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Multiple Sclerosis l: Introduction01:19

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Multiple sclerosis is a chronic autoimmune disease of the central nervous system (CNS) that affects the brain, spinal cord, and optic nerves. It is an inflammatory demyelinating disorder and a leading cause of neurological disability in young adults.EpidemiologyMS commonly begins between 20 and 40 years of age and is twice as common in women. Its exact cause remains unclear, but genetic susceptibility contributes, with higher risk in first-degree relatives and identical twins. A greater...
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Hemispheric asymmetry measured by texture analysis and diffusion tensor imaging in two multiple sclerosis subtypes.

Sami Savio1, Ullamari Hakulinen2, Pertti Ryymin3

  • 1Department of Electronics and Communications Engineering, Tampere University of Technology, Tampere, Finland Department of Radiology, Tampere University Hospital, Tampere, Finland sami.savio@tut.fi.

Acta Radiologica (Stockholm, Sweden : 1987)
|July 16, 2014
PubMed
Summary

Texture analysis (TA) and diffusion tensor imaging (DTI) can help differentiate multiple sclerosis (MS) subtypes. TA achieved over 80% accuracy in classifying primary progressive MS (PPMS) and relapsing-remitting MS (RRMS).

Keywords:
MR diffusionMagnetic resonance imaging (MRI)braintissue characterization

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Area of Science:

  • Neuroimaging
  • Radiology
  • Medical Image Analysis

Background:

  • Distinguishing between primary progressive multiple sclerosis (PPMS) and relapsing-remitting multiple sclerosis (RRMS) can be challenging.
  • Accurate subtyping is crucial for appropriate patient management and treatment strategies.

Purpose of the Study:

  • To quantitatively differentiate between PPMS and RRMS using texture analysis (TA) and diffusion tensor imaging (DTI).
  • To assess the utility of TA and DTI in identifying MS subtypes and their characteristics.

Main Methods:

  • T1-weighted MRI and DTI data from 17 PPMS and 19 RRMS patients were analyzed.
  • Texture analysis was performed on T1W images, while fractional anisotropy and apparent diffusion coefficient were derived from DTI.
  • Specific brain regions, including the caudate nucleus, thalamus, cerebral peduncle, and centrum semiovale, were investigated for hemispherical differences.

Main Results:

  • Statistically significant hemispherical differences were observed using both TA and DTI parameters.
  • Patients with RRMS exhibited greater significant thalamic differences between hemispheres compared to PPMS patients (P < 0.01).
  • Texture analysis demonstrated a classification accuracy exceeding 80% for distinguishing PPMS and RRMS subtypes.

Conclusions:

  • Texture analysis is a valuable tool for differentiating between PPMS and RRMS.
  • Diffusion tensor imaging may help identify hemispherical asymmetry characteristic of RRMS patients.