3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

BACKGROUND: The detectability performance of a CT scanner is difficult to precisely quantify when nonlinearities are present in reconstruction. An efficient detectability assessment method that is sensitive to small effects of dose and scanner settings is desirable. We previously proposed a method using a search challenge instrument: a phantom is embedded with hundreds of lesions at random locations, and a model observer is used to detect lesions. Preliminary tests in simulation and a prototype showed promising results. PURPOSE: In this work, we fabricated a full-size search challenge phantom with design updates, including changes to lesion size, contrast, and number, and studied our implementation by comparing the lesion detectability from a nonprewhitening (NPW) model observer between different reconstructions at different exposure levels, and by estimating the instrument sensitivity to detect changes in dose. METHODS: Designed to fit into QRM anthropomorphic phantoms, our search challenge phantom is a cylindrical insert 10 cm wide and 4 cm thick, embedded with 12 000 lesions (nominal width of 0.6 mm, height of 0.8 mm, and contrast of -350 HU), and was fabricated using PixelPrint, a 3D printing technique. The insert was scanned alone at a high dose to assess printing accuracy. To evaluate lesion detectability, the insert was placed in a QRM thorax phantom and scanned from 50 to 625 mAs with increments of 25 mAs, once per exposure level, and the average of all exposure levels was used as high-dose reference. Scans were reconstructed with three different settings: filtered-backprojection (FBP) with Br40 and Br59, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) with strength level 5 and Br59 kernel. An NPW model observer was used to search for lesions, and detection performance of different settings were compared using area under the exponential transform of free response ROC curve (AUC). Using propagation of uncertainty, the sensitivity to changes in dose was estimated by the percent change in exposure due to one standard deviation of AUC, measured from 5 repeat scans at 100, 200, 300, and 400 mAs. RESULTS: The printed insert lesions had an average position error of 0.20 mm compared to printing reference. As the exposure level increases from 50 mAs to 625 mAs, the lesion detectability AUCs increase from 0.38 to 0.92, 0.42 to 0.98, and 0.41 to 0.97 for FBP Br40, FBP Br59, and SAFIRE Br59, respectively, with a lower rate of increase at higher exposure level. FBP Br59 performed best with AUC 0.01 higher than SAFIRE Br59 on average and 0.07 higher than FBP Br40 (all P < 0.001). The standard deviation of AUC was less than 0.006, and the sensitivity to detect changes in mAs was within 2% for FBP Br59. CONCLUSIONS: Our 3D-printed search challenge phantom with 12 000 submillimeter lesions, together with an NPW model observer, provide an efficient CT detectability assessment method that is sensitive to subtle effects in reconstruction and is sensitive to small changes in dose.

Improving Stenosis Assessment in Energy Integrating Detector CT via Learned Monoenergetic Imaging Capability.

Coronary CT angiography (cCTA) is a fast non-invasive imaging exam for coronary artery disease (CAD) but struggles with dense calcifications and stents due to blooming artifacts, potentially causing stenosis overestimation. Virtual monoenergetic images (VMIs) at higher keV (e.g., 100 keV) from photon counting detector (PCD) CT have shown promise in reducing blooming artifacts and improving lumen visibility through its simultaneous high-resolution and multi-energy imaging capability. However, most cCTA exams are performed with single-energy CT (SECT) using conventional energy-integrating detectors (EID). Generating VMIs through EID-CT requires advanced multi-energy CT (MECT) scanners and potentially sacrifices temporal resolution. Given these limitations, MECT cCTA exams are not commonly performed on EID-CT and VMIs are not routinely generated. To tackle this, we aim to enhance the multi-energy imaging capability of EID-CT through the utilization of a convolutional neural network to LEarn MONoenergetic imAging from VMIs at Different Energies (LEMONADE). The neural network was trained using ten patient cCTA exams acquired on a clinical PCD-CT (NAEOTOM Alpha, Siemens Healthineers), with 70 keV VMIs as input (which is nominally equivalent to the SECT from EID-CT scanned at 120 kV) and 100 keV VMIs as the target. Subsequently, we evaluated the performance of EID-CT equipped with LEMONADE on both phantom and patient cases (n=10) for stenosis assessment. Results indicated that LEMONADE accurately quantified stenosis in three phantoms, aligning closely with ground truth and demonstrating stenosis percentage area reductions of 13%, 8%, and 9%. In patient cases, it led to a 12.9% reduction in average diameter luminal stenosis when compared to the original SECT without LEMONADE. These outcomes highlight LEMONADE's capacity to enable multi-energy CT imaging, mitigate blooming artifacts, and improve stenosis assessment for the widely available EID-CT. This has a high potential impact as most cCTA exams are performed on EID-CT.

Technical Note: Assessment of Pulse Pileup on Single-Energy and Multienergy Images From a Clinical Photon-Counting Detector Computed Tomography.

OBJECTIVE: Pulse pileup effects occur when pulses occur so close together that they fall on top of one another, resulting in count loss and errors in energy thresholding. To date, there has been little work systematically detailing the quantitative effects of pulse pileup on material decomposition accuracy for photon-counting detector (PCD) computed tomography (CT). Our aim in this work was to quantify the effects of pulse pileup on single-energy and multienergy CT images, including low-energy bin (BL), high-energy bin (BH), iodine map, and virtual noncontrast images from a commercial PCD-CT. METHODS: Scans of a 20-cm diameter multienergy CT phantom with 10 solid inserts were acquired at a fixed tube potential as the tube current was varied across the available range. Four types of images (BL, BH, iodine map, and virtual noncontrast) were reconstructed using an iterative reconstruction algorithm at strength 2, a quantitative reconstruction kernel (Qr40), 2-/1-mm slice thickness/increment, and a 210-mm field-of-view. The mean and standard deviation of CT numbers were recorded and the ratios of CT number between BL and BH images were calculated and plotted, along with noise versus tube current and noise × versus tube current. RESULTS: As tube current was increased, the range of variations in CT numbers was less than 13.4 HU for all inserts and image types evaluated. Noise × versus tube current showed a small positive slope equal to a noise increase from 100 mA of 10% at 500 mA and 15% at 900 mA compared with what would be expected if the slope was zero. CONCLUSIONS: Minimal impact on single-energy and multienergy CT numbers and noise performance was observed for the evaluated clinical PCD-CT system.

A minimum SNR criterion for computed tomography object detection in the projection domain.

BACKGROUND: A common rule of thumb for object detection is the Rose criterion, which states that a signal must be five standard deviations above background to be detectable to a human observer. The validity of the Rose criterion in CT imaging is limited due to the presence of correlated noise. Recent reconstruction and denoising methodologies are also able to restore apparent image quality in very noisy conditions, and the ultimate limits of these methodologies are not yet known. PURPOSE: To establish a lower bound on the minimum achievable signal-to-noise ratio (SNR) for object detection, below which detection performance is poor regardless of reconstruction or denoising methodology. METHODS: We consider a numerical observer that operates on projection data and has perfect knowledge of the background and the objects to be detected, and determine the minimum projection SNR that is necessary to achieve predetermined lesion-level sensitivity and case-level specificity targets. We define a set of discrete signal objects O $\mathcal{O}$ that encompasses any lesion of interest and could include lesions of different sizes, shapes, and locations. The task is to determine which object of O $\mathcal{O}$ is present, or to state the null hypothesis that no object is present. We constrain each object in O $\mathcal{O}$ to have equivalent projection SNR and use Monte Carlo methods to calculate the required projection SNR necessary. Because our calculations are performed in projection space, they impose an upper limit on the performance possible from reconstructed images. We chose O $\mathcal{O}$ to be a collection of elliptical or circular low contrast metastases and simulated detection of these objects in a parallel beam system with Gaussian statistics. Unless otherwise stated, we assume a target of 80% lesion-level sensitivity and 80% case-level specificity and a search field of view that is 6 cm by 6 cm by 10 slices. RESULTS: When O $\mathcal{O}$ contains only a single object, our problem is equivalent to two-alternative forced choice (2AFC) and the required projection SNR is 1.7. When O $\mathcal{O}$ consists of circular 6-mm lesions at different locations in space, the required projection SNR is 5.1. When O $\mathcal{O}$ is extended to include ellipses and circles of different sizes, the required projection SNR increases to 5.3. The required SNR increases if the sensitivity target, specificity target, or search field of view increases. CONCLUSIONS: Even with perfect knowledge of the background and target objects, the ideal observer still requires an SNR of approximately 5. This is a lower bound on the SNR that would be required in real conditions, where the background and target objects are not known perfectly. Algorithms that denoise lesions with less than 5 projection SNR, regardless of the denoising methodology, are expected to show vanishing effects or false positive lesions.

Renal Adiposity Does not Preclude Quantitative Assessment of Renal Function Using Dual-Energy Multidetector CT in Mildly Obese Human Subjects.

RATIONALE AND OBJECTIVES: Multidetector computed tomography (MDCT) is useful for measuring in the research setting single-kidney perfusion and function using iodinated contrast time-attenuation curves. Obesity promotes deposition of intrarenal fat, which might decrease tissue attenuation and thereby interfere with quantification of renal function using MDCT. The purpose of this study was to test the hypothesis that background subtraction adequately accounts for intrarenal fat deposition in mildly obese human subjects during renal contrast enhanced dynamic CT. MATERIALS AND METHODS: We prospectively recruited seventeen human subjects stratified as lean or mildly obese based on body mass index below or over 30 kg/m2, respectively. Renal perfusion was quantified from CT-derived indicator-dilution curves after background subtraction. Dual-energy MDCT images were postprocessed to generate iodine and virtual-noncontrast datasets, and the ratios between kidney/aorta CT numbers and iodine values calculated as surrogates of renal function. RESULTS: Subcutaneous adipose tissue was increased in obese subjects. Virtual-noncontrast maps revealed in obese patients a decrease in basal cortical and medullary attenuation. Overall, basal attenuation inversely correlated with body mass index, in line with renal fat deposition. Contrarily, the kidney/aorta CT attenuation (after background subtraction) and kidney/aorta iodine ratios were similar between lean and obese subjects and correlated directly. These observations show that following background subtraction, the CT number reliably reflects basal tissue attenuation. CONCLUSION: Therefore, our findings support our hypothesis that background subtraction enables reliable assessment of kidney function in mildly obese subjects using MDCT, despite decreased basal attenuation due to renal adiposity.

Clinical Assessment of Metal Artifact Reduction Methods in Dual-Energy CT Examinations of Instrumented Spines.

OBJECTIVE: The purpose of this study was to evaluate the performance of three metal artifact reduction methods in dual-energy CT (DECT) examinations of instrumented spines. MATERIALS AND METHODS: Twenty patients with instrumented spines who underwent spine DECT were retrospectively identified. All scans were obtained on a dual-source 128-MDCT scanner. In addition to the original DE mixed images, DECT images were reconstructed using an iterative metal artifact reconstruction algorithm (DE iMAR), virtual monochromatic imaging (VMI) algorithm (DE Mono+), and a combination of the two algorithms DE iMAR and DE Mono+, which we refer to here as "DE iMAR Mono+." The four image series were anonymized and randomized for a reader study. Four experienced neuroradiologists rated the images in terms of artifact scores of four anatomic regions and overall image quality scores in both bone and soft-tissue display window settings. In addition, a quantitative analysis was performed to assess the performance of the three metal artifact reduction methods. RESULTS: There were statistically significant differences in the artifact scores and overall image quality scores among the four methods (both, p < 0.001). DE iMAR Mono+ showed the best artifact scores and quality scores (all, p < 0.001). The intraclass correlation coefficient for the overall image quality score was 0.779 using the bone display window and 0.892 using the soft-tissue display window (both, p < 0.001). In addition, DE iMAR Mono+ reduced the artifacts by the greatest amount in the quantitative analysis. CONCLUSION: The method that used DE iMAR Mono+ showed the best performance of spine metal artifact reduction using DECT data. These results may be specific to this CT vendor and implant type.

Findings of CT-Derived Bone Strength Assessment in Inflammatory Bowel Disease Patients Undergoing CT Enterography in Clinical Practice.

BACKGROUND: Inflammatory bowel disease (IBD) patients are at risk of developing complications from metabolic bone disease, but the exact prevalence is unknown. We evaluated fracture risk in IBD patients using (1) biomechanical CT analysis (BCT) using bone strength and bone mineral density (BMD), (2) Cornerstone guidelines, and (3) other clinical features predicting fracture risk. METHODS: A retrospective review of consecutive IBD patients who underwent CT enterography (CTE) with BCT from March 2014 to March 2017 was performed. Measured outcomes were overall fracture risk classification (not increased, increased, or high) and femoral neck BMD World Health Organization classification (normal, osteopenia, or osteoporosis). RESULTS: Two hundred fifty-seven patients with IBD underwent CTE and BCT. Fracture risk was classified as not increased in 45.5% (116/255) of patients, increased in 44.7% (114/255), and high in 9.8% (25/255). Femoral neck BMD was classified as normal in 56.8% (142/250), osteopenia in 37.6% (94/250), and osteoporosis in 5.6% (14/250). In multivariate analysis, only increasing age was associated with increased fracture risk (odds ratio, 1.06; 95% confidence interval, 1.04-1.08; P < 0.001). Cornerstone guidelines were met by 35.3% (41/116), 56.1% (64/114), and 76.0% (19/25) of patients in the not increased, increased, and high-risk groups, respectively (P = 0.0001). No Cornerstone criteria were met by 40% (56/139) of patients in the increased and high-risk groups. CONCLUSIONS: Using BCT, increased or high fracture risk was detected in more than half of this cohort, the prevalence being associated with increased age. A significant proportion of patients with increased or high fracture risk did not meet Cornerstone guidelines. Therefore, IBD patients who do not meet Cornerstone guidelines may benefit from BCT screening.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

PURPOSE: The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. METHODS: Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo). RESULTS: When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%. CONCLUSIONS: Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.

Assessment of Low-Contrast Resolution for the American College of Radiology Computed Tomographic Accreditation Program: What Is the Impact of Iterative Reconstruction?

OBJECTIVE: To compare contrast-to-noise ratio (CNR) thresholds with visual assessment of low-contrast resolution (LCR) in filtered back projection (FBP) and iteratively reconstructed (IR) computed tomographic (CT) images. METHODS: American College of Radiology (ACR) CT accreditation phantom LCR images were acquired at CTDIvol levels of 8, 12, and 16 mGy using 2 scanner models and reconstructed using one FBP and 2 IR kernels. Acquisitions were repeated 100 times. Three board-certified medical physicists blindly reviewed the LCR section images. Pass-percentage rates (PPRs) using previous and current ACR CT accreditation criteria were compared. RESULTS: Observer PPRs for FBP images were less than 32%. For IR images, 5 of 18 settings/dose/model configurations had PPRs greater than 32% (maximum 76.3%). For CNR evaluation of FBP images, PPRs for 15 configurations were greater than 70%. For IR images, all PPRs were at least 96%. CONCLUSIONS: The CNR threshold used by the ACR CT accreditation program yields higher PPRs than visual assessment of LCR, potentially resulting in lower-quality images passing the ACR CNR criteria.

Neutron activation analysis with a Monte Carlo simulation for kidney stones.

Mechanistic questions regarding kidney stone formation have led researchers to look for the presence of trace elements. Neutron activation analysis is able to identify elements at parts-per-million concentrations. Four different types of kidney stones were irradiated with thermal neutrons to produce radioisotopes. Gamma spectroscopy of samples at different counting times was used to reduce identification errors by correlating results with the half-life of identified elements. For more precise identification, Monte Carlo simulation was used to cross-check the identification process. The simulation showed promising results that could lead to fast and accurate identification of trace elements as the simulation code is improved. Sodium (Na), potassium (K), calcium (Ca), bromine (Br), samarium (Sm), zinc (Zn), cadmium (Cd), ytterbium (Yb), gold (Au), cobalt (Co), and manganese (Mn) were identified as being present in the stones, by both the experimentally measured gamma spectrum and the simulation. Among these, Ca, Br, and Zn were found to be of potential clinical relevance via a literature review. Concentrations of the elements were compared to those noted in the literature. For uric acid stones, a correlation with the literature was found for Zn and Ca. A negative correlation was found between Zn and Br for non-uric acid stones. More samples are needed to test for statistical significance.

Construction of Realistic Liver Phantoms from Patient Images using 3D Printer and Its Application in CT Image Quality Assessment.

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.

Automated assessment of renal cortical surface roughness from computerized tomography images and its association with age.

RATIONALE AND OBJECTIVES: Nephrosclerosis occurs with aging and is characterized by increased kidney subcapsular surface irregularities at autopsy. Assessments of cortical roughness in vivo could provide an important measure of nephrosclerosis. The purpose of this study was to develop and validate an image-processing algorithm for quantifying renal cortical surface roughness in vivo and determine its association with age. MATERIALS AND METHODS: Renal cortical surface roughness was measured on contrast-enhanced abdominal computed tomography (CT) images of potential living kidney donors. A roughness index was calculated based on geometric curvature of each kidney from three-dimensional images and compared to visual observation scores. Cortical roughness was compared between the oldest and youngest donors, and its interaction with cortical volume and age assessed. RESULTS: The developed quantitative roughness index identified significant differences in kidneys with visual surface roughness scores of 0 (minimal), 1 (mild), and 2 (moderate; P < .001) in a random sample of 200 potential kidney donors. Cortical roughness was significantly higher in the 94 oldest (64-75 years) versus 91 youngest (18-25 years) potential kidney donors (P < .001). Lower cortical volume was associated with older age but not with roughness (r = -0.03, P = .75). The association of oldest age group with roughness (odds ratio [OR] = 1.8 per standard deviation [SD] of roughness index) remained significant after adjustment for total cortex volume (OR = 2.0 per SD of roughness index). CONCLUSIONS: A new algorithm to measure renal cortical surface roughness from CT scans detected rougher surface in older compared to younger kidneys, independent of cortical volume loss. This novel index may allow quantitative evaluation of nephrosclerosis in vivo using contrast-enhanced CT.

Estimating peak skin and eye lens dose from neuroperfusion examinations: use of Monte Carlo based simulations and comparisons to CTDIvol, AAPM Report No. 111, and ImPACT dosimetry tool values.

PURPOSE: CT neuroperfusion examinations are capable of delivering high radiation dose to the skin or lens of the eyes of a patient and can possibly cause deterministic radiation injury. The purpose of this study is to: (a) estimate peak skin dose and eye lens dose from CT neuroperfusion examinations based on several voxelized adult patient models of different head size and (b) investigate how well those doses can be approximated by some commonly used CT dose metrics or tools, such as CTDIvol, American Association of Physicists in Medicine (AAPM) Report No. 111 style peak dose measurements, and the ImPACT organ dose calculator spreadsheet. METHODS: Monte Carlo simulation methods were used to estimate peak skin and eye lens dose on voxelized patient models, including GSF's Irene, Frank, Donna, and Golem, on four scanners from the major manufacturers at the widest collimation under all available tube potentials. Doses were reported on a per 100 mAs basis. CTDIvol measurements for a 16 cm CTDI phantom, AAPM Report No. 111 style peak dose measurements, and ImPACT calculations were performed for available scanners at all tube potentials. These were then compared with results from Monte Carlo simulations. RESULTS: The dose variations across the different voxelized patient models were small. Dependent on the tube potential and scanner and patient model, CTDIvol values overestimated peak skin dose by 26%-65%, and overestimated eye lens dose by 33%-106%, when compared to Monte Carlo simulations. AAPM Report No. 111 style measurements were much closer to peak skin estimates ranging from a 14% underestimate to a 33% overestimate, and with eye lens dose estimates ranging from a 9% underestimate to a 66% overestimate. The ImPACT spreadsheet overestimated eye lens dose by 2%-82% relative to voxelized model simulations. CONCLUSIONS: CTDIvol consistently overestimates dose to eye lens and skin. The ImPACT tool also overestimated dose to eye lenses. As such they are still useful as a conservative predictor of dose for CT neuroperfusion studies. AAPM Report No. 111 style measurements are a better predictor of both peak skin and eye lens dose than CTDIvol and ImPACT for the patient models used in this study. It should be remembered that both the AAPM Report No. 111 peak dose metric and CTDIvol dose metric are dose indices and were not intended to represent actual organ doses.

Attenuation-based estimation of patient size for the purpose of size specific dose estimation in CT. Part I. Development and validation of methods using the CT image.

PURPOSE: For the purpose of size-specific dose estimation, information regarding patient attenuation is required. The purpose of this work is to describe a method for measuring patient attenuation and expressing the results in terms of a water cylinder, with cross sectional area A(w), which would absorb the same average dose as the irradiated patient. The ability to calculate A(w) directly from the CT image was validated with Monte Carlo simulations and an analytical model. METHODS: A series of virtual cylinders were created with diameters ranging from 10 to 40 cm and lengths of 40 cm. The cylinders were given an atomic number equal to that of water; the density of the cylinders was varied from 0.26 to 1.2 g∕cm(3). The average dose to the cylinders from an axial scan at the longitudinal center position was calculated using Monte Carlo simulation and an analytical model. The relationship between phantom cross sectional area and calculated dose was determined for each density value to determine the dependence of A(w) on object attenuation. In addition, A(w) was estimated from the virtual CT images based on two derived models expressing the potential dependence of A(w) on object attenuation, one model assuming a linear dependence and the other assuming a quadratic dependence. Model results were compared with those from the Monte Carlo simulation and the analytical dose calculation approach. Virtual thorax and abdomen phantoms of adult and pediatric sizes were created, and A(w) was estimated using geometrical size parameters or the derived models. The accuracy of each approach for estimating A(w) was determined by comparing the average dose to the virtual phantom calculated using Monte Carlo simulation to the average dose to a water equivalent phantom of cross sectional area A(w). RESULTS: In the absence of a bowtie filter, both the Monte Carlo simulation and analytical model showed that (A(w)∕A) had a quadratic dependence on (µ∕µ(w)). However, including a bowtie filter in the Monte Carlo simulation altered the relationship, such that A(w)∕A was linearly dependent on µ∕µ(w). Using this relationship, the dose absorbed by a water cylinder of area A(w) agreed with the dose absorbed by adult and pediatric, thorax and abdomen phantoms to within 6% (mean difference = 0.5 ± 4.8%). Estimates of A(w) (or the water equivalent diameter D(w)) using only anterior-posterior and lateral phantom dimensions led to dose estimates that agreed with Monte Carlo-derived dose values within 3% and 6% for the abdomen adult and pediatric phantoms, respectively. However, because of density differences between lung and tissue, larger differences in dose relative to Monte Carlo-derived values were observed in the thorax adult and pediatric phantoms (15% and 11%, respectively) when only geometrical parameters were used to estimate D(w). CONCLUSIONS: Patient attenuation can be quantified in terms of the diameter of a water cylinder that absorbs same average dose as the irradiated cross section of the patient. The linear dependence of A(w) on object attenuation makes it straightforward to calculate A(w) from a CT image on most operator consoles or clinical workstations.

Lowering kilovoltage to reduce radiation dose in contrast-enhanced abdominal CT: initial assessment of a prototype automated kilovoltage selection tool.

OBJECTIVE: The purpose of this study was to determine whether the use of an automated CT kilovoltage (kV) selection tool (Auto kV) can result in lower radiation dose without sacrificing image quality in contrast-enhanced abdominopelvic CT. MATERIALS AND METHODS: Tube potential, radiation dose, and iodine contrast-to-noise ratio (CNR) were retrospectively evaluated in 36 patients who underwent abdominopelvic CT with Auto kV, and compared with results from size-matched control patients using identical protocols. Two radiologists evaluated image quality (sharpness, noise, and diagnostic confidence) blinded to kV. Volume CT dose index (CTDI(vol)) was also compared with what each patient would have received from scanning at 120 kV. RESULTS: Mean (SD) CTDI(vol) was 16.0 (4.4) mGy after Auto kV versus 19.5 (4.0) mGy using standard 120-kV prescription and was 19.3 (6.0) mGy in control subjects (yielding dose reductions of 18.0% and 17.2%, respectively; p < 0.001 for both). Thirty of 36 patients were scanned at 100 kV (median dose reduction, 25%). Auto kV images were rated as very sharp in 33 (92%) and 36 (100%) cases versus 36 (100%) and 35 (97%) of the control cases, with all cases scored as having optimal noise. Readers had full diagnostic confidence in 34 (94%) and 36 (100%) of Auto kV cases; one reader scored "probably confident" in two cases (6%). Iodine CNRs for the aorta, liver, and portal vein were similar between Auto kV cases and control cases (p > 0.50, all comparisons). CONCLUSION: The use of an automated kV selection tool results in significant dose savings while maintaining diagnostic image quality and iodine CNR.

Validation of dual-source single-tube reconstruction as a method to obtain half-dose images to evaluate radiation dose and noise reduction: phantom and human assessment using CT colonography and sinogram-affirmed iterative reconstruction (SAFIRE).

OBJECTIVE: To evaluate a method for obtaining half-dose CT images for observer studies evaluating lower-dose CT. METHODS: Phantoms of varying sizes were scanned at multiple tube potentials using dose-matched dual-source (DS) and single-source (SS) protocols. Images from single-tube reconstruction of DS data were compared with SS images acquired at half-original CTDIvol. Thirty patients underwent supine SS and dose-matched prone DS CT colonography (CTC). Half-dose prone images were reconstructed with sinogram-affirmed iterative reconstruction (SAFIRE). Two radiologists scored image quality on 2-dimensional (2D) and 3D images. RESULTS: Image noise was similar between half-dose SS images and DS images reconstructed from one tube only with tube potential of 120 kV or more for phantoms 40 cm or smaller (P < 0.05). For both readers, the patients' CTC image quality scores were more than 84% concordant between SS or DS CTC images, and half-dose-prone CTC images with SAFIRE had 84% or more concordance with routine-dose CTC except for 3D image noise. CONCLUSIONS: In appropriately sized patients, DS acquisition with single-tube reconstruction can create half-dose images, permitting comparison to full-dose images. For CTC, there is comparable image quality for colonic evaluation between full-dose and half-dose images reconstructed with SAFIRE.

Peak skin and eye lens radiation dose from brain perfusion CT based on Monte Carlo simulation.

OBJECTIVE: The purpose of our study was to accurately estimate the radiation dose to skin and the eye lens from clinical CT brain perfusion studies, investigate how well scanner output (expressed as volume CT dose index [CTDI(vol)]) matches these estimated doses, and investigate the efficacy of eye lens dose reduction techniques. MATERIALS AND METHODS: Peak skin dose and eye lens dose were estimated using Monte Carlo simulation methods on a voxelized patient model and 64-MDCT scanners from four major manufacturers. A range of clinical protocols was evaluated. CTDI(vol) for each scanner was obtained from the scanner console. Dose reduction to the eye lens was evaluated for various gantry tilt angles as well as scan locations. RESULTS: Peak skin dose and eye lens dose ranged from 81 mGy to 348 mGy, depending on the scanner and protocol used. Peak skin dose and eye lens dose were observed to be 66-79% and 59-63%, respectively, of the CTDI(vol) values reported by the scanners. The eye lens dose was significantly reduced when the eye lenses were not directly irradiated. CONCLUSION: CTDI(vol) should not be interpreted as patient dose; this study has shown it to overestimate dose to the skin or eye lens. These results may be used to provide more accurate estimates of actual dose to ensure that protocols are operated safely below thresholds. Tilting the gantry or moving the scanning region further away from the eyes are effective for reducing lens dose in clinical practice. These actions should be considered when they are consistent with the clinical task and patient anatomy.

Dynamic CT technique for assessment of wrist joint instabilities.

PURPOSE: To develop a 4D [three-dimensional (3D) + time] CT technique to capture high spatial and temporal resolution images of wrist joint motion so that dynamic joint instabilities can be detected before the development of static joint instability and onset of osteoarthritis (OA). METHODS: A cadaveric wrist was mounted onto a custom motion simulator and scanned with a dual source CT scanner during radial-ulnar deviation. A dynamic 4D CT technique was utilized to reconstruct images at 20 equidistant time points from one motion cycle. 3D images of carpal bones were generated using volume rendering techniques (VRT) at each of the 20 time points and then 4D movies were generated to depict the dynamic joint motion. The same cadaveric wrist was also scanned after cutting all portions of the scapholunate interosseus ligament to simulate scapholunate joint instability. Image quality were assessed on an ordinal scale (1-4, 4 being excellent) by three experienced orthopedic surgeons (specialized in hand surgery) by scoring 2D axial images. Dynamic instability was evaluated by the same surgeons by comparing the two 4D movies of joint motion. Finally, dose reduction was investigated using the cadaveric wrist by scanning at different dose levels to determine the lowest radiation dose that did not substantially alter diagnostic image quality. RESULTS: The mean image quality scores for dynamic and static CT images were 3.7 and 4.0, respectively. The carpal bones, distal radius and ulna, and joint spaces were clearly delineated in the 3D VRT images, without motion blurring or banding artifacts, at all time points during the motion cycle. Appropriate viewing angles could be interactively selected to view any articulating structure using different 3D processing techniques. The motion of each carpal bone and the relative motion among the carpal bones were easily observed in the 4D movies. Joint instability was correctly and easily detected in the scan performed after the ligament was cut by observing the relative motion between the scaphoid and lunate bones. Diagnostic capability was not sacrificed with a volume CT dose index (CTDI(vol)) as low as 18 mGy for the whole scan, with estimated skin dose of approximately 33 mGy, which is much lower than the threshold for transient skin erythema (2000 mGy). CONCLUSIONS: The proposed dynamic 4D CT imaging technique generated high spatial and high temporal resolution images without requiring periodic joint motion. Preliminary results from this cadaveric study demonstrate the feasibility of detecting joint instability using this technique.

The feasibility of a scanner-independent technique to estimate organ dose from MDCT scans: using CTDIvol to account for differences between scanners.

PURPOSE: Monte Carlo radiation transport techniques have made it possible to accurately estimate the radiation dose to radiosensitive organs in patient models from scans performed with modern multidetector row computed tomography (MDCT) scanners. However, there is considerable variation in organ doses across scanners, even when similar acquisition conditions are used. The purpose of this study was to investigate the feasibility of a technique to estimate organ doses that would be scanner independent. This was accomplished by assessing the ability of CTDIvol measurements to account for differences in MDCT scanners that lead to organ dose differences. METHODS: Monte Carlo simulations of 64-slice MDCT scanners from each of the four major manufacturers were performed. An adult female patient model from the GSF family of voxelized phantoms was used in which all ICRP Publication 103 radiosensitive organs were identified. A 120 kVp, full-body helical scan with a pitch of 1 was simulated for each scanner using similar scan protocols across scanners. From each simulated scan, the radiation dose to each organ was obtained on a per mA s basis (mGy/mA s). In addition, CTDIvol values were obtained from each scanner for the selected scan parameters. Then, to demonstrate the feasibility of generating organ dose estimates from scanner-independent coefficients, the simulated organ dose values resulting from each scanner were normalized by the CTDIvol value for those acquisition conditions. RESULTS: CTDIvol values across scanners showed considerable variation as the coefficient of variation (CoV) across scanners was 34.1%. The simulated patient scans also demonstrated considerable differences in organ dose values, which varied by up to a factor of approximately 2 between some of the scanners. The CoV across scanners for the simulated organ doses ranged from 26.7% (for the adrenals) to 37.7% (for the thyroid), with a mean CoV of 31.5% across all organs. However, when organ doses are normalized by CTDIvoI values, the differences across scanners become very small. For the CTDIvol, normalized dose values the CoVs across scanners for different organs ranged from a minimum of 2.4% (for skin tissue) to a maximum of 8.5% (for the adrenals) with a mean of 5.2%. CONCLUSIONS: This work has revealed that there is considerable variation among modern MDCT scanners in both CTDIvol and organ dose values. Because these variations are similar, CTDIvol can be used as a normalization factor with excellent results. This demonstrates the feasibility of establishing scanner-independent organ dose estimates by using CTDIvol to account for the differences between scanners.

Estimating effective dose for CT using dose-length product compared with using organ doses: consequences of adopting International Commission on Radiological Protection publication 103 or dual-energy scanning.

OBJECTIVE: The objective of our study was to compare dose-length product (DLP)-based estimates of effective dose with organ dose-based calculations using tissue-weighting factors from publication 103 of the International Commission on Radiological Protection (ICRP) or dual-energy CT protocols. MATERIALS AND METHODS: Using scanner- and energy-dependent organ dose coefficients, we calculated effective doses for CT examinations of the head, chest, coronary arteries, liver, and abdomen and pelvis using routine clinical single- or dual-energy protocols and tissue-weighting factors published in 1991 in ICRP publication 60 and in 2007 in ICRP publication 103. Effective doses were also generated from the respective DLPs using published conversion coefficients that depend only on body region. For each examination type, the same volume CT dose index was used for single- and dual-energy scans. RESULTS: Effective doses calculated for CT examinations using organ dose estimates and ICRP 103 tissue-weighting factors differed relative to ICRP 60 values by -39% (-0.5 mSv, head), 14% (1 mSv, chest), 36% (4 mSv, coronary artery), 4% (0.6 mSv, liver), and -7% (-1 mSv, abdomen and pelvis). DLP-based estimates of effective dose, which were derived using ICRP 60-based conversion coefficients, were less than organ dose-based estimates for ICRP 60 by 4% (head), 23% (chest), 37% (coronary artery), 12% (liver), and 19% (abdomen and pelvis) and for ICRP 103 by -34% (head), 37% (chest), 74% (coronary artery), 16% (liver), and 12% (abdomen and pelvis). All results were energy independent. CONCLUSION: These differences in estimates of effective dose suggest the need to reassess DLP to E conversion coefficients when adopting ICRP 103, particularly for scans over the breast. For the evaluated scanner, DLP to E conversion coefficients were energy independent, but ICRP 60-based conversion coefficients underestimated effective dose relative to organ dose-based calculations.