Monoenergetic Images Research Articles

Assessment of dual-energy computed tomography derived virtual monoenergetic imaging for target volume delineation of brain metastases

BackgroundObjective and subjective assessment of image quality of brain metastases on dual-energy computed tomography (DECT) virtual monoenergetic imaging (VMI) and its impact on target volume delineation. Materials and Methods26 patients with 37 brain metastases receiving Magnetic Resonance Imaging (MRI) and DECT for stereotactic radiotherapy planning were included in this retrospective analysis. Lesion contrast (LC), contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were assessed for reconstructed VMI at 63 keV and artificial 120 kV Computed Tomography (CT). Image contrast and demarcation of metastases between 120 kV CT, VMI and MRI were subjectively assessed. Brain metastases were delineated by four radiation oncologists on VMI with a fixed or free brain window and contours were compared to solely MRI-based delineation using the Dice similarity coefficient. ResultsLC, CNR and SNR were significantly higher in VMI than in 120 kV CT (p < 0.0001). Image contrast and lesion demarcation were significantly better on VMI compared to 120 kV CT (p < 0.0001). Mean gross tumor volume (GTV)/planning target volume (PTV) Dice similarity coefficients were 0.87/0.9 for metastases without imaging uncertainties (no artifacts, calcification or impaired visibility with MRI) but worse for metastases with imaging uncertainties (0.71/0.74). Target volumes delineated on VMI were around 5–10% smaller compared to MRI. ConclusionImage quality of VMI is objectively and subjectively superior to conventional CT. VMI provides significant advantages in stereotactic radiotherapy planning with improved visibility of brain metastases and geometrically distortion-free representation of brain metastases. Beside a plausibility check of MRI-based target volume delineation, VMI might improve reliability and accuracy in target volume definition particularly in cases with imaging uncertainties with MRI.

Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma.

Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis of the aggressive macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic performance of dual-phase contrast-enhanced multiparametric DECT for predicting MTM HCC. Materials and Methods Patients with histopathologic examination-confirmed HCC who underwent contrast-enhanced DECT between June 2019 and June 2022 were retrospectively recruited from three independent centers (center 1, training and internal test data set; centers 2 and 3, external test data set). Radiologic features were visually analyzed and combined with clinical information to establish a clinical-radiologic model. Deep learning (DL) radiomics models were based on DL features and handcrafted features extracted from virtual monoenergetic images and material composition images on dual phase using binary least absolute shrinkage and selection operators. A DL radiomics nomogram was developed using multivariable logistic regression analysis. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC), and the log-rank test was used to analyze recurrence-free survival. Results A total of 262 patients were included (mean age, 54 years ± 12 [SD]; 225 men [86%]; training data set, n = 146 [56%]; internal test data set, n = 35 [13%]; external test data set, n = 81 [31%]). The DL radiomics nomogram better predicted MTM than the clinical-radiologic model (AUC = 0.91 vs 0.77, respectively, for the training set [P < .001], 0.87 vs 0.72 for the internal test data set [P = .04], and 0.89 vs 0.79 for the external test data set [P = .02]), with similar sensitivity (80% vs 87%, respectively; P = .63) and higher specificity (90% vs 63%; P < .001) in the external test data set. The predicted positive MTM groups based on the DL radiomics nomogram had shorter recurrence-free survival than predicted negative MTM groups in all three data sets (training data set, P = .04; internal test data set, P = .01; and external test data set, P = .03). Conclusion A DL radiomics nomogram derived from multiparametric DECT accurately predicted the MTM subtype in patients with HCC. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chu and Fishman in this issue.

Constrained one-step material decomposition reconstruction of head CT data from a silicon photon-counting prototype.

Spectral CT material decomposition provides quantitative information but is challenged by the instability of the inversion into basis materials. We have previously proposed the constrained One-Step Spectral CT Image Reconstruction (cOSSCIR) algorithm to stabilize the material decomposition inversion by directly estimating basis material images from spectral CT data. cOSSCIR was previously investigated on phantomdata. This study investigates the performance of cOSSCIR using head CT datasets acquired on a clinical photon-counting CT (PCCT) prototype. This is the first investigation of cOSSCIR for large-scale, anatomically complex, clinical PCCT data. The cOSSCIR decomposition is preceded by a spectrum estimation and nonlinear counts correction calibration step to address nonideal detectoreffects. Head CT data were acquired on an early prototype clinical PCCT system using an edge-on silicon detector with eight energy bins. Calibration data of a step wedge phantom were also acquired and used to train a spectral model to account for the source spectrum and detector spectral response, and also to train a nonlinear counts correction model to account for pulse pileup effects. The cOSSCIR algorithm optimized the bone and adipose basis images directly from the photon counts data, while placing a grouped total variation (TV) constraint on the basis images. For comparison, basis images were also reconstructed by a two-step projection-domain approach of Maximum Likelihood Estimation (MLE) for decomposing basis sinograms, followed by filtered backprojection (MLE + FBP) or a TV minimization algorithm (MLE + TVmin ) to reconstruct basis images. We hypothesize that the cOSSCIR approach will provide a more stable inversion into basis images compared to two-step approaches. To investigate this hypothesis, the noise standard deviation in bone and soft-tissue regions of interest (ROIs) in the reconstructed images were compared between cOSSCIR and the two-step methods for a range of regularization constraintsettings. cOSSCIR reduced the noise standard deviation in the basis images by a factor of two to six compared to that of MLE + TVmin , when both algorithms were constrained to produce images with the same TV. The cOSSCIR images demonstrated qualitatively improved spatial resolution and depiction of fine anatomical detail. The MLE + TVmin algorithm resulted in lower noise standard deviation than cOSSCIR for the virtual monoenergetic images (VMIs) at higher energy levels and constraint settings, while the cOSSCIR VMIs resulted in lower noise standard deviation at lower energy levels and overall higher qualitative spatial resolution. There were no statistically significant differences in the mean values within the bone region of images reconstructed by the studied algorithms. There were statistically significant differences in the mean values within the soft-tissue region of the reconstructed images, with cOSSCIR producing mean values closer to the expectedvalues. The cOSSCIR algorithm, combined with our previously proposed spectral model estimation and nonlinear counts correction method, successfully estimated bone and adipose basis images from high resolution, large-scale patient data from a clinical PCCT prototype. The cOSSCIR basis images were able to depict fine anatomical details with a factor of two to six reduction in noise standard deviation compared to that of the MLE + TVmin two-stepapproach.

Saving Contrast Media in Coronary CT Angiography with Photon-Counting Detector CT

To determine the optimal virtual monoenergetic image (VMI) energy level and the potential of contrast-media (CM) reduction for coronary computed tomography angiography (CCTA) with photon-counting detector CT (PCD-CT). In this institutional review board-approved study, patients who underwent CCTA with dual-source PCD-CT with an identical scan protocol and radiation dose were included. In group 1, CCTA was performed with our standard CM protocol (volume: 72-85.2mL, 370mg iodine/mL). VMIs were reconstructed from 40 to 60keV at 5keV increments. Objective image quality (IQ) (vascular attenuation, image noise, and contrast-to-noise ratio [CNR]) was measured. Two blinded, independent readers rated subjective IQ (overall IQ, subjective image contrast, and subjective noise using a five-point discrete visual scale). Results of group 1 served to determine the best VMI level for CCTA. In group 2, CM volume was reduced by 20%, and in group 3 by another 20%. A total of 100 patients were enrolled (45 females, mean age 54±13 years). Inter-reader agreement was good-to-excellent for all comparisons (κ > 0.6). In group 1, the best VMI level regarding objective and subjective IQ was 45keV, which was selected as the reference for groups 2 and 3. For group 2, mean vascular attenuation was 890 Hounsfield units (HU) and mean CNR was 26, with no differences compared to group 1, 45keV for both objective and subjective IQ. For group 3, mean vascular attenuation was 676 HU and mean CNR was 21, and all patients were rated as diagnostic except one (severe motion artifacts). Increased IQ of PCD-CT can be used for considerable CM volume reduction while still maintaining a diagnostic IQ of CCTA.

Effect of iodine concentration reduction by comparison of virtual monoenergetic image quality with dual-energy computed tomography

This study aimed to evaluate the image quality of virtual monoenergetic images (VMIs) with tube voltage modulation in pediatric abdominal computed tomography (CT) examination and to determine the effect of decreasing contrast agent concentration. Using a 1-year old pediatric phantom, five contrast agent concentration diluent tubes of 100%, 80%, 60%, 40%, and 20% of the same concentration as the average Hounsfield unit (HU) in the descending aorta were inserted, and the mixed image and VMIs (40, 60, and 80 keV) acquired using dual-energy CT were compared with single-energy CT (SECT) images. For quantitative evaluation, the HU and coefficient of variation (COV) of each image were compared and analyzed. The analysis revealed that the HU of the 40 keV VMIs, acquired with a tube voltage of 70 kV and 100% contrast agent concentration, was 61% higher than that of the SECT image. The results showed that SECT had the lowest COV among all contrast agent concentration and tube voltage combinations, while the 40 keV image acquired at 70 kV had the second-lowest COV value. The HU of the 40 keV image acquired at 70 kV at a contrast agent concentration of 100% was 9% higher than that of SECT at 80% concentration. This study confirms that 40 keV VMIs are more useful than SECT images for vascular diagnosis with contrast in pediatric abdominal CT examinations and that a 20% reduction in contrast agent concentration can reduce the risk of contrast agent concentration-induced nephrotoxicity in pediatric patients by increasing the subjective acceptability of image quality for diagnosis.

Impact of virtual monoenergetic levels on coronary plaque volume components using photon-counting computed tomography

ObjectivesVirtual monoenergetic images (VMIs) from photon-counting CT (PCCT) may change quantitative coronary plaque volumes. We aimed to assess how plaque component volumes change with respect to VMIs.MethodsCoronary CT angiography (CTA) images were acquired using a dual-source PCCT and VMIs were reconstructed between 40 and 180 keV in 10-keV increments. Polychromatic images at 120 kVp (T3D) were used as reference. Quantitative plaque analysis was performed on T3D images and segmentation masks were copied to VMI reconstructions. Calcified plaque (CP; > 350 Hounsfield units, HU), non-calcified plaque (NCP; 30 to 350 HU), and low-attenuation NCP (LAP; − 100 to 30 HU) volumes were calculated using fixed thresholds.ResultsWe analyzed 51 plaques from 51 patients (67% male, mean age 65 ± 12 years). Average attenuation and contrast-to-noise ratio (CNR) decreased significantly with increasing keV levels, with similar values observed between T3D and 70 keV images (299 ± 209 vs. 303 ± 225 HU, p = 0.15 for mean HU; 15.5 ± 3.7 vs. 15.8 ± 3.5, p = 0.32 for CNR). Mean NCP volume was comparable between T3D and 100–180-keV reconstructions. There was a monotonic decrease in mean CP volume, with a significant difference between all VMIs and T3D (p < 0.05). LAP volume increased with increasing keV levels and all VMIs showed a significant difference compared to T3D, except for 50 keV (28.0 ± 30.8 mm3 and 28.6 ± 30.1 mm3, respectively, p = 0.63).ConclusionsEstimated coronary plaque volumes significantly differ between VMIs. Normalization protocols are needed to have comparable results between future studies, especially for LAP volume which is currently defined using a fixed HU threshold.Clinical relevance statementDifferent virtual monoenergetic images from photon-counting CT alter attenuation values and therefore corresponding plaque component volumes. New clinical standards and protocols are required to determine the optimal thresholds to derive plaque volumes from photon-counting CT.Key Points• Utilizing different VMI energy levels from photon-counting CT for the analysis of coronary artery plaques leads to substantial changes in attenuation values and corresponding plaque component volumes.• Low-energy images (40–70 keV) improved contrast-to-noise ratio, however also increased image noise.• Normalization protocols are needed to have comparable results between future studies, especially for low-attenuation plaque volume which is currently defined using a fixed HU threshold.

Intra-individual comparison of image quality of the coronary arteries between photon-counting detector and energy-integrating detector CT systems

PurposeTo intra-individually compare the objective and subjective image quality of coronary computed tomography angiography (CCTA) between photon-counting detector CT (PCD-CT) and energy-integrating detector CT (EID-CT). MethodConsecutive patients undergoing clinically indicated CCTA on an EID-CT system were prospectively enrolled for a research CCTA performed on a PCD-CT system within 30 days. Polychromatic images were reconstructed for both EID- and PCD-CT, while virtual monoenergetic images (VMI) were generated at 40, 45, 50, 55, 60 and 70 keV for PCD-CT. Two blinded readers calculated contrast-to-noise ratio (CNR) for each major coronary artery and rated image noise, vessel attenuation, vessel sharpness, and overall quality on a 1–5 Likert scale. Patients were then stratified by body mass index (BMI) [high (>30 kg/m2) vs low (<30 kg/m2)] for subgroup analysis. ResultsA total of 20 patients (67.5 ± 9.0 years, 75% male) were included in the study. Compared with EID-CT, coronary artery CNR values from PCD-CT monoenergetic and polychromatic reconstructions were all significantly higher than CNR values from EID-CT, with incrementally greater differences in obese subjects (all p < 0.008). Subjective image noise and sharpness were also significantly higher for all VMI reconstructions compared to EID-CT (all p < 0.008). All subjective scores were significantly higher for 55, 60, and 70 keV PCD-CT than EID-CT values (all p < 0.05). ConclusionsThe improved objective and subjective image quality of PCD-CT compared to EID-CT may provide better visualization of the coronary arteries for a wide array of patients, especially those with a high BMI.

Establishing quality control action limits for CT number accuracy in spectral images using an American College of Radiology phantom.

Computed tomography (CT) number accuracy is important for quality assurance in CT imaging. However, in dual-energy CT imaging, there are no widely used action limits for CT number accuracy in spectral images, information that is urgently needed. To establish action limits for spectral CT images using longitudinal spectral data and an American College of Radiology (ACR) phantom. An ACR accreditation phantom was scanned routinely as part of a quality control program in our institution. We selected and analyzed 57 continuous weekly scans. The CT numbers or the density values of conventional and spectral images, including virtual monoenergetic images (40, 50, 70, 120, and 200keV), iodine maps, calcium suppressed, and virtual non-contrast images, were measured in the four inserts (solid water, bone, polyethylene, and acrylic) of the phantom. Longitudinal data were analyzed for correlation using Pearson's correlation coefficient (r) and standard deviation (SD). The SD ratios between spectral images and conventional images were calculated and the action limits for spectral images were established based on the action limits from the ACR. Strong to very strong correlations (r>0.70 or r<-0.70) were found among most spectral image types except the 200keV images using solid water, polyethylene, and acrylic inserts (r=[-0.45, 0.64]). The SD ratio was highest for the 40keV images, ranging from 2.8 to 6.5. The action limits of the bone insert were baseline±5.3mg/mL for the iodine map and ranged from baseline±23.0 HU to baseline±391.9 HU for the other image types. The action limits for solid water ranged from baseline±4.1 HU to baseline±25.3 HU. The results for the polyethylene and the acrylic insert were close to those for solid water. Baselines can be established using the average of the initial 5∼10 measurements. Using longitudinal data, we estimated the action limits for CT number accuracy in the spectral images. This paves the way for establishing a comprehensive quality control program for spectral CT imaging.

Image quality of spectral brain computed tomography angiography using halved dose of iodine contrast medium.

Reduction in iodinated contrast medium (CM) dose is highly motivated. Our aim was to evaluate if a 50% reduction of CM, while preserving image quality, is possible in brain CT angiography (CTA) using virtual monoenergetic images (VMI) on spectral CT. As a secondary aim, we evaluated if VMI can salvage examinations with suboptimal CM timing. Consecutive patients older than 18 years without intracranial stenosis/occlusion were included. Three imaging protocols were used: group 1, full CM dose; group 2, 50% CM dose suboptimal timing; and group 3, 50% CM dose optimized timing. Attenuation, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured in the internal carotid artery, M2 segment of the middle cerebral artery, and white matter for conventional images (CI) and VMI (40-200 keV). Qualitative image quality for CI and VMI (50 and 60 keV) was rated by 4 experienced reviewers. Qualitatively and quantitatively, VMI (40-60 keV) improved image quality within each group. Significantly higher attenuation and CNR was found for group 3 VMI 40-50 keV, with unchanged SNR, compared to group 1 CI. Group 3 VMI 50 keV also received significantly higher rating scores than group 1 CI. Group 2 VMI (40-50 keV) had significantly higher CNR compared to group 3 CI, but the subjective image quality was similar. VMI of 50 keV with 50% CM dose increases qualitative and quantitative image quality over CI with full CM dose. Using VMI reduces non-diagnostic examinations and may salvage CTA examinations deemed non-diagnostic due to suboptimal timing.

Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images

ObjectivesTo investigate photon-counting CT (PCCT)–derived virtual monoenergetic images (VMI) for artifact reduction in patients with unilateral total hip replacements (THR).MethodsForty-two patients with THR and portal-venous phase PCCT of the abdomen and pelvis were retrospectively included. For the quantitative analysis, region of interest (ROI)–based measurements of hypodense and hyperdense artifacts, as well as of artifact-impaired bone and the urinary bladder, were conducted, and corrected attenuation and image noise were calculated as the difference of attenuation and noise between artifact-impaired and normal tissue. Two radiologists qualitatively evaluated artifact extent, bone assessment, organ assessment, and iliac vessel assessment using 5-point Likert scales.ResultsVMI110keV yielded a significant reduction of hypo- and hyperdense artifacts compared to conventional polyenergetic images (CI) and the corrected attenuation closest to 0, indicating best possible artifact reduction (hypodense artifacts: CI: 237.8 ± 71.4 HU, VMI110keV: 8.5 ± 122.5 HU; p < 0.05; hyperdense artifacts: CI: 240.6 ± 40.8 HU vs. VMI110keV: 13.0 ± 110.4 HU; p < 0.05). VMI110keV concordantly provided best artifact reduction in the bone and bladder as well as the lowest corrected image noise. In the qualitative assessment, VMI110keV received the best ratings for artifact extent (CI: 2 (1–3), VMI110keV: 3 (2–4); p < 0.05) and bone assessment (CI: 3 (1–4), VMI110keV: 4 (2–5); p < 0.05), whereas organ and iliac vessel assessments were rated highest in CI and VMI70keV.ConclusionsPCCT-derived VMI effectively reduce artifacts from THR and thereby improve assessability of circumjacent bone tissue. VMI110keV yielded optimal artifact reduction without overcorrection, yet organ and vessel assessments at that energy level and higher were impaired by loss of contrast.Clinical relevance statementPCCT-enabled artifact reduction is a feasible method for improving assessability of the pelvis in patients with total hip replacements at clinical routine imaging.Key Points• Photon-counting CT-derived virtual monoenergetic images at 110 keV yielded best reduction of hyper- and hypodense artifacts, whereas higher energy levels resulted in artifact overcorrection.• The qualitative artifact extent was reduced best in virtual monoenergetic images at 110 keV, facilitating an improved assessment of the circumjacent bone.• Despite significant artifact reduction, assessment of pelvic organs as well as vessels did not profit from energy levels higher than 70 keV, due to the decline in image contrast.

Quantification of cartilage and subchondral bone cysts on knee specimens based on a spectral photon-counting computed tomography

Spectral photon-counting computed tomography (SPCCT) is a new technique with the capability to provide mono-energetic (monoE) images with high signal to noise ratio. We demonstrate the feasibility of SPCCT to characterize at the same time cartilage and subchondral bone cysts (SBCs) without contrast agent in osteoarthritis (OA). To achieve this goal, 10 human knee specimens (6 normal and 4 with OA) were imaged with a clinical prototype SPCCT. The monoE images at 60 keV with isotropic voxels of 250 × 250 × 250 µm3 were compared with monoE synchrotron radiation CT (SR micro-CT) images at 55 keV with isotropic voxels of 45 × 45 × 45 µm3 used as benchmark for cartilage segmentation. In the two OA knees with SBCs, the volume and density of SBCs were evaluated in SPCCT images. In 25 compartments (lateral tibial (LT), medial tibial, (MT), lateral femoral (LF), medial femoral and patella), the mean bias between SPCCT and SR micro-CT analyses were 101 ± 272 mm3 for cartilage volume and 0.33 mm ± 0.18 for mean cartilage thickness. Between normal and OA knees, mean cartilage thicknesses were found statistically different (0.005 < p < 0.04) for LT, MT and LF compartments. The 2 OA knees displayed different SBCs profiles in terms of volume, density, and distribution according to size and location. SPCCT with fast acquisitions is able to characterize cartilage morphology and SBCs. SPCCT can be used potentially as a new tool in clinical studies in OA.

Empirical optimization of energy bin weights for compressing measurements with realistic photon counting x-ray detectors.

Photon counting detectors (PCDs) provide higher spatial resolution, improved contrast-to-noise ratio (CNR), and energy discriminating capabilities. However, the greatly increased amount of projection data in photon counting computed tomography (PCCT) systems becomes challenging to transmit through the slip ring, process, and store. This study proposes and evaluates an empirical optimization algorithm to obtain optimal energy weights for energy bin data compression. This algorithm is universally applicable to spectral imaging tasks including 2 and 3 material decomposition (MD) tasks and virtual monoenergetic images (VMIs). This method is simple to implement while preserving spectral information for the full range of object thicknesses and is applicable to different PCDs, for example, silicon detectors and CdTe detectors. We used realistic detector energy response models to simulate the spectral response of different PCDs and an empirical calibration method to fit a semi-empirical forward model for each PCD. We numerically optimized the optimal energy weights by minimizing the average relative Cramér-Rao lower bound (CRLB) due to the energy-weighted bin compression, for MD and VMI tasks over a range of material area density (0-40g/cm2 water, 0-2.16g/cm2 calcium). We used Monte Carlo simulation of a step wedge phantom and an anthropomorphic head phantom to evaluate the performance of this energy bin compression method in the projection domain and image domain, respectively. The results show that for 2 MD, the energy bin compression method can reduce PCCT data size by 75% and 60%, with an average variance penalty of less than 17% and 3% for silicon and CdTe detectors, respectively. For 3 MD tasks with a K-edge material (iodine), this method can reduce the data size by 62.5% and 40% with an average variance penalty of less than 12% and 13% for silicon and CdTe detectors, respectively. We proposed an energy bin compression method that is broadly applicable to different PCCT systems and object sizes, with high data compression ratio and little loss of spectral information.

CT technology: photon-counting detector computed tomography

Photon-counting detector computed tomography (PCD-CT) is aCT technology that overcomes many limitations of conventional detectors. Direct conversion of photons hitting the detector into electrical signals combined with more sensitive and accurate photon detection simultaneously allows spectral evaluation and also potential reduction in radiation exposure to the patient. The combination of energy thresholds and elimination of detector septa allows for areduction of electronic noise, an increase of spatial resolution, and an improvement of dose efficiency. Recent research has confirmed significantly reduced image noise, reduced radiation dose, increased spatial resolution, improved iodine signal, and areduction in artifacts. Spectral imaging potentiates these effects and also allows retrospective calculation of virtual monoenergetic images, virtual noncontrast images or iodine maps. Thus, the photon-counting technique offers the possibility of using various contrast agents, with the prospect of single-scan multiphase imaging or visualization of specific metabolic processes. Therefore, further research and complementary approval processes are necessary for clinical application. Likewise, further research is needed to develop and validate optimal settings and reconstructions for awide variety of situations, as well as to test new application possibilities. The only photon-counting detector CT device available on the market to date received clinical approval in 2021. It remains to be seen which other applications will become possible through improvements in hardware and software. This technology has already demonstrated an impressive superiority compared with the current standard of CT imaging, especially regarding high-resolution imaging of detailed structures and examinations with high radiation exposure.

Spectral metal artifact reduction after posterior spinal fixation in photon-counting detector CT datasets

PurposeTo investigate the usefulness of virtual monoenergetic image (VMI) reconstructions derived from scans on a novel photon-counting detector CT (PCD-CT) for artifact reduction in patients after posterior spinal fixation. MethodsThis retrospective cohort study included 23 patients status post posterior spinal fixation. Subjects were scanned on a novel PCD-CT (NAEOTOM Alpha, Siemens Healthineers, Erlangen, Germany) as part of routine clinical care. 14 sets of VMI reconstructions were derived in 10 keV increments for the interval 60–190 keV. The mean and the standard deviation (SD) of CT-values in 12 defined locations around a pair of pedicle screws on one vertebral level and the SD of homogenous fat were measured and used to calculate an artifact index (AIx). ResultsAveraged over all regions, the lowest AIx was observed at VMI levels of 110 keV (32.5 (27.8–37.9)) which was significantly different from those of VMIs ≤ 90 keV (p < 0.001) or ≥160 keV (p < 0.015), respectively. Overall AIx values increased in both lower- and higher-keV levels. Regarding individual locations, either a monotonous AIx-decrease for increasing keV values or an AIx-minimum in intermediate-keV levels (100–140 keV) was found. In locations adjacent to larger metal parts, the increase of AIx values at the high-end of the keV spectrum was mainly explained by a reappearance of streak artifacts. ConclusionOur findings suggest that 110 keV is the optimal VMI setting for overall artifact suppression. In specific anatomical regions, however, slight adjustments towards higher-keV levels may provide better results.

Changes in coronary plaque component volumes comparing different virtual monoenergetic images using photon-counting computed tomography

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): BV was supported by the ÚNKP-22-3-II-SE New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. Introduction Photon-counting CT (PCCT) allows virtual monoenergetic images (VMIs) which may aid more precise assessment of coronary plaques. We aimed to analyze how plaque component volumes change on different VMIs. Methods Coronary CT angiography images were acquired using a dual-source PCCT and VMIs were reconstructed between 40–180 keV in 10 keV increments. Polychromatic images at 120 kVp (T3D) were also reconstructed and used as reference. Quantitative image quality analysis was performed on all reconstructed images. Quantitative plaque assessment was performed on T3D images and segmentation masks were copied to all VMI images. Calcified plaque (CP; &amp;gt;350 Hounsfield units, HU), non-calcified plaque (NCP; 30–350HU) and low-attenuation NCP (LAP; −100-30HU) volumes were calculated. Results We analyzed 51 plaques from 51 patients (67% male, mean age 65±12 years). Average attenuation and contrast-to-noise ratio (CNR) decreased significantly with increasing keV levels, with similar values observed between T3D and 70 keV images (299±209 vs 303±225 HU, p = 0.15 for mean HU; 15.5±3.7 vs. 15.8±3.5, p = 0.32 for CNR). Mean NCP volume was comparable between T3D and 100–180 keV reconstructions. There was a graded decrease in mean CP volume, with a significant difference between all VMI images and T3D (p&amp;lt;0.05). LAP volume increased with increasing VMI energy levels and all VMI images showed a significant difference compared to T3D, except for 50 keV (28.0±30.8 mm3 and 28.6±30.1 mm3, respectively, p = 0.63). Conclusion Fixed threshold settings result in significantly different plaque volumes when using VMIs as compared to T3D images. Normalization protocols are needed to have comparable results between future studies.

Establishing a quality assurance program for photon counting detector (PCD) CT: Tips and caveats.

To determine the suitability of a quality assurance (QA) program based on the American College of Radiology's (ACR) CT quality control (QC) manual to fully evaluate the unique capabilities of a clinical photon-counting-detector (PCD) CT system. A daily QA program was established to evaluate CT number accuracy and artifacts for both standard and ultra-high-resolution (UHR) scan modes. A complete system performance evaluation was conducted in accordance with the ACR CT QC manual by scanning the CT Accreditation Phantom with routine clinical protocols and reconstructing low-energy-threshold (T3D) and virtual monoenergetic images (VMIs) between 40 and 120keV. Spatial resolution was evaluated by computing the modulation transfer function (MTF) for the UHR mode, and multi-energy performance was evaluated by scanning a body phantom containing four iodine inserts with concentrations between 2 and 15mg I/cc. The daily QA program identified instances when the detector needed recalibration or replacement. CT number accuracy was impacted by image type: CT numbers at 70keV VMI were within the acceptable range (defined for 120kV). Other keV VMIs and the T3D reconstruction had at least one insert with CT number outside the acceptable range. The limiting resolution was nearly 40 lp/cm based on MTF measurements, which far exceeds the 12 lp/cm maximum capability of the ACR phantom. The CT numbers in the iodine inserts were accurate on all VMIs (3.8% average percentage error), while the iodine concentrations had an average root mean squared error of 0.3mg I/cc. Protocols and parameters must be properly selected on PCD-CT to meet current accreditation requirements with the ACR CT phantom. Use of the 70keV VMI allowed passing all tests prescribed in the ACR CT manual. Additional evaluations such an MTF measurement and multi-energy phantom scans are also recommended to comprehensively evaluate PCD-CT scanner performance.

Dual-Energy CT in Cardiothoracic Imaging: Current Developments.

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating multi-energy datasets and multiple DECT applications that were developed and clinically investigated for different fields of interest. Benefits for various clinical settings, such as oncology, trauma and emergency radiology, as well as musculoskeletal and cardiovascular imaging, were recently reported in the literature. State-of-the-art applications, such as virtual monoenergetic imaging (VMI), material decomposition, perfused blood volume imaging, virtual non-contrast imaging (VNC), plaque removal, and virtual non-calcium (VNCa) imaging, can significantly improve cardiothoracic CT image workflows and have a high potential for improvement of diagnostic accuracy and patient safety.

Photon-counting CT for diagnosis of acute pulmonary embolism: potential for contrast medium and radiation dose reduction

ObjectiveTo evaluate the image quality of an ultra-low contrast medium and radiation dose CT pulmonary angiography (CTPA) protocol for the diagnosis of acute pulmonary embolism using a clinical photon-counting detector (PCD) CT system and compare its performance to a dual-energy-(DE)-CTPA protocol on a conventional energy-integrating detector (EID) CT system.MethodsSixty-four patients either underwent CTPA with the novel scan protocol on the PCD-CT scanner (32 patients, 25 mL, CTDIvol 2.5 mGy·cm) or conventional DE-CTPA on a third-generation dual-source EID-CT (32 patients, 50 mL, CTDIvol 5.1 mGy·cm). Pulmonary artery CT attenuation, signal-to-noise ratio, and contrast-to-noise-ratio were assessed as objective criteria of image quality, while subjective ratings of four radiologists were compared at 60 keV using virtual monoenergetic imaging and polychromatic standard reconstructions. Interrater reliability was determined by means of the intraclass correlation coefficient (ICC). Effective dose was compared between patient cohorts.ResultsSubjective image quality was deemed superior by all four reviewers for 60-keV PCD scans (excellent or good ratings in 93.8% of PCD vs. 84.4% of 60 keV EID scans, ICC = 0.72). No examinations on either system were considered “non-diagnostic.” Objective image quality parameters were significantly higher in the EID group (mostly p < 0.001), both in the polychromatic reconstructions and at 60 keV. The ED (1.4 vs. 3.3 mSv) was significantly lower in the PCD cohort (p < 0.001).ConclusionsPCD-CTPA allows for considerable reduction of contrast medium and radiation dose in the diagnosis of acute pulmonary embolism, while maintaining good to excellent image quality compared to conventional EID-CTPA.Clinical relevance statementClinical PCD-CT allows for spectral assessment of pulmonary vasculature with high scan speed, which is beneficial in patients with suspected pulmonary embolism, frequently presenting with dyspnea. Simultaneously PCD-CT enables substantial reduction of contrast medium and radiation dose.Key Points• The clinical photon-counting detector CT scanner used in this study allows for high-pitch multi-energy acquisitions.• Photon-counting computed tomography allows for considerable reduction of contrast medium and radiation dose in the diagnosis of acute pulmonary embolism.• Subjective image quality was rated best for 60-keV photon-counting scans.

Investigation on the proton range uncertainty with spectral CT-based virtual monoenergetic images.

The stopping power ratio (SPR) prediction error will contribute to the range uncertainty of proton therapy. Spectral CT is promising in reducing the uncertainty in SPR estimation. The purpose of this research is to determine the optimal energy pairs of SPR prediction for each tissue and to evaluate the dose distribution and range difference between the spectral CT with the optimal energy pairs method and the single energy CT (SECT) method. A new method was proposed based on image segmentation to calculate the proton dose with spectral CT images for the head and body phantom. CT number of each organ region were converted to SPR with the optimal energy pairs of each organ. The CT images were segmented into different organ parts with thresholding method. Virtual monoenergetic (VM) images from 70keV to 140keV were investigated to determine the optimal energy pairs for each organ based on Gammex 1467 phantom. The beam data of Shanghai Advanced Proton Therapy facility (SAPT) was employed in matRad (an open-source software for radiation treatment planning) for the dose calculation. The optimal energy pairs were obtained for each tissue. The dose distribution of two tumor sites (brain and lung) were calculated with the aforementioned optimal energy pairs. The maximum dose deviation between spectral CT and SECT at the target region was 2.57% and 0.84% for the lung tumor and brain tumor respectively. The range difference between spectral and SECT was significant with 1.8411mm for the lung tumor. γ passing rate was 85.95% and 95.49% for the lung tumor and brain tumor with the criterion 2%/2mm. This work presents a way to determine the optimal energy pairs for each organ and to calculate the dose distribution based on the more accurate SPR prediction.

Virtual monoenergetic dual-layer dual-energy CT images in colorectal cancer: CT diagnosis could be improved?

To compare conventional CT images and virtual monoenergetic images (VMI) at dual-layer dual-energy CT (dlDECT) in patients with colorectal cancer (CRC) through quantitative analysis and to investigate the added value of VMI. Sixty-six consecutive patients with histologically documented CRC and available VMI reconstructions were retrospectively investigated. Subsequently, forty-two patients, without any colonic disease at colonoscopy, were selected as control group. Conventional CT images and VMI reconstructions at energy levels ranging from 40 (VMI40) to 100keV (VMI100) in 10keV increments, were obtained from the late arterial phase. First, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were obtained to select the best VMI reconstruction. Finally, the diagnostic accuracy of conventional CT and VMI40 in late arterial phase was evaluated. On quantitative analysis, SNR and CNR were higher for VMI40 (19.5 ± 7.7 and 11.8 ± 6.2, respectively) with statistically significant differences compared to conventional CT (P < 0.05) and all the other VMI reconstructions (P < 0.05), except for VMI50 (P > 0.05). The addition of VMI40 to conventional CT images significantly improved the area under the curve (AUC) for the diagnosis of CRC, increasing it from 0.875 to 0.943 for reader 1 (P < 0.05) and from 0.916 to 0.954 for reader 2 (P < 0.05). The improvement was greater in the less experienced radiologist (0.068) compared to the more experienced one (0.037). VMI40 has showed the highest quantitative image parameters. Furthermore, the use of VMI40 can lead to a significant improvement in the diagnostic performance for detecting CRC.