Matthew K. Fuld

Abdominal Imaging with Contrast-enhanced Photon-counting CT: First Human Experience

PURPOSE To evaluate the performance of a prototype photon-counting detector (PCD) computed tomography (CT) system for abdominal CT in humans and to compare the results with a conventional energy-integrating detector (EID). MATERIALS AND METHODS The study was HIPAA-compliant and institutional review board-approved with informed consent. Fifteen asymptomatic volunteers (seven men; mean age, 58.2 years ± 9.8 [standard deviation]) were prospectively enrolled between September 2 and November 13, 2015. Radiation dose-matched delayed contrast agent-enhanced spiral and axial abdominal EID and PCD scans were acquired. Spiral images were scored for image quality (Wilcoxon signed-rank test) in five regions of interest by three radiologists blinded to the detector system, and the axial scans were used to assess Hounsfield unit accuracy in seven regions of interest (paired t test). Intraclass correlation coefficient (ICC) was used to assess reproducibility. PCD images were also used to calculate iodine concentration maps. Spatial resolution, noise-power spectrum, and Hounsfield unit accuracy of the systems were estimated by using a CT phantom. RESULTS In both systems, scores were similar for image quality (median score, 4; P = .19), noise (median score, 3; P = .30), and artifact (median score, 1; P = .17), with good interrater agreement (image quality, noise, and artifact ICC: 0.84, 0.88, and 0.74, respectively). Hounsfield unit values, spatial resolution, and noise-power spectrum were also similar with the exception of mean Hounsfield unit value in the spinal canal, which was lower in the PCD than the EID images because of beam hardening (20 HU vs 36.5 HU; P < .001). Contrast-to-noise ratio of enhanced kidney tissue was improved with PCD iodine mapping compared with EID (5.2 ± 1.3 vs 4.0 ± 1.3; P < .001). CONCLUSION The performance of PCD showed no statistically significant difference compared with EID when the abdomen was evaluated in a conventional scan mode. PCD provides spectral information, which may be used for material decomposition.

Sinogram Affirmed Iterative Reconstruction (SAFIRE) versus weighted filtered back projection (WFBP) effects on quantitative measure in the COPDGene 2 test object

PURPOSE Assessing pulmonary emphysema using Quantitative CT of the lung depends on accurate measures of CT density. Sinogram-Affirmed-Iterative-Reconstruction (SAFIRE) is a new approach for reconstructing CT data acquired at significantly lower doses. However, quantitative effects of this method remain unexplored. The authors investigated the effects on the median values of materials in the COPDGene2 test-object as a function of the reconstruction method [weighted filtered back projection (WFBP) versus SAFIRE], test-object size, dose, and material composition using a Siemens SOMATOM Definition FLASH CT scanner. METHODS The COPDGene2 test-object contains eight materials; acrylic, water, four foams (20 lb, 12 lb, lung-equivalent, and 4 lb emphysema-equivalent), internal and external-air. The test-object was scanned with three different outer ring sizes, simulating three different body habitus. There is an average size (36 cm) Ring A, large size (40 cm) Ring B, and small size Ring C (30 cm). The CT protocol used 120 kVp, 0.5 s rotation, 1.0 pitch, and a 0.6 slice collimation with progressively decreasing x-ray exposure values, 11.94-0.74 mGy. With a thorax length of 30 cm, the corresponding effective doses would be 5.01-0.31 mSv. The effects of using SAFIRE versus WFBP were assessed using a two tailed t-test for each ring size, material, and dose. Multivariable linear regression was used to evaluate the relative effects of ring size, material composition, dose, and reconstruction method on the measured median value in HU. RESULTS SAFIRE versus WFBP, at the largest ring size and two lowest doses there was a significant difference in median values of 4 lb-foam, p<0.01. Using the smallest ring size at the lowest dose level there was a significant difference in the median value of 4 lb-foam, but the effect size was small, 1 HU. There is a significant difference in median values of both internal and external air using both the small and medium size rings at the three lowest dose levels, p<0.05. There are significant differences noted at both high and low dose levels when using the large ring size in the median values of internal and external air when, p<0.05. These effects on 4 lb-foam, inside and outside air are shown to be in part due to truncation effects on the median value since the lowest HU value in the CT scale used is -1024 HU. Multivariable linear regression results demonstrated significant effects on the measured material median value and standard deviation due to ring size, material composition, dose level, and reconstruction method, p<0.05. CONCLUSIONS The authors have shown that there is no significant effect on the median values obtained when using WFBP versus SAFIRE in materials with CT density between 120 and -856 HU using three different test-object sizes and CT doses that vary from 11.94 to 0.74 mGy. The authors have demonstrated there are significant effects on median values obtained when using WFBP versus SAFIRE in materials with CT density values between -937 and -1000 HU depending on the ring size and dose used. As expected, there is considerable reduction in image noise (lower standard deviation) using SAFIRE versus WFBP with all ring sizes, doses, and materials in the COPDGene2 test-object.

Low-dose lung cancer screening with photon-counting CT: a feasibility study

To evaluate the feasibility of using a whole-body photon-counting detector (PCD) CT scanner for low-dose lung cancer screening compared to a conventional energy integrating detector (EID) system. Radiation dose-matched EID and PCD scans of the COPDGene 2 phantom were acquired at different radiation dose levels (CTDIvol: 3.0, 1.5, and 0.75 mGy) and different tube voltages (120, 100, and 80 kVp). EID and PCD images were compared for quantitative Hounsfield unit (HU) accuracy, noise levels, and contrast-to-noise ratios (CNR) for detection of ground-glass nodules (GGN) and emphysema. The PCD HU accuracy was better than EID for water at all scan parameters. PCD HU stability for lung, GGN and emphysema regions were superior to EID and PCD attenuation values were more reproducible than EID for all scan parameters (all P  <  0.01), while HUs for lung, GGN and emphysema ROIs changed significantly for EID with decreasing dose (all P  <  0.001). PCD showed lower noise levels at the lowest dose setting at 120, 100 and 80 kVp (15.2  ±  0.3 HU versus 15.8  ±  0.2 HU, P  =  0.03; 16.1  ±  0.3 HU versus 18.0  ±  0.4 HU, P  =  0.003; and 16.1  ±  0.3 HU versus 17.9  ±  0.3 HU, P  =  0.001, respectively), resulting in superior CNR for evaluation of GGNs and emphysema at 100 and 80 kVp. PCD provided better HU stability for lung, ground-glass, and emphysema-equivalent foams at lower radiation dose settings with better reproducibility than EID. Additionally, PCD showed up to 10% less noise, and 11% higher CNR at 0.75 mGy for both 100 and 80 kVp. PCD technology may help reduce radiation exposure in lung cancer screening while maintaining diagnostic quality.

Standardizing CT lung density measure across scanner manufacturers

Purpose: Computed Tomography (CT) imaging of the lung, reported in Hounsfield Units (HU), can be parameterized as a quantitative image biomarker for the diagnosis and monitoring of lung density changes due to emphysema, a type of chronic obstructive pulmonary disease (COPD). CT lung density metrics are global measurements based on lung CT number histograms, and are typically a quantity specifying either the percentage of voxels with CT numbers below a threshold, or a single CT number below which a fixed relative lung volume, nth percentile, falls. To reduce variability in the density metrics specified by CT attenuation, the Quantitative Imaging Biomarkers Alliance (QIBA) Lung Density Committee has organized efforts to conduct phantom studies in a variety of scanner models to establish a baseline for assessing the variations in patient studies that can be attributed to scanner calibration and measurement uncertainty. Methods: Data were obtained from a phantom study on CT scanners from four manufacturers with several protocols at various tube potential voltage (kVp) and exposure settings. Free from biological variation, these phantom studies provide an assessment of the accuracy and precision of the density metrics across platforms solely due to machine calibration and uncertainty of the reference materials. The phantom used in this study has three foam density references in the lung density region, which, after calibration against a suite of Standard Reference Materials (SRM) foams with certified physical density, establishes a HU‐electron density relationship for each machine‐protocol. We devised a 5‐step calibration procedure combined with a simplified physical model that enabled the standardization of the CT numbers reported across a total of 22 scanner‐protocol settings to a single energy (chosen at 80 keV). A standard deviation was calculated for overall CT numbers for each density, as well as by scanner and other variables, as a measure of the variability, before and after the standardization. In addition, a linear mixed‐effects model was used to assess the heterogeneity across scanners, and the 95% confidence interval of the mean CT number was evaluated before and after the standardization. Results: We show that after applying the standardization procedures to the phantom data, the instrumental reproducibility of the CT density measurement of the reference foams improved by more than 65%, as measured by the standard deviation of the overall mean CT number. Using the lung foam that did not participate in the calibration as a test case, a mixed effects model analysis shows that the 95% confidence intervals are [−862.0 HU, −851.3 HU] before standardization, and [‐859.0 HU, −853.7 HU] after standardization to 80 keV. This is in general agreement with the expected CT number value at 80 keV of −855.9 HU with 95% CI of [−857.4 HU, −854.5 HU] based on the calibration and the uncertainty in the SRM certified density. Conclusions: This study provides a quantitative assessment of the variations expected in CT lung density measures attributed to non‐biological sources such as scanner calibration and scanner x‐ray spectrum and filtration. By removing scanner‐protocol dependence from the measured CT numbers, higher accuracy and reproducibility of quantitative CT measures were attainable. The standardization procedures developed in study may be explored for possible application in CT lung density clinical data.

Dual-energy computed tomography of the knee, ankle, and foot: noninvasive diagnosis of gout and quantification of monosodium urate in tendons and ligaments

Gout is a true crystal deposition arthropathy caused by the precipitation of monosodium urate into joints and periarticular soft tissues. It is the most common inflammatory arthropathy in men and women of older age with a male-to-female ratio of 3 to 8:1. The disease may progress from asymptomatic hyperuricemia through symptomatic acute gout attacks with asymptomatic periods into chronic symptomatic tophaceous gout. Although invasive arthrocentesis and demonstration of monosodium urate crystals on polarized light microscopy is definitive for the diagnosis of gout, dual-energy computed tomography (CT) allows for noninvasive visualization and reproducible volume quantification of monosodium urate crystals. Based on the high diagnostic performance, dual-energy CT has been included in the 2015 American College of Rheumatology/European League Against Rheumatism Collaborative Initiative Classification Criteria for Gout. Increasing evidence indicates the usefulness of dual-energy CT to guide the management of patients with suspected gout and monitor the effectiveness of urate-lowering medical therapy.

New Approaches to Reduce Radiation While Maintaining Image Quality in Multi-Detector-Computed Tomography

This review discusses new technological approaches to reduce radiation dose while maintaining image quality in multi-detector-computed tomography (CT) for both adult and pediatric applications. First, the review focuses on the principles of automatic exposure control (AEC) systems for modulation of the tube current according to patient’s size; as well as special AEC adaptations for cardiac CT and organ-based tube current modulation. The selection of the tube potential (kV) is also discussed, with particular emphasis in a new technology which allows an automatic selection of the tube potential with a corresponding adjustment in the tube current, according to patient’s size and diagnostic task. The principles of iterative reconstruction, which is quickly becoming a standard feature in CT scanners, are also presented with particular emphasis on dose reduction and image quality. A full section is devoted to two latest state-of-the-art applications which can be used for radiation dose reduction: virtual non-contrast imaging with dual-energy CT and ultra-low dose CT with added spectral filtration. In the final section, innovations in CT hardware are presented ranging from the X-ray tube to CT detectors, which enable data acquisition at faster speeds and better efficiency to improve the balance between radiation dose and image quality.

Assessment of iodine uptake by pancreatic cancer following chemotherapy using dual-energy CT

AbstractPancreatic cancer remains a major health problem, and only less than 20% of patients have resectable disease at the time of initial diagnosis. Systemic chemotherapy is often used in the patients with borderline resectable, locally advanced unresectable disease and metastatic disease. CT is often used to assess for therapeutic response; however, conventional imaging including CT may not correctly reflect treatment response after chemotherapy. Dual-energy (DE) CT can acquire datasets at two different photon spectra in a single CT acquisition, and permits separating materials and extract iodine by applying a material decomposition algorithm. Quantitative iodine mapping may have an added value over conventional CT imaging for monitoring the treatment effects in patients with pancreatic cancer and potentially serve as a unique biomarker for treatment response. In this pictorial essay, we will review the technique for iodine quantification of pancreatic cancer by DECT and discuss our observations of iodine quantification at baseline and after systemic chemotherapy with conventional cytotoxic agents, and illustrate example cases.

Workflow Design for CT of the Thorax

CT technology continues to evolve at a high rate providing higher dose efficiency, faster scanning speeds, and improved image quality. As such, one can argue that CT technology already provides adequate image quality for most diagnostic tasks in areas such as thoracic CT. Moreover, the acquisition time of many examinations, such as those of the thorax, can be well below one second, thus addressing major issues such as motion artifacts. However, the management of a patient within a typical radiology department or imaging center implies other workflow aspects that go beyond just the CT scan itself. Aspects that impact the workflow can be associated with each individual patient, the CT technologists and nurses, or radiologists and referring physicians. Hence, an important question arises such as how to address consistency in CT scanning in the era of personalized medicine? With the substantial increase in imaging data generated per examination, which can well exceed 1000 images per study in daily practice, another issue of concern is how quickly exams can be read after CT acquisition is complete, with data transfer speeds being a major limiting factor for the radiologists and referring physicians. Hence, we must endeavor to determine whether there are smarter ways to analyze or preprocess this information such that we can reduce the time required for interpretation by radiologists in order to reach a diagnosis. Or at the very least can we utilize these new workflow tools to improve accuracy? The answer to this question is heavily associated with the design of new workflows.