Improved Visualisation of Patient-Specific Heart Structure Using Three-Dimensional Printing Coupled with Image-Processing Techniques Inspired by Astrophysical Methods

TL;DR

This study introduces a novel method inspired by astrophysics image-processing to create detailed 3D printed models of patient-specific hearts from CT data, enhancing visualization for better cardiovascular procedural planning.

Contribution

It demonstrates how astrophysical image-processing techniques can improve 3D heart modeling from CT scans, providing a step-by-step open-source workflow for medical visualization.

Findings

Clearer visualization of heart structures, especially in small features.

Successful 3D printing of detailed heart models including the aortic valve.

Improved modeling accuracy over traditional methods.

Abstract

The aim of this study is to use image-processing techniques developed in the field of astrophysics as inspiration for a novel approach to the three-dimensional (3D) imaging of periprocedural medical data, with the intention of providing improved visualisation of patient-specific heart structure and thereby allowing for an improved quality of procedural planning with regards to individualized cardiovascular healthcare. Using anonymized patient DICOM data for a cardiac computed tomography (CT) angiography, two-dimensional slices of the patient's heart were processed using a series of software packages in order to produce an accurate 3D representation of the patient's heart tissue as a computer-generated stereolithography (STL) file, followed by the creation of a tactile 3D printout. We find that the models produced provide clear definition of heart structure, in particular in the left atrium, left ventricle and aorta. This level of clarity also allows for the aortic valve to be observed and 3D printed. This study provides a step-by-step blueprint of how this can be achieved using open source software, specifically Slicer 4.8.1, MeshLab and AutoDesk Netfabb. In addition, the implementation of astrophysical image-processing techniques shows an improvement in modelling of the heart based on the CT data, in particular in the case of small-scale features where echocardiography has previously been required for more reliable results.