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Three-Dimensional Printing of a Complex Aortic Anomaly

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Three-dimensional thrombus segmentation in abdominal aortic aneurysms using graph search based on a triangular mesh.

Kyungmoo Lee¹, Ryan K Johnson, Yin Yin

¹Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA, USA. kyungmle@engineering.uiowa.edu

Computers in Biology and Medicine

|January 16, 2010

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Accurate thrombus segmentation in abdominal aortic aneurysms (AAA) is crucial for patient care. A novel 3D graph search method using triangular meshes provides precise segmentation of thrombus and lumen in AAA, aiding diagnosis and treatment planning.

Area of Science:

Medical imaging analysis
Computational anatomy
Vascular disease research

Background:

Abdominal aortic aneurysm (AAA) involves localized aortic widening and often contains thrombus.
Accurate thrombus segmentation and analysis are vital for AAA diagnosis, risk stratification, and treatment decisions.

Purpose of the Study:

To develop and evaluate a 3D graph search method for segmenting thrombus within abdominal aortic aneurysms.
To quantitatively assess the accuracy of the proposed segmentation technique.

Main Methods:

Utilized a 3D graph search algorithm on a triangular mesh for thrombus segmentation.
Tested the method on 9 3D MDCT angiography datasets (9 patients with AAA, 1300 slices).
Employed interactive control point placement for segmentation guidance.

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Main Results:

Achieved mean unsigned errors of 0.99+/-0.18 mm for luminal surfaces and 1.90+/-0.72 mm for thrombotic surfaces.
Required an average of 9.9 control points across 2.1 slices per dataset for segmentation.
Demonstrated the method's efficacy in accurately segmenting AAA thrombus.

Conclusions:

The 3D graph search approach offers a robust and accurate method for thrombus segmentation in AAA.
This technique has significant potential to improve diagnostic accuracy and treatment planning for AAA patients.
Quantitative analysis of AAA thrombus is feasible and essential for clinical management.