Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). METHODS: In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. RESULTS: Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. CONCLUSION: DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. CLINICAL RELEVANCE STATEMENT: Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. KEY POINTS: • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm.

OBJECTIVES: The purpose of this study was to evaluate a three-material decomposition algorithm for hepatic fat quantification using a dual-layer computed tomography (DL-CT) and MRI as reference standard on a large patient cohort. METHOD: A total of 104 patients were retrospectively included in our study, i.e., each patient had an MRI exam and a DL-CT exam in our institution within a maximum of 31 days. Four regions of interest (ROIs) were positioned blindly and similarly in the liver, by two independent readers on DL-CT and MRI images. For DL-CT exams, all imaging phases were included. Fat fraction agreement between CT and MRI was performed using intraclass correlation coefficients (ICC), determination coefficients R2, and Bland-Altman plots. Diagnostic performance was determined using sensitivity, specificity, and positive and negative predictive values. The cutoff for steatosis was 5%. RESULTS: Correlation between MRI and CT data was excellent for all perfusion phases with ICC calculated at 0.99 for each phase. Determination coefficients R2 were also good for all perfusion phases (about 0.95 for all phases). Performance of DL-CT in the diagnosis of hepatic steatosis was good with sensitivity between 89 and 91% and specificity ranging from 75 to 80%, depending on the perfusion phase. The positive predictive value was ranging from 78 to 93% and the negative predictive value from 82 to 86%. CONCLUSION: Multi-material decomposition in DL-CT allows quantification of hepatic fat fraction with a good correlation to MRI data. CLINICAL RELEVANCE STATEMENT: The use of DL-CT allows for detection of hepatic steatosis. This is especially interesting as an opportunistic finding CT performed for other reasons, as early detection can help prevent or slowdown the development of liver metabolic disease. KEY POINTS: • Hepatic fat fractions provided by the dual-layer CT algorithm is strongly correlated with that measured on MRI. • Dual-layer CT is accurate to detect hepatic steatosis ≥ 5%. • Dual-layer CT allows opportunistic detection of steatosis, on CT scan performed for various indications.

Valid and reliable diagnostic performance of dual-energy CT in anterior cruciate ligament rupture.

OBJECTIVES: To determine whether dual-energy CT (DECT) can be used to accurately and reliably detect anterior cruciate ligament (ACL) rupture. MATERIALS AND METHODS: Participants with unilateral ACL rupture were prospectively enrolled, and the bilateral knees were scanned by DECT. A tissue-specific mapping algorithm was applied to improve the visualization of the ACLs. The 80-keV CT value, mixed-keV CT value, electron density (Rho), and effective atomic number (Zeff) were measured to quantitatively differentiate torn ACLs from normal ACLs. MRI and arthroscopy served as the reference standards. RESULTS: Fifty-one participants (mean age, 27.0 ± 8.7 years; 31 men) were enrolled. Intact and torn ACLs were explicitly differentiated on color-coded DECT images. The 80-keV CT value, mixed-keV CT value, and Rho were significantly lower for the torn ACLs than for the intact ACLs (p < 0.001). The optimal cutoff values were an 80-keV CT value of 61.8 HU, a mixed-keV CT value of 60.9 HU, and a Rho of 51.8 HU, with AUCs of 98.0% (95% CI: 97.0-98.9%), 99.2% (95% CI: 98.6-99.7%), and 99.8% (95% CI: 99.6-100.0%), respectively. Overall, DECT had almost perfect reliability and validity in detecting ACL integrity (sensitivity = 97.1% [95% CI: 88.1-99.8%]; specificity = 98.0% [95% CI: 89.5-99.9%]; PPV = 98.0% [95% CI: 93.0-99.8%]; NPV = 97.1% [95% CI: 91.7-99.4%]; accuracy = 97.5% [95% CI: 94.3-99.2%]). There was no evidence of a difference between MRI and DECT in the diagnostic performance (p > 0.99). CONCLUSION: DECT has excellent diagnostic accuracy and reliability in qualitatively and quantitatively diagnosing ACL rupture. CLINICAL RELEVANCE STATEMENT: DECT could validly and reliably diagnose ACL rupture using both qualitative and quantitative methods, which may become a promising substitute for MRI to evaluate the integrity of injured ACLs and the maturity of postoperative ACL autografts. KEY POINTS: • On color-coded DECT images, an uncolored ACL was a reliable sign for qualitatively diagnosing ACL rupture. • The 80-keV CT value, mixed-keV CT value, and Rho were significantly lower for the torn ACLs than for the intact ACLs, which contributed to the quantitative diagnosis of ACL rupture. • DECT had an almost perfect diagnostic performance for ACL rupture, and diagnostic capability was comparable between MRI and DECT.

Virtual monochromatic images for coronary artery imaging with a spectral photon-counting CT in comparison to dual-layer CT systems: a phantom and a preliminary human study.

OBJECTIVES: To evaluate the quality of virtual monochromatic images (VMIs) from spectral photon-counting CT (SPCCT) and two energy-integrating detector dual-energy CT (EID-DECT) scanners from the same manufacturer, for the coronary lumen. METHODS: A 21-cm section of the Mercury v4.0 phantom was scanned using a cardiac CT protocol. VMIs from 40 to 90 keV were reconstructed using high-resolution (HR) parameters for EID-DECT and SPCCT (CB and HRB kernels at 0.67 mm slice thickness, respectively). Ultra-high-resolution (UHR) parameters were used in addition to SPCCT (detailed-2 kernel, 0.43 mm slice thickness). Noise-power-spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were computed for 2-mm-diameter lumen detection. In consensus, two radiologists analyzed the quality of the images from 8 patients who underwent coronary CTA on both CT systems. RESULTS: For all keV images, fpeak, f50, and d' were higher with SPCCT. The fpeak and f50 were higher with UHR-SPCCT with greater noise and lower d' compared to those of the HR-SPCCT images. Noise magnitude was constant for all energy levels (keV) with both systems, and lower with HR images, and d' decreased as keV decreased. Subjective analysis showed greater lumen sharpness and overall quality for HR and UHR-SPCCT images using all keV, with a greater difference at low keV compared to HR-EID-DECT images. CONCLUSION: HR and UHR-SPCCT images gave greater detectability of the coronary lumen for 40 to 90 keV VMIs compared to two EID-DECT systems, with benefits of higher lumen sharpness and overall quality. KEY POINTS: • Compared with 2 dual-energy CT systems, spectral photon-counting CT (SPCCT) improved spatial resolution, noise texture, noise magnitude, and detectability of the coronary lumen. • Use of ultra-high-resolution parameters with SPCCT improved spatial resolution and noise texture and provided high detectability of the coronary lumen, despite an increase in noise magnitude. • In eight patients, radiologists found greater overall image quality with SPCCT for all virtual monochromatic images with a greater difference at low keV, compared with dual-energy CT systems.

Comparison of Radiation Dose and Image Quality between the 2nd Generation and 3rd Generation Dual-Source Single-Energy and Dual-Source Dual-Energy CT of the Abdomen.

Purpose: We compared the radiation dose and image quality between the 2nd generation and the 3rd generation dual-source single-energy (DSSE) and dual-source dual-energy (DSDE) CT of the abdomen. Materials and Methods: We included patients undergoing follow-up abdominal CT after partial or radical nephrectomy in the first 10 months of 2019 (2nd generation DS CT) and the first 10 months of 2020 (3rd generation DS CT). We divided the 320 patients into 4 groups (A, 2nd generation DSSE CT; B, 2nd generation DSDE CT; C, 3rd generation DSSE CT; and D, 3rd generation DSDE CT) (n = 80 each) matched by sex and body mass index. Radiation dose and image quality (objective and subjective qualities) were compared between the groups. Results: The mean size-specific dose estimation of 3rd generation DSDE CT group was significantly lower than that of the 2nd generation DSSE CT (42.5%, p = 0.013) and 2nd generation DSDE CT (46.9%, p = 0.015) groups. Interobserver agreement was excellent for the overall image quality (intraclass correlation coefficient [ICC]: 0.8867) and image artifacts (ICC: 0.9423). Conclusion: Our results showed a considerable reduction in the radiation dose while maintaining high image quality with 3rd generation DSDE CT as compared to the 2nd generation DSDE CT and 2nd generation DSSE CT.

Dual-energy CT in differentiating benign sinonasal lesions from malignant ones: comparison with simulated single-energy CT, conventional MRI, and DWI.

OBJECTIVES: To explore the value of dual-energy CT (DECT) for differentiating benign sinonasal lesions from malignant ones, and to compare this finding with simulated single-energy CT (SECT), conventional MRI (cMRI), and diffusion-weighted imaging (DWI). METHODS: Patients with sinonasal lesions (38 benign and 34 malignant) who were confirmed by histopathology underwent DECT, cMRI, and DWI. DECT-derived parameters (iodine concentration (IC), effective atomic number (Eff-Z), 40-180 keV (20-keV interval), virtual non-enhancement (VNC), slope (k), and linear-mixed 0.3 (Mix-0.3)), DECT morphological features, cMRI characteristics, and ADC value of benign and malignant tumors were compared using t test or chi-square test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and the area under the ROC curve (AUC) was compared using the Z test to select the optimal diagnostic approach. RESULTS: Significantly higher DECT-derived single parameters (IC, Eff-Z, 40 keV, 60 keV, 80 keV, slope (k), Mix-0.3) were found in malignant lesions than those of benign sinonasal lesions (all p < 0.004, Bonferroni correction). Combined quantitative parameters (IC, Eff-Z, 40 keV, 60 keV, 80 keV, slope (k)) can improve the diagnostic efficiency for discriminating these two entities. Combination of DECT quantitative parameters and morphological features can further improve the overall diagnostic performance, with AUC, sensitivity, specificity, and accuracy of 0.935, 96.67%, 90.00%, and 93.52%. Moreover, the AUC of DECT was higher than those of Mix-0.3 (simulated SECT), cMRI, DWI, and cMRI+DWI. CONCLUSIONS: Compared with simulated SECT, cMRI, and DWI, DECT appears to be a more accurate imaging technique for differentiating benign from malignant sinonasal lesions. KEY POINTS: • DE can differentiate benign sinonasal lesions from malignant ones based on DECT-derived qualitative parameters. • DECT appears to be more accurate in the diagnosis of sinonasal lesions when compared with simulated SECT, cMRI, and DWI.

Application value of artificial intelligence in dual-source CT coronary angiography / 中国基层医药

Objective:To investigate the application value of artificial intelligence in dual-source CT coronary angiography.Methods:The imaging data of 50 patients with coronary artery diseases who received treatment in Benxi Central Hospital from January to December 2021 were retrospectively analyzed. All patients underwent coronary computed tomography angiography examination and coronary arteriography. Coronary computed tomography angiography images were uploaded to the post-processing workstation and post-processed and analyzed by two radiologists. At the same time, the images were also post-processed by AI software and diagnosis reports were generated. In terms of coronary artery stenosis, the diagnostic results provided by AI software were compared with coronary angiography results. In terms of myocardial bridging, the diagnostic results provided by AI software were compared with radiologist's diagnosis. The accuracy of AI software was judged.Results:In the diagnosis of coronary artery stenosis, the sensitivity, specificity, positive predictive value and the negative predictive value of AI software were 93.22%, 81.32%, 76.39% and 94.87% respectively. These were well consistent with coronary arteriography results (Kappa = 0.71, P < 0.001). In the diagnosis of myocardial bridging, the sensitivity, specificity, positive predictive value and the negative predictive value of AI software were 30.77%, 81.45%, 25.81% and 84.87% respectively. These were poorly consistent with radiologists' diagnostic results (Kappa = 0.11, P = 0.162). Conclusion:AI-based dual-source CT coronary angiography is of high value in the diagnosis of coronary artery stenosis, but it is of low value in the diagnosis of myocardial bridging.

Value of dual energy CT parameters combined with serum procollagen Ⅰ N-terminal propeptide and beta C-terminal cross-linked telopeptide of type Ⅰ collagen in differential diagnosis of spinal bone metastasis from lung cancer and myeloma / 中国医师进修杂志

Objective:To analyze the value of dual energy CT parameters combined with serum procollagen Ⅰ N-terminal propeptide (PⅠNP) and beta C-terminal cross-linked telopeptide of type Ⅰ collagen (β-CTX) in differential diagnosis of spinal bone metastasis from lung cancer and myeloma.Methods:The clinical data of 54 patients with spinal bone metastasis from lung cancer and 50 patients with myeloma in Jincheng People′s Hospital from October 2019 to March 2021 were analyzed retrospectively. All patients were examined by dual energy CT on the day of admission, and the CT values at the energy levels of 40 to 80 keV (energy interval of 10 keV) were recorded. The serum PⅠNP and β-CTX levels were detected by chemiluminescent assay before treatment. The pathological examination results were taken as gold standard, and the CT values at the energy levels of 40 to 80 keV by dual energy CT and serum PⅠNP and β-CTX levels were compared between 2 groups. Receiver operating characteristic (ROC) curve was used to analyze the differential diagnosis value of the CT values at the energy levels of 40 to 80 keV, serum PⅠNP and β-CTX levels alone and combination.Results:The CT values at the energy levels of 40 to 80 keV by dual energy CT and serum PⅠNP and β-CTX levels in patients with spinal bone metastasis from lung cancer were significantly higher than those in patients with myeloma: 79.86 (61.20, 116.32) HU vs. 58.29 (46.92, 64.03) HU, 64.48 (50.27, 90.08) HU vs. 45.78 (38.59, 56.75) HU, 57.35 (43.31, 78.04) HU vs. 43.62 (36.91, 54.06) HU, 52.05 (42.98, 75.79) HU vs. 41.26 (32.84, 51.76) HU, 45.52 (38.55, 63.59) HU vs. 36.68 (28.72, 49.83) HU, 66.35 (31.15, 81.97) μg/L vs. 31.38 (27.76, 34.50) μg/L and 0.61 (0.48, 0.67) μg/L vs. 0.49 (0.47, 0.52) μg/L, and there were statistical differences ( P<0.05 or <0.01). ROC curve analysis result showed that the sensitivity of the combination of the CT values at the energy levels of 40 to 80 keV by dual energy CT was higher than those alone (83.33% vs. 59.26%, 61.11%, 62.96%, 64.81% and 66.67), the area under the curve (AUC) was also higher than those alone (0.882 vs. 0.798, 0.811, 0.817, 0.801 and 0.773), and there were statistical differences ( P<0.01 or <0.05); the sensitivity of the combination of serum PⅠNP and β-CTX levels was higher than those alone (81.48% vs. 57.41% and 62.96%), the AUC was higher than those alone (0.829 vs. 0.753 and 0.729), and there were statistical differences ( P<0.01 or <0.05); the sensitivity of all indexes combined in the differential diagnosis of spinal bone metastasis from lung cancer and myeloma was higher than those of the combination of the CT values at the energy levels of 40 to 80 keV by dual energy CT, the combination of serum PⅠNP and β-CTX levels (98.15% vs. 83.33% and 81.48%), the same as AUC (0.976 vs. 0.882 and 0.829), and there were statistical differences ( P<0.01); there were no significant differences in the specificity of each index alone and combination ( P>0.05). Conclusions:Compared with myeloma, the CT values at the energy levels of 40 to 80 keV by dual energy CT, serum PⅠNP and β-CTX levels in patients with spinal bone metastasis from lung cancer are increased, and the combination of the above indexes has ideal value in differential diagnosis of the two diseases.

Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT.

OBJECTIVES: To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements. METHODS: We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions. RESULTS: A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts. CONCLUSION: A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts. KEY POINTS: • A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93). • When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions. • Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Virtual Monochromatic Image Quality from Dual-Layer Dual-Energy Computed Tomography for Detecting Brain Tumors.

OBJECTIVE: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. MATERIALS AND METHODS: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. RESULTS: The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). CONCLUSION: In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.

Value of bone suppression software in chest radiographs for improving image quality and reducing radiation dose.

OBJECTIVES: To compare image quality and radiation dose between dual-energy subtraction (DES)-based bone suppression images (D-BSIs) and software-based bone suppression images (S-BSIs). METHODS: Chest radiographs (CXRs) of forty adult patients were obtained with the two X-ray devices, one with DES and one with bone suppression software. Three image quality metrics (relative mean absolute error (RMAE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM)) between original CXR and BSI for each of D-BSI and S-SBI groups were calculated for each bone and soft tissue areas. Two readers rated the visual image quality for original CXR and BSI for each of D-BSI and S-SBI groups. The dose area product (DAP) values were recorded. Paired t test was used to compare the image quality and DAP values between D-BSI and S-BSI groups. RESULTS: In bone areas, S-BSIs had better SSIM values than D-BSI (94.57 vs. 87.77) but worse RMAE and PSNR values (0.50 vs. 0.20; 20.93 vs. 34.37) (all p < 0.001). In soft tissue areas, S-BSIs had better SSIM values than D-BSI (97.56 vs. 91.42) but similar RMAE and PSNR values (0.29 vs. 0.27; 31.35 vs. 29.87) (all p < 0.001). Both readers gave S-BSIs significantly higher image quality scores than D-BSI (p < 0.001). The mean DAP in software-related images (0.98 dGy·cm2) was significantly lower than that in the DES-related images (1.48 dGy·cm2) (p < 0.001). CONCLUSION: Bone suppression software significantly improved the image quality of bone suppression images with a relatively lower radiation dose, compared with dual-energy subtraction technique. KEY POINTS: • Bone suppression software preserves structure similarity of soft tissues better than dual-energy subtraction technique in bone suppression images. • Bone suppression software achieves superior image quality for lung lesions than dual-energy subtraction technique in bone suppression images. • Bone suppression software can decrease the radiation dose over the hardware-based image processing technique.

Performance of four dual-energy CT platforms for abdominal imaging: a task-based image quality assessment based on phantom data.

OBJECTIVES: To compare the spectral performance of dual-energy CT (DECT) platforms using task-based image quality assessment based on phantom data. MATERIALS AND METHODS: Two CT phantoms were scanned on four DECT platforms: fast kV-switching CT (KVSCT), split filter CT (SFCT), dual-source CT (DSCT), and dual-layer CT (DLCT). Acquisitions on each phantom were performed using classical parameters of abdomen-pelvic examination and a CTDIvol at 10 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 140 keV of virtual monoenergetic images. A detectability index (d') was computed to model the detection task of two contrast-enhanced lesions as function of keV. RESULTS: The noise magnitude decreased from 40 to 70 keV for all DECT platforms, and the highest noise magnitude values were found for KVSCT and SFCT and the lowest for DSCT and DLCT. The average NPS spatial frequency shifted towards lower frequencies as the energy level increased for all DECT platforms, smoothing the image texture. TTF values decreased with the increase of keV deteriorating the spatial resolution. For both simulated lesions, higher detectability (d' value) was obtained at 40 keV for DLCT, DSCT, and SFCT but at 70 keV for KVSCT. The detectability of both simulated lesions was highest for DLCT and DSCT. CONCLUSION: Highest detectability was found for DLCT for the lowest energy levels. The task-based image quality assessment used for the first time for DECT acquisitions showed the benefit of using low keV for the detection of contrast-enhanced lesions. KEY POINTS: • Detectability of both simulated contrast-enhanced lesions was higher for dual-layer CT for the lowest energy levels. • The image noise increased and the image texture changed for the lowest energy levels. • The detectability of both simulated contrast-enhanced lesions was highest at 40 keV for all dual-energy CT platforms except for fast kV-switching platform.

Diagnostic accuracy of dual-energy CT for the detection of bone marrow edema in the appendicular skeleton: a systematic review and meta-analysis.

OBJECTIVES: This meta-analysis evaluated the diagnostic accuracy of dual-energy CT (DECT) for detecting bone marrow edema (BME) in the appendicular skeleton. METHODS: A systematic review of MEDLINE, EMBASE, Scopus, the Cochrane Library, and gray literature from inception through January 31, 2020, was performed. Original articles with > 10 patients evaluating the accuracy of DECT for detecting BME in the appendicular skeleton with a reference standard of MRI and/or clinical follow-up were included. Study details were independently extracted by two reviewers. Meta-analysis was performed using a bivariate random-effects model with multivariable meta-regression. Risk of bias (RoB) was evaluated with QUADAS-2. RESULTS: Twenty studies evaluating 790 patients for BME in the appendicular skeleton were included in analysis. The summary sensitivity, specificity, and AUC values for BME in the appendicular skeleton were 86% (95% confidence interval [CI] 82-89%), 93% (95% CI 90-95%), and 0.95, respectively. Quantitative analysis had a higher sensitivity than qualitative analysis on meta-regression (p = 0.01), but no difference in specificity (p = 0.28). No other covariates contributed to variability in accuracy (etiology (trauma vs non-trauma); location (upper vs lower extremity); and RoB). Studies demonstrated generally low or unclear RoB and applicability. Eight studies included index tests with high RoB when quantitative assessments used a retrospective cut-off value. CONCLUSIONS: DECT demonstrates a higher specificity than sensitivity and AUC > 0.9. In scenarios where MRI availability is limited or contraindicated, DECT could be an alternative to MRI for detecting BME in the appendicular skeleton. However, limitations in sources of variability and RoB warrant continued study. KEY POINTS: • Twenty studies evaluating 790 patients for bone marrow edema in the appendicular skeleton with dual-energy CT were included in analysis. • The summary sensitivity, specificity, and AUC values for detecting bone marrow in the appendicular skeleton were 86% (95% confidence interval [CI] 82-89%), 93% (95% CI 90-95%), and 0.95, respectively. • In scenarios where MRI availability is limited or is contraindicated, DECT could be an alternative to MRI for detecting bone marrow edema in the appendicular skeleton.

Bone marrow edema in sacroiliitis: detection with dual-energy CT.

OBJECTIVES: To evaluate the feasibility and diagnostic accuracy of dual-energy computed tomography (DECT) for the detection of bone marrow edema (BME) in patients suspected for sacroiliitis. METHODS: Patients aged 18-55 years with clinical suspicion for sacroiliitis were enrolled. All patients underwent DECT and 3.0 T MRI of the sacroiliac joints on the same day. Virtual non-calcium (VNCa) images were calculated from DECT images for demonstration of BME. VNCa images were scored by two readers independently using a binary system (0 = normal bone marrow, 1 = BME). Diagnostic performance was assessed with fluid-sensitive MRI as the reference standard. ROIs were placed on VNCa images, and CT numbers were displayed. Cutoff values for BME detection were determined based on ROC curves. RESULTS: Forty patients (16 men, 24 women, mean age 37.1 years ± 9.6 years) were included. Overall inter-reader agreement for visual image reading of BME on VNCa images was good (κ = 0.70). The sensitivity and specificity of BME detection by DECT were 65.4% and 94.2% on the quadrant level and 81.3% and 91.7% on the patient level. ROC analyses revealed AUCs of 0.90 and 0.87 for CT numbers in the ilium and sacrum, respectively. Cutoff values of - 44.4 HU (for iliac quadrants) and - 40.8 HU (for sacral quadrants) yielded sensitivities of 76.9% and 76.7% and specificities of 91.5% and 87.5%, respectively. CONCLUSIONS: Inflammatory sacroiliac BME can be detected by VNCa images calculated from DECT, with a good interobserver agreement, moderate sensitivity, and high specificity. KEY POINTS: • Virtual non-calcium images calculated from dual-energy CT can detect sacroiliac bone marrow edema in patients suspected for sacroiliitis. • Dual-energy CT has a high specificity in bone marrow edema detection. • Virtual non-calcium images for bone marrow edema in patients with a large amount of red bone marrow or obvious sclerosis near the articular surface should be interpreted with caution.

Dual-layer detector spectral CT versus magnetic resonance imaging for the assessment of iron overload in myelodysplastic syndromes and aplastic anemia.

BACKGROUND: The purpose of this study is to investigate the performance of dual-layer detector spectral CT for iron deposition compared to magnetic resonance imaging (MRI) T2* imaging. METHODS: Thirty-one patients with a clinical history of myelodysplastic syndromes and aplastic anemia underwent liver and cardiac T2*-weighted unenhanced MRI on a three-tesla MRI scanner, and underwent unenhanced CT scan laterally on a 128-row spectral detector CT. R2* values of the liver, septal muscle, and paraspinal muscle were calculated. Attenuation differences (ΔH) in the liver and myocardium were calculated between the lower (50 keV) and higher (120 keV) energy levels. RESULTS: The liver and cardiac T2* values were 9.54 ± 5.63 ms and 21.41 ± 2.44 ms, respectively. The liver-to-muscle and myocardium-to-muscle T2* value ratios were 0.37 ± 0.23 and 0.79 ± 0.19, respectively. The liver and cardiac ΔH were - 1.13 ± 4.24 HU and 2.22 ± 4.41 HU, respectively. There was a strong linear correlation between the liver R2* and ΔH (r = - 0.832, P < 0.001), but weak correlation existed between the cardiac R2* and ΔH (P = 0.041). CONCLUSIONS: Dual-layer detector spectral unenhanced CT seemed to be equally valuable to MRI T2* imaging for evaluating liver iron overload.

Dual-Energy Computed Tomography-Enabled Material Separation in Diagnosing Left Atrial Appendage Thrombus.

We explored the potential clinical value of material separation enabled by dual-energy spectral computed tomography in detecting left atrial appendage thrombi. The study enrolled 24 patients who were scheduled to undergo atrial fibrillation ablation (12 with and 12 without left atrial appendage thrombi). Computed tomograms were acquired in gemstone spectral imaging mode; the densities in the regions of the left atrial appendage cavities, pectinate muscles, and left atrial appendage thrombi were analyzed on monochromatic 70-keV images. Iodine and blood were chosen as the material basis pair; the iodine and blood densities were observed and quantitatively determined from the iodine- and blood-specific material decomposition images. On the 70-keV monochromatic and iodine-specific images, the left atrial appendage pectinate muscles and thrombi appeared as areas of hypodense attenuation. On the blood-specific images, similar areas of high attenuation were observed in the thrombi and cavities, whereas lower attenuation was noticed in the pectinate muscles. The quantitative iodine and blood densities in the pectinate muscles were lower than those in the cavities (P <0.001). The iodine densities in the thrombi were lower than those in the cavities (P <0.001); however, blood densities did not differ significantly between the thrombi and cavities (P=0.192). Compared with the pectinate muscles, the thrombi showed lower blood-density differences (P=0.003) and higher iodine-density differences (P=0.006) in relation to the cavities. Spectral computed tomography-enabled material separation is a novel method for differentiating left atrial appendage thrombi from pectinate muscles. The potential applications of this technology warrant further studies.

The value of single-source dual-energy CT imaging for discriminating microsatellite instability from microsatellite stability human colorectal cancer.

OBJECTIVES: To demonstrate the value of single-source dual-energy computed tomography (ssDECT) imaging for discriminating microsatellite instability (MSI) from microsatellite stability (MSS) colorectal cancer (CRC). METHODS: Thirty-eight and seventy-six patients with pathologically proven MSI and MSS CRC, respectively, were retrospectively selected and compared. These patients underwent contrast-enhanced abdominal ssDECT scans before any anti-cancer treatment. Effective atomic number (Eff-Z) in precontrast phase, slope k of spectral HU curve in precontrast (k-P), arterial (k-A), venous (k-V), and delayed phase (k-D), normalized iodine concentration in arterial (NIC-A), venous (NIC-V), and delayed phase (NIC-D), of tumors in two groups were measured by two reviewers. Consistency of measurements was tested by intra-class correlation coefficients (ICC). Mann-Whitney U test or Student's t test was used to compare above values between MSI and MSS. Multivariate logistic regression was used to analyze multiple parameters. Receiver operating characteristic curves were calculated to assess diagnostic efficacies. RESULTS: Interobserver agreement was excellent (ICC > 0.80). MSI CRC had significantly lower values in all measurements (NIC-A, V, D; k-P, A, V, D; Eff-Z) than MSS CRC. For discriminating MSI from MSS CRC, the area under curve (AUC) using k-A was the highest (AUC, 0.803; sensitivity, 72.4%; specificity, 76.3%). The multivariate logistic regression (selection method, Enter) with combined ssDECT parameters (NIC-A, NIC-V, NIC-D, Eff-Z, k-P, k-A, k-V, k-D) significantly improved diagnostic capability with AUC of 0.886 (sensitivity, 81.6%; specificity, 81.6%). CONCLUSIONS: The combination of multiple parameters in ssDECT imaging by multivariate logistic regression provides relatively high diagnostic accuracy for discriminating MSI from MSS CRC. KEY POINTS: • ssDECT generates multiple parameters for discriminating CRC with MSI from MSS. • ssDECT measurements for MSI CRC were significantly lower than MSS CRC. • Combination of ssDECT parameters further improves diagnostic capability for differentiation.

Investigation of correlation between quantitative parameters derived from dual?energy CT and the differentiation degree of laryngeal and hypopharyngeal squamous cell carcinoma / 中华放射学杂志

Objective To investigate the correlation between quantitative parameters derived from iodine overlay images and the monochromatic images of dual‐energy CT and the differentiation degree of laryngeal and hypopharyngeal squamous cell carcinoma(LHSCC). Methods Retrospective analysis of clinical and imaging data of eighty patients with different differentiation degree of LHSCC who underwent dual‐energy CT enhanced scan in the arterial and venous phase from March 2016 to January 2017 (20, 42 and 18 patients with well, moderately and poorly differentiation, respectively) was performed.Among them, twenty‐eight cases were stage T1, twenty‐four cases were stage T2, twenty cases were stage T3 and eight cases were stage T4. All patients were not treated with radiotherapy and chemotherapy before operation. Iodine overlay images and the monochromatic images of arterial and venous phases were acquired from Syngo MultiModality Workplace dual‐energy post‐processing software of Siemens, respectively. The mean iodine concentration (IC), standardized iodine concentration (SIC), and the slope of spectral curve(λ) of different differentiation degrees of LHSCC were calculated and compared. The correlation between quantitative parameters of LHSCC and its differentiation degree was performed by Spearman rank sum test. One‐way analysis of variance was used to compare the quantitative parameters of different differentiation degree of LHSCC. Receiver operating characteristic (ROC) curve was used for analyzing diagnostic efficiency. Results The IC, SIC, and λ in the arterial phase, and IC in the venous phase correlated positively with differentiation degree in LHSCC (r=0.258, 0.350, 0.262 and 0.275, respectively; P<0.05) in this group. The IC, SIC, and λ of poorly differentiated LHSCC in the arterial phase [(3.13 ± 0.54) mg/ml, (0.38±0.10), (5.40±0.92)] were higher than those of well differentiated LHSCC [(2.38±1.02) mg/ml, (0.25± 0.09) and (4.19 ± 1.18); t=2.73, 3.36 and 2.75 respectively; P<0.05] and moderately differentiated LHSCC [(2.56±0.85) mg/ml, (0.28±0.16) and (4.56±1.41); t=2.38, 3.06 and 2.21, P<0.05]. IC of poorly differentiated LHSCC in the venous phase [(2.59 ± 0.62) mg/ml] was significantly higher than that of well differentiated LHSCC [(1.96±0.56) mg/ml,t=2.45,P<0.05] and moderately differentiated [(2.02±0.93) mg/ml,t=2.56,P<0.05] LHSCC. There was no significant difference in the SIC and λ between different differentiation degrees of LHSCC (P>0.05) in the venous phase. The standardized iodine concentration in the arterial phase was the best in distinguishing poorly and moderately differentiated LHSCC, and poorly and well differentiated LHSCC with the area under the receiver operating curve 0.77 and 0.81, respectively, the sensitivity 88.2% and 70.0%, respectively, and the specificity 69.0% and 70.0%, respectively. Conclusions Quantitative parameters derived from dual‐energy CT might be useful in the evaluation of different differentiated degrees of LHSCC. In addition, the standardized iodine concentration of LHSCC in the arterial phase was the best in the estimation of different differentiated degrees of LHSCC.

Detection of monosodium urate crystals with dual-energy CT in gout patients / 中华全科医师杂志

Objective To evaluate the application of the dual-energy CT (DECT) in detection of monosodium urate (MSU) crystals in gout patients.Methods The imaging and clinical data of 101 patients with suspected gout were retrospectively analyzed,including 64 cases of clinically diagnosed gout (gout group) and 37 non-gout cases (non-gout group).The DECT examination was performed for 85 joints in gout group and 42 joints in non-joint group.The value of DECT in detection of MSU crystals was evaluated with receiver operating characteristic (ROC) curve.Results There were significant differences in gender (x2=5.32,P=0.03) and blood uric acid levels (t=1.95,P=0.04) between gout and non-gout groups.The detection rate of MSU in gout group was significantly higher than that of non-gout group (x2=30.52,P＜0.001).The area under the ROC curve (AUC) of DECT in detection of was 0.74±0.05 (Mean±SE),95％CI:0.64-0.85.The sensitivity,specificity,positive predictive value and negative predictive value of the DECT in detection of gouty stone was 0.844,0.703,83.1％ and 72.2％,respectively.Conclusion The dual-energy CT has high sensitivity,specificity and reliability for the detection and diagnosis of monosodium urate crystals in joints of gout patients.

Denoising images of dual energy X-ray absorptiometry using non-local means filters.

BACKGROUND: In general, the image quality of high and low energy images of dual energy X-ray absorptiometry (DXA) suffers from noise due to the use of a small amount of X-rays. Denoising of DXA images could be a key process to improve a bone mineral density map, which is derived from a pair of high and low energy images. This could further improve the accuracy of diagnosis of bone fractures and osteoporosis. OBJECTIVE: This study aims to develop and test a new technology to improve the quality, remove the noise, and preserve the edges and fine details of real DXA images. METHODS: In this study, a denoising technique for high and low energy DXA images using a non-local mean filter (NLM) was presented. The source and detector noises of a DXA system were modeled for both high and low DXA images. Then, the optimized parameters of the NLM filter were derived utilizing the experimental data from CIRS-BFP phantoms. After that, the optimized NLM was tested and verified using the DXA images of the phantoms and real human spine and femur. RESULTS: Quantitative evaluation of the results showed average 24.22% and 34.43% improvement of the signal-to-noise ratio for real high and low spine images, respectively, while the improvements were about 15.26% and 13.55% for the high and low images of the femur. The qualitative visual observations of both phantom and real structures also showed significantly improved quality and reduced noise while preserving the edges in both high and low energy images. Our results demonstrate that the proposed NLM outperforms the conventional method using an anisotropic diffusion filter (ADF) and median techniques for all phantom and real human DXA images. CONCLUSIONS: Our work suggests that denoising via NLM could be a key preprocessing method for clinical DXA imaging.