U.S. Diagnostic Reference Levels and Achievable Doses for 10 Pediatric CT Examinations.

Background Diagnostic reference levels (DRLs) and achievable doses (ADs) were developed for the 10 most commonly performed pediatric CT examinations in the United States using the American College of Radiology Dose Index Registry. Purpose To develop robust, current, national DRLs and ADs for the 10 most commonly performed pediatric CT examinations as a function of patient age and size. Materials and Methods Data on 10 pediatric (ie, patients aged 18 years and younger) CT examinations performed between 2016 and 2020 at 1625 facilities were analyzed. For head and neck examinations, dose indexes were analyzed based on patient age; for body examinations, dose indexes were analyzed for patient age and effective diameter. Data from 1 543 535 examinations provided medians for AD and 75th percentiles for DRLs for volume CT dose index (CTDIvol), dose-length product (DLP), and size-specific dose estimate (SSDE). Results Of all facilities analyzed, 66% of the facilities (1068 of 1625) were community hospitals, 16% (264 of 1625) were freestanding centers, 9.5% (154 of 1625) were academic facilities, and 3.5% (57 of 1625) were dedicated children's hospitals. Fifty-two percent of the patients (798 577 of 1 543 535) were boys, and 48% (744 958 of 1 543 535) were girls. The median age of patients was 14 years (boys, 13 years; girls, 15 years). The head was the most frequent anatomy examined with CT (876 655 of 1 543 535 examinations [57%]). For head without contrast material CT examinations, the age-based CTDIvol AD ranged from 19 to 46 mGy, and DRL ranged from 23 to 55 mGy, with both AD and DRL increasing with age. For body examinations, DRLs and ADs for size-based CTDIvol, SSDE, and DLP increased consistently with the patient's effective diameter. Conclusion Diagnostic reference levels and achievable doses as a function of patient age and effective diameter were developed for the 10 most commonly performed CT pediatric examinations using American College of Radiology Dose Index Registry data. These benchmarks can guide CT facilities in adjusting pediatric CT protocols and resultant doses for their patients. © RSNA, 2021 An earlier incorrect version appeared online. This article was corrected on October 29, 2021.

Improved Dose Estimates for Fluoroscopically Guided Lumbar Epidural Injections.

OBJECTIVE: The goal of the study was to determine the potential impact of system inaccuracies and table attenuation on fluoroscope-reported dose values. DESIGN: An Institutional Review Board-approved study was conducted to collect detailed acquisition and patient exposure data for fluoroscopy-guided lumbar epidural injections. BACKGROUND: System-reported dosimetry values, especially the air Kinetic Energy Released per unit MAss and dose-area product metrics, are routinely used for estimating the radiation burden to patients undergoing fluoroscopy-guided procedures. However, these metrics do not account for other factors, such as acquisition geometry, where the table may attenuate a substantial fraction of the x-ray intensity, and system dosimetry inaccuracies, which are only required to be accurate within ±35%. METHODS: Acquisition data from 46 patients undergoing fluoroscopy-guided lumbar epidural injections were collected to better estimate the true incident dose-area product. Gantry angles, x-ray technique factors, and field sizes were collected to characterize each procedure. Additionally, the fluoroscope dosimetry accuracy and table attenuation properties were evaluated as a function of kVp to generate the correction factors necessary for accurate dosimetry estimates. RESULTS: The system-reported values overestimated the total patient entrance dose-area product by an average of 34% (13-44%). Errors may be substantially higher for systems with less accurate fluoroscopes or more anterior-posterior projections. Correcting system-reported dosimetry values for systematic inaccuracies and variability can substantially improve fluoroscopic dose values. CONCLUSIONS: Including corrections for system output inaccuracies and acquisition factors such as table attenuation is necessary for any reliable assessment of radiation burden to patients associated with fluoroscopy-guided procedures.

Medical physics 3.0 versus 1.0: A case study in digital radiography quality control.

PURPOSE: The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail. METHODS: MP1.0 tests included traditional annual tests plus the manufacturer's automated Quality Assurance Procedures (QAP) of a DR system before and after a radiologist's image quality (IQ) complaint repeated after service intervention. Further analysis was conducted using nontraditional MP3.0 tests including longitudinal review of QAP results from a 15-yr database, exposure-dependent signal-to-noise (SNR2 ), clinical IQ, and correlation with the institutional service database. Clinical images were analyzed in terms of IQ metrics by the Duke University Clinical Imaging Physics Group using previously validated software. RESULTS: Traditional metrics did not indicate discrepant system performance at any time. QAP reported a decrease in contrast-to-noise ratio (CNR) after detector replacement, but remained above the manufacturer's action limit. Clinical images showed increased lung noise (Ln), mediastinum noise (Mn), and subdiaphragm-lung contrast (SLc), and decreased lung gray level (Lgl) following detector replacement. After detector recalibration, QAP CNR improved, but did not return to previous levels. Lgl and SLc no longer significantly differed from before detector recalibration; however, Ln and Mn remained significantly different. Exposure-dependent SNR2 documented the detector operating within acceptable limits 9 yr previously but subsequently becoming miscalibrated sometime before four prior annual tests. Service records revealed catastrophic failure of the computer containing the original detector calibration from 11 yr prior. It is likely that the incorrect calibration backup file was uploaded at that time. CONCLUSIONS: MP1.0 tests failed to detect substandard system performance, but MP3.0 methods determined the root cause of the problem. MP3.0 exploits the wealth of data with more sensitive performance indicators. Data analytics are powerful tools whose proper application could facilitate early intervention in degraded system performance.

Automated quality control assessment of clinical chest images.

PURPOSE: The purpose of this study was to determine whether a proposed suite of objective image quality metrics for digital chest radiographs is useful for monitoring image quality in a clinical setting unique from the one where the metrics were developed. METHODS: Seventeen gridless AP chest radiographs from a GE Optima portable digital radiography (DR) unit ("sub-standard" images; Group 2) and 17 digital PA chest radiographs ("standard-of-care" images; Group 1) and 15 gridless (non-routine) PA chest radiographs (images with a gross technical error; Group 3) from a Discovery DR unit were chosen for analysis. Group 2 images were acquired with a lower kVp (100 vs 125) and shorter source-to-image distance (127 cm vs 183 cm) and were expected to have lower quality than Group 1 images. Group 3 images were expected to have degraded contrast vs Group 1 images. Images were anonymized and securely transferred to the Duke University Clinical Imaging Physics Group for analysis using software described and validated previously. Individual image quality was reported in terms of lung gray level, lung detail, lung noise, rib-lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. Metrics were compared across groups. To improve precision of means and confidence intervals for routine exams, an additional 66 PA images were acquired, processed, and pooled with Group 1. Three observer studies were conducted to assess whether humans were able to identify images classified by the algorithm as abnormal. RESULTS: Metrics agreed with published Quality Consistency Ranges with three exceptions: higher lung gray level, lower rib-lung contrast, and lower subdiaphragm-lung contrast. Higher (stored) bit depth (14 vs 12) accounted for higher lung gray level values in our images. Values were most internally consistent for Group 1. The most sensitive metric for distinguishing between groups was mediastinum noise, followed closely by lung noise. The least sensitive metrics were mediastinum detail and rib-lung contrast. The algorithm was more sensitive than human observers at detecting suboptimal diagnostic quality images. CONCLUSIONS: The software appears promising for objectively and automatically identifying suboptimal images in a clinical imaging operation. The results can be used to establish local quality consistency ranges and action limits per facility preferences.

How does c-view image quality compare with conventional 2D FFDM?

PURPOSE: The FDA approved the use of digital breast tomosynthesis (DBT) in 2011 as an adjunct to 2D full field digital mammography (FFDM) with the constraint that all DBT acquisitions must be paired with a 2D image to assure adequate interpretative information is provided. Recently manufacturers have developed methods to provide a synthesized 2D image generated from the DBT data with the hope of sparing patients the radiation exposure from the FFDM acquisition. While this much needed alternative effectively reduces the total radiation burden, differences in image quality must also be considered. The goal of this study was to compare the intrinsic image quality of synthesized 2D c-view and 2D FFDM images in terms of resolution, contrast, and noise. METHODS: Two phantoms were utilized in this study: the American College of Radiology mammography accreditation phantom (ACR phantom) and a novel 3D printed anthropomorphic breast phantom. Both phantoms were imaged using a Hologic Selenia Dimensions 3D system. Analysis of the ACR phantom includes both visual inspection and objective automated analysis using in-house software. Analysis of the 3D anthropomorphic phantom includes visual assessment of resolution and Fourier analysis of the noise. RESULTS: Using ACR-defined scoring criteria for the ACR phantom, the FFDM images scored statistically higher than c-view according to both the average observer and automated scores. In addition, between 50% and 70% of c-view images failed to meet the nominal minimum ACR accreditation requirements-primarily due to fiber breaks. Software analysis demonstrated that c-view provided enhanced visualization of medium and large microcalcification objects; however, the benefits diminished for smaller high contrast objects and all low contrast objects. Visual analysis of the anthropomorphic phantom showed a measureable loss of resolution in the c-view image (11 lp/mm FFDM, 5 lp/mm c-view) and loss in detection of small microcalcification objects. Spectral analysis of the anthropomorphic phantom showed higher total noise magnitude in the FFDM image compared with c-view. Whereas the FFDM image contained approximately white noise texture, the c-view image exhibited marked noise reduction at midfrequency and high frequency with far less noise suppression at low frequencies resulting in a mottled noise appearance. CONCLUSIONS: Their analysis demonstrates many instances where the c-view image quality differs from FFDM. Compared to FFDM, c-view offers a better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of c-view images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging. Not explicitly explored in this study is how the combination of DBT + c-view performs relative to DBT + FFDM or FFDM alone.

Population of 224 realistic human subject-based computational breast phantoms.

PURPOSE: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. METHODS: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. RESULTS: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. CONCLUSIONS: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

Frequency response and distortion properties of nonlinear image processing algorithms and the importance of imaging context.

PURPOSE: The most common metrics for resolution analysis in medical imaging are valid only for (approximately) linear systems. While analogues to these metrics have been used in attempts to describe resolution performance in nonlinear systems, the analysis is incomplete since distortion effects are often ignored. The authors have developed a methodology to analyze the amplitude modulation and waveform distortion properties of nonlinear systems with specific application to medical image processing algorithms. METHODS: Using sinusoidal basis functions, two metrics were derived which distinguish amplitude modulation from nonlinear waveform distortion: principle frequency response and distortion power spectrum, respectively. Additionally, two figures of merit were developed to describe the relative impact of nonlinear distortion as a result of image processing: distortion index (DI) and ΣDI. Three nonlinear denoising algorithms, the median, bilateral, and wavelet denoising filters, were selected as example functions to demonstrate the utility of the metrics derived in this study. RESULTS: Each filter showed very different resolution and waveform distortion properties. In particular, the amplitude and extent of nonlinear distortion depended strongly on image context and the type of nonlinear mechanism employed. Nonlinear waveform distortion constituted up to 30% of the median filter output signal power in high contrast-to-noise ratio (CNR) scenarios. Conversely, nonlinear distortion never exceeded 1% of the bilateral filter output signal power. The wavelet denoising response contained between 1% and 9% distortion which varied weakly as a function of CNR. CONCLUSIONS: The analytical metrics described in the paper demonstrate the importance of considering both resolution- and distortion-related effects in characterizing the performance of nonlinear imaging systems with specific application to image processing algorithms. Findings with three common nonlinear algorithms demonstrate a range of CNR values over which it is important to consider the impact of the nonlinear nature of each algorithm. Background context is also shown to influence the degree to which the nonlinear nature of the algorithm influences resolution and distortion. While no single metric can yet anticipate observer performance in nonlinear systems, the approach described can demonstrate the range of imaging contexts over which such nonlinear effects are important to consider.

Estimation of the two-dimensional presampled modulation transfer function of digital radiography devices using one-dimensional test objects.

PURPOSE: The modulation transfer function (MTF) of medical imaging devices is commonly reported in the form of orthogonal one-dimensional (1D) measurements made near the vertical and horizontal axes with a slit or edge test device. A more complete description is found by measuring the two-dimensional (2D) MTF. Some 2D test devices have been proposed, but there are some issues associated with their use: (1) they are not generally available; (2) they may require many images; (3) the results may have diminished accuracy; and (4) their implementation may be particularly cumbersome. This current work proposes the application of commonly available 1D test devices for practical and accurate estimation of the 2D presampled MTF of digital imaging systems. METHODS: Theory was developed and applied to ensure adequate fine sampling of the system line spread function for 1D test devices at orientations other than approximately vertical and horizontal. Methods were also derived and tested for slit nonuniformity correction at arbitrary angle. Techniques were validated with experimental measurements at ten angles using an edge test object and three angles using a slit test device on an indirect-detection flat-panel system [GE Revolution XQ∕i (GE Healthcare, Waukesha, WI)]. The 2D MTF was estimated through a simple surface fit with interpolation based on Delaunay triangulation of the 1D edge-based MTF measurements. Validation by synthesis was also performed with simulated images from a hypothetical direct-detection flat-panel device. RESULTS: The 2D MTF derived from physical measurements yielded an average relative precision error of 0.26% for frequencies below the cutoff (2.5 mm(-1)) and approximate circular symmetry at frequencies below 4 mm(-1). While slit analysis generally agreed with the results of edge analysis, the two showed subtle differences at frequencies above 4 mm(-1). Slit measurement near 45° revealed radial asymmetry in the MTF resulting from the square pixel aperture (0.2 mm × 0.2 mm), a characteristic which was not necessarily appreciated with the orthogonal 1D MTF measurements. In simulation experiments, both slit- and edge-based measurements resolved the radial asymmetries in the 2D MTF. The average absolute relative accuracy error in the 2D MTF between the DC and cutoff (2.5 mm(-1)) frequencies was 0.13% with average relative precision error of 0.11%. Other simulation results were similar to those derived from physical data. CONCLUSIONS: Overall, the general availability, acceptance, accuracy, and ease of implementation of 1D test devices for MTF assessment make this a valuable technique for 2D MTF estimation.

Neurovascular changes measured by time-of-flight MR angiography in cholesterol-fed rabbits with cortical amyloid beta-peptide accumulation.

PURPOSE: To test the hypothesis that narrowing of cranial blood vessels in cholesterol-fed rabbits is a function of the duration of the high cholesterol diet. Such neurovascular changes, caused by elevated serum cholesterol, are linked to stroke and Alzheimer's disease risk. MATERIALS AND METHODS: Four groups of New Zealand White rabbits were studied. Six were fed a normal diet, 19 were fed a 2% cholesterol diet with 0.12 ppm copper in the drinking water for 8 weeks, 10 weeks, or 12 weeks. Time-of-flight (TOF) MR angiography (MRA) at 3 Tesla was used to measure arterial diameters in 11 vessels. Previously published data for amyloid beta-peptide (Abeta) accumulation in the brains measured postmortem were correlated to vessel diameters. Ventricular volumes of rabbits were measured on group-averaged data. RESULTS: Several vessel diameters decreased with cholesterol diet duration. The posterior communicating arteries showed the largest significant effect. Abeta accumulation was inversely correlated with arterial diameter. Ventricular volumes between the normal diet and 12 weeks cholesterol-fed groups were not significantly different. CONCLUSION: Reduction in vessel diameter of medium-sized vessels but not large vessels was measured in these hypercholesterolemic rabbits. The vessel diameter narrowing and cortical Abeta deposition occurred before measurable ventricular enlargement.