3-D Quantification of the Aortic Arch Morphology in 3-D CTA Data for Endovascular Aortic Repair

• Published in: IEEE transactions on biomedical engineering 2010-10, Vol.57 (10), p.2359-2368
• Main Authors: Worz, Stefan, von Tengg-Kobligk, Hendrik, Henninger, Verena, Rengier, Fabian, Schumacher, Hardy, Bockler, Dittmar, Kauczor, Hans-Ulrich, Rohr, Karl
• Format: Article
• Language: English
• Subjects: 3-D analytic intensity model; 3-D aortic arch segmentation; 3-D computed tomography angiography (CTA) data; Anatomy; Angiography - methods; Aorta, Thoracic - anatomy & histology; Applied sciences; Bioinformatics; Biological and medical sciences; Blood Vessel Prosthesis Implantation - methods; Carotid arteries; Computerized, statistical medical data processing and models in biomedicine; Curve fitting; Diseases of the cardiovascular system; endovascular graft (EVG); Exact sciences and technology; Humans; Image processing; Image Processing, Computer-Assisted - methods; Imaging phantoms; Imaging, Three-Dimensional; Information, signal and communications theory; Medical sciences; Models and simulation; Morphology; Permission; Phantoms, Imaging; Radiology; Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects); Signal processing; Surgery, Computer-Assisted - methods; Telecommunications and information theory; Thorax; Thorax - anatomy & histology; Tomography, X-Ray Computed - methods
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2010.2053539

We introduce a new model-based approach for the segmentation and quantification of the aortic arch morphology in 3-D computed tomography angiography (CTA) data for thoracic endovascular aortic repair (TEVAR). The approach is based on a model-fitting scheme using a 3-D analytic intensity model for thick vessels in conjunction with a two-step refinement procedure, and allows us to accurately quantify the morphology of the aortic arch. Based on the fitting results, we additionally compute the (local) 3-D vessel curvature and torsion as well as the relevant lengths not only along the 3-D centerline, but particularly also along the inner and outer contour. These measurements are important for preoperative planning in TEVAR applications. We have validated our approach based on 3-D synthetic as well as 3-D MR phantom images. Moreover, we have successfully applied our approach using 3-D CTA datasets of the human thorax and have compared the results with ground truth obtained by a radiologist. We have also performed a quantitative comparison with a commercial vascular analysis software.