Key result
Automated STJ detection algorithm achieves 1.4 mm median distance from manual delineation.
Why the study?
Planning of minimally invasive aortic valve replacement currently relies on manual selection of the intercostal space closest to the sinotubular junction on preoperative CT images, lacking automated methods for incision location detection.
Does an automated CTA-based algorithm accurately detect the sinotubular junction and intercostal spaces compared to manual delineation for mini-AVR planning?
Does an automated CTA-based algorithm accurately detect the sinotubular junction and intercostal spaces compared to manual delineation for mini-AVR planning?
An automated CTA-based algorithm can accurately detect the sinotubular junction and intercostal spaces, offering a potential tool for planning minimally invasive aortic valve replacement.
May aid mini-AVR planning but should not change practice; leaves open prospective validation of clinical benefit.
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.
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Elattar et al. (2016) studied Minimally invasive aortic valve replacement surgery (n=20). Automated algorithm for detecting the sinotubular junction and intercostal spaces vs. Manual delineation was evaluated on Accuracy of sinotubular junction detection (Euclidean distance between manually and automatically detected points). An automated algorithm for detecting the sinotubular junction achieved a median distance of 1.4 mm from manual delineation, compared to an interobserver variation of 1.0 mm.
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