Artificial Intelligence to Assist the Echocardiographic Identification of Transthyretin Cardiac Amyloidosis
The goal of this study is to develop an algorithm using artificial intelligence (AI) to assist identification of potential ATTR-CM cases using routine transthoracic echocardiography. The main questions it aims to answer are: * is the algorithm able to diagnose ATTR-CM * is the algorithm able to diagnose different types of ATTR-CM (ATTRv, ATTRwt) This is a non interventional study. Participant' echocardiographies will be, after deidentification, used to train, valid and test the algorithm.
• Cardiac transthyretin amyloidosis diagnosed on the classic criteria:
‣ Absence of monoclonal immunoglobulin AND
⁃ Presence of a bisphosphonate scintigraphy with enhancement in the cardiac area OR
• 2-Presence of a cardiac biopsy showing transthyretin (Congo red positive) cardiac amyloidosis (demonstrated either by immunostaining or by mass spectrometry) OR 3-Presence of a peripheral biopsy showing transthyretin amyloidosis (see above) associated with cardiac infiltration (parietal thickness \>12mm without other cause of cardiac hypertrophy)
• No opposition to research
• Indication for transthoracic echocardiography as part of cardiological follow-up
• Patient affiliated with social security
• Patient's agreement to participate in the research and signature of the consent form.
• Technical conditions of the examination and echogenicity allowing acquisition of good quality echocardiographic images, allowing post processing