News | Cardiac Diagnostics | November 01, 2017

Analytics 4 Life Presents Clinical Data on Machine-Learned Cardiac Imaging Technology at TCT 2017

Initial data from ongoing study evaluates diagnostic performance in obese, elderly and female patients

Analytics 4 Life Presents Clinical Data on Machine-Learned Cardiac Imaging Technology at TCT 2017

November 1, 2017 — Analytics 4 Life announced it will be presenting new clinical data on the company's ongoing Coronary Artery Disease Learning and Algorithm Development (CADLAD) study at the Transcatheter Cardiovascular Therapeutics (TCT) 2017 scientific symposium, Oct. 29-Nov. 2 in Denver.

The CADLAD study is a two-stage clinical trial at 13 sites in the United States measuring the diagnostic performance of the company's cardiac Phase Space Tomography Analysis (cPSTA) System in assessing cardiac health related to the presence of CAD. The cPSTA System, or CorVista, is a non-invasive, physician-directed diagnostic test that uses a handheld device to scan intrinsic signals from the body without radiation, contrast agents or cardiac stress. The signal data is then transmitted to a secure, cloud-based repository for analysis, and a report is generated to help physicians assess the presence of CAD.

The ongoing study is designed to test the utility of cPSTA in a large population and other important subgroups. Enrollment into the study's first stage, focused on product development, is complete, with enrollment in the study's second stage finishing before the end of this year. Results will be available early 2018 and will support the company's U.S. Food and Drug Administration (FDA) regulatory application.

Highlights of the data presented at TCT include:

  • Coronary angiography results were paired with cPSTA data from 512 subjects to generate a machine-learned algorithm to assess for significant CAD;
  • A separate verification cohort of 94 subjects was used to prospectively test the accuracy;
  • Analyses focused on total verification population and on CADLAD by gender (male vs. female), age (> 65 vs. < 65 years of age), and obesity (BMI of > 30 vs. < 30); and
  • Results suggest that the cPSTA System performs well overall across the verification population and respective subpopulations.

For more information: www.analytics4life.com

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