• The korean journal of orthodontics
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• v.52 no.1
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• pp.3-19
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• 2022

Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.96-106
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• 2022

Objective : The most common complication of anterior cervical discectomy and fusion (ACDF) is cage subsidence and maintenance of disc height affects postoperative clinical outcomes. We considered cage subsidence as an inappropriate indicator for evaluating preservation of disc height. Thus, this study aimed to consider patients with complications such as reduced total disc height compared to that before surgery and evaluate the relevance of several factors before ACDF. Methods : We retrospectively reviewed the medical records of 40 patients who underwent stand-alone single-level ACDF using a polyetheretherketone (PEEK) cage at our institution between January 2012 and December 2018. Our study population comprised 19 male and 21 female patients aged 24-70 years. The minimum follow-up period was 1 year. Twenty-seven patients had preoperative bone mineral density (BMD) data on dual-energy X-ray absorptiometry. Clinical parameters included sex, age, body mass index, smoking history, and prior medical history. Radiologic parameters included the C2-7 cobb angle, segmental angle, sagittal vertical axis, disc height, and total intervertebral height (TIH) at the preoperative and postoperative periods. Cage decrement was defined as the reduction in TIH at the 6-month follow-up compared to preoperative TIH. To evaluate the bone quality, Hounsfield unit (HU) value was calculated in the axial and sagittal images of conventional computed tomography. Results : Lumbar BMD values and cervical HU values were significantly correlated (r=0.733, p<0.001). We divided the patients into two groups based on cage decrement, and 47.5% of the total patients were regarded as cage decrement. There were statistically significant differences in the parameters of measuring the HU value of the vertebra and intraoperative distraction between the two groups. Using these identified factors, we performed a receiver operating characteristic (ROC) curve analysis. Based on the ROC curve, the cut-off point was 530 at the HU value of the upper cortical and cancellous vertebrae (p=0.014; area under the curve [AUC], 0.727; sensitivity, 94.7%; specificity, 42.9%) and 22.41 at intraoperative distraction (p=0.017; AUC, 0.722; sensitivity, 85.7%; specificity, 57.9%). Using this value, we converted these parameters into a bifurcated variable and assessed the multinomial regression analysis to evaluate the risk factors for cage decrement in ACDF. Intraoperative distraction and HU value of the upper vertebral body were independent factors of postoperative subsidence. Conclusion : Insufficient intraoperative distraction and low HU value showed a strong relationship with postoperative intervertebral height reduction following single stand-alone PEEK cage ACDF.

• Imaging Science in Dentistry
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• v.52 no.3
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• pp.267-273
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• 2022

Purpose: The aim of this study was to assess the influence of kilovoltage- peak (kVp) and the metal artifact reduction (MAR) tool on the detection of buccal and lingual peri-implant dehiscence in the presence of titanium-zirconia (Ti-Zr) and zirconia (Zr) implants in cone-beam computed tomography (CBCT) images. Materials and Methods: Twenty implant sites were created in the posterior region of human mandibles, including control sites (without dehiscence) and experimental sites (with dehiscence). Individually, a Ti-Zr or Zr implant was placed in each implant site. CBCT scans were performed using a Picasso Trio device, with variation in the kVp setting (70 or 90 kVp) and whether the MAR tool was used. Three oral radiologists scored the detection of dehiscence using a 5-point scale. The area under the receiver operating characteristic (ROC) curve, sensitivity, and specificity were calculated and compared by multi-way analysis of variance (α=0.05). Results: The kVp, cortical plate involved (buccal or lingual cortices), and MAR did not influence any diagnostic values (P>0.05). The material of the implant did not influence the ROC curve values(P>0.05). In contrast, the sensitivity and specificity were statistically significantly influenced by the implant material (P<0.05) with Zr implants showing higher sensitivity values and lower specificity values than Ti-Zr implants. Conclusion: The detection of peri-implant dehiscence was not influenced by kVp, use of the MAR tool, or the cortical plate. Greater sensitivity and lower specificity were shown for the detection of peri-implant dehiscence in the presence of a Zr implant.

• Nutrition Research and Practice
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• v.16 no.5
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• pp.604-615
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• 2022

BACKGROUND/OBJECTIVES: This study aimed to investigate cancer-specific survival (CSS) and associated risk factors in elderly gastric cancer (EGC) patients. SUBJECTS/METHODS: EGC patients (≥ 70 yrs) who underwent curative gastrectomy between January 2013 and December 2017 at our hospital were included. Clinicopathologic characteristics and survival data were collected. Receiver operating characteristic (ROC) analysis was used to extract the best cutoff point for body mass index (BMI). A Cox proportional hazards model was used to determine the risk factors for CSS. RESULTS: In total, 290 EGC patients were included, with a median age of 74.7 yrs. The median follow-up time was 31 (1-77) mon. The postoperative 1-yr, 3-yr and 5-yr CSS rates were 93.7%, 75.9% and 65.1%, respectively. Univariate analysis revealed risk factors for CSS, including age (hazard ratio [HR] = 1.08; 95% confidence interval [CI], 1.01-1.15), intensive care unit (ICU) admission (HR = 1.73; 95% CI, 1.08-2.79), nutritional risk screening (NRS 2002) score ≥ 5 (HR = 2.33; 95% CI, 1.49-3.75), and preoperative prognostic nutrition index score < 45 (HR = 2.06; 95% CI, 1.27-3.33). The ROC curve showed that the best BMI cutoff value was 20.6 kg/m². Multivariate analysis indicated that a BMI ≤ 20.6 kg/m² (HR = 2.30; 95% CI, 1.36-3.87), ICU admission (HR = 1.97; 95% CI, 1.17-3.30) and TNM stage (stage II: HR = 5.56; 95% CI, 1.59-19.43; stage III: HR = 16.20; 95% CI, 4.99-52.59) were significantly associated with CSS. CONCLUSIONS: Low BMI (≤ 20.6 kg/m²), ICU admission and advanced pathological TNM stages (II and III) are independent risk factors for CSS in EGC patients after curative gastrectomy. Nutrition support, better perioperative management and early diagnosis would be helpful for better survival.

• The Korean Journal of Pain
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• v.36 no.1
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• pp.113-127
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• 2023

Background: Resting-state functional connectivity (rs-FC) may aid in understanding the link between painmodulating brain regions and the descending pain modulatory system (DPMS) in fibromyalgia (FM). This study investigated whether the differences in rs-FC of the primary somatosensory cortex in responders and non-responders to the conditioned pain modulation test (CPM-test) are related to pain, sleep quality, central sensitization, and the impact of FM on quality of life. Methods: This cross-sectional study included 33 females with FM. rs-FC was assessed by functional magnetic resonance imaging. Change in the numerical pain scale during the CPM-test assessed the DPMS function. Subjects were classified either as non-responders (i.e., DPMS dysfunction, n = 13) or responders (n = 20) to CPM-test. A generalized linear model (GLM) and a receiver operating characteristic (ROC) curve analysis were performed to check the accuracy of the rs-FC to differentiate each group. Results: Non-responders showed a decreased rs-FC between the left somatosensory cortex (S1) and the periaqueductal gray (PAG) (P < 0.001). The GLM analysis revealed that the S1-PAG rs-FC in the left-brain hemisphere was positively correlated with a central sensitization symptom and negatively correlated with sleep quality and pain scores. ROC curve analysis showed that left S1-PAG rs-FC offers a sensitivity and specificity of 85% or higher (area under the curve, 0.78, 95% confidence interval, 0.63-0.94) to discriminate who does/does not respond to the CPM-test. Conclusions: These results support using the rs-FC patterns in the left S1-PAG as a marker for predicting CPM-test response, which may aid in treatment individualization in FM patients.

• Investigative Magnetic Resonance Imaging
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• v.26 no.1
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• pp.10-19
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• 2022

Purpose: To evaluate whether the added value of contrast leakage information from dynamic susceptibility contrast magnetic resonance imaging (DSC MRI) is a better prognostic imaging biomarker than the cerebral blood volume (CBV) value in distinguishing true progression from pseudoprogression in glioblastoma patients. Materials and Methods: Forty-nine glioblastoma patients who had undergone MRI after concurrent chemoradiotherapy with temozolomide were enrolled in this retrospective study. Twenty features were extracted from the normalized relative CBV (nCBV) and extraction fraction (EF) map of the contrast-enhancing region in each patient. After univariable analysis, we used multivariable stepwise logistic regression analysis to identify significant predictors for differentiating between pseudoprogression and true progression. Receiver operating characteristic (ROC) analysis was employed to determine the best cutoff values for the nCBV and EF features. Finally, leave-one-out cross-validation was used to validate the best predictor in differentiating between true progression and pseudoprogression. Results: Multivariable stepwise logistic regression analysis showed that MGMT (O⁶-methylguanine-DNA methyltransferase) and EF max were independent differentiating variables (P = 0.004 and P = 0.02, respectively). ROC analysis yielded the best cutoff value of 95.75 for the EF max value for differentiating the two groups (sensitivity, 61%; specificity, 84.6%; AUC, 0.681 ± 0.08; 95% CI, 0.524-0.837; P = 0.03). In the leave-one-out cross-validation of the EF max value, the cross-validated values for predicting true progression and pseudoprogression accuracies were 69.4% and 71.4%, respectively. Conclusion: We demonstrated that contrast leakage information parameter from DSC MRI showed significance in differentiating true progression from pseudoprogression in glioblastoma patients.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.367-377
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• 2023

This study investigates the utility of the Triglyceride-glucose(TyG) index and Cardiometabolic Index(CMI) as predictors for diagnosing metabolic syndrome. The study involved 1970 males, 1459 females, totaling 3429 participants who underwent health checkups at P Hospital in Busan between January 2023 and June 2023. Metabolic syndrome diagnosis was based on the presence of 3 or more risk factors out of the 5 criteria outlined by the American Heart Association/National Heart, Lung, and Blood Institute(AHA/NHLBI), and participants with 2 or fewer risk factors were categorized as normal. Statistical analyses included independent sample t-tests, chi-square tests, Pearson's correlation analysis, Receiver Operating Characteristic(ROC) curve analysis, and logistic regression analysis, using the Statistical Package for the Social Sciences(SPSS) program. Significance was established at p<0.05. The comparison revealed that the metabolic syndrome group exhibited attributes such as advanced age, male gender, elevated systolic and diastolic blood pressures, high blood sugar, elevated triglycerides, reduced LDL-C, elevated HDL-C, higher Cardiometabolic Index, Triglyceride-glucose index, and components linked to abdominal obesity. Pearson correlation analysis showed strong positive correlations between waist circumference/height ratio, waist circumference, Cardiometabolic Index, and triglycerides. Weak positive correlations were observed between LDL-C, body mass index, and Cardiometabolic index, while a strong negative correlation was found between Cardiometabolic Index and HDL-C. ROC analysis indicated that the Cardiometabolic Index(CMI), Triglyceride-glucose(TyG) index, and waist circumference demonstrated the highest Area Under the Curve(AUC) values, indicating their efficacy in diagnosing metabolic syndrome. Optimal cut-off values were determined as >1.34, >8.86, and >84.5 for the Cardiometabolic Index, Triglyceride-glucose index, and waist circumference, respectively. Logistic regression analysis revealed significant differences for age(p=0.037), waist circumference(p<0.001), systolic blood pressure(p<0.001), triglycerides(p<0.001), LDL-C(p=0.028), fasting blood sugar(p<0.001), Cardiometabolic Index(p<0.001), and Triglyceride-glucose index (p<0.001). The odds ratios for these variables were 1.015, 1.179, 1.090, 3.03, and 69.16, respectively. In conclusion, the Cardiometabolic Index and Triglyceride-glucose index are robust predictive indicators closely associated with metabolic syndrome diagnosis, and waist circumference is identified as an excellent predictor. Integrating these variables into clinical practice holds the potential for enhancing early diagnosis and prevention of metabolic syndrome.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.681-689
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• 2023

Objective : Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm. Methods : A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant. Results : The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided. Conclusion : Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.620-631
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• 2022

Purpose This study aimed to investigate the diagnostic performance of features suggestive of nodal metastasis on preoperative MRI in patients with invasive breast cancer. Materials and Methods We retrospectively reviewed the preoperative breast MRI of 192 consecutive patients with surgically proven invasive breast cancer. We analyzed MRI findings of axillary lymph nodes with regard to the size, long/short ratio, cortical thickness, shape and margin of the cortex, loss of hilum, asymmetry, signal intensity (SI) on T2-weighted images (T2WI), degree of enhancement in the early phase, and enhancement kinetics. Receiver operating characteristic (ROC) analysis, chi-square test, t test, and McNemar's test were used for statistical analysis. Results Increased shorter diameter, uneven cortical shape, increased cortical thickness, loss of hilum, asymmetry, irregular cortical margin, and low SI on T2WI were significantly suggestive of metastasis. ROC analysis revealed the cutoff value for the shorter diameter and cortical thickness as 8.05 mm and 2.75 mm, respectively. Increased cortical thickness (> 2.75 mm) and uneven cortical shape showed significantly higher sensitivity than other findings in McNemar's test. Irregular cortical margins showed the highest specificity (100%). Conclusion Cortical thickness > 2.75 mm and uneven cortical shape are more sensitive parameters than other findings, and an irregular cortical margin is the most specific parameter for predicting axillary metastasis in patients with invasive breast cancer.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.189-198
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• 2024

Objective: To investigate the prognostic utility of radiomics features extracted from ¹⁸F-fluorodeoxyglucose (FDG) PET/CT combined with clinical factors and metabolic parameters in predicting progression-free survival (PFS) and overall survival (OS) in individuals diagnosed with extranodal nasal-type NK/T cell lymphoma (ENKTCL). Materials and Methods: A total of 126 adults with ENKTCL who underwent ¹⁸F-FDG PET/CT examination before treatment were retrospectively included and randomly divided into training (n = 88) and validation cohorts (n = 38) at a ratio of 7:3. Least absolute shrinkage and selection operation Cox regression analysis was used to select the best radiomics features and calculate each patient's radiomics scores (RadPFS and RadOS). Kaplan-Meier curve and Log-rank test were used to compare survival between patient groups risk-stratified by the radiomics scores. Various models to predict PFS and OS were constructed, including clinical, metabolic, clinical + metabolic, and clinical + metabolic + radiomics models. The discriminative ability of each model was evaluated using Harrell's C index. The performance of each model in predicting PFS and OS for 1-, 3-, and 5-years was evaluated using the time-dependent receiver operating characteristic (ROC) curve. Results: Kaplan-Meier curve analysis demonstrated that the radiomics scores effectively identified high- and low-risk patients (all P < 0.05). Multivariable Cox analysis showed that the Ann Arbor stage, maximum standardized uptake value (SUVmax), and RadPFS were independent risk factors associated with PFS. Further, β2-microglobulin, Eastern Cooperative Oncology Group performance status score, SUVmax, and RadOS were independent risk factors for OS. The clinical + metabolic + radiomics model exhibited the greatest discriminative ability for both PFS (Harrell's C-index: 0.805 in the validation cohort) and OS (Harrell's C-index: 0.833 in the validation cohort). The time-dependent ROC analysis indicated that the clinical + metabolic + radiomics model had the best predictive performance. Conclusion: The PET/CT-based clinical + metabolic + radiomics model can enhance prognostication among patients with ENKTCL and may be a non-invasive and efficient risk stratification tool for clinical practice.