• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.961-968
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• 2022

Rotator cuff tears are a leading cause of shoulder pain in adults. Due to the increase in social activities, the number of patients complaining of shoulder pain is increasing, and interest in shoulder diseases is also increasing. With the development of ultrasound equipment, the sensitivity and specificity of diagnosis are high, and it is used to diagnose rotator cuff tears in musculoskeletal disease. Ultrasound is recognized as a complementary method to MRI examination in rotator cuff tears. Therefore, this study aimed to find out the diagnostic usefulness of ultrasound and MRI examinations in the diagnosis of shoulder rotator cuff tears.A retrospective analysis was performed on 262 patients who were diagnosed with final rotator cuff damage by arthroscopy after completing ultrasound and MRI examinations. Sensitivity, feature, positive predictive value, image predictive value, and touch were disassembled for the test results. In addition, the degree of clavicular tear was scored and recorded in 5 stages. Ultrasound examination was similar to MRI examination results for both full-thickness and partial tears, and there was no statistically significant difference. Partial tear test results showed higher positive predictive value and accuracy than MRI test. In conclusion, ultrasound can be fully utilized as a screening test for rotator cuff disease, and it is thought that it will be selected and used clinically according to the patient's constitution and situation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2893-2900
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• 2014

Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.

• Journal of Korean Neurosurgical Society
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• v.42 no.2
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• pp.92-96
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• 2007

Objective : The authors have speculated that metastatic brain lesions from renal cell carcinoma (RCC) show diverse radiological patterns and tumor responses after Gamma knife surgery (GKS), and have hypothesized that these can be predicted from tumor radiological characteristics. The goal of the current study was to identify the radiological characteristics of RCC brain metastases and the predictors of initial radiosurgical response after GKS. Methods : A retrospective analysis was performed on 48 lesions in 18 patients with RCC brain metastasis treated by GKS. The radiological characteristics of these lesions in magnetic resonance images (MRI) were classified into 3 categories according to enhancement patterns in T1-weighted images and signal intensity characteristics in T2-weighted images. Responses to GKS were analyzed according to these categories, and in addition, other potential predictive factors were also evaluated. Results : MRI findings in the three categories were diverse, though numbers of the lesion were comparable. At 2-month MRI follow-ups after GKS, response rate was 54% and the local tumor control rate 83%. T2 signal intensity was found to be the principal predictive factor of response to GKS, namely negative predictive factor. Other variables such as age, sex, tumor volume, dose, duration from initial diagnosis to GKS, and previous systemic therapies failed to show significant relationships with treatment response by multivariate analysis. Conclusion : Careful evaluation of the radiological characteristics of brain metastases from RCC is important prior to GKS because MRI heterogeneity has predictive value in terms of determining initial tumor response.

• Imaging Science in Dentistry
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• v.45 no.3
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• pp.147-151
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• 2015

Purpose: The aim of this study was to investigate the effects of metal artifacts on the accurate diagnosis of root fractures using cone-beam computed tomography (CBCT) images with large and small/limited fields of view (FOVs). Materials and Methods: Forty extracted molar and premolar teeth were collected. Access canals were made in all teeth using a rotary system. In half of the teeth, fractures were created by the application of mild pressure with a hammer. The teeth were then randomly put into a wax rim on an acryl base designed in the shape of a mandible. CBCT scans were obtained using a Newtom 5G system with FOVs of $18cm{\times}16cm$ and $6cm{\times}6cm$. A metal pin was then placed into each tooth, and CBCT imaging was again performed using the same fields of view. All scans were evaluated by two oral and maxillofacial radiologists. The specificity, sensitivity, positive predictive value, negative predictive value, and likelihood ratios (positive and negative) were calculated. Result: The maximum levels of sensitivity and specificity (100% and 100%, respectively) were observed in small-volume CBCT scans of teeth without pins. The highest negative predictive value was found in the small-volume group without pins, whereas the positive predictive value was 100% in all groups except the large-volume group with pins. Conclusion: The specificity of CBCT decreased with the presence of a pin in the large-volume group, but not in the small-volume group.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.107-117
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• 2022

Purpose : The purpose of this study was to establish a model of the predictive factors for success or failure of examinees undertaking the Korean physical therapist licensing examination (KPTLE). Additionally, we assessed the pass/fail cut-off point. Methods : We analyzed the results of 10,881 examinees who undertook the KPTLE, using data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was the test result (pass or fail), and the input variables were: sex, age, test subject, and total score. Frequency analysis, chi-square test, descriptive statistics, independent t-test, correlation analysis, binary logistic regression, and receiver operating characteristic (ROC) curve analyses were performed on the data. Results : Sex and age were not significant predictors of attaining a pass (p>.05). The test subjects with the highest probability of passing were, in order, medical regulation (MR) (Odds ratio (OR)=2.91, p<.001), foundations of physical therapy (FPT) (OR=2.86, p<.001), diagnosis and evaluation for physical therapy (DEPT) (OR=2.74, p<.001), physical therapy intervention (PTI) (OR=2.66, p<.001), and practical examination (PE) (OR=1.24, p<.001). The cut-off points for each subject were: FPT, 32.50; DEPT, 29.50; PTI, 44.50; MR, 14.50; and PE, 50.50. The total score (TS) was 164.50. The sensitivity, specificity, and the classification accuracy of the prediction model was 99 %, 98 %, and 99 %, respectively, indicating high accuracy. Area under the curve (AUC) values for each subject were: FPT, .958; DEPT, .968; PTI, .984; MR, .885; PE, .962; and TS, .998, indicating a high degree of fit. Conclusion : In our study, the predictive factors for passing KPTLE were identified, and the optimal cut-off point was calculated for each subject. Logistic regression was adequate to explain the predictive model. These results will provide universities and examinees with useful information for predicting their success or failure in the KPTLE.

• Korean Journal of Head & Neck Oncology
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• v.26 no.1
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• pp.3-8
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• 2010

Background : Though papillary microcarcinoma(PMC) of thyroid gland is known to have very favorable long-term prognosis, the recurrence in the neck and distant metastasis have been often reported. The predictive factors of node metastasis and tumor recurrence in clinical course were investigated to define surgical decision or guidelines in surgery of papillary microcarcinoma. Methods : The authors conducted a retrospective analysis of 216 patients of PMC treated with surgery at Department of Surgery, Busan Paik Hospital for the period from 1997 to 2007. Of these patients, 58 cases showing cervical lymph node metastasis at initial surgery were studied. Results : In overall 216 patients, the sex ratio of male to female was 1 : 9.3(male 21, female 195 cases), the mean age at the time of diagnosis was 44.7 years and the median tumor size was 6.61mm. Neck lymph node metastasis was found in 58 patients(26.9%), thyroid capsular invasion was 56 cases(25.9%), multifocality and bilaterality were found in 32(14.8%) and 29 cases(13.4%), respectively. Through statistical analysis, sex, capsular invasion, ETE, and tumor size(>5mm) were considered to be predictive factors of cervical lymph nodes metastasis. Of them, capsular invasion was the most predictive indicator of cervical lymph node metastasis on multivariate analysis. Nodal recurrence was observed in 6 of 58 patients of node positive at initial surgery. Conclusion : The cervical lymph node metastasis is known to be a risk factor of prognosis in PMC of thyroid gland. The results of this study showed four statistically significant independent predictive factors of cervical lymph node metastasis in PMC : capsular invasion, tumor size(>5mm), ETE, and sex. On multivariate analysis, capsular invasion was a great influencing factor in prediction of lymph node metastasis. Basically, patients who has predictive factors of cervical lymph node metastasis should have a thorough investigation, and close surveillance for nodal status is required in follow-up.

• The Korean Journal of Cytopathology
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• v.18 no.2
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• pp.119-125
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• 2007

Urine cytology is an important screening tool for urinary tract neoplasms. Liquid-based preparation methods, such as $ThinPrep^{(R)}$, have been introduced for non-gynecological samples. We aimed to assess the diagnostic accuracy of liquid-based preparations in urine cytology by comparing the results of the conventional Cytospin preparation method for the same samples. A total of 236 cases subject to urine cytology were enrolled in this study from January 2005 to December 2005. All cases were subjected to cystoscopy and if a malignancy was suspected, a biopsy was performed. Urine cytology slides were made using the $ThinPrep^{(R)}$ preparation method and the conventional Cytospin and/or direct smear method from the individual samples. The results of urine cytology were compared with the final cystoscopic or histological diagnoses. We analyzed the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of both cytology preparation methods. A total of 236 slides made using the liquid based method were satisfactory for slide quality, whereas 5 slides (2.1%) prepared by conventional methods were unsatisfactory because of air-drying, a thick smear, or a bloody or inflammatory background. The $ThinPrep^{(R)}$ method showed 53.1% sensitivity, 92.6% specificity, a 92,6% positive predictive value, a 94.1% negative predictive value and 85,6% accuracy, while the conventional method showed 51% sensitivity, 98.4% specificity, a 92.6% positive predictive value, a 98.4% negative predictive value and 88,6% accuracy. Although the diagnostic values were equivalent between the use of the two methods, the quality of the cytology slides and the time consumed during the microscopic examination for a diagnosis were superior for the $ThinPrep^{(R)}$ method than for the conventional method. In conclusion, our limited studies have shown that the use of the liquid based preparation method is beneficial to improve the quality of slides and reduce the duration for a microscopic examination, but did not show better sensitivity, accuracy and predictive values.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2037-2042
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• 2013

Background: Different methods of diagnosis have been found to be inefficient in terms of screening and early diagnosis of lung cancer. Cancer cells produce proteins whose serum levels may be elevated during the early stages of cancer development. Therefore, those proteins may be recognized as potential cancer markers. The aim of this study was to differentiate healthy individuals and lung cancer cases by analyzing their serum protein profiles and evaluate the efficacy of this method in the early diagnosis of lung cancer. Materials and Methods: 170 patients with lung cancer, 53 under high risk of lung cancer, and 47 healthy people were included in our study. Proteomic analysis of the samples was performed with the SELDI-TOF-MS approach. Results: The most discriminatory peak of the high risk group was 8141. When tree classification analysis was performed between lung cancer and the healthy control group, 11547 was determined as the most discriminatory peak, with a sensitivity of 85.5%, a specificity of 89.4%, a positive predictive value (PPV) of 96.7% and a negative predictive value (NPV) of 62.7%. Conclusions: We determined three different protein peaks 11480, 11547 and 11679 were only present in the lung cancer group. The 8141 peak was found in the high-risk group, but not in the lung cancer and control groups. These peaks may prove to be markers of lung cancer which suggests that they may be used in the early diagnosis of lung cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1861-1864
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• 2016

Although early diagnosis of thyroid nodule type is very important, the diagnostic accuracy of standard tests is a challenging issue. We here aimed to find an optimal combination of factors to improve diagnostic accuracy for distinguishing malignant from benign thyroid nodules before surgery. In a prospective study from 2008 to 2012, 345 patients referred for thyroidectomy were enrolled. The sample size was split into a training set and testing set as a ratio of 7:3. The former was used for estimation and variable selection and obtaining a linear combination of factors. We utilized smoothly clipped absolute deviation (SCAD) logistic regression to achieve the sparse optimal combination of factors. To evaluate the performance of the estimated model in the testing set, a receiver operating characteristic (ROC) curve was utilized. The mean age of the examined patients (66 male and 279 female) was $40.9{\pm}13.4years$ (range 15- 90 years). Some 54.8% of the patients (24.3% male and 75.7% female) had benign and 45.2% (14% male and 86% female) malignant thyroid nodules. In addition to maximum diameters of nodules and lobes, their volumes were considered as related factors for malignancy prediction (a total of 16 factors). However, the SCAD method estimated the coefficients of 8 factors to be zero and eliminated them from the model. Hence a sparse model which combined the effects of 8 factors to distinguish malignant from benign thyroid nodules was generated. An optimal cut off point of the ROC curve for our estimated model was obtained (p=0.44) and the area under the curve (AUC) was equal to 77% (95% CI: 68%-85%). Sensitivity, specificity, positive predictive value and negative predictive values for this model were 70%, 72%, 71% and 76%, respectively. An increase of 10 percent and a greater accuracy rate in early diagnosis of thyroid nodule type by statistical methods (SCAD and ANN methods) compared with the results of FNA testing revealed that the statistical modeling methods are helpful in disease diagnosis. In addition, the factor ranking offered by these methods is valuable in the clinical context.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.93-104
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• 2024

Facility diagnosis is essential for the smooth operation and life extension of rotating equipment used in industrial sites. Compared to other diagnostic methods, vibration diagnosis can find most of the initial defects, such as unbalance, alignment failure, bearing defects and resonance, compared to other diagnostic methods. Therefore, vibration analysis is the most commonly used facility diagnosis method in industrial sites, and is usefully used as a predictive preservation (PdM) technology to manage the condition of the facility. However, since the vibration diagnosis method is performed based on experience based on the standard, it is carried out by experts. Therefore, it is intended to contribute to the reliability of the facility by establishing a system that anyone can easily judge defects by establishing a vibration diagnosis method performed based on experience as a knowledgeable code system. An algorithm was developed based on the ISO-20816 standard for vibration measurement, and the reliability was verified by comparing the results of vibration measurement at various demonstration sites such as petrochemical plant compressors, hydrogen charging stations, and industrial machinery with the results of analysis using a development system. The developed algorithm can contribute to predictive maintenance (PdM) technology that anyone can diagnose the condition of the rotating machine at industrial sites and identify defects early to replace parts at the exact time of replacement. Furthermore, it is expected that it will contribute to reducing maintenance costs and downtime due to the failure of rotating machines when applied to various industrial sites such as oil refining facilities, transportation, production facilities, and aviation facilities.