Literature DB >> 19877239

Potential role of high-field MRI for studies in Parkinson's disease.

Norbert Schuff1.   

Abstract

Recent advancements in high field magnetic resonance imaging (MRI) technology (3 T and higher), providing increased signal sensitivity and images with more prominent contrasts intrinsic to the brain, offer new opportunities for assessing brain alterations in Parkinson's disease (PD). In this article, the principle benefits of high field MRI for PD research are described and new findings at high magnetic fields are reviewed. Several high field MRI methodologies, including structural MRI, imaging of brain iron, diffusion tensor imaging, arterial spin labeling perfusion imaging, rotating frame imaging, and magnetic resonance spectroscopy, are critically reviewed for their potential roles in studies of PD. Copyright 2009 Movement Disorder Society

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19877239     DOI: 10.1002/mds.22647

Source DB:  PubMed          Journal:  Mov Disord        ISSN: 0885-3185            Impact factor:   10.338


  6 in total

Review 1.  Differences between conventional and nonconventional MRI techniques in Parkinson's disease.

Authors:  A Baglieri; M A Marino; R Morabito; G Di Lorenzo; P Bramanti; S Marino
Journal:  Funct Neurol       Date:  2013 Apr-May

2.  Signal Alteration of Substantia Nigra on 3.0T Susceptibility-weighted Imaging in Parkinson's Disease and Vascular Parkinsonism.

Authors:  Xue-Jun Zhao; Xi-Yuan Niu; He-Yang You; Min Zhou; Xue-Bing Ji; Ying Liu; Lei Wu; Xiao-Ling Ding
Journal:  Curr Med Sci       Date:  2019-10-14

Review 3.  Perspectives of Ultra-High-Field MRI in Neuroradiology.

Authors:  E R Gizewski; C Mönninghoff; M Forsting
Journal:  Clin Neuroradiol       Date:  2015-07-17       Impact factor: 3.649

Review 4.  Does structural neuroimaging reveal a disturbance of iron metabolism in Parkinson's disease? Implications from MRI and TCS studies.

Authors:  Adriane Gröger; Daniela Berg
Journal:  J Neural Transm (Vienna)       Date:  2012-08-09       Impact factor: 3.575

5.  Predictive model of spread of Parkinson's pathology using network diffusion.

Authors:  S Pandya; Y Zeighami; B Freeze; M Dadar; D L Collins; A Dagher; A Raj
Journal:  Neuroimage       Date:  2019-03-06       Impact factor: 6.556

6.  Diffusion tensor imaging and correlations to Parkinson rating scales.

Authors:  Niklas Lenfeldt; William Hansson; Anne Larsson; Lars Nyberg; Richard Birgander; Lars Forsgren
Journal:  J Neurol       Date:  2013-08-23       Impact factor: 4.849

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.