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This study aimed to create an imaging-derived patient-specific computational model of low-flow, low-gradient (LFLG) aortic stenosis (AS) to obtain biomechanics data about the left ventricle. LFLG AS is now a commonly recognized sub-type of aortic stenosis. There remains much controversy over its management, and investigation into ventricular biomechanics may elucidate pathophysiology and better identify patients for valve replacement. ECG-gated cardiac computed tomography images from a patient with LFLG AS were obtained to provide patient-specific geometry for the computational model. Surfaces of the left atrium, left ventricle (LV), and outflow track were segmented. A previously validated multi-scale, multi-physics computational human heart model was adapted to the patient-specific geometry, yielding a model consisting of 91,000 solid elements. This model was coupled to a virtual circulatory system and calibrated to clinically measured parameters from echocardiography and cardiac catheterization data. The simulation replicated key physiologic parameters within 10% of their clinically measured values. Global LV systolic myocardial stress was 7.1 ± 1.8kPa. Mean stress of the basal, middle, and apical segments were 7.7 ± 1.8kPa, 9.1 ± 3.8kPa, and 6.4 ± 0.4kPa, respectively. This is the first patient-specific computational model of LFLG AS based on clinical imaging. Low myocardial stress correlated with low ejection fraction and eccentric LV remodeling. Further studies are needed to understand how alterations in LV biomechanics correlates with clinical outcomes of AS.

Aortic stenosis (AS) is the most common acquired heart valve disease in the developed world. Traditional methods of grading AS have relied on the measurement of aortic valve area and transvalvular pressure gradient. Recent research has highlighted the existence of AS variants that do not meet classic criteria for severe AS such as low-flow, low-gradient AS. With the development of sophisticated multi-scale computational models, investigation into the left ventricular (LV) biomechanics of AS offers new insights into the pathophysiology that may guide treatment decisions surrounding AS. Building upon our prior study entailing LV-aortic coupling where AS conditions were applied to the idealized geometry of the Living Heart Human Model, we now describe the first patient-specific adaptation of the model to a case of low flow, low gradient AS. EKG-gated cardiac computed tomography images were segmented to provide surfaces to which the generic Living Heart model was adapted. The model was coupled to a lumped-parameter circulatory system; it was then calibrated to patient clinical data from echocardiography/cardiac catheterization with strong correlation (simulation versus clinical measurement): ascending aorta systolic pressure: 109mmHg vs 116mmHg, ascending aorta diastolic pressure 50mmHg vs 45mmHg, LV systolic pressure: 118mmHg vs 128mmHg, peak transvalvular gradient: 9mmHg vs 12mmHg, LV ejection fraction: 23% vs 25%. This work illustrates how the Living Heart Human Model geometry can be efficiently adapted to patient-specific parameters, enabling future biomechanics investigations into the LV dysfunction of AS.