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临床试验/NCT04434898
NCT04434898已完成不适用

The Assessment of the Diagnosis and Prognosis of Patients With Alzheimer Disease or Parkinson Disease With Cognitive Impairment by Using Diffusion MRI

Chang Gung Memorial Hospital1 个研究点 分布在 1 个国家目标入组 212 人开始时间: 2017年10月1日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
212
试验地点
1
主要终点
An objective image-based evidence for the diagnosis, differential diagnosis and prognosis of Parkinson's Disease

研究概览

简要总结

The hypothesis is that the differential extent of microstructural damages in the affected brain regions can be specific to the disease of interest and could reflect the clinical severity. Therefore, the investigator propose that whole brain parcellation of diffusion MRI can be used to improve diagnosis and prediction of clinical outcomes in Parkinson's Disease.

  1. A regression model between clinical severity and two year clinical outcomes and diffusion properties from multiple parcellated regions will be developed.
  2. Blind validation will be performed.

详细描述

Currently, Alzheimer's Disease (AD) and Parkinson's Disease (PD) are diagnosed mainly by neurologists, based on clinical symptoms. However, there are no objective criteria available for their diagnosis. Although magnetic resonance imaging (MRI) is often employed in conjunction with clinical judgement, the images are mostly used to eliminate other diseases, rather than to confirm the diagnosis. Other imaging methods, such as Position Emission Tomography or Computed Tomography, may help in the diagnosis of AD and PD, but have harmful effects on the human body.

Diffusion MRI, and in particular Diffusion Tensor Imaging, are often employed in the evaluation of changes in connectivity in the central nervous system. As it is non-invasive and does not involve radiation, diffusion MRI is suitable to be used for longitudinal studies. It has been used for the evaluation of fiber density and cross-section in many diseases, including epilepsy, multiple sclerosis, and brain tumours, with good results. Several measurements can be obtained from diffusion MRI, including fractional anisotropy and mean, radial and axial diffusivity. Changes observed in diffusion MRI are related to changes in water content inside and outside of cells, so an increase in the diffusion coefficient could reflect an increase in cell membrane permeability, which may be attributed to cell death and rupturing. A higher diffusion coefficient may be indicative of more neuronal death. Therefore, using diffusion kurtosis, the investigator may be able to improve diagnoses of PD.

From research on AD, the investigator found that the diffusion coefficient of patients with mild cognitive impairment and AD is significantly higher than control patients. The investigator will carry out analysis on 90 brain regions, including the fusiform gyrus, hippocampus, parahippocampus and cingulum. The listed regions have been observed to have differences in mean diffusivity for AD patients and those at risk for AD, as compared to normal controls. In previous studies, overlaps were observed between areas where the mean diffusivity increases and areas where brain regions shrink, but there are more regions and larger areas where the diffusion coefficient increases. Therefore, the mean diffusivity may be a more suitable clinical index than the current method of brain volume. In addition, there is a correlation between increased mean diffusivity and the severity of mild cognitive impairment or AD. Amyloid deposition is consistent with disease progression, further supporting that mean diffusivity can be used to reflect the progression of mild cognitive impairment and AD.

The investigator plan to use Compressed Sensing to increase the speed of diffusion MRI. This includes image preprocessing, acquisition of Compressed Sensing observations, rebuilding the model, and reconstructing the algorithm. The investigator also plan to overcome the current limitations of region-of-interest analysis. One way of achieving this is by voxelwise analysis, however it has limitations caused by normalization of the image to a template space, and possible problems in tractography caused by rotation or distortion of the image. Furthermore, the use of a study specific template prevents the results from being available in Brodmann or Talairach coordinates. Most importantly, voxel analysis is not based on brain regions, so it is difficult to determine the properties of each region, and according to our algorithm, a large amount of voxel data would greatly reduce the resolution of the statistics and cause problems in statistical analysis. Therefore, the investigator have to use a common standard space, and develop a suitable imaging technique.

The investigator choose to use Automatic Anatomical Labelling (AAL), as this is a commonly used system used in neuroscience research. The investigator also use the Montreal Neuroscience Institute 152 Template (MNI152) as out standard template. In the imaging and processing of the whole brain, the investigator use Affine Transformation, as this is commonly used for MRI and diffusion MRI. This includes Camino, FSL, and SPM. The investigator will study how the aging of a healthy brain changes the diffusion MRI and make comparisons between aging in males and females.

研究设计

研究类型
Observational
观察模型
Case Control
时间视角
Prospective

入排标准

年龄范围
50 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • All subjects should meet the following criteria:
  • Between 50-80 years old
  • Right-handed
  • Able to understand study requirements and give informed consent
  • Agree to return for follow-up checks
  • Able to suspend intake of medication for at least 12 hours

排除标准

  • Cardiac pacemaker or defibrillator implantation Intracranial metal device implantation
  • Other major systemic diseases, such as renal failure, heart failure, stroke, AMI/unstable angina, poorly controlled diabetes mellitus, poorly controlled hypertension
  • Alcohol or drug abuse
  • Moderate to severe dementia
  • Severe movement disorders
  • Imaging data is similar to a nuclear medical examination, exclusion criteria is any abnormality that may affect cognitive function as reflected in computer tomography or MRI records, such as hydrocephalus or encephalitis. Mild cortical atrophy is acceptable.
  • History of intracranial surgery including thalamotomy, pallidotomy, and/or deep brain stimulation
  • Major physical or neuropsychiatric disorders
  • Structural abnormalities that may cause dementia, such as cortical infarction, tumour, or subdural hematoma
  • Besides medication for Parkinson's Disease, taking other medication with substances that can pass through the blood-brain barrier
  • Besides medication for Parkinson's Disease, taking other medication for more than 10 years
  • Treatments or concurrent illnesses other than Alzheimer's Disease that could interfere with cognitive function
  • Meet the criteria for dementia (DSM-IV)
  • Head trauma with loss of consciousness greater than 10 minutes
  • Severe loss of sensation

结局指标

主要结局

An objective image-based evidence for the diagnosis, differential diagnosis and prognosis of Parkinson's Disease

时间窗: end of the third year

The following will be measured for the diagnostic performance of diffusion MRI: 1. Regression between cognitive performance and baseline diffusion MRI using Pearson correlation 2. Leave one out cross validation

次要结局

  • Imaging(end of the third year)
  • Deep learning techniques(end of the third year)
  • Prognosis(end of the third year)

研究者

发起方
Chang Gung Memorial Hospital
申办方类型
Other
责任方
Principal Investigator
主要研究者

Wang . Jiun-Jie

Study Principal Investigator

Chang Gung Memorial Hospital

研究点 (1)

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