• Korean Journal of Radiology
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• 제25권1호
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

• Asian Pacific Journal of Cancer Prevention
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• 제14권10호
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• pp.6069-6075
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• 2013

Background: At present, the diagnosis of colorectal cancer (CRC) requires a colorectal biopsy which is an invasive procedure. We undertook this pilot study to develop an alternative method and potential new biomarkers for diagnosis, and validated a set of well-integrated tools called ClinProt to investigate the serum peptidome in CRC patients. Methods: Fasting blood samples from 67 patients diagnosed with CRC by histological diagnosis, 55 patients diagnosed with colorectal adenoma by biopsy, and 65 healthy volunteers were collected. Division was into a model construction group and an external validation group randomly. The present work focused on serum proteomic analysis of model construction group by ClinProt Kit combined with mass spectrometry. This approach allowed construction of a peptide pattern able to differentiate the studied populations. An external validation group was used to verify the diagnostic capability of the peptidome pattern blindly. An immunoassay method was used to determine serum CEA of CRC and controls. Results: The results showed 59 differential peptide peaks in CRC, colorectal adenoma and health volunteers. A genetic algorithm was used to set up the classification models. Four of the identified peaks at m/z 797, 810, 4078 and 5343 were used to construct peptidome patterns, achieving an accuracy of 100% (> CEA, P<0.05). Furthermore, the peptidome patterns could differentiate the validation group with high accuracy close to 100%. Conclusions: Our results showed that proteomic analysis of serum with MALDI-TOF MS is a fast and reproducible approach, which may provide a novel approach to screening for CRC.

• Genomics & Informatics
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• 제13권3호
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• pp.70-75
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• 2015

MicroRNAs (miRNAs) have been demonstrated to play an important role in carcinogenesis. Previous studies revealed that miRNAs are present in human plasma in a remarkably stable form that is protected from endogenous RNase activity. In this study, we measured the plasma expression levels of three miRNAs (miR-21, miR-27a, and miR-155) to investigate the usefulness of miRNAs for gastric cancer detection. We initially examined plasma miRNA expression levels in a screening cohort consisting of 15 patients with gastric cancer and 15 healthy controls from Korean population, using TaqMan quantitative real-time polymerase chain reaction. We observed that the expression level of miR-27a was significantly higher in patients with gastric cancer than in healthy controls, whereas the miR-21 and miR-155a expression levels were not significantly higher in the patients with gastric cancer. Therefore, we further validated the miR-27a expression level in 73 paired gastric cancer tissues and in a validation plasma cohort from 35 patients with gastric cancer and 35 healthy controls. In both the gastric cancer tissues and the validation plasma cohort, the miR-27a expression levels were significantly higher in patients with gastric cancer. Receiver-operator characteristic (ROC) analysis of the validation cohort, revealed an area under the ROC curve value of 0.70 with 75% sensitivity and 56% specificity in discriminating gastric cancer. Thus, the miR-27a expression level in plasma could be a useful biomarker for the diagnosis and/or prognosis of gastric cancer.

• Bioinformatics and Biosystems
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• 제1권1호
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• pp.28-37
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• 2006

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA micro arrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.

• Imaging Science in Dentistry
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• 제46권1호
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• pp.9-16
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• 2016

Purpose: To evaluate the upper airway dimensions of obstructive sleep apnea (OSA) and control subjects using a cone-beam computed tomography (CBCT) unit commonly applied in clinical practice in order to assess airway dimensions in the same fashion as that routinely employed in a clinical setting. Materials and Methods: This was a retrospective analysis utilizing existing CBCT scans to evaluate the dimensions of the upper airway in OSA and control subjects. The CBCT data of sixteen OSA and sixteen control subjects were compared. The average area, average volume, total volume, and total length of the upper airway were computed. Width and anterior-posterior (AP) measurements were obtained on the smallest axial slice. Results: OSA subjects had a significantly smaller average airway area, average airway volume, total airway volume, and mean airway width. OSA subjects had a significantly larger airway length measurement. The mean A-P distance was not significantly different between groups. Conclusion: OSA subjects have a smaller upper airway compared to controls with the exception of airway length. The lack of a significant difference in the mean A-P distance may indicate that patient position during imaging (upright vs. supine) can affect this measurement. Comparison of this study with a future prospective study design will allow for validation of these results.

• 사상체질의학회지
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• 제27권2호
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• pp.211-221
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• 2015

Objectives The aim of this study is to develop a Korea Sasang Constitutional Diagnostic Questionnaire (KS-15) with practicality and validity. Methods The data of body shape, temperament and symptoms were collected from 11 nationwide multi-centers in Korean Medical Clinics between Nov. 2009 to Aug. 2012. KS-15 algorithm was developed through Multinomial Logistic Regression and was applied for test group to verify it's classificatory function. Results The weight value of variables of KS-15 were different between male and female. The concordance of KS-15 with the expert in training group was 58.34% (72.8% in Tae-eumin, 54.8% in Soeumin, and 44.1% in Soyangin). The concordance of KS-15 with the expert in test group was 63.1% (63% in Tae-eumin, 83.3% in Soeumin, and 51.9% in Soyangin). Conclusions KS-15 seems to have suitable implement with practicality and validity. Further study is necessary to verify it accuracy and cut-off.

• 대한임상검사과학회지
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• 제51권4호
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• pp.414-419
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• 2019

JC polyomavirus (JCPyV)는 viral group I, Polyomaviridae로 분류되는 사람 병원성 바이러스 이다. JCPyV는 최근 하수 등 수질오염 지표로 제안됨에 따라 수질환경에서 모니터링 필요성이 제기되고 있다. 임상 및 환경 시료 중 JCPyV 검출을 위해서 PCR 시스템이 사용되어 왔다. 그러나 신속하고 높은 검출 민감도를 가진 방법의 필요성에 따라 이번 연구에서는 등온증폭 프라이머 조합을 개발하였다. 이번에 개발한 방법은 기존 PCR 시스템에 비해 더욱 신속 및 약 10배 더 높은 검출 민감도를 보여주었다. 또한 본 연구에서 개발한 검출 방법의 재 검정을 위해서 HaeIII 제한효소를 이용한 방법을 함께 고안하였다. 따라서 이번 연구는 임상, 환경 등의 시료에서 JCPyV를 모니터링 하기 위한 방법으로 활용이 기대된다.

• Korean Journal of Radiology
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• 제22권4호
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• pp.612-623
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• 2021

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988-0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618-0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion: The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.

• 한국임상수의학회지
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• 제18권4호
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• pp.329-333
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• 2001

새로 개발되거나 혹은 기존의 어떤 진단검사를 다양한 임상상황에 적용하기 위해서는 먼저 이들 검사법의 진단적 정확도를 추정하는 연구가 반드시 선행되어야 한다. 진단의 정확도에 대한 추정치를 모른다면 검사결과를 해석하는 것이 불가능하기 때문이다. 특히 동일한 개체에서 감염부위별로 3개 이상의 시료를 얻어 진단검사를 적용하는 경우 각 시료의 검사결과는 독립적인 측정시료가 아니라 개체내에서 연관성이 매우 높은 종속적인 시료에 해당 한다. 즉 동일한 개체에서 얻은 시료일수록 검사결과에서 유사한 반응을 보이며 이 경우 분석의 단위는 각각의 개체가 아니라 검사부위가 되는데 이는 의학연구에서 매우 흔하다. 본 연구에서는 Helicobacter 균에 의한 감염을 검출하기 위하여 동일한 개로부터 위의 해부학적 구조상 pyloric antrum, body 및 cardia의 생검시료에 대하여 urease 검사와 PCR 검사를 적용하여 각 검사의 진단적 정확도를 추정하였다. urease 검사의 민감도와 특이도는 0.74 (95% 신뢰구간: 0.64-0.84)와 0.87 (95% 신뢰구간: 0.67-1.00)이었으며 PCR 검사의 민감도와 특이도는 0.95 (95% 신뢰구간: 0.89-1.00)와 0.90 (95% 신뢰구간: 0.70-1.00)로 두 검사의 특이도는 높은 것으로 나타났다. 그러나 PCR 검사에 비하여 urease 검사의 경우 가음성 (false negative)의 가능성이 높기 때문에 진단결과에 대한 신중한 해석이 요구된다.

• 과학교육연구지
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• 제45권3호
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• pp.349-363
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• 2021

이 연구의 목적은 학교 STEAM 교육의 실행과 교육환경 기반을 진단하고 평가할 수 있는 학교 STEAM 교육 역량 진단 도구를 개발하는 것이다. 진단 도구의 개발은 STEAM 교육의 평가 또는 성과와 관련된 문헌 조사, 연구진의 반성적 재검토, 전문가 및 현장교사의 타당도 검증 등으로 이루어졌다. 학교 STEAM 교육 역량 진단 도구는 'STEAM 교육의 실천과 지속가능성의 계획', 'STEAM 교육과정 및 교수학습 방법', 'STEAM 학습 전문성 개발', '과정 중심 평가', '고등 교육 기관, 산업 파트너, 기술 센터와 연계 구축' 등 5개 영역과 하위영역의 총 14문항으로 구성된다. 학교 STEAM 역량 진단 도구의 타당화는 전문가의 내용 타당도 검증과 예비조사(pilot study)의 학교 교사의 실제에 의한 타당도를 통해 진행하였다. 개발된 학교 STEAM 역량 진단 도구를 활용하여 초등, 중, 고등학교 267개교를 진단한 결과, 5개 영역 평균이 1.46 ~ 2.18의 수준으로 나타났다. 이 진단 도구는 학교의 STEAM 교육의 실행 및 효과를 포괄적으로 진단·평가하고, 우리나라 STEAM 교육의 실행을 진단하고 이해하는데 기초 자료로 활용될 것으로 기대한다.