Literature DB >> 20570759

3-D quantification of the aortic arch morphology in 3-D CTA data for endovascular aortic repair.

Stefan Wörz1, Hendrik von Tengg-Kobligk, Verena Henninger, Fabian Rengier, Hardy Schumacher, Dittmar Böckler, Hans-Ulrich Kauczor, Karl Rohr.   

Abstract

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.

Entities:  

Mesh:

Year:  2010        PMID: 20570759     DOI: 10.1109/TBME.2010.2053539

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification.

Authors:  Cosmin Adrian Morariu; Tobias Terheiden; Daniel Sebastian Dohle; Konstantinos Tsagakis; Josef Pauli
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-08-29       Impact factor: 2.924

2.  True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography.

Authors:  Tim F Weber; Tobias Müller; Andreas Biesdorf; Stefan Wörz; Fabian Rengier; Tobias Heye; Tim Holland-Letz; Karl Rohr; Hans-Ulrich Kauczor; Hendrik von Tengg-Kobligk
Journal:  Int J Cardiovasc Imaging       Date:  2013-10-18       Impact factor: 2.357

3.  Aortic morphometry at endograft position as assessed by 3D image analysis affects risk of type I endoleak formation after TEVAR.

Authors:  Drosos Kotelis; Carolin Brenke; Stefan Wörz; Fabian Rengier; Karl Rohr; Hans-Ulrich Kauczor; Dittmar Böckler; Hendrik von Tengg-Kobligk
Journal:  Langenbecks Arch Surg       Date:  2015-02-22       Impact factor: 3.445

4.  Proximal scalloped custom-made Relay® stent graft in chronic type B dissection: endovascular repair in a drug abuser patient.

Authors:  Zoltán Szeberin; Balázs Nemes; Csaba Csobay-Novák; Zsuzsa Mihály; László Entz
Journal:  Interv Med Appl Sci       Date:  2016-03

5.  3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

Authors:  Matthias Müller-Eschner; Tobias Müller; Andreas Biesdorf; Stefan Wörz; Fabian Rengier; Dittmar Böckler; Hans-Ulrich Kauczor; Karl Rohr; Hendrik von Tengg-Kobligk
Journal:  Cardiovasc Diagn Ther       Date:  2014-04

6.  Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction.

Authors:  Arna van Engelen; Miguel Silva Vieira; Isma Rafiq; Marina Cecelja; Torben Schneider; Hubrecht de Bliek; C Alberto Figueroa; Tarique Hussain; Rene M Botnar; Jordi Alastruey
Journal:  J Cardiovasc Magn Reson       Date:  2017-03-08       Impact factor: 5.364

7.  Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension.

Authors:  Fabian Rengier; Stefan Wörz; Claudius Melzig; Sebastian Ley; Christian Fink; Nicola Benjamin; Sasan Partovi; Hendrik von Tengg-Kobligk; Karl Rohr; Hans-Ulrich Kauczor; Ekkehard Grünig
Journal:  PLoS One       Date:  2016-09-14       Impact factor: 3.240

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.