Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Cerebral small vessel diseases (SVD) are a very frequent group of disorders all characterized by alterations of the structure and/or function of small arteries, veins and capillaries. In these disorders, brain tissue lesions accumulate years before the occurrence of clinical symptoms which can be devastating such as stroke, cognitive disturbances and gait disorders. So far, chronic hypoperfusion was considered to be responsible for the accumulation of such lesions. However, recent results have suggested that the lesions underlying white matter hyperintensities (WMH), the most common MRI marker of SVD visible on conventional MRI in quite every subject with SVD long before the occurrence of clinical events, may depend on the considered brain area and may correspond to various mechanisms. Some WMH may even be associated with less severe clinical manifestations.The aim of the present study is to identify different types of WMH by studying 100 patients with different forms of SVD with the most advanced MRI (including ultra-high-resolution imaging at 7 Tesla, new diffusion protocol, sodium MRI, contrast-enhanced angiography and relaxometry and post-processing techniques), and post-processing techniques (machine learning, deep learning, artificial intelligence).
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental arm | Other |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Experimental Arm | Other |
|
| Measure | Description | Time Frame |
|---|---|---|
| Percentage of patients with a different form of white matter hyperintensities (WMH) | The different forms of white matter hyperintensities will be assessed and identified using MRI imaging.The pattern of co-variation of structural, functional, metabolic imaging modalities, estimated in each voxel of a reference space, both inside and outside the WMH, will be compared through massive statistical approaches, controlled, for multiple testing | at the time of specific imaging (between Day 1 to Day 60) |
| Measure | Description | Time Frame |
|---|---|---|
| Frequency of different WMH subtypes in different types of small cerebral vessel disease | Distribution of white matter hyperintensities in different brain areas according to the small cerebral vessel disease | at the time of specific imaging (between Day 1 to Day 60) |
| Frequency of large tract involvement |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Eric Jouvent, Pr | Contact | 0149956529 | eric.jouvent@aphp.fr | |
| Matthieu Resche-Rigon, Pr | Contact | 0142499742 | 0142499742 | matthieu.resche-rigon@univ-paris-diderot.fr |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hopital Lariboisière | Recruiting | Paris | 75010 | France |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D059345 | Cerebral Small Vessel Diseases |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
|
Large tratreconstructed from diffusion imaging) by WMH depending on the the small cerebral vessel disease |
| at the time of specific imaging (between Day 1 to Day 60) |
| Global cognitive function | The global cognitive functions will be assessed using MOCA. The MoCA assesses different cognitive domains: attention and concentration, executive functions, memory, language, visuoconstructional skills, conceptual thinking, calculations, and orientation to time and place | at inclusion |
| Language | Language assessment will be done using LAST and Boston Naming Test | at inclusion |
| Spatial exploration | The neglect and spatial exploration will be assessed with bells test from the BEN neglect battery | at inclusion |
| Spatial memory | Spatial memory will be assessed using the brief visual-spatial memory test (BVMT-R) | at inclusion |
| Visual memory | Visual memory will be assessed using the brief visual-spatial memory test (BVMT-R) | at inclusion |
| Episodic verbal memory | Episodic verbal memory test by the RL RI 16 | at inclusion |
| Working memory | Working memory will be evaluated by the working memory index of the WAIS-IV | at inclusion |
| Executive function | Executive function will be assessed by the versions A and B of the Trail Making Test | at inclusion |
| Attentional Performances status | Attentional Performances will be assessed using a battery on a computer which tests different attentionnal and executive function | at inclusion |
| Depression and Anxiety status | Depression and anxiety will be assessed using Hospital Anxiety and Depression Scale (HADS) questionnaire. The HAD scale is a self-assessment scale for detecting states of depression and anxiety in the setting of an hospital medical outpatient clinic. HADS is a self-administered scale of 14 items which assessed levels of depression and anxiety, divided into 2 subscales of 7 items (Anxiety or HADS-A, Depression or HADS-D). Each item is scored on a scale of 0 to 3. A score is generated for each of the two sub-scales (sum of the 7 items, ranging from 0 to 21). Limit scores, for each of the scores, distinguish: non-cases or asymptomatic ones (score ≤ 7); probable or borderline cases (score 8-10); clearly or clinically symptomatic cases (score ≥ 11). | at inclusion |
| Apathy status | Apathy status will be assessed using the Starkstein scale | at inclusion |
| Pulse wave Velocity count | Arterial stifness will be assessed by measuring the pulse wave velocity | at inclusion |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |