Journal of IMAB - Annual Proceeding (Scientific Papers)
Publisher: Peytchinski, Gospodin Iliev
ISSN: 1312 773X
Issue: 2016, vol. 22, issue 1
Subject Area: Medicine
Published online: 08 February 2016
J of IMAB 2016 Jan-Mar;22(1):1029-1032
INFLUENCE OF WHITE MATTER LESION FILLING ON VOLUMETRIC ASSESSMENT IN MULTIPLE SCLEROSIS
Ivan Dimitrov1, Radoslav Georgiev2, Ara Kaprelyan3, Yavor Enchev4, Margarita Grudkova3, Nataliya Usheva5, Borislav Ivanov6.
1) Department of Nursing, Medical University, Varna, Sliven Affiliate
2) Department of Imaging Diagnostics and Radiotherapy, Medical University, Varna
3) Department of Neurology, Medical University, Varna
4) Department of Neurosurgery and ENT Diseases, Medical University, Varna
5) Department of Social Medicine and Healthcare Organization, Medical University, Varna
6) Department of Clinical Medical Sciences, Dental Faculty, Medical University, Varna, Bulgaria.
Background: The continuous progress of information technology has made possible the creation of tools for post processing of magnetic resonance and other imaging modalities, including software programmes aimed at volumetric studies of the brain. They have the potential to enrich visual data with precise numeric values but have to be used with caution because of their possible susceptibility to errors if scans with specific pathology are fed in.
Objective: The purpose of the present study is to assess whether filling white matter lesions on magnetic resonance scans of multiple sclerosis patients would influence volumetric values.
Methods: MS lesions were filled on T1 3D images of 49 patients by the lesion-filling algorithm of FSL, using previously created lesion masks. Volumes of brain grey and white matter, peripheral grey matter and ventricle CSF were calculated using SIENAX for the filled and non-filled series, which were then compared.
Results: There were statistically significant differences for white matter volume before and after lesion filling (p<0.05). No other volumes were significantly different.
Conclusion: Filling of white matter lesions may be time-consuming, but can improve the accuracy of SIENAX by reducing bias due to misidentification of tissue intensity. Sometimes though, improvement of specific values may not reach statistical significance.
Key words: lesion filling, multiple sclerosis, SIENAX, volumetric study,
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Please cite this article in PubMed Style or AMA (American Medical Association) Style:
Dimitrov I, Georgiev R, Ara Kaprelyan A, Enchev Y, Grudkova M, Usheva N, Ivanov B. Influence of white matter lesion filling on volumetric assessment in multiple sclerosis. J of IMAB. 2016 Jan-Mar;22(1):1029-1032. DOI: http://dx.doi.org/10.5272/jimab.2016221.1029.
Correspondence to: Ivan Dimitrov, MD, PhD; First Clinic of Neurology, Sveta Marina University Hospital; 1, Hristo Smirnenski str., 9010 Varna, Bulgaria; E-mail: email@example.com
1. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004; 23 Suppl 1:S208-219. [PubMed] [CrossRef]
2. Smith SM, Zhang Y, Jenkinson M, Chen J, Matthews PM, Federico A, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. ;Neuroimage. 2002 Sep;17(1):479-489. [PubMed] [CrossRef]
3. Sdika M, Pelletier D. Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping. Hum Brain Mapp. 2009 Apr;30(4):1060-1067. [PubMed] [CrossRef]
4. Valverde S, Oliver A, Llado X. A white matter lesion-filling approach to improve brain tissue volume measurements. Neuroimage Clin. 2014 Aug;6:86-92. [PubMed] [ CrossRef]
5. Sepulcre J, Goni J, Masdeu JC, Bejarano B, Velez de Mendizabal N, Toledo JB, et al. Contribution of white matter lesions to gray matter atrophy in multiple sclerosis: evidence from voxel-based analysis of T1 lesions in the visual pathway. Arch Neurol. 2009 Feb;66(2):173-179. [PubMed] [CrossRef]
6. Chard DT, Jackson JS, Miller DH, Wheeler-Kingshott CA. Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. J Magn Reson Imaging. 2010 Jul;32(1):223-228. [PubMed] [CrossRef]
7. Battaglini M, Jenkinson M, De Stefano N. Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp. 2012 Sep;33(9):2062-2071. [PubMed] [CrossRef]
8. Popescu V, Ran NC, Barkhof F, Chard DT, Wheeler-Kingshott CA, Vrenken H. Accurate GM atrophy quantification in MS using lesion-filling with co-registered 2D lesion masks. Neuroimage Clin. 2014; 4:366-373. [PubMed] [CrossRef]
9. Datta S, Sajja BR, He R, Wolinsky JS, Gupta RK, Narayana PA. Segmentation and quantification of black holes in multiple sclerosis. Neuroimage. 2006 Jan;29(2):467-474. [PubMed] [CrossRef]
10. Maillard P, Delcroix N, Crivello F, Dufouil C, Gicquel S, Joliot M, et al. An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases. Neuroradiology. 2008 Jan;50(1):31-42. [PubMed] [CrossRef]
11. Asclepios Research Project. SepINRIA: A Software to Analyse Multiple Sclerosis Brain MRI. 2014. Available from: [Internet]
12. Magon S, Gaetano L, Chakravarty MM, Lerch JP, Naegelin Y, Stippich C, et al. White matter lesion filling improves the accuracy of cortical thickness measurements in multiple sclerosis patients: a longitudinal study. BMC Neurosci. 2014 Sep 8;15:106. [PubMed] [CrossRef]
13. de Boer R, Vrooman HA, van der Lijn F, Vernooij MW, Ikram MA, van der Lugt A, et al. White matter lesion extension to automatic brain tissue segmentation on MRI. Neuroimage. 2009 May;45(4):1151-1161. [PubMed] [CrossRef]
14. Prados F, Cardoso MJ, MacManus D, Wheeler-Kingshott CA, Ourselin S. A modality-agnostic patch-based technique for lesion filling in multiple sclerosis. Med Image Comput Comput Assist Interv. 2014;17(Pt 2):781-788. [PubMed].
Received: 29 October 2015
Published online: 08 February 2016
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