3D printing of human aneurysm aortic artery using CT scan images

Saripuzan, Muhammad Shahrul Rizal (2025) 3D printing of human aneurysm aortic artery using CT scan images. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

Aortic artery aneurysms are a critical condition characterised by the weakening and outward bulging of the aortic wall, necessitating prompt discovery and treatment strategy formulation. This research established a novel process for producing precise patient-specific 3D printed models of aortic aneurysms using CT scan imaging data. The integrated methodology amalgamated cardiovascular computed tomography (CT) with 3D printing for clinical applications, evaluating the efficacy of 3D models in preoperative surgery planning, educational endeavours, and enhanced patient outcomes. The process included image acquisition via high-resolution spiral CT angiography, image segmentation to delineate the aneurysm shape, 3D reconstruction to create a digital model, and 3D printing of the patient-specific physical model. The digital model was transferred into Ansys software for computational fluid dynamics (CFD) simulation to assist the study. This entailed delineating blood characteristics, establishing pragmatic boundary conditions, and modelling blood flow to examine flow patterns, pressure distribution, and wall shear stress. Stringent quality assurance protocols were established to assess segmentation, digital editing, and printing precision. The resultant 3D printed replicas, integrated with CFD data, provided accurate representations of each patient's distinct aortic aneurysm anatomy, allowing for visualisation of the aneurysm and surrounding structures for surgical planning, intervention simulation, and enhancing medical education and patient comprehension. This study illustrated the transformative potential of incorporating 3D printing and CFD analysis into cardiovascular medicine by examining technical aspects, assessing clinical impact, and evaluating economic feasibility. It provides a comprehensive solution for precise anatomical modelling, enhances diagnostic and therapeutic decision-making, and may improve outcomes for patients with aortic aneurysms.

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