Идёт набор NCT06260488

Histological Segmentation of the Superficial Femoral Artery From Microscan to CT Using Artificial Intelligence

Без фазы С лечением Peripheral Artery Disease Femoropopliteal Stenosis

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают: В протоколе указаны: Endovascular surgery.
Кому может быть актуально: Состояния в реестре: Peripheral Artery Disease, Femoropopliteal Stenosis. Базовые параметры: от 18 лет · Все.
Что важно проверить: Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится: Франция
Следующий шаг: Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →

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Официальное название

Histological Segmentation of the Superficial Femoral Artery From Microscan to CT Using Artificial Intelligence: a Feasibility Study (CTPred)

Обзор

The femoropopliteal artery segment (FPAS) is one of the longest arteries in the human body, undergoing torsion, compression, flexion and extension due to lower limb movements. Endovascular surgery is considered to be the treatment of choice for the peripheral arterial disease, the results of which depend on the physiological forces on the arterial wall, the anatomy of the vessels and the characteristics of the lesions being treated. The atheromatous disease includes, in a simple way, 3 categories of plaques: calcified, fibrous, and lipidic. The study of these plaques and their differentiation in imaging and histology in the FPAS has already been the subject of research. To treat them, there are angioplasty balloons and stents with different designs and components, with different mechanical properties and different impregnated molecules. There is no non-invasive method (imaging) to accurately differentiate lesions along the FPAS. The analysis is performed from the preoperative CT scan, but there are high-resolution scanners that allow a quasi-histological analysis of the tissue. This microscanner can be used ex vivo. In the framework of a project, the learning algorithm was be créated (Convolutional Neural Networks) to automatically segment microscanner slices: after taking FPAS from amputated limbs, we correlated ex-vivo microscanner images of the arteries with their histology. The correlation was then performed manually between the microscanner images, and the histological sections obtained. the algorithm well be trained on these slices and validated its performance. The validation of the CT and microscanner concordance was the subject of scientific publications.

Подробное описание

The aim of this study is to evaluate the technical feasibility of histological segmentation by the FPAS algorithm from CT. The results of this study will provide initial data to evaluate the interest of a subsequent larger scale study to validate the diagnostic capabilities of automated segmentation

Вмешательства

Процедура Endovascular surgery
routine endovascular surgery and FPAS harvesting from amputated limbs to evaluate the technical feasibility of histological segmentation by the FPAS algorithm from CT

Первичные конечные точки

Assessing the feasibility of histological segmentation of the superficial femoral artery on preoperative microscanner using artificial intelligence [Срок оценки: 1 hour]

Критерии участия

Критерии включения

Male or female of legal age
Subject with a planned transfemoral amputation in the vascular surgery department of the Hôpitaux Universitaires de Strasbourg as standard care
Subject with a CT as part of standard care
Subject who has given his/her non-opposition to participate in the study