• Dementia and Neurocognitive Disorders
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• v.23 no.1
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• pp.11-21
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• 2024

Background and Purpose: Although dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia, its clinical prevalence is low. We developed a short and easy-to-complete DLB screening questionnaire (DLBSQ) to raise diagnostic sensitivity in routine clinical settings. Methods: A total of 501 participants were retrospectively enrolled, including 71 controls, 184 patients without DLB, and 246 patients with probable DLB. All patients underwent clinical evaluation, including core features of DLB, the DLBSQ, brain magnetic resonance imaging, and detailed neuropsychological assessments. The diagnostic performance of the DLBSQ for probable DLB was investigated using a receiver operating characteristic curve analysis. Results: Total DLBSQ score was associated with visuospatial and frontal/executive dysfunction and the diagnosis of probable DLB. The area under the receiver operating characteristic curve for total DLBSQ score was 0.727. Youden's method revealed an optimal cutoff value of 3. The sensitivity and specificity of the DLBSQ were 68.7% and 62.4%, respectively. Its discriminating performance improved when cognitive test profiles were additionally considered (area under the curve: 0.822, sensitivity: 80.6%, and specificity: 70.4%). Conclusions: The DLBSQ might be a useful screening tool for DLB in routine clinical practice with good sensitivity and specificity.

• Korean Journal of Radiology
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• v.25 no.1
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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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• v.14 no.10
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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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• v.13 no.3
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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.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.26 no.3
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• pp.277-280
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• 2022

Backgrounds/Aims: Biliary colic is a common cause of emergency department (ED) visits; however, the natural history of the disease and thus the indications for urgent or scheduled surgery remain unclear. Limitations of previous attempts to elucidate this natural history at a population level are based on the reliance on the identification of biliary colic via administrative codes in isolation. The purpose of our study was to validate the use of International Statistical Classification of Diseases and Related Health Problems codes, 10th Revision, Canadian modification (ICD-10-CA) from ED visits in adequately differentiating patients with biliary colic from those with other biliary diagnoses such as cholecystitis or common bile duct stones. Methods: We performed a retrospective validation study using administrative data from two large academic hospitals in Toronto. We assessed all the patients presenting to the ED between January 1, 2012 and December 31, 2018, assigned ICD-10-CA codes in keeping with uncomplicated biliary colic. The codes were compared to the individually abstracted charts to assess diagnostic agreement. Results: Among the 991 patient charts abstracted, 26.5% were misclassified, corresponding to a positive predictive value of 73% (95% confidence interval 73%-74%). The most frequent reasons for inaccurate diagnoses were a lack of gallstones (49.8%) and acute cholecystitis (27.8%). Conclusions: Our findings suggest that the use of ICD-10 codes as the sole means of identifying biliary colic to the exclusion of other biliary pathologies is prone to moderate inaccuracy. Previous investigations of biliary colic utilizing administrative codes for diagnosis may therefore be prone to unforeseen bias.

• Bioinformatics and Biosystems
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• v.1 no.1
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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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• v.46 no.1
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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.

• Journal of Sasang Constitutional Medicine
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• v.27 no.2
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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.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.4
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• pp.414-419
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• 2019

JC polyomavirus (JCPyV) is a human pathogenic virus belonging to the family Polyomaviridae, a viral group containing dsDNA nucleic acid. A recent recommendation is to apply the presence of JCPyV as a fecal indicator for water contamination in environments like sewage, and techniques to monitor JCPyV in water are being proposed. To date, the conventional PCR system has been applied as a diagnostic method for detecting JCPyV. There is a need for a more rapid and sensitive JCPyV diagnostic detection method in clinical and environmental samples. In this study, we developed a loop-mediated isothermal amplification (LAMP) primer set for the detection of JCPyV. Our results indicate that the LAMP method using a specific primer set shows about 10-fold higher detection sensitivity than the conventional PCR system. The effectiveness of the LAMP method developed in this study has been validated by PCR product digestion using the HaeIII restriction enzyme. We, therefore, propose that the LAMP method using a specific primer set can be applied as a rapid and sensitive detection method for monitoring JCPyV in clinical and environmental samples.

• Korean Journal of Radiology
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• v.22 no.4
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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.