Simulation of Repair on Dynamic Patient-Specific Left Atrioventricular Valve Models.

PURPOSE

To develop and evaluate a dynamic, image-derived patient-specific physical simulation platform for the assessment of left atrioventricular valve (LAVV) repair strategies in pediatric patients with repaired atrioventricular canal defects.

METHODS

3D transesophageal echocardiographic images of two patients with regurgitant LAVVs were identified from an institutional database. Custom code in SlicerHeart was used to segment leaflets, define the annulus, and generate patient-specific valve molds. Silicone valve models were fabricated and tested in a pulse duplicator under simulated physiological conditions. Five unrepaired valves were analyzed for manufacturing consistency, and multiple surgical repair techniques were compared for two patient-specific models.

RESULTS

Manufacturing variability was low in annular metrics (CV for annular circumference: 2.1%; commissural distance: 4.1%; annulus height: 14.7%) but higher in leaflet closure metrics (billow height: 11.1%; billow volume: 18.9%; tenting height: 45.9%; tenting volume: 73.5%). In Patient 1, cleft closure and an Alfieri stitch both eliminated the regurgitant orifice area, but the Alfieri stitch resulted in elevated mean pressure gradient (17 mmHg vs. 4-9 mmHg for other repairs) and deteriorated with repeated loading. In Patient 2, no repair eliminated regurgitation entirely; however, combining an 11 mm patch augmentation with commissuroplasty reduced regurgitant area to 0.147 cm, the smallest observed among tested strategies.

CONCLUSION

This study demonstrates the feasibility of a dynamic physical simulation platform for preclinical LAVV repair evaluation. Although challenges remain in accurately modeling leaflet closure and chordal mechanics, this proof-of-concept work highlights the platform's potential for refining repair strategies before clinical application, which may be particularly relevant in small and heterogeneous populations with congenital heart disease.