Peak Kilovoltage Research Articles

Significance of Image Reconstruction Parameters for Future Lung Cancer Risk Prediction Using Low-Dose Chest Computed Tomography and the Open-Access Sybil Algorithm.

Sybil is a validated publicly available deep learning-based algorithm that can accurately predict lung cancer risk from a single low-dose computed tomography (LDCT) scan. We aimed to study the effect of image reconstruction parameters and CT scanner manufacturer on Sybil's performance. Using LDCTs of a subset of the National Lung Screening Trial participants, which we previously used for internal validation of the Sybil algorithm (test set), we ran the Sybil algorithm on LDCT series pairs matched on kilovoltage peak, milliampere-seconds, reconstruction interval, reconstruction diameter, and either reconstruction filter or axial slice thickness. We also evaluated the cumulative effect of these parameters by combining the best- and the worst-performing parameters. A subanalysis compared Sybil's performance by CT manufacturer. We considered any LDCT positive if future lung cancer was subsequently confirmed by biopsy or surgical resection. The areas under the curve (AUCs) for each series pair were compared using DeLong's test. There was no difference in Sybil's performance between 1049 pairs of standard versus bone reconstruction filter (AUC at 1 year 0.84 [95% confidence interval (CI): 0.70-0.99] vs 0.86 [95% CI: 0.75-0.98], P = 0.87) and 1961 pairs of standard versus lung reconstruction filter (AUC at 1 year 0.98 [95% CI: 0.97-0.99] vs 0.98 [95% CI: 0.96-0.99], P = 0.81). Similarly, there was no difference in 1288 pairs comparing 2-mm versus 5-mm axial slice thickness (AUC at 1 year 0.98 [95% CI: 0.94-1.00] vs 0.99 [95% CI: 0.97-0.99], P = 0.68). The best-case scenario combining a lung reconstruction filter with 2-mm slice thickness compared with the worst-case scenario combining a bone reconstruction filter with 2.5-mm slice thickness uncovered a significantly different performance at years 2-4 (P = 0.03). Subanalysis showed no significant difference in performance between Siemens and Toshiba scanners. Sybil's predictive performance for future lung cancer risk is robust across different reconstruction filters and axial slice thicknesses, demonstrating its versatility in various imaging settings. Combining favorable reconstruction parameters can significantly enhance predictive ability at years 2-4. The absence of significant differences between Siemens and Toshiba scanners further supports Sybil's versatility.

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.

Patient dose and associated exposure parameters in pelvic x-ray examinations: dependence on radiographic system.

Technological differences between computed radiography (CR) and digital radiography (DR) systems can influence patient doses and exposure parameters in pelvic x-ray examinations. The presence of radiosensitive organs in the pelvic region underscores the need to optimize these parameters for both CR and DR systems. This prospective study aimed to compare the patient doses and exposure parameters for adult patients undergoing pelvic x-ray examinations using CR and DR systems, based on data from Sri Lanka. The study included data from 56 x-ray examinations, with 25 using CR and 31 using DR. Patient demographic characteristics and exposure parameters (kVp: kilovoltage peak, mAs: tube current-exposure time product) were recorded, and patient doses were measured in terms of the kerma-area product (PKA) using a PKA meter. Despite similar mean weight and body mass index (BMI), the CR systems showed significantly higher mean kVp (7.4%), mAs (16.4%), and PKA (29.7%) than the DR systems (CR - kVp: 73.2, mAs: 37.8, PKA: 2.29Gy cm2; DR - kVp: 67.8, mAs: 31.6, PKA: 1.61Gy cm2). The Mann-Whitney U test revealed statistically significant differences in PKA and kVp between the CR and DR systems (p < 0.05). Furthermore, even with lower patient weight and BMI, the mean mAs and PKA in this study were substantially higher than those reported in the literature for both CR and DR systems. These results suggest the need to optimize current mAs settings for the studied hospitals and introduce radiographic system-specific exposure parameters and reference dose levels for pelvic x-ray examinations in order to enhance patient protection.

Relationship between pericoronary adipose tissue attenuation value and image reconstruction parameters

Rationale and objectivesTo investigate the relationship between the pericoronary adipose tissue CT mean attenuation (PCATMA) measurement and image reconstruction parameters (adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel, and slice thickness). Materials and methodsOne hundred and ninety-eight consecutive patients underwent CT coronary angiography at 100 kilovoltage peak (kVp) (n = 102) and 120 kVp (n = 96) were included. All scans were reconstructed by three means: 1. with 11 different ASIR-V percentages, standard kernel and 0.625 mm; 2. with soft, standard, detail, and bone kernels, 60 % ASIR-V, and 0.625 mm; 3. at 0.625 mm and 1.25 mm slice thickness, standard kernel and 60 % ASIR-V. PCATMA of the three main coronary arteries was calculated using a dedicated software. Linear regression, analysis of variance (ANOVA), Friedman test, and paired t-test were used for statistical analysis. ResultsLinear regression of pooled average data showed that the PCATMA was positively and linearly correlated with the ASIR-V percentage (all R squared >0.99). Regression analysis of individual data showed that most R squared were greater than 0.8 or 0.9, but their slope consisted of a relatively wide range. The difference of PCATMA among different kernels for each coronary artery reached statistically significant levels (P < 0.001), particularly for the difference between standard and bone kernel. Most of the differences between 0.625 mm and 1.25 mm for LAD, LCX, and RCA at 100 kVp and 120 kVp reached statistical significance (P < 0.001). ConclusionsPCATMA correlates linearly with the strength of ASIR-V. Reconstruction kernel and slice thickness also affect PCATMA, especially for the sharp kernels.

Reduction of metal artefacts from bilateral hip prostheses during lower extremity computed tomography angiography: an experimental phantom study.

Image quality reduction due to metallic artefacts is a significant challenge during vascular computed tomography (CT) imaging of the lower extremities in patients with hip prostheses. This study aims to analyse various reconstruction algorithms' ability to reduce metal artefacts due to two types of hip prostheses during lower extremity CT angiography examinations. A pelvis phantom was fabricated with the insertion of a tube filled with contrast media to simulate the femoral artery, and the phantom was then CT scanned with and without hip prostheses. Multimodal images were acquired using different kilovoltage peak (kVp) settings and reconstructed with different algorithms, such as filtered back projection (FBP), iterative reconstruction (iDose4), iterative model-based reconstruction (IMR) and orthopaedic metal artefact reduction (O-MAR). Image quality was assessed based on image noise, signal-to-noise ratio (SNR) and Hounsfield unit (HU) deviation. The IMR approach significantly improved image quality compared to iDose4 and FBP. For the vascular region, O-MAR improves SNR by 5 ± 1, 23 ± 5 and 42 ± 9 for FBP, iDose4 and IMR respectively, and improves HU precision towards the baseline values by 49% and 83% for FBP and IMR, respectively. The noise reduction was 71% and 89% for FBP and IMR, and 57% for iDose4. O-MAR greatly enhances SNR corrections among the most severe artefacts, with 29 ± 1 and 43 ± 4 for FBP and IMR, compared to iDose4 by 37 ± 7. IMR combined with O-MAR could improve the CT angiography of the lower extremities of patients with a hip prosthesis.

Performance of calcium quantifications on low-dose photon-counting detector CT with high-pitch: A phantom study

PurposeTo evaluate the performance of calcium quantification on photon-counting detector CT (PCD-CT) with high-pitch at low radiation doses compared to third-generation dual-source energy-integrating detector CT (EID-CT). Materials and methodsThe phantom with three calcium inserts (50, 100, and 300 mg of calcium per milliliter), with and without the elliptical outer layer, was evaluated using high-pitch (3.2) and standard pitch (0.8) on PCD-CT, and standard pitch on EID-CT. Scans were performed with different tube voltages (PCD-CT: 120 and 140 kilo-voltage peak [kVp]; EID-CT: 70/Sn150 and 100/Sn150 kVp) and four radiation doses (1, 3, 5, and, 10 milli-Gray [mGy]). Utilizing the true calcium concentrations (CCtrue) of the phantom as the gold standard references, regression equations for each kVp setting were formulated to convert CT attenuations (CaCT) into measured calcium concentrations (CCm). The correlation analysis between CaCT and CCtrue was performed. The percentage absolute bias (PAB) was calculated from the differences between CCm and CCtrue and used to analyze the effects of scanning parameters on calcium quantification accuracy. ResultsA strong correlation was found between CaCT and CCtrue on PCD-CT (r > 0.99) and EID-CT (r > 0.98). For high- and standard-pitch scans on PCD-CT, the accuracy of calcium quantification is comparable (p = 0.615): the median (interquartile range [IQR]) of PAB was 5.59% (2.79%–8.31%) and 4.87 % (2.62%–8.01%), respectively. The PAB median (IQR) was 7.43% (3.77%–11.75%) for EID-CT. The calcium quantification accuracy of PCD-CT is superior to EID-CT at the large phantom (5.46% [2.68%–9.55%] versus 9.01% [6.22%–12.74%]), and at the radiation dose of 1 mGy (4.43% [2.08%–8.59%] versus 13.89% [8.93%–23.09%]) and 3 mGy (4.61% [2.75%–6.51%] versus 9.97% [5.17%–14.41%]), all p < 0.001. ConclusionsCalcium quantification using low-dose PCD-CT with high-pitch scanning is feasible and accurate, and superior to EID-CT.

Quantitative analysis of blooming artifact caused by calcification based on X-ray energy difference using computed tomography

Blooming artifacts caused by calcifications appearing on computed tomography (CT) images lead to an underestimation of the coronary artery lumen size, and higher X-ray energy levels are suggested to reduce the blooming artifacts with subjective visual assessment. This study aimed to evaluate the effect of higher X-ray energy levels on the quantitative measurement of adjacent pixels affected by calcification using CT images. In this two-part study, CT images were acquired from dual-energy CT scanners by changing the X-ray energy levels such as kilovoltage peak (kVp) and kilo-electron volts (keV). Adjacent pixels affected by calcification were measured using the brightened length, excluding the actual calcified length, as determined by the full width at third maximum. In a separate clinical study, the adjacent affected pixels associated with 23 calcifications across 10 patients were measured using the same method as that used in the phantom study. Phantom and clinical studies showed that the change in kVp (field of view [FOV] 300 mm: p = 0.167, 0.494, and 0.861 for vendors 1, 2, and 3, respectively) and keV levels (p = 0.178 for vendor 2) failed to reduce the adjacent pixels affected by calcification, respectively. Moreover, the change in keV levels showed different aspects of adjacent pixels affected by calcification in the phantom study (FOV 300 mm: no significant difference [p = 0.191], increase [p < 0.001], and decrease [p < 0.001] for vendors 1, 2, and 3, respectively). Quantitative measurements revealed no significant relationship between higher X-ray energy levels and the adjacent pixels affected by calcification.

Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.

Dual-energy computed tomography (CT) can provide a range of image information beyond conventional CT through virtual monoenergetic images (VMIs). The purpose of this study was to investigate the impact of material decomposition in detector-based spectral CT on radiomics features and effectiveness of using deep learning-based image synthesis to improve the reproducibility of radiomics features. In this paper, spectral CT image data from 45 esophageal cancer patients were collected for investigation retrospectively. First, we computed the correlation coefficient of radiomics features between conventional kilovoltage peak (kVp) CT images and VMI. Then, a wavelet loss-enhanced CycleGAN (WLL-CycleGAN) with paired loss terms was developed to synthesize virtual monoenergetic CT images from the corresponding conventional single-energy CT (SECT) images for improving radiomics reproducibility. Finally, the radiomic features in 6 different categories, including gray-level co-occurrence matrix (GLCM), gray-level difference matrix (GLDM), gray-level run-length matrix (GLRLM), gray-level size-zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and wavelet, were extracted from the gross tumor volumes from conventional single energy CT, synthetic virtual monoenergetic CT images, and virtual monoenergetic CT images. Comparison between errors in the VMI and synthetic VMI (sVMI) suggested that the performance of our proposed deep learning method improved the radiomic feature accuracy. Material decomposition of dual-layer dual-energy CT (DECT) can substantially influence the reproducibility of the radiomic features, and the degree of impact is feature dependent. The average reduction of radiomics errors for 15 patients in testing sets was 96.9% for first-order, 12.1% for GLCM, 12.9% for GLDM, 15.7% for GLRLM, 50.3% for GLSZM, 53.4% for NGTDM, and 6% for wavelet features. The work revealed that material decomposition has a significant effect on the radiomic feature values. The deep learning-based method reduced the influence of material decomposition in VMIs and might improve the robustness and reproducibility of radiomic features in esophageal cancer. Quantitative results demonstrated that our proposed wavelet loss-enhanced paired CycleGAN outperforms the original CycleGAN.

Effect of kilovoltage and quality reference mAs on CT-based attenuation correction in 177Lu SPECT/CT imaging: a phantom study

IntroductionCT-based attenuation correction (CT-AC) plays a major role in accurate activity quantification by SPECT/CT imaging. However, the effect of kilovoltage peak (kVp) and quality-reference mAs (QRM) on the attenuation coefficient image (μ-map) and volume CT dose index (CTDIvol) have not yet been systematically evaluated. Therefore, the aim of this study was to fill this gap and investigate the influence of kVp and QRM on CT-AC in 177Lu SPECT/CT imaging.MethodsSeventy low-dose CT acquisitions of an Electron Density Phantom (seventeen inserts of nine tissue-equivalent materials) were acquired using various kVp and QRM combinations on a Siemens Symbia Intevo Bold SPECT/CT system. Using manufacturer reconstruction software, 177Lu μ-maps were generated for each CT image, and three low-dose CT related aspects were examined. First, the μ-map-based attenuation values (μmeasured) were compared with theoretical values (μtheoretical). Second, changes in 177Lu activity expected due to changes in the μ-map were calculated using a modified Chang method. Third, the noise in the μ-map was assessed by measuring the coefficient of variation in a volume of interest in the homogeneous section of the Electron Density Phantom. Lastly, two phantoms were designed to simulate attenuation in four tissue-equivalent materials for two different source geometries (1-mL and 10-mL syringes). 177Lu SPECT/CT imaging was performed using three different reconstruction algorithms (xSPECT Quant, Flash3D, STIR), and the SPECT-based activities were compared against the nominal activities in the sources.ResultsThe largest relative errors between μmeasured and μtheoretical were observed in the lung inhale insert (range: 18%-36%), while it remained below 6% for all other inserts. The resulting changes in 177Lu activity quantification were -3.5% in the lung inhale insert and less than -2.3% in all other inserts. Coefficient of variation and CTDIvol ranged from 0.3% and 3.6 mGy (130 kVp, 35 mAs) to 0.4% and 0.9 mGy (80 kVp, 20 mAs), respectively. The SPECT-based activity quantification using xSPECT Quant reconstructions outperformed all other reconstruction algorithms.ConclusionThis study shows that kVp and QRM values in low-dose CT imaging have a minimum effect on quantitative 177Lu SPECT/CT imaging, while the selection of low values of kVp and QRM reduce the CTDIvol.

Optimizing cone-beam computed tomography exposure for an effective radiation dose and image quality balance.

The aim of this study was to evaluate the influence of different cone-beam computed tomography (CBCT) acquisition protocols on reducing the effective radiation dose while maintaining image quality. The effective dose emitted by a CBCT device was calculated using thermoluminescent dosimeters placed in a Rando Alderson phantom. Image quality was assessed by 3 experienced evaluators. The relationship between image quality and confidence was evaluated using the Fisher exact test, and the agreement among raters was assessed using the kappa test. Multiple linear regression analysis was performed to investigate whether the technical parameters could predict the effective dose. P-values<0.05 were considered to indicate statistical significance. The optimized protocol (3 mA, 99 kVp, and 450 projection images) demonstrated good image quality and a lower effective dose for radiation-sensitive organs. Image quality and confidence had consistent values for all structures (P<0.05). Multiple linear regression analysis resulted in a statistically significant model. The milliamperage (b=0.504; t=3.406; P=0.027), kilovoltage peak (b=0.589; t=3.979; P=0.016) and number of projection images (b=0.557; t=3.762; P=0.020) were predictors of the effective dose. Optimized CBCT acquisition protocols can significantly reduce the effective radiation dose while maintaining acceptable image quality by adjusting the milliamperage and projection images.

Combination of metal artifact reduction and sharpening filter application for horizontal root fracture diagnosis in teeth adjacent to a zirconia implant.

This study examined the influence of metal artifact reduction (MAR), the application of sharpening filters, and their combination on the diagnosis of horizontal root fracture (HRF) in teeth adjacent to a zirconia implant on cone-beam computed tomography (CBCT) examinations. Nineteen single-rooted teeth (9 with HRF and 10 without) were individually positioned in the right central incisor socket of a dry human maxilla. A zirconia implant was placed adjacent to each tooth. Imaging was performed using an OP300 Maxio CBCT (Instrumentarium, Tuusula, Finland) unit with the following settings: a current of 8 mA, both MAR modes (enabled and disabled), a 5×5 cm field of view, a voxel size of 0.085 mm, and a peak kilovoltage of 90 kVp. Four oral and maxillofacial radiologists independently evaluated the CBCT scans under both MAR conditions and across 3 levels of sharpening filter application (none, Sharpen 1×, and Sharpen 2×). Diagnostic metrics were calculated and compared using 2-way analysis of variance (α=5%). The weighted kappa test was used to assess intra- and inter-examiner reliability in the diagnosis of HRF. MAR tool activation, sharpening filter use, and their combination did not significantly impact the area under the receiver operating characteristic curve, sensitivity, or specificity of HRF diagnosis (P>0.05). Intra- and inter-examiner agreement ranged from fair to substantial. The diagnosis of HRF in a tooth adjacent to a zirconia implant is not affected by the activation of MAR, the application of a sharpening filter, or the combination of these tools.

Radiation measurements in dentistry

When patients undergo X-ray examinations, millions of photons pass through their bodies. In dental radiography, the part of the head that receives the greatest dose is the skin in the area where the X-rays enter, including brain, salivary gland and thyroid. The effective usage of radiation in dental practice has been studied for many years and several guidelines have been proposed. While not high doses of radiation are associated with dental radiography in the field of using radiation in dentistry practice it is the most important to provide periodical radiation measurements for radiographs used in dental clinics, to measure such main X-rays specifications, as Kilovoltage Peak (kVp), Dose/Exposure, Dose/Exposure Rate, Exposure Time – Radiographic Modes, Elapsed Time – Fluoro Modes, Average Pulse Rate – Pulsed Fluoro, Average Pulse Width – Pulsed Fluoro and Half-value Layer HVL. Besides these parameters of mAs spesifications da DoseMate specifications also must be measured. Quality control of radiological devices is very important. So, we plan periodical radiation measurements in more than 50 dental clinics in Georgia and hope that results of these measurements will be successful, encouraging. After the measurements, the results will be known to all stakeholders. We will also talk about them in our next publications.

Ability of artificial intelligence to identify self-reported race in chest x-ray using pixel intensity counts.

Prior studies show convolutional neural networks predicting self-reported race using x-rays of chest, hand and spine, chest computed tomography, and mammogram. We seek an understanding of the mechanism that reveals race within x-ray images, investigating the possibility that race is not predicted using the physical structure in x-ray images but is embedded in the grayscale pixel intensities. Retrospective full year 2021, 298,827 AP/PA chest x-ray images from 3 academic health centers across the United States and MIMIC-CXR, labeled by self-reported race, were used in this study. The image structure is removed by summing the number of each grayscale value and scaling to percent per image (PPI). The resulting data are tested using multivariate analysis of variance (MANOVA) with Bonferroni multiple-comparison adjustment and class-balanced MANOVA. Machine learning (ML) feed-forward networks (FFN) and decision trees were built to predict race (binary Black or White and binary Black or other) using only grayscale value counts. Stratified analysis by body mass index, age, sex, gender, patient type, make/model of scanner, exposure, and kilovoltage peak setting was run to study the impact of these factors on race prediction following the same methodology. MANOVA rejects the null hypothesis that classes are the same with 95% confidence ( 7.38, ) and balanced MANOVA ( 2.02, ). The best FFN performance is limited [area under the receiver operating characteristic (AUROC) of 69.18%]. Gradient boosted trees predict self-reported race using grayscale PPI (AUROC 77.24%). Within chest x-rays, pixel intensity value counts alone are statistically significant indicators and enough for ML classification tasks of patient self-reported race.

The effect of added filtration on radiation dose and image quality in digital radiography of newborns.

Repeated chest and/or abdomen radiographs are needed on mobile digital radiography (DR) units to assess infants' health status. Optimization of DR tube peak kilovoltage (kVp) and tube current time product (mAs) to derive images of diagnostic quality at as low as reasonably achievable radiation dose has been a challenging task. To investigate the effect of exposure parameters and additional filtration on entrance skin dose and image quality in newborn DR imaging. A physical anthropomorphic phantom that simulates the average full-term neonate was used. Chest and chest/abdomen DR images were acquired at the manufacturer's recommended kVp/mAs exposure parameters followed by a series of image acquisitions at different kVp/mAs and beam filtration combinations. Entrance skin dose (ESD) and signal difference to noise ratio (SdNR) for soft tissue, bone and feeding gastric tube were estimated in raw unprocessed images. A figure of merit (FOM) analysis provided the kVp/mAs and filtration that generated images of adequate quality at the lowest ESD. Signal difference increased with kVp and progressively decreased with increasing filtration. Compared to the manufacturer's recommended 53 kVp/1.6 mAs exposure parameters, ESD was reduced by 76% (47.61μGy versus 11.3μGy) in the chest and 66% (47.61μGy versus 16.14μGy) in the chest/abdomen when the exposure parameters and additional beam filtration provided by the FOM analysis were used. The results derived from this phantom study suggest that additional beam filtration along with the appropriate leverage of exposure parameters can lower ESD while maintaining image quality in full-term newborns.

Establishing weight-based diagnostic reference levels for neonatal chest X-rays

IntroductionAs weights among neonates can vary from <900 g to >2.5 kg, weight-based Diagnostic Reference Levels (DRLs) specific to the neonatal intensive care unit (NICU) are essential. Repeated radiation exposure to this sensitive patient group raises concerns regarding high cumulative radiation doses and the potential for long-term health detriment. This study aimed to establish weight-based DRLs for neonates undergoing mobile chest radiography (CXR) in the NICU. MethodsNeonates were classified into three discrete groups; <1000, 1000–2500 and >2500 g. Data were collected prospectively over three months; 95 DAP values were collected, and five were excluded due to poor technique, leaving 90 patients that met the inclusion criteria for mobile CXR in the NICU. Dose-area-product (DAP) in mGycm2, the peak kilovoltage (kVp) and the product of tube current and exposure time (mAs) were retrieved from the Picture Archiving and Communication System (PACS). Images and radiological reports were also analysed to confirm diagnostic image quality (IQ). Local DRLs (LDRLs) were derived using the median DAP, and national DRLs were suggested using the 3rd quartile value. ResultsThe proposed LDRLs for neonates weighing <1000 g was 2.7 mGycm2, for neonates weighing between 1000 g and 2500 g, it was 3.7 mGycm2, and for neonates weighing >2500 g it was 6.6 mGycm2. The radiation dose received by the 90 (100%) neonates included in the study fell below 11.4 mGycm2; of these, 82% of the DAP values fell below the study institution's existing LDRL of 7.25 mGycm2. ConclusionWeight-based DRLs provide crucial information on doses to this specific radiation-sensitive group. This work recommends using weight-based categories for DRLs and serves as a benchmark for neonatal CXR standardisation and optimisation. Implications for practiceThe proposed weight-based DRLs can be adopted for neonates’ locally, nationally and internationally.

Prediction of low DEXA T-scores by routine computed tomography body scans at different kilovoltage peaks.

Previous studies have demonstrated positive correlations between computed tomography (CT) attenuation of lumbar spine vertebrae and their bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DEXA). However, these studies were performed using a standard 120 kilovoltage peak (kVp) setting. As radiation attenuation in mineralised tissues varies by the tube voltage applied, we determined the diagnostic accuracy of CT attenuation at identifying individuals with low BMD at different kVp settings. Single centre retrospective study of adults who had CT and DEXA scans within 6 months of each other. CT scans were performed at either 100 kVp, 120 kVp or dual energy (80 kVp/140 kVp). Attenuation was measured in axial cross-sections of L1-4 vertebrae and correlated with the results of DEXA. Receiver operated characteristic (ROC) curves were generated to determine diagnostic cut-off thresholds. Analysis included 268 subjects (169 females; mean age: 70, range: 20-94 years). CT attenuation values at L1 or mean L1-4 correlated positively with DEXA-derived T-scores. At L1, the optimal Hounsfield units (HU) thresholds for predicting DEXA T-scores of -2.5 or less at 100 kVp, 120 kVp and dual-energy scans were <170, <128 and <164, with corresponding AUCs of 0.925, 0.814 and 0.743 respectively. For mean L1-4, the HU thresholds were <173, <134 and <151, with corresponding AUCs of 0.933, 0.824 and 0.707 respectively. CT attenuation thresholds differ depending on the tube voltage used. We provide voltage-specific, probability-optimised thresholds for the identification of persons likely to have low BMD on DEXA scanning.

Optimal dual-energy computed tomography scan parameters to detect small-sized urinary stones and their composition

To investigate the optimal scanning parameters of dual-energy computed tomography (DECT), which can accurately determine sensitivity (the detectability of urinary stones) and accuracy (the composition matching of urinary stones), and to apply them to clinical trials. Fifteen urinary stones were chemically analyzed, and their chemical compositions were considered a reference standard with which we compared the uric acid (UA) and non-UA compositions determined using DECT. The urinary stones were placed inside a bolus and scanned with a dual-source CT scanner under various selected dual-energy conditions (A to X) using various solid water phantom thicknesses. These datasets were analyzed using the Siemens syngo.via software tool (integrated into the CT system) for matching the sensitivity and accuracy assessments. This study showed that 80% of the highest sensitivity (detection of urinary stones) and 92% of the highest accuracy (composition matching of urinary stones) were achieved under condition A (a collimation beam width setting of 2 × 32× 0.6mm, an automatic exposure control setting of 80/sn140 peak kilovoltage, and a slice thickness of 0.5/0.5mm) (P < 0.05). Application of the DECT energy parameters presented in the study will help identify the sensitivity and accuracy of UA and non-UA stone analysis, even in patients with small-sized urinary stones and in conditions difficult for analysis.

Assessing the Efficacy of Planmeca ProMax® 3D Cone-Beam CT Machine in the Detection of Root Fractures With Varied Metal Artifact Reduction Settings and Three Kilovoltage Peak Levels

This study aims to examine the accuracy of cone-beam computed tomography (CBCT) machines in detecting root fracture when using different metal artifact reduction (MAR) settings at different kilovoltage peak (kVp) levels. Sixty-six tooth roots were treated endodontically using a standardized technique. Of these, 33 roots were randomly selected to be fractured; the other 33 roots were intact and used as controls. The roots were placed randomly in prepared beef ribs to mimic the alveolar bone. Imaging was performed by Planmeca ProMax® 3D (Planmeca, Helsinki, Finland) using different MAR settings (no, low, mid, and high) at three different levels of kVp: 70, 80, and 90. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. There was a significant difference in accuracy when using different MAR settings within the group of 70 kVp. Likewise, within the group of 90 kVp. There was no significant difference between different MAR settings at 80 kVp. Using low MAR/90 kVp had significantly higher accuracy relative to other MAR settings at 90 kVp; it also had the highest values of sensitivity, specificity, and AUC in the study. Using mid and high MAR at 70 kVp or 90 kVp decreased accuracy significantly. Mid MAR/90 kVp was the least effective setting in this study. Using low MAR at 90 kVp significantly increased the accuracy within the group of 90 kVp. In contrast, mid MAR and high MAR in70 and 90 kVp, respectively, decreased accuracy significantly.

Impact of the implementation of the new radiation quantities recommended by ICRU/ICRP for practical use in interventional radiology: a Monte Carlo study

The International Commission on Radiation Units and Measurements (ICRU) proposed a new set of operational quantities for radiation protection for external radiation in its Report Committee 26 (ICRU 95). The new proposal aims to improve the coherence between the operational quantities and the definitions of the protection quantities in the recommendations of the International Commission on Radiological Protection set out in 2007 (Ann. ICRP 37). It is expected that this change in operational quantities will impact current dosimeter designs. Although for many photon energies, the conversion coefficients from physical field quantities to the new operational quantities will change relatively little, for radiation fields with low energy photon components, such as medical x-ray applications, there will be a significant decrease in the values of the conversion coefficients. This means that the numerical values of the new operational quantities will be much lower for the same radiation field. These values will be closer to the effective dose, but this change can still cause confusion for medical staff. It is important to examine the effect of the new set of dose conversion coefficients on the personal dose in realistic radiation fields. We performed a study to assess the effect of changing the definition of the operational quantity, personal dose equivalent (), in realistic radiation fields in interventional radiology (IR) workplaces. The x-ray tube kilovoltage peak (kVp) in IR ranges between 60 and 120 kV. The medical staff is exposed to the scattered photons which have a wide range of energies depending on the beam configuration and the patient size. The objective of this study is to ‘quantitatively’ estimate the impact of implementing the new ICRU quantities of Report 95 in IR radiation fields using Monte Carlo simulations. Simulations of 560 different configurations in IR were performed using MCNPX to calculate fluence binned per energy and angle of incidence. and were then calculated for each configuration using dose conversion coefficients from fluence given by ICRU Reports 95 and 57, respectively. The results show that the mean of the ratio, , is 1.6 for all simulated scenarios. This reduction will correct the current overestimation of the effective dose and should result in better compliance with the dose limits in IR. However, it may also have negative consequences on the safety culture among the medical staff. Special care will be needed when interpreting these lower doses.

Evaluating the effects of variation in CT scanning parameters on the image quality and Hounsfield units for optimization of dose in radiotherapy treatment planning: A semi-anthropomorphic thorax phantom study

The diagnosis accuracy of computed tomography (CT) systems and the reliability of calculated Hounsfield Units (HUs) are critical in tumor detection and cancer patients' treatment planning. This study evaluated the effects of scan parameters (Kilovoltage peak or kVp, milli-Ampere-second or mAS reconstruction kernels and algorithms, reconstruction field of view, and slice thickness) on image quality, HUs, and the calculated dose in the treatment planning system (TPS). A quality dose verification phantom was scanned several times by a 16-slice Siemens CT scanner. The DOSIsoft ISO gray TPS was applied for dose calculations. The SPSS.24 software was used to analyze the results and the P-value <0.05 was considered significant. Reconstruction kernels and algorithms significantly affected noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The noise increased and CNR decreased by raising the sharpness of reconstruction kernels. SNR and CNR had considerable increments at iterative reconstruction compared with the filtered back-projection algorithm. The noise decreased by raising mAS in soft tissues. Also, KVp had a significant effect on HUs. TPS--calculated dose variations were less than 2% for mediastinum and backbone and less than 8% for rib. Although HU variation depends on image acquisition parameters across a clinically feasible range, its dosimetric impact on the calculated dose in TPS can be neglected. Hence, it can be concluded that the optimized values of scan parameters can be applied to obtain the maximum diagnostic accuracy and calculate HUs more precisely without affecting the calculated dose in the treatment planning of cancer patients.