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Neuroradiology |
1 From the Departments of Radiology (Y.G., R.I.G., J.K.U., L.W., L.J.M.) and Neurology (D.L.K.), Hospital of the University of Pennsylvania, Founders, 3400 Spruce St, Philadelphia, PA 19104-4283; and the Division of Biometrics, School of Public Health, Hahnemann University (M.P.). Received April 19, 1999; revision requested May 5; revision received June 25; accepted August 2. Supported in part by National Institutes of Health grants RO1 NS29029 and NS37172. Address reprint requests to R.I.G. (e-mail: grossman@oasis.rad.upenn.edu).
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Abstract |
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MATERIALS AND METHODS: A computer-assisted segmentation technique with thin-section magnetic resonance (MR) imaging was used in 36 patients with MS (27 relapsing-remitting, nine secondary progressive) and in 20 control subjects to quantify brain and cerebrospinal fluid volumes. To determine the degree of brain atrophy, the percentage brain parenchyma volume (PBV) relative to that of intracranial contents was calculated.
RESULTS: At the beginning of the study, the PBV was smaller in the MS group than in the control group (P = .007); brain parenchyma volumes were similar. The median rate of brain volume loss was 17.3 mL per year in patients with relapsing-remitting MS and 23.6 mL per year in those with secondary progressive MS. There was a negative correlation between brain atrophy and Expanded Disability Status Scale (EDSS) score in patients with secondary progressive MS (r = -0.69, P = .004) and no correlation in patients with relapsing-remitting MS. T2 lesion volume did not correlate with brain atrophy in either group.
CONCLUSION: The correlation between brain atrophy and EDSS score was better in patients with secondary progressive MS than in those with relapsing-remitting MS.
Index terms: Brain, abnormalities, 13.83, 13.871 • Brain, MR, 13.121411, 13.121416 • Magnetic resonance (MR), volume measurement, 13.121411, 13.12146 • Sclerosis, multiple, 13.871
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Introduction |
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TOPAbstractIntroductionMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Generalized brain atrophy in MS has been reported in early neurologic imaging studies. The atrophy manifested as enlarged ventricles, increased sulcal cerebrospinal fluid (CSF) space (16–18), and atrophy of the corpus callosum (19,20). Most of these studies relied on a subjective assessment of atrophy with visual identification; thus, their reliability may be limited. To accurately assess the effects of brain atrophy in patients with MS, serial quantitative volumetric measurements in the same individual are required (21). Advances in computer-assisted segmentation techniques (22,23) provide an opportunity to quantitatively investigate brain atrophy on the basis of thin-section MR imaging with high reproducibility. To our knowledge, brain atrophy and clinical disability in patients with MS have been longitudinally evaluated in few studies (21).
In this study, we used a semiautomated whole-brain segmentation software program based on thin-section fast spin-echo imaging with two echo times to determine the annual rates of volumetric change in the brain parenchyma of patients with relapsing-remitting and secondary progressive MS and to test whether these changes correlate with clinical disability, T2 lesion volume, and disease duration.
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MATERIALS AND METHODS |
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TOPAbstractIntroductionMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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MR Imaging
MR imaging was performed with a 1.5-T unit (Signa; GE Medical Systems, Milwaukee, Wis) by using a quadrature transmit/receive head coil. All MR examinations were performed by using whole-brain transverse fast spin-echo T2-weighted imaging with 2,500/18 and 90 (repetition time msec/echo time msec [effective]), 3-mm-thick sections (contiguous, interleaved), a 22-cm field of view, a 256 x 192 matrix, more than 50 sections, an echo train length of eight, and a 0.86-mm pixel size. Patients underwent imaging every 6 months, and the total number of MR examinations performed was 189. The first (intermediate-weighted) and second (T2-weighted) echoes of the fast spin-echo sequence in each study were then transferred electronically to our medical image processing laboratory, where the T2 lesion volume, brain parenchyma volume, and CSF volume were calculated.
Image Processing
MR imaging data were transferred directly to the computer systems of the medical image processing group by means of a picture archiving and communication system. The images were processed by using an internal version of the 3DVIEWNIX (24) software system that was developed, maintained, and distributed by the Medical Image Processing Group of the University of Pennsylvania. All processing operations used to obtain the results reported herein were performed with a Sun Sparc 20 workstation (Sun Microsystems, Mountain View, Calif) by one neuroradiologist (Y.G.). Lesion volume calculations were performed with a validated semiautomatic computerized method based on the concept of "fuzzy connectedness" by using two (intermediate- and T2-weighted) image sets. This method has been described previously (22,23) and validated in several studies (25–28) and with more than 500 data sets. The known interobserver and intraobserver variability for this method has been found to be less than 1% for total lesion volume (28).
Parenchyma and CSF volumes also were determined with the 3DVIEWNIX system. The process began with the segmentation of the intracranial contents (28) after an operator briefly identified the gray matter, white matter, and CSF by specifying a few points in one section that was approximately centrally situated in the brain. All of the segmented sections (more than 50 in each study) were then reviewed, and any residual extracranial components were excluded, if needed, by the operator. This is the only processing step that requires manual interaction with each patient.
The CSF-only image was obtained with the whole-brain segmentation technique by using segmented T2- and intermediate-weighted data sets. With this method, which has been described by Udupa et al (22,23,28), an "angle image" of CSF was created by using the following equation: Iangle = tan-1(IT2/IINT), where Iangle, IT2, IINT are the signal intensities of the voxels on the angle, T2-weighted, and intermediate-weighted images, respectively. The power of the angle image comes from the effective elimination of the wide variation in CSF signal intensities that are commonly seen on T2- and intermediate-weighted images owing to inhomogeneity in the magnetic field. The resulting angle image has relatively homogeneous CSF signal intensity values that can be effectively segmented with thresholding. The threshold value was selected by using the T2-weighted images as a guide to produce a CSF-only image, which accurately depicted the CSF volume. Because of some sort of "normalization" achieved on the angle images, it was possible to fix this threshold without requiring a per-study adjustment. The CSF volume was calculated by summing the total volume of the voxels on the CSF-only image.
The brain parenchyma image (Fig 1a, 1b) was generated and the volume was calculated by subtracting the CSF-only image (Fig 1c, 1d) and volume data from the intracranial contents (ie, brain parenchyma plus CSF) after segmentation. To normalize for baseline differences in brain parenchyma volume among patients and control subjects, an additional parameter, the percentage brain parenchyma volume (PBV), was calculated as the percentage of brain volume within the volume of the intracranial contents. To determine the reproducibility of the various volume estimations, we performed repeated MR imaging within 1 week after the previous imaging examination in 10 randomly chosen patients. The previously described parameters were used to obtain the repeat images. For the whole-brain parenchyma volume calculation, we included those sections from the MR image sets that started from the section just before the cerebellum appears in the bottom and extended to the last section at the top of the brain.
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RESULTS |
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TOPAbstractIntroductionMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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To determine the relationship between PBV and EDSS, disease duration, and T2 lesion volume, longitudinal analysis was performed on a patient-by-patient basis by using the Pearson correlation coefficient test (Table 3). We found a negative correlation between PBV and EDSS score in patients with secondary progressive MS (Fig 2a) (r = -0.69, P = .004). There was, however, no correlation between PBV and EDSS score in patients with relapsing-remitting MS. Marked atrophy (-8.3%) was seen in one patient with relapsing-remitting MS who had a small change in EDSS score (from 2.0 to 2.5) during the 4-year follow-up period (Fig 1). A negative median correlation was also found between PBV and disease duration (r = -0.60, P = .001 for patients with relapsing-remitting MS; r = -0.86, P = .004 for patients with secondary progressive MS). No correlation was seen between PBV and lesion volume in either the patients with relapsing-remitting MS or those with secondary progressive MS (Fig 2b).
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DISCUSSION |
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TOPAbstractIntroductionMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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The PBV was significantly smaller in the patients with MS at entry (median disease duration, 3.3 years) than in the age-matched healthy control subjects at entry, although there was no statistically significant difference in brain volume (P = .139). This indicates that the correction for variation in brain size is necessary for volumetric quantification among subjects. We used the PBV to normalize the variation in brain size and to represent the degree of brain atrophy. We found a mean PBV of 88.2% in the control subjects and of 85.5% in the patients with MS (P = .007). The significant negative correlation (r = -0.79) between brain and CSF volume in patients is suggestive of a decrease in brain tissue and an increase in CSF volume over time.
The median rate of brain volume loss in our patients was 18.4 mL (-1.6%) per year. It is difficult to directly compare our results with those of Losseff et al (15), who reported a volume loss of 3.4 mL per year on the basis of their analysis of four 5-mm-thick sections. The median annual rate of brain volume loss in our study was 17.3 mL in patients with relapsing-remitting MS and 23.6 mL in those with secondary progressive MS (P = .2). In addition, the baseline information indicated a trend toward small PBV in patients with secondary progressive MS. The finding that patients with secondary progressive MS had more severe atrophy and higher EDSS scores at baseline than did the patients with relapsing-remitting MS is consistent with the findings of Losseff et al (15). This finding is also consistent with the increased number of low-signal-intensity lesions on the T1-weighted images; these lesions are more likely to represent axonal loss (29) and severe EDSS scores (30,31) in the patients with secondary progressive MS (32) than in those with relapsing-remitting MS. Although we did not have longitudinal data for the control subjects, the median rate of brain atrophy in MS (18.4 mL per year) appears to be greater than that seen with normal aging (0.7–2.0 mL per year) (33,34) and less than that with Alzheimer disease (40.0 mL per year) (34). Quantitative volumetric analysis of brain parenchyma may ultimately be helpful in understanding the mechanisms of brain tissue loss in patients with MS and the ability of immunomodulating drugs to modulate such tissue loss.
We found a correlation between brain atrophy and EDSS score in patients with secondary progressive MS (r = -0.69) but no such correlation in those with relapsing-remitting MS (r = 0.05). This differs with the findings of Losseff et al (15), who described a strong correlation between brain atrophy and EDSS score. There may be several reasons for this discrepancy. First, Losseff et al did not distinguish between patients with relapsing-remitting MS and those with secondary progressive MS. They selected two groups according to the EDSS score and did the correlation indirectly, by comparing groups with different EDSS scores. Second, our measurements of brain volume were performed on the whole brain rather than on four separate sections. Moreover, we looked at the PBV rather than the brain parenchyma volume itself, in which there was no significant difference between patients with MS and control subjects at cross-sectional analysis. Finally, the segmentation technique Losseff et al used was based on gadolinium-enhanced T1-weighted imaging with 5-mm-thick sections, whereas we used fast spin-echo imaging with two echo times and 3-mm-thick sections, which considerably minimizes blurring effects and the partial volume from sulcal CSF with gray matter (35), as reflected by the high precision we were able to achieve.
Although it is clear that axonal loss occurs in the brain in MS and is considered to be responsible for neurologic impairment (36), the direct and causal relationship between progressive axonal loss and progressive brain tissue loss is still poorly understood. One likely consequence of axonal damage is neuronal dropout (37), which may contribute to gray matter volume loss with a resultant decrease in N-acetylaspartate, a neuronal marker (38). There is no definitive data regarding which components—gray matter and/or white matter—are involved in brain atrophy in MS and to what degree. Our data suggest that loss of brain tissue occurs earlier in patients with relapsing-remitting MS but does not correlate with clinical disease progression. It is known that most patients with relapsing-remitting MS experience a clinical course characterized by recurring exacerbations of neurologic symptoms (39). Despite the progressive decrease in brain volume (Fig 1) in patients with relapsing-remitting MS, there is no correlation between PBV and clinical disability, as measured with the EDSS score. In the secondary progressive phase of MS, however, patients may experience a gradual progression of disability, which was shown in our study to have a stronger correlation with progressive brain atrophy compared with that in patients with relapsing-remitting MS.
The poor correlation between brain atrophy and lesion volume at MR imaging in patients with relapsing-remitting MS (r = -0.12) and in those with secondary progressive MS (r = .002) at longitudinal analysis was consistent with the findings of Losseff et al (15). T2 lesion volume (ie, total lesion load) is believed to represent only the component of MS lesions that are visible at MR imaging (26). In addition, it represents a heterogeneous pathologic substrate that includes edema, inflammation, demyelination, and gliosis, whereas brain atrophy is believed to be more specific and to represent the loss of neuronal cell bodies and axons (neuronal degeneration). The more significant development of brain atrophy (-2% per year) than of T2 lesion volume (-0.03% per year) in patients with secondary progressive MS, however, suggests that the T2 lesion load may not reflect the amount of brain tissue loss and that such tissue (presumably neurons) has a greater effect on disability measures and disease progression.
In conclusion, we quantitated the rate of development of whole-brain atrophy in patients with a natural course of MS by using a highly reproducible computer method that requires a minimized degree of operator help. A statistically significant yearly decline in brain parenchyma volume was identified in the patients with MS, and brain parenchyma volume correlated better with EDSS score in the patients with secondary progressive MS than in those with relapsing-remitting MS. Our findings suggest that chronic progressive brain atrophy in patients with long-standing MS may be a predictor of cumulative disability. Longitudinal quantitation of brain volume loss in patients with MS may therefore represent a sensitive and highly reproducible means of following and predicting clinical response to drug therapy in MS treatment trials.
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Footnotes |
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Author contributions: Guarantor of integrity of entire study, R.I.G.; study concepts, Y.G., R.I.G.; study design, Y.G., R.I.G., J.K.U.; definition of intellectual content, Y.G., R.I.G., J.K.U.; literature research, Y.G., R.I.G., J.K.U.; clinical studies, Y.G., R.I.G., D.L.K., L.J.M.; experimental studies, Y.G., L.J.M., R.I.G., J.K.U., L.W.; data acquisition, Y.G., L.W., L.J.M.; data analysis, Y.G., L.W., M.P.; statistical analysis, M.P.; manuscript preparation, Y.G., R.I.G., D.L.K.; manuscript editing, R.I.G., J.K.U., D.L.K.; manuscript review, R.I.G., J.K.U., D.L.K., M.P.
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N. F. Kalkers, E. Bergers, J. A. Castelijns, M. A. A. van Walderveen, J. C. J. Bot, H. J. Ader, C. H. Polman, and F. Barkhof Optimizing the association between disability and biological markers in MS Neurology, October 9, 2001; 57(7): 1253 - 1258. [Abstract] [Full Text] [PDF]
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G. Iannucci, M. Rovaris, L. Giacomotti, G. Comi, and M. Filippi Correlation of Multiple Sclerosis Measures Derived from T2-Weighted, T1-Weighted, Magnetization Transfer, and Diffusion Tensor MR Imaging AJNR Am. J. Neuroradiol., September 1, 2001; 22(8): 1462 - 1467. [Abstract] [Full Text] [PDF]
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J. L. Whitwell, W. R. Crum, H. C. Watt, and N. C. Fox Normalization of Cerebral Volumes by Use of Intracranial Volume: Implications for Longitudinal Quantitative MR Imaging AJNR Am. J. Neuroradiol., September 1, 2001; 22(8): 1483 - 1489. [Abstract] [Full Text] [PDF]
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M. Rovaris, G. Comi, M. A. Rocca, J. S. Wolinsky, and M. Filippi Short-term brain volume change in relapsing-remitting multiple sclerosis: Effect of glatiramer acetate and implications Brain, September 1, 2001; 124(9): 1803 - 1812. [Abstract] [Full Text] [PDF]
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Y. Ge, R. I. Grossman, J. K. Udupa, J. S. Babb, L. G. Nyul, and D. L. Kolson Brain Atrophy in Relapsing-Remitting Multiple Sclerosis: Fractional Volumetric Analysis of Gray Matter and White Matter Radiology, September 1, 2001; 220(3): 606 - 610. [Abstract] [Full Text] [PDF]
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R Zivadinov, J Sepcic, D Nasuelli, R De Masi, L M. Bragadin, M A Tommasi, S Zambito-Marsala, R Moretti, A Bratina, M Ukmar, et al. A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis J. Neurol. Neurosurg. Psychiatry, June 1, 2001; 70(6): 773 - 780. [Abstract] [Full Text] [PDF]
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Y. Ge, R. I. Grossman, J. K. Udupa, J. S. Babb, D. L. Kolson, and J. C. McGowan Magnetization Transfer Ratio Histogram Analysis of Gray Matter in Relapsing-remitting Multiple Sclerosis AJNR Am. J. Neuroradiol., March 1, 2001; 22(3): 470 - 475. [Abstract] [Full Text]
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C Gasperini, M Rovaris, M P Sormani, S Bastianello, C Pozzilli, G Comi, and M Filippi Intra-observer, inter-observer and inter-scanner variations in brain MRI volume measurements in multiple sclerosis Multiple Sclerosis, February 1, 2001; 7(1): 27 - 31. [Abstract] [PDF]
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M. Filippi, M. Rovaris, G. Iannucci, S. Mennea, M. P. Sormani, and G. Comi Whole brain volume changes in patients with progressive MS treated with cladribine Neurology, December 12, 2000; 55(11): 1714 - 1718. [Abstract] [Full Text] [PDF]
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E Fisher, R A Rudick, G Cutter, M Baier, D Miller, B Weinstock-Guttman, M K Mass, D S Dougherty, and N A Simonian Relationship between brain atrophy and disability: an 8-year follow-up study of multiple sclerosis patients Multiple Sclerosis, December 1, 2000; 6(6): 373 - 377. [Abstract] [PDF]
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M Filippi Enhanced magnetic resonance imaging in multiple sclerosis Multiple Sclerosis, October 1, 2000; 6(5): 320 - 326. [Abstract] [PDF]
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A. M. Saindane, Y. Ge, J. K. Udupa, J. S. Babb, L. J. Mannon, and R. I. Grossman The effect of gadolinium-enhancing lesions on whole brain atrophy in relapsing-remitting MS Neurology, July 12, 2000; 55(1): 61 - 65. [Abstract] [Full Text] [PDF]
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