• Korean Journal of Radiology
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• v.20 no.5
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• pp.801-811
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• 2019

Objective: To determine whether diffusion kurtosis imaging (DKI) is effective in monitoring tumor response to neoadjuvant chemotherapy in patients with osteosarcoma. Materials and Methods: Twenty-nine osteosarcoma patients (20 men and 9 women; mean age, 17.6 ± 7.8 years) who had undergone magnetic resonance imaging (MRI) and DKI before and after neoadjuvant chemotherapy were included. Tumor volume, apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and change ratio (ΔX) between pre-and post-treatment were calculated. Based on histologic response, the patients were divided into those with good response (≥ 90% necrosis, n = 12) and those with poor response (< 90% necrosis, n = 17). Several MRI parameters between the groups were compared using Student's t test. The correlation between image indexes and tumor necrosis was determined using Pearson's correlation, and diagnostic performance was compared using receiver operating characteristic curves. Results: In good responders, MD_post, ADC_post, and MK_post values were significantly higher than in poor responders (p < 0.001, p < 0.001, and p = 0.042, respectively). The ΔMD and ΔADC were also significantly higher in good responders than in poor responders (p < 0.001 and p = 0.01, respectively). However, no significant difference was observed in ΔMK (p = 0.092). MD_post and ΔMD showed high correlations with tumor necrosis rate (r = 0.669 and r = 0.622, respectively), and MD_post had higher diagnostic performance than ADC_post (p = 0.037) and MK_post (p = 0.011). Similarly, ΔMD also showed higher diagnostic performance than ΔADC (p = 0.033) and ΔMK (p = 0.037). Conclusion: MD is a promising biomarker for monitoring tumor response to preoperative chemotherapy in patients with osteosarcoma.

• Dementia and Neurocognitive Disorders
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• v.22 no.2
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• pp.69-77
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• 2023

Background and Purpose: The Montreal Cognitive Assessment (MoCA) has been known as a screening test for detecting mild cognitive impairment (MCI) better than Mini-Mental State Examination (MMSE). However, in previous domestic studies, no significant difference was found in the discriminability between MoCA and MMSE. Researchers have suggested that this might be because older Koreans are less educated than older Westerners. This study was conducted to examine the effect of education on the discriminability of MoCA compared to the MMSE. Methods: Participants were 123 cognitively normal elderly, 118 with vascular MCI, 108 with amnestic MCI, 121 with vascular dementia, and 113 with dementia of the Alzheimer's type. The Korean-MoCA (K-MoCA) and Korean-MMSE (K-MMSE) were administered. Multiple regression analyses and receiver operating characteristic (ROC) curve analyses were performed. Results: In all participants, education significantly affected both K-MoCA and K-MMSE scores along with age. The effect of education was re-examined by subgroup analysis after dividing subjects according to the level of education. Effect of education on K-MoCA and K-MMSE was only shown in the group with <9 years of education. ROC curve analyses revealed that the discriminability of K-MoCA to differentiate between vascular MCI and normal elderly was significantly higher than that of K-MMSE. When re-examining subgroups divided by education level, however, this higher discriminability of K-MoCA disappeared in the group with <9 years of education. Conclusions: These results indicate no difference in discriminating cognitive deficits between K-MoCA and K-MMSE in Korean elderly with <9 years of education.

• Korean Circulation Journal
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• v.53 no.10
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• pp.677-689
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• 2023

Background and Objectives: There is limited evidence regarding machine-learning prediction for the recurrence of atrial fibrillation (AF) after electrical cardioversion (ECV). This study aimed to predict the recurrence of AF after ECV using machine learning of clinical features and electrocardiograms (ECGs) in persistent AF patients. Methods: We analyzed patients who underwent successful ECV for persistent AF. Machine learning was designed to predict patients with 1-month recurrence. Individual 12-lead ECGs were collected before and after ECV. Various clinical features were collected and trained the extreme gradient boost (XGBoost)-based model. Ten-fold cross-validation was used to evaluate the performance of the model. The performance was compared to the C-statistics of the selected clinical features. Results: Among 718 patients (mean age 63.5±9.3 years, men 78.8%), AF recurred in 435 (60.6%) patients after 1 month. With the XGBoost-based model, the areas under the receiver operating characteristic curves (AUROCs) were 0.57, 0.60, and 0.63 if the model was trained by clinical features, ECGs, and both (the final model), respectively. For the final model, the sensitivity, specificity, and F1-score were 84.7%, 28.2%, and 0.73, respectively. Although the AF duration showed the best predictive performance (AUROC, 0.58) among the clinical features, it was significantly lower than that of the final machine-learning model (p<0.001). Additional training of extended monitoring data of 15-minute single-lead ECG and photoplethysmography in available patients (n=261) did not significantly improve the model's performance. Conclusions: Machine learning showed modest performance in predicting AF recurrence after ECV in persistent AF patients, warranting further validation studies.

• The Korean Journal of Nuclear Medicine
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• v.34 no.1
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• pp.55-61
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• 2000

Purpose: We performed this study to evaluate the changes of gallbladder ejection fraction (GBEF) in diabetic patients with or without autonomic neuropathy. Materials and Methods: This study included 37 diabetic patients (25 women, 12 men, mean age 51 years) and 24 normal controls (10 women, 14 men, mean age 38 years). After intravenous injection of 185 MBq of $^{99m}Tc$-DISIDA, serial anterior abdominal images were acquired before and after fatty meal. Regions of interest were applied on gallbladder and right hepatic lobe on 60 and 90 minute images to calculate GBEF. Results: GBEF was significantly reduced in diabetes with autonomic neuropathy ($43{\pm}12.3%$) and without autonomic neuropathy ($57.5{\pm}13.2%$) compared with normal controls ($68{\pm}11.6%$, p<0.05). And also, GBEF was significantly reduced in diabetes with autonomic neuropathy compared with diabetes without autonomic neuropathy (p<0.05). Fasting blood glucose level, age, sex, hemoglobin Alc, body mass index, serum lipid level were not different in these two diabetic patient groups (p>0.05). When 50.2% of GBEF was used as the criteria for diabetic autonomic neuropathy, the sensitivity and specificity were 80%, 76.5%, respectively. The area under receiver operating characteristic curve was 0.846. Conclusion: GBEF of diabetic patients with autonomic neuropathy was significantly reduced than that of diabetic patients without autonomic neuropathy.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.24-30
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• 2009

Purpose: Today, Prostate cancer has been gradually increasing, according to the change of internal incidence rate of cancer. Generally, prostate cancer has lead to dead over 90%, in case of metastasis of lymph node and bone. So, innovative development of new radiopharmaceutical and imaging modality is progressed for detection of that metastasis, in nuclear medicine, now. Therefore, this study shows the usefulness of $^{18}F$-Fluoride PET/CT improved diagnosability on bone metastasis of prostate cancer. Materials and Methods: In this study, 33 male patients with prostate cancer were examined (The mean age: $67.8{\pm}10.2$ years old). Every patient was done each whole body bone scan (WBBS) and $^{18}F$-Fluoride positron emission tomography/computed tomography ($^{18}F$-Fluoride PET/CT). And then, using Receiver Operating Characteristic Curve (ROC curve), each sensitivity and specificity of two modalities was measured and compared with. Results: In 22 patients (66.6%) of all, bone metastasis was detected. And, in WBBS, sensitivity was 63.6%, specificity, 81.8%; in $^{18}F$-Fluoride PET/CT, sensitivity was 100% and specificity was 90.9%. As a result of ROC curve, AUROC (The Area under an ROC) of WBBS was 0.778, and that of $^{18}F$-Fluoride PET/CT, 0.942. Conclusions: $^{18}F$-Fluoride PET/CT was higher both sensitivity and specificity than WBBS, and it was valuable to detect bone metastasis of prostate cancer more definitely, with 3D imaging realization. Also, in $^{18}F$-Fluoride PET/CT, physiological images were acquired in more short time than WBBS, so, it was possible to reduce patient's waiting time and complaint. Therefore, it is considered that $^{18}F$-Fluoride PET/CT is able to improve diagnosability by offering more accurate images, as cuts in a share of high cost.

• Tuberculosis and Respiratory Diseases
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• v.64 no.4
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• pp.266-271
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• 2008

Background: Estimation of the probability of a patient having an acute pulmonary embolism (PE) for patients with a suspected PE are well established in North America and Europe. However, an assessment of the prediction rules for a PE has not been clearly defined in Korea. The aim of this study is to assess the prediction rules for patients with a suspected PE in Korea. Methods: We performed a retrospective study of 210 inpatients or patients that visited the emergency ward with a suspected PE where computed tomography pulmonary angiography was performed at a single institution between January 2005 and March 2007. Simplified Wells rules and revised Geneva rules were used to estimate the clinical probability of a PE based on information from medical records. Results: Of the 210 patients with a suspected PE, 49 (19.5%) patients had an actual diagnosis of a PE. The proportion of patients classified by Wells rules and the Geneva rules had a low probability of 1% and 21%, an intermediate probability of 62.5% and 76.2%, and a high probability of 33.8% and 2.8%, respectively. The prevalence of PE patients with a low, intermediate and high probability categorized by the Wells rules and Geneva rules was 100% and 4.5% in the low range, 18.2% and 22.5% in the intermediate range, and 19.7% and 50% in the high range, respectively. Receiver operating characteristic curve analysis showed that the revised Geneva rules had a higher accuracy than the Wells rules in terms of detecting PE. Concordance between the two prediction rules was poor ($\kappa$ coefficient=0.06). Conclusion: In the present study, the two prediction rules had a different predictive accuracy for pulmonary embolisms. Applying the revised Geneva rules to inpatients and emergency ward patients suspected of having PE may allow a more effective diagnostic process than the use of the Wells rules.

• Journal of Yeungnam Medical Science
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• v.23 no.2
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• pp.205-212
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• 2006

Background: Malignant pulmonary nodules account for about 30 to 40 percent of solitary pulmonary nodules (SPN). Therefore, tissue characterization of SPNs is very important. Recently, PET/CT has been widely used for tissue characterization, and has become of importance. The purpose of this study was to compare and to assess multiple factors in PET/CT comparing benign and malignant nodules. Materials and Method: Nineteen patients with SPN underwent PET/CT and biopsy. The difference of standardized uptake value 1 (SUV1), standardized uptake value 2 (SUV2) and retention index in PET/CT between malignancy and benignancy were compared by Levene's test. Result: There were twelve malignant and seven benign nodules. SUV1 and SUV2 were significantly different between malignant nodule and benign nodule (p=0.006 and 0.022), but retention index was not significantly different between malignant nodule and benign nodule (p=0.526). By receiver-operating-characteristic (ROC) analysis, the sensitivity was 66.7% and the specificity was 71.4% at a cut off value of 5.40 in SUV1. The sensitivity was 75% and the specificity was 71.4% at cut off value of 7.45 in SUV2. Conclusion: There was a statistically significant difference in SUV1 and SUV2 between benign and malignant nodules. However, the cut off value of SUV1 and SUV2 by receiver-operating-characteristic (ROC) analysis was 5.40 and 7.45 which is different from previous studies. Therefore, studies on a larger sample of patients are required for confirmation.

• Journal of Veterinary Clinics
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• v.23 no.2
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• pp.105-110
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• 2006

A three-layer, feed-forward artificial neural network (ANN) with sixteen input neurons, three hidden neurons, and one output neuron was developed to identify the presence of infectious bronchitis (IB) infection as early as possible in laying hen flocks. Retrospective data from flocks that enrolled IB surveillance program between May 2003 and November 2005 were used to build the ANN. Data set of 86 flocks was divided randomly into two sets: 77 cases for training set and 9 cases for testing set. Input factors were 16 epidemiological findings including characteristics of the layer house, management practice, flock size, and the output was either presence or absence of IB. ANN was trained using training set with a back-propagation algorithm and test set was used to determine the network's capability to predict outcomes that it has never seen. Diagnostic performance of the trained network was evaluated by constructing receiver operating characteristic (ROC) curve with the area under the curve (AUC), which were also used to determine the best positivity criterion for the model. Several different ANNs with different structures were created. The best-fitted trained network, IBV_D1, was able to predict IB in 73 cases out of 77 (diagnostic accuracy 94.8%) in the training set. Sensitivity and specificity of the trained neural network was 95.5% (42/44, 95% CI, 84.5-99.4) and 93.9% (31/33, 95% CI, 79.8-99.3), respectively. For testing set, AVC of the ROC curve for the IBV_D1 network was 0.948 (SE=0.086, 95% CI 0.592-0.961) in recognizing IB infection status accurately. At a criterion of 0.7149, the diagnostic accuracy was the highest with a 88.9% with the highest sensitivity of 100%. With this value of sensitivity and specificity together with assumed 44% of IB prevalence, IBV_D1 network showed a PPV of 80% and an NPV of 100%. Based on these findings, the authors conclude that neural network can be successfully applied to the development of a screening model for identifying IB infection in laying hen flocks.

• The Korean Journal of Nuclear Medicine
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• v.33 no.2
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• pp.131-142
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• 1999

Purpose: Either gated myocardial perfusion SPECT or attenuation corrected SPECT can be used to improve specificity in the diagnosis of coronary artery disease. We investigated in this study whether gating or attenuation correction improved diagnostic performance of rest/stress perfusion SPECT in patients having intermediate pre-test likelihood of coronary artery disease. Materials and Methods: Sixty-eight patients underwent rest attenuation-corrected T1-20l/dipyridamole stress gated attenuation-corrected Tc-99m -MIBI SPECT using an ADAC vertex camera (M:F=29:39, aged $59{\pm}12$ years, coronary artery stenosis ${\geq}70%$, one vessel: 13, two vessel: 18, three vessel: 8, normal: 29). Using a five-point scale, three physicians graded the post-test likelihood of coronary artery disease for each arterial territory (1:normal, 2: possibly normal, 3:equivocal, 4. possibly abnormal, 5: abnormal). Sensitivity, specificity and area under receiver-operating-characteristic curves were compared for each operator between three methods : (A) non-attenuation-corrected SPECT; (B) gated SPECT added to (A): and (C) attenuation-corrected SPECT added to (B). Results: When grade 3 was used as the criteria for coronary artery disease, no differences in sensitivity and specificity were found between the three methods for each operator. Areas under receiver-operating-characteristic curves for diagnosis of coronary artery disease revealed no differences between each modality (p>0.05). Conclusion: In patients at intermediate risk of coronary artery disease, gated SPECT and attenuation- corrected SPECT did not improve diagnostic performance.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.38-42
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• 2019

Purpose Although computed tomography (CT) is used for coronary artery calcification, it is difficult to differentiate between high risk microcalcifications. Studies have shown that $^{18}F$-sodium fluoride ($^{18}F-NaF$) is very useful for the diagnosis of microcalcifications. In this study, we aimed to evaluate the usefulness of $^{18}F-NaF$ PET imaging in quantitative evaluation of calcification. Materials and Methods A total of 45 patients ($67.1{\pm}6.9years\;old$) were injected with 250 MBq of $^{18}F-NaF$ for 1 hour and images were acquired for 30 minutes. All patients underwent CT angiography (CTAngiography, CTA) before the PET scan. The SUVmax of calcification was measured and the background radioactivity of the left atrium was measured to determine Target to Background (TBR) and quantitatively analyzed. High risk group was classified through ROC curve (Receiver Operating Characteristic Curve). Results There were 226 coronary artery calcifications in the cohort and SUVmax was $1.15{\pm}0.39$. Of the 28 patients (62%), 58 were classified as high risk (TBR > 1.25). The remaining 168 were $TBR{\leq}1.25$. Conclusion $^{18}F-NaF$ PET images were available for quantitative assessment of microcalcifications and could be classified into high-risk groups. The combination of angiographic CT and $^{18}F-NaF$ PET may be a new method for early diagnosis of high-risk microcalcifications.