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  • Title: 3D printing based on cardiac CT assists anatomic visualization prior to transcatheter aortic valve replacement.
    Author: Ripley B, Kelil T, Cheezum MK, Goncalves A, Di Carli MF, Rybicki FJ, Steigner M, Mitsouras D, Blankstein R.
    Journal: J Cardiovasc Comput Tomogr; 2016; 10(1):28-36. PubMed ID: 26732862.
    Abstract:
    BACKGROUND: 3D printing is a promising technique that may have applications in medicine, and there is expanding interest in the use of patient-specific 3D models to guide surgical interventions. OBJECTIVE: To determine the feasibility of using cardiac CT to print individual models of the aortic root complex for transcatheter aortic valve replacement (TAVR) planning as well as to determine the ability to predict paravalvular aortic regurgitation (PAR). METHODS: This retrospective study included 16 patients (9 with PAR identified on blinded interpretation of post-procedure trans-thoracic echocardiography and 7 age, sex, and valve size-matched controls with no PAR). 3D printed models of the aortic root were created from pre-TAVR cardiac computed tomography data. These models were fitted with printed valves and predictions regarding post-implant PAR were made using a light transmission test. RESULTS: Aortic root 3D models were highly accurate, with excellent agreement between annulus measurements made on 3D models and those made on corresponding 2D data (mean difference of -0.34 mm, 95% limits of agreement: ± 1.3 mm). The 3D printed valve models were within 0.1 mm of their designed dimensions. Examination of the fit of valves within patient-specific aortic root models correctly predicted PAR in 6 of 9 patients (6 true positive, 3 false negative) and absence of PAR in 5 of 7 patients (5 true negative, 2 false positive). CONCLUSIONS: Pre-TAVR 3D-printing based on cardiac CT provides a unique patient-specific method to assess the physical interplay of the aortic root and implanted valves. With additional optimization, 3D models may complement traditional techniques used for predicting which patients are more likely to develop PAR.
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