CorVista® System

The CorVista® System is a non-invasive diagnostic aid that employs a machine learning algorithm to analyze synchronously acquired vectorcardiography (VCG) and photoplethysmography (PPG) signals, along with patient demographics, to indicate the likelihood of significant coronary artery disease in symptomatic adult patients. The system aims to enhance clinical decision-making by providing an adjunctive tool with demonstrated 88% sensitivity and 51% specificity, assisting in the diagnostic pathway for patients with suspected CAD.

The CorVista® System is a non-invasive medical device system designed to assist healthcare providers in evaluating adult patients presenting with cardiovascular symptoms, such as chest pain or dyspnea, for the presence of significant coronary artery disease (CAD). The system features a modular design, comprising the CorVista Base System—which includes hardware, firmware, and software for acquiring, transmitting, storing, and analyzing physiological data—and disease-specific 'Add-On Modules.' The CAD Add-On module employs a machine learning-based algorithm to analyze synchronously acquired cardiac electrical signals (via vectorcardiography - VCG) and hemodynamic signals (via photoplethysmography - PPG), along with patient demographics. This analysis generates a report indicating the likelihood of significant CAD, which is displayed on a secure web-based portal, intended to be used by clinicians in conjunction with their clinical judgment and the patient's overall clinical picture as an aid in diagnosis. The clinical performance of the CorVista® System with the CAD Add-On Module was assessed in a prospective, multicenter study involving 1,816 symptomatic subjects, using invasive coronary angiography (ICA) or Computed Tomography Angiography (CTA) as the reference standard for CAD diagnosis. The system demonstrated a diagnostic sensitivity of 88% and a specificity of 51% in identifying significant CAD, with an Area Under the Receiver Operating Characteristic curve (AUC-ROC) of 0.80, a performance level stated to be comparable to the rule-out capabilities of coronary computed tomography angiography (CCTA). Additional studies confirmed the repeatability and reproducibility of the CAD score output. The device also underwent extensive non-clinical testing, including software verification and validation, performance bench testing (covering battery lifecycle, signal quality, wireless coexistence, and label integrity), electrical and EMC safety testing, biocompatibility assessments, human factors/usability evaluations, and shelf life/cleaning validation, all of which met predefined acceptance criteria.

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. How does the CorVista System's algorithm specifically integrate VCG, PPG features, and patient demographics to derive the likelihood of CAD?; Given the specificity of 51%, what is the anticipated impact on downstream testing and potential for false positives in a clinical setting?; What were the key characteristics of the patient population (e.g., comorbidities, pre-test probability of CAD) in the validation study, and how might these affect real-world performance generalizability?; Could the modular design allow for future Add-On modules to detect other cardiovascular conditions beyond CAD using the same core VCG and PPG signals?; How does the system's performance (88% sensitivity, 51% specificity, 0.80 AUC) compare in terms of diagnostic accuracy and clinical utility to other non-invasive CAD diagnostic modalities beyond CCTA, such as various forms of stress testing or advanced ECG analysis?