- Oral presentation
- Open Access
Fully-automatic, patient-specific 3D aortic arch modeling for patient treatment with aortic arch anomalies
© Leonardi et al; licensee BioMed Central Ltd. 2012
- Published: 1 February 2012
- Aortic Arch
- Bicuspid Aortic Valve
- Aortic Sinus
- Transverse Arch
- Aortic Model
Timing and type of aortic wall abnormalities (AWC) repair are still being debated. Automatically patient-specific 3D aortic arch geometrical model estimation from MRI images can provide a better knowledge of the geometry of the aortic arch anomaly and can be useful to evaluate preoperatively the best treatment. Therefore, we have developed a software to automatically compute a patient-specific 3D aortic arch geometrical model from CMR data and we have validated it.
Timing and type of surgical or transcatheter repair of aortic wall abnormalities (AWC) in patients with aortic coarctation (COA) and/or bicuspid aortic valve (BAV) are presently being debated, as associated morbidity and mortality can still occur. We have developed a system to automatically compute a patient-specific 3D aortic arch geometrical model from CMR data, which provides crucial information to understand the geometry of the pathophysiological abnormalities of the aortic arch and to evaluate preoperatively the best treatment.
To validate the accuracy of the computed 3D geometrical model of the aortic arch by comparing manual measurements extracted directly from CMR images with the one automatically derived from the geometrical model.
Statistical results significantly correlated (p < 0.001, r = 0.94) between min and max manual and automatic aortic measurements: AS (min p < 0.001 r = 0.85; max p < 0.001 r = 0.94), STJ (min p < 0.001 r = 0.88; max p < 0.001 r = 0.90), AAO (min p < 0.001 r = 0.94; max p < 0.001 r = 0.94), TA (min p < 0.001 r = 0.89; max p < 0.001 r = 0.93), DA (min p < 0.001 r = 0.90; max p < 0.001 r = 0.92).
Mean measurement error of 1.59±0.6 mm was achieved for the min diameter and 1.44±0.9 mm for the max diameter. The maximal error occurred at the minimum diameter of each segment with the STJ the greatest (min 2.07±2.53) and the DA the least (min 0.8±0.83).
Mean processing time for fully automatic aortic model estimation and measurement extraction was 1.5 s.
Aortic parameters taken by our model are reliable, fully reproducible and faster as compared to manual methods. 2) The 3D aortic model is likely to improve therapeutic decision making in COA and/or BAV.
No funding to disclose.
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.