FAT-QT Details

The fully automated solution for T-QT studies

FAT-QT (Fully Automatic Thorough-QT) is the tool that combining the features of two confirmed AMPS tools, namely CalECG and "FDAEcg Suite", provides in a single tool the capability of performing fully automated analysis of 12-lead ECGs.

Taking advantage of the deeply improved automatic measuring algorithm BRAVO, included in the latest version of CalECG, as well as the enhanced quality filters developed for the “FDAEcg Suite” scoring module, FAT-QT has the capability to greatly reduce the amount of time needed to analyze ECG traces in the contest of Thorough-QT studies in particular, and in clinical trials in general, by pre-processing, measuring, and then sorting all the ECGs in different sets, based on overall quality.

The annotations that can be automatically measured include:   

  • RR, PR, QT, QTpeak, TpTe, JT and PP interval
  • QRS, ST and P-wave duration
  • T-wave and R-wave amplitude

Afterwards, using different scoring metrics, ECGs are sorted in categories, based on their quality. Scoring metrics are configurable, selectable by the user and include:   

  • Heart rate, Global RR and RR variability
  • QRS complexes heterogeneity
  • Protocol agreement percentage
  • The following ECG annotation-based metrics: QT, QTcB, QTcF, PR, QRS, QTpeak, TpTe Rep Beat
  • Lead specific (I, II, III, aVR, aVL, aVF, V1…V6) and all-leads LF noise
  • Lead specific and all-leads HF noise &  All frequencies noise
  • Lead specific HF noise around onset/offset of annotation
  • Lead specific T-wave amplitude

The number of categories (sets) are also configurable and can be as many as needed. At the end of the process good quality classified ECGs would not require any further expert review, greatly reducing the need for manual review analysis on a small subset of ECGs for each study, and thus allowing safer, faster, and cheaper processing of large amount of ECG traces.

You can review the paper Use of ECG Quality Metrics in Clinical Trials on the Publications page of our website, for more details on the software.

The paper Detecting moxifloxacin-induced QTc prolongation in thorough QT and early clinical phase studies using a highly automated ECG analysis approach illustrates the use of Fat-QT in Clinical Research.

Fat-QT Learn More

Clicking here below you can view a set of slides illustrating Fat-QT software.


FAT-QT Training video