[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.

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.

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.

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.

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 (CNR_a) and the equilibrium phase (CNR_e). 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 CNR_a was significantly higher on the iodine maps than on 70 keV images (p < 0.01). The CNR_e 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.

Reversible Brain Atrophy in Cryptogenic New-onset Refractory Status Epilepticus: A Case Report

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.

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.

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.

Computer Simulation of the Effects of Contrast Protocols on Aortic Signal Intensity on Magnetic Resonance Angiograms

BACKGROUND

While iodine-enhanced computed tomography has been studied, detailed information on gadolinium-enhanced magnetic resonance imaging has not been reported.

OBJECTIVE

We evaluated the effects of different gadolinium contrast agent (Gd-CA) factors on the enhancement of aortic magnetic resonance angiography (MRA) using computer simulation.

METHODS

We developed computer-simulation software that combines pharmacokinetic models and tables; it converts the blood concentration of particular Gd-CAs into the signal intensity (SI). We simulated aortic time-intensity curves (TIC) in our MRA study and compared the effect of the Gd-- CA volume, injection rate, and of different Gd-CAs on the TIC.

RESULTS

An increase in the Gd-CA volume from 14.0 to 28.0 ml increased maximal aortic intensity 1.11 times. Changing the injection rate from 1.0 to 2.8 ml/s increased it 1.10 times. The maximal SI of gadoterate-meglumine and gadobutrol was 1.03 and 1.01 times, respectively, that of gadoteridol.

CONCLUSION

In our computer-simulated MRA study, different Gd-CA factors resulted in no significant difference in the maximal aortic SI.

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.

Prospective Memory Deficits in Multiple Sclerosis: Voxel-based Morphometry and Double Inversion Recovery Analysis

Objective Prospective memory (PM) is an important social cognitive function in everyday life. PM is one of the most affected cognitive domains in multiple sclerosis (MS) patients. Gray matter (GM) atrophy and plaques have been attracting attention for various cognitive impairments in MS patients. This study aimed to clarify the atrophic GM regions associated with PM deficits and investigate the relationship between the atrophic GM regions and GM plaques. Methods Twenty-one MS patients and 10 healthy controls (HCs) underwent neuropsychological tests and MRI. PM was assessed using subtests of the Rivermead Behavioural Memory Test. A lesion symptom analysis was performed using voxel-based morphometry (VBM). We then evaluated GM plaques in the corresponding areas using double inversion recovery (DIR). Results MS patients showed lower PM scores than HCs (p=0.0064). The GM volume of MS patients tended to be lower than those of HCs. VBM analyses revealed correlations of the PM score with the orbital part of the left inferior frontal gyrus, the left hippocampus, and the right parahippocampus. There was no GM plaque in the orbital part of the left inferior frontal gyrus and the right parahippocampus. Only one patient (4.8%) had GM plaque in the left hippocampus. Conclusion The left inferior frontal gyrus, the left hippocampus, and the right parahippocampus were associated with PM in MS, whereas these atrophic GM regions were not associated with GM plaque. Regardless of the location of plaques on DIR, both PM deficit and GM atrophy should be detected using neuropsychological tests and VBM in MS patients.

Deep learning reconstruction of equilibrium phase CT images in obese patients

PURPOSE

To compare abdominal equilibrium phase (EP) CT images of obese and non-obese patients to identify the reconstruction method that preserves the diagnostic value of images obtained in obese patients.

METHODS

We compared EP images of 50 obese patients whose body mass index (BMI) exceeded 25 (group 1) with EP images of 50 non-obese patients (BMI < 25, group 2). Group 1 images were subjected to deep learning reconstruction (DLR), hybrid iterative reconstruction (hybrid-IR), and model-based IR (MBIR), group 2 images to hybrid-IR; group 2 hybrid-IR images served as the reference standard. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise. The overall image quality was assessed by 3 other radiologists; they used a confidence scale ranging from 1 (unacceptable) to 5 (excellent). Non-inferiority and potential superiority were assessed.

RESULTS

With respect to the image noise, group 1 DLR- were superior to group 2 hybrid-IR images; group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images. The quality scores of only DLR images in group 1 were superior to hybrid-IR images of group 2 while the quality scores of group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images.

CONCLUSIONS

DLR preserved the quality of EP images obtained in obese patients.

A primer for understanding radiology articles about machine learning and deep learning

The application of machine learning and deep learning in the field of imaging is rapidly growing. Although the principles of machine and deep learning are unfamiliar to the majority of clinicians, the basics are not so complicated. One of the major issues is that commentaries written by experts are difficult to understand, and are not primarily written for clinicians. The purpose of this article was to describe the different concepts behind machine learning, radiomics, and deep learning to make clinicians more familiar with these techniques.

Measurement of coronary artery calcium volume using ultra-high-resolution computed tomography: A preliminary phantom and cadaver study

•

Small calcifications were moe accurately detectable on SHR- than NR images.

•

The mean CAC volume was significantly higher on SHR- than NR images of the cadavers.

•

SHR imaging may facilitate the accurate quantification of the CAC.

Objectives

In this phantom- and cadaver study we investigated the differences of coronary artery calcium (CAC) volume on ultra-high-resolution computed tomography (U-HRCT) scans and conventional CT.

Methods

We scanned a coronary calcium phantom and the coronary arteries of five cadavers using U-HRCT in normal- and super-high resolution (NR, SHR) mode. The NR mode was similar to conventional CT; 896 detector channels, a matrix size of 512, and a slice thickness of 0.5 mm were applied. In SHR mode, we used 1792 detector channels, a matrix size of 1024, and a slice thickness of 0.25 mm. The CAC volume on NR- and SHR images were recorded. Differences in the physical- and the calculated CAC volume were defined as the error value and compared between NR- and SHR images of the phantom. Differences between the CAC volume on NR- and SHR scans of the cadavers were also recorded.

Results

The mean error value was lower on SHR- than NR images of the phantom (14.0 %, SD 11.1 vs 20.1 %, SD 15.2, p = 0.01). The mean CAC volume was significantly higher on SHR- than NR images of the cadavers (153.4 mm³, SD 161.0 vs 144.7 mm³, SD 164.8, p < 0.01).

Conclusions

As small calcifications were more clearly visualized on U-HRCT images in SHR mode than on conventional (NR) CT scans, SHR imaging may facilitate the accurate quantification of the CAC.

Deep learning reconstruction of drip-infusion cholangiography acquired with ultra-high-resolution computed tomography

PURPOSE

Deep learning reconstruction (DLR) introduces deep convolutional neural networks into the reconstruction flow. We examined the clinical applicability of drip-infusion cholangiography (DIC) acquired on an ultra-high-resolution CT (U-HRCT) scanner reconstructed with DLR in comparison to hybrid and model-based iterative reconstruction (hybrid-IR, MBIR).

METHODS

This retrospective, single-institution study included 30 patients seen between January 2018 and November 2019. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise and calculated the contrast-to-noise ratio (CNR) in the common bile duct. The overall visual image quality of the bile duct on thick-slab maximum intensity projections was assessed by two other radiologists and graded on a 5-point confidence scale ranging from 1 (not delineated) to 5 (clearly delineated). The difference among hybrid-IR, MBIR, and DLR images was compared.

RESULTS

The image noise was significantly lower on DLR than hybrid-IR and MBIR images and the CNR and the overall visual image quality of the bile duct were significantly higher on DLR than on hybrid-IR and MBIR images (all: p < 0.001).

CONCLUSION

DLR resulted in significant quantitative and qualitative improvement of DIC acquired with U-HRCT.

Pseudo-random Trajectory Scanning Suppresses Motion Artifacts on Gadoxetic Acid-enhanced Hepatobiliary-phase Magnetic Resonance Images

Purpose:

Hepatobiliary-phase (HBP) MRI with gadoxetic acid facilitates the differentiation between lesions with and without functional hepatocytes. Thus, high-quality HBP images are required for the detection and evaluation of hepatic lesions. However, the long scan time may increase artifacts due to intestinal peristalsis, resulting in the loss of diagnostic information. Pseudo-random acquisition order disperses artifacts into the background. The aim of this study was to investigate the clinical applicability of pseudo-random trajectory scanning for the suppression of motion artifacts on T₁-weighted images including HBP.

Methods:

Our investigation included computer simulation, phantom experiments, and a clinical study. For computer simulation and phantom experiments a region of interest (ROI) was placed on the area with motion artifact and the standard deviation inside the ROI was measured as image noise. For clinical study we subjected 62 patients to gadoxetic acid-enhanced hepatobiliary-phase imaging with a circular- and a pseudo-random trajectory (c-HBP and p-HBP); two radiologists graded the motion artifacts, sharpness of the liver edge, visibility of intrahepatic vessels, and overall image quality using a five-point scale where 1 = unacceptable and 5 = excellent. Differences in the qualitative scores were determined using the two-sided Wilcoxon signed-rank test.

Results:

The image noise was higher on the circular image compared with pseudo-random image (101.0 vs 60.9 on computer simulation image, 91.2 vs 67.7 on axial, 95.5 vs 86.9 on reformatted sagittal image for phantom experiments). For clinical study the score for motion artifacts was significantly higher with p-HBP than c-HBP imaging (left lobe: mean 3.4 vs 3.2, P < 0.01; right lobe: mean 3.6 vs 3.4, P < 0.01) as was the qualitative score for the overall image quality (mean 3.6 vs 3.3, P < 0.01).

Conclusion:

At gadoxetic acid-enhanced hepatobiliary-phase imaging, p-HBP scanning suppressed motion artifacts and yielded better image quality than c-HBP scanning.

Deep Learning Reconstruction at CT: Phantom Study of the Image Characteristics

OBJECTIVES

Noise, commonly encountered on computed tomography (CT) images, can impact diagnostic accuracy. To reduce the image noise, we developed a deep-learning reconstruction (DLR) method that integrates deep convolutional neural networks into image reconstruction. In this phantom study, we compared the image noise characteristics, spatial resolution, and task-based detectability on DLR images and images reconstructed with other state-of-the art techniques.

METHODS

We scanned a phantom harboring cylindrical modules with different contrast on a 320-row detector CT scanner. Phantom images were reconstructed with filtered back projection, hybrid iterative reconstruction, model-based iterative reconstruction, and DLR. The standard deviation of the CT number and the noise power spectrum were calculated for noise characterization. The 10% modulation-transfer function (MTF) level was used to evaluate spatial resolution; task-based detectability was assessed using the model observer method.

RESULTS

On images reconstructed with DLR, the noise was lower than on images subjected to other reconstructions, especially at low radiation dose settings. Noise power spectrum measurements also showed that the noise amplitude was lower, especially for low-frequency components, on DLR images. Based on the MTF, spatial resolution was higher on model-based iterative reconstruction image than DLR image, however, for lower-contrast objects, the MTF on DLR images was comparable to images reconstructed with other methods. The machine observer study showed that at reduced radiation-dose settings, DLR yielded the best detectability.

CONCLUSION

On DLR images, the image noise was lower, and high-contrast spatial resolution and task-based detectability were better than on images reconstructed with other state-of-the art techniques. DLR also outperformed other methods with respect to task-based detectability.

Contrast enhancement on 100- and 120 kVp hepatic CT scans at thin adults in a retrospective cohort study: Bayesian inference of the optimal enhancement probability

PURPOSE

To assess the probability of achieving optimal contrast enhancement in 100 kVp and 120 kVp-protocol on hepatic computed tomography (CT) scans.

MATERIALS AND METHODS

We enrolled 200 patients in a retrospective cohort study. Hundred patients were scanned with 120 kVp setting, and other 100 patients were scanned with 100 kVp setting. We measured the CT number in the abdominal aorta and hepatic parenchyma on unenhanced scans and hepatic arterial phase (HAP)-, and portal venous phase (PVP). The aortic enhancement at HAP and the hepatic parenchymal enhancement at PVP were compared between the two scanning protocols. Bayesian inference was used to assess the probability of achieving optimal contrast enhancement in each protocol.

RESULTS

The Bayesian analysis indicated that when 100 kVp-rotocol was used, the probability of achieving optimal aortic enhancement (>280 HU) was 98.8% ± 0.6%, whereas it was 88.7% ± 2.5% when 120 kVp-protocol was used. Also, the probability of achieving optimal hepatic parenchymal enhancement (>50 HU) was 95.3% ± 1.5%, whereas it was 64.7% ± 3.8% when 120 kVp-protocol was used.

CONCLUSION

Bayesian inference suggested that the post-test probability of optimal contrast enhancement at hepatic dynamic CT was lower under the 120 kVp than the 100 kVp-protocol.

P4760New minimally invasive and tailor-made strategy for cryoballoon ablation in patients with paroxysmal atrial fibrillation

Background

Currently, cryoballoon ablation (CBA) has proven to be highly effective in achieving free from atrial fibrillation (AF), especially paroxysmal AF. However, the optimal freezing protocol for each patient to achieve successful pulmonary vein isolation by only CBA is still uncertain. The aim of this study was to evaluate the clinical implications of a reduction in the freezing duration (<180s) during CBA guided by the time to target temperature.

Methods

From November 2015 to August 2018, 286 consecutive paroxysmal AF patients undergoing CBA were enrolled. We compared 107 patients undergoing a tailor-made CBA procedure (Group A; August 2017-August 2018) to 179 patients with a standard CBA procedure (Group B; November 2015–July 2017). In Group A, the freezing duration was reduced to 150s when the temperature reached ≤−40°C within 40s. Furthermore, we reduced it to 120s when it reached ≤−50°C within 60s. In the other patients, the freezing time was 180s except for excessive freezing over −60°C and/or emergent situations while monitoring the esophageal temperature and for phrenic nerve injury as in Group B.

Results

The baseline clinical characteristics were similar between two groups. In Group A, 89 patients (83%) underwent CBA with a reduction in the freezing time. The rate of having reduction time in left inferior PV (LIPV) and right inferior PV (RIPV) was lower compared with left superior PV (LSPV) and right superior PV (RSPV) (respectively 17%, 29%, 56%, and 63.5%). However, for right inferior PV, in 31 patients having the reduced freezing time, none of them required touch-up ablation. Although the procedure time and frequency of touch-up ablation did not differ between the 2 groups, total freezing time for each PV was significantly shorter in Group A than Group B as shown in figure (LSPV: 164±28s vs. 216±67s; p<0.001, LIPV: 187±44s vs. 218±69s; p<0.001, RSPV: 147±31s vs. 192±51s; p<0.001, RIPV: 180±50 vs. 218±73s; p<0.001). The AF free survival rate during the follow-up period (356±167 days) was similar between the 2 groups (log-rank test, p=0.38). Furthermore, the complication rate was similar 2 groups.

The freezing time for each PV

Conclusion

The safety and efficacy of the new tailor-made CBA strategy were non-inferior to the standard procedure. This study showed that the unnecessary freezing time could be reduced in most of paroxysmal AF patients.

Demonstration of Human Fetal Bone Morphology with MR Imaging: A Preliminary Study

Purpose:

CT is a useful modality for the evaluation of fetal skeletal dysplasia but radiation exposure is unavoidable. The purpose of this study is to compare the usefulness of MRI and CT for evaluating the fetal skeletal shape.

Methods:

This study was approved by our Institutional Review Board. Fetal specimens (n = 14) were scanned on a 3T MRI scanner using our newly-developed sequence. It is based on T2*-weighted imaging (TR, 12 ms; TE for opposed-phase imaging, 6.1 ms, for in-phase imaging, 7.3 ms; flip angle, 40°). The specimens were also scanned on a 320 detector-row CT scanner. Four radiologists visually graded and compared the visibility of the bone shape of eight regions on MRI- and CT-scans using a 5-point grading system.

Results:

The diagnostic ability of MRI with respect to the 5th metacarpals, femur, fibula, and pelvis was superior to CT (all, P < 0.050); there was no significant difference in the evaluation results of observers with respect to the cervical and lumbar spine, and the 5th metatarsal (0.058 ≤ P ≤ 1.000). However, the diagnostic ability of MRI was significantly inferior to CT for the assessment of the bone shape of the thoracic spine (observers A and C: P = 0.002, observers B and D: P = 0.001).

Conclusion:

The MRI method we developed represents a potential alternative to CT imaging for the evaluation of the fetal bone structure.

Deep Learning-based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases

Purpose

To evaluate the effect of a deep learning-based reconstruction (DLR) method on the conspicuity of hypovascular hepatic metastases on abdominal CT images.

Materials and Methods

This retrospective study with institutional review board approval included 58 patients with hypovascular hepatic metastases. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise and the contrast-to-noise ratio (CNR). CNR was calculated as region of interest ([ROI]_L - ROI_T)/N, where ROI_L is the mean liver parenchyma attenuation, ROI_T, the mean tumor attenuation, and N, the noise. Two other radiologists graded the conspicuity of the liver lesion on a five-point scale where 1 is unidentifiable and 5 is detected without diagnostic compromise. Only the smallest liver lesion in each patient, classified as smaller or larger than 10 mm, was evaluated. The difference between hybrid iterative reconstruction (IR) and DLR images was determined by using a two-sided Wilcoxon signed-rank test.

Results

The image noise was significantly lower, and the CNR was significantly higher on DLR images than hybrid IR images (median image noise: 19.2 vs 12.8 HU, P < .001; median CNR: tumors < 10 mm: 1.9 vs 2.5; tumors > 10 mm: 1.7 vs 2.2, both P < .001). The scores for liver lesions were significantly higher for DLR images than hybrid IR images (P < .01 for both in tumors smaller or larger than 10 mm).

Conclusion

DLR improved the quality of abdominal CT images for the evaluation of hypovascular hepatic metastases.© RSNA, 2019Supplemental material is available for this article.

P2694Early and late restenosis after excimer laser coronary angioplasty and paclitaxel-coated balloon combination therapy for drug-eluting stent restenosis

Background

Drug-eluting stent restenosis (DES-ISR) is associated with poorer outcomes than those of bare-metal stent restenosis after treatment with paclitaxel-coated balloon (PCB), and late restenosis after PCB angioplasty for DES-ISR is a residual problem. Excimer laser coronary angioplasty (ELCA) is thought to be advantageous for ISR treatment by removing neointima. However, whether the combination of ELCA and PCB angioplasty is more effective than the use of PCB only angioplasty in DES-ISR has not been studied so far.

Purpose

We evaluated the efficacy of ELCA and PCB combination therapy for DES-ISR at mid-and late-term after revascularization.

Methods

From January 2014 to March 2016, 166 DES-ISR lesions were treated with ELCA and no-ELCA prior to PCB. Two serial angiographic follow-ups were planned for the patients (at 6–12 and 18–24 months after procedure). Acute procedural and follow-up angiographic results were assessed by quantitative coronary angiography. ELCA and no-ELCA group included 74 lesions and 92 lesions, respectively.

Results

There was no significant difference between the two groups in the clinical characteristics except the prevalence of hemodialysis, the rate of first-generation DES (37.9% vs 36.8%, p=0.897), previous stent size (2.90±0.39 mm vs 2.77±0.39 mm, p=0.063), and reference vessel diameter (2.65±0.46 mm vs 2.60±0.65 mm, p=0.593). Early follow-up angiography was performed in 66 lesions (89.1%) of ELCA group, and was done in 76 lesions (82.6%) of no-ELCA group. In the ELCA group, percentage diameter stenosis (%DS) just after procedure and at 6–12 months later were significantly smaller than those of no-ELCA group. Besides, target lesion revascularization (TLR) rate at 6–12 months after procedure was tended to be lower in the ELCA group. Late follow-up angiography was performed for 93 lesions (81.6%) of the remaining 114 lesions (excluding TLR lesion), late restenosis was found 9 lesions (18.6%) in the ELCA group and 11 lesions (24.4%) in the no-ELCA group (p=0.504). Late luminal loss was similar in both groups (0.37±0.71 mm vs 0.24±0.82 mm, p=0.438), and %DS at 12–18 months after revascularization was not different between the two groups.

Changes of %DS and TLR rate

Conclusions

%DS in the ELCA group was smaller at just after procedure and the advantage was kept even after 1-year. However, late restenosis and TLR at 2-year after revascularization for DES-ISR could not be reduced by ELCA and PCB combination therapy.

Evaluation of raw-data-based and calculated electron density for contrast media with a dual-energy CT technique

Objectives

The aim of the current study is to evaluate the accuracy and the precision of raw-data-based relative electron density (RED_raw) and the calibration-based RED (RED_cal) at a range of low-RED to high-RED for tissue-equivalent phantom materials by comparing them with reference RED (RED_ref) and to present the difference of RED_raw and RED_cal for the contrast medium using dual-energy CT (DECT).

Methods

The RED_raw images were reconstructed by raw-data-based decomposition using DECT. For evaluation of the accuracy of the RED_raw, RED_ref was calculated for the tissue-equivalent phantom materials based on their specified density and elemental composition. The RED_cal images were calculated using three models: Lung-Bone model, Lung-Ti model and Lung-Ti (SEMAR) model which used single-energy metal artifact reduction (SEMAR). The difference between RED_raw and RED_cal was calculated.

Results

In the titanium rod core, the deviations of RED_raw and RED_cal (Lung-Bone model, Lung-Ti model and Lung-Ti model with SEMAR) from RED_ref were 0.45%, 50.8%, 15.4% and 15.0%, respectively. The largest differences between RED_raw and RED_cal (Lung-Bone model, Lung-Ti model and Lung-Ti model with SEMAR) in the contrast medium phantom were 8.2%, -23.7%, and 28.7%, respectively. However, the differences between RED_raw and RED_cal values were within 10% at 20 mg/ml. The standard deviation of the RED_raw was significantly smaller than the RED_cal with three models in the titanium and the materials that had low CT numbers.

Conclusion

The RED_cal values could be affected by beam hardening artifacts and the RED_cal was less accurate than RED_raw for high-Z materials as titanium.

Advances in knowledge

The raw-data-based reconstruction method could reduce the beam hardening artifact compared with image-based reconstruction and increase the accuracy for the RED estimation in high-Z materials, such as titanium and iodinated contrast medium.

Clinical staging of upper urinary tract urothelial carcinoma for T staging: Review and pictorial essay

Upper urinary tract urothelial carcinoma is staged using the TNM classification of malignant tumors. Preoperative TNM is important for treatment planning. Computed tomography urography is now widely used for clinical survey of upper urinary tract carcinoma because of its diagnostic accuracy. Computed tomography urography is recommended as the first-line imaging procedure in several guidelines. Several reports stated that computed tomography urography is also useful for staging. However, no educational and practical reviews detailing the T staging of upper urinary tract urothelial carcinomas using imaging are available. We discuss the scanning protocol, T staging using computed tomography urography, limitations, magnetic resonance imaging, computed tomography comparison and pitfalls in imaging of upper urinary tract urothelial carcinoma. A recent study reported the high diagnostic accuracy of computed tomography urography with respect to T3 or higher stage tumors. To date, images that show a Tis-T2 stage have not been reported, but various studies are ongoing. Although magnetic resonance imaging has lower spatial resolution than computed tomography urography, magnetic resonance imaging can be carried out without radiation exposure or contrast agents. Magnetic resonance imaging also offers the unique ability of diffusion-weighted imaging without contrast agent use. Some researchers reported that diffusion-weighted imaging is useful not only for detecting lesions, but for predicting the T stage and tumor grade. We recommend the appropriate use of computed tomography and magnetic resonance while considering the limitations of each modality and the pitfalls in upper urinary tract urothelial carcinoma imaging.

Metal artifact reduction techniques for single energy CT and dual-energy CT with various metal materials

Objective:

The aim of the current study is to evaluate the effectiveness of reduction metal artifacts using kV-CT image with the single-energy based metal artefact reduction (SEMAR) technique by single-energy reconstruction, monochromatic CT and rED reconstructed by dual-energy reconstruction.

Methods:

Seven different metal materials (brass, aluminum, copper, stainless, steel, lead and titanium) were placed inside the water-based PMMA phantom. After DECT-based scan, the artefact index (AI) were evaluated with the kV-CT images with and without SEMAR by single-energy reconstruction, and raw-data based electron density (rED), monochromatic CT images by dual-energy reconstruction. Moreover, the AI with evaluated with rED and the converted ED images from the kV-CT and monochromatic CT images.

Results:

The minimum average value of the AI with all-metal inserts was approximately 80 keV. The AI without SEMAR was larger than that with SEMAR for the 80 kV and 135 kV CT images. In the comparison of the AI for the rED and ED images that were converted from 80 kV and 135 kV CT images with and without SEMAR, the monochromatic CT images of the PMMA phantom with inserted metal materials at 80 keV revealed that the kV-CT with SEMAR reduced the metal artefact substantially.

Conclusion:

The converted ED from the kV-CT and monochromatic CT images could be useful for a comparison of the AI using the same contrast scale. The kV-CT image with SEMAR by single-energy reconstruction was found to substantially reduce metal artefact.

Advances in knowledge:

The effectiveness of reduction of metal artifacts using single-energy based metal artefact reduction (SEMAR) technique and dual-energy CT (DECT) was evaluated the electron density conversion techniques.

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

OBJECTIVES

Deep learning reconstruction (DLR) is a new reconstruction method; it introduces deep convolutional neural networks into the reconstruction flow. This study was conducted in order to examine the clinical applicability of abdominal ultra-high-resolution CT (U-HRCT) exams reconstructed with a new DLR in comparison to hybrid and model-based iterative reconstruction (hybrid-IR, MBIR).

METHODS

Our retrospective study included 46 patients seen between December 2017 and April 2018. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise and calculated the contrast-to-noise ratio (CNR) for the aorta, portal vein, and liver. The overall image quality was assessed by two other radiologists and graded on a 5-point confidence scale ranging from 1 (unacceptable) to 5 (excellent). The difference between CT images subjected to hybrid-IR, MBIR, and DLR was compared.

RESULTS

The image noise was significantly lower and the CNR was significantly higher on DLR than hybrid-IR and MBIR images (p < 0.01). DLR images received the highest and MBIR images the lowest scores for overall image quality.

CONCLUSIONS

DLR improved the quality of abdominal U-HRCT images.

KEY POINTS

• The potential degradation due to increased noise may prevent implementation of ultra-high-resolution CT in the abdomen. • Image noise and overall image quality for hepatic ultra-high-resolution CT images improved with deep learning reconstruction as compared to hybrid- and model-based iterative reconstruction.

Deep learning-based image restoration algorithm for coronary CT angiography

OBJECTIVES

The purpose of this study was to compare the image quality of coronary computed tomography angiography (CTA) subjected to deep learning-based image restoration (DLR) method with images subjected to hybrid iterative reconstruction (IR).

METHODS

We enrolled 30 patients (22 men, 8 women) who underwent coronary CTA on a 320-slice CT scanner. The images were reconstructed with hybrid IR and with DLR. The image noise in the ascending aorta, left atrium, and septal wall of the ventricle was measured on all images and the contrast-to-noise ratio (CNR) in the proximal coronary arteries was calculated. We also generated CT attenuation profiles across the proximal coronary arteries and measured the width of the edge rise distance (ERD) and the edge rise slope (ERS). Two observers visually evaluated the overall image quality using a 4-point scale (1 = poor, 4 = excellent).

RESULTS

On DLR images, the mean image noise was lower than that on hybrid IR images (18.5 ± 2.8 HU vs. 23.0 ± 4.6 HU, p < 0.01) and the CNR was significantly higher (p < 0.01). The mean ERD was significantly shorter on DLR than on hybrid IR images, whereas the mean ERS was steeper on DLR than on hybrid IR images. The mean image quality score for hybrid IR and DLR images was 2.96 and 3.58, respectively (p < 0.01).

CONCLUSIONS

DLR reduces the image noise and improves the image quality at coronary CTA.

KEY POINTS

• Deep learning-based image restoration is a new technique that employs the deep convolutional neural network for image quality improvement. • Deep learning-based restoration reduces the image noise and improves image quality at coronary CT angiography. • This method may allow for a reduction in radiation exposure.

Effect of Patient Characteristics on Vessel Enhancement in Pediatric Chest Computed Tomography Angiography

INTRODUCTION

To evaluate the effect of sex, age, height, cardiac output (CO), total body weight (TBW), body surface area (BSA), and lean body weight (LBW) on vessel enhancement of the ascending aorta in pediatric chest computed tomography angiography (c-CTA).

MATERIALS AND METHODS

This retrospective study received institutional review board approval; parental prior informed consent for inclusion was obtained for all patients. All 50 patients were examined using our routine protocol; iodine (600 mg/kg) was the contrast medium (CM). Unenhanced and contrast-enhanced scans were obtained. We calculated the CM volume per vessel enhancement and performed univariate and multivariate linear regression analysis of the relationship between CM volume per vessel enhancement and each of the body parameters.

RESULTS

All patient characteristics were significantly related to CM volume per vessel enhancement (P < .05). Multivariate linear regression analysis revealed a significant correlation between CM volume per vessel enhancement and TBW, BSA, and LBW, but not the patient sex, age, CO, and height. The LBW model for CM volume per vessel enhancement yielded the highest determination coefficient (R² = .913) and the lowest Akaike Information Criterion (400.324).

CONCLUSIONS

Our findings support the delivery of an iodine dose adjusted to the LBW at c-CTA.

Minimizing individual variations in arterial enhancement on coronary CT angiographs using "contrast enhancement optimizer": a prospective randomized single-center study

OBJECTIVES

To investigate the clinical utility of our newly developed contrast enhancement optimizer (CEO) software for coronary CT angiography (CCTA).

METHODS

We randomly assigned 295 patients (168 males, 127 females, median age 71 years) undergoing CCTA to one of two contrast media injection protocols. Group A (n = 150) was injected with a CEO-selected iodine dose based on patient factors. In group B (n = 145), we used our standard protocol (245 mg I/kg). We recorded the CT number in the ascending aorta and determined whether the CT number was equivalent in groups A and B. For the equivalence test, we adopted 75 Hounsfield units (HU) as the equivalence margin. The standard deviation in the CT number and the rate of patients with an acceptable CT number were compared using the F test and the chi-square test, respectively.

RESULTS

The iodine dose in group A was significantly smaller than that in group B (235.7 vs. 253.6 mg I/kg, p < 0.001). The CT number of the ascending aorta was 428.6 ± 55.5 HU in group A and 436.1 ± 68.7 HU in group B; the 95% confidence interval for the difference between the groups was -4.3 HU to 16.9 HU and within the range of the predetermined equivalence margins. In group A, the variance was significantly smaller than that in group B (p = 0.009). The number of patients with an acceptable CT number was significantly higher in group A than in group B (84.7% vs. 71.7%, p = 0.007).

CONCLUSIONS

The use of our CEO for CCTA studies yielded optimal aortic contrast enhancement in significantly more patients than the standard protocol based on the body weight.

KEY POINTS

• With our contrast enhancement optimizer (CEO) software, optimal and stable aortic enhancement can be obtained on coronary CT angiography scans irrespective of patient factors. • Management of contrast media becomes more appropriate by the CEO software. • The CEO software can control contrast enhancement at different tube voltage levels.

Development and Validation of Generalized Linear Regression Models to Predict Vessel Enhancement on Coronary CT Angiography

Objective

We evaluated the effect of various patient characteristics and time-density curve (TDC)-factors on the test bolus-affected vessel enhancement on coronary computed tomography angiography (CCTA). We also assessed the value of generalized linear regression models (GLMs) for predicting enhancement on CCTA.

Materials and Methods

We performed univariate and multivariate regression analysis to evaluate the effect of patient characteristics and to compare contrast enhancement per gram of iodine on test bolus (ΔHUTEST) and CCTA (ΔHUCCTA). We developed GLMs to predict ΔHUCCTA. GLMs including independent variables were validated with 6-fold cross-validation using the correlation coefficient and Bland–Altman analysis.

Results

In multivariate analysis, only total body weight (TBW) and ΔHUTEST maintained their independent predictive value (p < 0.001). In validation analysis, the highest correlation coefficient between ΔHUCCTA and the prediction values was seen in the GLM (r = 0.75), followed by TDC (r = 0.69) and TBW (r = 0.62). The lowest Bland–Altman limit of agreement was observed with GLM-3 (mean difference, −0.0 ± 5.1 Hounsfield units/grams of iodine [HU/gI]; 95% confidence interval [CI], −10.1, 10.1), followed by ΔHUCCTA (−0.0 ± 5.9 HU/gI; 95% CI, −11.9, 11.9) and TBW (1.1 ± 6.2 HU/gI; 95% CI, −11.2, 13.4).

Conclusion

We demonstrated that the patient's TBW and ΔHUTEST significantly affected contrast enhancement on CCTA images and that the combined use of clinical information and test bolus results is useful for predicting aortic enhancement.

Improved differentiation between high- and low-grade gliomas by combining dual-energy CT analysis and perfusion CT

The purpose of this study was to investigate the value of the cerebral blood volume (CBV) obtained with perfusion computed tomography (CT) and the electron density (ED) measured by dual-energy CT for differentiating high- from low-grade glioma (HGG, LGG).The CBV and ED were obtained in 9 LGG and 7 HGG patients. The CBV and ED of LGGs and HGGs were compared. Receiver operating characteristic (ROC) curves were generated for CBV, ED, and CBV plus ED. The correlation between CBV, ED, and the MIB-1 labeling index of the tumors was examined. All of these analyses were also performed using relative CBV (rCBV) and ED (rED) (the value of tumors/the value of contralateral white matter).The mean CBV, ED, rCBV, and rED values were significantly higher in HGG than LGG (P < .05). By ROC analysis, the combination of rCBV plus rED as well as CBV plus ED were more accurate than CBV, ED, rCBV, rED alone. There was a significant correlation between ED and MIB-1 (P = .04).ED improved diagnostic accuracy of perfusion CT for differentiating HGG from LGG.

How to Improve the Conspicuity of Breast Tumors on Computed High b-value Diffusion-weighted Imaging

PURPOSE

The aim of this study was to compare the tumor conspicuity on actual measured diffusion-weighted images (aDWIs) and computed DWI (cDWI) of human breast tumors and to examine, by use of a phantom, whether cDWI improves their conspicuity.

MATERIALS AND METHODS

We acquired DWIs (b-value 0, 700, 1400, 2100, 2800, and 3500 s/mm²) of 148 women with breast tumors. cDWIs with b-values of 1400, 2100, 2800, and 3500 s/mm² were calculated from aDWI scans where b = 0 and 700 s/mm²; the tumor signal-to-noise ratio (SNR) was compared at each b-value. We also subjected a phantom harboring a breast tumor and mammary glands to DWI. For reference we used two models. The model with b = 0, 1000, 1500, 2000, 2500, and 3000 s/mm² was our multiple b-value model. In the single b-value model, we applied b = 0 and 1000 s/mm² and changed the number of excitations (NEX). cDWIs were generated at b = 0 and 1000 and used to compare the SNR, the contrast ratio (CR), and the contrast-to-noise ratio (CNR).

RESULTS

In the phantom study, the CNR of cDWI generated from high SNR images obtained at lower b-values and a high NEX was outperformed aDWI. However, the CR and CNR on cDWI obtained using the same scanning parameters were inferior to aDWI scans. Similarly, in the clinical study, breast tumor conspicuity was worse on high b-value cDWIs than aDWIs.

CONCLUSION

To improve tumor conspicuity on cDWI, the quality of the source images must be improved. It may easily cause inferior conspicuity to aDWIs if high b-value cDWIs were generated from insufficient SNR images.

Automatic contrast medium extraction system using electron density data with dual-energy CT

OBJECTIVE:

The purpose of the current study is to create a contrast medium extraction method using raw-data-based electron density (rED) and CT number from dual-energy CT (DECT) for automatic delineation of the contrast region.

METHODS:

A CT-ED phantom containing tissue-equivalent inserts and an acrylic phantom with an iodinated contrast medium were scanned by DECT. The contrast medium extraction system was created using Python. The accuracy of the contrast medium extraction was evaluated by measuring the diameter in terms of the full width at half maximum (FWHM) and the ratio of the volume (ROV).

RESULTS:

Mean-2SD CT numbers and the difference of the CT numbers (DCT) of the contrast medium at 0-130 mg ml^-1 contrast medium concentration and the bone materials were more than -33 and -20 HU, respectively. In the correlation of rED and CT number, the gradient with the contrast medium phantom was greater than that with the CT-ED phantom. The accuracy of the contrast medium at 80 kV/135 kV and 100 kV/135 kV tube voltages. The gradient of the CT-ED and contrast medium phantoms were different. The gradient in the CT-ED phantom and the contrast medium was 0.0012 and 0.0003 at 80 kV/135 kV, and 0.0015 and 0.0005 at 100 kV/135 kV tube voltages, respectively. The ratio of the measured to the actual diameter in FWHM and ROV was 0.98-1.00 at 2-130 mg ml^-1. At a tube voltage of 100 kV/135 kV. The ratio of the measured to the actual diameter in ROV was 0.66 and FWHM was 0.90 at 2 mg ml^-1 contrast medium concentration. The ratio of the measured to the actual diameter in FWHM and ROV was 0.98-1.00 at 3-130 mg ml^-1.

CONCLUSION:

We created the contrast medium extraction method with rED and CT number images. The contrast medium extraction method could be used with DECT images at 80 kV/135 kV. The method is expected to only extract images from the region containing the contrast medium.

ADVANCES IN KNOWLEDGE:

We created the contrast medium extraction method using raw-data-based electron density and CT number from DECT and it is expected to only extract information from the region containing the contrast medium.

Neointimal formation after carotid artery stenting: phantom and clinical evaluation of model-based iterative reconstruction (MBIR)

OBJECTIVES

The objective of this study was to investigate the usefulness of model-based iterative reconstruction (IR) for detecting neointimal formations after carotid artery stenting.

METHODS

In a cervical phantom harbouring carotid artery stents, we placed simulated neointimal formations measuring 0.40, 0.60, 0.80 and 1.00 mm along the stent wall. The thickness of in-stent neointimal formations was measured on images reconstructed with filtered-back projection (FBP), hybrid IR (AIDR 3D), and model-based IR (FIRST). The clinical study included 43 patients with carotid stents. Cervical computed tomography (CT) images obtained on a 320-slice scanner were reconstructed with AIDR 3D and FIRST. Five blinded observers visually graded the likelihood of neointimal formations on AIDR 3D and AIDR 3D plus FIRST images. Carotid ultrasound images were the reference standard. We analysed results of visual grading by using a Jack-knife type receiver observer characteristics analysis software.

RESULTS

In the phantom study, the difference between the measured and the true diameter of the neointimal formations was smaller on FIRST than FBP or AIDR 3D images. In the clinical study, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of AIDR 3D were 58%, 88%, 83%, 67% and 73%, respectively. For AIDR 3D plus FIRST images they were 84%, 78%, 80%, 82% and 81%, respectively. The mean area under the curve was significantly higher on AIDR 3D plus FIRST than AIDR 3D images (0.82 vs 0.72; p < 0.01).

CONCLUSIONS

The model-based IR algorithm helped to improve diagnostic performance for the detection of neointimal formations after carotid artery stenting.

KEY POINTS

• Neointimal formations can be visualised more accurately with model-based IR. • Model-based IR improves the detection of neointimal formations after carotid artery stenting. • Model-based IR is suitable for follow up after carotid artery stenting.

Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography

Objective

To evaluate the effect of patient characteristics on popliteal aortic contrast enhancement at lower extremity CT angiography (LE-CTA) scanning.

Materials and Methods

Prior informed consent to participate was obtained from all 158 patients. All were examined using a routine protocol; the scanning parameters were tube voltage 100 kVp, tube current 100 mA to 770 mA (noise index 12), 0.5-second rotation, 1.25-mm detector row width, 0.516 beam pitch, and 41.2-mm table movement, and the contrast material was 85.0 mL. Cardiac output (CO) was measured with a portable electrical velocimeter within 5 minutes of starting the CT scan. To evaluate the effects of age, sex, body size, CO, and scan delay on the CT number of popliteal artery, the researchers used multivariate regression analysis.

Results

A significant positive correlation was seen between the CT number of the popliteal artery and the patient age (r = 0.39, p < 0.01). A significant inverse correlation was observed between the CT number of the popliteal artery and the height (r = −0.48), total body weight (r = −0.52), body mass index (r = −0.33), body surface area (BSA) (r = −0.56), lean body weight (r = −0.56), and CO (r = −0.35) (p < 0.001 for all). There was no significant correlation between the enhancement and the scan delay (r = 0.06, p = 0.47). The BSA, CO, and age had significant effects on the CT number (standardized regression: BSA −0.42, CO −0.22, age 0.15; p < 0.05, respectively).

Conclusion

The BSA, CO, and age are significantly correlated with the CT number of the popliteal artery on LE-CTA.

Effect of contrast material injection duration on arterial enhancement at CT in patients with various cardiac indices: Analysis using computer simulation

Arterial peak enhancement on contrast-enhanced CT (CECT) images is thought to be higher in patients with low cardiac function. Using computer simulations, we tested the hypothesis that the relationship between the cardiac index and the aortic peak CT number (PCTN) is affected by the contrast material (CM) injection duration. We created computer simulation software for the contrast enhancement of various organs and vessels based on the Bae pharmacokinetics model and implemented models for CM transmission within organs and CM diffusion in blood plasma based on the osmotic pressure. Aortic contrast enhancement at coronary- and abdominal CT angiographs (CTA) was simulated for a representative 60-year-old Japanese male 166 cm in height and 65.0 kg in weight. The injection protocol for coronary CTA was: CM dose 45.5 ml, iodine dose, 245 mg/kg body weight (BW); injection duration 8–20 sec in 2-sec increments. For abdominal CTA it was CM dose 74.3 ml; iodine dose 400 mg/kg BW; injection duration 10–40 sec in 5-sec increments. In both protocols the iodine concentration was 350 mgI/ml, osmotic pressure was 590 mOsm/kgH₂O, and the cardiac index ranged from 0.1–6.0 l/min/m². Under all protocols, the aortic PCTN increased as the injection duration decreased and as the cardiac index rose to the cardiac index value. It then decreased as it exceeded the cardiac index value. At coronary CTA, at an injection duration of 8 or 10 sec, the PCTN exceeded 350 Hounsfield units (HU) at a cardiac index from 0.9–5.6 l/min/m². At an HU value greater than 350, the range of the cardiac index narrowed when the injection duration was 12 sec or longer. On abdominal CTA scans performed with an injection duration of 10-, 15-, or 20 sec, the PCTN exceeded 350 HU at a cardiac index ranging from 0.4–5.3 l/min/m². When the injection duration ranged from 25–40 sec, there was narrowing of the range of the cardiac index at which the PCTN exceeded 350 HU. For coronary and abdominal CTA, contrast enhancement protocols with shorter injection durations yield a diagnostically adequate aortic PCTN at a wide range of cardiac indices.

Accuracy of the raw-data-based effective atomic numbers and monochromatic CT numbers for contrast medium with a dual-energy CT technique

OBJECTIVE

To evaluate the accuracy of raw-data-based effective atomic number (Z_eff) values and monochromatic CT numbers for contrast material of varying iodine concentrations, obtained using dual-energy CT.

METHODS

We used a tissue characterization phantom and varying concentrations of iodinated contrast medium. A comparison between the theoretical values of Z_eff and that provided by the manufacturer was performed. The measured and theoretical monochromatic CT numbers at 40-130 keV were compared.

RESULTS

The average difference between the Z_eff values of lung (inhale) inserts in the tissue characterization phantom was 81.3% and the average Z_eff difference was within 8.4%. The average difference between the Z_eff values of the varying concentrations of iodinated contrast medium was within 11.2%. For the varying concentrations of iodinated contrast medium, the differences between the measured and theoretical monochromatic CT values increased with decreasing monochromatic energy. The Z_eff and monochromatic CT numbers in the tissue characterization phantom were reasonably accurate.

CONCLUSION

The accuracy of the raw-data-based Z_eff values was higher than that of image-based Z_eff values in the tissue-equivalent phantom. The accuracy of Z_eff values in the contrast medium was in good agreement within the maximum SD found in the iodine concentration range of clinical dynamic CT imaging. Moreover, the optimum monochromatic energy for human tissue and iodinated contrast medium was found to be 70 keV. Advances in knowledge: The accuracy of the Z_eff values and monochromatic CT numbers of the contrast medium created by raw-data-based, dual-energy CT could be sufficient in clinical conditions.

Hepatocellular carcinoma treated with sorafenib: Arterial tumor perfusion in dynamic contrast-enhanced CT as early imaging biomarkers for survival

OBJECTIVES

To investigate whether hepatic perfusion CT yields early imaging biomarkers predictive of the prognosis of hepatocellular carcinoma (HCC) patients treated with sorafenib.

METHODS

We evaluated 36 HCC patients who underwent hepatic perfusion CT before- and one week after sorafenib therapy. We measured arterial and portal perfusion in the hepatic tumor and liver parenchyma [(AP)(PP)_tumor], [(AP)(PP)_liver]. The perfusion ratio was calculated by dividing the post- by the pre-sorafenib value. The effect of each value on the overall survival rate was analyzed with the Cox proportional hazards model; statistically significant parameters were subjected to receiver operating characteristic analysis based on median survival after sorafenib administration to determine the overall survival rate with the Kaplan-Meier method.

RESULTS

Pre-AP_tumor was significantly associated with the overall survival rate (hazard ratio (HR) and 95% confidence interval (CI), 0.16 and 0.02-0.84, p=0.03). The AP_tumor ratio tended to be associated with the overall survival rate (HR and 95% CI, 2.94 and 0.94-7.88, p=0.06). The overall survival rate was higher in patients with pre-AP_tumor>71.7mL/min/100mL, and with AP_tumor ratio≦1.1 (p<0.01 and 0.03, respectively, in Kaplan-Meier method with log-rank).

CONCLUSION

Hepatic perfusion CT yields early imaging biomarkers for predicting overall survival in HCC patients treated with sorafenib.

Diagnostic accuracy of in-stent restenosis using model-based iterative reconstruction at coronary CT angiography: initial experience

OBJECTIVE

The purpose of our study was to compare the diagnostic performance of coronary CT angiography (CTA) subjected to model-based iterative reconstruction (IR) or hybrid IR to rule out coronary in-stent restenosis.

METHODS

We enrolled 16 patients who harboured 22 coronary stents. They underwent coronary CTA on a 320-slice CT scanner. The images were reconstructed with hybrid IR (AIDR 3D) and model-based IR (FIRST) algorithms. We calculated the stent lumen attenuation increase ratio and measured the visible stent lumen diameter. Two blinded observers visually graded the likelihood of in-stent restenosis (lesions ≥ 50%) on hybrid IR and FIRST images.

RESULTS

The stent lumen attenuation increase ratio on FIRST- was lower than on AIDR 3D images (0.20 vs 0.32). The ratio of the visible- compared to the true stent lumen diameter was higher on FIRST- than AIDR 3D images (52.5 vs 47.5%). Invasive coronary angiography identified five stents (22.7%) with significant in-stent restenosis. The use of FIRST improved the sensitivity (60 vs 100%), positive (75.0 vs 83.3%) and negative predictive value (88.9 vs 100%) and the accuracy (86.4 vs 95.5%) for the detection of in-stent restenosis. Specificity was 94.1% for both reconstruction methods.

CONCLUSION

The model-based IR algorithm may improve diagnostic performance for the detection of in-stent restenosis. Advances in knowledge: Compared to hybrid IR, the new model-based IR algorithm reduced blooming artefacts and improved the image quality. It can be expected to improve diagnostic performance for the detection of in-stent restenosis on coronary CTA images.