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Advisor(s)
Abstract(s)
Objectives: To verify if the mAs and reconstruction techniques affect the visualisation of relevant structures in lung Computed Tomography (CT) using a phantom. Methods: Images were acquired using various mAs and reconstruction techniques. Image quality (IQ) was analysed applying two approaches: perceptual, using 5 observers and objective (edge gradient calculation) to verify the sharpness of the structures. Dose was recorded. Wilcoxon Signed Rank test was used to compare the data from the perceptual image analysis. P-values were calculated (Bonferroni-Correction method) to compare reconstruction techniques and mAs. A
Kappa Test with linear weighting was performed to calculate the level of agreement between observers. Results: The Wilcoxon-Signed-Rank-Test showed no significant difference between the reconstruction techniques tested (p<0.05). In addition, the test showed no significant difference between any of the mAs values with a Bonferroni correction (p = 0.0167). For 10 mAs the observers scored differently, depending on which structures they were looking at. The overall IQ was acceptable and the nodules were well defined. The agreement for visualising the range of anatomical regions (Kappa test linear-weighting) suggests that observer 2 and 3 had a poor agreement level (0-0.366) and observer 1,4 and 5 had moderate agreement (0.5714-0.751). Conclusion: The visual measures of IQ were largely unaffected by reconstruction techniques or mAs values. However, further work is needed for a better understanding of visual and clinical value of reconstruction techniques at lower doses.
Description
Keywords
Lungs CT Reconstruction techniques mAs Image quality Optimisation.
Citation
Reis CS, Faqir T, Harsaker V, Hogg P, Kristoffersen L, van Rein IL, et al. Optimisation of chest computed tomography using a phantom: impact of mAs and reconstruction techniques on image quality. In: Hogg P, Blakeley C, Buissink C, editors. OPTIMAX 2015 – Multicultural team-based research in radiography: a holistic educational approach. Groningen: Hanze University of Applied Sciences; 2016. p. 112-27.
Publisher
Hanze University of Applied Sciences