跳至主要内容
临床试验/NCT05177523
NCT05177523招募中不适用

INsIDER: Imaging the Interplay Between Axonal Damage and Repair in Multiple Sclerosis

University Hospital, Basel, Switzerland1 个研究点 分布在 1 个国家目标入组 300 人开始时间: 2018年9月4日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
发起方
入组人数
300
试验地点
1
主要终点
MRI- change in axonal integrity and organization over 2 years in aMS, naPMS and HC, by using machine learning techniques

研究概览

简要总结

This project is to:

  1. Quantify differences in axonal integrity and organization in aMS versus naPMS patients.
  2. Quantify changes in axonal integrity and organization in aMS versus naPMS patients over a two-year period.
  3. Validate the combination of imaging parameters that best differentiate aMS versus naPMS patients using histopathology.

详细描述

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system characterized by multifocal inflammatory infiltrates, microglial activation and degradation of oligodendrocytes, myelin and axons. Clinical MS categories exhibit variable amount of central nervous system (CNS) damage and repair, depending on numerous variables including genetic, immunological, pathological and environmental factors.

Therefore, understanding the interplay between axonal damage (i.e. axonal demyelination/degeneration/loss/disorganization) and (ii) axonal repair (i.e. axonal remyelination/reorganization) in living MS patients may be the key to understand disease progression, to establish accurate disease monitoring criteria and to predict disease response to future reparative therapies. New in-vivo methods are necessary to elucidate the interplay between axonal damage and repair in the brain of living patients with MS. Advanced MRI (aMRI) permits a multifaced quantification of the various components of the axons and their organization. Neurite Orientation Dispersion and Density Imaging (NODDI) and Diffusion Kurtosis (DK) are new approaches in clinical research This study is to identify in vivo the specific neuropathological pattern of axonal damage and repair exhibited by active MS (aMS) and non-active progressive MS (naPMS) patient by leveraging the information provided by model-based diffusion metrics (NODDI, DK), Magnetization Transfer Imaging (MTI), Multi-echo Susceptibility-Based imaging (SBI), Myelin Water Imaging (MWI) and quantitative T1 relaxometry (qT1). These advanced MRI contrasts provide complementary and partially redundant information about the axonal structure and its organization (i.e. density and orientation of axons and dendrites in the brain tissue, axonal integrity and myelination, presence of myelin and iron, and brain tissue architecture). Therefore, their combination may prove high sensitivity and specificity to axonal damage and repair.

This project has 3 main aims:

Aim 1. Quantify differences in axonal integrity and organization in aMS versus naPMS patients.

Aim 2. Quantify changes in axonal integrity and organization in aMS versus naPMS patients over a two-year period.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

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

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

MRI- change in axonal integrity and organization over 2 years in aMS, naPMS and HC, by using machine learning techniques

时间窗: at baseline and 2 years (+/- 3 months) after baseline

After magnetic resonance (MR) data preprocessing (image denoising, standardization, bias field correction) classical machine learning techniques will be used to classify a number of MRI metrics which will be averaged over a number of regions of interest (ROIs) including (i) normal-appearing white and brain matter in brain lobes and cervical spinal cord, (ii) basal ganglia, (iii) thalamus, (vi) cerebellum, MS lesions. Complex input data (voxels/patches) will be generated to learn from, then a deep learning model for supervised classification will be defined to identify the combination of aMRI parameters that characterize aMS, naPMS and HC.

次要结局

  • Change in Hospital Anxiety and Depression Scale (HADS)(at baseline and 2 years (+/- 3 months) after baseline)
  • Change in Symbol Digital Modalities Test (SDMT)(at baseline and 2 years (+/- 3 months) after baseline)
  • Change in auditory verbal learning and memory test/ Verbaler Lern- und Merkfähigkeitstest (VLMT)(at baseline and 2 years (+/- 3 months) after baseline)
  • Change in Brief Visuospatial Memory Test (BVMT)(at baseline and 2 years (+/- 3 months) after baseline)
  • Change in MUSIC Test(at baseline and 2 years (+/- 3 months) after baseline)

研究者

发起方
University Hospital, Basel, Switzerland
申办方类型
Other
责任方
Sponsor

研究点 (1)

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