Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.

Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease. Image analysis was fully automated and did not require specific user interaction. The thoracolumbar spine was segmented by a pretrained convolutional neuronal network. Volumetric VNCa data of the spine's bone marrow space were processed using the maximum, medium, and low calcium suppression indices. Histograms of VNCa attenuation were created for each exam and suppression setting. We included 500 exams of 168 individuals (88 female, patient age 61.0 ± 15.9). A total of 8298 vertebrae were segmented. The attenuation histograms' overlap of two consecutive exams, as a measure for intraindividual consistency, yielded a median of 0.93 (IQR: 0.88-0.96). As our main result, we provide the age- and sex-specific bone marrow attenuation profiles of a large-scale cohort of individuals with healthy trabecular bone structure as a reference for future studies. We conclude that artificial-intelligence-supported, fully automated volumetric assessment is an intraindividually robust method to image the spine's bone marrow using VNCa data from DECT.

Detection of patients with chronic thromboembolic pulmonary hypertension by volumetric iodine quantification in the lung-a case control study.

BACKGROUND: To evaluate whether volumetric iodine quantification of the lung allows for the automatic identification of patients with chronic thromboembolic pulmonary hypertension (CTEPH) and whether the extent of pulmonary malperfusion correlates with invasive hemodynamic parameters. METHODS: Retrospective data base search identified 30 consecutive patients with CTEPH who underwent CT pulmonary angiography (CTPA) on a spectral-detector CT scanner. Thirty consecutive patients who underwent an identical CT examination for evaluation of suspected acute pulmonary embolism and had no signs of pulmonary embolism or PH, served as control cohort. Lungs were automatically segmented for all patients and normal and malperfused volumes were segmented based on iodine density thresholds. Results were compared between groups. For correlation analysis between the extent of malperfused volume and mean pulmonary artery pressure (mPAP) and pulmonary vascular resistance (PVR) 3 patients were excluded because of a time span of more than 30 days between CTPA and right heart catheterization. RESULTS: Patients with CTEPH had a higher percentage of malperfused lung compared to controls (43.25%±24.72% vs. 21.82%±20.72%; P=0.001) and showed reduced mean iodine density in malperfused and normal-perfused lung areas, as well as in the vessel volume. Controls showed a left-tailed distribution of iodine density in malperfused lung areas while patients with CTEPH had a more symmetrical distribution (Skew: -0.382±0.435 vs. -0.010±0.396; P=0.004). Patients with CTEPH showed a significant correlation between the percentage of malperfused lung volume and the PVR (r=0.57, P=0.001). CONCLUSIONS: Volumetric iodine quantification helps to identify patients with CTEPH by showing increased areas of malperfusion. The extent of malperfusion might provide a measurement for disease severity in patients with CTEPH.

Calcium scoring using virtual non-contrast images from a dual-layer spectral detector CT: comparison to true non-contrast data and evaluation of proportionality factor in a large patient collective.

OBJECTIVE: Determination of coronary artery calcium scoring (CACS) in non-contrast computed tomography (CT) images has been shown to be an important prognostic factor in coronary artery disease (CAD). The objective of this study was to evaluate the accuracy of CACS from virtual non-contrast (VNC) imaging generated from spectral data in comparison to standard (true) non-contrast (TNC) imaging in a representative patient cohort with clinically approved software. METHODS: One hundred three patients referred to coronary CTA with suspicion of CAD were investigated on a dual-layer spectral detector CT (SDCT) scanner. CACS was calculated from both TNC and VNC images by software certified for medical use. Patients with a CACS of 0 were excluded from analysis. RESULTS: The mean age of the study population was 61 ± 11 years with 48 male patients (67%). Inter-quartile range of clinical CACS was 22-282. Correlation of measured CACS from true- and VNC images was high (0.95); p < 0.001. The slope was 3.83, indicating an underestimation of VNC CACS compared to TNC CACS by that factor. Visual analysis of the Bland-Altman plot of CACS showed good accordance with both methods after correction of VNC CACS by the abovementioned factor. CONCLUSIONS: In clinical diagnostics of CAD, the determination of CACS is feasible using VNC images generated from spectral data obtained on a dual-layer spectral detector CT. When multiplied by a correction factor, results were in good agreement with the standard technique. This could enable radiation dose reductions by obviating the need for native scans typically used for CACS. KEY POINTS: • Calcium scoring is feasible from contrast-enhanced CT images using a dual-layer spectral detector CT scanner. • When multiplied by a correction factor, calcium scoring from virtual non-contrast images shows good agreement with the standard technique. • Omitting native scans for calcium scoring could enable radiation dose reduction.

Influence of acquisition settings and radiation exposure on CT lung densitometry-An anthropomorphic ex vivo phantom study.

OBJECTIVES: To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom. MATERIALS AND METHODS: Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kVp and 80kVp, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kVp/120 mAs serving as the standard of reference. RESULTS: Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05). CONCLUSIONS: Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required.

Liver lesion localisation and classification with convolutional neural networks: a comparison between conventional and spectral computed tomography.

PURPOSE: To evaluate the benefit of the additional available information present in spectral CT datasets, as compared to conventional CT datasets, when utilizing convolutional neural networks for fully automatic localisation and classification of liver lesions in CT images. MATERIALS AND METHODS: Conventional and spectral CT images (iodine maps, virtual monochromatic images (VMI)) were obtained from a spectral dual-layer CT system. Patient diagnosis were known from the clinical reports and classified into healthy, cyst and hypodense metastasis. In order to compare the value of spectral versus conventional datasets when being passed as input to machine learning algorithms, we implemented a weakly-supervised convolutional neural network (CNN) that learns liver lesion localisation without pixel-level ground truth annotations. Regions-of-interest are selected automatically based on the localisation results and are used to train a second CNN for liver lesion classification (healthy, cyst, hypodense metastasis). The accuracy of lesion localisation was evaluated using the Euclidian distances between the ground truth centres of mass and the predicted centres of mass. Lesion classification was evaluated by precision, recall, accuracy and F1-Score. RESULTS: Lesion localisation showed the best results for spectral information with distances of 8.22 ± 10.72 mm, 8.78 ± 15.21 mm and 8.29 ± 12.97 mm for iodine maps, 40 keV and 70 keV VMIs, respectively. With conventional data distances of 10.58 ± 17.65 mm were measured. For lesion classification, the 40 keV VMIs achieved the highest overall accuracy of 0.899 compared to 0.854 for conventional data. CONCLUSION: An enhanced localisation and classification is reported for spectral CT data, which demonstrates that combining machine-learning technology with spectral CT information may in the future improve the clinical workflow as well as the diagnostic accuracy.

Spectral Photon-Counting Computed Tomography for Coronary Stent Imaging: Evaluation of the Potential Clinical Impact for the Delineation of In-Stent Restenosis.

OBJECTIVES: In-stent restenosis (ISR) is one of the main long-term complications after coronary stent placement, and the ability to evaluate ISR noninvasively using coronary computed tomography (CT) angiography remains challenging. For this application, spectral photon-counting CT (SPCCT) has the potential to increase image quality and reduce artifacts due to its advanced detector technology.Our study aimed to verify the technical and clinical potential of a novel SPCCT prototype using an ISR phantom setup. MATERIALS AND METHODS: Soft plaque-like restenosis (45 HU; approximately 50% of the stent lumen) were inserted into 10 different coronary stents (3 mm diameter), which were placed in a vessel phantom and filled with a contrast agent (400 HU). A research prototype SPCCT and a clinical dual-layer CT (DLCT; IQon; Philips) with comparable acquisition and reconstruction parameters were used to scan the phantoms. Conventional polyenergetic (PolyE) and monoenergetic (MonoE) images with 4 different energy levels (40, 60, 90, 120 keV) were reconstructed. Qualitative (delineation of the stenosis and adjacent residual lumen using a 5-point Likert scale) and quantitative (image noise, visible lumen diameter, lumen diameter adjacent to the stenosis, contrast-to-noise ratio of the restenosis) parameters were evaluated for both systems. RESULTS: The qualitative results averaged over all reconstructions were significantly superior for SPCCT compared with DLCT (eg, subjective rating of the best reconstruction of each scanner: DLCT PolyE: 2.80 ± 0.42 vs SPCCT MonoE 40 keV: 4.25 ± 1.03). Stenosis could be clearly detected in 9 and suspected in 10 of the 10 stents with both SPCCT and DLCT. The residual lumen next to the stenosis was clearly delineable in 7 of 10 stents (0.64 ± 0.11 mm or 34.97% of the measured stent lumen) with SPCCT, while it was not possible to delineate the residual lumen for all stents using DLCT. The measured diameter of the lumen within the stent was significantly higher for SPCCT compared with DLCT in all reconstructions with the best results for the MonoE 40 keV images (SPCCT: 1.80 ± 0.17 mm; DLCT: 1.50 ± 0.31 mm). The image noise and the contrast-to-noise ratio were better for DLCT than for SPCCT (contrast-to-noise ratio: DLCT MonoE 40: 31.58 ± 12.54; SPCCT MonoE 40: 4.64 ± 1.30). CONCLUSIONS: Spectral photon-counting CT allowed for the noninvasive evaluation of ISR with reliable results regarding the residual lumen for most tested stents and the clear identification or suspicion of stenosis for all stents. In contrast, the residual lumen could not be detected for a single stent using DLCT.

Experimental application of an automated alignment correction algorithm for geological CT imaging: phantom study and application to sediment cores from cold-water coral mounds.

BACKGROUND: In computed tomography (CT) quality assurance, alignment of image quality phantoms is crucial for quantitative and reproducible evaluation and may be improved by alignment correction. Our goal was to develop an alignment correction algorithm to facilitate geological sampling of sediment cores taken from a cold-water coral mount. METHODS: An alignment correction algorithm was developed and tested with a CT acquisition at 120 kVp and 150 mAs of an image quality phantom. Random translation (maximum 15 mm) and rotation (maximum 2.86°) were applied and ground-truth was compared to parameters determined by alignment correction. Furthermore, mean densities were evaluated in four regions of interest (ROIs) placed in the phantom low-contrast section, comparing values before and after correction to ground truth. This process was repeated 1000 times. After validation, alignment correction was applied to CT acquisitions (140 kVp, 570 mAs) of sediment core sections up to 1 m in length, and sagittal reconstructions were calculated for sampling planning. RESULTS: In the phantom, average absolute differences between applied and detected parameters after alignment correction were 0.01 ± 0.06 mm (mean ± standard deviation) along the x-axis, 0.11 ± 0.08 mm along the y-axis, 0.15 ± 0.07° around the x-axis, and 0.02 ± 0.02° around the y-axis, respectively. For ROI analysis, differences in densities were 63.12 ± 30.57, 31.38 ± 32.10, 18.27 ± 35.57, and 9.59 ± 26.37 HU before alignment correction and 1.22 ± 1.40, 0.76 ± 0.9, 0.45 ± 0.86, and 0.36 ± 0.48 HU after alignment correction, respectively. For sediment core segments, average absolute detected parameters were 3.93 ± 2.89 mm, 7.21 ± 2.37 mm, 0.37 ± 0.33°, and 0.21 ± 0.22°, respectively. CONCLUSIONS: The alignment correction algorithm was successfully evaluated in the phantom and allowed a correct alignment of sediment core segments, thus aiding in sampling planning. Application to other tasks, like image quality analysis, seems possible.

Thoracic-abdominal imaging with a novel dual-layer spectral detector CT: intra-individual comparison of image quality and radiation dose with 128-row single-energy acquisition.

BACKGROUND: A novel, multi-energy, dual-layer spectral detector computed tomography (SDCT) is commercially available now with the vendor's claim that it yields the same or better quality of polychromatic, conventional CT images like modern single-energy CT scanners without any radiation dose penalty. PURPOSE: To intra-individually compare the quality of conventional polychromatic CT images acquired with a dual-layer spectral detector (SDCT) and the latest generation 128-row single-energy-detector (CT128) from the same manufacturer. MATERIAL AND METHODS: Fifty patients underwent portal-venous phase, thoracic-abdominal CT scans with the SDCT and prior CT128 imaging. The SDCT scanning protocol was adapted to yield a similar estimated dose length product (DLP) as the CT128. Patient dose optimization by automatic tube current modulation and CT image reconstruction with a state-of-the-art iterative algorithm were identical on both scanners. CT image contrast-to-noise ratio (CNR) was compared between the SDCT and CT128 in different anatomic structures. Image quality and noise were assessed independently by two readers with 5-point-Likert-scales. Volume CT dose index (CTDIvol), and DLP were recorded and normalized to 68 cm acquisition length (DLP68). RESULTS: The SDCT yielded higher mean CNR values of 30.0% ± 2.0% (26.4-32.5%) in all anatomic structures ( P < 0.001) and excellent scores for qualitative parameters surpassing the CT128 (all P < 0.0001) with substantial inter-rater agreement (κ ≥ 0.801). Despite adapted scan protocols the SDCT yielded lower values for CTDIvol (-10.1 ± 12.8%), DLP (-13.1 ± 13.9%), and DLP68 (-15.3 ± 16.9%) than the CT128 (all P < 0.0001). CONCLUSION: The SDCT scanner yielded better CT image quality compared to the CT128 and lower radiation dose parameters.

Dual-energy CT iodine maps as an alternative quantitative imaging biomarker to abdominal CT perfusion: determination of appropriate trigger delays for acquisition using bolus tracking.

OBJECTIVE: Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion. METHODS: Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kVp with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kVp image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time. RESULTS: Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min-1, respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (rmax = 0.89; p < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05). CONCLUSION: An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

Utilization of virtual mono-energetic images (MonoE) derived from a dual-layer spectral detector CT (SDCT) for the assessment of abdominal arteries in venous contrast phase scans.

OBJECTIVES: To investigate the utilization of virtual mono-energetic images (MonoE) at low kiloelectron volt (keV) levels derived from a dual-layer spectral detector CT (SDCT) for the assessment of abdominal arteries in venous contrast phase scans using arterial phase imaging as an internal reference standard. MATERIALS AND METHODS: A total of 50 patients who received arterial and venous phase imaging of the abdomen on a SDCT system were included in this study. Absolute attenuation, noise, signal- and contrast to noise ratios (SNR; CNR) as well as arterial diameters in defined landmarks were assessed. In arterial phase, conventional reconstructions (CRART) as well as MonoEART at 40keV and in venous phase, conventional reconstructions (CRVEN) as well as MonoEVEN at 70 and 40keV were investigated and intra-individual comparisons were performed. If an artery stenosis (10 patients) was present, the degree of stenosis was assessed according to the system of the North American Symptomatic Carotid Endarterectomy Trial (NASCET). RESULTS: MonoE 40keV yielded significantly higher attenuation values (in arterial as well as in venous phase) compared to CRART (p<0.001) while noise levels were substantially low. This resulted in markedly superior SNR and CNR in large vessel compared to CRART. Luminal diameters were significantly smaller in MonoE 40keV in both contrast phases compared to CRART (p<0.001), whereas no significant differences were found between both MonoE reconstructions (p≥0.92). The degree of vessel stenosis was significantly higher in MonoE 40keV of both contrast phases compared to CRART (p≥0.02). CONCLUSION: MonoE at low keV of venous contrast phase scans derived from a novel SDCT are suitable for the assessment of arteries in the abdomen and subsequent stenosis assessment. However, MonoE at 40keV constantly showed significant smaller luminal diameters than the corresponding conventional reconstructions (including the reference standard). This is possibly due to an improved differentiation of the vessel lumen from the wall and raises the question, which imaging technique should be used as an appropriate reference standard for vascular SDCT imaging studies.

Influence of spectral detector CT based monoenergetic images on the computer-aided detection of pulmonary artery embolism.

OBJECTIVE: To evaluate the influence of monoenergetic reconstructions using a spectral detector CT (SDCT) on the computer aided detection (CAD) of pulmonary artery embolism (PAE) on CT pulmonary angiography (CTPA) and CT in venous contrast phase (CTV). MATERIAL AND METHODS: A retrospective data base search identified 15 patients with CTPA and 18 patients with CTV and diagnosis of PAE. For these patients, monoenergetic (monoE) images at different energy levels or with a fixed attenuation in the pulmonary artery were generated and independently analyzed using a commercially available computer aided detection (CAD) tool. Attenuation in the pulmonary artery and in the embolus was measured. RESULTS: For CTPA and CTV, in monoenergetic images the difference in attenuation between vessel and embolus was significantly higher than in conventional images. In CTPA the detection rate was highest in the >500 HU monoE images with 67,9% detected emboli and 93,3% of patients correctly identified as having PAE. At the same time the false positive rate could be significantly reduced by using monoE images compared to conventional images. Detection rates for CTV were lower than in CTPA but were raised significantly by monoE reconstructions. CONCLUSIONS: The combination of SDCT and CAD improves the diagnostic accuracy of CAD and enables CAD interpretation of CTV.

Improvement of Image Quality in Unenhanced Dual-Layer CT of the Head Using Virtual Monoenergetic Images Compared With Polyenergetic Single-Energy CT.

OBJECTIVES: The aims of this study were to compare virtual monoenergetic images and polyenergetic images reconstructed from unenhanced dual-layer detector computed tomography (DLCT) of the head and to determine kiloelectron volt levels that optimize image quality, particularly the gray-white matter contrast, and reduce beam hardening artifacts caused by the skull. MATERIALS AND METHODS: Institutional review board approval was obtained. Forty patients that received DLCT were included in this retrospective study; of these patients, 22 were women and 18 were men. The average age was 61.5 ± 14.3 years. Virtual monoenergetic images were reconstructed from spectral base images at 40 keV to 120 keV. To calculate signal-to-noise ratio and contrast-to-noise ratio, attenuation and standard deviation of supratentorial gray and white matter were measured in virtual monoenergetic and polyenergetic images. Beam hardening artifacts were detected close to the calvarium and in the posterior fossa. Two radiologists rated the assessment of gray-white matter differentiation and of the subcalvarial space, as well as the artifacts caused by the skull and image noise. Student t test and Wilcoxon test were used to determine significance. RESULTS: Compared with polyenergetic images, superior signal-to-noise ratio and superior contrast-to-noise ratio of gray and white matter were observed in virtual monoenergetic images at low kiloelectron volt levels (P < 0.0001). Subcalvarial artifacts were significantly lower at 120 keV (P < 0.02). Artifacts measured in the posterior fossa were generally lower at high kiloelectron volt levels; however, no statistical significance was detected. Virtual monoenergetic images were rated superior to polyenergetic images in regard to all 4 criteria (P < 0.0001). The observers reported an optimal radiological assessment of gray-white matter differentiation at 65 keV and optimal assessment of subcalvarial space at 120 keV. CONCLUSIONS: In comparison to polyenergetic images, virtual monoenergetic images reconstructed from unenhanced DLCT of the head at 65 keV and 120 keV allow to optimize gray-white matter contrast and reduce beam hardening artifacts caused by the skull, respectively.

Monoenergetic reconstructions for imaging of coronary artery stents using spectral detector CT: In-vitro experience and comparison to conventional images.

PURPOSE: Accurate assessment of coronary stents using non-invasive CT imaging remains challenging despite new stent materials and improvements in CT technology. Virtual monoenergetic (monoE) images reconstructed from dual energy CT acquisitions potentially decrease artifacts caused by coronary stents. A novel spectral detector technology provides monoE and conventional images simultaneously for all conducted scans. The purpose of our study was to systematically investigate the influence of different monoE reconstructions on the visualization of coronary stent lumen in comparison to conventional images. METHOD AND MATERIALS: Ten different coronary stents (diameter 3.0 mm) embedded in plastic tubes filled with contrast agent (500 HU) were scanned with a 128-row spectral detector CT (IQon, Philips, 120 kV, 125 mAs). Images were reconstructed (0.67 mm slice thickness, 0.35 mm increment) with a stent-specific conventional reconstruction kernel and 6 different monoE settings (60, 70, 80, 90, 100, 150 keV). Image quality for each stent and reconstruction was quantified using established parameters: image noise (standard deviation (SD) within a standardized ROI), in-stent attenuation difference (mean attenuation difference between stented and non-stented lumen) and visible lumen diameter (mean visible diameter of the stented tube). RESULTS: Image noise was significantly lower in all monoE data dets compared to conventional images (conventional: 13.41, 60 keV: 11.62, 70 keV: 11.67, 80 keV: 11.69, 90 keV: 11.71, 100 keV: 11.75, 150 keV: 11.80 HU SD; p < 0.01). The in-stent attenuation difference was significantly smaller in monoE data with higher keV levels than in conventional images (conventional: 148.18, 60 keV: 154.13 p = 0.036, 70 keV: 143.43 p = 0.109, 80 keV: 137.25 p = 0.052, 90 keV: 133.02 p = 0.043, 100 keV: 130.12 p = 0.039, 150 keV: 123.99 HU p = 0.035). The visible lumen diameter was significantly greater in monoE data with higher keV levels than in conventional images (conventional: 0.65, 60 keV: 0.68 p = 0.542, 70 keV: 0.71 p = 0.053, 80 keV: 0.74 p < 0.01, 90 keV: 0.77 p < 0.01, 100 keV: 0.82 p < 0.01, 150 keV: 0.87 mm p < 0.01). CONCLUSION: In comparison to conventional CT images, well-established parameters for objective assessment of CT image quality for coronary stents are significantly improved by utilization of monoE reconstructions with adequate keV levels derived from data acquired on a novel spectral detector CT platform.

Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87.

PURPOSE: Based on the guidelines from "Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography" of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated. METHODS: The extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers. RESULTS: Spatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment. CONCLUSIONS: The presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods.

Correlation of quantitative dual-energy computed tomography iodine maps and abdominal computed tomography perfusion measurements: are single-acquisition dual-energy computed tomography iodine maps more than a reduced-dose surrogate of conventional computed tomography perfusion?

OBJECTIVES: Study objectives were the quantitative evaluation of whether conventional abdominal computed tomography (CT) perfusion measurements mathematically correlate with quantitative single-acquisition dual-energy CT (DECT) iodine concentration maps, the determination of the optimum time of acquisition for achieving maximum correlation, and the estimation of the potential for radiation exposure reduction when replacing conventional CT perfusion by single-acquisition DECT iodine concentration maps. MATERIALS AND METHODS: Dual-energy CT perfusion sequences were dynamically acquired over 51 seconds (34 acquisitions every 1.5 seconds) in 24 patients with histologically verified pancreatic carcinoma using dual-source DECT at tube potentials of 80 kVp and 140 kVp. Using software developed in-house, perfusion maps were calculated from 80-kVp image series using the maximum slope model after deformable motion correction. In addition, quantitative iodine maps were calculated for each of the 34 DECT acquisitions per patient. Within a manual segmentation of the pancreas, voxel-by-voxel correlation between the perfusion map and each of the iodine maps was calculated for each patient to determine the optimum time of acquisition topt defined as the acquisition time of the iodine map with the highest correlation coefficient. Subsequently, regions of interest were placed inside the tumor and inside healthy pancreatic tissue, and correlation between mean perfusion values and mean iodine concentrations within these regions of interest at topt was calculated for the patient sample. RESULTS: The mean (SD) topt was 31.7 (5.4) seconds after the start of contrast agent injection. The mean (SD) perfusion values for healthy pancreatic and tumor tissues were 67.8 (26.7) mL per 100 mL/min and 43.7 (32.2) mL per 100 mL/min, respectively. At topt, the mean (SD) iodine concentrations were 2.07 (0.71) mg/mL in healthy pancreatic and 1.69 (0.98) mg/mL in tumor tissue, respectively. Overall, the correlation between perfusion values and iodine concentrations was high (0.77), with correlation of 0.89 in tumor and of 0.56 in healthy pancreatic tissue at topt. Comparing radiation exposure associated with a single DECT acquisition at topt (0.18 mSv) to that of an 80 kVp CT perfusion sequence (2.96 mSv) indicates that an average reduction of Deff by 94% could be achieved by replacing conventional CT perfusion with a single-acquisition DECT iodine concentration map. CONCLUSIONS: Quantitative iodine concentration maps obtained with DECT correlate well with conventional abdominal CT perfusion measurements, suggesting that quantitative iodine maps calculated from a single DECT acquisition at an organ-specific and patient-specific optimum time of acquisition might be able to replace conventional abdominal CT perfusion measurements if the time of acquisition is carefully calibrated. This could lead to large reductions of radiation exposure to the patients while offering quantitative perfusion data for diagnosis.