Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-06-01T09:53:08.468Z Has data issue: false hasContentIssue false
  • English
  • Français

Resolution-Dependent Estimates of Multiple Sclerosis Lesion Loads

Published online by Cambridge University Press:  02 December 2014

M.K. Erskine ,
L.L. Cook ,
K.E. Riddle ,
J.R. Mitchell  and
S.J. Karlik
M.K. Erskine
Affiliation:
Department of Physiology, University of Western Ontario, London, Ontario, Canada
L.L. Cook
Affiliation:
Department of Physiology, University of Western Ontario, London, Ontario, Canada
K.E. Riddle
Affiliation:
Department of Diagnostic Radiology and Nuclear Medicine, London Health Sciences Centre, London, Ontario, Canada
J.R. Mitchell
Affiliation:
Calgary Neuroscience Research Group, University of Calgary, Calgary, Alberta, Canada
S.J. Karlik
Affiliation:
Department of Physiology, and Department of Pathology, University of Western Ontario, and Department of Diagnostic Radiology and Nuclear Medicine, London Health Sciences Centre, London, Ontario, Canada
Rights & Permissions [Opens in a new window]

Abstract:

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Background:

Changes in brain lesion loads assessed with magnetic resonance imaging obtained at 1.5 Telsa (T) are used as a measure of disease evolution in natural history studies and treatment trials of multiple sclerosis.

Methods:

A comparison was made between the total lesion volume and individual lesions observed on 1.5 T images and on high-resolution 4 T images. Lesions were quantified using a computer-assisted segmentation tool.

Results:

There was a 46% increase in the total number of lesions detected with 4 T versus 1.5 T imaging (p<0.005). The 4 T also showed a 60% increase in total lesion volume when compared with the 1.5 T (p<0.005). In several instances, the 1.5 T scans showed individual lesions that coalesced into larger areas of abnormality in the 4 T scans. The relationship between individual lesion volumes was linear (slope 1.231) showing that the lesion volume observed at 4 T increased with the size of the lesion detected at 1.5 T. The 4 T voxels were less than one quarter the size of those used at 1.5 T and there were no consistent differences between their signal-to-noise ratios.

Conclusions:

The increase in signal strength that accompanied the increase in field strength compensated for the loss in signal amplitude produced by the use of smaller voxels. This enabled the acquisition of images with improved resolution, resulting in increased lesion detection at 4 T and larger lesion volumes.

Résumé:

RÉSUMÉ:Introduction:

Les changements du fardeau lésionnel cérébral évalués par imagerie par résonance magnétique obtenue à 1,5 Telsa (T) sont utilisés comme mesure de l’évolution de la maladie dans les études sur l’histoire naturelle de la maladie et au cours des essais thérapeutiques dans la sclérose en plaques.

Méthodes:

Le volume total des lésions et les lésions individuelles observées sur des images 1,5 T ont été comparés aux données obtenues sur des images 4 T à haute résolution. Un outil de segmentation assistée par ordinateur a été utilisé pour quantifier les lésions.

Résultat:

L’imagerie 4 T détectait 46% plus de lésions que l’imagerie 1,5 T (p < 0,005) et un volume total de lésions 60% plus élevé (p < 0,005). Dans plusieurs cas, les scans 1,5 T montraient des lésions individuelles qui se fusionnaient en zones anormales plus vastes sur les scans 4 T. La relation entre le volume individuel des lésions était linéaire (pente de 1,231) démontrant que le volume des lésions observées sur l’imagerie 4 T augmentait selon la taille de la lésion détectée à l’imagerie 1,5 T. Les voxels 4 T étaient moins que le quart de la taille de ceux utilisés à 1,5 T et il n’y avait pas de différence constante entre leur rapport signal-bruit.

Conclusions:

L’augmentation de la forcedu signal qui accompagnait l’augmentation de la force du champ magnétique compensait pour la perte d’amplitude du signal produit par l’utilisation de voxels plus petits, ce qui permettait l’acquisition d’images dont la résolution était meilleure et donc une meilleure détection des lésions et une meilleure appréciation de leur volume par l’imagerie 4 T.

Type
Original Articles
Information
Canadian Journal of Neurological Sciences , Volume 32 , Issue 2 , May 2005 , pp. 205 - 212
Copyright
Copyright © The Canadian Journal of Neurological 2005

References

1. Pretorius, PM, Quaghebeur, G. The role of MRI in the diagnosis of MS. Clin Radiol 2003; 58: 434–448.CrossRefGoogle ScholarPubMed
2. Noseworthy, JH, Lucchinetti, C, Rodriguez, M, Weinshenker, BG. Multiple sclerosis. N Engl J Med 2000; 343: 938–952.CrossRefGoogle ScholarPubMed
3. Weiner, HL. A 21 point unifying hypothesis on the etiology andtreatment of multiple sclerosis. Can J Neurol Sci 1998; 25: 93–101.CrossRefGoogle Scholar
4. Miller, DH, Albert, PS, Barkhof, F, et al. Guidelines for the use ofmagnetic resonance techniques in monitoring the treatment of multiple sclerosis. Ann Neurol 1996; 39: 6–16.CrossRefGoogle Scholar
5. Gareau, PJ, Rutt, BK, Bowen, CV, Karlik, SJ, Mitchell, JR. In vivomeasurements of multi-component T2 relaxation behaviour in guinea pig brain. Magn Reson Imaging 1999; 17: 1319–1325.CrossRefGoogle Scholar
6. Bagnato, F, Jeffries, N, Richert, ND, et al. Evolution of T1 black holesin patients with multiple sclerosis imaged monthly for 4 years. Brain 2003; 126: 1782–1789.CrossRefGoogle Scholar
7. Jack, CR Jr, Berquist, TH, Miller, GM, et al. Field strength in neuro-MR imaging: a comparison of 0.5 T and 1.5 T. J Comput Assist Tomogr 1990; 14: 505–513.CrossRefGoogle ScholarPubMed
8. Steinberg, HV, Alarcon, JJ, Bernadino, ME. Focal hepatic lesions:comparative MR imaging at 0.5 and 1.5 T. Radiology 1990; 174: 153–156.CrossRefGoogle Scholar
9. Lee, JH, Garwood, M, Menon, R, et al. High contrast and fast three-dimensional magnetic resonance imaging at high fields. Magn Reson Med 1995; 34: 308–312.CrossRefGoogle ScholarPubMed
10. Mitchell, JR, Karlik, SJ, Lee, DH, Fenster, A. Computer-assistedidentification and quantification of multiple sclerosis lesions in MR imaging volumes in the brain. J Magn Reson Imaging 1994; 4: 197–208.CrossRefGoogle ScholarPubMed
11. Caramia, F, Pantano, P, Di Legge, S et al. A longitudinal study of MRdiffusion changes in normal appearing white matter of patients with early multiple sclerosis. Magn Reson Imaging 2002; 20(5): 383–388.CrossRefGoogle Scholar
12. Whittall, KP, MacKay, AL, Li, DK, et al. Normal-appearing whitematter in multiple sclerosis has heterogeneous, diffuselyprolonged T(2). Magn Reson Med 2002; 47(2): 403–408.CrossRefGoogle Scholar
13. Allen, IV, McQuaid, S, Mirakhur, M, Nevin, G. Pathologicalabnormalities in the normal-appearing white matter in multiple sclerosis. Neurol Sci 2001; 22(2): 141–144.CrossRefGoogle ScholarPubMed
14. Cook, LL, Foster, PJ, Mitchell, JR, Karlik, SJ. In vivo 4.0-T magneticresonance investigation of spinal cord inflammation, demyelination, and axonal damage in chronic-progressive experimental allergic encephalomyelitis. J Magn Reson Imaging 2004; 20(4): 563–571.CrossRefGoogle Scholar
15. ’t Hart, BA, Bauer, J, Muller, H-J, et al. Histopathological characterization of magnetic resonance imaging-detectable brain white matter lesions in a primate model of multiple sclerosis: a correlative study in marmoset (Callithrix juacchus). Am J Pathol 1998; 153: 649–663.CrossRefGoogle Scholar
16. Filippi, M, Horsfield, MA, Campi, A, et al. Resolution-dependentestimates of lesion volumes in magnetic resonance imaging studies of the brain in multiple sclerosis. Ann Neurol 1995; 38: 749–754.CrossRefGoogle ScholarPubMed
17. Stone, LA, Albert, PS, Smith, ME, et al. Changes in the amount ofdiseased white matter over time in patients with relapsing-remitting multiple sclerosis. Neurology 1995; 45: 1808–1814.CrossRefGoogle ScholarPubMed
18. Filippi, M, van Waesberghe, JH, Horsfield, MA, et al. Interscannervariation in brain MRI lesion load measurements in MS: implications for clinical trials. Neurology 1997; 49: 371–377.CrossRefGoogle ScholarPubMed
19. Horsfield, MA, Barker, GJ, Barkhof, F, et al. Guidelines for usingquantitative magnetization transfer magnetic resonance imaging for monitoring treatment of multiple sclerosis. J Magn Reson Imaging 2003; 17: 389–397.CrossRefGoogle Scholar
20. Filippi, M, Yousry, T, Horsfield, MA, et al. A high-resolution three-dimensional T1-weighted gradient echo sequence improves the detection of disease activity in multiple sclerosis. Ann Neurol 1996; 40: 901–907.CrossRefGoogle ScholarPubMed
21. Filippi, M, Yousry, T, Baratti, C, et al. Quantitative assessment of MRI lesion load in multiple sclerosis: a comparison of conventional spin-echo with fast fluid-attenuated inversion recovery. Brain 1996; 119: 1349–1355.CrossRefGoogle ScholarPubMed
22. Rovaris, M, Gawne-Cain, ML, Wang, L, Miller, DH. A comparison of conventional and fast spin-echo sequences for the measurement of lesion load in multiple sclerosis using a semi-automated contour technique. Neuroradiology 1997; 39: 161–165.CrossRefGoogle ScholarPubMed
23. Filippi, M, Rocca, MA, Horsfield, MA, et al. Increased spatialresolution using a three-dimensional T1-weighted gradientecho MR sequence results in greater hypointense lesion volumes in multiple sclerosis. AJNR Am J Neuroradiol 1998; 19: 235–238.Google Scholar
24. Filippi, M, Horsfield, MA, Rovaris, M, et al. Intraobserver andinterobserver variability in schemes for estimating volume of brain lesions on MR images in multiple sclerosis. AJNR Am JNeuroradiol 1998; 19: 239–244.Google Scholar
25. Grimaud, J, Lai, M, Thorpe, J, et al. Quantification of MRI lesion loadin multiple sclerosis: a comparison of three computer-assisted techniques. Magn Reson Imaging 1996; 14: 495–505.CrossRefGoogle Scholar
26. Rovaris, M, Rocca, MA, Yousry, I, et al. Lesion load quantification on fast-flair, rapid acquisition relaxation-enhanced, and gradient spin echo brain MRI scans from multiple sclerosis patients. Magn Reson Imaging 1999; 17: 1105–1110.CrossRefGoogle ScholarPubMed
27. Firbank, MJ, Coulthard, A, Harrison, RM, Williams, ED. Partialvolume effects in MRI studies of multiple sclerosis. Magn Reson Imaging 1999; 17: 593–607.CrossRefGoogle Scholar
28. Wang, L, Lai, HM, Thompson, AJ, Miller, DH. Survey of thedistribution of lesion size in multiple sclerosis: implication for the measurement of total lesion load. J Neurol Neurosurg Psychiatry 1997; 63: 452–455.CrossRefGoogle Scholar
29. Molyneux, PD, Tubridy, N, Parker, GJM, et al. The effect of sectionthickness on MR lesion detection and quantification in multiple sclerosis. AJNR Am J Neuroradiol 1998; 19: 1715–1720.Google Scholar
30. Filippi, M, Gawne-Cain, ML, Gasperini, C, et al. Effect of trainingand different measurement strategies on the reproducibility of brain MRI lesion load measurements in multiple sclerosis. Neurology 1998; 50: 238–244.CrossRefGoogle Scholar
31. Gawne-Cain, ML, Webb, S, Tofts, P, Miller, DH. Lesion volumemeasurement in multiple sclerosis: how important is accurate repositioning? J Magn Reson Imaging 1996; 6: 705–713.CrossRefGoogle Scholar
32. Filippi, M, Marciano, N, Capra, R, et al. The effect of impreciserepositioning on lesion volume measurement in patients with multiple sclerosis. Neurology 1997; 49: 274–276.CrossRefGoogle ScholarPubMed
33. Filippi, M, Paty, DW, Kappos, L, et al. Correlations between changesin disability and T2-weighted brain MRI activity in multiple sclerosis: a follow-up study. Neurology 1995; 45: 255–260.CrossRefGoogle Scholar
34. Filippi, M, Horsfield, MA, Ader, HJ, et al. Guidelines for usingquantitative measures of brain magnetic resonance imaging abnormalities in monitoring the treatment of multiple sclerosis. Ann Neurol 1998; 43: 499–506.CrossRefGoogle Scholar
35. Mastronardo, G, Rocca, MA, Rovaris, M,.. et al. A comparison of thesensitivity of monthly unenhanced and enhanced MRI techniques in detecting new multiple sclerosis lesions. Proceedings of the ISMRM, Sixth Scientific Meeting and Exhibition, Sydney, Australia, 1998: 1314.Google Scholar
36. Miller, DH, Barkhof, F, Berry, I, et al. Magnetic resonance imaging inmonitoring the treatment of multiple sclerosis: concerted action guidelines. J Neurol Neurosurg Psychiatry 1991; 54: 683–688.CrossRefGoogle Scholar
37. Wicks, DA, Tofts, PS, Miller, DH, et al. Volume measurement of multiple sclerosis lesions with magnetic resonance images. A preliminary study. Neuroradiology 1992; 34: 475–479.CrossRefGoogle ScholarPubMed