Ultrasound, scanner, MRI, PetScan… To see the disease better, doctors have a wide and evolving range of tools. Yesterday a simple aid to diagnosis, imaging now stands out as an essential tool both in improving diagnoses and in controlling treatments. Imaging is now able to identify abnormal mechanisms within tissues, ie the pathophysiological processes at the origin of diseases that can be diagnosed earlier and more precisely. Finally, imaging is now a major interface between artificial intelligence and medicine.

The advantages of the IHU ICAN

The IHU-ICAN positions itself as a a key player in cardiovascular and metabolicdisease imaging thanks to its expert teams of researchers and clinicians and the establishment of a a cardiovascular and metabolic imaging platform, unique in Île-de-France, with the acquisition in 2020 of a state-of-the-art 1.5T cardiovascular MRI

Artificial Intelligence (AI) offers medical imaging new perspectives because it allows to go further in the analysis and interpretation of imagery thanks to its ability to integrate, combine and interpret a multitude of data. in a very short time.

The AI is able to integrate data from the patient’s history, the history of their disease, the clinical context, the biological parameters and the data from other paraclinical examinations and previous examinations. The experience gained over the integration of data coupled with data from the existing medical literature allows AI to develop new diagnostic strategies, prognostic evaluation and personalized patient management.

From now on, the new concept of imaging “biomarker” is firmly established, and the advanced phenotyping made possible by techniques such as MRI, scanner, ultrasound or optical imaging now makes it possible to open unprecedented windows of exploration in humans, particularly in the field of cardiometabolic diseases.

Projects led by ICAN teams

EIT Health / CMRAI

It causes more deaths than road accidents, and yet we rarely talk about it. Silent, the aortic aneurysm is discovered nine times out of ten by chance, often during an ultrasound. Can we better prevent aortic ruptures? This is the challenge taken up by the CMRAIproject led by the IHU ICAN and Sorbonne University and funded by EIT Health.

The aortic aneurysm is defined by the localized dilation of the aorta which constitutes a risk of rupture resulting in the death of the patient. If diagnosed early enough, treatment is often based on the management of high blood pressure. In other cases, a surgical procedure is considered to treat the aneurysm as soon as possible. But unfortunately the diagnosis is often late, made during the rupture, and constitutes a dramatic event associated with a mortality rate of 80-90%.

IHU-ICAN is at the initiative of the CMRAI projectThis project is conducted with 9 other European partners: 7 academic partners: Sorbonne University (France), Assistance Publique – Hôpitaux de Paris (France), Hanover Medical School (Germany), Medical University of Vienna (Austria), Vall d’Hebron Hospital (Spain), Santa Cruz Hospital (Portugal), University of Sciences of Lisbon (Portugal), and 2 industrial partners: Imageens (France) and Siemens Healthineers (Germany) Translated with (free version)

The CMRAI project aims to improve aortic aneurysm detection, therapeutic decision making and management using Magnetic Resonance Imaging (MRI) coupled with automated and multiparametric analysis of the aorta.

Supported by Prof. Alban Redheuil, head of Cardiovascular and Thoracic Imaging (ICT) at the Pitié-Salpêtrière Hospital and medical head of the ICAN Imaging platform, Dr. Nadjia Kachenoura, head of the Cardiovascular Imaging (iCV) team at the Biomedical Imaging Laboratory (LIB) and scientific head of the ICAN Imaging platform, and Ted Baldwin, CEO of the Imageens strategy, the CMRai projectai involves several IHU ICAN departments:

This project will therefore make it possible to define, from the first signs of the disease, an aortic aneurysm risk score for each patient, and therefore to define a follow-up and personalized management strategy.

CAST AF on Cardiac Arrhythmia

Cardiac arrhythmias or abnormal heart rhythms are common and a leading cause of sudden death from stroke and heart failure. The CATS AF project focuses on the most common cardiac arrhythmia, atrial fibrillation. Atrial fibrillation is favored by an often very localized remodeling of the heart muscle, difficult to identify, which is necessary to identify patients at risk and to institute early personalized treatment of the risk of arrhythmia. The CAST AF project consists of comparing MRI imaging data to characterize the myocardial tissue, its histology, in particular fibrosis and the presence of fatty tissue, its contractility (strain) and a very high resolution mapping of electrical activity. of the heart recorded using probes inserted inside the heart in patients treated for the treatment of atrial arrhythmia.


The IHU ICAN has close ties with the biomedical imaging laboratory (LIB SU, INSERM, CNRS) which develops new image analysis software such as the HeartFun software which makes it possible to see the blood flow in the aorta ( 4D flow imaging) or software that can analyze the deformation of the walls of the heart, which provides information on the trophicity of the heart muscle (strain). The IHU ICAN offers all the expertise and the regulatory medical environment to validate this software in patients and define their interest in clinical practice.