Extremity radiographs derived from low-dose ultra-high-resolution CT: a phantom study.

OBJECTIVE: To demonstrate the potential of low-dose ultra-high-resolution CT (UHRCT) images to generate high-quality radiographic images on extremity phantoms and to estimate the radiation dose required for this. MATERIALS AND METHODS: A hand and knee phantom containing real human bones was imaged on an UHRCT scanner at full-dose, half-dose, and quarter-dose levels using a high-resolution extremity protocol. The raw data was reconstructed using both filtered back projection (FBP) and an iterative reconstruction algorithm (AIDR3D). Using custom designed software, each CT volume data set was converted to attenuation coefficients, and then a synthesized radiograph (synDX) was generated by forward projecting the volume data sets from a point source onto a 2D synthetic detector. The signal-to-noise ratio (SNR) was measured in the synDXs across all dose levels and the root-mean-squared error (RMSE) was computed with the FD synDXs as the reference. RESULTS: The proposed workflow generates high-quality synDXs at any arbitrary angle. For FBP, the SNR largely tracked with the radiation dose levels for both the knee and hand phantoms. For the knee phantom, iterative reconstruction provided a 6.1% higher SNR when compared to FBP. The RMSE was overall higher for the lowest dose levels and monotonically decreased with increasing dose. No substantial differences were observed qualitatively in the visualization of skeletal detail of the phantoms. CONCLUSION: The fine detail provided by UHRCT acquisitions of extremities facilitates the ability to generate quality radiographs, potentially eliminating the need for additional scanning on a conventional digital radiography system.

CT Phantom Evaluation of 67,392 American College of Radiology Accreditation Examinations: Implications for Opportunistic Screening of Osteoporosis Using CT.

OBJECTIVE. The purpose of this study was to investigate whether systematic bias in attenuation measurements occurs among CT scanners made by four major manufacturers and the relevance of this bias regarding opportunistic screening for osteoporosis. MATERIALS AND METHODS. Data on attenuation measurement accuracy were acquired using the American College of Radiology (ACR) accreditation phantom and were evaluated in a blinded fashion for four CT manufacturers (8500 accreditation submissions for manufacturer A; 18,575 for manufacturer B; 8278 for manufacturer C; and 32,039 for manufacturer D). The attenuation value for water, acrylic (surrogate for trabecular bone), and Teflon (surrogate for cortical bone; Chemours) materials for an adult abdominal CT technique (120 kV, 240 mA, standard reconstruction algorithm) was used in the analysis. Differences in attenuation value across all manufacturers were assessed using the Kruskal-Wallis test followed by a post hoc test for pairwise comparisons. RESULTS. The mean attenuation value for water ranged from -0.3 to 2.7 HU, with highly significant differences among all manufacturers (p < 0.001). For the trabecular bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 120.9 (SD, 3.5), 124.6 (3.3), 126.9 (4.4), and 123.9 (3.4) HU for manufacturers A, B, C, and D, respectively. For the cortical bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 939.0 (14.2), 874.3 (13.3), 897.6 (11.3), and 912.7 (13.4) HU for manufacturers A, B, C, and D, respectively. CONCLUSION. CT scanners made by different manufacturers show systematic offsets in attenuation measurement when compared with each other. Knowledge of these off-sets is useful for optimizing the accuracy of opportunistic diagnosis of osteoporosis.

Longitudinal Evaluation of Myocardial Fatty Acid and Glucose Metabolism in Fasted and Nonfasted Spontaneously Hypertensive Rats Using MicroPET/CT.

Using longitudinal micro positron emission tomography (microPET)/computed tomography (CT) studies, we quantified changes in myocardial metabolism and perfusion in spontaneously hypertensive rats (SHRs), a model of left ventricular hypertrophy (LVH). Fatty acid and glucose metabolism were quantified in the hearts of SHRs and Wistar-Kyoto (WKY) normotensive rats using long-chain fatty acid analog 18F-fluoro-6-thia heptadecanoic acid (18F-FTHA) and glucose analog 18F-fluorodeoxyglucose (18F-FDG) under normal or fasting conditions. We also used 18F-fluorodihydrorotenol (18F-FDHROL) to investigate perfusion in their hearts without fasting. Rats were imaged at 4 or 5 times over their life cycle. Compartment modeling was used to estimate the rate constants for the radiotracers. Blood samples were obtained and analyzed for glucose and free fatty acid concentrations. SHRs demonstrated no significant difference in 18F-FDHROL wash-in rate constant ( P = .1) and distribution volume ( P = .1), significantly higher 18F-FDG myocardial influx rate constant ( P = 4×10-8), and significantly lower 18F-FTHA myocardial influx rate constant ( P = .007) than WKYs during the 2009-2010 study without fasting. SHRs demonstrated a significantly higher 18F-FDHROL wash-in rate constant ( P = 5×10-6) and distribution volume ( P = 3×10-8), significantly higher 18F-FDG myocardial influx rate constant ( P = 3×10-8), and a higher trend of 18F-FTHA myocardial influx rate constant (not significant, P = .1) than WKYs during the 2011-2012 study with fasting. Changes in glucose plasma concentrations were generally negatively correlated with corresponding radiotracer influx rate constant changes. The study indicates a switch from preferred fatty acid metabolism to increased glucose metabolism with hypertrophy. Increased perfusion during the 2011-2012 study may be indicative of increased aerobic metabolism in the SHR model of LVH.

Phantom-based standardization of CT angiography images for spot sign detection.

PURPOSE: The CT angiography (CTA) spot sign is a strong predictor of hematoma expansion in intracerebral hemorrhage (ICH). However, CTA parameters vary widely across centers and may negatively impact spot sign accuracy in predicting ICH expansion. We developed a CT iodine calibration phantom that was scanned at different institutions in a large multicenter ICH clinical trial to determine the effect of image standardization on spot sign detection and performance. METHODS: A custom phantom containing known concentrations of iodine was designed and scanned using the stroke CT protocol at each institution. Custom software was developed to read the CT volume datasets and calculate the Hounsfield unit as a function of iodine concentration for each phantom scan. CTA images obtained within 8 h from symptom onset were analyzed by two trained readers comparing the calibrated vs. uncalibrated density cutoffs for spot sign identification. ICH expansion was defined as hematoma volume growth >33%. RESULTS: A total of 90 subjects qualified for the study, of whom 17/83 (20.5%) experienced ICH expansion. The number of spot sign positive scans was higher in the calibrated analysis (67.8 vs 38.9% p < 0.001). All spot signs identified in the non-calibrated analysis remained positive after calibration. Calibrated CTA images had higher sensitivity for ICH expansion (76 vs 52%) but inferior specificity (35 vs 63%) compared with uncalibrated images. CONCLUSION: Normalization of CTA images using phantom data is a feasible strategy to obtain consistent image quantification for spot sign analysis across different sites and may improve sensitivity for identification of ICH expansion.

Microcalcification detectability in breast CT images using CNN observers.

BACKGROUND: Breast computed tomography (CT) is an emerging breast imaging modality, and ongoing developments aim to improve breast CT's ability to detect microcalcifications. To understand the effects of different parameters on microcalcification detectability, a virtual clinical trial study was conducted using hybrid images and convolutional neural network (CNN)-based model observers. Mathematically generated microcalcifications were embedded into breast CT data sets acquired at our institution, and parameters related to calcification size, calcification contrast, cluster diameter, cluster density, and image display method (i.e., single slices, slice averaging, and maximum-intensity projections) were evaluated for their influence on microcalcification detectability. PURPOSE: To investigate the individual effects and the interplay of parameters affecting microcalcification detectability in breast CT. METHODS: Spherical microcalcifications of varying diameters (0.04, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40 mm) and native intensities were computer simulated to portray the partial volume effects of the imaging system. Calcifications were mathematically embedded into 109 patient breast CT volume data sets as individual calcifications or as clusters of calcifications. Six numbers of calcifications (1, 3, 5, 7, 10, 15) distributed within six cluster diameters (1, 3, 5, 6, 8, 10 mm) were simulated to study the effect of cluster density. To study the role of image display method, 2D regions of interest (ROIs) and 3D volumes of interest (VOIs) were generated using single slice extraction, slice averaging, and maximum-intensity projection (MIP). 2D and 3D CNNs were trained on the ROIs and VOIs, and receiver operating characteristic (ROC) curve analysis was used to evaluate detection performance. The area under the ROC curve (AUC) was used as the primary performance metric. RESULTS: Detection performance decreased with increasing section thickness, and peak detection performance occurred using the native section thickness (0.2 mm) and MIP display. The MIP display method, despite using a single slice, yielded comparable performance to the native section thickness, which employed 50 slices. Reduction in slices did not sacrifice detection accuracy and provided significant computational advantages over multi-slice image volumes. Larger cluster diameters resulted in reduced overall detectability, while smaller cluster diameters led to increased detectability. Additionally, we observed that the presence of more calcifications within a cluster improved the overall detectability, while fewer calcifications decreased it. CONCLUSIONS: As breast CT is still a relatively new breast imaging modality, there is an ongoing need to identify optimal imaging protocols. This work demonstrated the utility of MIP presentation for displaying image volumes containing microcalcification clusters. It is likely that human observers may also benefit from viewing MIPs compared to individual slices. The results of this investigation begin to elucidate how model observers interact with microcalcification clusters in a 3D volume, and will be useful for future studies investigating a broader set of parameters related to breast CT.

Translating contrast enhanced computed tomography images to liver radioembolization dose distribution for more comprehensively indicating patients.

1.1 Objective Contrast-enhanced computed tomography (CECT) is commonly used in the pre-treatment evaluation of liver Y-90 radioembolization feasibility. CECT provides detailed imaging of the liver and surrounding structures, allowing healthcare providers to assess the size, location, and characteristics of liver tumors prior to the treatment. Here we propose a method for translating CECT images to an expected dose distribution for tumor(s) and normal liver tissue. 1.2 Approach A pre-procedure CECT is used to obtain an iodine arterial-phase distribution by subtracting the non-contrast CT from the late arterial phase. The liver segments surrounding the targeted tumor are selected using Couinaud's method. The resolution of the resulting images is then degraded to match the resolution of the Positron Emission Tomography (PET) images, which can image the Y-90 activity distribution post-treatment. The resulting images are then used in the same way as PET images to compute doses using the Local Deposition Method (LDM). CECT images from three patients were used to test this method retrospectively and were compared with Y-90 PET-based dose distributions through dose volume histograms. 1.3 Main results Results show a concordance between predicted and delivered Y-90 dose distributions with less than 10% difference in terms of mean dose, for doses greater than 10% of the 98th percentile (D2%). 1.4 Significance CECT-derived predictions of Y-90 radioembolization dose distributions seem promising as a supplementary tool for physicians when assessing treatment feasibility. This dosimetry prediction method could provide a more comprehensive pre-treatment evaluation - offering greater insights than a basic assessment of tumor opacification on CT images.

Correcting for asymmetry of the proximal tibial epiphysis is warranted to determine postoperative alignment deviations in kinematic alignment from planned alignment of the tibial component on the native tibia.

BACKGROUND: In total knee arthroplasty, unrestricted kinematic alignment aims to restore pre-arthritic lower limb alignment and joint lines. Joint line orientations of the contralateral healthy proximal tibia might be used to evaluate accuracy of tibial component alignment post-operatively if asymmetry is minimal. Our objective was to evaluate left-to-right asymmetry of the proximal tibial epiphysis in posterior tibial slope and varus-valgus orientation as related to unrestricted kinematic alignment principles. METHODS: High resolution CT images (0.5 mm slice thickness) were acquired from bilateral lower limbs of 11 skeletally mature subjects with no skeletal abnormalities. Images were segmented to generate 3D tibia models. Asymmetry was quantified by differences in orientations required to shape-match the proximal epiphysis of the mirror 3D tibia model to the proximal epiphysis of the contralateral 3D tibia model. FINDINGS: Systematic and random differences (i.e. mean ± standard deviation) in tibial slope and varus-valgus orientation were - 0.8° ± 1.2° and - 0.2° ± 0.8°, respectively. Ninety five percent confidence intervals on the means included 0° indicating that systematic differences were minimal. INTERPRETATION: Since random differences due to asymmetry are substantial in relation to random surgical deviations from pre-arthritic joint lines previously reported, post-operative computer tomograms of the contralateral healthy tibia should not be used to directly assess accuracy of tibial component alignment on a group level without correcting for differences in tibial slope and varus-valgus orientation due to asymmetry.

Joint AAPM Task Group 282/EFOMP Working Group Report: Breast dosimetry for standard and contrast-enhanced mammography and breast tomosynthesis.

Currently, there are multiple breast dosimetry estimation methods for mammography and its variants in use throughout the world. This fact alone introduces uncertainty, since it is often impossible to distinguish which model is internally used by a specific imaging system. In addition, all current models are hampered by various limitations, in terms of overly simplified models of the breast and its composition, as well as simplistic models of the imaging system. Many of these simplifications were necessary, for the most part, due to the need to limit the computational cost of obtaining the required dose conversion coefficients decades ago, when these models were first implemented. With the advancements in computational power, and to address most of the known limitations of previous breast dosimetry methods, a new breast dosimetry method, based on new breast models, has been developed, implemented, and tested. This model, developed jointly by the American Association of Physicists in Medicine and the European Federation for Organizations of Medical Physics, is applicable to standard mammography, digital breast tomosynthesis, and their contrast-enhanced variants. In addition, it includes models of the breast in both the cranio-caudal and the medio-lateral oblique views. Special emphasis was placed on the breast and system models used being based on evidence, either by analysis of large sets of patient data or by performing measurements on imaging devices from a range of manufacturers. Due to the vast number of dose conversion coefficients resulting from the developed model, and the relative complexity of the calculations needed to apply it, a software program has been made available for download or online use, free of charge, to apply the developed breast dosimetry method. The program is available for download or it can be used directly online. A separate User's Guide is provided with the software.

Pre-whitened matched filter and convolutional neural network based model observer performance for mass lesion detection in non-contrast breast CT.

BACKGROUND: Mathematical model observers have been shown to reasonably predict human observer performance and are useful when human observer studies are infeasible. Recently, convolutional neural networks (CNNs) have also been used as substitutes for human observers, and studies have shown their utility as an optimal observer. In this study, a CNN model observer is compared to the pre-whitened matched filter (PWMF) model observer in detecting simulated mass lesions inserted into 253 acquired breast computed tomography (bCT) images from patients imaged at our institution. PURPOSE: To compare CNN and PWMF model observers for detecting signal-known-exactly (SKE) location-known-exactly (LKE) simulated lesions in bCT images with real anatomical backgrounds, and to use these model observers collectively to optimize parameters and understand trends in performance with breast CT. METHODS: Spherical lesions with different diameters (1, 3, 5, 9 mm) were mathematically inserted into reconstructed patient bCT image data sets to mimic 3D mass lesions in the breast. 2D images were generated by extracting the center slice along the axial dimension or by slice averaging across adjacent slices to model thicker sections (0.4, 1.2, 2.0, 6.0, 12.4, 20.4 mm). The role of breast density was retrospectively studied using the range of breast densities intrinsic to the patient bCT data sets. In addition, mass lesions were mathematically inserted into Gaussian images matched to the mean and noise power spectrum of the bCT images to better understand the performance of the CNN in the context of a known ideal observer (the PWMF). The simulated Gaussian and bCT images were divided into training and testing data sets. Each training data set consisted of 91 600 images, and each testing data set consisted of 96 000 images. A CNN and PWMF was trained on the Gaussian training images, and a different CNN and PWMF was trained on the bCT training images. The trained model observers were tested, and receiver operating characteristic (ROC) curve analysis was used to evaluate detection performance. The area under the ROC curve (AUC) was the primary performance metric used to compare the model observers. RESULTS: In the Gaussian background, the CNN performed essentially identically to the PWMF across lesion sizes and section thicknesses. In the bCT background, the CNN outperformed the PWMF across lesion size, breast density, and most section thicknesses. These findings suggest that there are higher-order features in bCT images that are harnessed by the CNN observer but are inaccessible to the PWMF. CONCLUSIONS: The CNN performed equivalently to the ideal observer in Gaussian textures. In bCT background, the CNN captures more diagnostic information than the PWMF and may be a more pertinent observer when conducting optimal performance studies in breast CT images.

Model observer performance in contrast-enhanced lesions in breast CT: The influence of contrast concentration on detectability.

BACKGROUND: The use of iodine-based contrast agent for better delineation of tumors in breast CT (bCT) has been shown to be compelling, similar to the tumor enhancement in contrast-enhanced breast MRI. Contrast-enhanced bCT (CE-bCT) is a relatively new tool, and a structured evaluation of different imaging parameters at play has yet to be conducted. In this investigation, data sets of acquired bCT images from 253 patients imaged at our institution were used in concert with simulated mathematically inserted spherical contrast-enhanced lesions to study the role of contrast enhancement on detectability. PURPOSE: To quantitatively evaluate the improvement in lesion detectability due to contrast enhancement across lesion diameter, section thickness, view plane, and breast density using a pre-whitened matched filter (PWMF) model observer. METHODS: The relationship between iodine concentration and Hounsfield units (HU) was measured using spectral modeling. The lesion enhancement from clinical CE-bCT images in 22 patients was evaluated, and the average contrast enhancement (ΔHU) was determined. Mathematically generated spherical mass lesions of varying diameters (1, 3, 5, 9, 11, 15 mm) and contrast enhancement levels (0, 0.25, 0.50, 0.75, 1) were inserted at random locations in 253 actual patient bCT datasets. Images with varying thicknesses (0.4-19.8 mm) were generated by slice averaging, and the role of view plane (coronal and axial planes) was studied. A PWMF was used to generate receiver operating characteristic (ROC) curves across parameters of lesion diameter, contrast enhancement, section thickness, view plane, and breast density. The area under the ROC curve (AUC) was used as the primary performance metric, generated from over 90,000 simulated lesions. RESULTS: An average 20% improvement (ΔAUC = 0.1) in lesion detectability due to contrast enhancement was observed across lesion diameter, section thickness, breast density, and view plane. A larger improvement was observed when stratifying patients based on breast density. For patients with VGF ≤ 40%, detection performance improved up to 20% (until AUC →1), and for patients with denser breasts (VGF > 40%), detection performance improved more drastically, ranging from 20% to 80% for 1- and 5-mm lesions. For the 1 mm lesion, detection performance raised slightly at the 1.2 mm section thickness before falling off as thickness increased. For larger lesions, detection performance was generally unaffected as section thickness increased up until it reached 5.8 mm, where performance began to decline. Detection performance was higher in the axial plane compared to the coronal plane for smaller lesions and thicker sections. CONCLUSIONS: For emerging diagnostic tools like CE-bCT, it is important to optimize imaging protocols for lesion detection. In this study, we found that intravenous contrast can be used to detect small lesions in dense breasts. Optimal section thickness for detectability has dependencies on breast density and lesion size, therefore, display thickness should be adjusted in real-time using display software. These findings may be useful for the development of CE-bCT as well as other x-ray-based breast imaging modalities.

Performance of high-resolution CT for detection and discrimination tasks related to stenotic lesions - A phantom study using model observers.

BACKGROUND: Accurate detection and grading of atheromatous stenotic lesions within the cardiac, renal, and intracranial vasculature is imperative for early recognition of disease and guiding treatment strategies. PURPOSE: In this work, a stenotic lesion phantom was used to compare high resolution and normal resolution modes on the same CT scanner in terms of detection and size discrimination performance. MATERIALS AND METHODS: The phantom is comprised of three acrylic cylinders (each 15.0 cm in diameter and 1.3 cm thick) with a matching array of holes in each module. The outer two modules contain holes that are slightly larger than the corresponding hole in the central module to simulate stenotic narrowing in vasculature. The stack of modules was submerged in an iodine solution simulating contrast-enhanced stenotic lesions with a range of lumen diameters (1.32-10.08 mm) and stenosis severity (0%, 50%, 60%, 70%, and 80%). The phantom was imaged on the Canon Aquilion Precision high-resolution CT scanner in high-resolution (HR) mode (0.25 mm × 0.50 mm detector element size) and normal-resolution (NR) mode (0.50 mm × 0.50 mm) using 120 kV and two dose levels (14 and 21 mGy SSDE) with 30 repeat scans acquired for each combination. Filtered back-projection (FBP) and a hybrid-iterative reconstruction (AIDR) were used with the FC18 kernel, as well as a deep learning algorithm (AiCE) which is only available for HR. A non-prewhitening model observer with an eye filter was implemented to quantify performance for detection and size discrimination tasks in the axial plane. RESULTS: Detection performance improved with increasing diameter, dose, and for AIDR in comparison to FBP for a fixed resolution mode. Performance in the HR mode was generally higher than NR for the smaller lumen diameters (1-5 mm) with decreasing differences as the diameter increased. Performance in NR mode surpassed HR mode for lumen diameters greater than ∼4 mm and ∼5 mm for 14 mGy and 21 mGy, respectively. AiCE provided consistently higher detection performance compared with AIDR-FC18 (48% higher for a 6 mm lumen diameter). Discrimination performance increased with increasing nominal diameter, dose, and for larger differences in stenosis severity. When comparing discrimination performance in HR to NR modes, the largest relative differences occur at the smallest nominal diameters and smallest differences in stenosis severity. The AiCE reconstruction algorithm produced the highest overall discrimination performance values, and these were significantly higher than AIDR-FC18 for nominal diameters of 7.14 and 10.08 mm. CONCLUSIONS: HR mode outperforms NR for detection up to a specific diameter and the results improve with AiCE and for higher dose levels. For the task of size discrimination, HR mode consistently outperforms NR if AIDR-FC18 is used for dose levels of at least 21 mGy, and the results improve with AiCE and for the smallest differences in stenosis severity investigated (50% vs. 60%). High-resolution CT appears to be beneficial for detecting smaller simulated lumen diameters (<5 mm) and is generally advantageous for discrimination tasks related to stenotic lesions, which inherently contain information at higher frequencies, given the right reconstruction algorithm and dose level.

Correcting for distal femoral asymmetry is necessary to determine postoperative alignment deviations from planned alignment of the femoral component.

BACKGROUND: One method for assessing the accuracy of manual, patient-specific, navigational, and robotic-assisted total knee arthroplasty (TKA) instrumentation is to use a post-operative computer tomogram and determine the deviation of the femoral component alignment relative to the planned alignment in the native (i.e. healthy) contralateral distal femoral epiphysis. However, side-to-side asymmetry might introduce errors which inflate alignment deviations. This study quantified asymmetry in the distal femoral epiphysis. METHODS: High resolution CT images (0.5 mm slice thickness) were acquired from bilateral lower limb specimens of 13 skeletally mature subjects with no skeletal abnormalities. Images were segmented to generate 3D femur models. Asymmetry was quantified by differences in positions and orientations required to shape-match the distal epiphysis of the mirror 3D femur model to the distal epiphysis of the contralateral 3D femur model. RESULTS: Asymmetry was due to random rather than systematic differences. Random differences (i.e. standard deviations) in proximal-distal (P-D) and anterior-posterior (A-P) positions were 1.1 mm and in varus-valgus (V-V) and internal-external (I-E) orientations were 0.9° and 1.3°, respectively. These represented substantial relative errors of up to 50 % in previously reported overall alignment deviations. CONCLUSIONS: Although small in an absolute sense, asymmetry of the distal femur epiphysis introduced substantial relative errors when assessing accuracy of femoral component alignment in TKA. When post-operative computer tomograms are used to assess the accuracy of manual, patient specific, navigational, and robotic-assisted TKA instrumentation, the overall deviation should be corrected for asymmetry to better indicate the accuracy of the surgical technique.

Radiology Environmental Impact: What Is Known and How Can We Improve?

The healthcare sector generates approximately 10% of the total carbon emissions in the United States. Radiology is thought to be a top contributor to the healthcare carbon footprint due to high energy-consuming devices and waste from interventional procedures. In this article, we provide a background on Radiology's environmental impact, describe why hospitals should add sustainability as a quality measure, and give a framework for radiologists to reduce the carbon footprint through quality improvement and collaboration.

Comparisons of glandular breast dose between digital mammography, tomosynthesis and breast CT based on anthropomorphic patient-derived breast phantoms.

PURPOSE: To evaluate the bias to the mean glandular dose (MGD) estimates introduced by the homogeneous breast models in digital breast tomosynthesis (DBT) and to have an insight into the glandular dose distributions in 2D (digital mammography, DM) and 3D (DBT and breast dedicated CT, BCT) x-ray breast imaging by employing breast models with realistic glandular tissue distribution and organ silhouette. METHODS: A Monte Carlo software for DM, DBT and BCT simulations was adopted for the evaluation of glandular dose distribution in 60 computational anthropomorphic phantoms. These computational phantoms were derived from 3D breast images acquired via a clinical BCT scanner. RESULTS: g·c·s·T conversion coefficients based on homogeneous breast model led to a MGD overestimate of 18% in DBT when compared to MGD estimated via anthropomorphic phantoms; this overestimate increased up to 21% for recently computed DgNDBT conversion coefficients. The standard deviation of the glandular dose distribution in BCT resulted 60% lower than in DM and 55% lower than in DBT. The glandular dose peak - evaluated as the average value over the 5% of the gland receiving the highest dose - is 2.8 times the MGD in DM, this factor reducing to 2.6 and 1.6 in DBT and BCT, respectively. CONCLUSIONS: Conventional conversion coefficients for MGD estimates based on homogeneous breast models overestimate MGD by 18%, when compared to MGD estimated via anthropomorphic phantoms. The ratio between the peak glandular dose and the MGD is 2.8 in DM. This ratio is 8% and 75% higher than in DBT and BCT, respectively.

Quantification of airway dimensions using a high-resolution CT scanner: A phantom study.

PURPOSE: Small airways with inner diameters less than 2 mm are sites of major airflow limitations in patients with chronic obstructive pulmonary disease (COPD) and asthma. The purpose of this study is to investigate the limitations for accurate assessment of small airway dimensions using both high-resolution CT (HRCT) and conventional normal-resolution CT at low dose levels. METHODS: To model the normal human airways from the 3rd to 20th generations, a cylindrical polyurethane phantom with 14 airway tubes of inner diameters (ID) ranging from 0.3 to 3.4 mm and wall thicknesses (WT) ranging from 0.15 to 1.6 mm was placed within an Anthropomorphic QRM-Thorax phantom. The Aquilion Precision (Canon Medical Systems Corporation) HRCT scanner was used to acquire images at 80, 100, and 120 kV using high resolution mode (HR, 0.25 mm × 160 detector configuration) and normal-resolution (NR) mode (0.5 mm × 80 detector configuration). The HR data were reconstructed using a 1024 × 1024 matrix (0.22 × 0.22 × 0.25 mm voxel size) and the NR data were reconstructed using a 512 × 512 matrix (0.43 × 0.43 × 0.50 mm). Two reconstruction algorithms (filtered back projection; FBP and an adaptive iterative dose reduction 3D algorithm; AIDR 3D) and three reconstruction kernels (FC30, FC52, and FC56) were investigated. The C T D I vol dose values ranged from 0.2 to 6.2 mGy. A refined automated full-width half-maximum (FWHM) method was used for the measurement of airway dimensions, where the density profiles were computed by radial oversampling using a polar coordinate system. Both ID and WT were compared to the known dimensions using a regression model, and the root-mean-square error (RMSE) and average error were computed across all 14 airway tubes. RESULTS: The results indicate that the ID can be measured within a 15% error down to approximately 0.8 and 2.0 mm using the HR and NR modes, respectively. The overall RMSE (and average error) of ID measurements for HR and NR were 0.10 mm (-0.70%) and 0.31 mm (-2.63%), respectively. The RMSE (and average error) of WT measurements using HR and NR were 0.10 mm (23.27%) and 0.27 mm (53.56%), respectively. The WT measurement using HR yielded a factor of two improvement in accuracy as compared to NR. CONCLUSIONS: High-resolution CT can provide more accurate measurements of airway dimensions as compared with NR CT, potentially improving quantitative assessment of pathologies such as COPD and asthma. The HR mode acquired and reconstructed with AIDR3D and the FC52 kernel provides most accurate measurement of airway dimensions. Low-dose HR measurements at dose level above 0.9 mGy can provide improved accuracy on both inner diameters and wall thicknesses compared to full dose NR airway phantom measurements.

High-resolution µ CT imaging for characterizing microcalcification detection performance in breast CT.

Purpose: To demonstrate the utility of high-resolution micro-computed tomography ( µ CT ) for determining ground-truth size and shape properties of calcium grains for evaluation of detection performance in breast CT (bCT). Approach: Calcium carbonate grains ( ∼ 200 µ m ) were suspended in 1% agar solution to emulate microcalcifications ( µ Calcs ) within a fibroglandular tissue background. Ground-truth imaging was performed on a commercial µ CT scanner and was used for assessing calcium-grain size and shape, and for generating µ Calc signal profiles. Calcium grains were placed within a realistic breast-shaped phantom and imaged on a prototype bCT system at 3- and 6-mGy mean glandular dose (MGD) levels, and the non-prewhitening detectability was assessed. Additionally, the µ CT -derived signal profiles were used in conjunction with the bCT system characterization (MTF and NPS) to obtain predictions of bCT detectability. Results: Estimated detectability of the calcium grains on the bCT system ranged from 2.5 to 10.6 for 3 mGy and from 3.8 to 15.3 for 6 mGy with large fractions of the grains meeting the Rose criterion for visibility. Segmentation of µ CT images based on morphological operations produced accurate results in terms of segmentation boundaries and segmented region size. A regression model linking bCT detectability to µ Calc parameters indicated significant effects of µ Calc size and vertical position within the breast phantom. Detectability using µ CT -derived detection templates and bCT statistical properties (MTF and NPS) were in good correspondence with those measured directly from bCT ( R 2 > 0.88 ). Conclusions: Parameters derived from µ CT ground-truth data were shown to produce useful characterizations of detectability when compared to estimates derived directly from bCT. Signal profiles derived from µ CT imaging can be used in conjunction with measured or hypothesized statistical properties to evaluate the performance of a system, or system component, that may not currently be available.

Location and direction dependence in the 3D MTF for a high-resolution CT system.

PURPOSE: The purpose of this study was to quantify location and direction-dependent variations in the 3D modulation transfer function (MTF) of a high-resolution CT scanner with selectable focal spot sizes and resolution modes. METHODS: The Aquilion Precision CT scanner (Canon Medical Systems) has selectable 0.25 mm or 0.5 mm detectors (by binning) in both the axial (x-y) and detector array width (z) directions. For the x-y and z orientations, detectors are configured (x-y) = 0.5 mm/(z) = 0.5 mm for normal resolution (NR), 0.25/0.5 mm for high resolution (HR), and 0.25/0.25 mm for super high resolution (SHR). Six focal spots (FS1-FS6) range in size from 0.4 (x-y) × 0.5 mm (z) for FS1 to 1.6 × 1.4 mm for FS6. Phantoms fabricated from spherical objects were positioned at radial distances of 0, 4.0, 7.5, 11.0, 14.5, and 18.5 cm. Axial and helical acquisitions were utilized and reconstructed using filtered back projection with the FC18 "Body," FC30 "Bone," and FC81 "Bone Sharp" kernels. The reconstructions were used to measure a 1D slice of the 3D MTF by oversampling the 3D ESF in the axial plane [MTF(fr ); φ = 0°)], 45° out of the axial plane [MTF(fr ); φ = 45°)], in the longitudinal direction [MTF(fr ); φ = 80°)], and along the radial and azimuthal directions within the axial plane. RESULTS: The MTF(fr ); φ = 45°) drops to 10% (f10 ) at 1.20, 1.45, and 2.06 mm-1 for NR, HR, and SHR, respectively, for a helical acquisition with FS1, FC30, and r = 4 cm from the isocenter. The MTF(fr ); φ = 45°) includes contributions of both the axial-plane MTF (f10  = 1.10, 2.04, and 2.01 mm-1 ) and the longitudinal MTF (f10  = 1.17, 1.18, and 1.82 mm-1 ) for the NR, HR, and SHR modes, respectively. For SHR, the axial scan mode showed a 15-25% improvement over helical mode in the longitudinal resolution. Helical pitch, ranging from 0.569 to 1.381, did not appreciably affect the 3D resolution (<2%). The radial MTFs across the axial field of view (FOV) showed dependencies on the focal spot length in z; for example, for SHR with FS2 (0.6 × 0.6 mm), f10 at  r = 11 cm was within 17% of the value at r = 4 cm, but for SHR with FS3 (0.6 × 1.3), the reduction in f10 was 46% from 4 to 11 cm from the isocenter. The azimuthal MTF also decreased as r increased but less so for longer gantry rotation times and smaller focal spot dimensions in the axial plane. The longitudinal MTF was minimally affected (<11%) by position in the FOV and was principally affected by the focal spot length in the z-dimension. CONCLUSIONS: The 3D MTF was measured throughout the FOV of a high-resolution CT scanner, quantifying the advantages of different resolution modes and focal spot sizes on the axial-plane and longitudinal MTF. Reconstruction kernels were shown to impact axial-plane resolution, imparting non-isotropic 3D resolution characteristics. Focal spot size (both in x-y and in z) and gantry rotation time play important roles in preserving the high-resolution characteristics throughout the field of view for this new high-resolution CT scanner technology.

Theory, method, and test tools for determination of 3D MTF characteristics in cone-beam CT.

PURPOSE: The modulation transfer function (MTF) is widely used as an objective metric of spatial resolution of medical imaging systems. Despite advances in capability for three-dimensional (3D) isotropic spatial resolution in computed tomography (CT) and cone-beam CT (CBCT), MTF evaluation for such systems is typically reported only in the axial plane, and practical methodology for assessment of fully 3D spatial resolution characteristics is lacking. This work reviews fundamental theoretical relationships of two-dimensional (2D) and 3D spread functions and reports practical methods and test tools for analysis of 3D MTF in CBCT. METHODS: Fundamental aspects of 2D and 3D MTF measurement are reviewed within a common notational framework, and three MTF test tools with analysis code are reported and made available online (https://istar.jhu.edu/downloads/): (a) a multi-wire tool for measurement of the axial plane MTF [denoted as M T F ( f r ; φ = 0 ∘ ) , where φ is the measurement angle out of the axial plane] as a function of position in the axial plane; (b) a wedge tool for measurement of the MTF in any direction in the 3D Fourier domain [e.g.,  φ  = 45°, denoted as M T F ( f r ; φ = 45 ∘ ) ]; and (c) a sphere tool for measurement of the MTF in any or all directions in the 3D Fourier domain. Experiments were performed on a mobile C-arm with CBCT capability, showing that M T F ( f r ; φ = 45 ∘ ) yields an informative one-dimensional (1D) representation of the overall 3D spatial resolution characteristics, capturing important characteristics of the 3D MTF that might be missed in conventional analysis. The effects of anisotropic filters and detector readout mode were investigated, and the extent to which a system can be said to provide "isotropic" resolution was evaluated by quantitative comparison of MTF at various φ . RESULTS: All three test tools provided consistent measurement of M T F ( f r ; φ = 0 ∘ ) , and the wedge and sphere tools demonstrated how measurement of the MTF in directions outside the axial plane ( φ > 0 ∘ ) can reveal spatial resolution characteristics to which conventional axial MTF measurement is blind. The wedge tool was shown to reduce statistical measurement error compared to the sphere tool due to improved sampling, and the sphere tool was shown to provide a basis for measurement of the MTF in any or all directions (outside the null cone) from a single scan. The C-arm system exhibited non-isotropic spatial resolution with conventional non-isotropic 1D apodization filters (i.e., frequency cutoff filters) - which is common in CBCT - and implementation of isotropic 2D apodization yielded quantifiably isotropic MTF. Asymmetric pixel binning modes were similarly shown to impart non-isotropic effects on the 3D MTF, and the overall 3D MTF characteristics were evident in each case with a single, 1D measurement of the 1D M T F ( f r ; φ = 45 ∘ ). CONCLUSION: Three test tools and corresponding MTF analysis methods were presented within a consistent framework for analysis of 3D spatial resolution characteristics in a manner amenable to routine, practical measurements. Experiments on a CBCT C-arm validated many intuitive aspects of 3D spatial resolution and quantified the extent to which a CBCT system may be considered to have isotropic resolution. Measurement of M T F ( f r ; φ = 45 ∘ ) provided a practical 1D measure of the underlying 3D MTF characteristics and is extensible to other CT or CBCT systems offering high, isotropic spatial resolution.

Computer-aided diagnosis of masses in breast computed tomography imaging: deep learning model with combined handcrafted and convolutional radiomic features.

Purpose: A computer-aided diagnosis (CADx) system for breast masses is proposed, which incorporates both handcrafted and convolutional radiomic features embedded into a single deep learning model. Approach: The model combines handcrafted and convolutional radiomic signatures into a multi-view architecture, which retrieves three-dimensional (3D) image information by simultaneously processing multiple two-dimensional mass patches extracted along different planes through the 3D mass volume. Each patch is processed by a stream composed of two concatenated parallel branches: a multi-layer perceptron fed with automatically extracted handcrafted radiomic features, and a convolutional neural network, for which discriminant features are learned from the input patches. All streams are then concatenated together into a final architecture, where all network weights are shared and the learning occurs simultaneously for each stream and branch. The CADx system was developed and tested for diagnosis of breast masses ( N = 284 ) using image datasets acquired with independent dedicated breast computed tomography systems from two different institutions. The diagnostic classification performance of the CADx system was compared against other machine and deep learning architectures adopting handcrafted and convolutional approaches, and three board-certified breast radiologists. Results: On a test set of 82 masses (45 benign, 37 malignant), the proposed CADx system performed better than all other model architectures evaluated, with an increase in the area under the receiver operating characteristics curve (AUC) of 0.05 ± 0.02 , and achieving a final AUC of 0.947, outperforming the three radiologists ( AUC = 0.814 - 0.902 ). Conclusions: In conclusion, the system demonstrated its potential usefulness in breast cancer diagnosis by improving mass malignancy assessment.