Optimisation of computed tomography protocols for cardiac imaging using three-dimensional printing technology - Kamarul Amin Abdullah
Objectives: This thesis investigates the application of 3D-printing technology for optimising coronary computed tomography (CT) angiography (CCTA) protocols using iterative reconstruction (IR) algorithm as a dose optimisation strategy. The specific objectives are to: (i) design and develop a novel 3D-printed cardiac insert phantom derived from a volumetric computed tomography (CT) image datasets of the Lungman phantom; (ii) and (iii) investigate its application to evaluate the effect on CT image quality of IR algorithms and their strengths with a low tube current or voltage for dose reduction of CCTA protocols. Methods: The study was conducted in three phases. In phase one, the novel 3D-printed cardiac insert phantom was designed and developed. The size and shape of this printed phantom replicated the original cardiac insert of the Lungman anthropomorphic chest phantom. The attenuation (Hounsfield Unit, HU) values of the printed phantom filling materials were compared to coronary CT angiography (CCTA) patients and Catphan® 500 images. In phase two, the printed phantom was plilCed within the Lungman phantom and scanned at multiple dose levels, and the datasets were reconstructed using the filtered back projection (FBP) and different IR algorithm strengths. The image quality characteristics of image noise, signal-noise ratio (SNR), and contrast-noise ratio (CNR) were measured and compared to the previous literature to determine the dose reduction potential. In the third phase, the influence of using different lR algorithm strengths with low-tube voltage for dose optimisation studies was investigated. The printed phantom and the Catphan® 500 phantoms were scanned at different tube currents and voltages. The results obtained were then compared to the patient datasets to measure the agreement between the phantoms and patient datasets. Results: In phase one, a novel 3D-printed cardiac insert phantom was developed. The measurements of CT HU values were consistent between the printed phantom, patient and Catphan® 500 images. In phase two, the results of the printed phantom showed that decreasing dose levels had significantly increased the image noise (p<O.OOl). As a result, the SNR and CNR were significantly decreased (p<O.OOl). The application of IR algorithm at various strengths had yielded a stepwise improvement of noise image Quality with a dose reduction potential of up to 40%. Image noise was reduced significantly (p<O.OOl) and thus increased the SNR and CNR as compared to the FBP. In phase three, the printed phantom results showed a significant interaction between the effects of low-tube voltage and the IR algorithm strengths on image quality (all p<O.OOl) but not the CT HU values. The mean differences in image quality characteristics were small between the patient-phantom datasets. The optimised CT protocols allowed up to 57% dose reduction in CCTA protocols while maintaining the image quality. Conclusions: The 3D printing technology was used to produce a novel design of cardiac insert phantom for the Lungman phantom. The 3D-printed cardiac insert phantom can be used to evaluate the effect of using IR algorithm on dose reduction and image quality. The dose optimisation assessment using the phantom-method demonstrated a combination of IR algorithm and low tube voltage could further reduce the radiation dose to the patient while maintaining the image quality. This thesis proposes and validates a new method of developing phantoms for CCTA dose optimisation studies.