Myocardial extracellular volume quantification in cardiac amyloidosis: a comparative study between cardiac computed tomography and magnetic resonance imaging.

OBJECTIVES: Myocardial extracellular volume (ECV) on computed tomography (CT), an alternative to cardiac magnetic resonance (CMR), has significant practical clinical advantages. However, the consistency between ECVs quantified via CT and CMR in cardiac amyloidosis (CA) has not been investigated sufficiently. Therefore, the current study investigated the application of CT-ECV in CA with CMR-ECV as the reference standard. METHODS: We retrospectively evaluated 31 patients with CA who underwent cardiac CT and CMR. Pearson correlation analysis was performed to investigate correlations between CT-ECV and CMR-ECV at each segment. Further, correlations between ECV and clinical parameters were assessed. RESULTS: There were no significant differences in the mean global ECVs between CT scan and CMR (51.3% ± 10.2% vs 50.0% ± 10.5%). CT-ECV was correlated with CMR-ECV at the septal (r = 0.88), lateral (r = 0.80), inferior (r = 0.79), anterior (r = 0.77) segments, and global (r = 0.87). In both CT and CMR, the ECV had a weak to strong correlation with high-sensitivity cardiac troponin T level, a moderate correlation with global longitudinal strain, and an inverse correlation with left ventricular ejection fraction. Further, the septal ECV and global ECV had a slightly higher correlation with the clinical parameters. CONCLUSIONS: Cardiac CT can quantify myocardial ECV and yield results comparable to CMR in patients with CA. Moreover, a significant correlation between CT-ECV and clinical parameters was observed. Thus, CT-ECV can be an imaging biomarker and alternative to CMR-ECV. CLINICAL RELEVANCE STATEMENT: Cardiac CT can quantify myocardial ECV and yield results comparable to CMR in patients with CA, and CT-ECV can be used clinically as an imaging biomarker and alternative to CMR-ECV. KEY POINTS: • A significant correlation was found between CT myocardial extracellular volume and cardiac MR myocardial extracellular volume in patients with cardiac amyloidosis. • In CT and cardiac MR, the myocardial extracellular volume correlated well with high-sensitivity cardiac troponin T level, global longitudinal strain, and left ventricular ejection fraction. • CT myocardial extracellular volume can be an imaging biomarker and alternative to cardiac MR myocardial extracellular volume.

Transarterial Embolization of Renal Arteriovenous Malformations: Treatment Outcomes According to Angiographic Classification.

PURPOSE: To assess the different adjunctive catheter techniques required to achieve complete occlusion of renal arteriovenous malformations (rAVMs) of different angioarchitectural types. MATERIALS AND METHODS: Overall, data on 18 patients with rAVM (Type 1, n = 7; Type 2, n = 2; Type 3, n = 9; mean age, 53.8 years) who underwent 25 procedures between 2011 and 2022 were reviewed. The clinical presentations, endovascular techniques, arteriovenous malformation (AVM) occlusion rate, adverse events (including the incidence of renal infarction), and clinical symptoms and outcomes (including recurrence/increase of AVM) were analyzed according to the Cho-Do angioarchitectural classification. Posttreatment renal infarction was classified as no infarction, small infarction (<12.5%), medium infarction (12.5%-25%), and large infarction (>25%) using contrast-enhanced computed tomography or magnetic resonance imaging. RESULTS: Hematuria and heart failure were presenting symptoms in 10 and 2 patients, respectively. The embolic materials used were as follows: Type 1 rAVM, coils alone or with n-butyl-2-cyanoacrylate (nBCA); Type 2 rAVM, nBCA alone or with coils; and Type 3 rAVMs, nBCA alone. Fourteen patients underwent adjunctive catheter techniques, including flow control with a balloon catheter and multiple microcatheter placement, alone or in combination. Immediate postprocedural angiography revealed complete occlusion in 15 patients (83%) and marked regression of rAVM in 3 (17%). Small asymptomatic renal infarctions were observed in 6 patients with Type 3 rAVMs without any decrease in renal function. No major adverse events were observed. All symptomatic patients experienced symptom resolution. Recurrence/increase of rAVM was not observed during the mean 32-month follow-up period (range, 2-120 months). CONCLUSIONS: Transarterial embolization using adjunctive catheter techniques according to angioarchitectural types can be an effective treatment for rAVMs.

A Novel Approach to Detecting Contrast Extravasation in Computed Tomography: Evaluating the Injection Pressure-to-Injection Rate Ratio.

OBJECTIVE: The purpose of this study was to evaluate the usefulness of the injection pressure-to-injection rate (IPIR) ratio for the early detection of contrast extravasation at the venipuncture site during contrast-enhanced computed tomography. METHODS: We retrospectively enrolled 57,528 patients who underwent contrast-enhanced computed tomography examinations in a single hospital. The power injector recorded the contrast injection pressure at 0.25-second intervals. We constructed logistic regression models using the IPIR ratio as the independent variable and extravasation occurrence as the dependent variable (IPIR ratio models) at 1, 2, 3, 4, 5, and 6 seconds after the start of contrast administration. Univariate logistic regression models in which injection pressure is used as an independent variable (injection pressure models) were also constructed as a reference baseline. The performance of the models was evaluated with the area under the receiver operating characteristic curves. RESULTS: Of the 57,528 cases, 46,022 were assigned to the training group and 11,506 were assigned to the test group, which included 112 extravasation cases (0.24%) in the training group and 28 (0.24%) in the test group. The area under the receiver operating characteristic curves for the IPIR ratio models and injection pressure models were 0.555 versus 0.563 at t = 1 (P = 0.270), 0.712 versus 0.678 at t = 2 (P = 0.305), 0.758 versus 0.693 at t = 3 (P = 0.032), 0.776 versus 0.688 at t = 4 (P = 0.005), 0.810 versus 0.699 at t = 5 (P = 0.002), and 0.811 versus 0.706 at t = 6 (P = 0.002). CONCLUSIONS: The IPIR ratio models perform better in detecting contrast extravasation at 3 to 6 seconds after the start of contrast administration than injection pressure models.

CT Extracellular Volume Fraction versus Myocardium-to-Lumen Signal Ratio for Cardiac Amyloidosis.

Background Large studies on the diagnostic performance of CT-derived myocardial extracellular volume fraction (ECV) for detecting cardiac amyloidosis are lacking. A simple and practical index as a surrogate for CT ECV would be clinically useful. Purpose To compare the diagnostic performances between CT-derived myocardial ECV and myocardium-to-lumen signal ratio for the detection of cardiac amyloidosis in a large patient sample. Materials and Methods This retrospective study included patients who underwent CT ECV analysis because of suspected heart failure or cardiomyopathy between January 2018 and July 2021. CT ECV was quantified using routine pre-transcatheter aortic valve replacement planning cardiac CT, pre-atrial fibrillation ablation planning cardiac CT, or coronary CT angiography with the addition of unenhanced and delayed phase cardiac CT scans. The diagnostic performances of CT ECV and myocardium-to-lumen signal ratio in delayed phase cardiac CT (a simplified index not requiring unenhanced CT and hematocrit) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results Of 552 patients (mean age, 69 years ± 14 [SD]; 295 men), 41 had cardiac amyloidosis. The sensitivity of CT ECV for amyloidosis was 90% (37 of 41 patients [95% CI: 77, 97]), with a specificity of 92% (472 of 511 patients [95% CI: 90, 95]) and optimal ECV cutoff value of 37% (AUC, 0.97 [95% CI: 0.96, 0.99]). The sensitivity of myocardium-to-lumen signal ratio was 88% (36 of 41 patients [95% CI: 74, 96]), with a specificity of 92% (469 of 511 patients [95% CI: 89, 94]) and optimal myocardium-to-lumen signal ratio cutoff value of 0.87 (AUC, 0.96 [95% CI: 0.94, 0.97]; P = .27 for comparison with ECV). Conclusion CT-derived myocardial extracellular volume fraction and myocardium-to-lumen signal ratio showed comparable and excellent diagnostic performance in detecting cardiac amyloidosis in a large patient sample. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Williams in this issue.

Improving image quality with super-resolution deep-learning-based reconstruction in coronary CT angiography.

OBJECTIVES: To evaluate the effect of super-resolution deep-learning-based reconstruction (SR-DLR) on the image quality of coronary CT angiography (CCTA). METHODS: Forty-one patients who underwent CCTA using a 320-row scanner were retrospectively included. Images were reconstructed with hybrid (HIR), model-based iterative reconstruction (MBIR), normal-resolution deep-learning-based reconstruction (NR-DLR), and SR-DLR algorithms. For each image series, image noise, and contrast-to-noise ratio (CNR) at the left main trunk, right coronary artery, left anterior descending artery, and left circumflex artery were quantified. Blooming artifacts from calcified plaques were measured. Image sharpness, noise magnitude, noise texture, edge smoothness, overall quality, and delineation of the coronary wall, calcified and noncalcified plaques, cardiac muscle, and valves were subjectively ranked on a 4-point scale (1, worst; 4, best). The quantitative parameters and subjective scores were compared among the four reconstructions. Task-based image quality was assessed with a physical evaluation phantom. The detectability index for the objects simulating the coronary lumen, calcified plaques, and noncalcified plaques was calculated from the noise power spectrum (NPS) and task-based transfer function (TTF). RESULTS: SR-DLR yielded significantly lower image noise and blooming artifacts with higher CNR than HIR, MBIR, and NR-DLR (all p < 0.001). The best subjective scores for all the evaluation criteria were attained with SR-DLR, with significant differences from all other reconstructions (p < 0.001). In the phantom study, SR-DLR provided the highest NPS average frequency, TTF50%, and detectability for all task objects. CONCLUSION: SR-DLR considerably improved the subjective and objective image qualities and object detectability of CCTA relative to HIR, MBIR, and NR-DLR algorithms. CLINICAL RELEVANCE STATEMENT: The novel SR-DLR algorithm has the potential to facilitate accurate assessment of coronary artery disease on CCTA by providing excellent image quality in terms of spatial resolution, noise characteristics, and object detectability. KEY POINTS: • SR-DLR designed for CCTA improved image sharpness, noise property, and delineation of cardiac structures with reduced blooming artifacts from calcified plaques relative to HIR, MBIR, and NR-DLR. • In the task-based image-quality assessments, SR-DLR yielded better spatial resolution, noise property, and detectability for objects simulating the coronary lumen, coronary calcifications, and noncalcified plaques than other reconstruction techniques. • The image reconstruction times of SR-DLR were shorter than those of MBIR, potentially serving as a novel standard-of-care reconstruction technique for CCTA performed on a 320-row CT scanner.

Deep learning-based reconstruction can improve the image quality of low radiation dose head CT.

OBJECTIVES: To evaluate the image quality of deep learning-based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those of standard-dose (STD) HIR images. METHODS: This retrospective study included 114 patients who underwent unenhanced head CT using the STD (n = 57) or LD (n = 57) protocol on a 320-row CT. STD images were reconstructed with HIR; LD images were reconstructed with HIR (LD-HIR), MBIR (LD-MBIR), and DLR (LD-DLR). The image noise, gray and white matter (GM-WM) contrast, and contrast-to-noise ratio (CNR) at the basal ganglia and posterior fossa levels were quantified. The noise magnitude, noise texture, GM-WM contrast, image sharpness, streak artifact, and subjective acceptability were independently scored by three radiologists (1 = worst, 5 = best). The lesion conspicuity of LD-HIR, LD-MBIR, and LD-DLR was ranked through side-by-side assessments (1 = worst, 3 = best). Reconstruction times of three algorithms were measured. RESULTS: The effective dose of LD was 25% lower than that of STD. Lower image noise, higher GM-WM contrast, and higher CNR were observed in LD-DLR and LD-MBIR than those in STD (all, p ≤ 0.035). Compared with STD, the noise texture, image sharpness, and subjective acceptability were inferior for LD-MBIR and superior for LD-DLR (all, p < 0.001). The lesion conspicuity of LD-DLR (2.9 ± 0.2) was higher than that of HIR (1.2 ± 0.3) and MBIR (1.8 ± 0.4) (all, p < 0.001). Reconstruction times of HIR, MBIR, and DLR were 11 ± 1, 319 ± 17, and 24 ± 1 s, respectively. CONCLUSION: DLR can enhance the image quality of head CT while preserving low radiation dose level and short reconstruction time. KEY POINTS: • For unenhanced head CT, DLR reduced the image noise and improved the GM-WM contrast and lesion delineation without sacrificing the natural noise texture and image sharpness relative to HIR. • The subjective and objective image quality of DLR was better than that of HIR even at 25% reduced dose without considerably increasing the image reconstruction times (24 s vs. 11 s). • Despite the strong noise reduction and improved GM-WM contrast performance, MBIR degraded the noise texture, sharpness, and subjective acceptance with prolonged reconstruction times relative to HIR, potentially hampering its feasibility.

Coronary Stent Evaluation by CTA: Image Quality Comparison Between Super-Resolution Deep Learning Reconstruction and Other Reconstruction Algorithms.

BACKGROUND. A super-resolution deep learning reconstruction (SR-DLR) algorithm may provide better image sharpness than earlier reconstruction algorithms and thereby improve coronary stent assessment on coronary CTA. OBJECTIVE. The purpose of our study was to compare SR-DLR and other reconstruction algorithms in terms of image quality measures related to coronary stent evaluation in patients undergoing coronary CTA. METHODS. This retrospective study included patients with at least one coronary artery stent who underwent coronary CTA between January 2020 and December 2020. Examinations were performed using a 320-row normal-resolution scanner and were reconstructed with hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), normal-resolution deep learning reconstruction (NR-DLR), and SR-DLR algorithms. Quantitative image quality measures were determined. Two radiologists independently reviewed images to rank the four reconstructions (4-point scale: 1 = worst reconstruction, 4 = best reconstruction) for qualitative measures and to score diagnostic confidence (5-point scale: score ≥ 3 indicating an assessable stent). The assessability rate was calculated for stents with a diameter of 3.0 mm or less. RESULTS. The sample included 24 patients (18 men, six women; mean age, 72.5 ± 9.8 [SD] years), with 51 stents. SR-DLR, in comparison with the other reconstructions, yielded lower stent-related blooming artifacts (median, 40.3 vs 53.4-58.2), stent-induced attenuation increase ratio (0.17 vs 0.27-0.31), and quantitative image noise (18.1 vs 20.9-30.4 HU) and higher in-stent lumen diameter (2.4 vs 1.7-1.9 mm), stent strut sharpness (327 vs 147-210 ΔHU/mm), and CNR (30.0 vs 16.0-25.6) (all p < .001). For both observers, all ranked measures (image sharpness; image noise; noise texture; delineation of stent strut, in-stent lumen, coronary artery wall, and calcified plaque surrounding the stent) and diagnostic confidence showed a higher score for SR-DLR (median, 4.0 for all features) than for the other reconstructions (range, 1.0-3.0) (all p < .001). The assessability rate for stents with a diameter of 3.0 mm or less (n = 37) was higher for SR-DLR (86.5% for observer 1 and 89.2% for observer 2) than for HIR (35.1% and 43.2%), MBIR (59.5% and 62.2%), and NR-DLR (62.2% and 64.9%) (all p < .05). CONCLUSION. SR-DLR yielded improved delineation of the stent strut and in-stent lumen, with better image sharpness and less image noise and blooming artifacts, in comparison with HIR, MBIR, and NR-DLR. CLINICAL IMPACT. SR-DLR may facilitate coronary stent assessment on a 320-row normal-resolution scanner, particularly for small-diameter stents.

Second Percutaneous Transluminal Angioplasty Versus Surgical Reconstruction for Hemodialysis Access Failure Within a Short Time Period.

BACKGROUND: The purpose of this study was to compare patency and nonabandonment rates for second percutaneous transluminal angioplasty (PTA) and surgical reconstruction for the treatment of failing vascular access due to restenosis or reocclusion in a short time after initial PTA. METHODS: Seventy two consecutive patients who underwent second treatment within 90 days after the initial PTA were evaluated retrospectively. The patency (time to corrective procedure) and access abandonment were compared among patients who underwent a second PTA (n = 35) and those who underwent surgical reconstruction (n = 37). Univariate and multivariate analyses were performed to determine independent predictors of patency and access abandonment at 1 year after the treatment. RESULTS: At 1 year after the treatment, the patency rates were 35.1% and 11.4% (P = 0.02) and nonabandonment rates were 64.9% and 77.1% (P = 0.25) for surgical reconstruction and second PTA, respectively. The Kaplan-Meier survival analysis showed that the surgical reconstruction group had better patency probability (P = 0.02), but there was no difference in the nonabandonment probability between the groups (P = 0.29). Shorter time to retreatment was associated with good patency. The female gender was likely to be associated with access abandonment. CONCLUSIONS: The access abandonment between the 2 procedures had no difference, although surgical reconstruction provided better patency than second PTA.

Radiation Dose Reduction for 80-kVp Pediatric CT Using Deep Learning-Based Reconstruction: A Clinical and Phantom Study.

BACKGROUND. Deep learning-based reconstruction (DLR) may facilitate CT radiation dose reduction, but a paucity of literature has compared lower-dose DLR images with standard-dose iterative reconstruction (IR) images or explored application of DLR to low-tube-voltage scanning in children. OBJECTIVE. The purpose of this study was to assess whether DLR can be used to reduce radiation dose while maintaining diagnostic image quality in comparison with hybrid IR (HIR) and model-based IR (MBIR) for low-tube-voltage pediatric CT. METHODS. This retrospective study included children 6 years old or younger who underwent contrast-enhanced 80-kVp CT with a standard-dose or lower-dose protocol. Standard images were reconstructed with HIR, and lower-dose images were reconstructed with HIR, MBIR, and DLR. Size-specific dose estimate (SSDE) was calculated for both protocols. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantified. Two radiologists independently evaluated noise magnitude, noise texture, streak artifact, edge sharpness, and overall quality. Interreader agreement was assessed, and mean values were calculated. To evaluate task-based object detection performance, a phantom was imaged with 80-kVp CT at six doses (SSDE, 0.6-5.3 mGy). Detectability index (d') was calculated from the noise power spectrum and task-based transfer function. Reconstruction methods were compared. RESULTS. Sixty-five children (mean age, 25.0 ± 25.2 months) who underwent CT with standard- (n = 31) or lower-dose (n = 34) protocol were included. SSDE was 54% lower for the lower-dose than for the standard-dose group (1.9 ± 0.4 vs 4.1 ± 0.8 mGy). Lower-dose DLR and MBIR yielded lower image noise and higher SNR and CNR than standard-dose HIR (p < .05). Interobserver agreement on subjective features ranged from a kappa coefficient of 0.68 to 0.78. The readers subjectively scored noise texture, edge sharpness, and overall quality lower for lower-dose MBIR than for standard-dose HIR (p < .001), though higher for lower-dose DLR than for standard-dose HIR (p < .001). In the phantom, DLR provided higher d' than HIR and MBIR at each dose. Object detectability was greater for 2.0-mGy DLR than for 4.0-mGy HIR for low-contrast (3.67 vs 3.57) and high-contrast (1.20 vs 1.04) objects. CONCLUSION. Compared with IR algorithms, DLR results in substantial dose reduction with preserved or even improved image quality for low-tube-voltage pediatric CT. CLINICAL IMPACT. Use of DLR at 80 kVp allows greater dose reduction for pediatric CT than do current IR techniques.

Extracardiac Biopsy Sensitivity in Transthyretin Amyloidosis Cardiomyopathy Patients With Positive 99 mTc-Labeled Pyrophosphate Scintigraphy Findings.

BACKGROUND: The accurate sensitivity of amyloid deposition in extracardiac tissue (subcutaneous tissue and gastrointestinal tract) has not been evaluated in transthyretin amyloidosis cardiomyopathy (ATTR-CM) patients. This study aimed to evaluate the sensitivity of amyloid deposition in obtained endomyocardial and extracardiac biopsies.Methods and Results: This study retrospectively evaluated 175 consecutive ATTR-CM patients (wild-type [ATTRwt]: 134, hereditary [ATTRv]: 41) who had positive findings on 99 mTc-labeled pyrophosphate (99 mTc-PYP) scintigraphy and underwent tissue biopsy of at least one organ (subcutaneous tissue, gastrointestinal tract, and endomyocardium). Amyloid deposition was observed in the subcutaneous tissue of 57/150 patients (38%), gastrointestinal tract of 80/131 patients (61%), and endomyocardium of 108/109 patients (99%). Compared to patients with ATTRv, ATTRwt had significantly lower sensitivity in subcutaneous tissue (73% vs. 25%, P<0.01) and tended to be lower in the gastrointestinal tract (74% vs. 57%, P=0.08) biopsies. Among 124 patients who underwent both subcutaneous tissue and gastrointestinal tract biopsies, amyloid was detected in at least 1 specimen in 91 (73%) patients. The sensitivity of the combination of extracardiac biopsies was 66% and 94% in ATTRwt-CM and ATTRv-CM, respectively. Multivariate analysis reveals that ATTRv was the only significant predictor of amyloid deposition in the subcutaneous tissue. CONCLUSIONS: Subcutaneous tissue and gastrointestinal tract biopsy sensitivity are inadequate, especially in patients with ATTRwt; however, the combination of these extracardiac biopsies contributes to increased sensitivity in patients with positive 99 mTc-PYP scintigraphy findings.

Evaluating of the Quality of Hepatic Diffusion Weighted Imaging Using Multiband Imaging With Variable-Rate Selective Excitation.

OBJECTIVE: To assess the image quality of diffusion-weighted imaging (DWI) using multiband (MB) imaging with variable-rate selective excitation (VERSE) and compare it to conventional DWI. METHODS: We retrospectively evaluated hepatic DWI images of patients (n = 76) according to either the conventional method (SENSE, acceleration factor = 2) (n = 38) or fast scanning method (MB imaging with VERSE, acceleration factor = 2 × 2) (n = 38). We also conducted a volunteer study (n = 15) for those scanning methods. During quantitative analysis, the signal-to-noise ratio (SNR), apparent diffusion coefficient values, and contrast in the liver, spleen, and spinal cord were compared between the 2 groups. During qualitative analysis, all images were independently and blindly evaluated by 2 board-certified radiologists. The image contrast, noise, artifacts, and sharpness were assessed, and the performance of classification was measured using receiver operating characteristic curve analysis. RESULTS: In the retrospective study, the SNRs of the hepatic parenchyma and spinal cord between the 2 protocols were significantly different (liver, 8.9 [interquartile range {IQR}, 7.6-12.2] vs 13.0 [IQR, 10.0-16.7]; P < 0.001 and spinal cord, 6.0 [IQR, 4.7-9.4] vs 4.3 [IQR, 3.8-6.8]; P < 0.02). No significant differences between the 2 protocols in the other retrospective analyses were noted. In the receiver operating characteristic curve analysis, area under the curve was 0.49 (95% confidence intervals, 0.40-0.58). CONCLUSION: Multiband VERSE reduced scan time and SNR of hepatic DWI; however, subjective image quality parameters were not significantly impacted.

Clinical impact of cerebral infarction in patients with non-small cell lung cancer.

BACKGROUND: Lung cancer patients have a high risk of cerebral infarction, but the clinical significance of cerebral infarction in advanced non-small cell lung cancer (NSCLC) remains unclear. This study aimed to comprehensively investigate the incidence, prognostic impact, and risk factors of cerebral infarction in patients with NSCLC. METHODS: We retrospectively examined 710 consecutive patients with advanced or post-operative recurrent NSCLC treated between January 2010 and July 2020 at Kumamoto University Hospital. Cerebral infarction was diagnosed according to the detection of high-intensity lesions on diffusion-weighted magnetic resonance imaging regardless of the presence of neurological symptoms during the entire course from 3 months before NSCLC diagnosis. The prognostic impact and risk factors of cerebral infarction were evaluated based on propensity score matching (PSM) and multivariate logistic regression analysis. RESULTS: Cerebral infarction occurred in 36 patients (5%). Of them, 21 (58%) and 15 (42%) patients developed asymptomatic and symptomatic cerebral infarction, respectively. PSM analysis for survival showed that cerebral infarction was an independent prognostic factor (hazards ratio: 2.45, 95% confidence interval (CI): 1.24-4.85, P = 0.010). On multivariate logistic regression analysis, D-dimer (odds ratio [OR]: 1.09, 95% CI 1.05-1.14, P < 0.001) and C-reactive protein (OR: 1.10, 95% CI 1.01-1.19, P = 0.023) levels were independent risk factors. CONCLUSION: Cerebral infarction occurred in 5% of NSCLC patients, and asymptomatic cerebral infarction was more frequent. Cerebral infarction was a negative prognostic factor and was associated with hyper-coagulation and inflammation. The high frequency of asymptomatic cerebral infarction and its risk in NSCLC patients with these conditions should be recognized.

Effect of image quality on myocardial extracellular volume quantification using cardiac computed tomography: a phantom study.

BACKGROUND: The image quality directly affects the accuracy of computed tomography (CT) extracellular volume (ECV) quantification. PURPOSE: To investigate the effects of image quality and acquisition protocol on the accuracy of ECV quantification. MATERIAL AND METHODS: One-volume scans were performed on a 320-row multidetector CT volume scanner using a multi-energy CT phantom. To simulate the blood pool and myocardium, solid rods representing blood and soft tissue were used in precontrast CT. Moreover, the solid rods including different iodine concentrations were used in postcontrast CT. The tube voltage was set at 120 kVp, and the tube current was changed from 750 mA (100% dose) to 190 mA (25% dose). All images underwent full- and half-scan reconstructions based on model-based iterative reconstruction. The ECV was calculated from the CT numbers between pre- and postcontrast. RESULTS: The mean ECV with full- and half-scan reconstructions at the central portion was 0.275 at 100% scan dose to 0.271 at 25% scan dose and 0.276 at 100% scan dose to 0.269 at 25% scan dose. Compared with that in the 100% scan dose, the variation in each ECV increased with decreasing radiation dose. The ECV at the center of the image along the z-axis had lower variation than that at outer portion of the images. On the reconstruction algorithm, there was no statistical difference in ECVs with full- and half-scan reconstructions. CONCLUSION: For stable ECV quantifications, excessive radiation dose reduction may be inappropriate, and it is better to consider the variations in ECV values depending on the slice location.

Effects of tube voltage and iodine contrast medium on radiation dose of whole-body CT.

BACKGROUND: The low-tube-voltage scan generally needs a higher tube current than the conventional 120 kVp to maintain the image noise. In addition, the low-tube-voltage scan increases the photoelectric effect, which increases the radiation absorption in organs. PURPOSE: To compare the organ radiation dose caused by iodine contrast medium between low tube voltage with low contrast medium and that of conventional 120-kVp protocol with standard contrast medium. MATERIAL AND METHODS: After the propensity-matching analysis, 66 patients were enrolled including 33 patients with 120 kVp and 600 mgI/kg and 33 patients with 80 kVp and 300 mgI/kg (50% iodine reduction). The pre- and post-contrast phases were assessed in all patients. The Monte Carlo simulation tool was used to simulate the radiation dose. The computed tomography (CT) numbers for 10 organs and the organ doses were measured. The organ doses were normalized by the volume CT dose index, and the 120-kVp protocol was compared with the 80-kVp protocol. RESULTS: On contrast-enhanced CT, there were no significant differences in the mean CT numbers of the organs between 80-kVp and 120-kVp protocols except for the pancreas, kidneys, and small intestine. The normalized organ doses at 80 kVp were significantly lower than those of 120 kVp in all organs (e.g. liver, 1.6 vs. 1.9; pancreas, 1.5 vs. 1.8; spleen, 1.7 vs. 2.0) on contrast-enhanced CT. CONCLUSION: The low tube voltage with low-contrast-medium protocol significantly reduces organ doses at the same volume CT dose index setting compared with conventional 120-kVp protocol with standard contrast medium on contrast-enhanced CT.

Unenhanced Dual-Layer Spectral-Detector CT for Characterizing Indeterminate Adrenal Lesions.

Background Unenhanced dual-layer spectral-detector CT may facilitate adrenal lesion characterization; however, no studies have evaluated its incremental diagnostic yield for indeterminate lesions (unenhanced attenuation >10 HU) in comparison to that with conventional unenhanced CT. Purpose To determine whether spectral attenuation analysis improves characterization of lipid-poor adrenal adenomas from nonadenomas compared to that with mean attenuation and histogram analysis of conventional CT images. Materials and Methods This retrospective study included patients with indeterminate adrenal lesions who underwent unenhanced dual-layer spectral-detector CT between March 2018 and June 2020. Mean attenuation on conventional 120-kVp images (HUconv), histogram-based percentage negative pixels (proportion of all pixels <0 HU) on conventional 120-kVp images, and mean attenuation on virtual monoenergetic images (VMIs) at 40-140 keV were measured for each lesion. The attenuation difference between virtual monoenergetic 140- and 40-keV images (ΔHU; ie, Hounsfield unit at 140 keV - Hounsfield unit at 40 keV) and ΔHU indexed with HUconv (ΔHU index; ie, ΔHU/HUconv × 100) were calculated. Conventional and virtual monoenergetic imaging parameters were compared between lipid-poor adenomas and nonadenomas by using the Mann-Whitney U test. Receiver operating characteristic analysis was performed to determine the sensitivity for attaining at least 95% specificity in characterizing adenomas from nonadenomas; sensitivity was compared by using the McNemar test. Results A total of 232 patients (mean age ± standard deviation, 67 years ± 11; 145 men) with 129 lipid-poor adenomas and 103 nonadenomas were evaluated. HUconv and mean attenuation on VMIs at 40-140 keV were lower and the percentage negative pixels, ΔHU, and ΔHU index higher in lipid-poor adenomas than in nonadenomas (P < .001 for all). Attenuation differences between adenomas and nonadenomas on VMIs were maximal at 40 keV (23 HU at 40 keV vs 5 HU at 140 keV). The highest sensitivities for differentiating adenomas and nonadenomas were achieved for virtual monoenergetic ΔHU index (77% [99 of 129 adenomas]), attenuation on 40-keV images (71% [91 of 129 adenomas]), and ΔHU (67% [87 of 129 adenomas]) compared to HUconv (35% [45 of 129 adenomas]) and percentage negative pixels (30% [39 of 129 adenomas]) (P < .001 for all; specificity, 95% [98 of 103 nonadenomas]). Conclusion Spectral attenuation analysis enabled differentiation of lipid-poor adenomas from nonadenomas with higher sensitivity than mean attenuation or histogram analysis of conventional CT images. © RSNA, 2021 Online supplemental material is available for this article.

Relative Enhancement Ratio of Portal Venous Phase to Unenhanced CT in the Diagnosis of Lipid-poor Adrenal Adenomas.

Background The development of an accurate, practical, noninvasive, and widely available diagnostic approach to characterize lipid-poor adrenal lesions (greater than 10 HU at unenhanced CT) remains an ongoing demand. Purpose To investigate whether combined assessment of unenhanced and portal venous phase CT allows for the differentiation of lipid-poor adrenal adenomas from nonadenomas. Materials and Methods Patients with lipid-poor adrenal lesions who underwent unenhanced and portal venous phase CT with a single-energy scanner between January 2016 and March 2020 were identified retrospectively. For each lesion, the unenhanced and contrast-enhanced attenuation were measured; the absolute enhancement (contrast-enhanced minus unenhanced attenuation [HU]) and relative enhancement ratio ([absolute enhancement divided by unenhanced attenuation] × 100%) were calculated. The sensitivity achieved at 95% specificity to distinguish adenomas from nonadenomas was determined with receiver operating characteristic curve analysis and compared among parameters with use of the McNemar test. Results A total of 220 patients (mean age ± standard deviation, 66 years ± 12; 134 men) with 131 lipid-poor adenomas and 89 nonadenomas were analyzed. The sensitivity (achieved at 95% specificity) of the relative enhancement ratio (86% [113 of 131 adenomas; 95% CI: 79, 92] at a threshold of >210%) was higher than that of unenhanced attenuation (50% [66 of 131 adenomas; 95% CI: 42, 59] at a threshold of ≤21 HU), contrast-enhanced attenuation (3% [four of 131 adenomas; 95% CI: 1, 8] at a threshold of >120 HU), and absolute enhancement (24% [32 of 131 adenomas; 95% CI: 17, 33] at a threshold of >74 HU; all P < .001). The sensitivities of the relative enhancement ratio were 100% (58 of 58 adenomas; 95% CI: 94, 100), 83% (52 of 63 adenomas; 95% CI: 71, 91), and 30% (three of 10 adenomas; 95% CI: 7, 65) for adenomas measuring unenhanced attenuation of more than 10 HU up to 20 HU, 21-30 HU, and more than 30 HU, respectively. Conclusion A relative enhancement ratio threshold of greater than 210%, measured at unenhanced and portal venous phase CT, accurately differentiated lipid-poor adenomas from nonadenomas, particularly for lesions with unenhanced attenuation of 10-30 HU. © RSNA, 2021 Online supplemental material is available for this article.

Liver fibrosis assessment with multiphasic dual-energy CT: diagnostic performance of iodine uptake parameters.

OBJECTIVES: To evaluate the ability of iodine uptake parameters from hepatic multiphasic CT to predict liver fibrosis, and compare absolute contrast enhancement (ΔHU) with dual-energy iodine density (ID) methods. METHODS: One hundred seventeen patients with pathologically proven liver fibrosis who underwent dual-energy CT during portal-venous phase (PVP) and 3-min delayed phase (DP) between January 2017 and Octotber 2019 were retrospectively included. Two radiologists measured the hepatic and blood-pool iodine uptake using ΔHU and ID methods; extracellular volume fraction (ECV) and the iodine washout rate (IWR) calculated with both methods were compared between different fibrosis stages (F0-1 vs. F2-4, F0-2 vs. F3-4, or F0-3 vs. F4). The inter-observer reproducibility (intraclass correlation coefficients [ICCs]) for ECV and IWR was compared between the ΔHU and ID methods. The areas under the receiver operating characteristic curves (AUCs) to predict liver fibrosis severity were calculated for serum and imaging fibrosis markers. To identify independent predictors, multivariable logistic regression analysis was performed, and combined performance was assessed for the ΔHU and ID models. RESULTS: Patients with F ≥ 2 (n = 70), F ≥ 3 (n = 51), and F4 (n = 29) had higher ECV and lower IWR than those with F ≤ 1, F ≤ 2, and F ≤ 3, respectively (all p < 0.001). ICCs were higher in the ID method than in the ΔHU method (ECV: p = 0.045; IWR: p < 0.001). The AUC ranges of ECVΔHU, ECVID, IWRΔHU, and IWRID for predicting liver fibrosis severity were 0.65-0.71, 0.67-0.73, 0.76-0.81, and 0.81-0.85, respectively. IWR and fibrosis-4 index were independent predictors, with combined AUCs of 0.82-0.87 for the ΔHU model and 0.86-0.89 for the ID model. CONCLUSIONS: IWR more accurately predicted liver fibrosis than ECV in routine multiphasic CT. The dual-energy ID method yielded higher inter-observer reproducibility and predictive values than the single-energy ΔHU method. KEY POINTS: • The IWR calculated from hepatic iodine uptake during PVP and 3-min DP predicted liver fibrosis (AUC, 0.76-0.85), while the ECV had a relatively limited predictive value (ACU, 0.65-0.73). • Compared with the conventional ΔHU method, the dual-energy ID method provided superior inter-observer reproducibility for measurement of ECV (p = 0.046) and IWR (p < 0.001). • The IWR and FIB-4 served as independent predictors of liver fibrosis; their combination yielded the high diagnostic performance particularly when using the ID method (combined AUCs of 0.86-0.89).

Usefulness of Cardiac Computed Tomography in the Diagnosis of Anti-Cancer Therapy-Related Cardiac Dysfunction　- Consistency With Magnetic Resonance Imaging.

BACKGROUND: Cardiac magnetic resonance (CMR) imaging is the golden standard used for the diagnosis of cancer therapy-related cardiac dysfunction (CTRCD). The consistency of cardiac computed tomography (CCT) in CTRCD cases using CMR imaging is investigated in this study.Methods and Results:In 7 clinically confirmed CTRCD patients, focal late enhancement was confirmed on both CCT and CMR for 4 patients. Myocardial extracellular volume (ECV) values measured by CCT and CMR were elevated in all patients, suggesting the presence of diffuse myocardial damage. CONCLUSIONS: The study findings indicated that CCT could provide adequate information about late myocardial enhancement and ECV quantification, indicating the effective evaluation of CTRCD by CCT.

Deep Learning-based Reconstruction for Lower-Dose Pediatric CT: Technical Principles, Image Characteristics, and Clinical Implementations.

Optimizing the CT acquisition parameters to obtain diagnostic image quality at the lowest possible radiation dose is crucial in the radiosensitive pediatric population. The image quality of low-dose CT can be severely degraded by increased image noise with filtered back projection (FBP) reconstruction. Iterative reconstruction (IR) techniques partially resolve the trade-off relationship between noise and radiation dose but still suffer from degraded noise texture and low-contrast detectability at considerably low-dose settings. Furthermore, sophisticated model-based IR usually requires a long reconstruction time, which restricts its clinical usability. With recent advances in artificial intelligence technology, deep learning-based reconstruction (DLR) has been introduced to overcome the limitations of the FBP and IR approaches and is currently available clinically. DLR incorporates convolutional neural networks-which comprise multiple layers of mathematical equations-into the image reconstruction process to reduce image noise, improve spatial resolution, and preserve preferable noise texture in the CT images. For DLR development, numerous network parameters are iteratively optimized through an extensive learning process to discriminate true attenuation from noise by using low-dose training and high-dose teaching image data. After rigorous validations of network generalizability, the DLR engine can be used to generate high-quality images from low-dose projection data in a short reconstruction time in a clinical environment. Application of the DLR technique allows substantial dose reduction in pediatric CT performed for various clinical indications while preserving the diagnostic image quality. The authors present an overview of the basic concept, technical principles, and image characteristics of DLR and its clinical feasibility for low-dose pediatric CT. ©RSNA, 2021.

A preliminary study of deep learning-based reconstruction specialized for denoising in high-frequency domain: usefulness in high-resolution three-dimensional magnetic resonance cisternography of the cerebellopontine angle.

PURPOSE: Deep learning-based reconstruction (DLR) has been developed to reduce image noise and increase the signal-to-noise ratio (SNR). We aimed to evaluate the efficacy of DLR for high spatial resolution (HR)-MR cisternography. METHODS: This retrospective study included 35 patients who underwent HR-MR cisternography. The images were reconstructed with or without DLR. The SNRs of the CSF and pons, contrast of the CSF and pons, and sharpness of the normal-side trigeminal nerve using full width at half maximum (FWHM) were compared between the two image types. Noise quality, sharpness, artifacts, and overall image quality of these two types of images were qualitatively scored. RESULTS: The SNRs of the CSF and pons were significantly higher with DLR than without DLR (CSF 21.81 ± 7.60 vs. 15.33 ± 4.03, p < 0.001; pons 5.96 ± 1.38 vs. 3.99 ± 0.48, p < 0.001). There were no significant differences in the contrast of the CSF and pons (p = 0.225) and sharpness of the normal-side trigeminal nerve using FWHM (p = 0.185) without and with DLR, respectively. Noise quality and the overall image quality were significantly higher with DLR than without DLR (noise quality 3.95 ± 0.19 vs. 2.53 ± 0.44, p < 0.001; overall image quality 3.97 ± 0.17 vs. 2.97 ± 0.12, p < 0.001). There were no significant differences in sharpness (p = 0.371) and artifacts (p = 1) without and with DLR. CONCLUSION: DLR can improve the image quality of HR-MR cisternography by reducing image noise without sacrificing contrast or sharpness.