Using Patient-Specific Contrast Enhancement Optimizer Simulation Software During the Transcatheter Aortic Valve Implantation-Computed Tomography Angiography in Patients With Aortic Stenosis.

OBJECTIVES: This study assessed whether patient-specific contrast enhancement optimizer simulation software (p-COP) can reduce the contrast material (CM) dose compared with the conventional body weight (BW)-tailored scan protocol during transcatheter aortic valve implantation-computed tomography angiography (TAVI-CTA) in patients with aortic stenosis. METHODS: We used the CM injection protocol selected by the p-COP in group A (n = 30). p-COP uses an algorithm that concerns data on an individual patient's cardiac output. Group B (n = 30) was assigned to the conventional BW-tailored CM injection protocol group. We compared the CM dose, CM amount, injection rate, and computed tomography (CT) values in the abdominal aorta between the 2 groups and classified them as acceptable (>280 Hounsfield units (HU)) or unacceptable (<279 HU) based on the optimal CT value and visualization scores for TAVI-CTA. We used the Mann-Whitney U test to compare patient characteristics and assess the interpatient variability of subjects in both groups. RESULTS: Group A received 56.2 mL CM and 2.6 mL/s of injection, whereas group B received 76.9 mL CM and 3.4 mL/s of injection (P < 0.01). The CT value for the abdominal aorta at the celiac level was 287.0 HU in group A and 301.7HU in group B (P = 0.46). The acceptable (>280 HU) and unacceptable (<280 HU) CT value rates were 22 and 8 patients in group A and 24 and 6 patients in group B, respectively (P = 0.76). We observed no significant differences in the visualization scores between groups A and B (visualization score = 3, P = 0.71). CONCLUSION: The utilization of p-COP may decrease the CM dosage and injection rate by approximately 30% in individuals with aortic stenosis compared with the body-weight-tailored scan protocol during TAVI-CTA.

[Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm].

PURPOSE: To verify the optimal imaging conditions for coronary computed tomography angiography (CCTA) examinations when using high-definition (HD) mode and deep learning image reconstruction (DLIR) in combination. METHOD: A chest phantom and an in-house phantom using 3D printer were scanned with a 256-row detector CT scanner. The scan parameters were as follows - acquisition mode: ON (HD mode) and OFF (normal resolution [NR] mode), rotation time: 0.28 s/rotation, beam coverage width: 160 mm, and the radiation dose was adjusted based on CT-AEC. Image reconstruction was performed using ASiR-V (Hybrid-IR), TrueFidelity Image (DLIR), and HD-Standard (HD mode) and Standard (NR mode) reconstruction kernels. The task-based transfer function (TTF) and noise power spectrum (NPS) were measured for image evaluation, and the detectability index (d') was calculated. Visual evaluation was also performed on an in-house coronary phantom. RESULT: The in-plane TTF was better for the HD mode than for the NR mode, while the z-axis TTF was lower for DLIR than for Hybrid-IR. The NPS values in the high-frequency region were higher for the HD mode compared to those for the NR mode, and the NPS was lower for DLIR than for Hybrid-IR. The combination of HD mode and DLIR showed the best value for in-plane d', whereas the combination of NR mode and DLIR showed the best value for z-axis d'. In the visual evaluation, the combination of NR mode and DLIR showed the best values from a noise index of 45 HU. CONCLUSION: The optimal combination of HD mode and DLIR depends on the image noise level, and the combination of NR mode and DLIR was the best imaging condition under noisy conditions.

Nature of the Intracellular-contrast-enhancing Fat-saturated T1-weighted Gradient-echo (ICE-TIGRE) Sequence: A Fat-suppressed T1-weighted Technique with Motion-sensitised Driven-equilibrium for Improved Contrast Enhancement in Liver Imaging.

Gadoxetic acid is both an extracellular- and hepatocyte-specific contrast agent. Signals from the extracellular space may lower the contrast between lesions and the surrounding hepatic parenchyma. To improve hepatocyte-specific enhancement, we developed an intracellular contrast-enhancing fat-saturated T1-weighted gradient-echo nature of the sequence (ICE-TIGRE). It incorporates the motion-sensitized driven-equilibrium (MSDE) pulse to suppress signals from the blood flow. We investigated the optimal ICE-TIGRE scanning parameters, i.e., the order of the MSDE and the fat saturation pulses, the duration time, and the b value of the MSDE pulse, using a phantom and three volunteers without applying gadoxetic acid. ICE-TIGRE successfully increased the contrast between the liver parenchyma and the portal vein. To maintain fat saturation, the preparation pulse order should be MSDE-fat saturation. A duration time of 21 ms should be applied to minimize the effect of the T2 factor on the T1 contrast, and a b value of 60 s/mm2 should be applied to maximize the diffusion contrast for ICE-TIGRE with the imaging system used in this study.

Spectral Super-Resolution for High Dynamic Range Images.

The images we commonly use are RGB images that contain three pieces of information: red, green, and blue. On the other hand, hyperspectral (HS) images retain wavelength information. HS images are utilized in various fields due to their rich information content, but acquiring them requires specialized and expensive equipment that is not easily accessible to everyone. Recently, Spectral Super-Resolution (SSR), which generates spectral images from RGB images, has been studied. Conventional SSR methods target Low Dynamic Range (LDR) images. However, some practical applications require High Dynamic Range (HDR) images. In this paper, an SSR method for HDR is proposed. As a practical example, we use the HDR-HS images generated by the proposed method as environment maps and perform spectral image-based lighting. The rendering results by our method are more realistic than conventional renderers and LDR SSR methods, and this is the first attempt to utilize SSR for spectral rendering.

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma.

Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-energy CT equipped with a cascaded deep-learning reconstruction which completes the views missing in the sinogram space and improves the image quality in the image space because it uses deep convolutional neural networks trained on fully sampled dual-energy data acquired via dual kV rotations. We investigated the clinical utility of iodine maps generated from DL-SCTI scans for assessing hepatocellular carcinoma (HCC). In the clinical study, dynamic DL-SCTI scans (tube voltage 135 and 80 kV) were acquired in 52 patients with hypervascular HCCs whose vascularity was confirmed by CT during hepatic arteriography. Virtual monochromatic 70 keV images served as the reference images. Iodine maps were reconstructed using three-material decomposition (fat, healthy liver tissue, iodine). A radiologist calculated the contrast-to-noise ratio (CNR) during the hepatic arterial phase (CNRa) and the equilibrium phase (CNRe). In the phantom study, DL-SCTI scans (tube voltage 135 and 80 kV) were acquired to assess the accuracy of iodine maps; the iodine concentration was known. The CNRa was significantly higher on the iodine maps than on 70 keV images (p < 0.01). The CNRe was significantly higher on 70 keV images than on iodine maps (p < 0.01). The estimated iodine concentration derived from DL-SCTI scans in the phantom study was highly correlated with the known iodine concentration. It was underestimated in small-diameter modules and in large-diameter modules with an iodine concentration of less than 2.0 mgI/ml. Iodine maps generated from DL-SCTI scans can improve the CNR for HCCs during hepatic arterial phase but not during equilibrium phase in comparison with virtual monochromatic 70 keV images. Also, when the lesion is small or the iodine concentration is low, iodine quantification may result in underestimation.

Evaluation of the second-generation whole-heart motion correction algorithm (SSF2) used to demonstrate the aortic annulus on cardiac CT.

The main purpose of pre-transcatheter aortic valve implantation (TAVI) cardiac computed tomography (CT) for patients with severe aortic stenosis is aortic annulus measurements. However, motion artifacts present a technical challenge because they can reduce the measurement accuracy of the aortic annulus. Therefore, we applied the recently developed second-generation whole-heart motion correction algorithm (SnapShot Freeze 2.0, SSF2) to pre-TAVI cardiac CT and investigated its clinical utility by stratified analysis of the patient's heart rate during scanning. We found that SSF2 reconstruction significantly reduced aortic annulus motion artifacts and improved the image quality and measurement accuracy compared to standard reconstruction, especially in patients with high heart rate or a 40% R-R interval (systolic phase). SSF2 may contribute to improving the measurement accuracy of the aortic annulus.

Improvement of Spatial Resolution on Coronary CT Angiography by Using Super-Resolution Deep Learning Reconstruction.

RATIONALE AND OBJECTIVES: Our objective was to compare the image quality of coronary CT angiography reconstructed with super-resolution deep learning reconstruction (SR-DLR) and with hybrid iterative reconstruction (IR) images. MATERIALS AND METHODS: This retrospective study included 100 patients who underwent coronary CT angiography using a 320-detector-row CT scanner. The CT images were reconstructed with hybrid IR and SR-DLR. The standard deviation of the CT number was recorded and the CT attenuation profile across the left main coronary artery was generated to calculate the contrast-to-noise ratio (CNR) and measure the edge rise slope (ERS). Overall image quality was evaluated and plaque detectability was assessed on a 4-point scale (1 = poor, 4 = excellent). For reference, invasive coronary angiography of 14 patients was used. RESULTS: The mean image noise on SR-DLR was significantly lower than on hybrid IR images (15.6 vs 22.9 HU; p < 0.01). The mean CNR was significantly higher and the ERS was steeper on SR-DLR- compared to hybrid IR images (CNR: 32.4 vs 20.4, p < 0.01; ERS: 300.0 vs 198.2 HU/mm, p < 0.01). The image quality score was better on SR-DLR- than on hybrid IR images (3.6 vs 3.1; p < 0.01). SR-DLR increased the detectability of plaques with < 50% stenosis (p < 0.01). CONCLUSION: SR-DLR was superior to hybrid IR with respect to the image noise, the sharpness of coronary artery margins, and plaque detectability.

An introduction to photon-counting detector CT (PCD CT) for radiologists.

The basic performance of photon-counting detector computed tomography (PCD CT) is superior to conventional CT (energy-integrating detector CT: EID CT) because its spatial- and contrast resolution of soft tissues is higher, and artifacts are reduced. Because the X-ray photon energy separation is better with PCD CT than conventional EID-based dual-energy CT, it has the potential to improve virtual monochromatic- and virtual non-contrast images, material decomposition including quantification of the iodine distribution, and K-edge imaging. Therefore, its clinical applicability may be increased. Although the image quality of PCD CT scans is superior to that of EID CT currently, further improvement may be possible. The introduction of iterative image reconstruction and reconstruction with deep convolutional neural networks will be useful.

Reversible Brain Atrophy in Cryptogenic New-onset Refractory Status Epilepticus.

Cryptogenic new-onset refractory status epilepticus (C-NORSE) is a neurologic emergency condition characterized by refractory status epilepticus (RSE) of unknown cause. Brain atrophy in a setting of C-NORSE is usually irreversible. A 33-year-old woman who was highly suspected of C-NORSE once showed mild frontotemporal atrophy on brain magnetic resonance imaging (MRI), but follow-up MRI revealed recovery of the brain atrophy. Her cognitive function also gradually improved, with a reduction in seizure frequency. Early initiation of intensive immunotherapy with anti-seizure medications may have minimized irreversible brain damage associated with RSE, resulting in a relatively good outcome.

Utility of Wavelet Denoising with Geometry Factor Weighting for Gadoxetic Acid-enhanced Hepatobiliary-phase MR Imaging.

PURPOSE: The wavelet denoising with geometry factor weighting (g-denoising) method can reduce the image noise by adapting to spatially varying noise levels induced by parallel imaging. The aim of this study was to investigate the clinical applicability of g-denoising on hepatobiliary-phase (HBP) images with gadoxetic acid. METHODS: We subjected 53 patients suspected of harboring hepatic neoplastic lesions to gadoxetic acid-enhanced HBP imaging with and without g-denoising (g+HBP and g-HBP). The matrix size was reduced for g+HBP images to avoid prolonging the scanning time. Two radiologists calculated the SNR, the portal vein-, and paraspinal muscle contrast-to-noise ratio (CNR) relative to the hepatic parenchyma (liver-to-portal vein- and liver-to-muscle CNR). Two other radiologists independently graded the sharpness of the liver edge, the visibility of intrahepatic vessels, the image noise, the homogeneity of liver parenchyma, and the overall image quality using a 5-point scale. Differences between g-HBP and g+HBP images were determined with the two-sided Wilcoxon signed-rank test. RESULTS: The liver-to-portal- and liver-to-muscle CNR and the SNR were significantly higher on g+HBP- than g-HBP images (P < 0.01), as was the qualitative score for the image noise, homogeneity of liver parenchyma, and overall image quality (P < 0.01). Although there were no significant differences in the scores for the sharpness of the liver edge or the score assigned for the visibility of intrahepatic vessels (P = 0.05, 0.43), with g+HBP the score was lower in three patients for the sharpness of the liver edge and in six patients for the visibility of intrahepatic vessels. CONCLUSION: At gadoxetic acid-enhanced HBP imaging, g-denoising yielded a better image quality than conventional HBP imaging although the anatomic details may be degraded.

Performance of Ultra-High-Resolution Computed Tomography in Super High-Resolution Mode at the Routine Radiation Dose: Phantom Study.

OBJECTIVE: Using a chest phantom, we compared the image quality of ultra-high-resolution computed tomography (U-HRCT) images acquired in super high-resolution (SHR) and normal resolution (NR) mode and at the routine radiation dose. The detector size was 0.25 and 0.5 mm, respectively. METHODS: A chest phantom was scanned on a U-HRCT scanner. The scan parameters were tube voltage 120 kV and volume CT dose index 13.0 mGy, the routine radiation dose for conventional scans. The rotation time was 0.5 s/rot, the number of matrices was 512 in NR and 1024 in SHR mode. For physical evaluation, the modulation transfer function was measured on the spherical simulated nodule, and the noise power spectrum on the cylindrical water phantom. A CT value profile curve was created using an in-house simulated bronchial phantom. For visual evaluation, 3 radiologists and 3 radiology technologists evaluated overall image quality using a 4-grade scale (grade 1, poor; and grade 4, excellent). RESULTS: The 10% of modulation transfer function was 13.5 lp/cm in NR and 14.9 lp/cm in SHR mode ( P <0.01). ƒ peak was 5.6 lp/cm in NR and 8.8 lp/cm in SHR mode ( P <0.01), and the peak of noise power spectrum shifted. On the profile curves, the CT value at the edge changed in NR but not in SHR mode. The overall image quality was grade 3.0 ± 0.7 in SHR and grade 2.0 ± 0.7 in NR mode ( P <0.01). CONCLUSIONS: The image quality of SHR mode with U-HRCT was superior to that of NR mode at the routine radiation dose.

Prediction of Aortic Contrast Enhancement on Dynamic Hepatic Computed Tomography-Performance Comparison of Machine Learning Methods and Simulation Software.

OBJECTIVES: The aim of this study was to compare prediction ability between ensemble machine learning (ML) methods and simulation software for aortic contrast enhancement on dynamic hepatic computed tomography. METHODS: We divided 339 human hepatic dynamic computed tomography scans into 2 groups. One group consisted of 279 scans used to create cross-validation data sets, the other group of 60 scans were used as test data sets. To evaluate the effect of the patient characteristics on enhancement, we calculated changes in the contrast medium dose per enhancement of the abdominal aorta in the hepatic arterial phase. The parameters for ML were the patient sex, age, height, body weight, body mass index, and cardiac output. We trained 9 ML regressors by applying 5-fold cross-validation, integrated the predictions of all ML regressors for ensemble learning and the simulations, and used the training and test data to compare their Pearson correlation coefficients. RESULTS: Comparison of different ML methods showed that the Pearson correlation coefficient for the real and predicted contrast medium dose per enhancement of the abdominal aorta was highest with ensemble ML (r = 0.786). It was higher than that obtained with the simulation software (r = 0.350). With ensemble ML, the Bland-Altman limit of agreement [mean difference, 5.26 Hounsfield units (HU); 95% limit of agreement, -112.88 to 123.40 HU] was narrower than that obtained with the simulation software (mean difference, 11.70 HU; 95% limit of agreement, -164.71 to 188.11 HU). CONCLUSION: The performance for predicting contrast enhancement of the abdominal aorta in the hepatic arterial phase was higher with ensemble ML than with the simulation software.

Usefulness of the patient-specific contrast enhancement optimizer simulation software during the whole-body computed tomography angiography.

To evaluate whether the patient-specific contrast enhancement optimizer simulation software (p-COP) is useful for predicting contrast enhancement during whole-body computed tomography angiography (WBCTA). We randomly divided the patients into two groups using a random number table. We used the contrast material (CM) injection protocol selected by p-COP in group A (n = 52). The p-COP used an algorithm including data on the individual patient's cardiac output. Group B (n = 50) was assigned to the conventional CM injection protocol based on body weight. We compared the CT number in the abdominal aorta at the celiac artery level between the two groups and classified them as acceptable (> 280 HU) and unacceptable (< 279 HU) based on the optimal CT number for the WBCTA scans. To evaluate the difference in both injection protocols, we compared the visual inspection of the images of the artery of Adamkiewicz in both protocols. The CM dosage and injection rate in group A were significantly lower than those in group B (480.8 vs. 501.1 mg I/kg and 3.1 vs. 3.3 ml/s, p < 0.05). The CT number of the abdominal aorta at the celiac level was 382.4 ± 62.3 HU in group A and 363.8 ± 71.3 HU in group B (p = 0.23). CM dosage and injection rate were positively correlated to cardiac output for group A (r = 0.80, p < 0.05) and group B (r = 0.16, p < 0.05). The number of patients with an acceptable CT number was higher in group A [46/6 (86.7%)] than in group B [43/7 (71.4%)], but not significant (p = 0.71). The visualization rate for the Adamkiewicz artery was not significantly different between groups A and B (p = 0.89). The p-COP was useful for predicting contrast enhancement during WBCTA with a lower CM dosage and a lower contrast injection rate than that based on the body weight protocol. In patients with lower cardiac output a reduction in contrast injection rate and CM dosage did not lead to a reduced imaging quality, thus particularly in this group CM dosage can be reduced by p-COP.

Dual-energy CT: minimal essentials for radiologists.

Dual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed.

Tumor heterogeneity evaluated by computed tomography detects muscle-invasive upper tract urothelial carcinoma that is associated with inflammatory tumor microenvironment.

To detect muscle-invasive upper tract urothelial carcinoma, we evaluated the internal texture of the tumor using texture analysis of computed tomography images in 86 cases of upper tract urothelial carcinoma. The internal texture of the tumor was evaluated as the value of computed tomography attenuation number of the unenhanced image, and the median, standard deviation, skewness and kurtosis were calculated. Each parameter was compared with clinicopathological factors, and their associations with postoperative prognosis were investigated. Immunohistochemistry was performed to investigate the histological and molecular mechanisms of the inflammatory tumor microenvironment. The histogram of computed tomography attenuation number in non-muscle invasive tumor was single-peaked, whereas muscle invasive tumor showed a multi-peaked shape. In the parameters obtained by texture analysis, standard deviation was significantly associated with pathological stage (p < 0.0001), tumor grade (p = 0.0053), lymphovascular invasion (p = 0.0078) and concomitant carcinoma in situ (p = 0.0177) along with recurrence-free (p = 0.0191) and overall survival (p = 0.0184). The standard deviation value correlated with the amount of stromal components (p < 0.0001) and number of tumor-infiltrating macrophages (p < 0.0001). In addition, higher expression of high mobility group box 1 was found in heterogeneous tumor. Tumor heterogeneity evaluated by texture analysis was associated with muscle-invasive upper tract urothelial carcinoma and represented an inflammatory tumor microenvironment and useful as the clinical assessment to differentiate muscle invasive tumor.

Accuracy of thin-slice model-based iterative reconstruction designed for brain CT to diagnose acute ischemic stroke in the middle cerebral artery territory: a multicenter study.

PURPOSE: Model-based iterative reconstruction (MBIR) yields higher spatial resolution and a lower image noise than conventional reconstruction methods. We hypothesized that thin-slice MBIR designed for brain CT could improve the detectability of acute ischemic stroke in the middle cerebral artery (MCA) territory. METHODS: Included were 41 patients with acute ischemic stroke in the MCA territory; they were seen at 4 medical centers. The controls were 39 subjects without acute stroke. Images were reconstructed with hybrid IR and with MBIR designed for brain CT at slice thickness of 2 mm. We measured the image noise in the ventricle and compared the contrast-to-noise ratio (CNR) in the ischemic lesion. We analyzed the ability of reconstructed images to detect ischemic lesions using receiver operating characteristics (ROC) analysis; 8 observers read the routine clinical hybrid IR with 5 mm-thick images, while referring to 2 mm-thick hybrid IR images or MBIR images. RESULTS: The image noise was significantly lower on MBIR- than hybrid IR images (1.2 vs. 3.4, p < 0.001). The CNR was significantly higher with MBIR than hybrid IR (6.3 vs. 1.6, p < 0.001). The mean area under the ROC curve was also significantly higher on hybrid IR plus MBIR than hybrid IR (0.55 vs. 0.48, p < 0.036). Sensitivity, specificity, and accuracy were 41.2%, 88.8%, and 65.7%, respectively, for hybrid IR; they were 58.8%, 86.1%, and 72.9%, respectively, for hybrid IR plus MBIR. CONCLUSION: The additional thin-slice MBIR designed for brain CT may improve the detection of acute MCA stroke.

Advanced CT techniques for assessing hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the sixth-most common cancer in the world, and hepatic dynamic CT studies are routinely performed for its evaluation. Ongoing studies are examining advanced imaging techniques that may yield better findings than are obtained with conventional hepatic dynamic CT scanning. Dual-energy CT-, perfusion CT-, and artificial intelligence-based methods can be used for the precise characterization of liver tumors, the quantification of treatment responses, and for predicting the overall survival rate of patients. In this review, the advantages and disadvantages of conventional hepatic dynamic CT imaging are reviewed and the general principles of dual-energy- and perfusion CT, and the clinical applications and limitations of these technologies are discussed with respect to HCC. Finally, we address the utility of artificial intelligence-based methods for diagnosing HCC.

Incidence and factor analysis of laryngohyoid fractures in hanging individuals-computed tomography study.

OBJECTIVES: Although laryngohyoid fracture indicates the applied neck pressure and is an important finding in hanging individuals, the reported rate varies widely and its true incidence remains controversial. We used computed tomography (CT) studies to investigate the incidence of laryngohyoid fracture in hanging individuals and identify factors contributing to such fractures. METHODS: Considered for inclusion in this study were 107 attempted or successful hanging individuals subjected to CT studies between 2005 and 2019. After excluding 19 whose images were inadequate for evaluation, 88 subjects were included. Body suspension was complete in 20, partial in 49, and unknown in 19; 54 (61.4%) individuals died. Two radiologists performed image analysis and recorded the presence and site of laryngohyoid fractures. Multiple logistic regression analysis was used for factor analysis of laryngohyoid fractures; it included the gender, the age (< or ≧ 40 years), the type of suspension (complete or incomplete), and the outcome (death or survival). RESULTS: Of the 88 subjects, 35 (39.8%) presented with laryngohyoid fractures on CT images; the superior horn of the thyroid cartilage was fractured in 32 (91.4%) of the 35. Age was the only factor significantly related to laryngohyoid fracture (odds ratio = 2.85, 95% confidence interval = 1.08-7.52). CONCLUSIONS: In hanging individuals, the incidence of laryngohyoid fracture on CT images was 39.8%. The superior horn of the thyroid cartilage was the most frequent fracture site. KEY POINTS: • The incidence of laryngohyoid fracture on CT images of hanging individuals was almost 40%; the superior horn of the thyroid cartilage was the most frequent fracture site. • In older hanging individuals, attention must be paid to laryngohyoid fractures on CT images.