Affiliations: CNR, Radiology Department, University Federico II, via Pansini 5, I-80123 Napoli, Italy
via Manzoni 213, I-80123 Napoli, Italy
CNR, Nuclear Medicine Center, Radiology Department, University "Federico II, " via Pansini 5. I-80123 Napoli, Italy. alfanobr@unina. it
References: Rudick, R., Antel, J., Confavreux, C., Clinical outcomes assessment in multiple sclerosis (1996) Ann Neurol, 40, pp. 469-47
Miller, D.H., Grossman, R.I., Reingold, S.C., McFarland, H.F., The role of magnetic resonance techniques in understanding and managing multiple sclerosis (1998) Brain, 121, pp. 3-24
Miller, D.H., Magnetic resonance in monitoring the treatment of multiple sclerosis (1994) Ann Neurol, 36 (SUPPL.), pp. S91-S94
Filippi, M., Horsfield, M.A., Tofts, P.S., Quantitative assessment of MRI lesion load in monitoring the evolution of multiple sclerosis (1995) Brain, 118, pp. 1601-1612
Miller, D.H., Albert, P.S., Barkhof, F., Guidelines for the use of magnetic resonance techniques in monitoring the treatment of multiple sclerosis. US National MS Society Task Force (1996) Ann Neurol, 39, pp. 6-16
Filippi, M., Rovaris, M., Campi, A., Pereira, C., Comi, G., Semi-automated thresholding technique for measuring lesion volumes in multiple sclerosis: Effects of the change of the threshold on the computed lesion loads (1996) Acta Neurol Scand, 93, pp. 30-34
Rovaris, M., Rocca, M., Sormani, M., Comi, G., Filippi, M., Reproducibility of brain MRI lesion volume measurements in multiple sclerosis using a local thresholding technique: Effects of formal operator training (1999) Eur Neurol, 41, pp. 226-230
Paty, D.W., Li, D.K., Oger, J.J., Magnetic resonance imaging in the evaluation of clinical trials in multiple sclerosis (1994) Ann Neurol, 36 (SUPPL.), pp. S95-S96
Clarke, L.P., Velthuizen, R.P., Camacho, M.A., MRI segmentation: Methods and applications (1995) Magn Reson Imaging, 13, pp. 343-368
Bedell, B.J., Narayana, P.A., Wolinsky, J.S., A dual approach for minimizing false lesion classifications on magnetic resonance images (1997) Magn Reson Med, 37, pp. 94-102
Alfano, B., Brunetti, A., Covelli, E.M., Unsupervised, automated segmentation of the normal brain using a multispectral relaxomettic MR approach (1997) Magn Reson Med, 37, pp. 84-93
Jackson, E.F., Narayana, P.A., Wolinsky, J.S., Doyle, T.J., Accuracy and reproducibility in volumetric analysis of multiple sclerosis lesions (1993) J Comput Assist Tomogr, 17, pp. 200-205
Alfano, B., Larobina, M., Brunetti, A., Fully automated measurement of disease burden in multiple sclerosis with a relaxometric MR approach (1998), p. 2166. , Proceedings of the International Society for Magnetic Resonance in Medicine 6(th) Annual Meeting, SidneyAlfano, B., Brunetti, A., Arpaia, M., Multiparametric display of spin echo data from MR brain studies (1995) J Magn Reson Imaging, 5, pp. 217-225
Vinitski, S., Gonzalez, C., Mohamed, F., Improved intracranial lesion characterization by tissue segmentation based on a 3D feature map (1997) Magn Reson Med, 37, pp. 457-469
Larsson, H.B., Barker, G.J., MacKay, A., Nuclear magnetic resonance relaxation in multiple sclerosis (1998) J Neurol Neurosurg Psychiatry, 64 (SUPPL. 1), pp. S70-S76
Brunetti, A., Tedeschi, G., Di Costanzo, A., White matter lesion detection in multiple sclerosis: Improved interobserver concordance with multispectral MRI display (1997) J Neurol, 244, pp. 586-590
Filippi, M., Marciano, N., Capra, R., The effect of imprecise repositioning on lesion volume measurements in patients with multiple sclerosis (1997) Neurology, 49, pp. 274-276
Filippi, M., Van Waesberghe, J.H., Horsfield, M.A., Interscanner variation in brain MRI lesion load measurements in MS: Implications for clinical trials (1997) Neurology, 49, pp. 371-377
Guttmann, C.R., Kikinis, R., Anderson, M.C., Quantitative follow-up of patients with multiple sclerosis using MRI: Reproducibility (1999) J Magn Reson Imaging, 9, pp. 509-518
Kikinis, R., Guttmann, C.R., Metcalf, D., Quantitative follow-up of patients with multiple sclerosis using MRI: Technical aspects (1999) J Magn Reson Imaging, 9, pp. 519-530
Miller, D. H., Grossman, R. I., Reingold, S. C., McFarland, H. F., The role of magnetic resonance techniques in understanding and managing multiple sclerosis (1998) Brain, 121, pp. 3-24
Miller, D. H., Magnetic resonance in monitoring the treatment of multiple sclerosis (1994) Ann Neurol, 36 (SUPPL.), pp. S91-S94
Miller, D. H., Albert, P. S., Barkhof, F., Guidelines for the use of magnetic resonance techniques in monitoring the treatment of multiple sclerosis. US National MS Society Task Force (1996) Ann Neurol, 39, pp. 6-16
Paty, D. W., Li, D. K., Oger, J. J., Magnetic resonance imaging in the evaluation of clinical trials in multiple sclerosis (1994) Ann Neurol, 36 (SUPPL.), pp. S95-S96
Clarke, L. P., Velthuizen, R. P., Camacho, M. A., MRI segmentation: Methods and applications (1995) Magn Reson Imaging, 13, pp. 343-368
Bedell, B. J., Narayana, P. A., Wolinsky, J. S., A dual approach for minimizing false lesion classifications on magnetic resonance images (1997) Magn Reson Med, 37, pp. 94-102
Jackson, E. F., Narayana, P. A., Wolinsky, J. S., Doyle, T. J., Accuracy and reproducibility in volumetric analysis of multiple sclerosis lesions (1993) J Comput Assist Tomogr, 17, pp. 200-205
Larsson, H. B., Barker, G. J., MacKay, A., Nuclear magnetic resonance relaxation in multiple sclerosis (1998) J Neurol Neurosurg Psychiatry, 64 (SUPPL. 1), pp. S70-S76
Guttmann, C. R., Kikinis, R., Anderson, M. C., Quantitative follow-up of patients with multiple sclerosis using MRI: Reproducibility (1999) J Magn Reson Imaging, 9, pp. 509-518
Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis
A fully automated magnetic resonance (MR) segmentation method for identification and volume measurement of demyelinated white matter has been developed. Spin-echo MR brain scans were performed in 38 patients with multiple sclerosis (MS) and in 46 healthy subjects. Segmentation of normal tissues and white matter lesions (WML) was obtained, based on their relaxation rates and proton density maps. For WML identification, additional criteria included three-dimensional (3D) lesion shape and surrounding tissue composition. Segmented images were generated, and normal brain tissues and WML volumes were obtained. Sensitivity, specificity, and reproducibility of the method were calculated, using the WML identified by two neuroradiologists as the gold standard. The average volume of 'abnormal' white matter in normal subjects (false positive) was 0.11 ml (range 0-0.59 ml). In MS patients the average WML volume was 31.0 ml (range 1.1-132.5 ml), with a sensitivity of 87.3%. In the reproducibility study, the mean SD of WML volumes was 2.9 ml. The procedure appears suitable for monitoring disease changes over time. (C) 2000 Wiley-Liss, Inc.
Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis