Literature DB >> 27438802

Prediction of upper extremity motor recovery after subacute intracerebral hemorrhage through diffusion tensor imaging: a systematic review and meta-analysis.

Pradeep Kumar1, Arun Kumar Yadav2, Shubham Misra2, Amit Kumar2, Kamalesh Chakravarty2, Kameshwar Prasad2.   

Abstract

INTRODUCTION: Early assessment of the pyramidal tracts is important for intracerebral hemorrhage (ICH) patients in order to decide the optimal treatment or to assess appropriate rehabilitation strategies, and management of patient expectations and goals. The purpose of this study was to systematically review and summarize the current available literature on the value of Fractional Anisotropy (FA) parameter of the diffusion tensor imaging (DTI) in predicting upper extremity (UE) motor recovery after subacute ICH.
METHODS: PubMed, EMBASE, MEDLINE, Google Scholar, and Cochrane CENTRAL searches were conducted from 1 January 1950 to 31 March 2016 which were supplemented with relevant articles identified in the references. Pooled estimate using correlation between DTI parameter FA and UE motor recovery was done using comprehensive meta-analysis software.
RESULTS: Out of 97 citations, only eight studies met the criteria for inclusion in the systematic review and six studies were included in the meta-analysis. A random effects model revealed that DTI parameter FA is a significant predictor for UE motor recovery after subacute ICH (correlation coefficient = 0.56; 95 % confidence interval 0.44 to 0.65, P value <0.001). However, moderate heterogeneity was observed between the studies (Tau-squared = 0.28, I-squared = 70.3).
CONCLUSION: The studies reported so far on correlation between FA parameter of DTI and UE motor recovery in ICH patients are few with small sample sizes. This meta-analysis suggests a strong correlation between DTI parameter FA and UE motor recovery in ICH patients. Further well-designed prospective studies embedded with larger sample size are needed to confirm these findings.

Entities:  

Keywords:  Diffusion tensor imaging; Diffusion tensor tractography; Intracerebral hemorrhage; Prediction; Upper extremity recovery

Mesh:

Year:  2016        PMID: 27438802     DOI: 10.1007/s00234-016-1718-6

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  27 in total

1.  Diffusion tensor MR imaging of the human brain.

Authors:  C Pierpaoli; P Jezzard; P J Basser; A Barnett; G Di Chiro
Journal:  Radiology       Date:  1996-12       Impact factor: 11.105

2.  Cortical adaptations and motor performance improvements associated with short-term bimanual training.

Authors:  Alison L Smith; W Richard Staines
Journal:  Brain Res       Date:  2006-01-06       Impact factor: 3.252

3.  Motor outcome for patients with acute intracerebral hemorrhage predicted using diffusion tensor imaging: an application of ordinal logistic modeling.

Authors:  Tetsuo Koyama; Masao Tsuji; Hiroji Miyake; Takehisa Ohmura; Kazuhisa Domen
Journal:  J Stroke Cerebrovasc Dis       Date:  2011-04-20       Impact factor: 2.136

4.  Functional potential in chronic stroke patients depends on corticospinal tract integrity.

Authors:  Cathy M Stinear; P Alan Barber; Peter R Smale; James P Coxon; Melanie K Fleming; Winston D Byblow
Journal:  Brain       Date:  2007-01       Impact factor: 13.501

Review 5.  Inflammation in intracerebral hemorrhage: from mechanisms to clinical translation.

Authors:  Yu Zhou; Yanchun Wang; Jian Wang; R Anne Stetler; Qing-Wu Yang
Journal:  Prog Neurobiol       Date:  2013-11-26       Impact factor: 11.685

6.  Diffusion tensor imaging predicts long-term motor functional outcome in patients with acute supratentorial intracranial hemorrhage.

Authors:  Da-Ming Wang; Jie Li; Jian-Ren Liu; Hao-Yu Hu
Journal:  Cerebrovasc Dis       Date:  2012-09-18       Impact factor: 2.762

7.  Motor outcome according to diffusion tensor tractography findings in the early stage of intracerebral hemorrhage.

Authors:  Sang-Hyun Cho; Seong Ho Kim; Byung Yun Choi; Soo Ho Cho; Jae Hoon Kang; Chu-Hee Lee; Woo Mok Byun; Sung Ho Jang
Journal:  Neurosci Lett       Date:  2007-05-04       Impact factor: 3.046

8.  Diffusion tensor tractography predicts motor functional outcome in patients with spontaneous intracerebral hemorrhage.

Authors:  Hideyuki Yoshioka; Toru Horikoshi; Shigeki Aoki; Masaaki Hori; Keiichi Ishigame; Mikito Uchida; Masao Sugita; Tsutomu Araki; Hiroyuki Kinouchi
Journal:  Neurosurgery       Date:  2008-01       Impact factor: 4.654

9.  Polymorphonuclear neutrophil in brain parenchyma after experimental intracerebral hemorrhage.

Authors:  Xiurong Zhao; Guanghua Sun; Han Zhang; Shun-Ming Ting; Shen Song; Nicole Gonzales; Jaroslaw Aronowski
Journal:  Transl Stroke Res       Date:  2014-04-03       Impact factor: 6.829

10.  Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.

Authors:  David Moher; Larissa Shamseer; Mike Clarke; Davina Ghersi; Alessandro Liberati; Mark Petticrew; Paul Shekelle; Lesley A Stewart
Journal:  Syst Rev       Date:  2015-01-01
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  10 in total

1.  Specific DTI seeding and diffusivity-analysis improve the quality and prognostic value of TMS-based deterministic DTI of the pyramidal tract.

Authors:  Tizian Rosenstock; Davide Giampiccolo; Heike Schneider; Sophia Jutta Runge; Ina Bährend; Peter Vajkoczy; Thomas Picht
Journal:  Neuroimage Clin       Date:  2017-08-12       Impact factor: 4.881

2.  Predicting Motor Outcome in Acute Intracerebral Hemorrhage.

Authors:  J Puig; G Blasco; M Terceño; P Daunis-I-Estadella; G Schlaug; M Hernandez-Perez; V Cuba; G Carbó; J Serena; M Essig; C R Figley; K Nael; C Leiva-Salinas; S Pedraza; Y Silva
Journal:  AJNR Am J Neuroradiol       Date:  2019-04-18       Impact factor: 3.825

3.  Microstructural Properties of Human Brain Revealed by Fractional Anisotropy Can Predict the After-Effect of Intermittent Theta Burst Stimulation.

Authors:  Ikko Kimura; Hiroki Oishi; Masamichi J Hayashi; Kaoru Amano
Journal:  Cereb Cortex Commun       Date:  2021-12-15

Review 4.  White matter tractography for neurosurgical planning: A topography-based review of the current state of the art.

Authors:  Walid I Essayed; Fan Zhang; Prashin Unadkat; G Rees Cosgrove; Alexandra J Golby; Lauren J O'Donnell
Journal:  Neuroimage Clin       Date:  2017-06-15       Impact factor: 4.881

Review 5.  Current Clinical Applications of Diffusion-Tensor Imaging in Neurological Disorders.

Authors:  Woo Suk Tae; Byung Joo Ham; Sung Bom Pyun; Shin Hyuk Kang; Byung Jo Kim
Journal:  J Clin Neurol       Date:  2018-02-28       Impact factor: 3.077

6.  Delayed recovery of the affected finger extensors at chronic stage in a stroke patient: A case report.

Authors:  Sung Ho Jang; Han Do Lee
Journal:  Medicine (Baltimore)       Date:  2017-10       Impact factor: 1.889

7.  Whole Brain White Matter Microstructure and Upper Limb Function: Longitudinal Changes in Fractional Anisotropy and Axial Diffusivity in Post-Stroke Patients.

Authors:  Nicodemus Edrick Oey; Geoffrey Sithamparapillai Samuel; Joseph Kai Wei Lim; Antonius Mj VanDongen; Yee Sien Ng; Juan Zhou
Journal:  J Cent Nerv Syst Dis       Date:  2019-07-30

8.  The role of preoperative diffusion tensor imaging in predicting and improving functional outcome in pediatric patients undergoing epilepsy surgery: a systematic review.

Authors:  Jose Leon-Rojas; Isabel Cornell; Antonio Rojas-Garcia; Felice D'Arco; Jasmina Panovska-Griffiths; Helen Cross; Sotirios Bisdas
Journal:  BJR Open       Date:  2021-07-05

9.  Utility of Transcranial Magnetic Stimulation and Diffusion Tensor Imaging for Prediction of Upper-Limb Motor Recovery in Acute Ischemic Stroke Patients.

Authors:  Pradeep Kumar; Manya Prasad; Animesh Das; Deepti Vibha; Ajay Garg; Vinay Goyal; Achal K Srivastava
Journal:  Ann Indian Acad Neurol       Date:  2021-09-27       Impact factor: 1.383

Review 10.  White Matter Injury after Intracerebral Hemorrhage: Pathophysiology and Therapeutic Strategies.

Authors:  Chuanyuan Tao; Xin Hu; Hao Li; Chao You
Journal:  Front Hum Neurosci       Date:  2017-08-25       Impact factor: 3.169

  10 in total

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