Hongrye Kim;Mou Seop Lee;Su Young Yoon;Jonghee Han;Jin Young Lee;Junepill Seok
Journal of Trauma and Injury
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v.37
no.2
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pp.114-123
/
2024
Purpose: Appropriate scoring systems can help classify and treat polytrauma patients. This study aimed to validate chest trauma scoring systems in polytrauma patients. Methods: Data from 1,038 polytrauma patients were analyzed. The primary outcomes were one or more complications: pneumonia, chest complications requiring surgery, and mortality. The Thoracic Trauma Severity Score (TTSS), Chest Trauma Score, Rib Fracture Score, and RibScore were compared using receiver operating characteristic (ROC) analysis in patients with or without head trauma. Results: In total, 1,038 patients were divided into two groups: those with complications (822 patients, 79.2%) and those with no complications (216 patients, 20.8%). Sex and body mass index did not significantly differ between the groups. However, age was higher in the complications group (64.1±17.5 years vs. 54.9±17.6 years, P<0.001). The proportion of head trauma patients was higher (58.3% vs. 24.6%, P<0.001) and the Glasgow Coma Scale score was worse (median [interquartile range], 12 [6.5-15] vs. 15 [14-15]; P<0.001) in the complications group. The number of rib fractures, the degree of rib fracture displacement, and the severity of pulmonary contusions were also higher in the complications group. In the area under the ROC curve analysis, the TTSS showed the highest predictive value for the entire group (0.731), head trauma group (0.715), and no head trauma group (0.730), while RibScore had the poorest performance (0.643, 0.622, and 0.622, respectively) Conclusions: Early injury severity detection and grading are crucial for patients with blunt chest trauma. The chest trauma scoring systems introduced to date, including the TTSS, are not acceptable for clinical use, especially in polytrauma patients with traumatic brain injury. Therefore, further revisions and analyses of chest trauma scoring systems are recommended.
Objective: This study aimed to evaluate the diagnostic value of combining the quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) to breast ultrasound (US) to differentiate between benign and malignant breast masses. Materials and Methods: A total of 200 pathologically confirmed breast lesions in 192 patients were retrospectively reviewed using breast US with B-mode imaging, SWE, and SMI. Breast masses were assessed based on the breast imaging reporting and data system (BI-RADS) and quantitative parameters using the maximum elasticity (Emax) and ratio (Eratio) in SWE and the vascular index in SMI (SMIVI). The area under the receiver operating characteristic curve (AUC) value, sensitivity, specificity, accuracy, negative predictive value, and positive predictive value of B-mode alone versus the combination of B-mode US with SWE or SMI of both parameters in differentiating between benign and malignant breast masses was compared, respectively. Hypothetical performances of selective downgrading of BI-RADS category 4a (set 1) and both upgrading of category 3 and downgrading of category 4a (set 2) were calculated. Results: Emax with a cutoff value of 86.45 kPa had the highest AUC value compared to Eratio of 3.57 or SMIVI of 3.35%. In set 1, the combination of B-mode with Emax or SMIVI had a significantly higher AUC value (0.829 and 0.778, respectively) than B-mode alone (0.719) (p < 0.001 and p = 0.047, respectively). B-mode US with the addition of Emax, Eratio, and SMIVI had the best diagnostic performance of AUC value (0.849). The accuracy and specificity increased significantly from 68.0% to 84.0% (p < 0.001) and from 46.1% to 79.1% (p < 0.001), respectively, and the sensitivity decreased from 97.6% to 90.6% without statistical loss (p = 0.199). Conclusion: Combining all quantitative values of SWE and SMI with B-mode US improved the diagnostic performance in differentiating between benign and malignant breast lesions.
Tae-Hyung Kim;Sungmin Woo;Sangwon Han;Chong Hyun Suh;Soleen Ghafoor;Hedvig Hricak;Hebert Alberto Vargas
Korean Journal of Radiology
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v.21
no.6
/
pp.684-694
/
2020
Objective: The purpose was to review the diagnostic performance of the length of tumor capsular contact (LCC) on magnetic resonance imaging (MRI) for detecting prostate cancer extraprostatic extension (EPE). Materials and Methods: PubMed and EMBASE databases were searched up to March 24, 2019. We included diagnostic accuracy studies that evaluated LCC on MRI for EPE detection using radical prostatectomy specimen histopathology as the reference standard. Quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled and graphically presented using hierarchical summary receiver operating characteristic (HSROC) plots. Meta-regression and subgroup analyses were conducted to explore heterogeneity. Results: Thirteen articles with 2136 patients were included. Study quality was generally good. Summary sensitivity and specificity were 0.79 (95% confidence interval [CI] 0.73-0.83) and 0.67 (95% CI 0.60-0.74), respectively. Area under the HSROC was 0.81 (95% CI 0.77-0.84). Substantial heterogeneity was present among the included studies according to Cochran's Q-test (p < 0.01) and Higgins I2 (62% and 86% for sensitivity and specificity, respectively). In terms of heterogeneity, measurement method (curvilinear vs. linear), prevalence of Gleason score ≥ 7, MRI readers' experience, and endorectal coils were significant factors (p ≤ 0.01), whereas method to determine the LCC threshold, cutoff value, magnet strength, and publication year were not (p = 0.14-0.93). Diagnostic test accuracy estimates were comparable across all assessed MRI sequences. Conclusion: Greater LCC on MRI is associated with a higher probability of prostate cancer EPE. Due to heterogeneity among the studies, further investigation is needed to establish the optimal cutoff value for each clinical setting.
Objective: To assess diffusion tensor imaging (DTI) parameters of the hepatic parenchyma for the differentiation of biliary atresia (BA) from Alagille syndrome (ALGS). Materials and Methods: This study included 32 infants with BA and 12 infants with ALGS groups who had undergone DTI. Fractional anisotropy (FA) and mean diffusivity (MD) of the liver were calculated twice by two separate readers and hepatic tissue was biopsied. Statistical analyses were performed to determine the mean values of the two groups. The optimum cut-off values for DTI differentiation of BA and ALGS were calculated by receiver operating characteristic (ROC) analysis. Results: The mean hepatic MD of BA (1.56 ± 0.20 and 1.63 ± 0.2 × 10-3 mm2/s) was significantly lower than that of ALGS (1.84 ± 0.04 and 1.79 ± 0.03 × 10-3 mm2/s) for both readers (r = 0.8, p = 0.001). Hepatic MD values of 1.77 and 1.79 × 10-3 mm2/s as a threshold for differentiating BA from ALGS showed accuracies of 82 and 79% and area under the curves (AUCs) of 0.90 and 0.91 for both readers, respectively. The mean hepatic FA of BA (0.34 ± 0.04 and 0.36 ± 0.04) was significantly higher (p = 0.01, 0.02) than that of ALGS (0.30 ± 0.06 and 0.31 ± 0.05) for both readers (r = 0.80, p = 0.001). FA values of 0.30 and 0.28 as a threshold for differentiating BA from ALGS showed accuracies of 75% and 82% and AUCs of 0.69 and 0.68 for both readers, respectively. Conclusion: Hepatic DTI parameters are promising quantitative imaging parameters for the detection of hepatic parenchymal changes in BA and ALGS and may be an additional noninvasive imaging tool for the differentiation of BA from ALGS.
Objective: To assess the contrast-enhanced CT and ultrasonography (US) findings of intracholecystic papillary neoplasm (ICPN) and determine the imaging features predicting ICPN associated with invasive carcinoma (ICPN-IC). Materials and Methods: In this retrospective study, we enrolled 119 consecutive patients, including 60 male and 59 female, with a mean age ± standard deviation of 63.3 ± 12.1 years, who had pathologically confirmed ICPN (low-grade dysplasia [DP] = 34, high-grade DP = 35, IC = 50) and underwent preoperative CT or US. Two radiologists independently assessed the CT and US findings, focusing on wall and polypoid lesion characteristics. The likelihood of ICPN-IC was graded on a 5-point scale. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of ICPN-IC separately for wall and polypoid lesion findings. The performances of CT and US in distinguishing ICPN-IC from ICPN with DP (ICPN-DP) was evaluated using the area under the receiver operating characteristic curve (AUC). Results: For wall characteristics, the maximum wall thickness (adjusted odds ratio [aOR] = 1.4; 95% confidence interval [CI]: 1.1-1.9) and mucosal discontinuity (aOR = 5.6; 95% CI: 1.3-23.4) on CT were independently associated with ICPN-IC. Among 119 ICPNs, 110 (92.4%) showed polypoid lesions. Regarding polypoid lesion findings, multiplicity (aOR = 4.0; 95% CI: 1.6-10.4), lesion base wall thickening (aOR = 6.0; 95% CI: 2.3-15.8) on CT, and polyp size (aOR = 1.1; 95% CI: 1.0-1.2) on US were independently associated with ICPN-IC. CT showed a higher diagnostic performance than US in predicting ICPN-IC (AUC = 0.793 vs. 0.676; p = 0.002). Conclusion: ICPN showed polypoid lesions and/or wall thickening on CT or US. A thick wall, multiplicity, presence of wall thickening in the polypoid lesion base, and large polyp size are imaging findings independently associated with invasive cancer and may be useful for differentiating ICPN-IC from ICPN-DP.
Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27-42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836-0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.
Objective: To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on 18F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19 del) and exon 21 L858R missense (21 L858R) mutations using FDG PET/CT radiomics. Materials and Methods: We retrospectively analyzed 179 patients with lung adenocarcinoma. They were randomly assigned to training (n = 125) and testing (n = 54) cohorts in a 7:3 ratio. A total of 2632 radiomics features were extracted from the tumor region of interest from the PET (1316) and CT (1316) images. Six PET/CT radiomics features that remained after the feature selection step were used to calculate the radiomics model score (rad-score). Subsequently, a combined clinical and radiomics model was constructed based on sex, smoking history, tumor diameter, and rad-score. The performance of the combined model in identifying EGFR mutations was assessed using a receiver operating characteristic (ROC) curve. Furthermore, in a subsample of 99 patients, a PET/CT radiomics model for distinguishing 19 del and 21 L858R EGFR mutational subtypes was established, and its performance was evaluated. Results: The area under the ROC curve (AUROC) and accuracy of the combined clinical and PET/CT radiomics models were 0.882 and 81.6%, respectively, in the training cohort and 0.837 and 74.1%, respectively, in the testing cohort. The AUROC and accuracy of the radiomics model for distinguishing between 19 del and 21 L858R EGFR mutational subtypes were 0.708 and 66.7%, respectively, in the training cohort and 0.652 and 56.7%, respectively, in the testing cohort. Conclusion: The combined clinical and PET/CT radiomics model could identify the EGFR mutational status in lung adenocarcinoma with moderate accuracy. However, distinguishing between EGFR 19 del and 21 L858R mutational subtypes was more challenging using PET/CT radiomics.
Objective: To determine the anatomical characteristics of the petrous ridge and trigeminal nerve in trigeminal neuralgia (TN) without neurovascular compression (NVC). Materials and Methods: From May 2017 to March 2021, 66 patients (49 female and 17 male; mean age ± standard deviation [SD], 56.8 ± 13.3 years) with TN without NVC and 57 controls (46 female and 11 male; 52.0 ± 15.6 years) were enrolled. The angle of the petrous ridge (APR) and angle of the trigeminal nerve (ATN) were measured using magnetic resonance imaging with a high-resolution three-dimensional T2 sequence. Data on the symptomatic side were compared with those on the asymptomatic side in patients and with the mean measurements of the bilateral sides in controls. Receiver operating characteristic (ROC) analysis was conducted to evaluate the performance of APR and ATN in distinguishing TN patients from controls. Results: In TN patients without NVC, the mean ± standard deviation (SD) of APR on the symptomatic side (98.40° ± 19.75°) was significantly smaller than that of the asymptomatic side (105.59° ± 22.45°, p = 0.019) and controls (108.44° ± 15.98°, p = 0.003). The mean ATN ± SD on the symptomatic side (144.41° ± 8.92°) was significantly smaller than that of the asymptomatic side (149.67° ± 8.09°, p = 0.003) and controls (150.45° ± 8.48°, p = 0.001). The area under the ROC curve for distinguishing TN patients from controls was 0.673 (95% confidence interval [CI]: 0.579-0.758) for APR and 0.700 (CI: 0.607-0.782) for ATN. The sensitivity and specificity using the diagnostic cutoff yielding the highest Youden index were 81.8% (54/66) and 49.1% (28/57), respectively, for APR (with a cutoff score of 94.30°) and 65.2% (43/66) and 66.7% (38/57), respectively, for ATN (cutoff score, 148.25°). Conclusion: In patients with TN without NVC, APR and ATN were smaller than those in controls, which may explain the potential cause of TN and provide additional information for diagnosis.
Objective: Viscoelasticity is an essential feature of nerves, although little is known about their viscous properties. The discovery of shear wave dispersion (SWD) imaging has presented a new approach for the non-invasive evaluation of tissue viscosity. The present study investigated the feasibility of using SWD imaging to evaluate diabetic neuropathy using the sciatic nerve in a diabetic rat model. Materials and Methods: This study included 11 diabetic rats in the diabetic group and 12 healthy rats in the control group. Bilateral sciatic nerves were evaluated 3 months after treatment with streptozotocin. We measured the nerve cross-sectional area (CSA), nerve stiffness using shear wave elastography (SWE), and nerve viscosity using SWD imaging. The motor nerve conduction velocity (MNCV) was also measured. These four indicators and the histology of the sciatic nerves were then compared between the two groups. The performance of CSA, SWE, and SWD imaging in distinguishing the two groups was assessed using receiver operating characteristic (ROC) analysis. Results: Nerve CSA, stiffness, and viscosity in the diabetic group was significantly higher than those in the control group (all p < 0.05). The results also revealed a significantly lower MNCV in the diabetic group (p = 0.005). Additionally, the density of myelinated fibers was significantly lower in the diabetic group (p = 0.004). The average thickness of the myelin sheath was also lower in the diabetic group (p = 0.012). The area under the ROC curve for distinguishing the diabetic neuropathy group from the control group was 0.876 for SWD imaging, which was significantly greater than 0.677 for CSA (p = 0.030) and 0.705 for SWE (p = 0.035). Conclusion: Sciatic nerve viscosity measured using SWD imaging was significantly higher in diabetic rats. The viscosity measured using SWD imaging performed well in distinguishing the diabetic neuropathy group from the control group. Therefore, SWD imaging may be a promising method for the evaluation of diabetic neuropathy.
Heera Yoen;Soo-Yeon Kim;Dae-Won Lee;Han-Byoel Lee;Nariya Cho
Korean Journal of Radiology
/
v.24
no.7
/
pp.626-639
/
2023
Objective: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). Materials and Methods: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. Results: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. Conclusion: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.
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