LVivo IQS

The LVivo IQS is an AI-powered software module developed to improve cardiac ultrasound examinations by delivering real-time quality assessment for Right Ventricle images from the 4-chamber apical view. Its methodology utilizes an AI-based algorithm, provided as an accessory module with an API for integration, to objectively score image adequacy, thereby aiming to enhance the consistency and diagnostic value of echocardiograms, particularly in Point of Care Ultrasound settings.

The LVivo IQS, from DiA Imaging Analysis Ltd., is an AI-based software algorithm and Application Programming Interface (API) that functions as an extension to an existing cardiac imaging platform. Its specific purpose is to provide a real-time Quality Score for ultrasound images of the heart's Right Ventricle (RV) obtained from the 4-chamber apical view. This module is designed as a medical device accessory that can be integrated by other computer programmers into their legally marketed ultrasound imaging devices. The broader LVivo platform is intended for the non-invasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of cardiac structures and function in patients with suspected heart disease, with this new module enhancing its capability to deliver immediate feedback on image acquisition quality. The performance of this new RV-focused LVivo IQS module was validated through two primary studies. The first was a retrospective analysis comparing the algorithm's quality assessments of 49,623 ultrasound frames from 100 patient examinations against the evaluations of experienced sonographers, achieving a 77% overall agreement, thereby meeting its success criterion. The second study assessed its real-time utility in a Point of Care Ultrasound (POCUS) environment involving 182 patients, where scans were performed by medical interns. This evaluation demonstrated that 85% of images visually deemed adequate (ACEP score 3-5) by the interns also received at least a "Medium" quality score from the LVivo IQS system, and 92% of these algorithm-assessed clips were confirmed as clinically interpretable by expert cardiologists.

AI Regulatory Concerns

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• Q1. How does the LVivo IQS algorithm for Right Ventricle quality assessment differentiate between subtle variations in image quality that might impact diagnostic accuracy for specific RV pathologies (e.g., RV strain, dilation)?; What is the learning curve and variability in performance when LVivo IQS is used by operators with different levels of sonography experience, especially in challenging POCUS environments?; How does the real-time quality feedback from LVivo IQS specifically influence image acquisition times and the proportion of diagnostically adequate studies obtained by less experienced users?; Are there specific patient characteristics (e.g., body habitus, co-morbidities affecting image windows) or ultrasound machine settings that significantly impact the accuracy of the LVivo IQS quality scoring for the RV?; Beyond general interpretability, how does the LVivo IQS quality score correlate with the accuracy of quantitative measurements (e.g., RV dimensions, TAPSE) derived from the acquired images?