| Title |
Automated 3D segmentation and diameter measurement of the thoracic aorta on non-contrast enhanced CT
|
|---|---|
| Published in |
European Radiology, January 2019
|
| DOI | 10.1007/s00330-018-5931-z |
| Pubmed ID | |
| Authors |
Zahra Sedghi Gamechi, Lidia R. Bons, Marco Giordano, Daniel Bos, Ricardo P. J. Budde, Klaus F. Kofoed, Jesper Holst Pedersen, Jolien W. Roos-Hesselink, Marleen de Bruijne |
| Abstract |
To develop and evaluate a fully automatic method to measure diameters of the ascending and descending aorta on non-ECG-gated, non-contrast computed tomography (CT) scans. The method combines multi-atlas registration to obtain seed points, aorta centerline extraction, and an optimal surface segmentation approach to extract the aorta surface around the centerline. From the extracted 3D aorta segmentation, the diameter of the ascending and descending aorta was calculated at cross-sectional slices perpendicular to the extracted centerline, at the level of the pulmonary artery bifurcation, and at 1-cm intervals up to 3 cm above and below this level. Agreement with manual annotations was evaluated by dice similarity coefficient (DSC) for segmentation overlap, mean surface distance (MSD), and intra-class correlation (ICC) of diameters on 100 CT scans from a lung cancer screening trial. Repeatability of the diameter measurements was evaluated on 617 baseline-one year follow-up CT scan pairs. The agreement between manual and automatic segmentations was good with 0.95 ± 0.01 DSC and 0.56 ± 0.08 mm MSD. ICC between the diameters derived from manual and from automatic segmentations was 0.97, with the per-level ICC ranging from 0.87 to 0.94. An ICC of 0.98 for all measurements and per-level ICC ranging from 0.91 to 0.96 were obtained for repeatability. This fully automatic method can assess diameters in the thoracic aorta reliably even in non-ECG-gated, non-contrast CT scans. This could be a promising tool to assess aorta dilatation in screening and in clinical practice. • Fully automatic method to assess thoracic aorta diameters. • High agreement between fully automatic method and manual segmentations. • Method is suitable for non-ECG-gated CT and can therefore be used in screening. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 15% |
| Researcher | 10 | 12% |
| Student > Ph. D. Student | 7 | 9% |
| Student > Bachelor | 7 | 9% |
| Student > Doctoral Student | 5 | 6% |
| Other | 16 | 20% |
| Unknown | 24 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 20 | 25% |
| Engineering | 15 | 19% |
| Computer Science | 6 | 7% |
| Earth and Planetary Sciences | 3 | 4% |
| Nursing and Health Professions | 2 | 2% |
| Other | 8 | 10% |
| Unknown | 27 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2019.
All research outputs
#20,550,733
of 23,124,001 outputs
Outputs from European Radiology
#3,369
of 4,189 outputs
Outputs of similar age
#371,139
of 437,851 outputs
Outputs of similar age from European Radiology
#51
of 70 outputs
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