Exploration of time sequential, patient specific 3D heart unlocks clinical understanding

Analysis and evaluation of patient-specific three-dimensional printing in complex septal myectomy

OBJECTIVES

This study aimed to assess the effectiveness of three-dimensional printing (3DP) in patients with complex hypertrophic cardiomyopathy requiring combined transaortic and transapical septal myectomy.

METHODS

We created 3DP models for 7 patients undergoing this surgery approach between June and October 2022 using silicone-like resin and conducted mock operations. The models were compared with echocardiography to identify abnormal muscle bundles and heart structures. These patients were then compared with a 1:2 matched group without 3DP, considering age, sex and additional operations.

RESULTS

The models mostly presenting with midventricular obstruction showed high consistency with original computed tomography data (r = 0.978, P < 0.001). 3DP identified more abnormal muscle bundles than echocardiography, primarily between the interventricular septum and apex. Excised specimens in mock operations mirrored those in actual myectomies. While cardiopulmonary bypass time was not significantly different, a near-20-min decrease was observed in the 3DP group (135.5 ± 31.1 vs 154.4 ± 36.6 min, P = 0.054).

CONCLUSIONS

While no significant differences in surgical outcomes were observed, 3DP appeared to enhance the visualization and understanding of spatial structures (average Likert scale score 4.0), potentially contributing to surgical proficiency (overall rating score 3.9). The use of 3DP may offer additional value in the preparation and execution of operations for complex hypertrophic cardiomyopathy cases.

HEARTBEAT4D: An Open-source Toolbox for Turning 4D Cardiac CT into VR/AR

Four-dimensional data sets are increasingly common in MRI and CT. While clinical visualization often focuses on individual temporal phases capturing the tissue(s) of interest, it may be possible to gain additional insight through exploring animated 3D reconstructions of physiological motion made possible by augmented or virtual reality representations of 4D patient imaging. Cardiac CT acquisitions can provide sufficient spatial resolution and temporal data to support advanced visualization, however, there are no open-source tools readily available to facilitate the transformation from raw medical images to dynamic and interactive augmented or virtual reality representations. To address this gap, we developed a workflow using free and open-source tools to process 4D cardiac CT imaging starting from raw DICOM data and ending with dynamic AR representations viewable on a phone, tablet, or computer. In addition to assembling the workflow using existing platforms (3D Slicer and Unity), we also contribute two new features: 1. custom software which can propagate a segmentation created for one cardiac phase to all others and export to surface files in a fully automated fashion, and 2. a user interface and linked code for the animation and interactive review of the surfaces in augmented reality. Validation of the surface-based areas demonstrated excellent correlation with radiologists' image-based areas (R > 0.99). While our tools were developed specifically for 4D cardiac CT, the open framework will allow it to serve as a blueprint for similar applications applied to 4D imaging of other tissues and using other modalities. We anticipate this and related workflows will be useful both clinically and for educational purposes.