scholarly journals A Tumefactive Multiple Sclerosis Lesion in the Brain: An Uncommon Site with Atypical Magnetic Resonance Image Findings

2013 ◽  
Vol 69 (5) ◽  
pp. 337
Author(s):  
Min Sun Jeong ◽  
Hyun Sook Kim ◽  
Jae Hoon Kim ◽  
Eun Kyung Kim ◽  
Yun Sun Choi
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Magnetic Resonance Image ◽  
Multiple Sclerosis Lesion ◽  
The Brain ◽  
Tumefactive Multiple Sclerosis

scholarly journals Distribution of multiple sclerosis lesions detected by brain magnetic resonance imaging in Erbil city

2021 ◽  
Vol 25 (1) ◽  
pp. 446-455
Author(s):  
Dina Tawfeeq ◽  
Shawnam Dawood
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Brain Stem ◽  
Signal Intensity ◽  
Brain Regions ◽  
Multiple Sclerosis Lesion ◽  
Resonance Imaging ◽  
The Brain

Background and objective: Many epidemiological studies and clinical manifestation studies of multiple sclerosis have been done in Iraq. Up to our knowledge, no such observational study to the radiological feature of the multiple sclerosis lesion has been done yet in Erbil in comparison to other worldwide studies. This study aimed to assess the distribution of multiple sclerosis lesions in brain regions detected by magnetic resonance imaging among Erbil population. Methods: This was a cross-sectional study conducted at the College of Medicine, Hawler Medical University, from April 2018 to July 2019. A review of magnetic resonance imaging scans of the brain of 120 patients was done. Special attention was directed toward identifying the variance in multiple sclerosis lesions distribution in the brain regions and their MR signal intensity characteristics. Results: Periventricular lesions were observed in more than 90% of the study sample. The next common was juxtacortical lesions (24.8%), followed by corpus callosum lesions (16.8 %), while brain stem lesions were the least observed proportions. No significant difference was detected in the distribution of multiple sclerosis lesions among ethnicities and genders, except for basal ganglia lesions, which were significantly more common in women (P = 0.016).The magnetic resonance imaging signal intensity of the lesion was significantly variable among disease duration. Conclusion: The T2 hyper intense lesions were most commonly seen in the periventricular region. Juxtacortical and corpus callosum lesions were also frequently observed. The proportions of the brain stem and cerebellum lesions appeared to be lower in comparison to previous studies. Keywords: Multiple Sclerosis; Magnetic Resonance Imaging; Distribution; Lesion.

Sagittal T2 weighted magnetic resonance image of the brain

BMJ ◽  
2010 ◽  
Vol 341 (aug31 3) ◽  
pp. c4678-c4678
Author(s):  
A. Nair
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Image ◽  
The Brain

scholarly journals Experimental design and sample size considerations in longitudinal magnetic resonance imaging-based biomarker detection for multiple sclerosis

2020 ◽  
Vol 29 (9) ◽  
pp. 2617-2628 ◽  
Author(s):  
Menghan Hu ◽  
Matthew K Schindler ◽  
Blake E Dewey ◽  
Daniel S Reich ◽  
Russell T Shinohara ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Magnetic Resonance ◽  
Sample Size ◽  
Disease Progression ◽  
Multiple Sclerosis Lesion ◽  
Resonance Imaging ◽  
Study Duration ◽  
Multiple Sclerosis Disease

Several modeling approaches have been developed to quantify differences in multiple sclerosis lesion evolution on magnetic resonance imaging to identify the effect of treatment on disease progression. These studies have limited clinical applicability due to onerous scan frequency and lengthy study duration. Efficient methods are needed to reduce the required sample size, study duration, and sampling frequency in longitudinal magnetic resonance imaging studies. We develop a data-driven approach to identify parameters of study design for evaluation of longitudinal magnetic resonance imaging biomarkers of multiple sclerosis lesion evolution. Our design strategies are considerably shorter than those described in previous studies, thus having the potential to lower costs of clinical trials. From a dataset of 36 multiple sclerosis patients with at least six monthly magnetic resonance imagings, we extracted new lesions and performed principal component analysis to estimate a biomarker that recapitulated lesion recovery. We tested the effect of multiple sclerosis disease modifying therapy on the lesion evolution index in three experimental designs and calculated sample sizes needed to appropriately power studies. Our proposed methods can be used to calculate required sample size and scan frequency in observational studies of multiple sclerosis disease progression as well as in designing clinical trials to find effects of treatment on multiple sclerosis lesion evolution.

scholarly journals ADvanced IMage Algebra (ADIMA): a novel method for depicting multiple sclerosis lesion heterogeneity, as demonstrated by quantitative MRI

2012 ◽  
Vol 19 (6) ◽  
pp. 732-741 ◽  
Author(s):  
Marios C Yiannakas ◽  
Daniel J Tozer ◽  
Klaus Schmierer ◽  
Declan T Chard ◽  
Valerie M Anderson ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Quantitative Mri ◽  
Multiple Sclerosis Lesion ◽  
Proton Density ◽  
Image Algebra ◽  
Quantitative Magnetic Resonance ◽  
Magnetic Resonance Parameters ◽  
Mri Scans ◽  
T1 And T2

Background: There are modest correlations between multiple sclerosis (MS) disability and white matter lesion (WML) volumes, as measured by T2-weighted (T2w) magnetic resonance imaging (MRI) scans (T2-WML). This may partly reflect pathological heterogeneity in WMLs, which is not apparent on T2w scans. Objective: To determine if ADvanced IMage Algebra (ADIMA), a novel MRI post-processing method, can reveal WML heterogeneity from proton-density weighted (PDw) and T2w images. Methods: We obtained conventional PDw and T2w images from 10 patients with relapsing–remitting MS (RRMS) and ADIMA images were calculated from these. We classified all WML into bright (ADIMA-b) and dark (ADIMA-d) sub-regions, which were segmented. We obtained conventional T2-WML and T1-WML volumes for comparison, as well as the following quantitative magnetic resonance parameters: magnetisation transfer ratio (MTR), T1 and T2. Also, we assessed the reproducibility of the segmentation for ADIMA-b, ADIMA-d and T2-WML. Results: Our study’s ADIMA-derived volumes correlated with conventional lesion volumes ( p < 0.05). ADIMA-b exhibited higher T1 and T2, and lower MTR than the T2-WML ( p < 0.001). Despite the similarity in T1 values between ADIMA-b and T1-WML, these regions were only partly overlapping with each other. ADIMA-d exhibited quantitative characteristics similar to T2-WML; however, they were only partly overlapping. Mean intra- and inter-observer coefficients of variation for ADIMA-b, ADIMA-d and T2-WML volumes were all < 6 % and < 10 %, respectively. Conclusion: ADIMA enabled the simple classification of WML into two groups having different quantitative magnetic resonance properties, which can be reproducibly distinguished.

scholarly journals An active contour model for brain magnetic resonance image segmentation based on multiple descriptors

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141878341 ◽  
Author(s):  
Chen Hong ◽  
Yu Xiaosheng ◽  
Wu Chengdong ◽  
Wu Jiahui
Keyword(s):  
Image Segmentation ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Magnetic Resonance Image ◽  
Active Contour ◽  
Active Contour Model ◽  
Full Description ◽  
Contour Model ◽  
Brain Magnetic Resonance Image ◽  
The Brain

With the increasing use of surgical robots, robust and accurate segmentation techniques for brain tissue in the brain magnetic resonance image are needed to be embedded in the robot vision module. However, the brain magnetic resonance image segmentation results are often unsatisfactory because of noise and intensity inhomogeneity. To obtain accurate segmentation of brain tissue, one new multiphase active contour model, which is based on multiple descriptors mean, variance, and the local entropy, is proposed in this study. The model can bring about a more full description of local intensity distribution. Also, the entropy is introduced to improve the performance of robustness to noise of the algorithm. The segmentation and bias correction for brain magnetic resonance image can be simultaneously incorporated by introducing the bias factor in the proposed approach. At last, three experiments are carried out to test the performance of the method. The results in the experiments show that method proposed in this study performed better than most current methods in regard to accuracy and robustness. In addition, the bias-corrected images obtained by proposed method have better visual effect.

Emerging tumefactive multiple sclerosis after switching therapy from natalizumab to fingolimod

2012 ◽  
Vol 18 (11) ◽  
pp. 1650-1652 ◽  
Author(s):  
Sebastian Jander ◽  
Bernd Turowski ◽  
Bernd C Kieseier ◽  
Hans-Peter Hartung
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Multiple Sclerosis Patient ◽  
Resonance Imaging ◽  
Mri Features ◽  
Switching Therapy ◽  
Magnetic Resonance Imaging Mri ◽  
First Time ◽  
Tumefactive Multiple Sclerosis

In this report we describe a multiple sclerosis patient who developed a relapse with magnetic resonance imaging (MRI) features of tumefactive demyelination after switching therapy from natalizumab to fingolimod. Tumefactive lesions emerged 16 weeks after stopping natalizumab and eight weeks after commencing fingolimod therapy but had been absent at the time of diagnosis and throughout the preceding course of the disease. Thus, the first-time occurrence of atypical lesion features may have been caused by the change in immunotherapy. The possible relevance of natalizumab withdrawal vs fingolimod introduction is discussed against the background of recently published case studies.

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