Technical limitations and error propagation in the 3D printing pipeline for congenital heart disease: an integrative review—a narrative synthesis
Abstract
Three-dimensional (3D) printing has gained prominence in the management of congenital heart disease (CHD) by augmenting spatial understanding, facilitating preoperative planning, and supporting education for clinicians and families. The clinical validity of printed models, however, is contingent upon accuracy maintained across a multistage pipeline that spans image acquisition, segmentation and modelling, printer-specific processing, and post-processing with subsequent clinical interpretation. Technical and human factors introduce discrepancies at each stage; these inaccuracies may accumulate and propagate, thereby altering the geometric and qualitative fidelity of the final model. This integrative review examines the principal sources of error across the pipeline, outlines mechanisms of propagation, and considers implications for decision-making in CHD, with particular emphasis on paediatric applications where permissible tolerances are narrow. Drawing upon contemporary literature, we provide recommendations for protocol standardization, validation procedures, operator training, and transparent documentation. An inter-observer experiment is proposed to quantify segmentation-induced variability using similarity and surface distance metrics, linking measurable divergence to potential clinical impact. A pragmatic error-minimizing pipeline is also described to improve reliability and promote reproducibility in clinical practice.
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BibTeX
@article{balaji2026technical,
title = {{Technical limitations and error propagation in the 3D printing pipeline for congenital heart disease: an integrative review—a narrative synthesis}},
author = {Ayush Balaji and Sinling Tiffany Yu and Nabil Hussein and Tristan Ramcharan and Benjamin Pinkey and Antonio Fratini and Adrian Crucean},
journal = {European Heart Journal. Imaging Methods and Practice},
year = {2026},
month = nov,
doi = {10.1093/ehjimp/qyag170},
url = {https://doi.org/10.1093/ehjimp/qyag170},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Technical limitations and error propagation in the 3D printing pipeline for congenital heart disease: an integrative review—a narrative synthesis
AU - Ayush Balaji
AU - Sinling Tiffany Yu
AU - Nabil Hussein
AU - Tristan Ramcharan
AU - Benjamin Pinkey
AU - Antonio Fratini
AU - Adrian Crucean
PY - 2026
DA - 2026/11/05
JO - European Heart Journal. Imaging Methods and Practice
DO - 10.1093/ehjimp/qyag170
UR - https://doi.org/10.1093/ehjimp/qyag170
AB - Three-dimensional (3D) printing has gained prominence in the management of congenital heart disease (CHD) by augmenting spatial understanding, facilitating preoperative planning, and supporting education for clinicians and families. The clinical validity of printed models, however, is contingent upon accuracy maintained across a multistage pipeline that spans image acquisition, segmentation and modelling, printer-specific processing, and post-processing with subsequent clinical interpretation. Technical and human factors introduce discrepancies at each stage; these inaccuracies may accumulate and propagate, thereby altering the geometric and qualitative fidelity of the final model. This integrative review examines the principal sources of error across the pipeline, outlines mechanisms of propagation, and considers implications for decision-making in CHD, with particular emphasis on paediatric applications where permissible tolerances are narrow. Drawing upon contemporary literature, we provide recommendations for protocol standardization, validation procedures, operator training, and transparent documentation. An inter-observer experiment is proposed to quantify segmentation-induced variability using similarity and surface distance metrics, linking measurable divergence to potential clinical impact. A pragmatic error-minimizing pipeline is also described to improve reliability and promote reproducibility in clinical practice.
SN - 2755-9637
ER -