Monoenergetic CT Research Articles

Dual-energy CT in acute cholecystitis- features predicting culture-positive bile and outcome

PurposeLow mono-energetic CT has been shown to improve visualization of acute abdominal inflammatory processes. We aimed to determine its utility in patients with acute cholecystitis and potential added value in clinical decision making. MethodsSixty-seven consecutive patients with radiological signs of cholecystitis on contrast-enhanced dual-layer CT imaging were retrospectively identified over a four-year period (2/17–8/21). A ranked Likert scale was created for imaging findings present in acute cholecystitis, including gallbladder mucosal integrity and enhancement and pericholecystic liver parenchymal enhancement. These rankings were correlated with laboratory data, followed by sensitivity, specificity, and odds-ratios calculations. ResultsMucosal integrity and pericholecystic liver enhancement were better seen on low-energetic images by unanimous consensus. Presence of pericholecystic liver enhancement and poorer mucosal wall integrity correlated with positive bile cultures (sensitivity: 93.8 % and 96.9 %, specificity: 37.5 and 50.0 %; odds-ratio: 9.0[1.1–68.1 95 %CI] and 31.0 [2.7–350.7 95 %CI], p = 0.017 and p ≤ 0.001) in patients undergoing cholecystostomy (n = 40/67). Moreover, binary regression modeling showed that the strongest predictor variable for bile culture positivity was the score for pericholecystic liver enhancement (Exp(B) = 0.6, P = 0.022). By contrast, other laboratory markers and other imaging findings (such as GB wall thickness) showed lower sensitivities (76–82 %), specificities (16–21 %) and odds ratios (0.2–4.4) for the prediction of infected bile. ConclusionsPericholecystic liver enhancement and gallbladder wall integrity are better visualized on low-DECT images. These findings also potentially predict bile culture positivity in patients with cholecystitis, which may influence clinical management including the need for intervention.

Low-KeV Virtual Monoenergetic Dual-Energy CT with Deep Learning Reconstruction for Assessing Hepatocellular Carcinoma

Low-KeV Virtual Monoenergetic Dual-Energy CT with Deep Learning Reconstruction for Assessing Hepatocellular Carcinoma

Low-iodine 40-keV virtual monoenergetic CT angiography of the lower extremities.

To evaluate a reduced iodine volume protocol for lower extremity CT angiography (CTA) using dual-energy CT (DECT). This retrospective study included consecutive patients who underwent lower extremity CTA from June to December 2022. A 10 ml 1:1 mixed test bolus was performed, followed by a 40 ml full bolus at a 2.5/s injection rate, using 400 mg/ml iodine contrast media. Conventional and 40 keV virtual monoenergetic images (VMI) were reconstructed. For both reconstructions, five main artery segments were assessed with a 3-point image quality score as well as quantitative attenuation, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements with diagnostic quality thresholds (respectively >150 HU and >3). Forty patients were included in the study (mean age 68 ± 12 yo). 200 artery segments were assessed. Median qualitative image scores were 3 [IQR, 3, 3] for both reconstructions. 40 keV VMI upgraded qualitative scores for 51 (26%) of patients, including 9 (5%) from nondiagnostic to diagnostic quality. 40 keV VMI obtained attenuation and CNR diagnostic quality for respectively 100% and 100% of segments, compared with 96% and 98% for conventional images (p < 0.001). Distal artery segments showed the most differences between 40 keV VMI and conventional images. A low-iodine lower extremity CTA protocol is feasible, with 40 keV virtual monoenergetic spectral reconstruction enabling maintained diagnostic image quality at the distal artery segments.

Single energy metal artifact reduction performs better than virtual monoenergetic dual-energy reconstruction in CT of the equine proximal phalanx.

Metal artifacts in CT negatively impact the evaluation of surgical implants and the surrounding tissues. The aim of this prospective experimental study was to evaluate the ability of a single energy metal artifact reduction (SEMAR™, Canon) algorithm and virtual monoenergetic (VM) dual-energy CT (DECT) scanning techniques to reduce metal artifacts from stainless steel screws surgically inserted into the equine proximal phalanx. Seven acquisitions of 18 cadaver limbs were performed on a Canon Aquilion One Vision CT scanner (Helical +SEMAR, Volume +SEMAR, Standard Helical, Standard Volume and VM DECT at 135, 120, and 105keV) and reconstructed in a bone kernel. Blinded subjective evaluation performed by three observers indicated a significant effect of acquisition in both adjacent tissues (P<0.001) and distant tissues (P<0.001) and the best metal artifact reduction was seen with Helical +SEMAR and Volume +SEMAR. The subjective overall preference of CT acquisition type was (1) Helical +SEMAR, (2) Volume +SEMAR, (3) VM DECT 135keV, (4) VM DECT 120keV, (5) VM DECT 105keV, (6) Standard Helical, (7) Standard Volume (P<0.001). Unblinded objective evaluation performed by one observer showed that VM DECT 120keV, Helical +SEMAR, and Volume +SEMAR performed similarly and were objectively the best at reducing blooming artifact. Overall, the best metal artifact reduction was obtained with SEMAR, followed by VM DECT. However, VM DECT performance varies with energy level and was associated with decreased image quality in distant tissues and artifactual overcorrection of metal artifacts at high energy levels.

Quantitative parameters in novel spectral computed tomography: Assessment of Ki-67 expression in patients with gastric adenocarcinoma.

The level of Ki-67 expression has served as a prognostic factor in gastric cancer. The quantitative parameters based on the novel dual-layer spectral detector computed tomography (DLSDCT) in discriminating the Ki-67 expression status are unclear. To investigate the diagnostic ability of DLSDCT-derived parameters for Ki-67 expression status in gastric carcinoma (GC). Dual-phase enhanced abdominal DLSDCT was performed preoperatively in 108 patients with gastric adenocarcinoma. Primary tumor monoenergetic CT attenuation value at 40-100 kilo electron volt (kev), the slope of the spectral curve (λHU), iodine concentration (IC), normalized IC (nIC), effective atomic number (Zeff) and normalized Zeff (nZeff) in the arterial phase (AP) and venous phase (VP) were retrospectively compared between patients with low and high Ki-67 expression in gastric adenocarcinoma. Spearman's correlation coefficient was used to analyze the association between the above parameters and Ki-67 expression status. Receiver operating characteristic (ROC) curve analysis was performed to compare the diagnostic efficacy of the statistically significant parameters between two groups. Thirty-seven and 71 patients were classified as having low and high Ki-67 expression, respectively. CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, and Zeff-related parameters were significantly higher, but IC-related parameters were lower in the group with low Ki-67 expression status than the group with high Ki-67 expression status, and other analyzed parameters showed no statistical difference between the two groups. Spearman's correlation analysis showed that CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, Zeff, and nZeff exhibited a negative correlation with Ki-67 status, whereas IC and nIC had positive correlation with Ki-67 status. The ROC analysis demonstrated that the multi-variable model of spectral parameters performed well in identifying the Ki-67 status [area under the curve (AUC) = 0.967; sensitivity 95.77%; specificity 91.89%)]. Nevertheless, the differentiating capabilities of single-variable model were moderate (AUC value 0.630 - 0.835). In addition, the nZeff VP and nICVP (AUC 0.835 and 0.805) showed better performance than CT40 kev-VP, CT70 kev-VP and CT100 kev-VP (AUC 0.630, 0.631 and 0.662) in discriminating the Ki-67 status. Quantitative spectral parameters are feasible to distinguish low and high Ki-67 expression in gastric adenocarcinoma. Zeff and IC may be useful parameters for evaluating the Ki-67 expression.

Evaluation of thin-slice abdominal DECT using deep-learning image reconstruction in 74keV virtual monoenergetic images: an image quality comparison.

To compare noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image quality using deep-learning image reconstruction (DLIR) vs. adaptive statistical iterative reconstruction (ASIR-V) in 0.625 and 2.5mm slice thickness gray scale 74keV virtual monoenergetic (VM) abdominal dual-energy CT (DECT). This retrospective study was approved by the institutional review board and regional ethics committee. We analysed 30 portal-venous phase abdominal fast kV-switching DECT (80/140kVp) scans. Data were reconstructed to ASIR-V 60% and DLIR-High at 74keV in 0.625 and 2.5mm slice thickness. Quantitative HU and noise assessment were measured within liver, aorta, adipose tissue and muscle. Two board-certified radiologists evaluated image noise, sharpness, texture and overall quality based on a five-point Likert scale. DLIR significantly reduced image noise and increased CNR as well as SNR compared to ASIR-V, when slice thickness was maintained (p < 0.001). Slightly higher noise of 5.5-16.2% was measured (p < 0.01) in liver, aorta and muscle tissue at 0.625mm DLIR compared to 2.5mm ASIR-V, while noise in adipose tissue was 4.3% lower with 0.625mm DLIR compared to 2.5mm ASIR-V (p = 0.08). Qualitative assessments demonstrated significantly improved image quality for DLIR particularly in 0.625mm images. DLIR significantly reduced image noise, increased CNR and SNR and improved image quality in 0.625mm slice images, when compared to ASIR-V. DLIR may facilitate thinner image slice reconstructions for routine contrast-enhanced abdominal DECT.

Effects of different virtual monoenergetic CT image data on chest wall post-processing "unfolded ribs" and proposal of an algorithm improvement.

To find out if the use of different virtual monoenergetic data sets enabled by DECT technology might have a negative impact on post-processing applications, specifically in case of the "unfolded ribs" algorithm. Metal or beam hardening artifacts are suspected to generate image artifacts and thus reduce diagnostic accuracy. This paper tries to find out how the generation of "unfolded rib" CT image reformates is influenced by different virtual monoenergetic CT images and looks for possible improvement of the post-processing tool. Between March 2021 and April 2021, thin-slice dual-energy CT image data of the chest were used creating "unfolded rib" reformates. The same data sets were analyzed in three steps: first the gold standard with the original algorithm on mixed image data sets followed by the original algorithm on different keV levels (40-120keV) and finally using a modified algorithm which in the first step used segmentation based on mixed image data sets, followed by segmentation based on different keV levels. Image quality (presence of artifacts), lesion and fracture detectability were assessed for all series. Both, the original and the modified algorithm resulted in more artifact-free image data sets compared to the gold standard. The modified algorithm resulted in significantly more artifact-free image data sets at the keV-edges (40-120keV) compared the original algorithm. Especially "black artifacts" and pseudo-lesions, potentially inducing false positive findings, could be reduced in all keV level with the modified algorithm. Detection of focal sclerotic, lytic or mixed (k = 0.990-1.000) lesions was very good for all keV levels. The Fleiss-kappa test for detection of fresh and old rib fractures was ≥ 0.997. The use of different virtual monoenergetic keVs for the "unfolded rib" algorithm is generating different artifacts. Segmentation-based artifacts could be eliminated by the proposed new algorithm, showing the best results at 70-80keV.

Quantitative and qualitative assessments of deep learning image reconstruction in low-keV virtual monoenergetic dual-energy CT.

To evaluate a novel deep learning image reconstruction (DLIR) technique for dual-energy CT (DECT) derived virtual monoenergetic (VM) images compared to adaptive statistical iterative reconstruction (ASIR-V) in low kiloelectron volt (keV) images. We analyzed 30 venous phase acute abdominal DECT (80/140 kVp) scans. Data were reconstructed to ASIR-V and DLIR-High at four different keV levels (40, 50, 74, and 100) with 1- and 3-mm slice thickness. Quantitative Hounsfield unit (HU) and noise assessment were measured within the liver, aorta, fat, and muscle. Subjective assessment of image noise, sharpness, texture, and overall quality was performed by two board-certified radiologists. DLIR reduced image noise by 19.9-35.5% (p < 0.001) compared to ASIR-V in all reconstructions at identical keV levels. Contrast-to-noise ratio (CNR) increased by 49.2-53.2% (p < 0.001) in DLIR 40-keV images compared to ASIR-V 50 keV, while no significant difference in noise was identified except for 1 and 3 mm in aorta and for 1-mm liver measurements, where ASIR-V 50 keV showed 5.5-6.8% (p < 0.002) lower noise levels. Qualitative assessment demonstrated significant improvement particularly in 1-mm reconstructions (p < 0.001). Lastly, DLIR 40 keV demonstrated comparable or improved image quality ratings when compared to ASIR-V 50 keV (p < 0.001 to 0.22). DLIR significantly reduced image noise compared to ASIR-V. Qualitative assessment showed that DLIR significantly improved image quality particularly in thin sliced images. DLIR may facilitate 40 keV as a new standard for routine low-keV VM reconstruction in contrast-enhanced abdominal DECT. • DLIR enables 40 keV as the routine low-keV VM reconstruction. • DLIR significantly reduced image noise compared to ASIR-V, across a wide range of keV levels in VM DECT images. • In low-keV VM reconstructions, improvements in image quality using DLIR were most evident and consistent in 1-mm sliced images.

Performance of an Artificial Intelligence-based Application for the Detection of Plaque-based Stenosis on Monoenergetic Coronary CT Angiography: Validation by Invasive Coronary Angiography

To explore the value of an artificial intelligence (AI)-based application for identifying plaque-specific stenosis and obstructive coronary artery disease from monoenergetic spectral reconstructions on coronary computed tomography angiography (CTA). This retrospective study enrolled 71 consecutive patients (52 men, 19 women; 63.3 ± 10.7 years) who underwent coronary CTA and invasive coronary angiography for diagnosing coronary artery disease. The conventional 120 kVp images and eight different virtual monoenergetic images (VMIs) (from 40 keV to 140 keV at increment of 10 keV) were reconstructed. An AI system automatically detected plaques from the conventional 120 kVp images and VMIs and calculated the degree of stenosis, which was further compared to invasive coronary angiography. The assessment was performed at a segment, vessel, and patient level. Vessel and segment-based analyses showed comparable diagnostic performance between conventional CTA images and VMIs from 50 keV to 90 keV. For vessel-based analysis, the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of conventional CTA were 74.3% (95% CI: 64.9%-82.0%), 85.6% (95% CI: 77.0%-91.4%), 84.3% (95% CI: 75.2%-90.7%), 76.1% (95% CI: 67.1%-83.3%) and 79.8% (95% CI: 73.7%-84.9%), respectively; the average sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy values of the VMIs ranging from 50 keV to 90 keV were 71.6%, 90.7%, 87.5%, 64.1% and 81.6%, respectively. For plaque-based assessment, diagnostic performance of the average VMIs ranging from 50 keV to 100 keV showed no significant statistical difference in diagnostic accuracy compared to those of conventional CTA images in detecting calcified (91.4% vs. 93.8%, p > 0.05), noncalcified (92.6% vs. 85.2%, p > 0.05) or mixed (80.2% vs. 81.2%, p > 0.05) stenosis, although the specificity was slightly higher (53.4% vs. 40.0%, p > 0.05) in detecting stenosis caused by mixed plaques. For VMIs above 100 keV, the diagnostic accuracy dropped significantly. Our study showed that the performance of an AI-based application employed to detect significant coronary stenosis in virtual monoenergetic reconstructions ranging from 50 keV to 90 keV was comparable to conventional 120 kVp reconstructions.

Virtual monoenergetic dual-energy CT reconstructions at 80 keV are optimal non-contrast CT technique for early stroke detection.

Virtual monoenergetic (VM) dual-energy computed tomography (DE-CT) enables grey-to-white matter contrast-to-noise ratio optimization, potentially increasing ischaemic brain oedema visibility. The aim of this study was to compare the diagnostic accuracy of VM and standard DE-CT reconstructions for early stroke detection. Consecutive patients with non-contrast DE-CT of the brain scanned within 12 h of stroke symptom onset were prospectively included in the study. Patients with other significant brain pathology were excluded. Two radiologists jointly evaluated standard and VM reconstructions (from 40 to 190 keV at increments of 10 keV) for early stroke signs on a four-point Likert scale: (a) stroke definitely present, (b) stroke probably present, (c) probably no stroke, and (d) definitely no stroke. Follow-up imaging and clinical data served as the standard of reference. Diagnostic accuracy was evaluated by receiver operating characteristic analysis. Stroke incidence among 184 patients was 76%. In 64 patients follow-up imaging served as the standard of reference: ischemic brain oedema detection was significantly more accurate on VM reconstructions at 80 keV compared with standard DE-CT reconstructions (area under the curve (AUC) = 0.821 vs. AUC = 0.672, p = 0.002). The difference was most prominent within the first 3 h after symptom onset (at 11%, AUC = 0.819 vs. AUC = 0.709, p = 0.17) and in patients with National Institutes of Health Stroke Scale above 16 (at 37.5%, AUC = 1 vs. AUC = 0.625, p = 0.14). VM DE-CT reconstructions at 80 keV appear to be the optimal non-contrast CT technique for diagnosing early ischaemic stroke, particularly within the first 3 h after symptom onset and in severely ill patients.

COMPARISON OF METAL ARTEFACTS FOR DIFFERENT DUAL ENERGY CT TECHNIQUES.

This study compares dual-energy computed tomography (DECT) images of a phantom including different material inserts and with additional lateral titanium or stainless steel inserts, simulating bilateral hip prostheses. Dual-source (DS) and fast kV-switching (FKS) DECT with/without metal artefact reduction (MAR) were compared with regards to virtually monoenergetic CT number accuracy and the depiction of different materials. Streak artefacts were observed between the metal inserts that were more severe with steel compared to titanium inserts. The artefact severity and CT number accuracy depended on the photon energy (keV) for both DECT techniques. While MAR generally increased the CT number accuracy and material depiction within the streak artefacts, it sometimes decreased the accuracy outside the streak artefacts for both DS and FKS. FKS depicted the metal inserts more accurately than DS with regards to both CT numbers and external diameter.

Conditional generative adversarial networks to generate pseudo low monoenergetic CT image from a single-tube voltage CT scanner.

To generate pseudo low monoenergetic CT images of the abdomen from 120-kVp CT images with cGAN. We retrospectively included 48 patients who underwent contrast-enhanced abdominal CT using dual-energy CT. We reconstructed paired data sets of 120 kVp CT images and virtual low monoenergetic (55-keV) CT images. cGAN was prepared to generate pseudo 55-keV CT images from 120-kVp CT images. The pseudo 55keV CT images in epoch 10, 50, 100, and 500 were compared to the 55keV images generated using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The PSNRs were 28.0, 28.5, 28.6, and 28.8 at epochs 10, 50, 100, and 500, respectively. The SSIM was approximately constant from epochs 50 to 500. Pseudo low monoenergetic abdominal CT images were generated from 120-kVp CT images using cGAN, and the images had good quality similar to that of monochromatic images obtained with DECT software.

Accuracy of 190-keV Virtual Monoenergetic Dual-Energy CT for Determining the Presence or Absence of Intravitreal Silicone Oil.

OBJECTIVE. We hypothesized that intravitreal silicone oil would show attenuation similar to that of fat on dual-energy CT 190-keV virtual monoenergetic images (VMIs) with high frequency and that this appearance would enable confident determination of the presence or absence of intravitreal silicone oil. The purpose of the present study was to test our hypothesis in a blinded multireader study of selected patients with and without intravitreal silicone oil as well as in an unblinded ROI-based assessment. MATERIALS AND METHODS. In this retrospective study of 50 dual-energy CT examinations of the head that included 100 globes (64 that were normal, 19 that exhibited hyperattenuating mimics, and 17 that contained silicone oil), three neuroradiologists independently assessed anonymized 190-keV VMIs for intravitreal attenuation similar to that of fat. Interobserver agreement was calculated. The mean attenuation value on weighted-average images and 190-keV VMIs was recorded. RESULTS. The three readers identified intravitreal attenuation values similar to that of fat in 100% of globes that contained silicone oil and 0% of globes that did not contain silicone oil (100% sensitivity, specificity, PPV, and accuracy) with 100% agreement. The mean attenuation value of silicone oil on 190-keV VMIs was -55 HU, which was significantly less than the mean attenuation on 190-keV VMIs of normal globes and hyperattenuating mimics (p < .001 for both). CONCLUSION. Intravitreal silicone oil shows attenuation of -60 to -49 HU on 190-keV VMIs. With the use of these images only, three neuroradiologists identified intravitreal silicone oil with 100% accuracy and perfect agreement.

Optimal Mono-energy in Mono-energetic Spectral Computed Tomography of Enhanced Renal Cortex in Cortical Phase Based on Iodine Concentration

Objective To identify the optimal mono-energetic enhanced spectral CT for renal cortex in cortical phase based on the iodine concentration. Methods Fifty patients with normal renal function received the abdominal enhanced spectral CT examination.The iodine concentration and CT values of the multiple mono-energetic spectral images were measured on renal cortex in cortical phase,and the correlation between the iodine concentration and the CT values and the coefficient of variation(CV)were analyzed. Results The correlation analysis demonstrated that the correlation coefficient was 0.994,0.994,0.993,0.987,0.976,0.960,and 0.938 between mono-energetic spectral CT images(40-100 keV with interval 10 keV,respectively)and iodine concentration(all P <0.001).The correlation coefficients of 40 keV,50 keV(P=0.007)and 60 keV(P=0.030)were significantly higher compared with that of 70 keV,and the correlation coefficients were not significantly among 40 keV,50 keV and 60 keV(P =0.590).The CV of renal cortex in cortical phase was 0.21,0.20,and 0.19 for 40 keV,50 keV,and 60 keV,respectively. Conclusion 60 keV is the optimal mono-energy for the enhanced spectral CT of the renal cortex in cortical phase.

Virtual calcium-suppression in dual energy computed tomography predicts metabolic activity of focal MM lesions as determined by fluorodeoxyglucose positron-emission-tomography

PurposeRecent studies showed that dual energy CT (DECT) allows for detection of bone marrow infiltration in multiple myeloma (MM) by obtaining virtual non-calcium (VNCa) images. This feasibility study investigated, if VNCa imaging might discriminate metabolically active, focal lesions in MM against avital lesions in MM patients, considering fluorodeoxyglucose positron-emission-tomography CT (FDG PET/CT) as the standard of reference. MethodThe study included 60 osteolytic lesions in 10 consecutive low-dose whole body CT scans of patients with MM, who underwent both FDG PET/CT and DECT at a tertiary care university hospital. Circular ROI measurements were performed in predefined lesions on the monoenergetic CT (MECT) and VNCa images by three blinded radiologists. Each lesion was rated vital or avital by a blinded specialist of nuclear medicine, based on their FDG metabolism. ResultsEach of the three readers could separate FDG PET/CT negative and positive MM lesions when analyzing the VNCa images, while MECT did not show a significant difference. Best results were yielded by high calcium suppression with excellent inter-rater reliability (average sensitivity 0.91, specificity 0.88, cutoff -46.9 HU), followed by medium and low calcium suppression. ConclusionsIn contrast to MECT imaging, VNCa imaging in DECT appears to be feasible to assess metabolic activity of focal MM lesions as defined by the standard of reference, FDG PET/CT. Considering the higher cost and radiation exposure of FDG PET/CT, DECT VNCa imaging might develop to be the modality of choice to assess metabolic activity of focal MM lesions.

Improved Sensitivity and Reader Confidence in CT Colonography Using Dual-Layer Spectral CT: A Phantom Study.

Background Limited cathartic preparations for CT colonography with fecal tagging can improve patient comfort but may result in nondiagnostic examinations from poorly tagged stool. Dual-energy CT may overcome this limitation by improving the conspicuity of the contrast agent, but more data are needed. Purpose To investigate whether dual-energy CT improves polyp detection in CT colonography compared with conventional CT at different fecal tagging levels in vitro. Materials and Methods In this HIPAA-compliant study, between December 2017 and August 2019, a colon phantom 30 cm in diameter containing 60 polyps of different shapes (spherical, ellipsoid, flat) and size groups (5-9 mm, 11-15 mm) was constructed and serially filled with simulated feces tagged with four different iodine concentrations (1.26, 2.45, 4.88, and 21.00 mg of iodine per milliliter), then it was scanned with dual-energy CT with and without an outer fat ring to simulate large body size (total diameter, 42 cm). Two readers independently reviewed conventional 120-kVp CT and 40-keV monoenergetic dual-energy CT images to record the presence of polyps and confidence (three-point scale.) Generalized estimating equations were used for sensitivity comparisons between conventional CT and dual-energy CT, and a Wilcoxon signed-rank test was used for reader confidence. Results Dual-energy CT had higher overall sensitivity for polyp detection than conventional CT (58.8%; 95% confidence interval [CI]: 49.7%, 67.3%; 564 of 960 polyps vs 42.1%; 95% CI: 32.1%, 52.8%; 404 of 960 polyps; P < .001), including with the fat ring (48% and 31%, P < .001). Reader confidence improved with dual-energy CT compared with conventional images on all tagging levels (P < .001). Interrater agreement was substantial (κ = 0.74; 95% CI: 0.70, 0.77). Conclusion Compared with conventional 120-kVp CT, dual-energy CT improved polyp detection and reader confidence in a dedicated dual-energy CT colonography phantom, especially with suboptimal fecal tagging. © RSNA, 2020.

Virtual monochromatic reconstructions of dual energy CT in abdominal trauma: optimization of energy level improves pancreas laceration conspicuity and diagnostic confidence.

Pancreatic injury is associated with significant morbidity and mortality. Pancreatic lacerations can be challenging to identify as the pancreas is not scanned at peak enhancement in most trauma CT protocols. This study qualitatively and quantitively assessed pancreatic lacerations with virtual monoenergetic dual-energy CT (DE CT) to establish an optimal energy level for visualization of pancreatic lacerations. Institutional review board approval was obtained. We retrospectively examined 17 contrast-enhanced CT studies in patients with blunt trauma with MRCP, ERCP, or surgically proven pancreatic lacerations. All studies were performed in our Emergency Department from 2016 to 2019 with a 128 slice dual-source DE CT scanner. Conventional 120kVp and noise-optimized virtual monoenergetic imaging (VMI) datasets were created. VMI energy levels were constructed from 40 to 100keV in 10keV increments and analyzed quantitatively and qualitatively. Pancreatic laceration attenuation, background parenchymal attenuation, and noise were calculated. Qualitative assessment was performed by two independent readers. The optimal CNR for the assessment of pancreatic lacerations was observed at VMI-40 in comparison with standard reconstructions and the remaining VMI energy levels (p = 0.001). Readers reported improved contrast resolution, diagnostic confidence, and laceration conspicuity at VMI at 40keV (p = 0.016, p = 0.002, and p = 0.0012 respectively). However, diagnostic acceptability and subjective noise were improved on conventional polyenergentic images (p = 0.0006 and p = 0.001 respectively). Dual energy CT at VMI-40 maximizes the CNR of pancreatic laceration, improves diagnostic confidence, and increases laceration conspicuity.

Measurement Reliability and Diagnostic Accuracy of Virtual Monoenergetic Dual-Energy CT in Patients with Colorectal Liver Metastases

To compare dual-energy CT virtual monoenergetic images (VMI) and standard reconstructions for reliability of quantitative size measurements and diagnostic accuracy for the detection of colorectal liver metastases (CRLM). We retrospectively included 98 patients (mean age, 61.1±11.5 years) with colorectal cancer, of whom 49 subjects had CRLM. All patients underwent a portal-venous phase dual-energy CT examination. Standard linearly-blended reformats and 40-keV VMI were reconstructed. For both reconstruction techniques, two blinded readers performed measurements of CRLM twice in a preset sequence. Three additional radiologists independently assessed all liver lesions in terms of dignity (benign vs. malignant). Sensitivity, specificity and diagnostic accuracy were calculated on a per-patient basis using MRI as reference standard. Readers scored the suitability for metric measurements and their diagnostic confidence using 5-point Likert scales. Inter-rater agreement was evaluated using intraclass correlation coefficient (ICC). Inter-rater agreement for lesion size measurements was higher for 40-keV VMI (ICC, 0.88) compared to standard linearly-blended series (ICC, 0.80). Sensitivity and diagnostic accuracy for the detection of CRLM were significantly higher for VMI at 40-keV compared to standard reconstructions (90.6% vs. 80.6%, and 89.1% vs. 81.3%; p < 0.001). Reader scores indicated that 40-keV VMI were more suitable for metric lesion measurements and provided greater diagnostic confidence compared to standard reformats (median, 5 vs. 3, and 5 vs. 4; both p < 0.001). Low-keV VMI reconstructions improve reliability of quantitative size measurements and diagnostic accuracy for the assessment of CRLM compared to standard linearly-blended images.

Optimal energy selection for proton stopping-power-ratio estimation using dual-energy CT-based monoenergetic imaging

The dual-energy computed tomography (DECT)-based approach holds promise in reducing the overall uncertainty in proton stopping-power-ratio (SPR) estimation, but cannot be easily implemented with most commercial proton treatment planning systems (TPS). In this study, we revisited the idea of coupling the stoichiometric calibration method with virtual monoenergetic CT datasets (MonoCT) generated by modern DECT scanners, because of its readiness for implementation with the existing TPS. Our objective was to determine the optimal energy of the MonoCT dataset for stoichiometric calibration and estimate the overall uncertainty in SPR estimation at the optimal energy. We performed stoichiometric calibration for MonoCT datasets across the energy range available on a Siemens Force DECT scanner and a Philips IQon DECT scanner in a 10 keV step. We estimated the uncertainties of different sources (imaging, modeling, and inherent uncertainties) for different tissue types (lung, soft, and bone tissues) associated with each energy; these were then combined into a single composite uncertainty for three tumor sites (head-and-neck (HN), lung, and prostate). The optimal energy was eventually selected based on the composite range uncertainty, which turned out to be 160 keV for both DECT scanners. At 160 keV, the total uncertainties (2σ) in SPR estimation were determined to be 3.2%–4.5%, 0.9%, and 1.4%–1.6% for lung, soft, and bony tissues, respectively. These results were comparable to the corresponding values estimated for the DECT approach evaluated in our previous study: 3.8%, 1.2% and 2.0%, for lung, soft, and bony tissues, respectively. The composite range uncertainties (2σ) were estimated as 1.5%, 1.7%, and 1.5% for prostate, lung, and HN, respectively. Our results demonstrated the potential of MonoCT images for reducing proton SPR uncertainty. Further clinical studies are needed to compare this approach with the DECT approach directly on real patient cases.

Virtual monoenergetic dual-energy CT for evaluation of hepatic and splenic lacerations.

To evaluate the utility of virtual monoenergetic imaging in assessing hepatic and splenic lacerations and to determine the optimal energy level to maximize injury contrast-to-noise ratio. We retrospectively examined 49 contrast-enhanced abdominal CT studies performed on a dual-source dual-energy CT (DECT) scanner with reported liver and/or splenic lacerations. All studies included portal venous phase imaging acquired simultaneously at low (80 or 100kVp) and high (140kVp with tin filtration) energy levels. Conventional 120kVp-equivalent images were generated for routine review by blending the low and high energy acquisitions. Virtual monoenergetic reconstructions were retrospectively generated in 10keV increments from 40 to 90keV. Liver or splenic laceration attenuation, background parenchymal attenuation, and noise were measured on each set of monoenergetic and conventional images. Injury-to-parenchyma contrast and contrast-to-noise ratios (CNR) were calculated. Differences between CNR of monoenergetic series and conventional images were assessed with a paired t test. Liver laceration was identified in 28 patients, and splenic laceration in 22 patients. Background noise was lower at higher monoenergetic levels, with the lowest noise seen at 90keV, less than that of conventional images (stddev 8.0 for 90keV and 8.5 for conventional based on noise of uninjured liver/spleen parenchyma, p < 0.001). For both liver and splenic lacerations, injury-to-parenchyma contrast was greater at lower monoenergetic levels, with maximum at 40keV. Contrast at 40-70keV was significantly greater than that of conventional images (p < 0.001). Injury-to parenchyma CNR was also greater at 40-70keV than that of conventional images and with statistical significance. CNR was highest at 40keV for both liver (6.5 for 40keV and 5.4 for conventional, p < 0.001) and splenic lacerations (7.5 vs. 5.8, p < 0.001). DECT virtual monoenergetic imaging at low keV improves injury-to-parenchyma CNR of hepatic and splenic lacerations compared with traditional polyenergetic reconstructions. Specially, the optimal energy level for assessing both was 40keV.