AI-assisted computed tomography analysis for pre-procedural planning prior to TAVI.

BACKGROUND: Several software programs have specifically been developed to analyse cardiac computed tomography prior to transcatheter aortic valve implantation (TAVI). However, they are not able to perform a complete analysis independently. We report the performance of a fully automated, deep learning-based algorithm for pre-procedural CT analysis as compared to the current clinical standard. METHODS: Patients with symptomatic severe aortic stenosis undergoing TAVI were retrospectively enrolled. The pre-procedural dataset was analysed by both a standard TAVI CT-analysis software and by a fully automated CT analysis platform with a deep learning-based algorithm. RESULTS: Ninety-eight patients were included in the analysis. The mean annulus diameter was 24.4 ± 2.4 mm (conventional = 3mensio, Pie Medical Imaging, 3 M) vs. 24.0 ± 2.4 mm (artificial intelligence = AI), mean absolute error (MAE): 0.64 mm, mean absolute percentage error (MAPE): 2.6%. The mean annulus perimeter was measured at 77.7 ± 7.4 mm (3 M) vs. 76.1 ± 7.5 mm (AI), MAE: 2.26 mm, MAPE: 2.9%. The mean annulus area was calculated at 468.9 ± 92.1 mm2 (3 M) vs. 455.6 ± 91.0 mm2 (AI), MAE: 22.4 mm2, MAPE: 4.8%. The intraclass correlation coefficients (ICCs) of all abovementioned parameter were > 0.95 showing an excellent correlation between the two methods. The distance from the annulus to the left coronary artery depicted to 14.0 ± 3.2 mm (3 M) vs. 12.6 ± 2.8 mm (AI), MAE: 2.1 mm, MAPE: 14.3%. The distance to the right coronary artery was 17.1 ± 2.7 mm (3 M) vs. 16.5 ± 3.2 mm (AI), MAE: 1.7 mm, MAPE: 10.1%. The ICCs of the distances to the coronary ostia showed good correlation between both methods. CONCLUSION: In this retrospective analysis, a deep learning-based analysis of pre-procedural CT datasets showed good to excellent correlation with conventional assessment for the preprocedural TAVI CT measurements. AI-based fully automated CT analysis could emerge to a valuable alternative to conventional CT assessment in the pre-procedural-planning for TAVI.