Literature DB >> 27209285

Automatic detection of aorto-femoral vessel trajectory from whole-body computed tomography angiography data sets.

Xinpei Gao1, Pieter H Kitslaar2,3, Ricardo P J Budde4, Shengxian Tu5, Michiel A de Graaf6, Liang Xu7, Bo Xu7, Arthur J H A Scholte6, Jouke Dijkstra1, Johan H C Reiber1,8.   

Abstract

Extraction of the aorto-femoral vessel trajectory is important to utilize computed tomography angiography (CTA) in an integrated workflow of the image-guided work-up prior to trans-catheter aortic valve replacement (TAVR). The aim of this study was to develop a new, fully-automated technique for the extraction of the entire arterial access route from the femoral artery to the aortic root. An automatic vessel tracking algorithm was first used to find the centerline that connected the femoral accessing points and the aortic root. Subsequently, a deformable 3D-model fitting method was used to delineate the lumen boundary of the vascular trajectory in the whole-body CTA dataset. A validation was carried out by comparing the automatically obtained results with semi-automatically obtained results from two experienced observers. The whole framework was validated on whole body CTA datasets of 36 patients. The average Dice similarity indexes between the segmentations of the automatic method and observer 1 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta were 0.977 ± 0.030, 0.980 ± 0.019, 0.982 ± 0.016; the average Dice similarity indexes between the segmentations of the automatic method and observer 2 were 0.950 ± 0.040, 0.954 ± 0.031 and 0.965 ± 0.019, respectively. The inter-observer variability resulted in a Dice similarity index of 0.954 ± 0.038, 0.952 ± 0.031 and 0.969 ± 0.018 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta. The average minimal luminal diameters (MLDs) of the ilio-femoral artery were 6.03 ± 1.48, 5.70 ± 1.43 and 5.52 ± 1.32 mm for the automatic method, observer 1 and observer 2 respectively. The MLDs of the aorta were 13.43 ± 2.54, 12.40 ± 2.93 and 12.08 ± 2.40 mm for the automatic method, observer 1 and observer 2 respectively. The automatic measurement overestimated the MLD slightly in the ilio-femoral artery at the average by 0.323 mm (SD = 0.49 mm, p < 0.001) compared to observer 1 and by 0.51 mm (SD = 0.71 mm, p < 0.001) compared to observer 2. The proposed segmentation approach can automatically provide reliable measurements of the entire arterial accessing route that can be used to support TAVR procedures. To the best of our knowledges, this approach is the first fully automatic segmentation method of the whole aorto-femoral vessel trajectory in CTA images.

Entities:  

Keywords:  Aorto-femoral; CTA; Fully-automatic; Segmentation; TAVR

Mesh:

Year:  2016        PMID: 27209285     DOI: 10.1007/s10554-016-0901-5

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  24 in total

1.  Automatic lumen and outer wall segmentation of the carotid artery using deformable three-dimensional models in MR angiography and vessel wall images.

Authors:  Ronald van 't Klooster; Patrick J H de Koning; Reza Alizadeh Dehnavi; Jouke T Tamsma; Albert de Roos; Johan H C Reiber; Rob J van der Geest
Journal:  J Magn Reson Imaging       Date:  2011-10-26       Impact factor: 4.813

2.  Imaging for approach selection of TAVI: assessment of the aorto-iliac tract diameter by computed tomography-angiography versus projection angiography.

Authors:  E M A Wiegerinck; H A Marquering; N Y Oldenburger; M A Elattar; R N Planken; B A J M De Mol; J J Piek; J Baan
Journal:  Int J Cardiovasc Imaging       Date:  2013-12-11       Impact factor: 2.357

3.  Automatic segmentation, detection and quantification of coronary artery stenoses on CTA.

Authors:  Rahil Shahzad; Hortense Kirişli; Coert Metz; Hui Tang; Michiel Schaap; Lucas van Vliet; Wiro Niessen; Theo van Walsum
Journal:  Int J Cardiovasc Imaging       Date:  2013-08-08       Impact factor: 2.357

Review 4.  A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes.

Authors:  David Lesage; Elsa D Angelini; Isabelle Bloch; Gareth Funka-Lea
Journal:  Med Image Anal       Date:  2009-08-12       Impact factor: 8.545

5.  Transfemoral access assessment for transcatheter aortic valve replacement: evidence-based application of computed tomography over invasive angiography.

Authors:  Kazuaki Okuyama; Hasan Jilaihawi; Mohammad Kashif; Nobuyuki Takahashi; Tarun Chakravarty; Heera Pokhrel; Jigar Patel; James S Forrester; Mamoo Nakamura; Wen Cheng; Raj R Makkar
Journal:  Circ Cardiovasc Imaging       Date:  2014-12-31       Impact factor: 7.792

Review 6.  Multidimensional MDCT angiography in the context of transcatheter aortic valve implantation.

Authors:  Ajit H Goenka; Paul Schoenhagen; Michael A Bolen; Milind Y Desai
Journal:  AJR Am J Roentgenol       Date:  2014-10       Impact factor: 3.959

Review 7.  Transcatheter aortic valve replacement: current perspectives and future implications.

Authors:  Shikhar Agarwal; E Murat Tuzcu; Amar Krishnaswamy; Paul Schoenhagen; William J Stewart; Lars G Svensson; Samir R Kapadia
Journal:  Heart       Date:  2014-11-19       Impact factor: 5.994

Review 8.  Outcomes and safety of percutaneous aortic valve replacement.

Authors:  Alan Zajarias; Alain G Cribier
Journal:  J Am Coll Cardiol       Date:  2009-05-19       Impact factor: 24.094

9.  Predicting vascular complications during transfemoral transcatheter aortic valve replacement using computed tomography: a novel area-based index.

Authors:  Amar Krishnaswamy; Akhil Parashar; Shikhar Agarwal; Dhruv K Modi; Kanhaiya L Poddar; Lars G Svensson; Eric E Roselli; Paul Schoenhagen; E Murat Tuzcu; Samir R Kapadia
Journal:  Catheter Cardiovasc Interv       Date:  2014-04-15       Impact factor: 2.692

10.  Normal thoracic aorta diameter on cardiac computed tomography in healthy asymptomatic adults: impact of age and gender.

Authors:  Song Shou Mao; Nasir Ahmadi; Birju Shah; Daniel Beckmann; Annie Chen; Luan Ngo; Ferdinand R Flores; Yan Lin Gao; Matthew J Budoff
Journal:  Acad Radiol       Date:  2008-07       Impact factor: 3.173

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  3 in total

1.  Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.

Authors:  Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana
Journal:  Acad Radiol       Date:  2019-08-10       Impact factor: 3.173

2.  Cardiovascular imaging 2016 in the International Journal of Cardiovascular Imaging.

Authors:  Johan H C Reiber; Johan De Sutter; Paul Schoenhagen; Arthur E Stillman; Nico R L Vande Veire
Journal:  Int J Cardiovasc Imaging       Date:  2017-06       Impact factor: 2.357

3.  Prescreening and treatment of aortic dissection through an analysis of infinite-dimension data.

Authors:  Peng Qiu; Yixuan Li; Kai Liu; Jinbao Qin; Kaichuang Ye; Tao Chen; Xinwu Lu
Journal:  BioData Min       Date:  2021-04-01       Impact factor: 2.522

  3 in total

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