Accelerated Diffusion MRI for Diagnosis of Hungtington Disease
|The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.|
|ClinicalTrials.gov Identifier: NCT01884181|
Recruitment Status : Recruiting
First Posted : June 21, 2013
Last Update Posted : August 4, 2016
The hypotheses of the project are
- Diffusion MRI using compressed sensing could have reduced motion sensitivity and improved susceptibility related artifact because of accelerated acquisition.
- The macromolecule deposition in the brain of patients with Huntington Disease (HD) can lead to changes detectible by diffusion MRI.
To validate the hypothesis that the new accelerated diffusion MRI technique could produce a new biomarker for HD, patients with Huntington Disease will be recruited. The diffusion index will be calculated using accelerated acquisition. The diagnostic performance will be evaluated for data reconstructed with and without acceleration. The correlation with the disease severity will be assessed.
|Condition or disease|
Diffusion magnetic resonance imaging has emerged as a sensitive, noninvasive tool for assessing the abnormalities in the central nervous system. Applications have been reported in many neurological disorders. However, because of the motion-sensitizing diffusion gradient and the prolonged diffusion encoding time, clinical practice could be difficult especially in patients with motor disorders such as Huntington Disease. Currently there existed no useful biomarker which could reflect either the disease progression or severity of Huntington disease. There is a growing interest in imaging Huntington disease using diffusion magnetic resonance imaging because of its capability to depict the micro-environmental changes.
Unfortunately the excessive motor abnormality such as chorea yields the acquisition of diffusion magnetic resonance imaging unfeasible in a clinical setting. The diffusion MRI with compressed sensing demonstrated reduced motion sensitivity and improved susceptibility related artifact because of the accelerated acquisition. Because of the reduced acquisition time, diffusion MRI in patient with Huntington Disease would be possible. It is therefore expected that the macromolecule deposition in the brain of patients with HD can lead to detectible changes in diffusion properties. The accelerated diffusion MRI techniques will be used to acquire data from healthy volunteers and patients with Huntington disease. The aim of the study is to develop and optimize a novel accelerated diffusion Magnetic Resonance Imaging (MRI) technique using advanced compressed sensing techniques. The joint sparsity constraint algorithm will be implemented in an in-line reconstruction platform for the diffusion MRI processing.
The second aim is to test the efficiency of the new accelerated diffusion MRI technique from phantom and in healthy human. Finally to validate the hypothesis that the new accelerated diffusion MRI technique could produce a new biomarker for HD, patients with Huntington Disease will be recruited. The diffusion index will be calculated using accelerated acquisition. The diagnostic performance will be evaluated for data reconstructed with and without acceleration. The correlation with the disease severity will be assessed. A risk management report will be concluded at the end of project execution for registration in the department of health. The acceleration diffusion MRI could provide new insight to the etiology of the disease. The in-line image reconstruction platform could be used for pediatric or psychiatric patients who cannot hold still in the scanner for a prolonged period and in patients with movement disorders.
|Study Type :||Observational|
|Estimated Enrollment :||80 participants|
|Observational Model:||Case Control|
|Official Title:||Accelerated Diffusion MRI as a Potential Image Based Biomarker for Hungtington Disease|
|Study Start Date :||January 2014|
|Estimated Primary Completion Date :||December 2017|
|Estimated Study Completion Date :||December 2017|
Huntington Disease Group
Established diagnosis by a neurological examination and genetic assessment of CAG expansion in the Htt gene.
- Feasibility study on healthy human. [ Time Frame: the 30th month ]
Diffusion MRI will be acquired form healthy volunteers.
Images will be acquired with and without compressed sensing DTI The reproducibility of compressed sensing diffusion MRI will be assessed in human
- Diagnosis Huntington Disease [ Time Frame: end of the fourth year ]
- Diffusion MRI will be acquired from patients with HD
- Diagnostic performance will be analyzed when compared to the healthy control in Validation II in a case control study.
- The correlation with disease severity and the image finding will be examined. Approach
1. ROI selected from basal ganglia 2. The receiver operative characteristic analysis will be performed and the area under curve will be determined. 3. The disease severity will be assessed by Unified Huntington Disease Scale. The correlation will be assessed by Spearmann's Ranked correlation.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01884181
|Contact: Jiun-Jie Wang, PhDfirstname.lastname@example.org|
|Contact: Chiung-Mei Chen, PhD||+886-328-1200 ext email@example.com|
|ChangGung Memorial Hospital, Linkou||Recruiting|
|Tao Yuan, Taiwan, 333|
|Contact: Yong-Ting Kuo, BSc +886-3-3281200 ext 8408 firstname.lastname@example.org|
|Principal Investigator: Jiun-Jie Wang, PhD|
|Sub-Investigator: Chiung-Mei Chen, PhD|
|Sub-Investigator: Yih-Ru Wu, MD|
|Sub-Investigator: Yi-Ming Wu, MD|
|Sub-Investigator: Ho-Fai Wong, MD|
|Sub-Investigator: Yao-Liang Chen, MD|
|Sub-Investigator: Jur-Shan Cheng, PhD|
|Principal Investigator:||Jiun-Jie Wang, PhD||ChangGung University|