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PURPOSE: To determine the suitability of a quality assurance (QA) program based on the American College of Radiology's (ACR) CT quality control (QC) manual to fully evaluate the unique capabilities of a clinical photon-counting-detector (PCD) CT system. METHODS: A daily QA program was established to evaluate CT number accuracy and artifacts for both standard and ultra-high-resolution (UHR) scan modes. A complete system performance evaluation was conducted in accordance with the ACR CT QC manual by scanning the CT Accreditation Phantom with routine clinical protocols and reconstructing low-energy-threshold (T3D) and virtual monoenergetic images (VMIs) between 40 and 120 keV. Spatial resolution was evaluated by computing the modulation transfer function (MTF) for the UHR mode, and multi-energy performance was evaluated by scanning a body phantom containing four iodine inserts with concentrations between 2 and 15 mg I/cc. RESULTS: The daily QA program identified instances when the detector needed recalibration or replacement. CT number accuracy was impacted by image type: CT numbers at 70 keV VMI were within the acceptable range (defined for 120 kV). Other keV VMIs and the T3D reconstruction had at least one insert with CT number outside the acceptable range. The limiting resolution was nearly 40 lp/cm based on MTF measurements, which far exceeds the 12 lp/cm maximum capability of the ACR phantom. The CT numbers in the iodine inserts were accurate on all VMIs (3.8% average percentage error), while the iodine concentrations had an average root mean squared error of 0.3 mg I/cc. CONCLUSION: Protocols and parameters must be properly selected on PCD-CT to meet current accreditation requirements with the ACR CT phantom. Use of the 70 keV VMI allowed passing all tests prescribed in the ACR CT manual. Additional evaluations such an MTF measurement and multi-energy phantom scans are also recommended to comprehensively evaluate PCD-CT scanner performance.

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As deep-learning-based denoising and reconstruction methods are gaining more popularity in clinical CT, it is of vital importance that these new algorithms undergo rigorous and objective image quality assessment beyond traditional metrics to ensure diagnostic information is not sacrificed. Channelized Hotelling observer (CHO), which has been shown to be well correlated with human observer performance in many clinical CT tasks, has a great potential to become the method of choice for objective image quality assessment for these non-linear methods. However, practical use of CHO beyond research labs have been quite limited, mostly due to the strict requirement on a large number of repeated scans to ensure sufficient accuracy and precision in CHO computation and the lack of efficient and widely acceptable phantom-based method. In our previous work, we developed an efficient CHO model observer for accurate and precise measurement of low-contrast detectability with only 1-3 repeated scans on the most widely used ACR accreditation phantom. In this work, we applied this optimized CHO model observer to evaluating the low-contrast detectability of a deep learning-based reconstruction (DLIR) equipped on a GE Revolution scanner. The commercially available DLIR reconstruction method showed consistent increase in low-contrast detectability over the FBP and the IR method at routine dose levels, which suggests potential dose reduction to the FBP reconstruction by up to 27.5%.

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Background The size-specific dose estimate (SSDE) is a patient-focused CT dose metric. However, published size-dependent conversion factors (fsize) used to calculate SSDE were determined primarily by using phantoms; only eight to 15 patient data sets were used, all at 120 kV. Purpose To determine the effect of different tube potentials on the water-equivalent diameter (WED) and SSDE for patient CT scans of the head, chest, and abdomen. Materials and Methods This retrospective study used 250 noncontrast CT scans acquired between March 2013 and June 2017. Bony structures were segmented, and their CT numbers were modified to reflect bone attenuation at 70, 90, 110, 130, and 150 kV. Soft-tissue CT numbers were unchanged because of negligible energy dependence. fsize was measured in anthropomorphic phantoms for each tube potential and fit to an exponential function. WED and SSDE were determined for each patient at all tube potentials, regression analysis was performed relative to the WED and SSDE at 120 kV, and mean differences relative to 120 kV were calculated. Results In 250 patients (median age, 21.5 years; interquartile range, 44 years; 130 women), WED for all tube potentials was linearly related to the WED at 120 kV in all body regions (R2 = 0.995-1.000). The effect of tube potential on WED was negligible for torso examinations (Cohen d < 0.05). In the head, a medium effect size was observed at 70 kV; however, the mean absolute difference in WED was small (-0.49 cm ± 0.08 [standard deviation]; P < .001). For commonly used combinations of tube potential and patient size, the mean differences in SSDE at alternative tube potentials relative to SSDE at 120 kV were less than 5%. Conclusion At noncontrast CT, published size-dependent conversion factors accurately determined size-specific dose estimates on 250 patient scans at five tube potentials other than 120 kV. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Boone in this issue.

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CONTEXT: Hypoparathyroidism is characterized by low serum calcium, increased serum phosphorus, and inappropriately low or decreased serum parathyroid hormone, which may be associated with soft tissue calcification in the basal ganglia of the brain. OBJECTIVE: To assess the prevalence and factors involved in the pathophysiology of basal ganglia calcification (BGC) in the brain in chronic hypoparathyroidism and to evaluate proposed pathophysiologic mechanisms. DESIGN: Case-control study with retrospective review of medical records over 20 years. SETTING: Single academic medical center. PATIENTS: 142 patients with chronic hypoparathyroidism and computed tomography (CT) head scans followed between January 1, 2000 and July 9, 2020, and 426 age- and sex-matched controls with CT head scans over the same interval. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Demographic, biochemical, and CT head imaging findings, with semiquantitative assessment of volumetric BGC. RESULTS: The study found that 25.4% of 142 patients followed for a median of 17 years after diagnosis of chronic hypoparathyroidism had BGC, which developed at a younger age than in controls. BGC was 5.1-fold more common in nonsurgical patients and less common in postsurgical patients. Low serum calcium and low calcium/phosphate ratio correlated with BGC. Neither serum phosphorus nor calcium × phosphate product predicted BGC. Lower serum calcium was associated with greater volume of BGC. The extent of BGC varied widely, with nonsurgical patients generally having a greater volume and distribution of calcification. CONCLUSIONS: BGC is associated with low serum calcium and low serum calcium/phosphate ratio, which may be related to severity of the disease, its etiology, or duration of treatment.

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PURPOSE: The aim of this study was to demonstrate that a low helical pitch causes increased photon starvation artifacts at ultra-low-dose CT. METHODS: A cylindrical water phantom with a diameter of 30 cm was scanned on two different generation CT scanners: a 64-slice scanner (Sensation 64, Siemens Healthcare) and a 192-slice scanner (Somatom Force, Siemens Healthcare) at multiple effective mAs levels (mAs/pitch = 200, 100, 50, 25, and 12). The corresponding CTDIvol values were 4.1, 2.0, 1.0, 0.5 mGy, on the 64-slice scanner and 3.8, 1.9, 1.0, 0.5 mGy on the 192-slice scanner, for the selected effective mAs values. For each dose setting, the scan was repeated at four helical pitches: 1.2, 0.9, 0.6, and the lowest achievable pitch on each scanner. The tube current was automatically adjusted by the scanner so that the effective mAs, and thus CTDIvol , were kept the same for different pitches. All CT data sets were reconstructed with a slice thickness of 3mm and a medium smooth kernel. Images acquired at the same dose level but different helical pitches were visually inspected to assess photon starvation artifacts and noise levels. RESULTS: At the same radiation dose, image noise increased with the decreasing helical pitch. The increase was more severe on the old-generation 64-slice scanner. Photon starvation artifacts were evident at 200 effective mAs on the 64-slice scanner at 80 kV. On the 192-slice scanner there was no visible photon starvation artifacts at both 200 and 50 effective mAs (CTDIvol  = 4.1 mGy and 1.0 mGy, respectively); nor was there a visible impact from the lower helical pitch. Only when the dose was lowered to be extremely low (~0.26 mGy, achievable at 70 kV), did photon starvation artifacts become evident. CONCLUSIONS: A low helical pitch may increase image noise and photon starvation artifacts compared to a higher pitch for the same dose level, particularly at ultra-low dose CT.

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OBJECTIVE: The purpose of this study was to quantify the dose reduction resulting from the use of lead aprons for pediatric chest CT as a function of the distance between the apron and the bottom of the scan range. MATERIALS AND METHODS: Semianthropomorphic phantoms of the head, abdomen, and pelvis were placed adjacent to a chest phantom to mimic the habitus of a 5-year-old child. A chest CT scan was performed, and a point dosimeter was used to measure the radiation dose at points within and outside the scan range. A lead apron was placed 1, 5, and 10 cm from the bottom of the CT scan range, and the measurements were repeated. The weighted-average dose was calculated for each measurement position. RESULTS: The weighted-average dose within and outside the scan range was 1.7 and 0.067 mGy, respectively. The mean (percentage) dose reduction outside the scan range resulting from use of the lead apron was 0.013 mGy (19.1%), 0.007 mGy (10.1%), and 0.003 mGy (4.3%) when the lead apron was placed at distances of 1, 5, and 10 cm from the bottom of the scan range, respectively. The corresponding total percentage dose reduction (including the dose from the primary scan) was 0.7%, 0.4%, and 0.2%, respectively. CONCLUSION: As the lead apron was placed farther from the scan range, the amount of dose reduction diminished. The reduction in dose was extremely small compared with the overall dose from the examination. The small dose reduction gained from the use of lead shielding over the abdomen and pelvis during chest CT examination of pediatric patients may not outweigh the associated potential risks of artifacts and infection.

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BACKGROUND: The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis. RESULTS: A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm. CONCLUSIONS: A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications.

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Protocol review is important to decrease the risk of patient injury and increase the consistency of CT image quality. A large volume of CT protocols makes manual review labor-intensive, error-prone, and costly. To address these challenges, we have developed a software system for automatically managing and monitoring CT proto-cols on a frequent basis. This article describes our experiences in the implementation and evaluation of this protocol monitoring system. In particular, we discuss various strategies for addressing each of the steps in our protocol-monitoring workflow, which are: maintaining an accurate set of master protocols, retrieving protocols from the scanners, comparing scanner protocols to master protocols, reviewing flagged differences between the scanner and master protocols, and updating the scanner and/or master protocols. In our initial evaluation focusing only on abdo-men and pelvis protocols, we detected 309 modified protocols in a 24-week trial period. About one-quarter of these modified protocols were determined to contain inappropriate (i.e., erroneous) protocol parameter modifications that needed to be corrected on the scanner. The most frequently affected parameter was the series description, which was inappropriately modified 47 times. Two inappropriate modifications were made to the tube current, which is particularly important to flag as this parameter impacts both radiation dose and image quality. The CT protocol changes detected in this work provide strong motivation for the use of an automated CT protocol quality control system to ensure protocol accuracy and consistency.

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The purpose of this study was to use three-dimensional (3-D) printing techniques to construct liver and brain phantoms having realistic pathologies, anatomic structures, and heterogeneous backgrounds. Patient liver and head computed tomography (CT) images were segmented into tissue, vessels, liver lesion, white and gray matter, and cerebrospinal fluid (CSF). Stereolithography files of each object were created and imported into a commercial 3-D printer. Printing materials were assigned to each object after test scans, which showed that the printing materials had CT numbers ranging from 70 to 121 HU at 120 kV. Printed phantoms were scanned on a CT scanner and images were evaluated. CT images of the liver phantom had measured CT numbers of 77.8 and 96.6 HU for the lesion and background, and 137.5 to 428.4 HU for the vessels channels, which were filled with iodine solutions. The difference in CT numbers between lesions and background (18.8 HU) was representative of the low-contrast values needed for optimization tasks. The liver phantom background was evaluated with Haralick features and showed similar texture between patient and phantom images. CT images of the brain phantom had CT numbers of 125, 134, and 108 HU for white matter, gray matter, and CSF, respectively. The CT number differences were similar to those in patient images.

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The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for IR and needs to be validated with human detection performance. On the other hand, the spatial domain model observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial domain model observer with both FBP and IR images, using human detection performance as the gold standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice (2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening model observer and a spatial domain channelized Hotelling observer. The performance of these two mode observers was compared in terms of how well they correlated with human observer performance. Our results demonstrated that the spatial domain model observer correlated well with human observers across various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with human observers using FBP images, but overestimated the detection performance using IR images.

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Channelized Hotelling observer (CHO) has been validated against human observers for detection/classification tasks in clinical CT and shows encouraging correlations. However, the goodness of correlations depends on the number of repeated scans used in CHO to estimate the template and covariance matrices. The purpose of this study is to investigate how the number of repeated scans affects the CHO performance in predicting human observers. A phantom containing 21 low-contrast objects (3 contrast levels and 7 sizes) was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. Images were reconstructed using a filtered-backprojection kernel and a commercial iterative reconstruction method. For each dose level and reconstruction setting, the low-contrast detectability, quantified with the area under receiver operating characteristic curve (Az), was calculated using a previously validated CHO. To determine the dependency of CHO performance on the number of repeated scans, the Az value was calculated for each object and dose/reconstruction setting using all 100 repeated scans. The Az values were also calculated using randomly selected subsets of the scans (from 10 to 90 scans with an increment of 10 scans). Using the Az from the 100 scans as the reference, the accuracy of Az from a smaller number of scans was determined. The minimum necessary number of scans was subsequently derived. For the studied signal-known-exactly detection task, results demonstrated that, the minimal number of scans required to accurately predict human observer performance depends on dose level, object size and contrast level, and channel filters.

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PURPOSE: The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. METHODS: A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDIvol = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. RESULTS: The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF50% value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF50% value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. CONCLUSIONS: A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.

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The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered backprojection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered backprojection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.

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OBJECTIVE: To investigate whether the integrated circuit (IC) detector results in reduced noise in computed tomography (CT) colonography (CTC). METHODS: Three hundred sixty-six consecutive patients underwent clinically indicated CTC using the same CT scanner system, except for a difference in CT detectors (IC or conventional). Image noise, patient size, and scanner radiation output (volume CT dose index) were quantitatively compared between patient cohorts using each detector system, with separate comparisons for the abdomen and pelvis. RESULTS: For the abdomen and pelvis, despite significantly larger patient sizes in the IC detector cohort (both P < 0.001), image noise was significantly lower (both P < 0.001), whereas volume CT dose index was unchanged (both P > 0.18). Based on the observed image noise reduction, radiation dose could alternatively be reduced by approximately 20% to result in similar levels of image noise. CONCLUSION: Computed tomography colonography images acquired using the IC detector had significantly lower noise than images acquired using the conventional detector. This noise reduction can permit further radiation dose reduction in CTC.

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PURPOSE: To assess the z-axis resolution improvement and dose reduction potential achieved using a z-axis deconvolution technique with iterative reconstruction (IR) relative to filtered backprojection (FBP) images created with the use of a z-axis comb filter. METHODS: Each of three phantoms were scanned with two different acquisition modes: (1) an ultrahigh resolution (UHR) scan mode that uses a comb filter in the fan angle direction to increase in-plane spatial resolution and (2) a z-axis ultrahigh spatial resolution (zUHR) scan mode that uses comb filters in both the fan and cone angle directions to improve both in-plane and z-axis spatial resolution. All other scanning parameters were identical. First, the ACR CT Accreditation phantom, rotated by 90° so that the high-contrast spatial resolution targets were parallel to the coronal plane, was scanned to assess limiting spatial resolution and image noise. Second, section sensitivity profiles (SSPs) were measured using a copper foil embedded in an acrylic cylinder and the full-width-at-half-maximum (FWHM) and full-width-at-tenth-maximum (FWTM) of the SSPs were calculated. Third, an anthropomorphic head phantom containing a human skull was scanned to assess clinical acceptability for imaging of the temporal bone. For each scan, FBP images were reconstructed for the zUHR scan using the narrowest image thickness available. For the CT accreditation phantom, zUHR images were also reconstructed using an IR algorithm (SAFIRE, Siemens Healthcare, Forchheim, Germany) to assess the influence of the IR algorithm on image noise. A z-axis deconvolution technique combined with the IR algorithm was used to reconstruct images at the narrowest image thickness possible from the UHR scan data. Images of the ACR and head phantoms were reformatted into the coronal plane. The head phantom images were evaluated by a neuroradiologist to assess acceptability for use in patients undergoing clinically indicated CT imaging of the temporal bone. RESULTS: The limiting spatial resolution was 12 lp/cm for the FBP-zUHR images and the IR-UHR images, although visual assessment indicated a slight improvement for the IR-UHR images. Image noise was 213.0, 181.8, and 153.5 for the FBP-zUHR, IR-zUHR, and IR-UHR images, respectively. While the FWHM was essentially the same for the FBP-zUHR and IR-UHR images, the FWTM of the IR-UHR images was almost 50% smaller compared to the FBP-zUHR images (0.83 vs 1.25 mm, respectively). Images of the anthropomorphic head phantom were judged to be of higher quality for the IR-UHR images compared to the FBP-zUHR images. CONCLUSIONS: With use of a z-axis deconvolution technique, z-axis spatial resolution was improved for scans acquired using a comb filter only in the fan angle direction relative to FBP images acquired with a comb filter in both the fan and cone angle directions. By avoiding use of the comb filter in the cone angle direction and use of an IR algorithm, image noise was substantially reduced for the same scanner output (CTDIvol). Thus, overall image quality (spatial resolution and image noise) can be maintained relative to the FBP-zUHR technique at a lower radiation dose.

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PURPOSE: To determine the precision and accuracy of CTDI(100) measurements made using commercially available optically stimulated luminescent (OSL) dosimeters (Landaur, Inc.) as beam width, tube potential, and attenuating material were varied. METHODS: One hundred forty OSL dosimeters were individually exposed to a single axial CT scan, either in air, a 16-cm (head), or 32-cm (body) CTDI phantom at both center and peripheral positions. Scans were performed using nominal total beam widths of 3.6, 6, 19.2, and 28.8 mm at 120 kV and 28.8 mm at 80 kV. Five measurements were made for each of 28 parameter combinations. Measurements were made under the same conditions using a 100-mm long CTDI ion chamber. Exposed OSL dosimeters were returned to the manufacturer, who reported dose to air (in mGy) as a function of distance along the probe, integrated dose, and CTDI(100). RESULTS: The mean precision averaged over 28 datasets containing five measurements each was 1.4% ± 0.6%, range = 0.6%-2.7% for OSL and 0.08% ± 0.06%, range = 0.02%-0.3% for ion chamber. The root mean square (RMS) percent differences between OSL and ion chamber CTDI(100) values were 13.8%, 6.4%, and 8.7% for in-air, head, and body measurements, respectively, with an overall RMS percent difference of 10.1%. OSL underestimated CTDI(100) relative to the ion chamber 21∕28 times (75%). After manual correction of the 80 kV measurements, the RMS percent differences between OSL and ion chamber measurements were 9.9% and 10.0% for 80 and 120 kV, respectively. CONCLUSIONS: Measurements of CTDI(100) with commercially available CT OSL dosimeters had a percent standard deviation of 1.4%. After energy-dependent correction factors were applied, the RMS percent difference in the measured CTDI(100) values was about 10%, with a tendency of OSL to underestimate CTDI relative to the ion chamber. Unlike ion chamber methods, however, OSL dosimeters allow measurement of the radiation dose profile.

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OBJECTIVE: The purpose of this study was to determine typical radiation dose levels to patients undergoing CT-guided interventional procedures. MATERIALS AND METHODS: A total of 571 patients undergoing CT interventional procedures were included in this retrospective data analysis study. Enrolled patients underwent one of five procedures: cryoablation, aspiration, biopsy, drain, or injection. With each procedure, two scan modes were used, either intermittent (no table increment) or helical mode. Skin dose was estimated from the volumetric CT dose index (CTDI(vol)) and phantom measurements. Effective dose was calculated by multiplying dose-length product (DLP) and conversion factor (k factor) for helical mode, and using Monte Carlo organ dose coefficients for intermittent mode. RESULTS: The mean (± SD) skin doses were 728 ± 382, 130 ± 104, 128 ± 81, 152 ± 105, and 195 ± 147 mGy, and the mean effective doses were 119.7 ± 50.3, 20.1 ± 11.0, 13.8 ± 9.2, 25.3 ± 15.4, and 9.1 ± 5.5 mSv for each of the five procedures, respectively. The maximum skin dose was 1.95 Gy. The mean effective dose across all procedure types was 24.1 mSv, with 2.3 mSv from intermittent scans and 21.8 mSv from helical scans. CONCLUSION: Substantial dose differences were observed among the five procedures. The risk of deterministic effects appears to be very low, because the maximum observed skin dose did not exceed the threshold for transient skin erythema (2 Gy). The average risk of stochastic effects was comparable to that of 1-10 abdomen and pelvis CT examinations. Although the intermittent mode can contribute substantially to skin dose, it contributes minimally to the effective dose because of the much shorter scan range used.

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OBJECTIVE: The purpose of our study was to evaluate the dose and image quality performance of a dedicated cone-beam CT (CBCT) scanner in comparison with an MDCT scanner. MATERIALS AND METHODS: The conventional dose metric, CT dose index (CTDI), is no longer applicable to CBCT scanners. We propose to use two dose metrics, the volume average dose and the mid plane average dose, to quantify the dose performance in a circular cone-beam scan. Under the condition of equal mid plane average dose, we evaluated the image quality of a CBCT scanner and an MDCT scanner, including high-contrast spatial resolution, low-contrast spatial resolution, noise level, CT number uniformity, and CT number accuracy. RESULTS: For the sinus scanning protocol, the CBCT system had comparable high-contrast resolution and inferior low-contrast resolution to those obtained with the MDCT scanner when the doses were matched (mid plane average dose 9.2 mGy). The CT number uniformity and accuracy were worse on the CBCT scanner. The image artifacts caused by beam hardening and scattering were also much more severe on the CBCT system. CONCLUSION: With a matched radiation dose, the CBCT system for sinus study has comparable high-contrast resolution and inferior low-contrast resolution relative to the MDCT scanner. Because of the more severe image artifacts on the CBCT system due to the small field of view and the lack of accurate scatter and beam-hardening correction, the utility of the CBCT system for diagnostic tasks related to soft tissue should be carefully assessed.

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In x-ray computed tomography (CT), the most common parameter used to estimate and minimize patient dose is the CT dose index (CTDI). The CTDI is a volume-averaged measure that is used in situations where the table is incremented in conjunction with the tube rotation. Variants of the CTDI correct for averaging across the field of view and for adjacent beam overlaps or gaps. CTDI is usually measured with a pencil-shaped ionization chamber, although methods have been developed that use alternative detectors, including an optically stimulated luminescence probe and a solid-state real-time dosimeter. Because the CTDI represents an averaged dose to a homogeneous cylindrical phantom, the measurements are only an approximation of the patient dose. Furthermore, dose from interventional or perfusion CT, in which the table remains stationary between multiple scans, is best evaluated with point dose measurements made with small detectors. CTDI and point dose values are nearly the same for measurement of surface dose from spiral CT. However, for measurement of surface dose from perfusion CT, the dose is overestimated by a factor of two or more with CTDI values in comparison with point dose values. Both CTDI and point dose measurement are valuable for evaluating CT scanner output and estimating patient dose.

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A study was conducted to investigate how operator exposure in interventional radiology is affected by various common fluoroscopic imaging conditions. Stray radiation levels surrounding the imaging chain of a C-arm angiographic system were measured with an anthropomorphic abdomen phantom under different imaging conditions, and isodose curves were constructed. Operator exposure was shown to increase with patient dose-area product as the imaging field of view (FOV) is changed, with the highest scatter levels occurring with an intermediate-sized FOV. Use of copper spectral beam filtration was found to result in decreased operator exposure, whereas use of wedge-shaped equalization filters was found to increase exposure. The effect of increasing patient abdomen thickness was simulated by surrounding the phantom with plastic bolus material. Increasing the thickness by 5 cm resulted in a doubling of exposure at the operator's waist. Exposure to the operator's upper body was significantly reduced when the FOV was positioned on the far side of the patient. Operator exposure can be maintained at an acceptable level by taking these variables into consideration and incorporating the suggested dose reduction techniques into routine practice to the greatest extent possible.

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