• Korean Journal of Radiology
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• v.22 no.11
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• pp.1841-1849
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• 2021

Objective: To prospectively investigate the feasibility of shear wave elastography (SWE) as a new quantitative and objective method for evaluating the stiffness of the gastrocnemius medialis (GM) muscle during passive stretching in patients with Parkinson's disease (PD). Materials and Methods: SWE of the GM muscle was performed in 28 patients with PD [13 female and 15 male; mean age ± standard deviation (SD): 63.0 ± 8.5 years] and 12 healthy controls (5 female and 7 male; mean age ± SD: 59.3 ± 6.4 years) during passive ankle rotation. A Young's modulus-ankle angle curve was constructed. The GM slack angle and baseline Young's modulus (E₀) were compared between the markedly symptomatic and mildly symptomatic sides of patients with PD, and healthy controls. Additionally, the correlation between the GM slack angle and the severity of rigidity, and the observer reproducibility of SWE in determining the GM slack angle were evaluated. Results: The GM slack angle was smaller on both the markedly and mildly symptomatic sides in patients with PD than in healthy controls (mean ± SD of -29.13° ± 3.79° and -25.65° ± 3.39°, respectively, vs. -21.22° ± 3.52°; p < 0.001 and p = 0.006, respectively). Additionally, in patients with PD, the GM slack angle on the markedly symptomatic side was smaller than that on the mildly symptomatic side (p = 0.003). The E0 value was lower on both the markedly and mildly symptomatic sides in patients with PD than in healthy controls (mean ± SD of 10.11 ± 2.85 kPa and 10.08 ± 1.88 kPa, respectively, vs. 12.23 ± 1.02 kPa; p = 0.012 and p < 0.001, respectively). However, no significant difference was found between the markedly and mildly symptomatic sides in patients with PD (p = 0.634). A negative linear relationship was observed between the GM slack angle and lower limb rigidity score on the markedly symptomatic side in patients with PD (r = -0.719; p < 0.001). The intraclass correlation coefficients for observer reproducibility of SWE ranged from 0.880 to 0.951. Conclusion: The slack angle determined by SWE may be a useful quantitative and reproducible method for evaluating muscle stiffness in patients with PD.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1850-1857
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• 2021

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI^TM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1680-1689
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• 2021

Objective: To investigate the diagnostic yield of diffusion-weighted imaging (DWI) in patients with transient global amnesia (TGA) and identify significant parameters affecting diagnostic yield. Materials and Methods: A systematic literature search of the MEDLINE and EMBASE databases was conducted to identify studies that assessed the diagnostic yield of DWI in patients with TGA. The pooled diagnostic yield of DWI in patients with TGA was calculated using the DerSimonian-Laird random-effects model. Subgroup analyses were also performed of slice thickness, magnetic field strength, and interval between symptom onset and DWI. Results: Twenty-two original articles (1732 patients) were included. The pooled incidence of right, left, and bilateral hippocampal lesions was 37% (95% confidence interval [CI], 30-44%), 42% (95% CI, 39-46%), and 25% (95% CI, 20-30%) of all lesions, respectively. The pooled diagnostic yield of DWI in patients with TGA was 39% (95% CI, 27-52%). The Higgins I² statistic showed significant heterogeneity (I² = 95%). DWI with a slice thickness ≤ 3 mm showed a higher diagnostic yield than DWI with a slice thickness > 3 mm (pooled diagnostic yield: 63% [95% CI, 53-72%] vs. 26% [95% CI, 16-40%], p < 0.01). DWI performed at an interval between 24 and 96 hours after symptom onset showed a higher diagnostic yield (68% [95% CI, 57-78%], p < 0.01) than DWI performed within 24 hours (16% [95% CI, 7-34%]) or later than 96 hours (15% [95% CI, 8-26%]). There was no difference in the diagnostic yield between DWI performed using 3T vs. 1.5T (pooled diagnostic yield, 31% [95% CI, 25-38%] vs. 24% [95% CI, 14-37%], p = 0.31). Conclusion: The pooled diagnostic yield of DWI in TGA patients was 39%. DWI obtained with a slice thickness ≤ 3 mm or an interval between symptom onset and DWI of > 24 to 96 hours could increase the diagnostic yield.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1875-1885
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• 2021

Objective: Central nervous system involvement in coronavirus disease 2019 (COVID-19) has been increasingly reported. We performed a systematic review and meta-analysis to evaluate the incidence of radiologically demonstrated neurologic complications and detailed neuroimaging findings associated with COVID-19. Materials and Methods: A systematic literature search of MEDLINE/PubMed and EMBASE databases was performed up to September 17, 2020, and studies evaluating neuroimaging findings of COVID-19 using brain CT or MRI were included. Several cohort-based outcomes, including the proportion of patients with abnormal neuroimaging findings related to COVID-19 were evaluated. The proportion of patients showing specific neuroimaging findings was also assessed. Subgroup analyses were also conducted focusing on critically ill COVID-19 patients and results from studies that used MRI as the only imaging modality. Results: A total of 1394 COVID-19 patients who underwent neuroimaging from 17 studies were included; among them, 3.4% of the patients demonstrated COVID-19-related neuroimaging findings. Olfactory bulb abnormalities were the most commonly observed (23.1%). The predominant cerebral neuroimaging finding was white matter abnormality (17.6%), followed by acute/subacute ischemic infarction (16.0%), and encephalopathy (13.0%). Significantly more critically ill patients had COVID-19-related neuroimaging findings than other patients (9.1% vs. 1.6%; p = 0.029). The type of imaging modality used did not significantly affect the proportion of COVID-19-related neuroimaging findings. Conclusion: Abnormal neuroimaging findings were occasionally observed in COVID-19 patients. Olfactory bulb abnormalities were the most commonly observed finding. Critically ill patients showed abnormal neuroimaging findings more frequently than the other patient groups. White matter abnormalities, ischemic infarctions, and encephalopathies were the common cerebral neuroimaging findings.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.413-421
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• 2020

Objective: A widely applicable, non-invasive screening method for non-alcoholic fatty liver disease (NAFLD) is needed. We aimed to develop and validate an index combining computed tomography (CT) and routine clinical data for screening for NAFLD in a large cohort of adults with pathologically proven NAFLD. Materials and Methods: This retrospective study included 2218 living liver donors who had undergone liver biopsy and CT within a span of 3 days. Donors were randomized 2:1 into development and test cohorts. CTL-S was measured by subtracting splenic attenuation from hepatic attenuation on non-enhanced CT. Multivariable logistic regression analysis of the development cohort was utilized to develop a clinical-CT index predicting pathologically proven NAFLD. The diagnostic performance was evaluated by analyzing the areas under the receiver operating characteristic curve (AUC). The cutoffs for the clinical-CT index were determined for 90% sensitivity and 90% specificity in the development cohort, and their diagnostic performance was evaluated in the test cohort. Results: The clinical-CT index included CTL-S, body mass index, and aspartate transaminase and triglyceride concentrations. In the test cohort, the clinical-CT index (AUC, 0.81) outperformed CTL-S (0.74; p < 0.001) and clinical indices (0.73-0.75; p < 0.001) in diagnosing NAFLD. A cutoff of ≥ 46 had a sensitivity of 89% and a specificity of 41%, whereas a cutoff of ≥ 56.5 had a sensitivity of 57% and a specificity of 89%. Conclusion: The clinical-CT index is more accurate than CTL-S and clinical indices alone for the diagnosis of NAFLD and may be clinically useful in screening for NAFLD.

• Korean Journal of Radiology
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• v.21 no.1
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• pp.88-100
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• 2020

Objective: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images. Materials and Methods: A fully convolutional network-based segmentation system was developed using a training dataset of 883 CT scans from 467 subjects. Axial CT images obtained at the inferior endplate level of the 3rd lumbar vertebra were used for the analysis. Manually drawn segmentation maps of the skeletal muscle, visceral fat, and subcutaneous fat were created to serve as ground truth data. The performance of the fully convolutional network-based segmentation system was evaluated using the Dice similarity coefficient and cross-sectional area error, for both a separate internal validation dataset (426 CT scans from 308 subjects) and an external validation dataset (171 CT scans from 171 subjects from two outside hospitals). Results: The mean Dice similarity coefficients for muscle, subcutaneous fat, and visceral fat were high for both the internal (0.96, 0.97, and 0.97, respectively) and external (0.97, 0.97, and 0.97, respectively) validation datasets, while the mean cross-sectional area errors for muscle, subcutaneous fat, and visceral fat were low for both internal (2.1%, 3.8%, and 1.8%, respectively) and external (2.7%, 4.6%, and 2.3%, respectively) validation datasets. Conclusion: The fully convolutional network-based segmentation system exhibited high performance and accuracy in the automatic segmentation of abdominal muscle and fat on CT images.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.471-482
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• 2020

Objective: We aimed to determine the optimized image-based surrogate endpoints (IBSEs) in targeted therapies for glioblastoma through a systematic review and meta-analysis of phase III randomized controlled trials (RCTs). Materials and Methods: A systematic search of OVID-MEDLINE and EMBASE for phase III RCTs on glioblastoma was performed in December 2017. Data on overall survival (OS) and IBSEs, including progression-free survival (PFS), 6-month PFS (6moPFS), 12-month PFS (12moPFS), median PFS, and objective response rate (ORR) were extracted. Weighted linear regression analysis for the hazard ratio for OS and the hazard ratios or odds ratios for IBSEs was performed. The associations between IBSEs and OS were evaluated. Subgroup analyses according to disease stage (newly diagnosed glioblastoma versus recurrent glioblastoma), types of test treatment, and types of response assessment criteria were performed. Results: Twenty-three phase III RCTs published between 2000 and 2017, including 8387 patients, met the inclusion criteria. OS showed strong correlations with PFS (standardized β coefficient [R] = 0.719), 6moPFS (R = 0.647), and 12moPFS (R = 0.638). OS showed no correlations with median PFS and ORR. In subgroup analysis according to types of therapies, PFS showed the highest correlations with OS in targeted therapies for cell cycle pathways (R = 0.913) and growth factor receptors and their downstream pathways (R = 0.962). 12moPFS showed the highest correlation with OS in antiangiogenic therapy (R = 0.821). The response assessment in neuro-oncology criteria provided higher correlation coefficients between OS and IBSEs than the Macdonald criteria. Conclusion: Overall, PFS is an optimized IBSE in targeted therapies for glioblastoma; however, 12moPFS is optimal in antiangiogenic therapy.

• Korean Journal of Radiology
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• v.22 no.4
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• pp.652-662
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• 2021

Objective: To investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA). Materials and Methods: Preoperative CT image findings were consecutively evaluated in 317 patients with resected IMA from January 2011 to December 2015. The association between CT features and long-term survival were assessed by univariate analysis. The independent prognostic factors were identified by the multivariate Cox regression analyses. The survival comparison of IMA patients was investigated using the Kaplan-Meier method and propensity scores. Furthermore, the prognostic impact of CT features was assessed based on different imaging subtypes, and the results were adjusted using the Bonferroni method. Results: The median follow-up time was 52.8 months; the 5-year disease-free survival (DFS) and overall survival rates of resected IMAs were 68.5% and 77.6%, respectively. The univariate analyses of all IMA patients demonstrated that 15 CT imaging features, in addition to the clinicopathologic characteristics, significantly correlated with the recurrence or death of IMA patients. The multivariable analysis revealed that five of them, including imaging subtype (p = 0.002), spiculation (p < 0.001), tumor density (p = 0.008), air bronchogram (p < 0.001), emphysema (p < 0.001), and location (p = 0.029) were independent prognostic factors. The subgroup analysis demonstrated that pneumonic-type IMA had a significantly worse prognosis than solitary-type IMA. Moreover, for solitary-type IMAs, the most independent CT imaging biomarkers were air bronchogram and emphysema with an adjusted p value less than 0.05; for pneumonic-type IMA, the tumors with mixed consolidation and ground-glass opacity were associated with a longer DFS (adjusted p = 0.012). Conclusion: CT imaging features characteristic of IMA may provide prognostic information and individual risk assessment in addition to the recognized clinical predictors.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1323-1331
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• 2021

Objective: To identify the association between renal tumor complexity and pathologic renal sinus invasion (RSI) and evaluate the usefulness of computed tomography tumor features for predicting RSI in patients with renal cell carcinoma (RCC). Materials and Methods: This retrospective study included 276 consecutive patients who underwent radical nephrectomy for RCC with a size of ≤ 7 cm between January 2014 and October 2017. Tumor complexity and anatomical renal sinus involvement were evaluated using two standardized scoring systems: the radius (R), exophytic or endophytic (E), nearness to collecting system or sinus (N), anterior or posterior (A), and location relative to polar lines (RENAL) nephrometry and preoperative aspects and dimensions used for anatomical classification (PADUA) system. CT-based tumor features, including shape, enhancement pattern, margin at the interface of the renal sinus (smooth vs. non-smooth), and finger-like projection of the mass, were also assessed by two independent radiologists. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of RSI. The positive predictive value, negative predictive value (NPV), accuracy of anatomical renal sinus involvement, and tumor features were evaluated. Results: Eighty-one of 276 patients (29.3%) demonstrated RSI. Among highly complex tumors (RENAL or PADUA score ≥ 10), the frequencies of RSI were 42.4% (39/92) and 38.0% (71/187) using RENAL and PADUA scores, respectively. Multivariable analysis showed that a non-smooth margin and the presence of a finger-like projection were significant predictors of RSI. Anatomical renal sinus involvement showed high NPVs (91.7% and 95.2%) but low accuracy (40.2% and 43.1%) for RSI, whereas the presence of a non-smooth margin or finger-like projection demonstrated comparably high NPVs (90.0% and 91.3% for both readers) and improved accuracy (67.0% and 73.9%, respectively). Conclusion: A non-smooth margin or the presence of a finger-like projection can be used as a preoperative CT-based tumor feature for predicting RSI in patients with RCC.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1044-1053
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• 2021

Objective: Motion-corrected averaging with a single-shot technique was introduced for faster acquisition of late-gadolinium-enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging while free-breathing. We aimed to evaluate the image quality (IQ) of free-breathing motion-corrected single-shot LGE (moco-ss-LGE) in patients with hypertrophic cardiomyopathy (HCM). Materials and Methods: Between April and December 2019, 30 patients (23 men; median age, 48.5; interquartile range [IQR], 36.5-61.3) with HCM were prospectively enrolled. Breath-held single-shot LGE (bh-ss-LGE) and free-breathing moco-ss-LGE images were acquired in random order on a 3T MR system. Semi-quantitative IQ scores, contrast-to-noise ratios (CNRs), and quantitative size of myocardial scar were assessed on pairs of bh-ss-LGE and moco-ss-LGE. The mean ± standard deviation of the parameters was obtained. The results were compared using the Wilcoxon signed-rank test. Results: The moco-ss-LGE images had better IQ scores than the bh-ss-LGE images (4.55 ± 0.55 vs. 3.68 ± 0.45, p < 0.001). The CNR of the scar to the remote myocardium (34.46 ± 11.85 vs. 26.13 ± 10.04, p < 0.001), scar to left ventricle (LV) cavity (13.09 ± 7.95 vs. 9.84 ± 6.65, p = 0.030), and LV cavity to remote myocardium (33.12 ± 15.53 vs. 22.69 ± 11.27, p < 0.001) were consistently greater for moco-ss-LGE images than for bh-ss-LGE images. Measurements of scar size did not differ significantly between LGE pairs using the following three different quantification methods: 1) full width at half-maximum method; 23.84 ± 12.88% vs. 24.05 ± 12.81% (p = 0.820), 2) 6-standard deviation method, 15.14 ± 10.78% vs. 15.99 ± 10.99% (p = 0.186), and 3) 3-standard deviation method; 36.51 ± 17.60% vs. 37.50 ± 17.90% (p = 0.785). Conclusion: Motion-corrected averaging may allow for superior IQ and CNRs with free-breathing in single-shot LGE imaging, with a herald of free-breathing moco-ss-LGE as the scar imaging technique of choice for clinical practice.