Key result
MRI-derived VR models accurately assess TPVR candidacy in 88% of patients.
Why the study?
Cardiovascular MRI with MRA supports indications for TPVR, but the feasibility of generating virtual RVOT models from MRA datasets and evaluating TPVR candidacy in virtual reality compared with CT-derived industry fit analysis needed assessment.
Does virtual reality visualisation of MRA-based anatomic models accurately evaluate candidacy for transcatheter pulmonary valve replacement compared to CT-based industry fit analysis?
Does virtual reality visualisation of MRA-based anatomic models accurately evaluate candidacy for transcatheter pulmonary valve replacement compared to CT-based industry fit analysis?
Generating virtual reality models from MRA datasets is feasible and may identify additional candidates for transcatheter pulmonary valve replacement who fail standard CT-based industry screening.
Answers are grounded in this paper and cite their sources.
May expand TPVR candidacy using MRI-VR beyond CT screening; extends feasibility but remains hypothesis-generating pending larger trials.
Cardiovascular MRI with magnetic resonance angiography supports clinical indication for transcatheter pulmonary valve replacement. We aimed to: (1) assess the feasibility of generating virtual right ventricular outflow tract models directly from magnetic resonance angiography datasets and (2) compare transcatheter pulmonary valve replacement candidacy based on visualisation of anatomic and valve models in virtual reality to outcomes and dispositions suggested by industry fit analysis derived from cardiac CT. Patients with native or surgically palliated right ventricular outflow tracts considered for transcatheter pulmonary valve replacement with temporally related magnetic resonance angiography and cardiac CT were included. Magnetic resonance angiography models were generated using commercial software; virtual valves were created using industry dimensions. A blinded interventional cardiologist determined pulmonary valve replacement candidacy using virtual reality review. A total of 16 patients (N = 7 males, 44%) with a median age 15.5 years (interquartile range [IQR] 13.9, 17.8) were identified. Median time for model generation was 20.6 minutes (IQR 18.5, 22.0). 11/16 (69%) patients passed industry screening fit analysis; 14/16 (88%) ultimately underwent transcatheter pulmonary valve replacement. Four patients who passed virtual reality screening failed industry screening but underwent successful transcatheter pulmonary valve replacement. One patient passed virtual reality and industry screening but did not undergo transcatheter pulmonary valve replacement. One patient passed virtual reality screening but failed industry screening and was not offered transcatheter pulmonary valve replacement. In conclusion, generating virtual models from clinical magnetic resonance angiography datasets is feasible. Modelling may help evaluate transcatheter pulmonary valve replacement candidacy, but must be used in conjunction with other data.
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Wilson et al. (2026) studied this question. Virtual reality-based models from MRI data accurately assessed candidacy for transcatheter pulmonary valve replacement in 88% of patients, demonstrating effective feasibility.
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