The purpose of the study is to use a simple photography of conjunctival vessels to search for an association between conjunctival vessels abnormalities and the load of small vessel disease as quantified by MRI in patients with TIA s and minor strokes. The artificial intelligence (AI) tools will permit to classify abnormalities of conjunctival vessels that predict the load of small vessel disease in TIAs and strokes.
Small vessel disease is a risk factor of ischemic or hemorrhagic stroke and a direct cause of lacunar and hemorrhagic infarcts. Moreover, it is associated of cognitive impairment, like psychomotor retardation, deficits of attention, planning, and set-shifting, and dysexecutive syndrome. This disease affects the cerebral vessels of small diameters. Magnetic Resonance Imaging (MRI) is the gold standard for the diagnosis and the screening of this pathology. However it is an imaging with limit access and high cost. Vessels of bulbar conjunctiva have a small caliber like the small cerebral vessels and have the same origin: carotid arteries. They are easy to study with photography. The analysis of these vessels may be a new way of screening the small vessel disease, easier to use than MRI. Retinal vascularization is also easier to study with photography of fundus without dilatation by retinograph. Several studies already demonstrated an association between retinal abnormalities and load of small vessel disease. However, no relation was established between these modification and impairment of conjunctival vascularization in this cerebral pathology although those have the same arterial origin and vascular diameters. The strategy is to take a picture of temporal bulbar conjunctiva and fundus for patients with symptoms of TIA and minor stroke with all etiologies. Patients will be classified according to Fazekas staging and presence of lacunar infarcts. First, photography of bulbar conjunctiva will be analyzed by an artificial intelligence in " deep learning " to demonstrate a correlation between abnormalities of conjunctival vessels and staging of small cerebral disease. After that, photography of fundus will be analyzed with the same AI to search a correlation between conjunctival and retinal vascularization in small vessel disease. The present study will include patients with symptoms of TIAs and minor strokes coming at clinic of TIA in University Hospital Toulouse. A consultation by a neurologist will be done, than MRI will be prescribed for each of them. After a therapeutic care, they will go to the ophthalmologist for a photo of their bulbar conjunctival of each eye and photography of fundus without dilatation. The follow up will be realized the same day.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
850
patient will have photo of their bulbar conjunctival of each eye and photography of fundus without dilatation
NASR Nathalie
Toulouse, France
RECRUITINGNumbers of conjunctival vascular abnormalities
Association between numbers of conjunctival vascular abnormalities and the load of small cerebral disease highlighted by neural network in " deep learning ". This outcome is collected after the end of the inclusion of all patients.
Time frame: day 1
Classification of different types of vascular abnormalities in different grades of small vessel disease
Classification of different types of vascular abnormalities found in different grades of small vessel disease using the same neural network and also their association with cerebral macroangiopathy
Time frame: Day 1
Absence of difference between the 2 eyes
Research for the absence of difference of abnormalities between both eyes
Time frame: Day 1
same stade of vascular abnormalities
Association between abnormalities detected in fundus with retinograph and conjunctival vessels morphology in assessment of load of small vessel disease.Same sensitivity and specificity as conjunctiva photographs for each stage of vascular abnormalities
Time frame: Day 1
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