Tube Voltage Research Articles

Reduced inflammation assessed by pericoronary adipose tissue is associated with coronary plaque calcification

Abstract Introduction Pericoronary adipose tissue attenuation (PCAT) quantified from coronary computed tomography angiography (CCTA) is increasingly recognized as an inflammation marker in coronary artery disease (CAD). Inflamed PCAT has been linked to non-calcified plaque (NCP) and cardiovascular morbidity and mortality. Nevertheless, gaps remain in understanding how PCAT behaves during plaque stabilization. Purpose We investigated associations between coronary artery inflammation assessed by PCAT and the presence and type of coronary plaques, plaque burden, and coronary calcification. Methods An observational study involving 506 patients with suspected chronic coronary syndrome who underwent CCTA. PCAT was averaged across the proximal 40 mm segments of all three coronary vessels to represent the patient level. Plaque presence and types (calcified, mixed, and soft) were assessed. Total, NCP, and calcified plaque (CP) burdens were measured as normalized atheroma volumes. Coronary calcification was quantified using Agatson coronary artery calcification (CAC) score and categorized based on cut-offs of 0, 100, 400. Results The mean PCAT was -81.1 ±6.3 Hounsfield Unit (HU) without plaque and -79.7 ±6.0 HU with plaque (p= 0.01). PCAT differed between calcified (-81.8 HU), mixed (-79.8 HU), and soft (-77.0 HU) plaques (p<0.0001). Multivariate linear analysis (adjusted for clinical risk factors, cardiovascular medication, and tube voltage) showed PCAT positively associated with total plaque burden (estimate= 1.1 [95% CI: 0.3-1.8], p=0.004) and NCP burden (estimate= 2.4 [95% CI: 1.4-3.4]; p<0.0001), while the association with CP burden was negative, but not statistically significant (estimate= -1.7 [95%CI : -4.1-0.7], p=0.2). Multivariate linear analysis, which accounted for both calcified and non-calcified plaque, reaffirmed the positive association to NCP burden (estimate= 2.7 [95% CI: 1.7-3.7]; p<0.0001) and a significant negative association between CP burden (estimate= - 3.3 [95% CI: -5.8- -1.0]; p=0.007) and PCAT. No significant differences in PCAT levels were found among patients with a CAC score of 0 and those with CAC scores exceeding 400, or across different stages of CAC score categories (p>0.8). Conclusion PCAT increased with plaque presence, rising from calcified to mixed to soft plaques. Increased NCP burden associated with higher PCAT, while higher CP burden seemed to reduce PCAT, though not statistical significant. Interestingly, when NCP was absent, higher levels of CP burden were associated with reduced inflammation. This supports the hypothesis of plaque stabilization, proposing that calcification might stabilize the vessel and indirectly contribute to reducing inflammation.Figure 1 PCAT by plaque typesTable 1 PCAT & plaque burden

The Effect of Tube Voltage Variations on CT Scan Image Quality at Prof. I G. N. G. Ngoerah General Hospital, Denpasar, Indonesia

Aims: Knowing the SNR and CNR values obtained from the image results that have been varied in the tube voltage. Knowing the effect of variations in the tube voltage value on the quality of the CT scan image that will be produced. Place and Duration of Study: Radiology installation of Prof. I G. N. G. Ngoerah General Hospital, Denpasar from May 2024 to August 2024. Methodology: This study used a Canon Aquilion LB CT Scanner to scan a TOS phantom containing 6 materials (polypropylene, nylon, acrylic, derlin, air, and water) with varying tube voltages (80 kV, 100 kV, 120 kV, 135 kV). The data were analyzed using PSPP and Excel to calculate SNR and CNR, and statistical tests for normality, Pearson correlation, and simple regression were performed. Results: The image data analyzed includes the average value of the object ROI, the average ROI background, and the standard deviation of the background. The data is grouped based on the variation of the tube voltage, the average value and standard deviation of the ROI on each material, and the standard deviation of the background. The results obtained for the relationship between the variation of the tube voltage and the SNR value are that the tube voltage affects the SNR value by 94,02% in polypropylene, 97,79% in nylon, 97,71% in acrylic, 96,42% in derlin, and 94,22% in air. And for the relationship between the tube voltage and the CNR value, the tube voltage affects the CNR value by 93,65% in polypropylene, 97,35% in nylon, 96,81% in acrylic, 95,62% in derlin, and 94,65% in air. Conclusion: Selecting the right tube voltage is important to optimize CT scan image quality, with 120 kV and 135 kV recommended for organs such as the kidney, liver, and lungs as they produce better SNR and CNR. Organs with significant attenuation differences show increased SNR and CNR, while soft tissues such as fat experience decreased contrast at high voltages. The use of tube voltage must be adjusted to diagnostic needs and evaluated through quality control according to BAPETEN regulation Number 2 of 2018.

Tube voltage in chest and abdomen DR imaging: Which settings return maximal non-prewhitening model observer with eye filter (NPWE) detectability?

The non-prewhitening computational model observer with eye filter (NPWE) has been shown to reasonably predict human observer performance in general radiography and is an appropriate substitute when real clinical trials are not feasible. In this study, the NPWE model observer is used to detect specific tasks (circular designer nodules) ranging between 1 and 30mm in diameter using chest and abdomen phantom images acquired across the diagnostic energy range (60-125 kVp) with and without an anti-scatter grid. The aim of this study was to derive tube voltage (kVp) settings that return maximal NPWE detectability (d') of designer nodules, for digital radiography (DR) chest and abdomen imaging. Images of a chest phantom (LucAl phantom) and a surrogate for an abdomen (18.5cm PMMA) were acquired across the diagnostic energy range (60-125 kVp) with matched effective dose (for the respective anatomies), with and without an anti-scatter grid, on a general x-ray system. Images were captured using an Agfa DX-D 40C wireless indirect caesium iodide (CsI) imaging panel. Modulation transfer function (MTF), normalized noise power spectrum (NNPS), and contrast (C) were measured in each image and the detectability index d' was calculated for circular designer nodules with diameters ranging from 1 to 30mm (in steps of 1mm). The calculated d' peaked at a nodule diameter of 3mm irrespective of tube voltage, for both chest and abdomen images. A tube voltage of 80kVp returned maximal d' for chest imaging across all nodule diameters both with and without an anti-scatter grid. A tube voltage of 70 kVp returned maximal d' for abdomen imaging. The NPWE observer model has been used to derive tube voltages (kVp) that return maximal detectability (d') of designer nodules for chest and abdomen radiography using a modern DR imaging system. This will provide the medical physicist with a starting point in the task of optimising tube voltage range for chest and abdomen imaging.

Deep learning architecture for scatter estimation in cone-beam computed tomography head imaging with varying field-of-measurement settings.

X-ray scatter causes considerable degradation in the cone-beam computed tomography (CBCT) image quality. To estimate the scatter, deep learning-based methods have been demonstrated to be effective. Modern CBCT systems can scan a wide range of field-of-measurement (FOM) sizes. Variations in the size of FOM can cause a major shift in the scatter-to-primary ratio in CBCT. However, the scatter estimation performance of deep learning networks has not been extensively evaluated under varying FOMs. Therefore, we train the state-of-the-art scatter estimation neural networks for varying FOMs and develop a method to utilize FOM size information to improve performance. We used FOM size information as additional features by converting it into two channels and then concatenating it to the encoder of the networks. We compared our approach for a U-Net, Spline-Net, and DSE-Net, by training them with and without the FOM information. We utilized a Monte Carlo-simulated dataset to train the networks on 18 FOM sizes and test on 30 unseen FOM sizes. In addition, we evaluated the models on the water phantoms and real clinical CBCT scans. The simulation study demonstrates that our method reduced average mean-absolute-percentage-error for U-Net by 38%, Spline-Net by 40%, and DSE-net by 33% for the scatter estimation in the 2D projection domain. Furthermore, the root-mean-square error on the 3D reconstructed volumes was improved for U-Net by 43%, Spline-Net by 30%, and DSE-Net by 23%. Furthermore, our method improved contrast and image quality on real datasets such as water phantom and clinical data. Providing additional information about FOM size improves the robustness of the neural networks for scatter estimation. Our approach is not limited to utilizing only FOM size information; more variables such as tube voltage, scanning geometry, and patient size can be added to improve the robustness of a single network.

Quantitative CT imaging and radiation-absorbed dose estimations of 166Ho microspheres: paving the way for clinical application

BackgroundMicrobrachytherapy enables high local tumor doses sparing surrounding tissues by intratumoral injection of radioactive holmium-166 microspheres (166Ho-MS). Magnetic resonance imaging (MRI) cannot properly detect high local Ho-MS concentrations and single-photon emission computed tomography has insufficient resolution. Computed tomography (CT) is quicker and cheaper with high resolution and previously enabled Ho quantification. We aimed to optimize Ho quantification on CT and to implement corresponding dosimetry.MethodsTwo scanners were calibrated for Ho detection using phantoms and multiple settings. Quantification was evaluated in five phantoms and seven canine patients using subtraction and thresholding including influences of the target tissue, injected amounts, acquisition parameters, and quantification volumes. Radiation-absorbed dose estimation was implemented using a three-dimensional 166Ho specific dose point kernel generated with Monte Carlo simulations.ResultsCT calibration showed a near-perfect linear relation between radiodensity (HU) and Ho concentrations for all conditions, with differences between scanners. Ho detection during calibration was higher using lower tube voltages, soft-tissue kernels, and without a scanner detection limit. The most accurate Ho recovery in phantoms was 102 ± 11% using a threshold of mean tissue HU + (2 × standard deviation) and in patients 98 ± 31% using a 100 HU threshold. Thresholding allowed better recovery with less variation and dependency on the volume of interest compared to the subtraction of a single HU reference value. Corresponding doses and histograms were successfully generated.ConclusionCT quantification and dosimetry of 166Ho should be considered for further clinical application with on-site validation using radioactive measurements and intra-operative Ho-MS and dose visualizations.Relevance statementImage-guided holmium-166 microbrachytherapy currently lacks reliable quantification and dosimetry on CT to ensure treatment safety and efficacy, while it is the only imaging modality capable of quantifying high in vivo holmium concentrations.Key PointsLocal injection of 166Ho-MS enables high local tumor doses while sparing surrounding tissue.CT enables imaging-based quantification and radiation-absorbed dose estimation of concentrated Ho in vivo, essential for treatment safety and efficacy.Two different CT scanners and multiple acquisition and reconstruction parameters showed near-perfect linearity between radiodensity and Ho concentration.The most accurate Ho recoveries on CT were 102 ± 11% in five phantoms and 98 ± 31% in seven canine patients using thresholding methods.Dose estimations and volume histograms were successfully implemented for clinical application using a dose point kernel based on Monte Carlo simulations.Graphical

Radiation shielding transmission data for modern digital radiography.

Radiography is one of the most widely used x-ray imaging modalities. In National Council on Radiation Protection and Measurements (NCRP) Report No. 147, transmission data for radiographic systems were evaluated on those installed before 2000. For x-ray systems (except intraoral dental) manufactured on or after June 10, 2006, the U.S. required minimum half-value layer (HVL) was increased; for example, 2.9 (2.3) mm Al at 80kV, where the value in parenthesis denotes the earlier requirement before the above date. To calculate the transmission of the broad x-ray beam of modern digital radiography (DR) through shielding materials. X-ray beam HVLs on two DR systems (Agfa DR 600, GE Revolution XR/d) were measured in 10kV increments between 60 and 120kV, with a calibrated ionization chamber (Radcal model 10×5-60) and varying thickness of aluminum 1100 plates. Monte Carlo (Geant4) simulation was performed to calculate the transmission of broad x-ray beams through lead, concrete, gypsum, and steel, with x-ray HVLs matching those of the DR 600 at two beam filtrations (default, 1mm Al plus 0.1mm Cu added filtration). The transmission data were fitted to the Archer equation. HVLs on two DR systems with default beam filtration were consistent (median difference, 2.1%; maximum difference, 5.5%). An additional beam filtration option (1mm Al plus 0.1mm Cu) on the DR 600 substantially increased HVLs by 45.2%-61.2%. Transmission fitting parameters were provided for seven tube voltages (60-120kV) at two beam filtrations. This work presents transmission data for modern DR systems, indicating increased x-ray beam filtration compared to the primary x-ray beam in NCRP Report No. 147. The updated transmission data can enhance structural shielding evaluations at individual tube voltages or with a workload distribution.

Performance of iodine quantification through high-pitch dual-source photon-counting CT: a phantom study.

To investigate the feasibility and accuracy of iodine quantification using PCD-CT in standard-pitch and high-pitch scanning at different scan parameters in a phantom model. Four inserts with known iodine concentrations (2, 5, 10, and 15mg/mL) were placed in the removable CT phantom and scanned using high-pitch (3.2) and standard-pitch (0.8) modes on PCD-CT. Two tube voltages (120 and 140 kVp) and four radiation doses (1, 3, 5, and 10mGy) were alternated. Each scan setting was repeated three times. Mean iodine concentration for each insert across three consecutive slices was recorded. Percentage absolute bias (PAB) was assessed for iodine quantification. A total of 96 acquisitions were conducted. In small phantom, the average for PAB was 2.96% (range: 1.75% ~ 4.56%) and 1.67% (range: 1.00% ~ 3.42%) for high-pitch and standard-pitch acquisitions, respectively. In large phantom, it was 3.72% (range: 1.75% ~ 5.97%) and 2.94% (range: 1.75% ~ 4.70%). Linear regression analysis revealed that only phantom size significantly influenced (P < 0.001) the accuracy of iodine quantification. The high-pitch scan mode in PCD-CT can be used to quantify iodine density with similar accuracy compared with standard pitch.

206 - Realizing sub-mSv in radiation dose and 25mL in contrast dose in coronary CT angiography in normal size patients using 70kVp tube voltage and deep learning image reconstruction

206 - Realizing sub-mSv in radiation dose and 25mL in contrast dose in coronary CT angiography in normal size patients using 70kVp tube voltage and deep learning image reconstruction

154 - Reducing radiation doses and improving image quality in myocardial delayed enhancement CT with low tube voltage and deep learning image reconstruction

154 - Reducing radiation doses and improving image quality in myocardial delayed enhancement CT with low tube voltage and deep learning image reconstruction

86 - Study of appropriate tube voltage for chest temporal subtraction (T-sub) image

86 - Study of appropriate tube voltage for chest temporal subtraction (T-sub) image

Contrast and quantum noise in single-exposure dual-energy thoracic imaging with photon-counting x-ray detectors

Objective.Photon-counting x-ray detectors (PCDs) can produce dual-energy (DE) x-ray images of lung cancer in a single x-ray exposure. It is important to understand the factors that affect contrast, noise and the contrast-to-noise ratio (CNR). This study quantifies the dependence of CNR on tube voltage, energy threshold and patient thickness in single exposure, DE, bone-suppressed thoracic imaging with PCDs, and elucidates how the fundamental processes inherent in x-ray detection by PCDs contribute to CNR degradation.Approach.We modeled the DE CNR for five theoretical PCDs, ranging from an ideal PCD that detects every primary photon in the correct energy bin while rejecting all scattered radiation to a non-ideal PCD that suffers from charge-sharing and electronic noise, and detects scatter. CNR was computed as a function of tube voltage and high energy threshold for average and larger-than-average patients. Model predictions were compared with experimental data extracted from images acquired using a cadmium telluride (CdTe) PCD with two energy bins and analog charge summing for charge-sharing suppression. The imaging phantom simulated attenuation, scatter and contrast in lung nodule imaging. We quantified CNR improvements achievable with anti-correlated noise reduction (ACNR) and measured the range of exposure rates over which pulse pile-up is negligible.Main Results.The realistic model predicted overall trends observed in the experimental data. CNR improvements with ACNR were approximately five-fold, and modeled CNR-enhancements were on average within 10% of experiment. CNR increased modestly (i.e.<20%) when increasing the tube voltage from 90 kV to 130 kV. Optimal energy thresholds ranged from 50 keV to 70 keV across all tube voltages and patient thicknesses with and without ACNR. Quantum efficiency, electronic noise, charge sharing and scatter degraded CNR by ~50%. Charge sharing and scatter had the largest effect on CNR, degrading it by ~30% and ~15% respectively. Dead-time losses were less than 5% for patient exposure rates within the range of clinical exposure rates.Significance.In this study, we (1) employed analytical and computational models to assess the impact of different factors on CNR in single-exposure DE imaging with PCDs, (2) evaluated the accuracy of these models in predicting experimental trends, (3) quantified improvements in CNR achievable through ACNR and (4) determined the range of patient exposure rates at which pulse pile-up can be considered negligible. To the best of our knowledge, this study represents the first systematic investigation of single-exposure DE imaging of lung nodules with PCDs.

Application value of individualized tube voltage, contrast injection, and adaptive statistical iterative reconstruction V algorithm based on body mass index in renal computed tomography angiography for radiation and iodinated contrast dose reduction.

To explore the application value of body mass index (BMI)-based kilovoltage peak (kVp) selection and contrast injection protocol combined with different adaptive statistical iterative reconstruction V (ASIR-V) strengths in renal computed tomography angiography (CTA) in reducing radiation and contrast medium (CM) doses. One-hundred renal CTA patients were prospectively enrolled and were divided into individualized kVp group (group A, n = 50) and conventional 100kVp group (group B, n = 50), both with automatic tube current modulation and CM of Iohexol at 350mgI/mL concentration. Group A: 70kVp, noise index (NI) of 18 and CM dose rate of 17mgI/kg/s for 10 s for BMI <25kg/m2 patients; 80kVp, NI = 17, and CM dose rate of 19mgI/kg/s for 10 s for 25 kg/m2≤BMI≤30kg/m2 patients. Group B: 100kVp, 50 mL of CM at the flow rate of 4.5 mL/s. The objective image quality, effective radiation dose, CM dose, injection rate, and image quality were compared between the 2 groups. There was no significant difference in patient characteristics between the 2 groups (P > .05). Compared to group B, group A significantly reduced effective radiation dose by 28.4%, CM dose by 27.2%, and injection rate by 22.7% (all P < .001). The 2 groups had similar SD values in erector spine (P > .05). Group A had significantly higher CT values, SNR, and CNR values of the renal arteries than group B (all P < .001). The 2 radiologists had excellent agreement (Kappa value > 0.8) in the subjective scores of renal CTA images and showed no statistically significant difference between the 2 groups (4.57 ± 0.42 vs 4.41 ± 0.49) (P > .05). BMI-based scan and reconstruction protocol in renal CTA significantly reduces radiation and contrast doses while maintaining diagnostic image quality. (i) BMI-based individualized tube voltage selection and contrast injection protocol in renal CTA reduces both radiation and contrast doses over conventional protocol. (ii) The combination of lower kVp and higher weight ASIR-V maybe used to improve image quality in terms of contrast enhancement and image noise under lower radiation and contrast dose conditions. (iii) Renal CTA of normal size (BMI ≤ 30kg/m2) patients acquired at low radiation dosage and low iodine contrast dose through the combination of low tube voltage and ASIR-V algorithm achieves excellent diagnostic image quality with a good inter-rater agreement.

3D printing of realistic body phantoms: Comparison of measured and simulated organ doses on the example of a CT scan on a pregnant woman

AbstractBackgroundMedical examinations or treatment of pregnant women using ionizing radiation are sometimes unavoidable. In such cases, the risk of harm to the embryo and fetus after exposure to ionizing radiation must be carefully estimated. However, no commercially available anthropomorphic body phantoms of pregnant women are available for dose measurements. A promising possibility for the production of body phantoms for patient groups that are not adequately represented by the phantoms of reference persons is 3D printing. However, this approach is still in the evaluation phase.PurposeTo print the abdomen of a woman in the late stage of pregnancy and compare the dose distribution measured using thermoluminescence dosimeters (TLDs) in the printed phantom for two different computed tomography (CT) protocols with the corresponding results of Monte Carlo simulations on voxel models of the pregnant woman.Materials and methodsThe physical phantom was produced through multi‐material extrusion printing using different print materials identified in previous studies to simulate homogeneous soft tissues and the mean compositions of maternal and fetal bones. The 3D printed abdomen was combined with a conventionally produced anthropomorphic female phantom to obtain a whole‐body phantom of a pregnant woman. Dose values resulting from two different CT scans acquired at tube voltages of 80 and 120 kV were measured using TLDs positioned in the physical phantom and cross‐validated with the results of Monte Carlo simulations performed for two different voxel models. The first was a voxelized model of the produced phantom itself and the second a realistic digital model of a pregnant woman. Representative CT values of the materials used in the printed phantom were determined from the acquired CT images.ResultsThe CT values of maternal and fetal tissue structures in the phantom are comparable to CT values of real human tissues. The difference between most organ doses measured in the 3D printed phantom and simulated in the voxel models was below 20% and equivalent within the measurement uncertainties. Only the dose to the fetal head was up to 50% higher and not equivalent for the realistic model and the 80 kV‐protocol. As expected, the agreement was better for the voxelized than for the realistic model. For both models a slight energy dependence was observed, with larger deviations for the 80‐kV protocol especially for organs located in the pelvic region.ConclusionIndividualized physical body phantoms, such as that of a pregnant woman, can be produced using 3D printing. The good agreement between measured and simulated doses to the fetus cross‐validates both dosimetric methods. Therefore, this study demonstrates the suitability of 3D printing phantoms for patients not adequately represented by commercially available body phantoms of reference persons.

Effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction strength level on the detection and characterization of pulmonary nodules in ultra-low-dose chest CT

ObjectiveTo explore the effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction (ASiR-V) strength level on the detection and characterization of pulmonary nodules by an artificial intelligence (AI) software in ultra-low-dose chest CT (ULDCT).Materials and methodsAn anthropomorphic thorax phantom containing 12 spherical simulated nodules (Diameter: 12 mm, 10 mm, 8 mm, 5 mm; CT value: -800HU, -630HU, 100HU) was scanned with three ULDCT protocols: Dose-1 (70kVp:0.11mSv, 100kVp:0.10mSv), Dose-2 (70kVp:0.34mSv, 100kVp:0.32mSv), Dose-3 (70kVp:0.53mSv, 100kVp:0.51mSv). All scanning protocols were repeated five times. CT images were reconstructed using four different strength levels of ASiR-V (0%=FBP, 30%, 50%, 70%ASiR-V) with a slice thickness of 1.25 mm. The characteristics of the physical nodules were used as reference standards. All images were analyzed using a commercially available AI software to identify nodules for calculating nodule detection rate (DR) and to obtain their long diameter and short diameter, which were used to calculate the deformation coefficient (DC) and size measurement deviation percentage (SP) of nodules. DR, DC and SP of different imaging groups were statistically compared.ResultsImage noise decreased with the increase of ASiR-V strength level, and the 70 kV images had lower noise under the same strength level (mean-value 70 kV: 40.14 ± 7.05 (dose 1), 27.55 ± 7.38 (dose 2), 23.88 ± 6.98 (dose 3); 100 kV: 42.36 ± 7.62 (dose 1); 30.78 ± 6.87 (dose 2); 26.49 ± 6.61 (dose 3)). Under the same dose level, there were no differences in DR between 70 kV and 100 kV (dose 1: 58.76% vs. 58.33%; dose 2: 73.33% vs. 70.83%; dose 3: 75.42% vs. 75.42%, all p > 0.05). The DR of GGNs increased significantly at dose 2 and higher (70 kV: 38.12% (dose 1), 60.63% (dose 2), 64.38% (dose 3); 100 kV: 37.50% (dose 1), 59.38% (dose 2), 66.25% (dose 3)). In general, the use of ASiR-V at higher strength levels (> 50%) and 100 kV provided better (lower) DC and SP.ConclusionDetection rates are similar between 70 kV and 100 kV scans. The 70 kV images have better noise performance under the same ASiR-V level, while images of 100 kV and higher ASiR-V levels are better in preserving the nodule morphology (lower DC and SP); the dose levels above 0.33mSv provide high sensitivity for nodules detection, especially the simulated ground glass nodules.

Radiation protection in dental imaging: Evaluating the impact of the SABA thyroid shield during panoramic and cone beam computed tomography

BackgroundDental panoramic radiography (DPR) and cone beam computed tomography (CBCT) are an imaging modalities in dentistry. However, these procedures involve exposure to ionising radiation, raising concerns about radiation-induced thyroid damage. To mitigate these risks, thyroid shields have been introduced. This study aimed to evaluate the effectiveness of the SABA thyroid shield in reducing thyroid radiation exposure during DPR and CBCT scans. MethodAn experimental study to measure surface dose in the thyroid region during (DPR) and (CBCT) scans using an Anthropomorphic Phantom and a Solid-State Detector. The attenuation percentage was calculated between radiation surface doses with and without shielding. The significance of the Saba thyroid shield was calculated using a t-test. ResultsFor DPR scans, the average surface doses in the thyroid reduced significantly from 301.1 μGy (at 85 kVp) and 170.3 μGy (at 60 kVp) to 64.43 μGy and 12.94 μGy, respectively, when the Saba thyroid shield was used. For CBCT scans, the average surface doses in the thyroid decreased significantly from 814.43 μGy (for 11 × 13 cm2 field size) and 32.40 μGy (for 5 × 5 cm2 field size) to 62.91 μGy and 12.07 μGy, respectively, with the application of the Saba thyroid shield. The maximum attenuation percentages in the thyroid for the DPR and CBCT scans were 92.40% and 92.27%, respectively. Statistically significant differences between the surface dose reduction with the Saba shield and without it was observed in both DPR scans (p < 0.0000) and CBCT scans (p < 0.0003). ConclusionThe study demonstrates that Saba thyroid shields effectively reduce doses in the thyroid region during dental DPR and CBCT scans. The dose reduction depends on tube voltage for DPR scans, field size, and its position for CBCT scans. Findings highlight the importance of using Saba thyroid shields to minimise radiation exposure and protect the thyroid gland during dental scans.

Visualization of spatial dose distribution for effective radiation protection education in interventional radiology: obtaining high-accuracy spatial doses.

In recent years, eye lens exposure among radiation workers has become a serious concern in medical X-ray fluoroscopy and interventional radiology (IVR), highlighting the need for radiation protection education and training. This study presents a method that can maintain high accuracy when calculating spatial dose distributions obtained via Monte Carlo simulation and establishes another method to three-dimensionally visualize radiation using the obtained calculation results for contributing to effective radiation-protection education in X-ray fluoroscopy and IVR. The Monte Carlo particle and heavy ion transport code system (PHITS, Ver. 3.24) was used for calculating the spatial dose distribution generated by an angiography device. We determined the peak X-ray tube voltage and half value layer using Raysafe X2 to define the X-ray spectrum from the source and calculated the X-ray spectrum from the measured results using an approximation formula developed by Tucker et al. Further, we performed measurements using the "jungle-gym" method under the same conditions as the Monte Carlo calculations for verifying the accuracy of the latter. An optically stimulated luminescence dosimeter (nanoDot dosimeter) was used as the measuring instrument. In addition, we attempted to visualize radiation using ParaView (version 5.12.0-RC2) using the spatial dose distribution confirmed by the above calculations. A comparison of the measured and Monte Carlo calculated spatial dose distributions revealed that some areas showed large errors (12.3 and 24.2%) between the two values. These errors could be attributed to the scattering and absorption of X-rays caused by the jungle gym method, which led to uncertain measurements, and (2) the angular and energy dependencies of the nanoDot dosimetry. These two causes explain the errors in the actual values, and thus, the Monte Carlo calculations proposed in this study can be considered to have high-quality X-ray spectra and high accuracy. We successfully visualized the three-dimensional spatial dose distribution for direct and scattered X-rays separately using the obtained spatial dose distribution. We established a method to verify the accuracy of Monte Carlo calculations performed through the procedures considered in this study. Various three-dimensional spatial dose distributions were obtained with assured accuracy by applying the Monte Carlo calculation (e.g., changing the irradiation angle and adding a protective plate). Effective radiation-protection education can be realized by combining the present method with highly reliable software to visualize dose distributions.

Development and validation of the surmising model for volumetric breast density using X-ray exposure conditions in digital mammography.

The use of breast density as a biomarker for breast cancer treatment has not been well established owing to the difficulty in measuring time-series changes in breast density. In this study, we developed a surmising model for breast density using prior mammograms through a multiple regression analysis, enabling a time series analysis of breast density. We acquired 1320 mediolateral oblique view mammograms to construct the surmising model using multiple regression analysis. The dependent variable was the breast density of the mammary gland region segmented by certified radiological technologists, and independent variables included the compressed breast thickness (CBT), exposure current times exposure second (mAs), tube voltage (kV), and patients' age. The coefficient of determination of the surmising model was 0.868. After applying the model, the correlation coefficients of the three groups based on the CBT (thin group, 18-36mm; standard group, 38-46mm; and thick group, 48-78mm) were 0.913, 0.945, and 0.867, respectively, suggesting that the thick breast group had a significantly low correlation coefficient (p = 0.00231). In conclusion, breast density can be accurately surmised using the CBT, mAs, tube voltage, and patients' age, even in the absence of a mammogram image.

Optimizing Neuroimaging Techniques for Enhanced Visualization of Intracranial Aneurysms

Intracranial aneurysms, abnormal dilations of blood vessels in the brain, pose significant health risks, especially when ruptured, leading to conditions such as subarachnoid hemorrhage and stroke. The primary objective of this study is to evaluate the diagnostic accuracy of different computed tomography angiography (CTA) protocols for detecting intracranial aneurysms and to identify methods for optimizing scanning parameters to reduce radiation exposure while ensuring high image quality. Results from the analysis of various CTA protocols revealed that lowering tube voltages (80-120 kV) and milliampere seconds (mAs) effectively reduced radiation exposure without compromising the quality of images. Additionally, the use of advanced reconstruction algorithms, including deep learning techniques, significantly improved the visualization of small vascular structures, thereby enhancing diagnostic accuracy. These findings provide valuable insights for enhancing clinical practices in the fields of neurology and radiology.

Gram-Scale Synthesis of Renal-Clearable Tantalum Nanodots with High Water Solubility for Computed Tomography Imaging In Vivo.

Tantalum (Ta) emerges as a promising element for advanced computed tomography (CT) imaging probes owing to its high X-ray attenuation coefficient and excellent biocompatibility. Nevertheless, the synthesis of renally clear Ta-based imaging probes through simple methods remains a significant challenge. Herein, we introduce a simple and gram-scale approach for the synthesis of renal-clearable Ta nanodots with high water solubility for CT imaging in vivo. The Ta nanodots, coordination polymers, are fabricated via coordination reactions involving Ta(OH)5, citric acid (CA), and hydrogen peroxide. The Ta nanodots exhibit an ultrasmall hydrodynamic diameter (2.8 nm), high water solubility (1.88 g/mL, 688 mg Ta/mL), superior X-ray absorption capacity, gram-scale production capability (>10 g in lab synthesis), renal-clearable ability, and good biocompatibility. The Ta nanodots possess superior CT imaging efficacy across diverse tube voltages, enabling highly sensitive gastrointestinal CT imaging, renal CT imaging, and CT angiography (CTA). Moreover, Ta nanodots maintain robust CT imaging capabilities even at high X-ray energies, and Ta nanodots-based spectral CT achieves metallic artifacts-minimized CTA. The proposed Ta nanodots present substantial potential as a potent CT imaging probe for diagnosing various diseases.

Comparative study of image quality and radiation dose in thoracic-abdominal-pelvic CT Enhancement with different tube voltages and reconstruction algorithms

ObjectivesTo evaluate the image quality and radiation dose in thoracic-abdominal-pelvic computed tomography enhancement using ATVM (Automatic Tube Voltage Modulation)coupled with AIIR versus routine tube voltage combined with Karl-3D IR. The optimal noise level for the AIIR in thoracic-abdominal-pelvic CT enhancement was also determined. MethodsGroup A was scanned using ATVM, and images were reconstructed using AIIR with 1–5 noise levels. Group B was scanned and reconstructed using the fixed tube voltage (120 kVp) combined with Karl 3D level 5 IR. The image quality of the reconstructed images of AIIR with 1–5 noise levels were compared and the best image reconstruction noise level for AIIR was preferred. Image quality and radiation dose were statistically analyzed for group A (best image reconstruction noise level for AIIR) and group B. ResultsAIIR level 3 is the optimal noise level for CT-enhanced image reconstruction of the thorax, abdomen, and pelvis. The mean SNR, CNR, and subjective evaluation of AIIR level 3 Group A images were better than those of Karl 3D level 5 Group B images (p < 0.05). The mean SSDE and the mean ED of the AIIR Group A patients were reduced by 46% and 41%, respectively, compared with those of Group B. ConclusionsATVM technology combined with the AIIR algorithm improved image quality and reduced patient radiation dose in thoracic-abdominal-pelvic CT scans. The optimal noise level for the reconstruction of high-quality arterial and venous-phase images was AIIR level 3.