open access

Vol 53, No 1 (2019)
Research paper
Published online: 2018-12-11
Submitted: 2018-11-06
Accepted: 2018-11-06
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Spatial distribution of white matter degenerative lesions and cognitive dysfunction in relapsing-remitting multiple sclerosis patients

Natalia Nowaczyk, Alicja Kalinowska-Łyszczarz, Włodzimierz Paprzycki, Sławomir Michalak, Radosław Kaźmierski, Mikołaj A. Pawlak
DOI: 10.5603/PJNNS.a2018.0001
·
Pubmed: 30742302
·
Neurol Neurochir Pol 2019;53(1):18-25.

open access

Vol 53, No 1 (2019)
Research paper
Published online: 2018-12-11
Submitted: 2018-11-06
Accepted: 2018-11-06

Abstract

Aim. The aim of this study was to assess degenerative lesion localisation in the course of relapsing-remitting multiple sclerosis (RRMS) and to identify the association between localisation and the frequency of T1-hypointense lesions (black holes) with cognitive dysfunction. We also searched for neuroradiological predictors of cognitive dysfunction in patients. The clinical rationale for the study was previous research, and our own findings suggest that lesion localisation plays an important role in cognitive performance and neurological disability of MS patients.

Material and methods. Forty-two patients were included in the study. All subjects underwent neuropsychological examination using Raven’s Coloured Progressive Matrices, a naming task from the Brief Repeatable Battery of Neuropsychological Tests, and attention to detail tests. Magnetic resonance imaging (MRI) was acquired on 1.5 Tesla scanner and black holes were manually segmented on T1-weighted volumetric images using the FMRIB Software Library. Linear regression was applied to establish a relationship between black hole volume per lobe and cognitive parameters. Bonferroni correction of voxelwise analysis was used to correct for multiple comparisons.

Results. The following associations between black hole volume and cognition were identified: frontal lobes black hole volume was associated with phonemic verbal fluency (t = –4.013, p < 0.001), parietal black hole volume was associated with attention (t = –3.776, p < 0.001), and parietal and temporal black hole volumes were associated with nonverbal intelligence (p < 0.001). The volume of parietal black holes was the best predictor of cognitive dysfunction.

Conclusions. Our approach, including measurement of focal axonal loss based on T1-volumetric MRI sequence and brief neuropsychological assessment, might improve personalised diagnostic and therapeutic decisions in clinical practice.

Abstract

Aim. The aim of this study was to assess degenerative lesion localisation in the course of relapsing-remitting multiple sclerosis (RRMS) and to identify the association between localisation and the frequency of T1-hypointense lesions (black holes) with cognitive dysfunction. We also searched for neuroradiological predictors of cognitive dysfunction in patients. The clinical rationale for the study was previous research, and our own findings suggest that lesion localisation plays an important role in cognitive performance and neurological disability of MS patients.

Material and methods. Forty-two patients were included in the study. All subjects underwent neuropsychological examination using Raven’s Coloured Progressive Matrices, a naming task from the Brief Repeatable Battery of Neuropsychological Tests, and attention to detail tests. Magnetic resonance imaging (MRI) was acquired on 1.5 Tesla scanner and black holes were manually segmented on T1-weighted volumetric images using the FMRIB Software Library. Linear regression was applied to establish a relationship between black hole volume per lobe and cognitive parameters. Bonferroni correction of voxelwise analysis was used to correct for multiple comparisons.

Results. The following associations between black hole volume and cognition were identified: frontal lobes black hole volume was associated with phonemic verbal fluency (t = –4.013, p < 0.001), parietal black hole volume was associated with attention (t = –3.776, p < 0.001), and parietal and temporal black hole volumes were associated with nonverbal intelligence (p < 0.001). The volume of parietal black holes was the best predictor of cognitive dysfunction.

Conclusions. Our approach, including measurement of focal axonal loss based on T1-volumetric MRI sequence and brief neuropsychological assessment, might improve personalised diagnostic and therapeutic decisions in clinical practice.

Get Citation

Keywords

relapsing-remitting multiple sclerosis (RRMS), T1-hypointense lesions, black holes, magnetic resonance imaging (MRI), cognitive dysfunction

About this article
Title

Spatial distribution of white matter degenerative lesions and cognitive dysfunction in relapsing-remitting multiple sclerosis patients

Journal

Neurologia i Neurochirurgia Polska

Issue

Vol 53, No 1 (2019)

Pages

18-25

Published online

2018-12-11

DOI

10.5603/PJNNS.a2018.0001

Pubmed

30742302

Bibliographic record

Neurol Neurochir Pol 2019;53(1):18-25.

Keywords

relapsing-remitting multiple sclerosis (RRMS)
T1-hypointense lesions
black holes
magnetic resonance imaging (MRI)
cognitive dysfunction

Authors

Natalia Nowaczyk
Alicja Kalinowska-Łyszczarz
Włodzimierz Paprzycki
Sławomir Michalak
Radosław Kaźmierski
Mikołaj A. Pawlak

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