EchoMeasure

EchoMeasure is a medical imaging software that leverages machine learning to automate the processing and measurement of DICOM-compliant transthoracic cardiac ultrasound images. Its core purpose is to provide accurate, automated anatomical measurements and quality checks, aiding healthcare practitioners in clinical decision-making for adult patients.

A company named iCardio.ai has received a determination regarding their medical imaging software, EchoMeasure. This software, which functions as a medical image management and processing system, was found to be substantially equivalent to a legally marketed device. This determination permits iCardio.ai to market the EchoMeasure, subject to adherence to general controls and other applicable regulations for such products.EchoMeasure is designed to process previously acquired DICOM-compliant transthoracic cardiac ultrasound images, providing automated view classification, quality checks, and estimations of various cardiac anatomical measurements. The software, which incorporates machine learning algorithms, generates key measurements intended to support qualified cardiologists, sonographers, and other licensed healthcare practitioners in clinical decision-making for adult patients. Performance data indicated that the software met its predetermined accuracy limits, showing good agreement with established ground truth and consistent performance across different patient demographics and ultrasound scanner manufacturers.

AI Regulatory Concerns

Powered by

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. What are the specific machine learning models and training datasets used by EchoMeasure, and what are their individual contributions to accuracy and generalizability?; How does EchoMeasure's automated quality check mechanism identify and manage suboptimal image acquisition or artifacts that could impact measurement accuracy?; Beyond meeting predetermined accuracy limits, what is the clinical significance of EchoMeasure's measurement agreement, particularly in borderline cases or for tracking subtle changes over time?; Have any studies been conducted to assess the impact of EchoMeasure's integration into clinical workflows on physician efficiency, diagnostic throughput, or inter-observer variability compared to purely manual methods?; Are there plans for EchoMeasure to expand its capabilities to other cardiac imaging modalities (e.g., transesophageal echo, cardiac MRI) or to integrate with electronic health record systems for enhanced clinical utility?