Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques.

OBJECTIVES: To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches. METHODS: Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration. RESULTS: Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001). CONCLUSIONS: We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver. CLINICAL RELEVANCE STATEMENT: Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging. KEY POINTS: • Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Comparison of Four Dual-Energy CT Scanner Technologies for Determining Renal Stone Composition: A Phantom Approach.

Background Studies have investigated the value of various dual-energy CT (DECT) technologies for determining renal stone composition. However, sparse multivendor comparison data exist. Purpose To compare the performance of four DECT technologies in determining renal stone composition at standard- and low-dose acquisitions. Materials and Methods This was an in vitro phantom study. Seventy-one urinary stones (size: 2.7-14.1 mm) of known chemical composition (51 calcium, four struvite, four cystine, and 12 urate) were placed in a custom-made cylindrical phantom. Consecutive scans with manufacturer-recommended protocols and dose-optimized institutional protocols (up to 80% reduction in volumetric CT dose index) were obtained with rapid kilovolt peak switching DECT (rsDECT) (n = 2), dual-source DECT (n = 2), twin-beam DECT (tbDECT) (n = 1), and dual-layer detector-based CT (dlDECT) (n = 1) scanners. The image data sets were analyzed using effective atomic number and dual-energy ratio indexes of maximally available and comparable spectra. The performance of each combination of scanner technology, method, and acquisition was assessed. Logistic regression models were used to calculate the area under the receiver operating characteristic curve (AUC). Results After image analysis, all scanners except tbDECT had an AUC greater than 0.95 in at least one acquisition in distinguishing urate from other stones. All DECT techniques were able to help differentiate calcium oxalate monohydrate stones with moderate accuracy (AUC: 0.70-0.83), and brushite was differentiated from urate with AUC greater than 0.99. There was no correlation between performance and acquisition with dose-optimized and/or vendor-recommended settings. Conclusion All four dual-energy CT (DECT) technologies enabled accurate determination of stone composition at standard- and low-dose acquisitions; however, performance varied based on the scanner parameters, DECT technique, and stone type. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Ringl and Apfaltrer in this issue.

Robustness of dual-energy CT-derived radiomic features across three different scanner types.

OBJECTIVES: To investigate the robustness of radiomic features between three dual-energy CT (DECT) systems. METHODS: An anthropomorphic body phantom was scanned on three different DECT scanners, a dual-source (dsDECT), a rapid kV-switching (rsDECT), and a dual-layer detector DECT (dlDECT). Twenty-four patients who underwent abdominal DECT examinations on each of the scanner types during clinical follow-up were retrospectively included (n = 72 examinations). Radiomic features were extracted after standardized image processing, following ROI placement in phantom tissues and healthy appearing hepatic, splenic and muscular tissue of patients using virtual monoenergetic images at 65 keV (VMI65keV) and virtual unenhanced images (VUE). In total, 774 radiomic features were extracted including 86 original features and 8 wavelet transformations hereof. Concordance correlation coefficients (CCC) and analysis of variances (ANOVA) were calculated to determine inter-scanner robustness of radiomic features with a CCC of ≥ 0.9 deeming a feature robust. RESULTS: None of the phantom-derived features attained the threshold for high feature robustness for any inter-scanner comparison. The proportion of robust features obtained from patients scanned on all three scanners was low both in VMI65keV (dsDECT vs. rsDECT:16.1% (125/774), dlDECT vs. rsDECT:2.5% (19/774), dsDECT vs. dlDECT:2.6% (20/774)) and VUE (dsDECT vs. rsDECT:11.1% (86/774), dlDECT vs. rsDECT:2.8% (22/774), dsDECT vs. dlDECT:2.7% (21/774)). The proportion of features without significant differences as per ANOVA was higher both in patients (51.4-71.1%) and in the phantom (60.6-73.4%). CONCLUSIONS: The robustness of radiomic features across different DECT scanners in patients was low and the few robust patient-derived features were not reflected in the phantom experiment. Future efforts should aim to improve the cross-platform generalizability of DECT-derived radiomics. KEY POINTS: • Inter-scanner robustness of dual-energy CT-derived radiomic features was on a low level in patients who underwent clinical examinations on three DECT platforms. • The few robust patient-derived features were not confirmed in our phantom experiment. • Limited inter-scanner robustness of dual-energy CT derived radiomic features may impact the generalizability of models built with features from one particular dual-energy CT scanner type.

Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.

OBJECTIVES: There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC. METHODS: In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set. RESULTS: Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively. CONCLUSION: FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions. KEY POINTS: • Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.

Arterial involvement and resectability scoring system to predict R0 resection in patients with pancreatic ductal adenocarcinoma treated with neoadjuvant chemoradiation therapy.

OBJECTIVES: To derive a CT-based scoring system incorporating arterial involvement and resectability status to predict R0 resection in patients with pancreatic ductal adenocarcinoma (PDAC) undergoing neoadjuvant chemoradiation therapy (CRT). METHODS: This retrospective study included 112 patients with PDAC who underwent dynamic contrast-enhanced CT before and after neoadjuvant CRT. A 5-point score was used to determine arterial involvement (A score; 1 = no involvement, 2 = haziness, 3 = abutment, 4 = encasement, 5 = deformity) and 4-point score evaluating resectability status (R score; 1 = resectable, 2 = borderline resectable [BR] with venous involvement, 3 = BR with arterial involvement, 4 = locally advanced [LA]). A score before and after CRT were summed with R score before and after CRT to compute the AR score (ARtotal). The associations between ARtotal, R0 resection, overall survival (OS), and disease-free survival (DFS) were assessed. RESULTS: The ARtotal was associated with R0 resection (p < .001) and showed area under the ROC curve of 0.79 for differentiating R0 and R1 resections. Median OS was significantly lower for patients with ARtotal  > 9 (median: 35.2 months) compared to patients with ARtotal ≤ 9 (median: not estimable) (p < .001). Similar results were observed for DFS (median, 16.8 months in > 9 vs median, not estimable in ≤ 9; p < .001). CONCLUSIONS: A composite score which incorporates degree of arterial involvement and resectability status before and after neoadjuvant CRT is associated with R0 resection and discriminates between R0 and R1 resections in PDAC. KEY POINTS: • A scoring system incorporating arterial involvement and resectability status was associated with R0 resection. • ARtotal > 9 could predict patients' overall and disease-free survival.

Renal Lesion Characterization by Dual-Layer Dual-Energy CT: Comparison of Virtual and True Unenhanced Images.

BACKGROUND. Prior studies have provided mixed results for the ability to replace true unenhanced (TUE) images with virtual unenhanced (VUE) images when characterizing renal lesions by dual-energy CT (DECT). Detector-based dual-layer DECT (dlDECT) systems may optimize performance of VUE images for this purpose. OBJECTIVE. The purpose of this article was to compare dual-phase dlDECT examinations evaluated using VUE and TUE images in differentiating cystic and solid renal masses. METHODS. This retrospective study included 110 patients (mean age, 64.3 ± 11.8 years; 46 women, 64 men) who underwent renal-mass protocol dlDECT between July 2018 and February 2022. TUE, VUE, and nephrographic phase image sets were reconstructed. Lesions were diagnosed as solid masses by histopathology or MRI. Lesions were diagnosed as cysts by composite criteria reflecting findings from MRI, ultrasound, and the TUE and nephrographic phase images of the dlDECT examinations. One radiologist measured lesions' attenuation on all dlDECT image sets. Lesion characterization was compared between use of VUE and TUE images, including when considering enhancement of 20 HU or greater to indicate presence of a solid mass. RESULTS. The analysis included 219 lesions (33 solid masses; 186 cysts [132 simple, 20 septate, 34 hyperattenuating]). TUE and VUE attenuation were significantly different for solid masses (33.4 ± 7.1 HU vs 35.4 ± 8.6 HU, p = .002), simple cysts (10.8 ± 5.6 HU vs 7.1 ± 8.1 HU, p < .001), and hyperattenuating cysts (56.3 ± 21.0 HU vs 47.6 ± 16.3 HU, p < .001), but not septate cysts (13.6 ± 8.1 HU vs 14.0 ± 6.8 HU, p = .79). Frequency of enhancement 20 HU or greater when using TUE and VUE images was 90.9% and 90.9% in solid masses, 0.0% and 9.1% in simple cysts, 15.0% and 10.0% in septate cysts, and 11.8% and 38.2% in hyperattenuating cysts. All solid lesions were concordant in terms of enhancement 20 HU or greater when using TUE and VUE images. Twelve simple cysts and nine hyperattenuating cysts showed enhancement of 20 HU or greater when using VUE but not TUE images. CONCLUSION. Use of VUE images reliably detected enhancement in solid masses. However, VUE images underestimated attenuation of simple and hyperattenuating cysts, leading to false-positive findings of enhancement by such lesions. CLINICAL IMPACT. The findings do not support replacement of TUE acquisitions with VUE images when characterizing renal lesions by dlDECT.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels.

BACKGROUND. Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC) values, particularly at low iodine levels. OBJECTIVE. The purpose of this study was to develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. METHODS. An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using root-mean-square error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. RESULTS. In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mg I/mL compared with 0.40 ± 0.08 mg I/mL for ICCP (38% decrease in mean RMSE; p < .05). Intrapatient between-platform variability across serial DECT examinations was higher for ICPB than ICCP (RMSD, 97% vs 88%; p < .001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD, 97% vs 101%; p = .12) or portal vein (RMSD, 97% vs 97%; p = .81). CONCLUSION. The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. CLINICAL IMPACT. With further validation, the cross-platform method, which has been implemented as a web-based app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Longitudinal reproducibility of attenuation measurements on virtual unenhanced images: multivendor dual-energy CT evaluation.

OBJECTIVES: The accuracy of virtual unenhanced (VUE) images has been extensively investigated, yet data on their longitudinal reproducibility is limited. The study purpose was to evaluate the longitudinal reproducibility of VUE attenuation measurements on three different dual-energy CT (DECT) scanner types. METHODS: A total of 137 patients with repeated abdominal DECT either on a rapid kV switching (rsDECT; n = 46), a dual-layer detector (dlDECT; n = 43), or a dual-source scanner (dsDECT; n = 48) were retrospectively included. Attenuation was measured on VUE and corresponding contrast-enhanced images in the liver, spleen, kidneys, aorta, portal vein, and fat. Longitudinal reproducibility was evaluated by calculating the absolute inter-scan differences (HU) and the inter-scan variation (%). Measurement pairs with differences ≤ 10 HU were considered reproducible. Influence of contrast-enhanced attenuation on VUE reproducibility was analyzed using linear regression. RESULTS: The scanner-specific cohorts showed similar age (p-range: 0.35-0.99), sex (p-range: 0.68-1), body weight (p-range: 0.26-0.87), body diameter (p-range: 0.34-0.76), and inter-scan time (p-range: 0.52-0.83). In total, 94.9% of VUE measurements were reproducible for rsDECT, 93.8% for dlDECT, and 90.6% for dsDECT. Overall inter-scan variation was lowest in fat (4.0 (1.7-8.2)%) and highest in tissues with high contrast enhancement: the aorta (13.3 (4.6-21.3)%), portal vein (10.8 (5.7-19.8)%), and kidneys (10.7 (3.9-18.0)%). Significant differences in inter-scan variation were found between the scanner types for the aorta, portal vein, kidneys, and spleen. Inter-scan differences in contrast-enhanced attenuation significantly influenced inter-scan differences in VUE attenuation (p < 0.001; t-ratio: 4.34). CONCLUSIONS: Longitudinal reproducibility of VUE attenuation was high for all scanners, yet inter-scan variation of VUE attenuation was influenced by contrast enhancement, showing greatest magnitude and discrepancy between scanner types in vessels and the kidneys. KEY POINTS: • We found that 94.9% of attenuation measurements on virtual unenhanced images were reproducible for rapid kV switching DECT, 93.8% for dual-layer detector DECT, and 90.6% for dual-source DECT. • Inter-scan variation of attenuation in virtual unenhanced images was comparable between the three scanner types in the liver and fat, whereas inter-scan variation in the spleen, kidneys, portal vein, and aorta showed significant differences between scanner types (p < 0.05). • Inter-scan attenuation differences in contrast-enhanced images significantly influenced inter-scan differences in virtual unenhanced attenuation (p < 0.001, t-ratio: 4.34), suggesting a residual impact of contrast enhancement differences between examinations.

Inter-scan and inter-scanner variation of quantitative dual-energy CT: evaluation with three different scanner types.

OBJECTIVES: To investigate inter-scan and inter-scanner variation of iodine concentration (IC) and attenuation in virtual monoenergetic images at 65 keV (HU65keV) in patients with repeated abdominal examinations on dual-source (dsDECT), rapid kV switching (rsDECT), and dual-layer detector DECT (dlDECT). METHODS: We retrospectively included 131 patients who underwent two abdominal DECT examinations on the same scanner (dsDECT: n = 46, rsDECT: n = 45, dlDECT: n = 40). IC and HU65keV were measured by placing regions of interest in the liver, spleen, kidneys, aorta, portal vein, and inferior vena cava. Overall IC and HU65keV for each scanner, their inter-scan differences and proportional variation were calculated and compared between scanner types. RESULTS: The three scanner-specific cohorts showed similar weight, body diameter, age, sex, and contrast media injection parameters as well as inter-scan differences hereof (p range: 0.23-0.99). Absolute inter-scan differences of HU65keV and IC were comparable between scanners (p range: 0.08-1.0). Overall inter-scan variation was significantly higher in IC than HU65keV (p < 0.05). For the liver, rsDECT showed significantly lower inter-scan variation of IC compared to dsDECT/dlDECT (p = 0.005/0.01), while for the spleen, this difference was only significant compared to dsDECT (p = 0.015). Normalizing IC of the liver to the portal vein and of the spleen to the aorta did not significantly reduce inter-scan variation (p = 0.97 and 0.50). CONCLUSIONS: Iodine measurements across different DECT scanners show inter-scan variation which is higher compared to variation of attenuation values. Inter-scanner differences in longitudinal variation and overall iodine concentration depend on the scanner pairs and organs assessed and should be acknowledged in clinical and scientific DECT applications. KEY POINTS: • All scanner types showed comparable inter-scan variation of attenuation, while for iodine, the rapid kV switching DECT showed lower variability in the liver and spleen. • Iodine concentration showed higher inter-scan variation than attenuation measurements; normalization to vessels did not significantly improve inter-scan reproducibility of iodine concentration in parenchymal organs. • Differences between the three scanner types regarding overall iodine concentration and attenuation obtained from both timepoints were within the range of average intra-patient, inter-scan differences for most assessed organs and vessels.

Low keV portal venous phase as a surrogate for pancreatic phase in a pancreatic protocol dual-energy CT: feasibility, image quality, and lesion conspicuity.

OBJECTIVE: To assess the feasibility of a proposed pancreatic protocol CT generated from portal-venous phase (PVP) dual-energy CT (DECT) acquisition and its impact on image quality, lesion conspicuity, and arterial visualization/involvement. METHODS: We included 111 patients (mean age, 66.8 years) who underwent pancreatic protocol DECT (pancreatic phase, PP, and PVP). The original DECT acquisition was used to create two data sets-standard protocol (50 keV PP/65 keV PVP) and proposed protocol (40 keV/65 keV PVP). Three reviewers evaluated the two data sets for image quality, lesion conspicuity, and arterial visualization/involvement using a 5-point scale. The signal-to-noise ratio (SNR) of pancreas and lesion-to-pancreas contrast-to-noise ratio (CNR) was calculated. Qualitative scores, quantitative parameters, and dose-length product (DLP) were compared between standard and proposed protocols. RESULTS: The image quality, SNR of pancreas, and lesion-to-pancreas CNR of the standard and proposed protocol were comparable (p = 0.11-1.00). Lesion conspicuity was comparable between the standard and proposed protocols for pancreatic ductal adenocarcinoma (p = 0.55) and pancreatic cysts (p = 0.28). The visualization of larger arteries and arterial involvement were comparable between the two protocols (p = 0.056-1.00) while the scores were higher for smaller vessels in the standard protocol (p < 0.0001-0.0015). DLP of the proposed protocol (670.4 mGy·cm) showed a projected 42% reduction than the standard protocol (1145.9 mGy·cm) (p < 0.0001). CONCLUSION: Pancreatic protocol CT generated from a single PVP DECT acquisition is feasible and could potentially be an alternative to the standard pancreatic protocol with PP and PVP. KEY POINTS: • The lesion conspicuity for focal pancreatic lesions was comparable between the proposed protocol and standard dual-phase pancreatic protocol CT. • Qualitative and quantitative image assessments were almost comparable between two protocols. • The radiation dose of a proposed protocol showed a projected 42% reduction from the conventional protocol.

Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations.

OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V. METHODS: In this retrospective study, 50 patients (62% F; 56.74 ± 17.05 years) underwent portal venous phase. Four reconstructions (ASIR-V at 40%, and DLIR at three strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H)) were generated. Qualitative and quantitative image quality analysis was performed on the 200 image datasets. Qualitative scores were obtained for image noise, contrast, small structure visibility, sharpness, and artifact by three blinded radiologists on a 5-point scale (1, excellent; 5, very poor). Radiologists also indicated image preference on a 3-point scale (1, most preferred; 3, least preferred). Quantitative assessment was performed by measuring image noise and contrast-to-noise ratio (CNR). RESULTS: DLIR had better image quality scores compared to ASIR-V. Scores on DLIR-H for noise (1.40 ± 0.53), contrast (1.41 ± 0.55), small structure visibility (1.51 ± 0.61), and sharpness (1.60 ± 0.54) were the best (p < 0.05) followed by DLIR-M (1.85 ± 0.52, 1.66 ± 0.57, 1.69 ± 0.59, 1.68 ± 0.46), DLIR-L (2.29 ± 0.58, 1.96 ± 0.61, 1.90 ± 0.65, 1.86 ± 0.46), and ASIR-V (2.86 ± 0.67, 2.55 ± 0.58, 2.34 ± 0.66, 2.01 ± 0.36). Ratings for artifacts were similar for all reconstructions (p > 0.05). DLIRs did not influence subjective textural perceptions and were preferred over ASIR-V from the beginning. All DLIRs had a higher CNR (26.38-102.30%) and lower noise (20.64-48.77%) than ASIR-V. DLIR-H had the best objective scores. CONCLUSION: Sinogram-based deep learning image reconstructions were preferred over iterative reconstruction subjectively and objectively due to improved image quality and lower noise, even in large patients. Use in clinical routine may allow for radiation dose reduction. KEY POINTS: • Deep learning image reconstructions (DLIRs) have a higher contrast-to-noise ratio compared to medium-strength hybrid iterative reconstruction techniques. • DLIR may be advantageous in patients with large body habitus due to a lower image noise. • DLIR can enable further optimization of radiation doses used in abdominal CT.

Multisystem Assessment of the Imaging Manifestations of Coagulopathy in Hospitalized Patients With Coronavirus Disease (COVID-19).

BACKGROUND. Coronavirus disease (COVID-19) is known to be associated with a distinct form of coagulopathy. OBJECTIVE. The purpose of this study was to describe the imaging manifestations of COVID-19-associated coagulopathy across anatomic sites and modalities in hospitalized patients and to identify clinical variables associated with positive imaging findings. METHODS. We conducted a retrospective review of consecutive adult patients with COVID-19 admitted to our hospital over a 3-week period. Data on patient demographics, hematologic values, cross-sectional imaging examinations, and clinical outcomes (death and intubation) were collected. Imaging was reviewed for manifestations of coagulopathy. Multivariable logistic regression analyses were performed to assess associations of patient demographics, hematologic markers, and outcomes with the need for imaging and imaging manifestations of coagulopathy. RESULTS. Of 308 hospitalized patients with COVID-19, 142 (46%) underwent 332 cross-sectional imaging examinations. Of these, 37 (26%) had imaging results positive for coagulopathy. The most common imaging manifestations of coagulopathy were pulmonary embolus (n = 21) on contrast-enhanced CT or CTA, thrombus in the upper- or lower-extremity veins (n = 13) on Doppler ultrasound, end-organ infarction in the bowel (n = 4) and kidney (n = 4) on contrast-enhanced CT, and thrombus or parenchymal infarction in the brain (n = 2) on contrast-enhanced CTA or MRI with MRA. Among patients with imaging results positive for coagulopathy, eight (22%) had multisite involvement. Thrombi were multifocal in four of five patients with positive upper-extremity and three of eight patients with positive lower-extremity examination results and involved superficial veins, deep veins, or both. In multivariable analysis, intubation (p < .001) and prolonged prothrombin time (p = .04) were significantly associated with undergoing imaging. No patient variable was significantly associated with imaging results positive for coagulopathy (p > .05). CONCLUSION. Imaging commonly shows manifestations of coagulopathy in hospitalized patients with COVID-19. Over one-fifth of patients with such manifestations show multisite involvement. Clinical variables poorly predict which patients have positive imaging results, indicating a complementary role of imaging in detecting COVID-19-associated coagulopathy. CLINICAL IMPACT. In patients with COVID-19 with suspected systemic coagulopathy, pulmonary CTA, extremity Doppler ultrasound, contrast-enhanced abdominal CT, and contrast-enhanced brain MRI and MRA may all be appropriate in the absence of imaging contraindications.

Dual-Energy CT Images: Pearls and Pitfalls.

Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. Online supplemental material is available for this article. ©RSNA, 2021.

Recognizing and Minimizing Artifacts at Dual-Energy CT.

Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential.

Update on Multienergy CT: Physics, Principles, and Applications.

Multienergy CT involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different x-ray energies, multienergy CT allows distinction of tissues and materials beyond that possible with conventional CT. Multienergy CT technologies can operate at the source or detector level. Dual-source, rapid tube-voltage switching, and dual-layer detector CT are the most commonly used multienergy CT technologies. Most of the currently available technologies typically use two energy levels, commonly referred to as dual-energy CT. With use of two or more energy bins, photon-counting detector CT can perform multienergy CT beyond current dual-energy CT technologies. Multienergy CT postprocessing can be performed in the projection or image domain using two-material or multimaterial decomposition. The most commonly used multienergy CT images are virtual monoenergetic images (VMIs), iodine maps, virtual noncontrast (VNC) images, and uric acid images. Low-energy VMIs are used to boost contrast signal and enhance lesion conspicuity. High-energy VMIs are used to decrease some artifacts. Iodine maps are used to evaluate perfusion, characterize lesions, and evaluate response to therapy. VNC images are used to characterize lesions and save radiation dose by eliminating true noncontrast images from multiphasic acquisitions. Uric acid images are used for characterization of renal calculi and gout. Online supplemental material is available for this article. ©RSNA, 2020.

Texture Analysis as a Radiomic Marker for Differentiating Benign From Malignant Adrenal Tumors.

OBJECTIVE: The aim of this study was to evaluate the use of texture analysis for differentiation between benign from malignant adrenal lesions on contrast-enhanced abdominal computed tomography (CT). METHODS: After institutional review board approval, a retrospective analysis was performed, including an electronic search of pathology records for all biopsied adrenal lesions. Patients were included if they also had a contrast-enhanced abdominal CT in the portal venous phase. Computed tomographic images were manually segmented, and texture analysis of the segmented tumors was performed. Texture analysis results of benign and malignant tumors were compared, and areas under the curve (AUCs) were calculated. RESULTS: One hundred twenty-five patients were included in the analysis. Excellent discriminators of benign from malignant lesions were identified, including entropy and standard deviation. These texture features demonstrated lower values for benign lesions compared with malignant lesions. Entropy values of benign lesions averaged 3.95 using a spatial scaling factor of 4 compared with an average of 5.08 for malignant lesions (P < .0001). Standard deviation values of benign lesions averaged 19.94 on the unfiltered image compared with an average of 34.32 for malignant lesions (P < .0001). Entropy demonstrated AUCs ranging from 0.95 to 0.97 for discriminating tumors, with sensitivities and specificities ranging from 81% to 95% and 88% to 100%, respectively. Standard deviation demonstrated AUCs ranging from 0.91 to 0.94 for discriminating tumors, with sensitivities and specificities ranging from 73% to 93% and 86% to 95%, respectively. CONCLUSION: Texture analysis offers a noninvasive tool for differentiating benign from malignant adrenal tumors on contrast-enhanced CT images. These results support the further development of texture analysis as a quantitative biomarker for characterizing adrenal tumors.

Low-keV and Low-kVp CT for Positive Oral Contrast Media in Patients with Cancer: A Randomized Clinical Trial.

Background Substantial gain in the attenuation of iodine on low-kVp and dual-energy CT processed low-keV virtual monochromatic images provides an opportunity for customization of positive oral contrast media administration. Purpose To perform an intrapatient comparison of bowel labeling, opacification, and taste preference with iodinated oral contrast medium (ICM) in standard (sICM) and 25%-reduced (rICM) concentrations at low tube voltage (100 kVp) or on low-energy (50-70 keV) virtual monochromatic images compared with barium-based oral contrast medium (BCM) at 120 kVp. Materials and Methods In this prospective clinical trial, 200 adults (97 men, 103 women; mean age, 63 years ± 13 [standard deviation]) who weighed less than 113 kg and who were undergoing oncologic surveillance (from April 2017 to July 2018) and who had previously undergone 120-kVp abdominopelvic CT with BCM randomly received sICM (7.2 g iodine) or rICM (5.4 g iodine) and underwent 100-kVp CT or dual-energy CT (80/140 kVp) scans to be in one of four groups (n = 50 each): sICM/100 kVp, rICM/100 kVp, sICM/dual-energy CT, and rICM/dual-energy CT. Qualitative analysis was performed for image quality (with a five-point scale), extent of bowel labeling, and homogeneity of opacification (with a four-point scale). Intraluminal attenuation of opacified small bowel was measured. A post-CT patient survey was performed to indicate contrast medium preference, taste of ICM (with a five-point scale), and adverse effects. Data were analyzed with analogs of analysis of variance. Results All CT studies were of diagnostic image quality (3.4 ± 0.3), with no difference in the degree of bowel opacification between sICM and rICM (P > .05). Compared with BCM/120 kVp (282 HU ± 73), mean attenuation was 78% higher with sICM/100 kVp (459 HU ± 282) and 26%-121% higher at sICM/50-65 keV (50 keV = 626 HU ± 285; 65 keV = 356 HU ± 171). With rICM, attenuation was 46% higher for 100 kVp (385 HU ± 215) and 19%-108% higher for 50-65 keV (50 keV = 567 HU ± 270; 65 keV = 325 HU ± 156) compared with BCM (P < .05). A total of 171 of 200 study participants preferred ICM to BCM, with no taste differences between sICM and rICM (3.9 ± 0.6). Fifteen participants had diarrhea with BCM, but none had diarrhea with ICM. Conclusion A 25%-reduced concentration of iodinated oral contrast medium resulted in acceptable bowel labeling while yielding substantially higher luminal attenuation at low-kVp and low-keV CT examinations with improved preference in patients undergoing treatment for cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Laghi in this issue.

Correction to: Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization.

The original version of this article, published on 27 May 2019, unfortunately contained a mistake. The following correction has therefore been made in the original.