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Objectives: Limited aortic annulus exposure during minimal invasive aortic valve replacement (mini-AVR) proves to be challenging and contributes to procedure complexity, resulting in longer procedure times. New innovations like sutureless valves have been introduced to reduce procedure complexity. Additionally, preoperative imaging could also contribute to reducing procedure times. Therefore, we hypothesize that Computed Tomography (CT)-image based measurements are associated with mini-AVR complexity., Methods: One hundred patients who underwent a mini-sternotomy and had a preoperative CT scan were included. With a CT-based mini-AVR planning tool, we measured access distance, access angle, annulus dimensions, and calcium volume. The associations of these measurements with cardiopulmonary bypass (CPB) time and aortic cross-clamp (AoX) time were assessed using univariable and multivariable regression models. In the multivariable models, these measurements were adjusted for age and suture technique., Results: In the univariable regression models, calcium volume and annulus dimensions were associated with longer CPB and AoX time. After adjusting for age and suture technique, increasing calcium volume was still associated with longer CPB (adjusted β-coefficient 0.002, 95%-CI (0.005, 0.019), p-value = 0.002) and AoX time (adjusted β-coefficient 0.010, 95%-CI (0.004, 0.016), p-value = 0.002). However, after adjusting for these confounders, the association between annulus dimensions and procedure times lost statistical significance., Conclusion: Increase in calcium volume are associated with longer CPB and AoX times, with age and sutureless valve implantation as independent confounders. In contrast to previous studies, access angle was not associated with procedure complexity.

Objectives: Minimally invasive aortic valve replacement has proven its value over the last decade by its significant advancement and reduction in mortality, morbidity and admission time. However, minimally invasive aortic valve replacement is associated with some on-site difficulties such as limited aortic annulus exposure. Currently, computed tomography scans are used to evaluate the anatomical relationship among the intercostal spaces, ascending aorta and aortic valve prior to surgery. We hypothesized that quantitative measurements of access distance and access angle are associated with outcome and access difficulty., Methods: We introduce a novel minimally invasive aortic valve replacement planning prototype that allows automatic measurements of access angle, access distance and aortic annulus dimensions. The prototype visualizes these measurements on the chest cage as ISO contours. The association of these measures with outcome parameters such as extracorporeal circulation time, aortic cross-clamping time and access difficulty score was assessed. We included 14 patients who received a new valve by ministernotomy., Results: The mean access angle was 40.3 ± 5.1°. It was strongly associated with aortic cross-clamping time (Pearson correlation coefficient = 0.60, P = 0.02) and access difficulty score (Spearman's rank correlation coefficient = 0.57, P = 0.03). Access angles were significantly different between easy and difficult access groups (P = 0.03). There was no significant association between access distance and outcome parameters., Conclusions: Access angle is strongly associated with procedure complexity. The automated presentation of this measure suggests added value of the prototype in clinical practice.

Minimally invasive aortic valve replacement (mini-AVR) procedures are a valuable alternative to conventional open heart surgery. Currently, planning of mini-AVR consists of selection of the intercostal space closest to the sinotubular junction on preoperative computer tomography images. We developed an automated algorithm detecting the sinotubular junction (STJ) and intercostal spaces for finding the optimal incision location. The accuracy of the STJ detection was assessed by comparison with manual delineation by measuring the Euclidean distance between the manually and automatically detected points. In all 20 patients, the intercostal spaces were accurately detected. The median distance between automated and manually detected STJ locations was 1.4 [IQR= 0.91-4.7] mm compared to the interobserver variation of 1.0 [IQR= 0.54-1.3] mm. For 60% of patients, the fourth intercostal space was the closest to the STJ. The proposed algorithm is the first automated approach for detecting optimal incision location and has the potential to be implemented in clinical practice for planning of various mini-AVR procedures., (Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.)