Combining transmural left ventricular mechanics and energetics to predict oxygen demand

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Computational Biology

Background:

• Accurate prediction of myocardial oxygen demand is crucial for understanding cardiac function and disease.
• Previous models focused on global left ventricular (LV) function, but lacked spatial resolution.
• A distributed model predicting transmural oxygen demand based on LV structure and function was previously developed.

Purpose of the Study:

• To experimentally validate the predictive capabilities of a distributed model for global left ventricular (LV) oxygen demand.
• To compare the model's predictions with experimental data under varying hemodynamic conditions.
• To assess the model's ability to provide spatial information on oxygen demand distribution.

Main Methods:

• Experimental measurements in anesthetized, open-chest dogs.
• Calculation of myocardial oxygen demand from arterio-venous oxygen difference and coronary flow.
• Manipulation of LV loading conditions via pressurized arterial chamber, phenylephrine, and arteriovenous shunt.
• Cardiac pacing at two distinct heart rates.

Main Results:

• The distributed oxygen demand model's global predictions showed good agreement with experimental data.
• The model provided spatial information, predicting an endocardial to epicardial (endo/epi) oxygen demand ratio between 1.05 and 1.14.
• This predicted endo/epi ratio aligns with available experimental findings.
• End-diastolic volume was identified as the primary determinant of the transmural oxygen demand ratio under the studied conditions.

Conclusions:

• The distributed oxygen demand model offers a valid approach for predicting global cardiac metabolic function.
• The model successfully captures spatial variations in oxygen demand across the LV wall.
• End-diastolic volume is a key factor influencing transmural oxygen demand distribution, providing insights into regional myocardial energetics.