title: Evaluation of an algorithm for highly automated measurements of QT interval.
abstract: BACKGROUND
  Noise, artifact, and labile morphology of ECGs collected from freely moving animals in safety pharmacology studies render accurate measurements of QT interval challenging. Consequently, a high percentage of beats are uninterpretable and results provided by currently available analysis algorithms often require extensive manual review to correct errors. Performance of a novel algorithm, Multi-Domain Signal Processing™ (MDSP), is evaluated as a means of removing noise (denoising) without distorting morphology and for obtaining accurate beat-to-beat QT measurements.
  
  
  METHODS
  Performance was evaluated using controlled experiments and an observational evaluation as follows: a) a clean ECG strip was intentionally corrupted with varying levels of noise to provide recordings of known signal-to-noise ratio (SNR). SNR and fidelity were compared pre- and post-MDSP denoising, b) beat-to-beat QT of a noisy ECG was measured manually pre- and post-MDSP denoising and automatically by MDSP, c) beat-to-beat QT of a clean ECG was measured manually and automatically using MDSP, and d) beat-to-beat QT was computed for 3 freely moving non-human primates (NHP) pre- and post-torsadogen administration and the impact of averaging on QTSD, QT/RR dynamics and relationship was evaluated.
  
  
  RESULTS
  MDSP reduced noise amplitude by up to 85% while preserving signal morphology. Mean QTs for manual and automatic measurements on a noisy ECG were within 2±15ms. MDSP-denoising prior to manual QT measurements resulted in a 22% decrease in QTSD compared to measurements obtained without denoising. Average QT standard deviation of the mean (QTSD) for automatic MDSP-derived measurements for 3 freely moving subjects was 7ms with 2.5% of beats automatically excluded due to noise.
  
  
  CONCLUSIONS
  This work demonstrates that the MDSP algorithm shows promise as a tool for providing accurate automatic beat-to-beat measurements of QT interval from NHP in safety pharmacology studies. A methodology is presented for characterizing the impact of noise on algorithm performance.
authors.affiliation: VivaQuant, LLC/University of Minnesota, St. Paul, MN, USA. mbrockway@vivaquant.com
authors.forename: Marina
authors.initials: M
authors.lastname: Brockway
authors.forename: Robert
authors.initials: R
authors.lastname: Hamlin
mesh_terms: D000465:Algorithms; D000818:Animals; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D004562:Electrocardiography / Q000379:methods* / Q000662:veterinary; D011323:Primates; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio