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Updated: May 11, 2026
Development and Evaluation of 3D-Printed Cardiovascular Phantoms for Interventional Planning and Training
Published on: January 18, 2021
Automatic 3D camera positioning in cardiac computed tomography: A phantom study
Y H Hadi1, A Legoff2, N Moore3
1Discipline of Medical Imaging and Radiation Therapy, School of Medicine and Health, University College Cork, Ireland; Department of Medical Imaging and Intervention, King Abdullah Medical City (KAMC), Makkah, Saudi Arabia.
Introduction:
Cardiac computed tomography angiography (CCTA) is essential for diagnosing coronary artery disease, with accurate positioning critical for optimising image quality (IQ) and radiation exposure. Vertical misalignment can degrade IQ and increase radiation dose. Automatic 3D camera positioning systems claim to improve accuracy and reduce errors, though research on their effectiveness in CCTA remains limited. This study evaluates positioning accuracy, radiation dose, and IQ when using automatic 3D camera positioning in CCTA across scenarios.
Methods:
This prospective phantom study utilised the Multipurpose Chest N1 Phantom (Kyoto Kagaku, Japan) across three body sizes. Positioning variations included supine versus prone, head-first versus feet-first orientations, and various body surface coverings. CT scans were undertaken on a GE Revolution Apex Elite (GE Healthcare, USA) scanner. Vertical offsets from the isocentre were measured using DoseWatch software (GE Healthcare), while radiation dose was quantified through dose-length product (DLP) and Computed Tomography Dose Index (CTDIvol). IQ was assessed by calculating the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and conspicuity index.
Results:
Automatic 3D camera positioning achieved a mean (standard deviation) vertical offset of -1.0 (1.5) mm. Larger phantom sizes were significantly associated with increased off-centring, as indicated by Fisher's exact test (p = 0.004), and greater offsets correlated with higher radiation doses (r = 0.45, p < 0.05). IQ metrics, including SNR and CNR, decreased with increased offsets; SNR dropped from 71. to 50.9, and CNR from 0.2 to -0.6.
Conclusion:
This study demonstrates that automated 3D camera positioning in CCTA supports radiographers by enhancing positioning accuracy, lowering radiation exposure and improving IQ. Further work should examine the impact of automatic 3D camera positioning within clinical practice.
Implication For Practice:
Automatic 3D camera positioning in CCTA will likely improve patient care and safety.
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