A CNN-based denoising method trained with images acquired with electron density phantoms for thin-sliced coronary artery calcium scans.

PURPOSE: This work proposed a convolutional neural network (CNN)-based method trained with images acquired with electron density phantoms to reduce quantum noise for coronary artery calcium (CAC) scans reconstructed with slice thickness less than 3 mm. METHODS: A DenseNet model was used to estimate quantum noise for CAC scans reconstructed with slice thickness of 0.5, 1.0 and 1.5 mm. Training data was acquired using electron density phantoms in three different sizes. The label images of the CNN model were real noise maps, while the input images of the CNN model were pseudo noise maps. Image denoising was conducted by subtracting the CNN output images from thin-sliced CAC scans. The efficacy of the proposed method was verified through both phantom study and patient study. RESULTS: By means of phantom study, the proposed method was proven effective in reducing quantum noise in CAC scans reconstructed with 1.5-mm slice thickness without causing significant texture change or variation in HU values. With regard to patient study, calcifications were more clear on the denoised CAC scans reconstructed with slice thickness of 0.5, 1.0 and 1.5 mm than on 3-mm slice images, while over-smooth changes were not observed in the denoised CAC scans reconstructed with 1.5-mm slice thickness. CONCLUSION: Our results demonstrated that the electron density phantoms can be used to generate training data for the proposed CNN-based denoising method to reduce quantum noise for CAC scans reconstructed with 1.5-mm slice thickness. Because anthropomorphic phantom is not a necessity, our method could make image denoising more practical in routine clinical practice.

Reducing scan time in 177 Lu planar scintigraphy using convolutional neural network: A Monte Carlo simulation study.

PURPOSE: The aim of this study was to reduce scan time in 177 Lu planar scintigraphy through the use of convolutional neural network (CNN) to facilitate personalized dosimetry for 177 Lu-based peptide receptor radionuclide therapy. METHODS: The CNN model used in this work was based on DenseNet, and the training and testing datasets were generated from Monte Carlo simulation. The CNN input images (IMGinput ) consisted of 177 Lu planar scintigraphy that contained 10-90% of the total photon counts, while the corresponding full-count images (IMG100% ) were used as the CNN label images. Two-sample t-test was conducted to compare the difference in pixel intensities within region of interest between IMG100% and CNN output images (IMGoutput ). RESULTS: No difference was found in IMGoutput for rods with diameters ranging from 13 to 33 mm in the Derenzo phantom with a target-to-background ratio of 20:1, while statistically significant differences were found in IMGoutput for the 10-mm diameter rods when IMGinput containing 10% to 60% of the total photon counts were denoised. Statistically significant differences were found in IMGoutput for both right and left kidneys in the NCAT phantom when IMGinput containing 10% of the total photon counts were denoised. No statistically significant differences were found in IMGoutput for any other source organs in the NCAT phantom. CONCLUSION: Our results showed that the proposed method can reduce scan time by up to 70% for objects larger than 13 mm, making it a useful tool for personalized dosimetry in 177 Lu-based peptide receptor radionuclide therapy in clinical practice.

Reduction of Viral and Bacterial Activity by Using a Self-Powered Variable-Frequency Electrical Stimulation Device.

Viruses and bacteria, which can rapidly spread through droplets and saliva, can have serious effects on people's health. Viral activity is traditionally inhibited using chemical substances, such as alcohol or bleach, or physical methods, such as thermal energy or ultraviolet-light irradiation. However, such methods cannot be used in many applications because they have certain disadvantages, such as causing eye or skin injuries. Therefore, in the present study, the electrical stimulation method is used to stimulate a virus, namely, coronavirus 229E, and two types of bacteria, namely, Escherichia coli and Staphylococcus aureus, to efficiently reduce their infectivity of healthy cells (such as the Vero E6 cell in a viral activity-inhibition experiment). The infectivity effects of the aforementioned virus and bacteria were examined under varying values of different electrical stimulation parameters, such as the stimulation current, frequency, and total stimulation time. The experimental results indicate that the activity of coronavirus 229E is considerably inhibited through direct-current pulse stimulation with a current of 25 mA and a frequency of 2 or 20 Hz. In addition, E. coli activity was reduced by nearly 80% in 10 s through alternating-current pulse stimulation with a current of 50 mA and a frequency of 25 Hz. Moreover, a self-powered electrical stimulation device was constructed in this study. This device consists of a solar panel and battery to generate small currents with variable frequencies, which has advantages of self-powered and variable frequencies, and the device can be utilized on desks, chairs, or elevator buttons for the inhibition of viral and bacterial activities.

Investigating the Feasibility of Using DenseNet to Improve Coronary Calcification Detection in CT.

OBJECTIVES: Interscan reproducibility of coronary artery calcium (CAC) scoring can be improved by using a smaller slice thickness but at the cost of higher image noise. This study aimed to investigate the feasibility of using densely connected convolutional network (DenseNet) to reduce the image noise in CAC scans reconstructed with slice thickness < 3 mm for improving coronary calcification detection in CT. METHODS: Phantom data acquired with QRM and CIRS phantoms were used for model training and testing, where the DenseNet model adopted in this work was a convolutional neural network (CNN) designed for super resolution recovery. After phantom study, the proposed method was evaluated in terms of its ability to improve calcification detection using patient data. The CNN input images (IMGinput) were CAC scans reconstructed with 0.5-, 1.0- and 1.5-mm slice thickness, while CNN label images were CAC scans reconstructed with 3-mm slice thickness (IMG3mm). Region of interest (ROI) analysis was carried out on IMG3mm, IMGinput and CNN output images (IMGoutput). Two-sample t test was used to compare the difference in Hounsfield Unit (HU) values within ROI between IMG3mm and IMGoutput. RESULTS: For the calcifications in QRM phantoms, no statistically significant difference was found when comparing the HU values of 400- and 800-HA calcifications identified on IMG3mm to those on IMGoutput with slice thickness of 0.5, 1.0 or 1.5 mm. On the other hand, statistically significant difference was found when comparing the HU values of 200-HA calcifications identified on IMG3mm to those on IMGoutput with a slice thickness of 0.5 and 1.0 mm. Meanwhile, no statistically significant difference was found when comparing the HU values of 200-HA calcifications identified on IMG3mm to those on IMGoutput with a slice thickness of 1.5 mm. As for the rod inserts in CIRS phantoms simulating 9 different tissue types in human body, there was no statistically significant difference between IMG3mm and IMGoutput with slice thickness of 1.5 mm, and all the p values were larger than 0.10. With regards to patient study, more calcification pixels were detected on IMGoutput with a slice thickness of 1.5 mm than on IMG3mm, so calcifications were more clear on the denoised images. CONCLUSION: According to our results, the CNN-based denoising method could reduce statistical noise in IMGinput with a slice thickness of 1.5 mm without causing significant texture change or variation in HU values. The proposed method could improve cardiovascular risk prediction by detecting small and soft calcifications that are barely identified on 3-mm slice images used in conventional CAC scans.

Investigating the lesion detectability of Tc-99m planar scintigraphy acquired with LEHRS collimator for patients with different body sizes: A phantom study.

PURPOSE: The aim of this work was to investigate the lesion detectability of Tc-99m planar scintigraphy acquired with a low-energy high-resolution and sensitivity (LEHRS) collimator and processed by Clarity 2D for patients with different body sizes through phantom study. METHODS: A NEMA IEC body phantom set was covered by two layers of 25-mm-thick bolus to construct phantom in three different sizes. All image data were performed on a Discovery NM/CT 870 DR with an LEHRS collimator and processed by Clarity 2D with blend ratio a of 0%, 20%, 40%, 60%, 80%, and 100%. The lesion detectability in gamma scintigraphy was evaluated by calculating the contrast-to-noise ratio (CNR). Multiple linear regression methods were used to analyze the impact of body size, target size, and Clarity 2D blending weight on the lesion detectability of Tc-99m planar scintigraphy. RESULTS: It was found that changing the blend ratio could improve CNR, and this phenomenon was more significant in anterior view than in posterior view. Our results also suggested that the blend ratio should be selected according to patient body size in order to maintain consistent CNR. Hence, when a blend ratio of 60% was used for a patient before cancer treatment, a lower blend ratio should be used for the same patient experiencing treatment-related weight loss to achieve consistent lesion detectability in Tc-99m planar scintigraphy acquired with LEHRS and processed by Clarity 2D. CONCLUSION: The magnitude of photon attenuation and scattering is higher in patients with larger body size, so Tc-99m planar scintigraphy usually has lower lesion detectability in obese patients. Although photon attenuation and scattering are inevitable during image formation, their impacts on image quality can be eased by employing appropriate image protocol parameters.

Effect of Body Mass Index in Coronary CT Angiography Performed on a 256-Slice Multi-Detector CT Scanner.

We aimed to investigate the effect of a patient's body mass index (BMI) on radiation dose and image quality in prospectively ECG-triggered coronary CT angiography (CCTA) performed on a 256-slice multi-detector CT scanner. In total, 87 consecutive patients receiving CCTA examinations acquired with tube current modulation (TCM) and iterative reconstruction (IR) were enrolled in this study. The dose report recorded from the CT scanner console was used to derive the effective dose for patients. Subjective image quality scoring and objective noise measurements were conducted to quantify the impact of BMI on the image quality of CCTA. Because of the TCM technique, we expected tube current and radiation dose to increase as BMI increased. However, using TCM did not always guarantee sufficient radiation exposure to achieve consistent image quality for overweight or obese patients since the maximum X-ray tube output in milliamperes and kilovoltage peak was reached. The impact of photon starvation noise on image quality was not significant until BMI ≥ 27 kg/m2; this result could be due to IR's noise reduction capability. Our results also suggest that using TCM with a noise index of 25 HU can reduce radiation dose without compromising image quality compared to images obtained based on the manufacturer's default settings.

Compensating Positron Range Effects of Ga-68 in Preclinical PET Imaging by Using Convolutional Neural Network: A Monte Carlo Simulation Study.

This study aimed to investigate the feasibility of positron range correction based on three different convolutional neural network (CNN) models in preclinical PET imaging of Ga-68. The first model (CNN1) was originally designed for super-resolution recovery, while the second model (CNN2) and the third model (CNN3) were originally designed for pseudo CT synthesis from MRI. A preclinical PET scanner and 30 phantom configurations were modeled in Monte Carlo simulations, where each phantom configuration was simulated twice, once for Ga-68 (CNN input images) and once for back-to-back 511-keV gamma rays (CNN output images) with a 20 min emission scan duration. The Euclidean distance was used as the loss function to minimize the difference between CNN input and output images. According to our results, CNN3 outperformed CNN1 and CNN2 qualitatively and quantitatively. With regard to qualitative observation, it was found that boundaries in Ga-68 images became sharper after correction. As for quantitative analysis, the recovery coefficient (RC) and spill-over ratio (SOR) were increased after correction, while no substantial increase in coefficient of variation of RC (CVRC) or coefficient of variation of SOR (CVSOR) was observed. Overall, CNN3 should be a good candidate architecture for positron range correction in Ga-68 preclinical PET imaging.

Applying MRI Intensity Normalization on Non-Bone Tissues to Facilitate Pseudo-CT Synthesis from MRI.

This study aimed to facilitate pseudo-CT synthesis from MRI by normalizing MRI intensity of the same tissue type to a similar intensity level. MRI intensity normalization was conducted through dividing MRI by a shading map, which is a smoothed ratio image between MRI and a three-intensity mask. Regarding pseudo-CT synthesis from MRI, a conversion model based on a three-layer convolutional neural network was trained and validated. Before MRI intensity normalization, the mean value ± standard deviation of fat tissue in 0.35 T chest MRI was 297 ± 73 (coefficient of variation (CV) = 24.58%), which was 533 ± 91 (CV = 17.07%) in 1.5 T abdominal MRI. The corresponding results were 149 ± 32 (CV = 21.48%) and 148 ± 28 (CV = 18.92%) after intensity normalization. With regards to pseudo-CT synthesis from MRI, the differences in mean values between pseudo-CT and real CT were 3, 15, and 12 HU for soft tissue, fat, and lung/air in 0.35 T chest imaging, respectively, while the corresponding results were 3, 14, and 15 HU in 1.5 T abdominal imaging. Overall, the proposed workflow is reliable in pseudo-CT synthesis from MRI and is more practicable in clinical routine practice compared with deep learning methods, which demand a high level of resources for building a conversion model.

Investigating the feasibility of generating dual-energy CT from one 120-kVp CT scan: a phantom study.

INTRODUCTION: This study aimed to investigate the feasibility of generating pseudo dual-energy CT (DECT) from one 120-kVp CT by using convolutional neural network (CNN) to derive additional information for quantitative image analysis through phantom study. METHODS: Dual-energy scans (80/140 kVp) and single-energy scans (120 kVp) were performed for five calibration phantoms and two evaluation phantoms on a dual-source DECT scanner. The calibration phantoms were used to generate training dataset for CNN optimization, while the evaluation phantoms were used to generate testing dataset. A CNN model which takes 120-kVp images as input and creates 80/140-kVp images as output was built, trained, and tested by using Caffe CNN platform. An in-house software to quantify contrast enhancement and synthesize virtual monochromatic CT (VMCT) for CNN-generated pseudo DECT was implemented and evaluated. RESULTS: The CT numbers in 80-kVp pseudo images generated by CNN are differed from the truth by 11.57, 16.67, 13.92, 12.23, 10.69 HU for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. The corresponding results for 140-kVp CT are 3.09, 9.10, 7.08, 9.81, 7.59 HU. The estimates of iodine concentration calculated based on the proposed method are differed from the truth by 0.104, 0.603, 0.478, 0.698, 0.795 mg/ml for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. With regards to image quality enhancement, VMCT synthesized by using pseudo DECT shows the best contrast-to-noise ratio at 40 keV. CONCLUSION: In conclusion, the proposed method should be a practicable strategy for iodine quantification in contrast enhanced 120-kVp CT without using specific scanner or scanning procedure.

Evaluation of Impact of Factors Affecting CT Radiation Dose for Optimizing Patient Dose Levels.

The dose metrics and factors influencing radiation exposure for patients undergoing head, chest, and abdominal computed tomography (CT) scans were investigated for optimization of patient dose levels. The local diagnostic reference levels (DRLs) of adult CT scans performed in our hospital were established based on 28,147 consecutive examinations, including 5510 head scans, 9091 chest scans, and 13,526 abdominal scans. Among the six CT scanners used in our hospital, four of them are 64-slice multi-detector CT units (MDCT64), and the other two have detector slices higher than 64 (MDCTH). Multivariate analysis was conducted to evaluate the effects of body size, kVp, mAs, and pitch on volume CT dose index (CTDIvol). The local DRLs expressed in terms of the 75th percentile of CTDIvol for the head, chest, and abdominal scans performed on MDCT64 were 59.32, 9.24, and 10.64 mGy, respectively. The corresponding results for MDCTH were 57.90, 7.67, and 9.86 mGy. In regard to multivariate analysis, CTDIvol showed various dependence on the predictors investigated in this study. All regression relationships have coefficient of determination (R2) larger than 0.75, indicating a good fit to the data. Overall, the research results obtained through our workflow could facilitate the modification of CT imaging procedures once the local DRLs are unusually high compared to the national DRLs.

Optimization of HU threshold for coronary artery calcium scans reconstructed at 0.5-mm slice thickness using iterative reconstruction.

PURPOSE: This work investigated the simultaneous influence of tube voltage, tube current, body size, and HU threshold on calcium scoring reconstructed at 0.5-mm slice thickness using iterative reconstruction (IR) through multivariate analysis. Regression results were used to optimize the HU threshold to calibrate the resulting Agatston scores to be consistent with those obtained from the conventional protocol. METHODS: A thorax phantom set simulating three different body sizes was used in this study. A total of 14 coronary artery calcium (CAC) protocols were studied, including 1 conventional protocol reconstructed at 3-mm slice thickness, 1 FBP protocol, and 12 statistical IR protocols (3 kVp values*4 SD values) reconstructed at 0.5-mm slice thickness. Three HU thresholds were applied for calcium identification, including 130, 150, and 170 HU. A multiple linear regression method was used to analyze the impact of kVp, SD, body size, and HU threshold on the Agatston scores of three calcification densities for IR-reconstructed CAC scans acquired with 0.5-mm slice thickness. RESULTS: Each regression relationship has R2 larger than 0.80, indicating a good fit to the data. Based on the regression models, the HU thresholds as a function of SD estimated to ensure the quantification accuracy of calcium scores for 120-, 100-, and 80-kVp CAC scans reconstructed at 0.5-mm slice thickness using IR for three different body sizes were proposed. Our results indicate that the HU threshold should be adjusted according to the imaging condition, whereas a 130-HU threshold is appropriate for 120-kVp CAC scans acquired with SD = 55 for body size of 24.5 cm. CONCLUSION: The optimized HU thresholds were proposed for CAC scans reconstructed at 0.5-mm slice thickness using IR. Our study results may provide a potential strategy to improve the reliability of calcium scoring by reducing partial volume effect while keeping radiation dose as low as reasonably achievable.

Relationship between heart rate and optimal reconstruction phase in coronary CT angiography performed on a 256-slice multidetector CT.

OBJECTIVE: This study aimed to evaluate the relationship between heart rate (HR) and optimal reconstruction phase in prospectively electrocardiogram (ECG)-triggered coronary CT angiography (CCTA) performed on a newly introduced 256-slice multidetector CT (MDCT). METHODS: All the cases were selected retrospectively from the patients scheduled for CCTA in our department between January and April 2017. The scanner selected the optimal exposure phase based on 10 s ECG recordings. To ensure the success of CCTA, the operator also checked patient's age, breathing control, emotional status and past medical history to decide whether the automatically selected scan phase needs manual adjustment or not. Images were reconstructed in 1% steps of the R-R interval to determine the cardiac phase with least coronary motion. If CCTA images showed moderate motion blurring or discontinuity in the course of coronary segments, a cardiac motion correction algorithm was applied to the reconstructed images. Subjective diagnostic image quality was evaluated with 4-point grading scale. RESULTS: A total of 87 consecutive CCTA examinations were investigated in this study. Diastolic reconstruction was applied to all vessel segments in patients with HR <63 bpm, where 36.5 and 77.8% of vessel segments were reconstructed with the use of motion correction in HR ≤57 and 58-62 bpm, respectively. As for patients with HR ≥63 bpm, 89.3 and 71.7% of vessel segments were reconstructed in diastole in HR 63-67 and ≥68 bpm, respectively, while 81 and 100% of vessel segments were reconstructed with the use of motion correction in the same HR groups. CONCLUSION: Based on our results, a HR less than 67 bpm can be used to identify appropriate patients for diastolic reconstruction. Although the motion correction algorithm is an effective approach to reduce the impact of cardiac motion in CCTA, HR control is still important to optimize the image quality of CCTA. The relationship between HR and optimal reconstruction phase established in this study could be further used to tailor the ECG pulsing window for dose reduction in patients undergoing CCTA performed on the 256-slice MDCT. ADVANCES IN KNOWLEDGE: The HR thresholds to identify patients who are the best suitable candidates for diastolic or systolic reconstruction are scanner specific. This study investigated the relationship between HR and optimal reconstruction phase in prospectively ECG-triggered CCTA for a newly introduced 256-slice MDCT. Once the relationship is established, it could be used to tailor the ECG pulsing window for radiation dose reduction.

Optimizing the target detectability of cone beam CT performed in image-guided radiation therapy for patients of different body sizes.

PURPOSE: The target detectability of cone beam computed tomography (CBCT) performed in image-guided radiation therapy (IGRT) was investigated to achieve sufficient image quality for patient positioning over a course of treatment session while maintaining radiation exposure from CBCT imaging as low as reasonably achievable (ALARA). METHODS: Body CBCT scans operated in half-fan mode were acquired with three different protocols: CBCTlowD , CBCTmidD , and CBCThighD , which resulted in weighted CT dose index (CTDIw ) of 0.36, 1.43, and 2.78 cGy, respectively. An electron density phantom that is 18 cm in diameter was covered by four layers of 2.5-cm-thick bolus to simulate patients of different body sizes. Multivariate analysis was used to examine the impact of body size, radiation exposure, and tissue type on the target detectability of CBCT imaging, quantified as contrast-to-noise ratio (CNR). RESULTS: CBCTmidD allows sufficient target detection of adipose, breast, muscle, liver in a background of water for normal-weight adults with cross-sectional diameter less than 28 cm, while CBCThighD is suitable for adult patients with larger body sizes or body mass index over 25 kg/m2 . Once the cross-sectional diameter of adult patients is larger than 35 cm, the CTDIw of CBCT scans should be higher than 2.78 cGy to achieve required CNR. As for pediatric and adolescent patients with cross-sectional diameter less than 25 cm, CBCTlowD is able to produce images with sufficient target detection. CONCLUSION: The target detectability of soft tissues in default CBCT scans may not be sufficient for overweight or obese adults. Contrary, pediatric and adolescent patients would receive unnecessarily high radiation exposure from default CBCT scans. Therefore, the selection of acquisition parameters for CBCT scans optimized according to patient body size was proposed to ensure sufficient image quality for daily patient positioning in radiation therapy while achieving the ALARA principle.

Low-dose computed tomography scans with automatic exposure control for patients of different ages undergoing cardiac PET/CT and SPECT/CT.

PURPOSE: This study aimed to evaluate the efficacy of automatic exposure control (AEC) in order to optimize low-dose computed tomography (CT) protocols for patients of different ages undergoing cardiac PET/CT and single-photon emission computed tomography/computed tomography (SPECT/CT). METHODS: One PET/CT and one SPECT/CT were used to acquire CT images for four anthropomorphic phantoms representative of 1-year-old, 5-year-old and 10-year-old children and an adult. For the hybrid systems investigated in this study, the radiation dose and image quality of cardiac CT scans performed with AEC activated depend mainly on the selection of a predefined image quality index. Multiple linear regression methods were used to analyse image data from anthropomorphic phantom studies to investigate the effects of body size and predefined image quality index on CT radiation dose in cardiac PET/CT and SPECT/CT scans. RESULTS: The regression relationships have a coefficient of determination larger than 0.9, indicating a good fit to the data. According to the regression models, low-dose protocols using the AEC technique were optimized for patients of different ages. In comparison with the standard protocol with AEC activated for adult cardiac examinations used in our clinical routine practice, the optimized paediatric protocols in PET/CT allow 32.2, 63.7 and 79.2% CT dose reductions for anthropomorphic phantoms simulating 10-year-old, 5-year-old and 1-year-old children, respectively. The corresponding results for cardiac SPECT/CT are 8.4, 51.5 and 72.7%. CONCLUSION: AEC is a practical way to reduce CT radiation dose in cardiac PET/CT and SPECT/CT, but the AEC settings should be determined properly for optimal effect. Our results show that AEC does not eliminate the need for paediatric protocols and CT examinations using the AEC technique should be optimized for paediatric patients to reduce the radiation dose as low as reasonably achievable.

Improving Image Quality of On-Board Cone-Beam CT in Radiation Therapy Using Image Information Provided by Planning Multi-Detector CT: A Phantom Study.

PURPOSE: The aim of this study was to improve the image quality of cone-beam computed tomography (CBCT) mounted on the gantry of a linear accelerator used in radiation therapy based on the image information provided by planning multi-detector CT (MDCT). METHODS: MDCT-based shading correction for CBCT and virtual monochromatic CT (VMCT) synthesized using the dual-energy method were performed. In VMCT, the high-energy data were obtained from CBCT, while the low-energy data were obtained from MDCT. An electron density phantom was used to investigate the efficacy of shading correction and VMCT on improving the target detectability, Hounsfield unit (HU) accuracy and variation, which were quantified by calculating the contrast-to-noise ratio (CNR), the percent difference (%Diff) and the standard deviation of the CT numbers for tissue equivalent background material, respectively. Treatment plan studies for a chest phantom were conducted to investigate the effects of image quality improvement on dose planning. RESULTS: For the electron density phantom, the mean value of CNR was 17.84, 26.78 and 34.31 in CBCT, shading-corrected CBCT and VMCT, respectively. The mean value of %Diff was 152.67%, 11.93% and 7.66% in CBCT, shading-corrected CBCT and VMCT, respectively. The standard deviation within a uniform background of CBCT, shading-corrected CBCT and VMCT was 85, 23 and 15 HU, respectively. With regards to the chest phantom, the monitor unit (MU) difference between the treatment plan calculated using MDCT and those based on CBCT, shading corrected CBCT and VMCT was 6.32%, 1.05% and 0.94%, respectively. CONCLUSIONS: Enhancement of image quality in on-board CBCT can contribute to daily patient setup and adaptive dose delivery, thus enabling higher confidence in patient treatment accuracy in radiation therapy. Based on our results, VMCT has the highest image quality, followed by the shading corrected CBCT and the original CBCT. The research results presented in this study should be able to provide a route to reach a high level of image quality for CBCT imaging in radiation oncology.

Characterization of Scattered X-Ray Photons in Dental Cone-Beam Computed Tomography.

PURPOSE: Scatter is a very important artifact causing factor in dental cone-beam CT (CBCT), which has a major influence on the detectability of details within images. This work aimed to improve the image quality of dental CBCT through scatter correction. METHODS: Scatter was estimated in the projection domain from the low frequency component of the difference between the raw CBCT projection and the projection obtained by extrapolating the model fitted to the raw projections acquired with 2 different sizes of axial field-of-view (FOV). The function for curve fitting was optimized by using Monte Carlo simulation. To validate the proposed method, an anthropomorphic phantom and a water-filled cylindrical phantom with rod inserts simulating different tissue materials were scanned using 120 kVp, 5 mA and 9-second scanning time covering an axial FOV of 4 cm and 13 cm. The detectability of the CT image was evaluated by calculating the contrast-to-noise ratio (CNR). RESULTS: Beam hardening and cupping artifacts were observed in CBCT images without scatter correction, especially in those acquired with 13 cm FOV. These artifacts were reduced in CBCT images corrected by the proposed method, demonstrating its efficacy on scatter correction. After scatter correction, the image quality of CBCT was improved in terms of target detectability which was quantified as the CNR for rod inserts in the cylindrical phantom. CONCLUSIONS: Hopefully the calculations performed in this work can provide a route to reach a high level of diagnostic image quality for CBCT imaging used in oral and maxillofacial structures whilst ensuring patient dose as low as reasonably achievable, which may ultimately make CBCT scan a reliable and safe tool in clinical practice.

The feasibility of low-dose CT protocols for coronary artery calcium scoring and PET attenuation correction in cardiac PET/CT.

INTRODUCTION: The purpose of this study was to investigate the feasibility of using low-dose computed tomography (CT) in coronary artery calcium scoring and PET attenuation correction for patients in different weight categories undergoing cardiac PET/CT examinations. MATERIALS AND METHODS: Calcium scoring computed tomography (CSCT) scans and PET scans of anthropomorphic cardiac phantoms simulating normal-weight, mildly obese, and severely obese patients were acquired with a hybrid PET/CT scanner. CSCT images were acquired at 120 kVp, with tube current ranging from 10 to 550 mA. PET scans were performed in three-dimensional mode, with acquisition time of 3 min/bed position. The image quality of cardiac PET/CT was evaluated by assessing the signal-to-noise ratio. CT-based coronary artery calcium quantification was performed using the Agatston scoring system. RESULTS: On the basis of our results, the CSCT protocols using tube currents of 50 and 150 mA should be able to achieve the lowest possible radiation dose while maintaining the desired image quality for normal-weight and mildly obese patients undergoing cardiac PET/CT examinations, respectively. When the proposed low-dose CSCT protocols were performed, radiation dose could be reduced by 83.34 and 50% compared with those from CSCT scans acquired with standard tube current settings for normal-weight and mildly obese patients, respectively. In the scanning of severely obese patients, an increase in tube voltage or current would help improve the reliability of image information provided by cardiac PET/CT. CONCLUSION: Our study demonstrated the feasibility of low-dose CT protocols for coronary artery calcium scoring and PET attenuation correction in cardiac PET/CT to examine patients in different weight categories. The calculations performed in this work should be able to provide practical information to achieve necessary diagnostic information while keeping radiation dose as low as reasonably achievable.

Evaluation of radiation dose and image quality of CT scan for whole-body pediatric PET/CT: a phantom study.

PURPOSE: This study aimed to tailor the CT imaging protocols for pediatric patients undergoing whole-body PET/CT examinations with appropriate attention to radiation exposure while maintaining adequate image quality for anatomic delineation of PET findings and attenuation correction of PET emission data. METHODS: The measurements were made by using three anthropomorphic phantoms representative of 1-, 5-, and 10-year-old children with tube voltages of 80, 100, and 120 kVp, tube currents of 10, 40, 80, and 120 mA, and exposure time of 0.5 s at 1.75:1 pitch. Radiation dose estimates were derived from the dose-length product and were used to calculate risk estimates for radiation-induced cancer. The influence of image noise on image contrast and attenuation map for CT scans were evaluated based on Pearson's correlation coefficient and covariance, respectively. Multiple linear regression methods were used to investigate the effects of patient age, tube voltage, and tube current on radiation-induced cancer risk and image noise for CT scans. RESULTS: The effective dose obtained using three anthropomorphic phantoms and 12 combinations of kVp and mA ranged from 0.09 to 4.08 mSv. Based on our results, CT scans acquired with 80 kVp/60 mA, 80 kVp/80 mA, and 100 kVp/60 mA could be performed on 1-, 5-, and 10-year-old children, respectively, to minimize cancer risk due to CT scans while maintaining the accuracy of attenuation map and CT image contrast. The effective doses of the proposed protocols for 1-, 5- and 10-year-old children were 0.65, 0.86, and 1.065 mSv, respectively. CONCLUSIONS: Low-dose pediatric CT protocols were proposed to balance the tradeoff between radiation-induced cancer risk and image quality for patients ranging in age from 1 to 10 years old undergoing whole-body PET/CT examinations.

Infant cardiac CT angiography with 64-slice and 256-slice CT: comparison of radiation dose and image quality using a pediatric phantom.

BACKGROUND: The aims of this study were to investigate the image quality and radiation exposure of pediatric protocols for cardiac CT angiography (CTA) in infants under one year of age. METHODOLOGY/PRINCIPAL FINDINGS: Cardiac CTA examinations were performed using an anthropomorphic phantom representing a 1-year-old child scanned with non-electrocardiogram-gated (NG), retrospectively electrocardiogram-gated helical (RGH) and prospectively electrocardiogram-gated axial (PGA) techniques in 64-slice and 256-slice CT scanners. The thermoluminescent dosimeters (TLD) were used for direct organ dose measurement, while dose-length product and effective mAs were also used to estimate the patient dose. For image quality, noise and signal-to-noise-ratio (SNR) were assessed based on regions-of-interest drawn on the reconstructed CT images, and were compared with the proposed cardiac image quantum index (CIQI). Estimated dose results were in accordant to the measured doses. The NG scan showed the best image quality in terms of noise and SNR. The PGA scan had better image quality than the RGH scan with 83.70% dose reduction. Noise and SNR were also corresponded to the proposed CIQI. CONCLUSIONS/SIGNIFICANCE: The PGA scan protocol was a good choice in balancing radiation exposure and image quality for infant cardiac CTA. We also suggested that the effective mAs and the CIQI were suitable in assessing the tradeoffs between radiation dose and image quality for cardiac CTA in infants. These results are useful for future implementation of dose reduction strategies in pediatric cardiac CTA protocols.

Prospectively versus retrospectively ECG-gated 256-slice CT angiography to assess coronary artery bypass grafts--comparison of image quality and radiation dose.

OBJECTIVE: In this retrospective non-randomized cohort study, the image quality and radiation dose were compared between prospectively electrocardiogram (ECG)-gated axial (PGA) and retrospectively ECG-gated helical (RGH) techniques for the assessment of coronary artery bypass grafts using 256-slice CT. METHODS: We studied 124 grafts with 577 segments in 64 patients with a heart rate (HR) <85 bpm who underwent CT coronary angiography (CTCA); 34 patients with RGH-CTCA and 30 patients with PGA-CTCA. The image quality of the bypass grafts was assessed by a 5-point scale (1 = excellent to 5 = non-diagnostic) for each segment (proximal anastomosis, proximal, middle, distal course of graft body, and distal anastomosis). Other objective image quality indices such as noise, signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR) were assessed. Radiation doses were also compared. RESULTS: Patient characteristics of the two groups were well matched except HR. The HR of the PGA group was lower than that of the RGH group (62.0 ± 5.0 vs. 65.7 ± 7.4). For both groups, over 90% of segments received excellent or good image quality scores and none was non-evaluative. The image quality generally degraded as graft segment approached to distal anastomosis regardless of techniques and graft types. Image quality scores of the PGA group were better than those of the RGH group (1.51 ± 0.53 vs. 1.73 ± 0.62; p<0.001). There was no significantly difference of objective image quality between two techniques, and the effective radiation dose was significantly lower in the PGA group (7.0 ± 1.2 mSv) than that of the RGH group (20.0 ± 4.6 mSv) (p<0.001), with a 65.0% dose reduction. CONCLUSIONS: Following bypass surgery, 256-slice PGA-CTCA is superior to RGH-CTCA in limiting the radiation dose and obtaining better image quality for bypass grafts.