Quantitative cardiology and computer modeling analysis of heart failure in systole and in diastole

Area of Science:

• Computational cardiology
• Biomedical engineering
• Medical diagnostics

Background:

• Clinical cardiology diagnosis relies on assessing specific parameters.
• Computer modeling provides realistic interpretations of parameter variations through computational quantification.
• Existing diagnostic methods may have limitations in differentiating heart failure subtypes.

Purpose of the Study:

• To provide an overview of cardiac diagnosis based on systolic and diastolic abnormalities.
• To emphasize quantitative hemodynamic assessment and multi-scale modeling.
• To explore the inadequacy of ejection fraction for heart failure diagnosis and propose alternative parameters.

Main Methods:

• Utilized multi-scale computer modeling, from single fiber to global ventricular levels.
• Applied quantitative hemodynamic assessment and modeling.
• Investigated heart-arterial system interactions in conditions like left ventricular hypertrophy.

Main Results:

• Demonstrated applicability of classic force-velocity-length relations in modern quantitative cardiac assessment.
• Reproduced reduced systolic shortening and delayed diastolic relaxation associated with ischemia and stunning at the single muscle fiber level.
• Identified structural parameters at fiber and global levels as more appropriate than ejection fraction for quantifying cardiac function and diagnosing heart failure.

Conclusions:

• Computer modeling is invaluable for quantitative cardiology diagnosis.
• Structural parameters are superior to ejection fraction for differentiating heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF).
• Computational approaches can delineate critical parameters for accurate cardiac function assessment.