AI-echo to track disease progression in ATTR-CM
Royal Free Hospital, London
(Presenter)
Transthyretin cardiac amyloidosis (ATTR-CM) is a progressive and fatal cardiomyopathy with a rising number of diagnoses over the past two decades and a highly variable clinical course. While echocardiography has shown potential for tracking disease progression, variability in manual measurements by clinicians currently limits its use for longitudinal monitoring. As a result, no established echocardiographic parameters are available to assess disease progression in cardiac amyloidosis.
Presented at the Late Breaking Science session at EuroEcho–Imaging 2024, this study aimed to assess the association between changes in AI-measured echocardiographic parameters and prognosis in a large cohort of ATTR-CM patients.
Using Us2.ai’s fully automated machine learning algorithm, the study analyzed echocardiographic DICOM images without human interaction. A twelve-month survival analysis was conducted to examine the relationship between changes in echocardiographic parameters and mortality in ATTR-CM patients followed at the National Amyloidosis Centre (NAC) from 2007 to 2021.
The results highlight the potential of AI to track disease progression and treatment response using echocardiography in patients with ATTR-CM.
Results
Conclusion
