CE19 - Technologies pour la santé

Multi-parametric quantitative imaging and modeling for improved comprehensive diagnosis of Thoracic Aortic Aneurysms – QUANTAAS

Multi-parametric QUANtitative imaging and modeling for improved comprehensive diagnosis of Thoracic Aortic AneurysmS

Despite the complexity of aneurysmal disease of the aorta, the primary elements for clinical risk stratification are the speed of growth and the lumen diameter. However, acute events (rupture/dissection) do occur in aneurysms not meeting the clinical criteria, indicating their low sensitivity, because they fail to provide a specific view of the local phenomena. Identifying the conditions related to a high risk of acute events is of major clinical concern, particularly for treatment decisions.

Investigate in a joint approach the phenomena involved in the longitudinal progression of aneurysmal disease to provide a better understanding of their roles and interactions to improve the diagnosis

The originality of the proposal lies in our strategy to associate multi-modality imaging with co-development of post-processing and computational methods in order to create an integrative analysis system that will take into account the different aspects of the disease. Furthermore, data on both the morphological and the physiological state of the wall (deformation and interaction with the blood flow and inflammatory markers) will be acquired simultaneously in a patient population followed over time. This approach has not been done previously and is thus completely adapted to the comprehensive study of the multi-factorial progression of vascular disease.

Our approach is to propose a multi-disciplinary investigation sensitive to local processes in the pathological vessel wall. We will focus on the improvement of MR imaging techniques, image post-processing and modeling in order to develop a non-invasive diagnosis tool specifically adapted for TAA. We aim to obtain in vivo measurements of blood flow, wall motion and inflammation using improved acquisition strategies that will be developed during the course of this project.
To achieve this goal, three main technical objectives have been identified:
i) to develop novel quantitative imaging method in MRI (magnetic resonance imaging) and in innovative hybrid MRI/PET (positron emission tomography) and use them to perform comprehensive non-invasive imaging of the thoracic aorta in patients with TAA,
ii) to develop a patient-specific computer model of the thoracic aorta to assess the wall’s mechanical properties; and
iii) to develop an integrative diagnostic tool that will combine the multi-parametric quantitative information (mechanical, morphological and functional parameters) to obtain an improved diagnosis and assessment of patient prognosis.

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Clinical manifestations resulting from the rupture of thoracic aortic aneurysms (TAA) have devastating effects, with 40% mortality before reaching the hospital. The mechanisms underlying aneurysm progression, although not well understood, have a multi-factorial nature. One hypothesis points to abnormal blood flow as a mechanical trigger. Another hypothesis points to a structural weakness of the wall itself with inflammation as the underlying cause leading to the weakening of the wall. Abnormal pressure conditions, as for example in hypertensive patients, could potentially induce rupture in a weakened aortic wall. Identifying the conditions related to a high risk of rupture and rapid growth is thus a major clinical concern.
Current diagnostic imaging modalities are limited to simple parameters that are poor predictors of progression and rupture in individual patients. It is thus clear that an improvement of current clinical diagnosis is necessary in order to better assess the risk of rupture. The first step in this direction must be focused on improving our understanding of the complex biological phenomena which requires a multi-disciplinary approach that is sensitive to local processes in the wall.
In the QUANTAAS project we aim at improving the knowledge of pathophysiological phenomena involved in TAA progression. We will develop novel MR imaging technique for dynamic imaging of the vessel wall and of the blood flow. We will follow patients presenting with aneurysms of the thoracic aorta using comprehensive non-invasive multi-parametric imaging (MRI and PET). Our strategy is to associate multi-modality imaging with co-development of post-processing and computational methods of wall mechanics analysis in order to create an integrative analysis system that will take into account the different aspects of the disease.
The advances in knowledge regarding the physio-pathological phenomena in aneurysmal disease are expected to directly improve stratification of patients at risk of rapid aneurysmal growth. Our approach is expected to enable the selection of patients that could benefit from primary prevention therapies compared to patients that could require invasive treatment procedures. Furthermore, the surgical treatment would be proposed more often in the chronic state instead of the surgical repair performed in acute state, which would significantly improve patient outcome and recovery time. Another expected impact is the patient specific adaptation of the frequency of follow up. Of particular importance is the socio-economic impact of early diagnosis for young patients suffering from Marfan syndrome, a genetic disorder, affecting the connective tissue, which predisposes to TAA. Furthermore, it should help identify potential targets for early pharmacological intervention that could slow the progression of aneurysms. Current diagnostic imaging only offers morphological information of the vascular disease. However, physiological changes are believed to precede the morphological ones, and thus may be an early marker of a treatment response. Our project will enable the evaluation of the physiological state of the vessel wall offering an early marker of the response to treatment in individual patients, and thus allowing clinicians to adjust the treatment on a shorter time scale, reducing the cost and potential side effects of unnecessary treatments.

Project coordination

Monica SIGOVAN (CENTRE DE RECHERCHE EN ACQUISITION ET TRAITEMENT D'IMAGES POUR LA SANTE)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

CREATIS - CNRS CENTRE DE RECHERCHE EN ACQUISITION ET TRAITEMENT D'IMAGES POUR LA SANTE

Help of the ANR 291,115 euros
Beginning and duration of the scientific project: - 48 Months

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