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Pediatric head computed tomography (CT) scans necessitate precise determination of radiation dose to optimize image quality while minimizing patient exposure. This study explores the influence of head size variation on radiation dose and image quality using phantom and patients set, aiming to investigate the efficacy of Automatic Exposure Control (AEC) in dose modulation. Image noise and radiation dose were assessed using with and without AEC, maintaining a constant tube current of 180 mA. The correlation between CT dose index volume (CTDIvol) and water-equivalent diameter (Dw) was examined across 134 image sets, revealing an exponential relationship indicative of AEC's contribution to elevated radiation exposure in larger heads. Furthermore, a slice-based analysis demonstrated a consistent variation in tube current along the slice location, effectively modulated by Dw. However, discrepancies in tube current were observed in the caudal region, suggesting the influence of factors beyond section size. Refinement of analysis improved curve fitting, highlighting the importance of section size in dose modulation. AEC proved essential in maintaining image quality consistency across slices, with inactive AEC resulting in lower image noise in cranial slices. These findings highlight the significance of AEC-based dose modulation in pediatric head CT to ensure optimal image quality while minimizing radiation exposure, emphasizing the need for comprehensive understanding and implementation of AEC systems from different manufacturers. [ABSTRACT FROM AUTHOR]

In radiography procedures, radiographers’ suboptimal positioning and exposure parameter settings may necessitate image retakes, subjecting patients to unnecessary ionizing radiation exposure. Reducing retakes is crucial to minimize patient X-ray exposure and conserve medical resources. We propose a Digital Radiography (DR) Pre-imaging All-round Assistant (PIAA) that leverages Artificial Intelligence (AI) technology to enhance traditional DR. PIAA consists of an RGB-Depth (RGB-D) multi-camera array, an embedded computing platform, and multiple software components. It features an Adaptive RGB-D Image Acquisition (ARDIA) module that automatically selects the appropriate RGB camera based on the distance between the cameras and patients. It includes a 2.5D Selective Skeletal Keypoints Estimation (2.5D-SSKE) module that fuses depth information with 2D keypoints to estimate the pose of target body parts. Thirdly, it also uses a Domain expertise (DE) embedded Full-body Exposure Parameter Estimation (DFEPE) module that combines 2.5D-SSKE and DE to accurately estimate parameters for full-body DR views. Optimizes DR workflow, significantly enhancing operational efficiency. The average time required for positioning patients and preparing exposure parameters was reduced from 73 seconds to 8 seconds. PIAA shows significant promise for extension to full-body examinations. [ABSTRACT FROM AUTHOR]

Abstract Background Automatic exposure control (AEC) plays a crucial role in mammography by determining the exposure conditions needed to achieve specific image quality based on the absorption characteristics of compressed breasts. This study aimed to characterize the behavior of AEC for digital mammography (DM), digital breast tomosynthesis (DBT), and low-energy (LE) and high-energy (HE) acquisitions used in contrast-enhanced mammography (CEM) for three mammography systems from two manufacturers. Methods Using phantoms simulating various breast thicknesses, 363 studies were acquired using all available AEC modes 165 DM, 132 DBT, and 66 LE-CEM and HE-CEM. AEC behaviors were compared across systems and modalities to assess the impact of different technical components and manufacturers’ strategies on the resulting mean glandular doses (MGDs) and image quality metrics such as contrast-to-noise ratio (CNR). Results For all systems and modalities, AEC increased MGD for increasing phantom thicknesses and decreased CNR. The median MGD values (interquartile ranges) were 1.135 mGy (0.772–1.668) for DM, 1.257 mGy (0.971–1.863) for DBT, 1.280 mGy (0.937–1.878) for LE-CEM, and 0.630 mGy (0.397–0.713) for HE-CEM. Medians CNRs were 14.2 (7.8–20.2) for DM, 4.91 (2.58–7.20) for a single projection in DBT, 11.9 (8.0–18.2) for LE-CEM, and 5.2 (3.6–9.2) for HE-CEM. AECs showed high repeatability, with variations lower than 5% for all modes in DM, DBT, and CEM. Conclusions The study revealed substantial differences in AEC behavior between systems, modalities, and AEC modes, influenced by technical components and manufacturers’ strategies, with potential implications in radiation dose and image quality in clinical settings. Relevance statement The study emphasized the central role of automatic exposure control in DM, DBT, and CEM acquisitions and the great variability in dose and image quality among manufacturers and between modalities. Caution is needed when generalizing conclusions about differences across mammography modalities. Key points • AEC plays a crucial role in DM, DBT, and CEM. • AEC determines the “optimal” exposure conditions needed to achieve specific image quality. • The study revealed substantial differences in AEC behavior, influenced by differences in technical components and strategies. Graphical Abstract

Background: Automatic exposure control (AEC) plays a crucial role in mammography by determining the exposure conditions needed to achieve specific image quality based on the absorption characteristics of compressed breasts. This study aimed to characterize the behavior of AEC for digital mammography (DM), digital breast tomosynthesis (DBT), and low-energy (LE) and high-energy (HE) acquisitions used in contrast-enhanced mammography (CEM) for three mammography systems from two manufacturers. Methods: Using phantoms simulating various breast thicknesses, 363 studies were acquired using all available AEC modes 165 DM, 132 DBT, and 66 LE-CEM and HE-CEM. AEC behaviors were compared across systems and modalities to assess the impact of different technical components and manufacturers' strategies on the resulting mean glandular doses (MGDs) and image quality metrics such as contrast-to-noise ratio (CNR). Results: For all systems and modalities, AEC increased MGD for increasing phantom thicknesses and decreased CNR. The median MGD values (interquartile ranges) were 1.135 mGy (0.772–1.668) for DM, 1.257 mGy (0.971–1.863) for DBT, 1.280 mGy (0.937–1.878) for LE-CEM, and 0.630 mGy (0.397–0.713) for HE-CEM. Medians CNRs were 14.2 (7.8–20.2) for DM, 4.91 (2.58–7.20) for a single projection in DBT, 11.9 (8.0–18.2) for LE-CEM, and 5.2 (3.6–9.2) for HE-CEM. AECs showed high repeatability, with variations lower than 5% for all modes in DM, DBT, and CEM. Conclusions: The study revealed substantial differences in AEC behavior between systems, modalities, and AEC modes, influenced by technical components and manufacturers' strategies, with potential implications in radiation dose and image quality in clinical settings. Relevance statement: The study emphasized the central role of automatic exposure control in DM, DBT, and CEM acquisitions and the great variability in dose and image quality among manufacturers and between modalities. Caution is needed when generalizing conclusions about differences across mammography modalities. Key points: • AEC plays a crucial role in DM, DBT, and CEM. • AEC determines the "optimal" exposure conditions needed to achieve specific image quality. • The study revealed substantial differences in AEC behavior, influenced by differences in technical components and strategies. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT) is a widely used imaging technique in interventional radiology. Although CBCT offers great advantages in terms of improving comprehension of complex angioarchitectures and guiding therapeutic decisions, its additional degree of radiation exposure has also aroused considerable concern. In this study, we aimed to assess radiation exposure and its influential factors in patients undergoing CBCT scans of the head and abdomen during interventional procedures. A total of 752 patients were included in this retrospective study. Dose area product (DAP) and reference air kerma (RAK) were used as measures of patient dose. The results showed that the median values of DAP were 53.8 (50.5–64.4) Gy⋅cm2 for head CBCT and 47.4 (39.6–54.3) Gy⋅cm2 for that of the abdomen. Male gender and body mass index (BMI) were characterized by increased DAP and RAK values in both head and abdominal CBCT scans. Larger FOV size was associated with a higher DAP but a lower RAK value, especially in head CBCT scans. Exposure parameters under automatic exposure control (AEC) also varied according to patient BMI and gender. In conclusion, the patients received slightly higher radiation doses from head CBCT scans than from those applied to the abdomen. BMI, gender, and FOV size were the key factors that influenced the radiation dose administered to the patients during CBCT scans. Our results may help to define and minimize patients' exposure to radiation. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT) is a widely used imaging technique in interventional radiology. Although CBCT offers great advantages in terms of improving comprehension of complex angioarchitectures and guiding therapeutic decisions, its additional degree of radiation exposure has also aroused considerable concern. In this study, we aimed to assess radiation exposure and its influential factors in patients undergoing CBCT scans of the head and abdomen during interventional procedures. A total of 752 patients were included in this retrospective study. Dose area product (DAP) and reference air kerma (RAK) were used as measures of patient dose. The results showed that the median values of DAP were 53.8 (50.5–64.4) Gy⋅cm2 for head CBCT and 47.4 (39.6–54.3) Gy⋅cm2 for that of the abdomen. Male gender and body mass index (BMI) were characterized by increased DAP and RAK values in both head and abdominal CBCT scans. Larger FOV size was associated with a higher DAP but a lower RAK value, especially in head CBCT scans. Exposure parameters under automatic exposure control (AEC) also varied according to patient BMI and gender. In conclusion, the patients received slightly higher radiation doses from head CBCT scans than from those applied to the abdomen. BMI, gender, and FOV size were the key factors that influenced the radiation dose administered to the patients during CBCT scans. Our results may help to define and minimize patients’ exposure to radiation.

Around the background of rapid development of intelligent technology, an efficient image processing system oriented to the smart management of human faces is focused on. The system is mainly developed towards high speed, high definition, high integration and reliability. The article investigates a novel automatic image processing algorithm, covering three key modules: automatic exposure control, color interpolation and chromaticity space conversion. The algorithm can process the output image of CMOS sensor in Bayer format in real time and adjust the image parameters to obtain a high-quality image. In terms of face recognition performance, the algorithm has a significant advantage in recognition speed compared with other algorithms, and the average recognition accuracy reaches 94.258%. In the practical application of ID card portrait processing, the image shows a more uniform grayscale distribution in the range of 5 to 255 after automatic color adjustment, and the color quality is significantly improved. Meanwhile, in the portrait enhancement experiments, the images obtained with this image automatic processing algorithm outperform the traditional ID card image processing methods regarding information entropy, mutual information, standard deviation and peak signal-to-noise ratio (PSNR).

The current study aimed to investigate the relationship between body parameters and the current–time product (mAs) in chest digital radiography using a non-contact infrared thickness-measurement sensor. An anthropomorphic chest phantom was first used to understand variations in mAs over multiple positionings during chest radiography when using the automatic exposure control (AEC) technique. In a human study, 929 consecutive male subjects who underwent regular chest examinations were enrolled, and their height (H), weight (W), and body mass index (BMI) were recorded. In addition, their chest thickness (T) was measured at exhalation using a non-contact infrared sensor, and chest radiography was then performed using the AEC technique. Finally, the relationship between four body parameters (T, BMI, T*BMI, and W/H) and mAs was investigated by fitting the body parameters to mAs using three curve models. The phantom study showed that the maximum mAs was 1.76 times higher than the lowest mAs during multiple positionings in chest radiography. In the human study, all chest radiographs passed the routine quality control procedure and had an exposure index between 100 and 212. In curve fitting, the comparisons showed that W/H had a closer relationship with mAs than the other body parameters, while the first-order power model with W/H fitted to mAs performed the best and had an R-square of 0.9971. We concluded that the relationship between W/H and mAs in the first-order power model may be helpful in predicting the optimal mAs and reducing the radiation dose for chest radiography when using the AEC technique. [ABSTRACT FROM AUTHOR]

We investigated the relationship between the head size and radiation dose in pediatric brain computed tomography (CT) to evaluate the validity of automatic exposure control (AEC). Phantom experiments were performed to assess image noise with and without AEC, and indicated that AEC decreased differences in noise between slices of different section sizes. Retrospective analysis was conducted on 980 pediatric brain CT scans where the tube current was determined using AEC. The water equivalent diameter (WED) was employed as an index of the head size, and mean WED for each image set (WEDmean) and WED for each slice (WEDslice) were used for analysis. For the image-set-based analysis, volume CT dose index (CTDIvol) was compared to WEDmean. For the slice-based analysis, the tube current was compared to WEDslice using 20 of the 980 sets. Additionally, CTDIvol and WEDmean were compared between male and female patients matched for age, weight, or WEDmean. CTDIvol increased with increasing WEDmean, and an exponential curve was closely fitted to the relationship. Tube current changed similarly to the change in WEDslice for each image set, and an exponential curve was well-fitted to the plots of tube current against WEDslice when data from the 20 sets were pooled together. Although CTDIvol and WEDmean were slightly but significantly larger for male than female patients after matching for age or weight, a sex-dependent difference in CTDIvol was not found after matching for WEDmean. This study indicated successful dose modulation using AEC according to the head size for each patient and each slice location. The application of AEC to pediatric brain CT is recommended for radiation dose optimization.

Purpose: This work investigates the impact of tissue‐equivalent attenuator choice on measured signal‐to‐noise ratio (SNR) for automatic exposure control (AEC) performance evaluation in digital mammography. It also investigates how the SNR changes for each material when used to evaluate AEC performance across different mammography systems. Methods: AEC performance was evaluated for four mammography systems using seven attenuator sets at two thicknesses (4 and 8 cm). All systems were evaluated in 2D imaging mode, and one system was evaluated in digital breast tomosynthesis (DBT) mode. The methodology followed the 2018 ACR digital mammography quality control (DMQC) manual. Each system‐attenuator‐thickness combination was evaluated using For Processing images in ImageJ with standard ROI size and location. The closest annual physicist testing results were used to explore the impact of varying measured AEC performance on image quality. Results: The measured SNR varied by 44%–54% within each system across all attenuators at 4 cm thickness in 2D mode. The variation appeared to be largely due to changes in measured noise, with variations of 46%–67% within each system across all attenuators at 4 cm thickness in 2D mode. Two systems had failing SNR levels for two of the materials using the minimum SNR criterion specified in the ACR DMQC manual. Similar trends were seen in DBT mode and at 8 cm thickness. Within each material, there was 115%–131% variation at 4 cm and 82%–114% variation at 8 cm in the measured SNR across the four imaging systems. Variation in SNR did not correlate with system operating level based on visual image quality and average glandular dose (AGD). Conclusion: Choice of tissue‐equivalent attenuator for AEC performance evaluation affects measured SNR values. Depending on the material, the difference may be enough to result in failure following the longitudinal and absolute thresholds specified in the ACR DMQC manual. [ABSTRACT FROM AUTHOR]

We investigated the relationship between the head size and radiation dose in pediatric brain computed tomography (CT) to evaluate the validity of automatic exposure control (AEC). Phantom experiments were performed to assess image noise with and without AEC, and indicated that AEC decreased differences in noise between slices of different section sizes. Retrospective analysis was conducted on 980 pediatric brain CT scans where the tube current was determined using AEC. The water equivalent diameter (WED) was employed as an index of the head size, and mean WED for each image set (WEDmean) and WED for each slice (WEDslice) were used for analysis. For the image-set-based analysis, volume CT dose index (CTDIvol) was compared to WEDmean. For the slice-based analysis, the tube current was compared to WEDslice using 20 of the 980 sets. Additionally, CTDIvol and WEDmean were compared between male and female patients matched for age, weight, or WEDmean. CTDIvol increased with increasing WEDmean, and an exponential curve was closely fitted to the relationship. Tube current changed similarly to the change in WEDslice for each image set, and an exponential curve was well-fitted to the plots of tube current against WEDslice when data from the 20 sets were pooled together. Although CTDIvol and WEDmean were slightly but significantly larger for male than female patients after matching for age or weight, a sex-dependent difference in CTDIvol was not found after matching for WEDmean. This study indicated successful dose modulation using AEC according to the head size for each patient and each slice location. The application of AEC to pediatric brain CT is recommended for radiation dose optimization. [ABSTRACT FROM AUTHOR]

The current study aimed to investigate the relationship between body parameters and the current–time product (mAs) in chest digital radiography using a non-contact infrared thickness-measurement sensor. An anthropomorphic chest phantom was first used to understand variations in mAs over multiple positionings during chest radiography when using the automatic exposure control (AEC) technique. In a human study, 929 consecutive male subjects who underwent regular chest examinations were enrolled, and their height (H), weight (W), and body mass index (BMI) were recorded. In addition, their chest thickness (T) was measured at exhalation using a non-contact infrared sensor, and chest radiography was then performed using the AEC technique. Finally, the relationship between four body parameters (T, BMI, T*BMI, and W/H) and mAs was investigated by fitting the body parameters to mAs using three curve models. The phantom study showed that the maximum mAs was 1.76 times higher than the lowest mAs during multiple positionings in chest radiography. In the human study, all chest radiographs passed the routine quality control procedure and had an exposure index between 100 and 212. In curve fitting, the comparisons showed that W/H had a closer relationship with mAs than the other body parameters, while the first-order power model with W/H fitted to mAs performed the best and had an R-square of 0.9971. We concluded that the relationship between W/H and mAs in the first-order power model may be helpful in predicting the optimal mAs and reducing the radiation dose for chest radiography when using the AEC technique.

Abstract Background A significant proportion of the radiation dose from a PET-CT examination is dependent on the CT protocol, which should be optimised for clinical purposes. Matching protocols on different scanners within an imaging centre is important for the consistency of image quality and dose. This paper describes our experience translating low-dose CT protocols between scanner models utilising different automatic exposure control (AEC) methods and reconstruction algorithms. Methods The scanners investigated were a newly installed Siemens Biograph mCT PET with 64-slice SOMATOM Definition AS CT using sinogram affirmed iterative reconstruction (SAFIRE) and two GE Discovery 710 PET scanners with 128-slice Optima 660 CT using adaptive statistical reconstruction (ASiR). Following exploratory phantom work, 33 adult patients of various sizes were scanned using the Siemens scanner and matched to patients scanned using our established GE protocol to give 33 patient pairs. A comparison of volumetric CT dose index (CTDIvol) and image noise within these patient pairs informed optimisation, specifically for obese patients. Another matched patient study containing 27 patient pairs was used to confirm protocol matching. Size-specific dose estimates (SSDEs) were calculated for patients in the second cohort. With the acquisition protocol for the Siemens scanner determined, clinicians visually graded the images to identify optimal reconstruction parameters. Results In the first matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 10.7% (range − 41.7 to 50.1%), and the mean percentage difference in noise measured in the patients’ liver was 7.6% (range − 31.0 to 76.8%). In the second matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 20.5% (range − 43.1 to 1.9%), and the mean percentage difference in noise was 19.8% (range − 27.0 to 146.8%). For these patients, the mean SSDEs for patients scanned on the Siemens and GE scanners were 3.27 (range 2.83 to 4.22) mGy and 4.09 (range 2.81 to 4.82) mGy, respectively. The analysis of the visual grading study indicated no preference for any of the SAFIRE strengths. Conclusions Given the different implementations of acquisition parameters and reconstruction algorithms between vendors, careful consideration is required to ensure optimisation and standardisation of protocols.

Detector saturation in cone-beam computed tomography occurs when an object of highly varying shape and material composition is imaged using an automatic exposure control (AEC) system. When imaging a subject’s knees, high beam energy ensures the visibility of internal structures but leads to overexposure in less dense border regions. In this work, we propose to use an additional low-dose scan to correct the saturation artifacts of AEC scans. Overexposed pixels are identified in the projection images of the AEC scan using histogram-based thresholding. The saturation-free pixels from the AEC scan are combined with the skin border pixels of the low-dose scan prior to volumetric reconstruction. To compensate for patient motion between the two scans, a 3D non-rigid alignment of the projection images in a backward-forward-projection process based on fiducial marker positions is proposed. On numerical simulations, the projection combination improved the structural similarity index measure from 0.883 to 0.999. Further evaluations were performed on two in vivo subject knee acquisitions, one without and one with motion between the AEC and low-dose scans. Saturation-free reference images were acquired using a beam attenuator. The proposed method could qualitatively restore the information of peripheral tissue structures. Applying the 3D non-rigid alignment made it possible to use the projection images with inter-scan subject motion for projection image combination. The increase in radiation exposure due to the additional low-dose scan was found to be negligibly low. The presented methods allow simple but effective correction of saturation artifacts.

In computed tomography (CT), organ dose modulation (ODM) reduces radiation exposure from the anterior side to reduce radiation dose received by the radiosensitive organs located anteriorly. We investigated the effects of ODM applied to a part of the scan range on radiation dose in body CT. The thorax and thoraco-abdominopelvic region of an anthropomorphic whole-body phantom were imaged with and without ODM. ODM was applied to various regions, and the tube current modulation curves were compared. Additionally, the dose indices were compared with and without ODM in thoracic and thoraco-abdominopelvic CTs in 800 patients. ODM was applied to the thyroid in male patients and to the thyroid and breast in female patients. In phantom imaging of the thorax, the application of ODM below the scan range decreased the tube current, and that to the breast showed a further decrease. Decreased tube current was also observed in phantom imaging of the thoraco-abdominopelvic regions with ODM below the scan range, and the application of ODM to the whole scan range, thyroid, breast, and both thyroid and breast further reduced the tube current in the region to which ODM was applied. In patient imaging, the dose indices were significantly lower with ODM than without ODM, regardless of the scan range or sex. The absolute reduction in dose-length product was larger for thoraco-abdominopelvic CT (male, 43.2 mGy cm; female, 59.7 mGy cm) than for thoracic CT (male, 30.8 mGy cm; female, 37.6 mGy cm) in both sexes, indicating dose reduction in the abdominopelvic region to which ODM was not applied. In conclusion, The application of ODM in body CT reduces radiation dose not only in the region to which ODM is applied but also outside the region. In radiation dose management, it should be considered that even ODM applied to a limited region affects the dose indices., (© 2024 Society for Radiological Protection. Published on behalf of SRP by IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Automatic exposure control (AEC) is used to optimize the X-ray tube output during computed tomography (CT) scans. However, calculation of the tube current by AEC can be affected when a patient is not aligned with the rotational center of the X-ray tube. An automatic couch height-positioning compensation mechanism provides a corrective function when the patient is off-center. In this study, we aimed to (a) evaluate the performance characteristics of the positioning compensation mechanism and (b) confirm whether our proposed compensation method can be properly applied to a noise-based AEC system even if the CT device is not equipped with a positioning compensation mechanism. An elliptical phantom was scanned at various table heights on systems without/with the positioning compensation mechanism. Expressions describing the offset from the gantry's isocenter and adjusted standard deviation settings were derived and used in our proposed compensation method. A phantom was scanned at various table heights with our proposed compensation method, and volume CT dose index (CTDIvol) and image noise levels were obtained. An anthropomorphic chest phantom was also scanned using the proposed compensation method to verify its accuracy. When the positioning compensation mechanism was used, it yielded a constant CTDIvol and image noise levels at various table heights tested. A comparison between our proposed method and the positioning compensation mechanism for both the elliptical and chest phantoms yielded similar CTDIvol. Therefore, both automatic and manual positioning compensation methods are useful for avoiding AEC miscalculations in off-centered patient positioning cases. [ABSTRACT FROM AUTHOR]

Purpose: To develop a method to perform quality control (QC) of X‐ray tubes and automatic exposure control (AEC) as a part of the QC of the radiographic and fluoroscopic X‐ray system. Our aim is to verify the output from the X‐ray tube by comparing the measured radiation output, or air kerma, to the theoretical output given the applied exposure settings and geometry, in addition to comparing the measured kV to the nominal kV. The AEC system for fluoroscopic and conventional X‐ray systems is assessed by determining the absorbed dose to a homogenous phantom with different thicknesses. Method: This study presents a model to verify the X‐ray tube measurement results and a method to determine the dose to a homogenous phantom (Dphantom). The following input is needed: a parameterized model of the X‐ray spectrum, the X‐ray tube measurements using a multifunctional X‐ray meter, the exposure parameters recorded via imaging of polymethyl methacrylate (PMMA) slabs of different thickness that simulate the patient using AEC, and a parameterized model for calculating the dose to water from Monte Carlo simulations. The output is the entrance surface dose (ESD) and absorbed dose in the phantom, Dphantom (µGy). In addition, the parameterized X‐ray spectrum is used to compare theoretical and measured air kerma as a part of the QC of the X‐ray tube. To verify the proposed method, the X‐ray spectrum provided in this study, SPECTRUM, was compared to two commercially available spectra, SpekCalc and Institute of Physics and Engineering in Medicine (IPEM) 78. The fraction of energy imparted to the homogenous phantom was compared to the imparted fraction calculated by PCXMC. Results: The spectrum provided in this study was in good agreement with two previously published X‐ray spectra. The absolute percentage differences of the spectra varied from 0.05% to 3.9%, with an average of 1.4%, compared to SpekCalc. Similarly, the deviation from IPEM report 78 varied from 0.02% to 2.3%, with an average of 0.74%. The SPECTRUM was parameterized for calculation of the imparted fraction for target angles of 10°, 12°, and 15°, kV (50–150 kV) with the materials Al (2.2–8 mm), Cu (0–1 mm), and any combination of the filters, PMMA and water. The deviation of energy imparted from the results by PCXMC was less than 8% for all measurements across different kV, filtration, and vendors, obtained by using PMMA to record the exposure parameters, while the dose was calculated based on water with same thicknesses as the PMMA. Conclusion: This study presents an accurate and suitable method to perform a part of the QC of fluoroscopic and conventional X‐ray systems with respect to the X‐ray tube and the associated AEC system. The method is suitable for comparing protocols within and between systems via the absorbed dose. [ABSTRACT FROM AUTHOR]

Background: A significant proportion of the radiation dose from a PET-CT examination is dependent on the CT protocol, which should be optimised for clinical purposes. Matching protocols on different scanners within an imaging centre is important for the consistency of image quality and dose. This paper describes our experience translating low-dose CT protocols between scanner models utilising different automatic exposure control (AEC) methods and reconstruction algorithms. Methods: The scanners investigated were a newly installed Siemens Biograph mCT PET with 64-slice SOMATOM Definition AS CT using sinogram affirmed iterative reconstruction (SAFIRE) and two GE Discovery 710 PET scanners with 128-slice Optima 660 CT using adaptive statistical reconstruction (ASiR). Following exploratory phantom work, 33 adult patients of various sizes were scanned using the Siemens scanner and matched to patients scanned using our established GE protocol to give 33 patient pairs. A comparison of volumetric CT dose index (CTDIvol) and image noise within these patient pairs informed optimisation, specifically for obese patients. Another matched patient study containing 27 patient pairs was used to confirm protocol matching. Size-specific dose estimates (SSDEs) were calculated for patients in the second cohort. With the acquisition protocol for the Siemens scanner determined, clinicians visually graded the images to identify optimal reconstruction parameters. Results: In the first matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 10.7% (range − 41.7 to 50.1%), and the mean percentage difference in noise measured in the patients' liver was 7.6% (range − 31.0 to 76.8%). In the second matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 20.5% (range − 43.1 to 1.9%), and the mean percentage difference in noise was 19.8% (range − 27.0 to 146.8%). For these patients, the mean SSDEs for patients scanned on the Siemens and GE scanners were 3.27 (range 2.83 to 4.22) mGy and 4.09 (range 2.81 to 4.82) mGy, respectively. The analysis of the visual grading study indicated no preference for any of the SAFIRE strengths. Conclusions: Given the different implementations of acquisition parameters and reconstruction algorithms between vendors, careful consideration is required to ensure optimisation and standardisation of protocols. [ABSTRACT FROM AUTHOR]

PurposeAn imaging facility with a diverse fleet of CT scanners faces considerable challenges when propagating CT protocols with consistent image quality and patient dose across scanner makes and models. Although some protocol parameters can comfortably remain constant among scanners (eg, tube voltage, gantry rotation time), the automatic exposure control (AEC) parameter, which selects the overall mA level during tube current modulation, is difficult to match among scanners, especially from different CT manufacturers.MethodsObjective methods for converting tube current modulation protocols among CT scanners were developed. Three CT scanners were investigated, a GE LightSpeed 16 scanner, a GE VCT scanner, and a Siemens Definition AS+ scanner. Translation of the AEC parameters such as noise index and quality reference mAs across CT scanners was specifically investigated. A variable-diameter poly(methyl methacrylate) phantom was imaged on the 3 scanners using a range of AEC parameters for each scanner. The phantom consisted of 5 cylindrical sections with diameters of 13, 16, 20, 25, and 32 cm. The protocol translation scheme was based on matching either the volumetric CT dose index or image noise (in Hounsfield units) between two different CT scanners. A series of analytic fit functions, corresponding to different patient sizes (phantom diameters), were developed from the measured CT data. These functions relate the AEC metric of the reference scanner, the GE LightSpeed 16 in this case, to the AEC metric of a secondary scanner.ResultsWhen translating protocols between different models of CT scanners (from the GE LightSpeed 16 reference scanner to the GE VCT system), the translation functions were linear. However, a power-law function was necessary to convert the AEC functions of the GE LightSpeed 16 reference scanner to the Siemens Definition AS+ secondary scanner, because of differences in the AEC functionality designed by these two companies.ConclusionsProtocol translation on the basis of quantitative metrics (volumetric CT dose index or measured image noise) is feasible. Protocol translation has a dependency on patient size, especially between the GE and Siemens systems. Translation schemes that preserve dose levels may not produce identical image quality.

Purpose: To determine the accuracy of CT number and calcium score of a kV‐independent technique based on an artificial 120 kV reconstruction, and its potential to reduce radiation dose. Methods: Anthropomorphic chest phantoms were scanned on a third‐generation dual‐source CT system equipped with the artificial 120 kV reconstruction. First, a phantom module containing a 20‐mm diameter hydroxyapatite (HA) insert was scanned inside the chest phantoms at different tube potentials (70–140 kV) to evaluate calcium CT number accuracy. Next, three small HA inserts (diameter/length = 5 mm) were inserted into a pork steak and scanned inside the phantoms to evaluate calcium score accuracy at different kVs. Finally, the same setup was scanned using automatic exposure control (AEC) at 120 kV, and then with automatic kV selection (auto‐kV). Phantoms were also scanned at 120 kV using a size‐dependent mA chart. CT numbers of soft tissue and calcium were measured from different kV images. Calcium score of each small HA insert was measured using commercial software. Results: The CT number difference from 120 kV was small with tube potentials from 90 to 140 kV for both soft tissue and calcium (maximal difference of 4/5 HU, respectively). Consistent calcium scores were obtained from images of different kVs compared to 120 kV, with a relative difference <8%. Auto‐kV provided a 25–34% dose reduction compared to AEC alone. Conclusion: A kV‐independent calcium scoring technique can produce artificial 120 kV images with consistent soft tissue and calcium CT numbers compared to standard 120 kV examinations. When coupled with auto‐kV, this technique can reduce radiation by 25–34% compared to that with AEC alone, while providing consistent calcium scores as that of standard 120 kV examinations. [ABSTRACT FROM AUTHOR]

When using automatic exposure control (AEC) systems in computed tomography (CT), miscalculation of tube current occurs when a patient is not aligned with the rotational center of the X-ray tube. A positioning compensation mechanism provides a corrective function when the patient is off-center; however, not all CT systems are equipped with this mechanism. AEC systems can broadly be divided into noise- and empirical-based. The authors studied empirical-based AEC systems to derive a compensation process to achieve an equivalent effect to that offered by the mechanism and to verify the accuracy of this process. A relational equation was derived to keep the tube current constant with variations in table height and quality reference milliampere-seconds (QRmAs), and this was adopted as the proposed compensation method. The radiation dose and image quality were evaluated for phantom imaging with and without the proposed compensation method using AEC and varying table heights. The output radiation dose and image quality were also evaluated for anthropomorphic chest phantom imaging to verify the compensatory effect of the proposed method. With the proposed compensation method, changes in the table height resulted in only small changes in the output radiation dose and noise level. Conversely, when the proposed compensation method was not used, changes in the table height resulted in widely varying output radiation dose and noise level. Imaging the anthropomorphic chest phantom with the proposed compensation method also yielded a stable output radiation dose. [ABSTRACT FROM AUTHOR]

Purpose: To assess the utility of the standard body CTDI phantom in characterizing the operation scheme of tube current modulation (TCM) systems in CT. Methods: The body CDTI phantom was used to characterize two TCM systems: TCM1 and TCM2, implemented in scanners from different vendors. The phantom was aligned at the gantry isocenter in two configurations. In configuration A, the facet planes of the phantom were parallel to the patient table, while in configuration B they were vertical to the patient table and parallel to the patient's long axis. Acquisitions were performed using the routine abdominal examination protocol. mA(z) profiles were recorded from images' DICOM header. The water equivalent diameter (dw) and oval ratio (OR) were calculated as a function of z‐axis location. Image noise was defined as the standard deviation (SD) of the mean Hounsfield unit value measured in a region of interest at the center of the phantom's image. Regression analysis was performed to modulated mA and SD vs dw and OR. The spatial concordance between the change in phantom size and change in mA (SCmA) was calculated as the percent difference in the slope of mA(z) change between the 1st and 2nd half of the phantom. The corresponding spatial concordance between the change in phantom size and change in image noise (SCnoise) was calculated. Results: Modulated mA(z) along the z‐axis did not substantially differentiate between configurations A and B. Correlation between ln(mA) and OR was found to be higher compared to correlation between ln(mA) and dw. SCmA was 48% for TCM1 and 33% for TCM2. The corresponding SCnoise was 29% for TCM1 and 16% for TCM2. Conclusion: Apart from routine CT dosimetry evaluations, the standard CTDI phantom positioned in configuration A or B may additionally be used by medical physicists to evaluate the performance of TCM operational characteristics. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess patient dose from whole-body computed tomography (CT) in association with patient size, automatic exposure control (AEC) and intravenous (IV) contrast agent.

Introduction: Values for the CTDIvol, which is displayed on scanner consoles, give doses relative to a phantom much larger than most Thai patients, and the CTDIvoldoes not take account of differences in patient size, which affect organ doses. Objective: The purpose of this study was to evaluate relationships for size specific dose estimate (SSDE) and volume weighted computed tomography (CT) dose index (CTDIvol) with patient size for CT scanners operating under automatic tube current modulation (ATCM). Methods: Retrospective data from 244 patients who had undergone abdomen and pelvis examination on GE and Siemens CT scanners were included in this study. The combination of anteroposterior (AP) and lateral dimensions at the level of the first lumbar vertebra (L1) was used to represent patient size. Image noise within the liver was measured, and values of the absorbed dose for organs covered by the primary beam such as the liver, stomach and kidney were calculated using methods described in the literature. Values of CTDIvolwere recorded and SSDE calculated according to the American Association of Physics in Medicine (AAPM) Report No.204. Linear regression models were used to evaluate the relationship between SSDE, CTDIvol, image noise and patient size. Results: SSDE is 20%-50% larger than the CTDIvol, with values for larger patients being more representative. Both the CTDIvoland image noise decreased with patient size for Siemens scanners, but the decline in SSDE was less significant. For the GE scanner, the CTDIvolwas a factor of 3-4 lower in small patients compared to larger ones, while the SSDE only decreased by a factor of two. Noise actually decreased slightly with patient size. Conclusion: Values of SSDE were similar to the doses calculated for the liver, stomach and kidney, which are covered by the primary beam, confirming that it provides a good estimate of organ-absorbed dose.

Cone-beam computed tomography (CBCT) is a widely used imaging technique in interventional radiology. Although CBCT offers great advantages in terms of improving comprehension of complex angioarchitectures and guiding therapeutic decisions, its additional degree of radiation exposure has also aroused considerable concern. In this study, we aimed to assess radiation exposure and its influential factors in patients undergoing CBCT scans of the head and abdomen during interventional procedures. A total of 752 patients were included in this retrospective study. Dose area product (DAP) and reference air kerma (RAK) were used as measures of patient dose. The results showed that the median values of DAP were 53.8 (50.5-64.4) Gy⋅cm 2 for head CBCT and 47.4 (39.6-54.3) Gy⋅cm 2 for that of the abdomen. Male gender and body mass index (BMI) were characterized by increased DAP and RAK values in both head and abdominal CBCT scans. Larger FOV size was associated with a higher DAP but a lower RAK value, especially in head CBCT scans. Exposure parameters under automatic exposure control (AEC) also varied according to patient BMI and gender. In conclusion, the patients received slightly higher radiation doses from head CBCT scans than from those applied to the abdomen. BMI, gender, and FOV size were the key factors that influenced the radiation dose administered to the patients during CBCT scans. Our results may help to define and minimize patients' exposure to radiation.

This study proposes to adjust the sensitivity of automatic exposure control (AEC) for achieving consistent image quality over a range of subject thicknesses in abdominal radiography simulations. The relation between image quality and subject thickness was investigated using a digital radiography system with 10-, 15-, 20-, and 25-cm-thick acrylic phantom. Simple pixel signal-to-noise ratio (SNR) was measured to check the default AEC accuracy for each thickness, and image quality was evaluated using the signal-difference-to-noise ratio (SDNR) with an additional acrylic plate and bone-equivalent material. Based on the figure of merit theory, dose ratios to obtain constant image quality regardless of the subject thickness were calculated from SDNR results. The AEC setup was manually modified using this dose ratio, and visibility was examined using a CDRAD 2.0 contrast-detail analysis phantom. Moreover, the entrance surface dose (ESD) was estimated as an index of exposure dose using exposure parameters. The default AEC setup provided a constant simple pixel SNR for each subject thickness with a high accuracy. SDNRs decreased with an increase in the subject thickness. The calculated dose ratios relative to the results for 20 cm thickness were 0.424, 0.647, and 1.43 for 10, 15 and 25 cm, respectively, and a > 25% decrease in ESD was observed for smaller patients. CDRAD analysis using the modified AEC setup showed almost identical visibility for each thickness. Adjusting the sensitivity of AEC according to subject thickness can contribute toward the optimization of the exposure condition. [ABSTRACT FROM AUTHOR]

Recent advances in medical imaging technologies have led to the increased use of automatic exposure control (AEC) in digital X-ray equipment. This study is an attempt to measure the dose of exposure based on AEC use and to evaluate the image quality in chest radiography where AEC is used most frequently. We measured the dose of radiation using three (3) units of digital radiation generators for diagnosis in conditions that are frequently used in chest radiography (110kVp, 115kVp, 120kVp, 125kVp). We placed the dosimeter in front of a chest phantom while varying the distance of FID to 110 cm, 140 cm, and 180 cm depending on whether or not AEC was used. The CNR and SNR of the images obtained by setting the lung to signal, 5 regions of Interest (ROIs), and 5 places of media sternum to noise, were measured using the Image J Program. To determine the dose difference based on AEC use, we conducted a t-test, which revealed a significant difference. When AEC was used at FID 110 cm, a high dose of 11.98% appeared. When AEC was used at FID 140cm, a high dose of 8.64% appeared. When AEC was used at FID 180 cm, a high dose of 6.74% appeared. In the t-test for the difference in CNR and SNR based on AEC use, no significant difference was detected. As the distance of FID increased, high values of CNR and SNR were measured.The results of this study show that there is no difference between CNR and SNR regardless of the use of AEC, and the dose was high when using AEC. Therefore, chest X - ray examination should not be based on AEC only. Under appropriate radiological settings, it is possible to reduce unnecessary radiation exposure to the patient. [ABSTRACT FROM AUTHOR]

Abstract In an effort to reduce radiation exposure from computed tomography (CT), practitioners and facilities need to monitor radiation exposure while delivering high-quality diagnostic examinations. One way to minimize a patient's exposure to radiation from CT is the use of an automatic exposure control device. Current research is focusing on these devices and their actual benefits to patients. To assess the effectiveness of such a device, analysis of radiation doses per CT examination must occur. Machine-specific dose-length product and/or CT dose index are the only indicators of specific dose levels. This project compares current levels of radiation exposure to patients undergoing CT scans of the head versus the national levels as evaluated by the Nationwide Evaluation of X-ray Trends program. [ABSTRACT FROM AUTHOR]