The artificial intelligence (AI)-powered EchoGo Amyloidosis can reportedly detect cardiac amyloidosis by assessing a single echocardiogram.
The Food and Drug Administration (FDA) has granted Breakthrough Device Designation for EchoGo Amyloidosis (Ultromics), which provides artificial intelligence (AI) assessment of echocardiograms to help diagnose cardiac amyloidosis.
While cardiac amyloidosis can be challenging to diagnose due to a heterogenous array of subtypes, including ATTR amyloidosis (transthyretin amyloidosis) and AL amyloidosis (light chain amyloidosis), Ultromics said the EchoGo Amyloidosis modality (developed with support from Janssen Biotech, Inc.) can detect the condition based on one echocardiogram.
Ultromics and Janssen Biotech said the EchoGo Amyloidosis platform is an important innovation in diagnosing a disease that has five-year mortality rates ranging from 44 to 65 percent without early detection.
“While treatments exist to help slow or halt the progression of cardiac amyloidosis, underdiagnosis in the early stages of disease is a huge challenge,” noted Najat Khan, Ph.D., the chief data science officer and global head of Strategy and Operations at Janssen Research and Development, LLC. “When applied to routine tests like echocardiograms, artificial intelligence is demonstrating exciting potential to help facilitate earlier disease detection with the goal of connecting patients with treatment sooner and, ultimately, driving better health outcomes.”
Ultromics noted that EchoGo Amyloidosis platform is intended to be included within the company’s EchoGo Platform. Currently in the midst of preparing regulatory submission of the modality, Ultromics said the EchoGo Amyloidosis platform could receive clearance for commercialization by early 2024.
(Editor’s note: For related content, see “Study Finds AI More Effective Than Sonographer Interpretation of Cardiac Function on Echocardiograms” and “Adjunctive AI Software for Cardiac Ultrasound Gets FDA Nod.”)
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.