METHODS: The imaging performance of the camera system was assessed quantitatively and qualitatively at different source depths, source to collimator distances (SCD), activity levels, acquisition times and source separations, utilising bespoke phantoms.
RESULTS: The system sensitivity and spatial resolution of the HGC for 125I were 0.41 cps/MBq (at SCD 48 mm) and 1.53 ± 0.23 mm (at SCD 10 mm) respectively. The camera was able to detect the 125I seed at a SCD of 63 mm (with no scattering material in place) in images recorded within a 1-min acquisition time. The detection of the seeds beneath scattering material (simulating deep-seated tumours) was limited to depths of less than 20 mm beneath the skin surface with a SCD of 63 mm and seed activity of 2.43 MBq. Subjective assessments of the hybrid images acquired showed the capability of the HGC for localising the 125I seeds.
CONCLUSION: This preliminary ex vivo study demonstrates that the HGC is capable of detecting 125I seeds and could be a useful tool in radioactive seed localisation with the added benefit of providing hybrid optical γ images for guiding breast conserving surgery.
ADVANCES IN KNOWLEDGE: The SFOV HGC could provide high resolution fused optical-gamma images of 125I radioactive seeds indicating the potential use in intraoperative surgical procedure such as RSL.
METHODS: Dose measurement of a standard pear-shaped plan carried out in phantom to verify the MOSkin dose measurement accuracy. With MOSkin attached to the third diode, RP3 of the PTW 9112, both detectors were inserted into patients' rectum. The RP3 and MOSkin measured doses in 18 sessions as well as the maximum measured doses from PTW 9112, RPmax in 48 sessions were compared to the planned doses.
RESULTS: Percentage dose differences ΔD (%) in phantom study for two MOSkin found to be 2.22 ± 0.07% and 2.5 ± 0.07%. IVD of 18 sessions resulted in ΔD(%) of -16.3% to 14.9% with MOSkin and ΔD(%) of -35.7% to -2.1% with RP3. In 48 sessions, RPmax recorded ΔD(%) of -37.1% to 11.0%. MOSkin_measured doses were higher in 44.4% (8/18) sessions, while RP3_measured were lower than planned doses in all sessions. RPmax_measured were lower in 87.5% of applications (42/47).
CONCLUSIONS: The delivered doses proven to deviate from planned doses due to unavoidable shift between imaging and treatment as measured with MOSkin and PTW 9112 detectors. The integration of MOSkin on commercial PTW 9112 surface found to be feasible for rectal dose IVD during cervical HDR ICBT.
Methods: A patient-specific 3D-printed breast model was generated using 3D-printing techniques for the construction of the hollow skin and fibroglandular region shells. Then, the T1 relaxation times of the five selected materials (agarose gel, silicone rubber with/without fish oil, silicone oil, and peanut oil) were measured on a 3T MRI system to determine the appropriate ones to represent the MR imaging characteristics of fibroglandular and adipose tissues. Results were then compared to the reference values of T1 relaxation times of the corresponding tissues: 1,324.42±167.63 and 449.27±26.09 ms, respectively. Finally, the materials that matched the T1 relaxation times of the respective tissues were used to fill the 3D-printed hollow breast shells.
Results: The silicone and peanut oils were found to closely resemble the T1 relaxation times and imaging characteristics of these two tissues, which are 1,515.8±105.5 and 405.4±15.1 ms, respectively. The agarose gel with different concentrations, ranging from 0.5 to 2.5 wt%, was found to have the longest T1 relaxation times.
Conclusions: A patient-specific 3D-printed breast phantom was successfully designed and constructed using silicone and peanut oils to simulate the MR imaging characteristics of fibroglandular and adipose tissues. The phantom can be used to investigate different MR breast imaging protocols for the quantitative assessment of breast density.
METHOD: We simulate the CT head examination using a water phantom with a standard protocol (120 kVp/180 mAs) and a low dose protocol (100 kVp/142 mAs). The table height was adjusted to simulate miscentering by 5 cm from the isocenter, where the height was miscentered superiorly (MCS) at 109, 114, 119, and 124 cm, and miscentered inferiorly (MCI) at 99, 94, 89, and 84 cm. Seven circular regions of interest were used, with one drawn at the center, four at the peripheral area of the phantom, and two at the background area of the image.
RESULTS: For the standard protocol, the mean CNR decreased uniformly as table height increased and significantly differed (p
METHODS: A 3D-printed cardiac insert and Catphan 500 phantoms were scanned using CCTA protocols at 120 and 100 kVp tube voltages. All CT acquisitions were reconstructed using filtered back projection (FBP) and Adaptive Statistical Iterative Reconstruction (ASIR) algorithm at 40% and 60% strengths. Image quality characteristics such as image noise, signal-noise ratio (SNR), contrast-noise ratio (CNR), high spatial resolution, and low contrast resolution were analyzed.
RESULTS: There was no significant difference (P > 0.05) between 120 and 100 kVp measures for image noise for FBP vs ASIR 60% (16.6 ± 3.8 vs 16.7 ± 4.8), SNR of ASIR 40% vs ASIR 60% (27.3 ± 5.4 vs 26.4 ± 4.8), and CNR of FBP vs ASIR 40% (31.3 ± 3.9 vs 30.1 ± 4.3), respectively. Based on the Modulation Transfer Function (MTF) analysis, there was a minimal change of image quality for each tube voltage but increases when higher strengths of ASIR were used. The best measure of low contrast detectability was observed at ASIR 60% at 120 kVp.
CONCLUSIONS: Changing the IR strength has yielded different image quality noise characteristics. In this study, the use of 100 kVp and ASIR 60% yielded comparable image quality noise characteristics to the standard CCTA protocols using 120 kVp of ASIR 40%. A combination of 3D-printed and Catphan® 500 phantoms could be used to perform CT dose optimization protocols.
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
METHODS: The European Association of Nuclear Medicine (EANM) procedure guidelines version 2.0 for FDG-PET tumor imaging has adhered for this purpose. A NEMA2012/IEC2008 phantom was filled with tumor to background ratio of 10:1 with the activity concentration of 30 kBq/ml ± 10 and 3 kBq/ml ± 10% for each radioisotope. The phantom was scanned using different acquisition times per bed position (1, 5, 7, 10 and 15 min) to determine the Tmin. The definition of Tmin was performed using an image coefficient of variations (COV) of 15%.
RESULTS: Tmin obtained for 18F, 68Ga and 124I were 3.08, 3.24 and 32.93 min, respectively. Quantitative analyses among 18F, 68Ga and 124I images were performed. Signal-to-noise ratio (SNR), contrast recovery coefficients (CRC), and visibility (VH) are the image quality parameters analysed in this study. Generally, 68Ga and 18F gave better image quality as compared to 124I for all the parameters studied.
CONCLUSION: We have defined Tmin for 18F, 68Ga and 124I SPECT CT imaging based on NEMA2012/IEC2008 phantom imaging. Despite the long scanning time suggested by Tmin, improvement in the image quality is acquired especially for 124I. In clinical practice, the long acquisition time, nevertheless, may cause patient discomfort and motion artifact.
Methods and materials: The phantom is fabricated with two main parts, liver parenchyma and HCC inserts. The liver parenchyma was fabricated by adding 2.5 wt% of agarose powder combined with 2.6 wt% of wax powder while the basic material for the HCC samples was made from polyurethane solution combined with 5 wt% glycerol. Three HCC samples were inserted into the parenchyma by using three cylinders implanted inside the liver parenchyma. An automatic injector is attached to the input side of the cylinders and a suction device connected to the output side of the cylinders. After the phantom was prepared, the contrast materials were injected into the phantom and imaged using MRI, CT, and ultrasound.
Results: Both HCC samples and liver parenchyma were clearly distinguished using the three imaging modalities: MRI, CT, and ultrasound. Doppler ultrasound was also applied through the HCC samples and the flow pattern was observed through the samples.
Conclusion: A multimodal dynamic liver phantom, with HCC tumor models have been fabricated. This phantom helps to improve and develop different methods for detecting HCC in its early stages.