• Title/Summary/Keyword: receiver operating characteristic analysis

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Analysis of agricultural drought status using SAR-based soil moisture imageries (SAR 영상 기반 토양수분을 활용한 농업적 가뭄 분석)

  • Chanyang Sur;Hee-Jin Lee;Yonggwan Lee;Jeehun Chung;Seongjoon Kim;Won-Ho Nam
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.418-418
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    • 2023
  • 가뭄은 농업, 환경 및 사회경제적인 조건에 영향을 미치는 주요 자연 재해로 우리나라는 2015년부터 지속적인 가뭄 상황을 겪고 있다. 지속된 가뭄으로 인해 토양의 수분함량이 변화하여 농작물의 생장 활동 등에 영향을 미쳐 수확량이 낮아질 수 있다. 토양수분은 경사나 토질 등 지형학적인 특성에 따라 민감하게 반응하는 수문인자로, 특성을 광역적으로 정확하게 판단하기 어렵기 때문에 고해상도 원격탐사 자료를 활용하여 토양수분의 거동을 파악하는 연구들이 진행되고 있다. 특히, Synthetic Aperture Radar (SAR) 관측은 작물과 기본적인 토양의 유전체 및 기하학적 특성에 민감하게 반응하기 때문에, 토양수분 및 농업적 가뭄 분석 연구에 활용되고 있다. 본 연구는 2025년 발사될 예정인 C-band SAR 수자원 위성 산출물인 토양수분을 적용한 농업적 가뭄지수산정 알고리즘 기법 개발 연구를 위하여, 수자원 위성과 제원이 비슷한 Sentinel-1 자료를 통해 산정된 토양수분을 활용하여 농업적 가뭄지수인 Soil Moisture Drought Index (SMDI)를 산정하고자 한다. 산정된 SMDI의 검증을 위해 지점 관측된 토양수분 자료와 비교하여 Receiver Operating Characteristic (ROC) 분석 및 error matrix 기법 등을 활용하여 산정된 농업적 가뭄지수의 지역적 적용성을 파악하고자 한다. SAR 자료 기반의 농업적 가뭄지수 산정 알고리즘을 개발함으로써, 향후 제공될 수자원 위성의 자료를 활용한 가뭄 분석 연구에 활용될 수 있을 것으로 판단된다.

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Chest Radiography of Tuberculosis: Determination of Activity Using Deep Learning Algorithm

  • Ye Ra Choi;Soon Ho Yoon;Jihang Kim;Jin Young Yoo;Hwiyoung Kim;Kwang Nam Jin
    • Tuberculosis and Respiratory Diseases
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    • v.86 no.3
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    • pp.226-233
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    • 2023
  • Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

Diagnostic Role of Bile Pigment Components in Biliary Tract Cancer

  • Keun Soo Ahn;Koo Jeong Kang;Yong Hoon Kim;Tae-Seok Kim;Kwang Bum Cho;Hye Soon Kim;Won-Ki Baek;Seong-Il Suh;Jin-Yi Han
    • Biomolecules & Therapeutics
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    • v.31 no.6
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    • pp.674-681
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    • 2023
  • Bile pigment, bilirubin, and biliverdin concentrations may change as a results of biliary tract cancer (BTC) altering the mechanisms of radical oxidation and heme breakdown. We explored whether changes in bile pigment components could help distinguish BTC from benign biliary illness by evaluating alterations in patients with BTC. We collected bile fluid from 15 patients with a common bile duct stone (CBD group) and 63 individuals with BTC (BTC group). We examined the bile fluid's bilirubin, biliverdin reductase (BVR), heme oxygenase (HO-1), and bacterial taxonomic abundance. Serum bilirubin levels had no impact on the amounts of bile HO-1, BVR, or bilirubin. In comparison to the control group, the BTC group had considerably higher amounts of HO-1, BVR, and bilirubin in the bile. The areas under the curve for the receiver operating characteristic curve analyses of the BVR and HO-1 were 0.832 (p<0.001) and 0.891 (p<0.001), respectively. Firmicutes was the most prevalent phylum in both CBD and BTC, according to a taxonomic abundance analysis, however the Firmicutes/Bacteroidetes ratio was substantially greater in the BTC group than in the CBD group. The findings of this study showed that, regardless of the existence of obstructive jaundice, biliary carcinogenesis impacts heme degradation and bile pigmentation, and that the bile pigment components HO-1, BVR, and bilirubin in bile fluid have a diagnostic significance in BTC. In tissue biopsies for the diagnosis of BTC, particularly for distinguishing BTC from benign biliary strictures, bile pigment components can be used as additional biomarkers.

Assessment of Diffusion Tensor Imaging Parameters of Hepatic Parenchyma for Differentiation of Biliary Atresia from Alagille Syndrome

  • Ahmed Abdel Khalek Abdel Razek;Ahmed Abdalla;Reda Elfar;Germeen Albair Ashmalla;Khadiga Ali;Tarik Barakat
    • Korean Journal of Radiology
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    • v.21 no.12
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    • pp.1367-1373
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    • 2020
  • 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.

Prediction of Venous Trans-Stenotic Pressure Gradient Using Shape Features Derived From Magnetic Resonance Venography in Idiopathic Intracranial Hypertension Patients

  • Chao Ma;Haoyu Zhu;Shikai Liang;Yuzhou Chang;Dapeng Mo;Chuhan Jiang;Yupeng Zhang
    • Korean Journal of Radiology
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    • v.25 no.1
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    • pp.74-85
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    • 2024
  • 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.

MRI Findings in Trigeminal Neuralgia without Neurovascular Compression: Implications of Petrous Ridge and Trigeminal Nerve Angles

  • Hai Zhong;Wenshuang Zhang;Shicheng Sun;Yifan Bie
    • Korean Journal of Radiology
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    • v.23 no.8
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    • pp.821-827
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    • 2022
  • 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.

Quantification of Nerve Viscosity Using Shear Wave Dispersion Imaging in Diabetic Rats: A Novel Technique for Evaluating Diabetic Neuropathy

  • Feifei Liu;Diancheng Li;Yuwei Xin;Fang Liu;Wenxue Li;Jiaan Zhu
    • Korean Journal of Radiology
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    • v.23 no.2
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    • pp.237-245
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    • 2022
  • 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.

Bone Suppression on Chest Radiographs for Pulmonary Nodule Detection: Comparison between a Generative Adversarial Network and Dual-Energy Subtraction

  • Kyungsoo Bae;Dong Yul Oh;Il Dong Yun;Kyung Nyeo Jeon
    • Korean Journal of Radiology
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    • v.23 no.1
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    • pp.139-149
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    • 2022
  • Objective: To compare the effects of bone suppression imaging using deep learning (BSp-DL) based on a generative adversarial network (GAN) and bone subtraction imaging using a dual energy technique (BSt-DE) on radiologists' performance for pulmonary nodule detection on chest radiographs (CXRs). Materials and Methods: A total of 111 adults, including 49 patients with 83 pulmonary nodules, who underwent both CXR using the dual energy technique and chest CT, were enrolled. Using CT as a reference, two independent radiologists evaluated CXR images for the presence or absence of pulmonary nodules in three reading sessions (standard CXR, BSt-DE CXR, and BSp-DL CXR). Person-wise and nodule-wise performances were assessed using receiver-operating characteristic (ROC) and alternative free-response ROC (AFROC) curve analyses, respectively. Subgroup analyses based on nodule size, location, and the presence of overlapping bones were performed. Results: BSt-DE with an area under the AFROC curve (AUAFROC) of 0.996 and 0.976 for readers 1 and 2, respectively, and BSp-DL with AUAFROC of 0.981 and 0.958, respectively, showed better nodule-wise performance than standard CXR (AUAFROC of 0.907 and 0.808, respectively; p ≤ 0.005). In the person-wise analysis, BSp-DL with an area under the ROC curve (AUROC) of 0.984 and 0.931 for readers 1 and 2, respectively, showed better performance than standard CXR (AUROC of 0.915 and 0.798, respectively; p ≤ 0.011) and comparable performance to BSt-DE (AUROC of 0.988 and 0.974; p ≥ 0.064). BSt-DE and BSp-DL were superior to standard CXR for detecting nodules overlapping with bones (p < 0.017) or in the upper/middle lung zone (p < 0.017). BSt-DE was superior (p < 0.017) to BSp-DL in detecting peripheral and sub-centimeter nodules. Conclusion: BSp-DL (GAN-based bone suppression) showed comparable performance to BSt-DE and can improve radiologists' performance in detecting pulmonary nodules on CXRs. Nevertheless, for better delineation of small and peripheral nodules, further technical improvements are required.

Nomogram Models for Distinguishing Intraductal Carcinoma of the Prostate From Prostatic Acinar Adenocarcinoma Based on Multiparametric Magnetic Resonance Imaging

  • Ling Yang;Xue-Ming Li;Meng-Ni Zhang;Jin Yao;Bin Song
    • Korean Journal of Radiology
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    • v.24 no.7
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    • pp.668-680
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    • 2023
  • Objective: To compare multiparametric magnetic resonance imaging (MRI) features of intraductal carcinoma of the prostate (IDC-P) with those of prostatic acinar adenocarcinoma (PAC) and develop prediction models to distinguish IDC-P from PAC and IDC-P with a high proportion (IDC ≥ 10%, hpIDC-P) from IDC-P with a low proportion (IDC < 10%, lpIDC-P) and PAC. Materials and Methods: One hundred and six patients with hpIDC-P, 105 with lpIDC-P and 168 with PAC, who underwent pretreatment multiparametric MRI between January 2015 and December 2020 were included in this study. Imaging parameters, including invasiveness and metastasis, were evaluated and compared between the PAC and IDC-P groups as well as between the hpIDC-P and lpIDC-P subgroups. Nomograms for distinguishing IDC-P from PAC, and hpIDC-P from lpIDC-P and PAC, were made using multivariable logistic regression analysis. The discrimination performance of the models was assessed using the receiver operating characteristic area under the curve (ROC-AUC) in the sample, where the models were derived from without an independent validation sample. Results: The tumor diameter was larger and invasive and metastatic features were more common in the IDC-P than in the PAC group (P < 0.001). The distribution of extraprostatic extension (EPE) and pelvic lymphadenopathy was even greater, and the apparent diffusion coefficient (ADC) ratio was lower in the hpIDC-P than in the lpIDC-P group (P < 0.05). The ROC-AUCs of the stepwise models based solely on imaging features for distinguishing IDC-P from PAC and hpIDC-P from lpIDC-P and PAC were 0.797 (95% confidence interval, 0.750-0.843) and 0.777 (0.727-0.827), respectively. Conclusion: IDC-P was more likely to be larger, more invasive, and more metastatic, with obviously restricted diffusion. EPE, pelvic lymphadenopathy, and a lower ADC ratio were more likely to occur in hpIDC-P, and were also the most useful variables in both nomograms for predicting IDC-P and hpIDC-P.

Intravoxel Incoherent Motion Magnetic Resonance Imaging for Assessing Parotid Gland Tumors: Correlation and Comparison with Arterial Spin Labeling Imaging

  • Gao Ma;Xiao-Quan Xu;Liu-Ning Zhu;Jia-Suo Jiang;Guo-Yi Su;Hao Hu;Shou-Shan Bu;Fei-Yun Wu
    • Korean Journal of Radiology
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    • v.22 no.2
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    • pp.243-252
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    • 2021
  • Objective: To compare and correlate the findings of intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging and arterial spin labeling (ASL) imaging in characterizing parotid gland tumors. Materials and Methods: We retrospectively reviewed 56 patients with parotid gland tumors evaluated by MR imaging. The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and fraction of perfusion (f) values of IVIM imaging and tumor-to-parotid gland signal intensity ratio (SIR) on ASL imaging were calculated. Spearman rank correlation coefficient, chi-squared, Mann-Whitney U, and Kruskal-Wallis tests with the post-hoc Dunn-Bonferroni method and receiver operating characteristic curve assessments were used for statistical analysis. Results: Malignant parotid gland tumors showed significantly lower D than benign tumors (p = 0.019). Within subgroup analyses, pleomorphic adenomas (PAs) showed significantly higher D than malignant tumors (MTs) and Warthin's tumors (WTs) (p < 0.001). The D* of WTs was significantly higher than that of PAs (p = 0.031). The f and SIR on ASL imaging of WTs were significantly higher than those of MTs and PAs (p < 0.05). Significantly positive correlation was found between SIR on ASL imaging and f (r = 0.446, p = 0.001). In comparison with f, SIR on ASL imaging showed a higher area under curve (0.853 vs. 0.891) in discriminating MTs from WTs, although the difference was not significant (p = 0.720). Conclusion: IVIM and ASL imaging could help differentiate parotid gland tumors. SIR on ASL imaging showed a significantly positive correlation with f. ASL imaging might hold potential to improve the ability to discriminate MTs from WTs.