Automated QT analysis that learns from cardiologist annotations

ECG segmentation algorithm based on bidirectional hidden semi-Markov model

Accurate segmentation of electrocardiogram (ECG) waves is crucial for cardiovascular diseases (CVDs). In this study, a bidirectional hidden semi-Markov model (BI-HSMM) based on the probability distributions of ECG waveform duration was proposed for ECG wave segmentation. Four feature-vectors of ECG signals were extracted as the observation sequence of the hidden Markov model (HMM), and the statistical probability distribution of each waveform duration was counted. Logistic regression (LR) was used to train model parameters. The starting and ending positions of the QRS wave were first detected, and thereafter, bidirectional prediction was employed for the other waves. Forwardly, ST segment, T wave, and TP segment were predicted. Backwardly, P wave and PQ segments were detected. The Viterbi algorithm was improved by integrating the recursive formula of the forward prediction and backward backtracking algorithms. In the QT database, the proposed method demonstrated excellent performance (Acc = 97.98%, F1 score of P wave = 98.37%, F1 score of QRS wave = 97.60%, F1 score of T wave = 97.79%). For the wearable dynamic electrocardiography (DCG) signals collected by the Shandong Provincial Hospital (SPH), the detection accuracy was 99.71% and the F1 of each waveform was above 99%. The experimental results and real DCG signal validation confirmed that the proposed new BI-HSMM method exhibits significant ability to segment the resting and DCG signals; this is conducive to the detection and monitoring of CVDs.

Automated measurements for individualized heart rate correction of the QT interval

BACKGROUND

Subject-specific electrocardiographic QT interval correction for heart rate is often used in clinical trials with frequent electrocardiographic recordings. However, in these studies relatively few 10-s, 12-lead electrocardiograms may be available for calculating the individual correction. Highly automated QT and RR measurement tools have made it practical to measure electrocardiographic intervals on large volumes of continuous electrocardiogram data. The purpose of this study was to determine whether an automated method can be used in lieu of a manual method.

METHODS

In 49 subjects who completed all treatments in a four-armed crossover study we compared two methods for derivation of individualized rate-correction coefficients: manual measurement on 10-s electrocardiograms and automated measurement of QT and RR during continuous 24-h electrocardiogram recordings. The four treatments, received by each subject in a latin-square randomization sequence were placebo, moxifloxacin, and two doses of an investigational drug.

RESULTS

Analysis of continuous electrocardiogram data yielded a lower standard deviation of QT:RR regression values than the manual method, though the differences were not statistically significant. The within-subject and within-treatment coefficients of variation between the manual and automated methods were not significantly different. Corrected QT values from the two methods had similar rates of true and false positive identification of moxifloxacin's QT prolonging effect.

CONCLUSION

An automated method for individualized rate correction applied to continuous electrocardiogram data could be advantageous in clinical trials, as the automated method is simpler, is based upon a much larger volume of data, yields similar results, and requires no human over-reading of the measurements.

Comparative TQT analysis with three fully-automated platforms: comparison to core laboratory semi-automated results

BACKGROUND AND PURPOSE

Technological advances in machine-read QT measurement now enable detailed and precise cardiac repolarization assessments. This study assessed the applicability of three state-of-art ECG measurement applications to provide reliable continuous analyses from data obtained in a positive thorough QT study previously characterized with sparse semi-automated measurements performed by an ECG core laboratory.

METHODS

Continuous RR, QT, QTc measurements, and individual QT/RR relationships and their associated intra- and inter-subject variability were derived in parallel with BioQT, Ponemah PRO, and WinAtrec analysis software.

RESULTS

Despite slight vendor-specific differences in measurement variability and QTc, all machine-read methods demonstrated requisite assay sensitivity and yielded similar conclusions in accordance with SA analysis.

CONCLUSIONS

Three commercially available ECG analytical software applications reliably detected the drug-induced QT prolonging effects and replicated the SA core-laboratory conclusions, with greatly improved temporal resolution and reduced analytical costs. With broader experience, these data suggest that current SA methodologies could be effectively replaced by fully automated ECG analysis.

Highly automated QT measurement techniques in 7 thorough QT studies implemented under ICH E14 guidelines

Thorough QT (TQT) studies are designed to evaluate potential effect of a novel drug on the ventricular repolarization process of the heart using QTc prolongation as a surrogate marker for torsades de pointes. The current process to measure the QT intervals from the thousands of electrocardiograms is lengthy and expensive. In this study, we propose a validation of a highly automatic-QT interval measurement (HA-QT) method. We applied a HA-QT method to the data from 7 TQT studies. We investigated both the placebo and baseline-adjusted QTc interval prolongation induced by moxifloxacin (positive control drug) at the time of expected peak concentration. The comparative analysis evaluated the time course of moxifloxacin-induced QTc prolongation in one study as well. The absolute HA-QT data were longer than the FDA-approved QTc data. This trend was not different between ECGs from the moxifloxacin and placebo arms: 9.6 ± 24 ms on drug and 9.8 ± 25 ms on placebo. The difference between methods vanished when comparing the placebo-baseline-adjusted QTc prolongation (1.4 ± 2.8 ms, P = 0.4). The differences in precision between the HA-QT and the FDA-approved measurements were not statistically different from zero: 0.1 ± 0.1 ms (P = 0.7). Also, the time course of the moxifloxacin-induced QTc prolongation adjusted for placebo was not statistically different between measurements methods.

The thorough QT/QTc study 4 years after the implementation of the ICH E14 guidance

The ICH E14 guidance on how to clinically assess a new drug's liability to prolong the QT interval was adopted in May 2005. A centre-piece of the guidance was the establishment of one single trial, the 'thorough QT/QTc study', intended to confidently identify drugs that may cause QT prolongation. Initially perceived as a great challenge, this study has rapidly become a standard component of all clinical development programs for new molecular entities. The study is normally conducted in healthy volunteers, includes both a positive and a negative (placebo) control and is stringently powered to exclude an effect on the QTc interval exceeding 10 ms. The E14 guidance was intentionally not very prescriptive and allowed sponsors and service providers to explore new methodologies. This has allowed for a rapid development of new methods during the first years after the guidance's implementation, such as computer-assisted algorithms for QT measurements. Regulators have worked in close collaboration with pharmaceutical industry to set standards for the design and conduct of the 'thorough QT/QTc study', which therefore has evolved as a key component of cardiac safety assessment of new drugs. This paper summarizes the requirements on the 'thorough QT/QTc study' with emphasis on the standard that has evolved based on interactions between regulators and sponsors and the experience from a large number of completed studies.