InVision Precision Cardiac Amyloid

The InVision Precision Cardiac Amyloid device is an automated, machine learning-based Software as a Medical Device designed as an adjunctive screening tool to identify signs of cardiac amyloidosis from echocardiogram videos in adults aged 65 and over. Its core methodology involves leveraging artificial intelligence to provide alerts for potential cardiac amyloidosis, thereby facilitating timely referral for confirmatory investigations while emphasizing that patient management should not solely rely on its results.

InVision Medical Technology Corporation has secured a determination of substantial equivalence for its "InVision Precision Cardiac Amyloid" device, enabling its market entry as a Class II adjunctive cardiovascular status indicator. This regulatory milestone, concluded on May 21, 2025, affirms the device's compliance for commercial distribution and its equivalency to existing legally marketed predicate devices. The "InVision Precision Cardiac Amyloid" is an automated, machine learning-based Software as a Medical Device (SaMD) designed for screening adults aged 65 and over undergoing echocardiography. Its purpose is to provide physicians with information that alerts them for potential cardiac amyloidosis, prompting referral for confirmatory investigations, though it is not intended as a sole diagnostic tool for patient management decisions. The device's functionality and safety have been confirmed through comprehensive performance, human factors, and cybersecurity testing, and the company is required to adhere to ongoing regulatory provisions including registration, device listing, good manufacturing practices, labeling, medical device reporting, and unique device identification.

AI Regulatory Concerns

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

• Q1. How does the machine learning algorithm specifically identify signs of cardiac amyloidosis from echocardiogram videos?; What are the sensitivity and specificity metrics of the InVision Precision Cardiac Amyloid device in its clinical validation studies, particularly compared to current diagnostic standards?; What is the defined pathway for confirmatory investigations triggered by the device's alert, and how has this pathway improved patient outcomes in pilot studies?; What specific human factors and cybersecurity testing protocols were employed to ensure the device's safety and usability in a clinical setting?; Given its classification as an adjunctive screening tool, what are the guidelines or recommendations for clinicians on integrating the device's output into broader patient management decisions to avoid sole reliance?