METHODS: A customised polymethyl methacrylate (PMMA) cylindrical phantom was developed for performance evaluation of Planmeca ProMax 3D Mid digital dental CBCT unit. The fabricated phantom consists of four different layers for testing specific IQ parameters such as CT number accuracy and uniformity, noise and CT number linearity. The phantom was scanned using common scanning protocols in clinical routine (90.0 kV, 8.0 mA and 13.6 s). In region-of-interest (ROI) analysis, the mean CT numbers (in Hounsfield unit, HU) and noise for water and air were determined and compared with the reference values (0 HU for water and -1000 HU for air). For linearity test, the correlation between the measured HU of different inserts with their density was studied.
RESULTS: The average CT number were -994.1 HU and -2.4 HU, for air and water, respectively and the differences were within the recommended acceptable limit. The linearity test showed a strong positive correlation (R2 = 0.9693) between the measured HU and their densities.
CONCLUSION: The fabricated IQ phantom serves as a simple and affordable testing tool for digital dental CBCT imaging.
METHODS: Cardiac insert volumes were segmented from CT image datasets, derived from an anthropomorphic chest phantom of Lungman N-01 (Kyoto Kagaku, Japan). These segmented datasets were converted to a virtual 3D-isosurface of heart-shaped shell, while two other removable inserts were included using computer-aided design (CAD) software program. This newly designed cardiac insert phantom was later printed by using a fused deposition modelling (FDM) process via a Creatbot DM Plus 3D printer. Then, several selected filling materials, such as contrast media, oil, water and jelly, were loaded into designated spaces in the 3D-printed phantom. The 3D-printed cardiac insert phantom was positioned within the anthropomorphic chest phantom and 30 repeated CT acquisitions performed using a multi-detector scanner at 120-kVp tube potential. Attenuation (Hounsfield Unit, HU) values were measured and compared to the image datasets of real-patient and Catphan® 500 phantom.
RESULTS: The output of the 3D-printed cardiac insert phantom was a solid acrylic plastic material, which was strong, light in weight and cost-effective. HU values of the filling materials were comparable to the image datasets of real-patient and Catphan® 500 phantom.
CONCLUSIONS: A novel and cost-effective cardiac insert phantom for anthropomorphic chest phantom was developed using volumetric CT image datasets with a 3D printer. Hence, this suggested the printing methodology could be applied to generate other phantoms for CT imaging studies.
METHODS: The 3D-printed cardiac insert phantom was positioned into a chest phantom and scanned with a 16-slice CT scanner. Acquisitions were performed with CCTA protocols using 120 kVp at four different tube currents, 300, 200, 100 and 50 mA (protocols A, B, C and D, respectively). The image data sets were reconstructed with a filtered back projection (FBP) and three different IR algorithm strengths. The image quality metrics of image noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were calculated for each protocol.
RESULTS: Decrease in dose levels has significantly increased the image noise, compared to FBP of protocol A (P