Consistency of Monoenergetic Attenuation Measurements for a Clinical Dual-Source Photon-Counting Detector CT System Across Scanning Paradigms: A Phantom Study.

BACKGROUND. Use of virtual monoenergetic images (VMIs) from multienergy CT scans can mitigate inconsistencies in traditional attenuation measurements that result from variation in scan-related factors. Photon-counting detector (PCD) CT systems produce VMIs as standard image output under flexible scanning conditions. OBJECTIVE. The purpose of this article was to evaluate the consistency of monoenergetic attenuation measurements obtained from a clinical PCD CT scanner across a spectrum of scanning paradigms. METHODS. A phantom with 10 tissue-simulating inserts was imaged using a clinical dual-source PCD CT scanner. Nine scanning paradigms were obtained across combinations of tube voltages (90, 120, and 140 kVp) and image quality (IQ) levels (80, 145, and 180). Images were reconstructed at VMI levels of 50, 60, 70, and 80 keV. Consistency of attenuation measurements was assessed, using the 120 kVp with IQ level of 145 scanning paradigm as the reference scan. RESULTS. For all scanning paradigms, attenuation measurements showed intra-class correlation of 0.999 and higher with respect to the reference scan. Across inserts, mean bias relative to the reference scan ranged from -14.9 to 13.6 HU, -2.7 to 1.7 HU, and -3.9 to 3.8 HU at tube voltages of 90, 120, and 140 kVp, respectively; and from -14.9 to 13.6 HU, -6.4 to 3.8 HU, -3.7 to 1.4 HU, and -7.2 to 4.3 HU at VMI levels of 50, 60, 70, and 80 keV, respectively. Thus, mean bias did not exceed 5 HU for any insert at tube potentials of 120 kVp and 140 kVp, nor for any insert at a VMI level of 70 keV. At a VMI level of 50 keV and tube potential of 90 kVp, mean bias exceeded 5 HU for 14 of 30 possible combinations of inserts and scanning paradigms and exceeded 10 HU for four of 30 such combinations. At VMI levels of both 60 and 80 keV, mean bias exceeded 5 HU for only two combinations of inserts and scanning paradigms, all at a tube potential of 90 kVp. CONCLUSION. PCD CT generally provided consistent attenuation measurements across combinations of scanning paradigms and VMI levels. CLINICAL IMPACT. PCD CT may facilitate quantitative applications of CT data in clinical practice.

Generation of virtual monoenergetic images at 40 keV of the upper abdomen and image quality evaluation based on generative adversarial networks.

BACKGROUND: Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use. PURPOSE: To develop a model that converts conventional images (CI) into generative virtual monoenergetic images at 40 keV (Gen-VMI40keV) of the upper abdomen CT scan. METHODS: Totally 444 patients who underwent upper abdominal spectral contrast-enhanced CT were enrolled and assigned to the training and validation datasets (7:3). Then, 40-keV portal-vein virtual monoenergetic (VMI40keV) and CI, generated from spectral CT scans, served as target and source images. These images were employed to build and train a CI-VMI40keV model. Indexes such as Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity (SSIM) were utilized to determine the best generator mode. An additional 198 cases were divided into three test groups, including Group 1 (58 cases with visible abnormalities), Group 2 (40 cases with hepatocellular carcinoma [HCC]) and Group 3 (100 cases from a publicly available HCC dataset). Both subjective and objective evaluations were performed. Comparisons, correlation analyses and Bland-Altman plot analyses were performed. RESULTS: The 192nd iteration produced the best generator mode (lower MAE and highest PSNR and SSIM). In the Test groups (1 and 2), both VMI40keV and Gen-VMI40keV significantly improved CT values, as well as SNR and CNR, for all organs compared to CI. Significant positive correlations for objective indexes were found between Gen-VMI40keV and VMI40keV in various organs and lesions. Bland-Altman analysis showed that the differences between both imaging types mostly fell within the 95% confidence interval. Pearson's and Spearman's correlation coefficients for objective scores between Gen-VMI40keV and VMI40keV in Groups 1 and 2 ranged from 0.645 to 0.980. In Group 3, Gen-VMI40keV yielded significantly higher CT values for HCC (220.5HU vs. 109.1HU) and liver (220.0HU vs. 112.8HU) compared to CI (p < 0.01). The CNR for HCC/liver was also significantly higher in Gen-VMI40keV (2.0 vs. 1.2) than in CI (p < 0.01). Additionally, Gen-VMI40keV was subjectively evaluated to have a higher image quality compared to CI. CONCLUSION: CI-VMI40keV model can generate Gen-VMI40keV from conventional CT scan, closely resembling VMI40keV.

Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer.

BACKGROUND: Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT) utilizing new virtual monoenergetic images can enhance cancer detection rates. This study aimed to assess the impact of virtual monoenergetic images reconstructed from DECT arterial phase scans on the image quality of prostate lesions and their diagnostic performance for prostate cancer. METHODS: We conducted a retrospective analysis of 83 patients with prostate cancer or prostatic hyperplasia who underwent DECT scans at Meizhou People's Hospital between July 2019 and December 2023. The variables analyzed included age, tumor diameter and serum prostate-specific antigen (PSA) levels, among others. We also compared CT values, signal-to-noise ratio (SNR), subjective image quality ratings, and contrast-to-noise ratio (CNR) between virtual monoenergetic images (40-100 keV) and conventional linear blending images. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic efficacy of virtual monoenergetic images (40 keV and 50 keV) compared to conventional images. RESULTS: Virtual monoenergetic images at 40 keV showed significantly higher CT values (168.19 ± 57.14) compared to conventional linear blending images (66.66 ± 15.5) for prostate cancer (P < 0.001). The 50 keV images also demonstrated elevated CT values (121.73 ± 39.21) compared to conventional images (P < 0.001). CNR values for the 40 keV (3.81 ± 2.13) and 50 keV (2.95 ± 1.50) groups were significantly higher than the conventional blending group (P < 0.001). Subjective evaluations indicated markedly better image quality scores for 40 keV (median score of 5) and 50 keV (median score of 5) images compared to conventional images (P < 0.05). ROC curve analysis revealed superior diagnostic accuracy for 40 keV (AUC: 0.910) and 50 keV (AUC: 0.910) images based on CT values compared to conventional images (AUC: 0.849). CONCLUSIONS: Virtual monoenergetic images reconstructed at 40 keV and 50 keV from DECT arterial phase scans substantially enhance the image quality of prostate lesions and improve diagnostic efficacy for prostate cancer.

Iodine concentration, HU accuracy, and metal artifacts evaluation on second-generation dual-layer spectral detector CT images with metal implants: a phantom study.

BACKGROUND: Metal implants may affect the image quality, iodine concentration (IC), and CT Hounsfield unit (HU) quantification accuracy. PURPOSE: To investigate the quantitative accuracy of IC and HU from dual-layer spectral detector (DLCT) in the presence of metal artifacts. MATERIAL AND METHODS: An experimental cylindrical phantom containing eight iodine inserts and two metal inserts was designed. The phantom underwent scanning at three radiation dose levels and two tube voltage settings. A set of conventional images (CIs), virtual monoenergetic images (VMIs), and iodine concentration maps (ICMs) were generated and measured for all the eight iodine inserts. Quantitative indicators of mean absolute percentage error (MAPE), artifact index (AI), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and standard deviation (SD) on CIs and VMIs were calculated for IC and HU. Subjective score evaluation was also conducted. RESULTS: The MAPEiodine values of all regions of interest across different scanning configurations were all <5%. Almost all APEiodine values were <5%, indicating that metal artifacts had little impact on IC measurements. When the tube voltage was fixed, the SD value of attenuation decreased with the increase of the tube current; this is also true when the tube current was fixed. The middle energy reconstructions seemed to give a good balance between reducing artifacts and improving contrast. CONCLUSION: VMIs from DLCT can reduce metal artifacts, the accuracy of IC quantification is not sensitive to imaging parameters. In summary, metal implants exhibit minimal impact on image quality and IC quantification accuracy in reconstructed images from DLCT.

Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images.

PURPOSE: To compare the diagnostic performance of 40 keV and 70 keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer. METHODS: This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11 years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70 keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40 keV and 70 keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations. RESULTS: Overall, 137 patients (median age, 71 years; interquartile range, 63-78 years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40 keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70 keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs. CONCLUSIONS: The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70 keV VMIs, along with higher reader confidence.

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

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

Impact of four kVp combinations available in a dual-source CT on the spectral performance of abdominal imaging: A task-based image quality assessment on phantom data.

PURPOSE: To compare the spectral performance of four combinations of kVp available in a third generation dual-source CT (DSCT) on abdominal imaging. METHODS: An image-quality phantom was scanned with a DSCT using four kVp pairs (tube "A" voltage/tube "B" voltage): 100/Sn150 kVp, 90/Sn150 kVp, 80/Sn150 kVp, and 70/Sn150 kVp, classic parameters and dose level for abdomen examination (CTDIvol : 11 mGy). The noise power spectrum (NPS) and the task-based transfer function (TTF) of two inserts were computed on virtual monochromatic images (VMIs) at 40/50/60/70 keV and for mixed, low-, and high-kVp images. Detectability index (d') was computed on VMIs and mixed images to model the detection task of liver metastasis (LM) and hepatocellular carcinoma (HCC). Iodine quantification accuracy was assessed using the Root Mean Square Deviation (RMSDiodine ) and the iodine bias (IB). RESULTS: Noise magnitude decreased by -55%± 0% between 40 and 70 keV for all kVp pairs. Compared to 70/Sn150 kVp, noise magnitude was increased by 9% ± 0% with 80/Sn150 kVp, by 16% ± 1% with 90/Sn150 kVp and by 24%± 1% with 100/Sn150 kVp. The average NPS spatial frequency (fav ) shifted toward higher frequencies as energy level increased for all kVp pairs. Lowest fav values were found for 70/Sn150 kVp and highest for 100/Sn150 kVp. The value of TTF at 50% (f50 ) shifted toward lower frequencies with increasing energy level. The highest f50  values occurred for 100/Sn150 kVp and the lowest for 80/Sn150 kVp. For both lesions, d' was highest for 70/Sn150 kVp and lowest for 100/Sn150 kVp. Compared to 70/Sn150 kVp, d' decreased by -6% ± 3% with 80/Sn150 kVp, by -11% ± 2% with 90/Sn150 kVp and by -13%± 2% with 100/Sn150 kVp. For all acquisitions, the RSMDiodine and IB were the lowest for 100/Sn150 kVp (0.29 ± 0.10 mg/ml and 0.88 ± 0.30 mg/ml, respectively) and increased when the tube "A" voltage decreased (2.34 ± 0.29 mg/ml for 70/Sn150 kVp and 7.42 ± 0.51 mg/ml respectively). CONCLUSION: 70/Sn150 kVp presented the lowest image noise and highest detectability in VMIs of two small focal liver lesions. 100/Sn150 kVp presented the lowest image noise on mixed images and highest accuracy of iodine quantification in iodine images.

Dual-layer spectral computerized tomography for metal artifact reduction: small versus large orthopedic devices.

INTRODUCTION: Metal artifacts limit the diagnostic utility of computerized tomography (CT) for implant-related complications. Dual-layer spectral detector CT imaging has been suggested for artifact reduction. Our objective was to evaluate the utility of spectral CT in artifact reduction in patients with small and large metal implants. METHODS: In this prospective study, patients with metallic orthopedic implants underwent CT imaging using a prototype spectral detector CT scanner. Conventional images were generated with iterative reconstruction at 120 kVp, and virtual monochromatic images were generated at 20-keV intervals between 40 to 200 keV. Conventional and monochromatic images were compared quantitatively using signal-to-noise ratio (SNR) and artifact improvement. Qualitative analysis was performed independently by two musculoskeletal radiologists and included six image quality indicators. RESULTS: A total of 12 patients were scanned. In monochromatic images, as the energy level increased, the artifact size decreased progressively (p < 0.01). When conventional and monochromatic images were compared, maximum reduction was seen at 200 keV. Using qualitative assessments, 160 and 180 keV levels had the best overall diagnostic image quality. With increased energy level, there was improvement in qualitative ratings of bone-metal interface conspicuity (p = 0.002), degree of streak artifact (p = 0.010) and trabecular bone definition at 1 cm from implant (p = 0.023), and a trend towards significance for bone definition at 5 cm, soft tissue detail and overall diagnostic quality. Subgroup analysis revealed superior artifact reduction in small implants compared to large hardware. DISCUSSION: Our results support the utility of dual-layer spectral CT in metal artifact reduction. Virtual monochromatic images were diagnostically superior, especially for smaller implants. Virtual monoenergetic images at 160-180 keV are ideal for reducing artifacts.

Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.

PURPOSE: Virtual monoenergetic images (VMIs) derived from dual-energy computed tomography (DECT) have been explored for several clinical applications in recent years. However, VMIs at low and high keVs have high levels of noise. The aim of this study was to reduce image noise in VMIs by using a two-step noise reduction technique. METHODS: VMI was first denoised using a modified highly constrained backprojection (HYPR) method. After the first-step denoising, a general-threshold filtering method was performed. Two sets of anthropomorphic phantoms were scanned with a clinical dual-source DECT system. DECT data (80/140Sn kV) were reconstructed as VMI series at 12 different energy levels (range, 40-150 keV, interval, 10 keV). For comparison, the averaged VMIs obtained from 10 repeated DECT scans were used as the reference standard. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and root-mean-square error (RMSE) were used to evaluate the quality of VMIs. RESULTS: Compared to the original HYPR method, the proposed two-step image denoising method could provide better performance in terms of SNR, CNR, and RMSE. In addition, the proposed method could achieve effective noise reduction while preserving edges and small structures, especially for low-keV VMIs. CONCLUSION: The proposed two-step image denoising method is a feasible method for reducing noise in VMIs obtained from a clinical DECT scanner. The proposed method can also reduce edge blurring and the loss of intensity in small lesions.

Comparison of virtual monoenergetic and polyenergetic images reconstructed from dual-layer detector CT angiography of the head and neck.

OBJECTIVES: To compare the image quality of virtual monoenergetic images and polyenergetic images reconstructed from dual-layer detector CT angiography (DLCTA). METHODS: Thirty patients who underwent DLCTA of the head and neck were retrospectively identified and polyenergetic as well as virtual monoenergetic images (40 to 120 keV) were reconstructed. Signals (± SD) of the cervical and cerebral vessels as well as lateral pterygoid muscle and the air surrounding the head were measured to calculate the CNR and SNR. In addition, subjective image quality was assessed using a 5-point Likert scale. Student's t-test and Wilcoxon test were used to determine statistical significance. RESULTS: Compared to polyenergetic images, although noise increased with lower keV, CNR (p < 0.02) and SNR (p > 0.05) of the cervical, petrous and intracranial vessels were improved in virtual monoenergetic images at 40 keV and virtual monoenergetic images at 45 keV were also rated superior regarding vascular contrast, assessment of arteries close to the skull base and small arterial branches (p < 0.0001 each). CONCLUSIONS: Compared to polyenergetic images, virtual monoenergetic images reconstructed from DLCTA at low keV ranging from 40 to 45 keV improve the objective and subjective image quality of extra- and intracranial vessels and facilitate assessment of vessels close to the skull base and of small arterial branches. KEY POINTS: • Virtual monoenergetic images greatly improve attenuation, while noise only slightly increases. • Virtual monoenergetic images show superior contrast-to-noise ratios compared to polyenergetic images. • Virtual monoenergetic images significantly improve image quality at low keV.

A noise-optimized virtual monoenergetic reconstruction algorithm improves the diagnostic accuracy of late hepatic arterial phase dual-energy CT for the detection of hypervascular liver lesions.

OBJECTIVES: To assess the image quality and diagnostic accuracy of a noise-optimized virtual monoenergetic imaging (VMI+) algorithm compared with standard virtual monoenergetic imaging (VMI) and linearly-blended (M_0.6) reconstructions for the detection of hypervascular liver lesions in dual-energy CT (DECT). METHODS: Thirty patients who underwent clinical liver MRI were prospectively enrolled. Within 60 days of MRI, arterial phase DECT images were acquired on a third-generation dual-source CT and reconstructed with M_0.6, VMI and VMI+ algorithms from 40 to 100 keV in 5-keV intervals. Liver parenchyma and lesion contrast-to-noise-ratios (CNR) were calculated. Two radiologists assessed image quality. Lesion sensitivity, specificity and area under the receiver operating characteristic curves (AUCs) were calculated for the three algorithms with MRI as the reference standard. RESULTS: VMI+ datasets from 40 to 60 keV provided the highest liver parenchyma and lesion CNR (p ≤0.021); 50 keV VMI+ provided the highest subjective image quality (4.40±0.54), significantly higher compared to VMI and M_0.6 (all p <0.001), and the best diagnostic accuracy in < 1-cm diameter lesions (AUC=0.833 vs. 0.777 and 0.749, respectively; p ≤0.003). CONCLUSIONS: 50-keV VMI+ provides superior image quality and diagnostic accuracy for the detection of hypervascular liver lesions with a diameter < 1cm compared to VMI or M_0.6 reconstructions. KEY POINTS: • Low-keV VMI+ are characterized by higher contrast resulting from maximum iodine attenuation. • VMI+ provides superior image quality compared with VMI or M_0.6. • 50-keV_VMI+ provides higher accuracy for the detection of hypervascular liver lesions < 1cm.

Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms.

OBJECTIVE: Aim of this study was to assess the artifact reduction in patients with orthopedic hardware in the spine as provided by (1) metal-artifact-reduction algorithms (O-MAR) and (2) virtual monoenergetic images (MonoE) as provided by spectral detector CT (SDCT) compared to conventional iterative reconstruction (CI). METHODS: In all, 28 consecutive patients with orthopedic hardware in the spine who underwent SDCT-examinations were included. CI, O-MAR and MonoE (40-200 keV) images were reconstructed. Attenuation (HU) and noise (SD) were measured in order to calculate signal-to-noise ratio (SNR) of paravertebral muscle and spinal canal. Subjective image quality was assessed by two radiologists in terms of image quality and extent of artifact reduction. RESULTS: O-MAR and high-keV MonoE showed significant decrease of hypodense artifacts in terms of higher attenuation as compared to CI (CI vs O-MAR, 200 keV MonoE: -396.5HU vs. -115.2HU, -48.1HU; both p ≤ 0.001). Further, artifacts as depicted by noise were reduced in O-MAR and high-keV MonoE as compared to CI in (1) paravertebral muscle and (2) spinal canal-CI vs. O-MAR/200 keV: (1) 34.7 ± 19.0 HU vs. 26.4 ± 14.4 HU, p ≤ 0.05/27.4 ± 16.1, n.s.; (2) 103.4 ± 61.3 HU vs. 72.6 ± 62.6 HU/60.9 ± 40.1 HU, both p ≤ 0.001. Subjectively both O-MAR and high-keV images yielded an artifact reduction in up to 24/28 patients. CONCLUSION: Both, O-MAR and high-keV MonoE reconstructions as provided by SDCT lead to objective and subjective artifact reduction, thus the combination of O-MAR and MonoE seems promising for further reduction.

Pancreatic cancer in photon-counting CT: Low keV virtual monoenergetic images improve tumor conspicuity.

PURPOSE OF THE STUDY: The aim of the study was to identify differences in the tumor conspicuity of pancreatic adenocarcinomas in different monoenergetic or polyenergetic reconstructions and contrast phases in photon-counting CT (PCCT). MATERIAL AND METHODS: 34 patients were retrospectively enrolled in this study. Quantitative image analysis was performed with region of interest (ROI) measurements in different monoenergetic levels ranging from 40 up to 70 keV (5-point steps) and polyenergetic series. Tumor-parenchyma attenuation differences and contrast-to-noise-ratio (CNR) were calculated. A qualitative image analysis was accomplished by 4 radiologists using a 5-point Likert scale (1 = "not recognizable" up to 5 = "easy recognizable"). Differences between groups were evaluated for statistical significance using the Friedman test and in case of significant differences pair-wise post-hoc testing with Bonferroni correction was applied. RESULTS: Tumor-parenchyma attenuation difference was significantly different between the different image reconstructions for both arterial- and portal-venous-phase-images (p < 0.001). Tumor-parenchyma attenuation difference was significantly higher on arterial-phase-images at mono40keV compared to polyenergetic images (p < 0.001) and mono55keV images or higher (p < 0.001). For portal-venous-phase-images tumor-parenchyma attenuation difference was significantly higher on mono40keV images compared to polyenergetic images (p < 0.001) and mono50keV images (p = 0.03) or higher (p < 0.001). The same trend was seen for CNR. Tumor conspicuity was rated best on mono40keV images with 4.3 ± 0.9 for arterial-phase-images and 4.3 ± 1.1 for portal-venous-phase-images. In contrast, overall image quality was rated best on polyenergetic-images with 4.8 ± 0.5 for arterial-phase-images and 4.7 ± 0.6 for portal-venous-phase-images. CONCLUSION: Low keV virtual monoenergetic images significantly improve the tumor conspicuity of pancreatic adenocarcinomas in PCCT based on quantitative and qualitative results. On the other hand, readers prefer polyenergetic images for overall image quality.

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

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

Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.

Background: Dual-energy computed tomography (CT) can provide a range of image information beyond conventional CT through virtual monoenergetic images (VMIs). The purpose of this study was to investigate the impact of material decomposition in detector-based spectral CT on radiomics features and effectiveness of using deep learning-based image synthesis to improve the reproducibility of radiomics features. Methods: In this paper, spectral CT image data from 45 esophageal cancer patients were collected for investigation retrospectively. First, we computed the correlation coefficient of radiomics features between conventional kilovoltage peak (kVp) CT images and VMI. Then, a wavelet loss-enhanced CycleGAN (WLL-CycleGAN) with paired loss terms was developed to synthesize virtual monoenergetic CT images from the corresponding conventional single-energy CT (SECT) images for improving radiomics reproducibility. Finally, the radiomic features in 6 different categories, including gray-level co-occurrence matrix (GLCM), gray-level difference matrix (GLDM), gray-level run-length matrix (GLRLM), gray-level size-zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and wavelet, were extracted from the gross tumor volumes from conventional single energy CT, synthetic virtual monoenergetic CT images, and virtual monoenergetic CT images. Comparison between errors in the VMI and synthetic VMI (sVMI) suggested that the performance of our proposed deep learning method improved the radiomic feature accuracy. Results: Material decomposition of dual-layer dual-energy CT (DECT) can substantially influence the reproducibility of the radiomic features, and the degree of impact is feature dependent. The average reduction of radiomics errors for 15 patients in testing sets was 96.9% for first-order, 12.1% for GLCM, 12.9% for GLDM, 15.7% for GLRLM, 50.3% for GLSZM, 53.4% for NGTDM, and 6% for wavelet features. Conclusions: The work revealed that material decomposition has a significant effect on the radiomic feature values. The deep learning-based method reduced the influence of material decomposition in VMIs and might improve the robustness and reproducibility of radiomic features in esophageal cancer. Quantitative results demonstrated that our proposed wavelet loss-enhanced paired CycleGAN outperforms the original CycleGAN.

Application of dual-energy CT with prospective ECG-gating in cardiac CT angiography for children: Radiation and contrast agent dose.

OBJECTIVE: This research aimed to investigate the feasibility of utilizing dual-energy CT virtual monoenergetic images (VMI1) with prospective electrocardiogram (ECG2) gating for reducing radiation and contrast agent doses in pediatric patients with congenital heart disease (CHD3). METHODS: There were 100 pediatric patients with CHD included in this study. Group A (n = 50) underwent dual-energy scanning with prospective ECG-gating, and group B (n = 50) underwent conventional scanning with retrospective ECG-gating. Comparative analysis of CT values of lumen, objective image quality assessment, subjective image quality evaluations, and diagnostic efficacy were performed. RESULTS: CT values, image noise, signal-to-noise ratio (SNR4), and contrast-to-noise ratio (CNR5) were significantly affected by the VMI energy level, and they all increased with decreasing energy levels (P > 0.05). Combining subjective evaluation, the 45 keV VMI was considered the optimum image in group A. The 45 keV VMI exhibited higher CT values of lumen compared to conventional scanning images (P < 0.003 âˆ¼ 0.836), but meanwhile, the image noise was also higher in the 45 keV VMI (P = 0.004). Differences between the two groups in SNR, CNR, and diagnostic accuracy were not statistically significant. Compared to group B, the 45 keV VMI showed fewer contrast-induced artifacts (P < 0.001) and higher image quality score (P = 0.037). Group A had a 64 % reduction in radiation dose and a 40 % decrease in iodine dose compared to group B. CONCLUSION: The combination of dual-energy CT with prospective ECG-gating reduces radiation and iodine doses in pediatric patients with CHD. The 45 keV VMI can provide clinically acceptable image quality while declining contrast agent artifacts.

Imaging of hypodense gliotic lesions in photon counting computed tomography using virtual monoenergetic images.

OBJECTIVES: Glioses appear as hypodense lesions in non-contrast CT examinations of the head. Photon counting CT (PCCT) enables the calculation of virtual monoenergetic images (VMI). The aim of this study is to investigate in which VMI hypodense gliotic lesions can be delineated best. MATERIALS AND METHODS: 35 patients with an MRI-confirmed gliotic lesion and a non-contrast PCCT of the head were retrospectively included. All available VMI from 40 keV to 190 keV were calculated. In a quantitative analysis, conventional image quality parameters were calculated, in particular the contrast-to-noise ratio (CNR) of the hypodense lesion compared to the white matter. In a qualitative analysis, selected VMI were rated by experienced radiologists. RESULTS: The absolute maximum of CNR was 8.12 ± 5.64 in the VMI 134 keV, in post hoc testing, there were significant differences in comparison to VMI with keV ≤110 and keV ≥180 (corrected p < .05). In the qualitative analysis, there were only very slight differences in the rating of the VMI with 66 keV, 80 keV, 100 keV, and 134 keV with overall low agreement between the readers. CONCLUSIONS: The quantitative superiority of VMI 134 keV for the delineation of hypodense gliotic lesions did not translate into a superiority in the qualitative analysis. Therefore, it remains uncertain if the reconstruction of a high keV VMIs for the detection of hypodense gliotic lesions is useful in everyday clinical practice. However, more studies, are necessary to further assess this issue.

Nonenhanced Photon Counting CT of the Head : Impact of the keV Level, Iterative Reconstruction and Calvaria on Image Quality in Monoenergetic Images.

PURPOSE: Nonenhanced computed tomography (CT) of the head is among the most commonly performed CT examinations. The spectral information acquired by photon counting CT (PCCT) allows generation of virtual monoenergetic images (VMI). At the same time, image noise can be reduced using quantum iterative reconstruction (QIR). In this study, the image quality of VMI was evaluated depending on the keV level and the QIR level. Furthermore, the influence of the cranial calvaria was investigated to determine the optimal reconstruction for clinical application. METHODS: A total of 51 PCCT (NAEOTOM Alpha, Siemens Healthineers, Erlangen, Germany) of the head were retrospectively analyzed. In a quantitative analysis, gray and white matter ROIs were evaluated in different brain areas at all available keV levels and QIR levels with respect to signal, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The distance to the cranial calvaria of the ROIs was included in the analysis. This was followed by a qualitative reading by five radiologists including experienced neuroradiologists. RESULTS: In most ROIs, signal and noise varied significantly between keV levels (p < 0.0001). The CNR had a focal maximum at 66 keV and an absolute maximum at higher keV, slightly differently located depending on ROI and QIR level. With increasing QIR level, a significant reduction in noise was achieved (p < 0.0001) except just beneath the cranial calvaria. The cranial calvaria had a strong effect on the signal (p < 0.0001) but not on gray and white matter noise. In the qualitative reading, the 60 keV VMI was rated best. CONCLUSION: In nonenhanced PCCT of the head the selected keV level of the VMI and the QIR level have a crucial influence on image quality in VMI. The 60 keV and 66 keV VMI with high QIR level provided optimal subjective and objective image quality for clinical use. The cranial calvaria has a significant influence on the visualization of the adjacent brain matter; currently, this substantially limits the use of low keV VMIs (< 60 keV).

Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions.

To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enrolled. The 60 s delayed phase of DECTA was evaluated. Objective [noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR)] and subjective (overall image quality and endoleak conspicuity - 3 blinded readers assessment) image quality analyses were performed. The following reconstructions were evaluated: VMI 40, 60 keV VMI; IR VMI 40, 60 keV; DLM VMI 40, 60 keV. The noise level of the DLM VMI images was approximately 50% lower than that of VMI reconstruction. The highest CNR and SNR values were measured in VMI DLM images. The mean CNR in endoleak in 40 keV was accounted for as 1.83 ± 1.2; 2.07 ± 2.02; 3.6 ± 3.26 in VMI, VMI IR, and VMI DLM, respectively. The DLM algorithm significantly reduced noise and increased lesion conspicuity, resulting in higher objective and subjective image quality compared to other reconstruction techniques. The application of DLM algorithms to low-energy VMIs significantly enhances the diagnostic value of DECTA in evaluating endoleaks. DLM reconstructions surpass traditional VMIs and IR in terms of image quality.

Transcatheter Aortic Valve Implantation (TAVI) Planning with Dual-Layer Spectral CT Using Virtual Monoenergetic Image (VMI) Reconstructions and 20 mL of Contrast Media.

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical implantation and its implementation is progressively increasing worldwide. We routinely perform pre-procedural aortic angiography CT to assess aortic dimensions and vascular anatomy. This study aims to evaluate the image quality of CTA for TAVI planning using dual-layer spectral CT, with virtual monoenergetic image reconstructions at 40 keV. Thirty-one patients underwent a CTA protocol with the injection of 20 mL of contrast media. Image quality was assessed by measuring the mean density in Hounsfield Units (HU), the signal-to-noise ratio, and the contrast-to-noise ratio in VMI reconstructions. Additionally, a blinded subjective analysis was conducted by two observers. The results showed significant enhancement at all sampled vascular levels with a gradual decrease in HU from proximal to distal regions. Favourable subjective ratings were given for all parameters, with greater variability in the evaluation of iliac axes. A significant negative correlation (p < 0.05) was observed between BMI and CA at all vascular levels, indicating reduced contrast enhancement with increasing BMI. Spectral CT, along with reducing iodine load, allows for obtaining high-quality images without a significant increase in noise. The reduction in iodine load can have positive implications in clinical practice, improving patient safety and resource efficiency.