A methodology to generate structured computational grids from DICOM data: application to a patient-specific abdominal aortic aneurysm (AAA) model

Abstract

This study presents the generation of a multi-block structured grid on a real abdominal aortic aneurysm (AAA) acquired from Digital Imaging and Communication in Medicine (DICOM) data. With the use of a computed tomography exam (or medical images in standard DICOM format), the shape of a human organ is extracted and a structured computational grid is created. The structured grid generation is done by utilising Floater's and Gopalsamy et al.'s algorithm. The proposed methodology is applied to the AAA case, but it may also be applied to other human organs, enabling the scientist to develop an advanced patient-specific model. More importantly, the proposed methodology provides a precise reconstruction of the human organs, which is required in an AAA, where small variations in the geometry may alter the flow field, the stresses exerted on the walls and finally the rupture risk of the aneurysm.

Automatic lumen segmentation in CT and PC-MR images of abdominal aortic aneurysm

“…Image (1) Image (2) No Yes Due to variations of contrast enhancements from poor contrast in contrast-enhanced images to non-contrast enhanced images, one might consider an enhancement measure that can be used as the decision criterion on the level of how much further enhancement is needed. This step is performed after image pre-processing using LoG denoising.…”

“…Fifteen thousand people per year die from AAA rupture in the United States alone, making it the 13th leading cause of death, affecting 1 out of 20 men over 65 years old. [1,2].…”

“…To generate a patient-specific model from a patient's DICOM image data, segmentation of the organ of interest, e.g. AAA, is performed to highlight the object boundaries [2]. Vascular segmentation through the use of image processing tools provides significant information that allows for categorization, registration, visualization, and pattern recognition.…”

A semi-automated patient specific CFD analysis framework for cardiovascular system simulations

“…This procedure is done by an in-house code developed for the needs of the framework, which is described analyticaly in [11]. The in-house code has the abillity to produce a multiblock structured computational grid which conforms to the surface and with grid clustering near the artery walls.…”