in patients with heart failure Eur J Heart Fail, October 1, 2007; 9(10): 1003 - 1009. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Schmidt, K. Petrovic, S. Ropele, C. Enzinger, and F. Fazekas Progression of Leukoaraiosis and Cognition Stroke, September 1, 2007; 38(9): 2619 - 2625. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. D. Nave, S. Foresti, A. Pratesi, A. Ginestroni, M. Inzitari, E. Salvadori, M. Giannelli, S. Diciotti, D. Inzitari, and M. Mascalchi Whole-Brain Histogram and Voxel-Based Analyses of Diffusion Tensor Imaging in Patients with Leukoaraiosis: Correlation with Motor and Cognitive Impairment AJNR Am. J. Neuroradiol., August 1, 2007; 28(7): 1313 - 1319. [Abstract] [Full Text] [PDF] |
||||
![]() |
V. Hachinski, C. Iadecola, R. C. Petersen, M. M. Breteler, D. L. Nyenhuis, S. E. Black, W. J. Powers, C. DeCarli, J. G. Merino, R. N. Kalaria, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards Stroke, September 1, 2006; 37(9): 2220 - 2241. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. C.W. van Straaten, F. Fazekas, E. Rostrup, P. Scheltens, R. Schmidt, L. Pantoni, D. Inzitari, G. Waldemar, T. Erkinjuntti, R. Mantyla, et al. Impact of White Matter Hyperintensities Scoring Method on Correlations With Clinical Data: The LADIS Study Stroke, March 1, 2006; 37(3): 836 - 840. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. D. Murray, R. T. Staff, S. D. Shenkin, I. J. Deary, J. M. Starr, and L. J. Whalley Brain White Matter Hyperintensities: Relative Importance of Vascular Risk Factors in Nondemented Elderly People Radiology, October 1, 2005; 237(1): 251 - 257. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Dufouil, J. Chalmers, O. Coskun, V. Besancon, M.-G. Bousser, P. Guillon, S. MacMahon, B. Mazoyer, B. Neal, M. Woodward, et al. Effects of Blood Pressure Lowering on Cerebral White Matter Hyperintensities in Patients With Stroke: The PROGRESS (Perindopril Protection Against Recurrent Stroke Study) Magnetic Resonance Imaging Substudy Circulation, September 13, 2005; 112(11): 1644 - 1650. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Jeerakathil, P. A. Wolf, A. Beiser, J. Massaro, S. Seshadri, R. B. D'Agostino, and C. DeCarli Stroke Risk Profile Predicts White Matter Hyperintensity Volume: The Framingham Study Stroke, August 1, 2004; 35(8): 1857 - 1861. [Abstract] [Full Text] [PDF] |
||||
|
Stroke Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2002 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |