Identification of exercise-induced ischemia using QRS slopes

Area of Science:

• Cardiology
• Medical Imaging
• Biomedical Engineering

Background:

• Exercise stress testing is crucial for diagnosing coronary artery disease.
• Standard analysis relies on ST-segment depression, which can be subjective.
• Novel electrocardiogram (ECG) features may offer improved diagnostic accuracy for exercise-induced ischemia.

Purpose of the Study:

• To evaluate a computer-aided approach utilizing QRS slopes as unconventional ECG features for identifying exercise-induced ischemia.
• To compare the diagnostic performance of QRS slopes against expert manual analysis using ST-segment criteria.

Main Methods:

• A database of 927 patients undergoing exercise stress tests with simultaneous ECG and SPECT data was used.
• High-resolution 12-lead ECGs were recorded during rest, exercise, and recovery phases.
• QRS slopes were extracted from averaged representative beats using a Philips DXL 16-lead algorithm, and linear discriminant analysis with 10-fold cross-validation was employed.

Main Results:

• The computer-aided QRS slope analysis demonstrated performance comparable to expert manual interpretation.
• QRS slopes were identified as effective unconventional ECG parameters for ischemia detection.
• The method showed significant potential in improving the identification of exercise-induced ischemia.

Conclusions:

• QRS slopes represent a powerful, unconventional ECG parameter for diagnosing exercise-induced ischemia.
• Computer-aided analysis of QRS slopes offers a viable alternative or adjunct to traditional ST-segment analysis.
• This approach enhances the accuracy and objectivity of ischemia detection during exercise stress testing.