Comparison of Fibroscan, Shear Wave Elastography, and Shear Wave Dispersion Measurements in Evaluating Fibrosis and Necroinflammation in Patients Who Underwent Liver Biopsy.

OBJECTIVE: Our aim was to predict these stages of hepatic fibrosis and necroinflammation using measurements from two-dimensional shear wave elastography (2D-SWE), transient elastography (Fibroscan, TE), and shear wave dispersion (SWD). MATERIALS AND METHODS: In this prospectively designed study, chronic liver patients with nonspecific etiology whose biopsy was performed for up to 1 week were included. Two-dimensional SWE, SWD, and TE measurements were performed. The METAVIR and F-ISHAK classification was used for histopathological evaluation. RESULTS: Two-dimensional SWE and TE were considered significant for detecting hepatic fibrosis. In distinguishing ≥F2, for 2D-SWE, area under the receiver operating characteristics (AUROC) was 0.86 (confidence interval [CI], 0.75-0.96) for the cutoff value of 8.05 kPa ( P = 0.003); for TE, AUROC was 0.79 (CI, 0.65-0.94) for the cutoff value of 10.4 kPa ( P < 0.001). No significance was found for TE in distinguishing ≥F3 ( P = 0.132). However, for 2D-SWE, a cutoff value of 10.45 kPa ( P < 0.001), with AUROC = 0.87 (CI, 0.78-0.97) was determined for ≥F3. Shear wave dispersion was able to determine the presence of necroinflammation ( P = 0.016) and a cutoff value of 15.25 (meter/second)/kiloHertz ([m/s]/kHz) ( P = 0.006) and AUROC of 0.71 (CI, 0.57-0.85) were calculated for distinguishing ≥A2. In addition, a cutoff value of 17.25 (m/s)/kHz ( P = 0.023) and AUROC = 0.72 (CI, 0.51-0.93) were found to detect severe necroinflammation. The cutoff value for SWD was 15.25 (m/s)/kHz ( P = 0.013) for detecting ≥A2 in the reversible stage of fibrosis (F0, F1, and F2), and AUROC = 0.72 (CI, 0.56-0.88). CONCLUSIONS: Two-dimensional SWE and TE measurements were significant in detecting the irreversible stage and the stage that should be treated in hepatic fibrosis noninvasively. Shear wave dispersion measurements were significant in detecting necroinflammation noninvasively.

State-of-the-art Prostate Imaging.

Prostate cancer is one of the most common cancers in men. In addition to methods such as prostate-specific antigen test, digital rectal examination, and transrectal ultrasonography, magnetic resonance imaging has an important role for accurate and reproducible diagnosis. However, guidance in targeted biopsies and recent use in determining localization for treatment increase its importance. Due to technical difficulties, patient tolerance, and differences in interpretation, the prostate imaging reporting and data system recommends preparations for the patient and magnetic resonance imaging techniques. However, techniques continue to be developed to improve the diagnosis rate and image quality. In our article, patient preparation before imaging and techniques were tried to be discussed in detail. In addition, current approaches in biparametric magnetic resonance imaging and radiomics and new techniques such as T1 and T2 mapping will be mentioned.

Can laboratory parameters be an alternative to CT and RT-PCR in the diagnosis of COVID-19? A machine learning approach.

In this study, a machine learning-based decision support system that uses routine laboratory parameters has been proposed in order to increase the diagnostic success in COVID-19. The main goal of the proposed method was to reduce the number of misdiagnoses in the RT-PCR and CT scans and to reduce the cost of testing. In this study, we retrospectively reviewed the files of patients who presented to the coronavirus outpatient. The demographic, thoracic CT, and laboratory data of the individuals without any symptoms of the disease, who had negative RT-PCR test and who had positive RT-PCR test were analyzed. CT images were classified using hybrid CNN methods to show the superiority of the decision support system using laboratory parameters. Detection of COVID-19 from CT images achieved an accuracy of 97.56% with the AlexNet-SVM hybrid method, while COVID-19 was classified with an accuracy of 97.86% with the proposed method using laboratory parameters.

Reference Ranges of Age-Based Liver, Spleen, Pancreas, and Kidney Size in Conjunction with Waist Circumference in Children.

OBJECTIVE: In the initial phases of parenchymal diseases, the only finding would be an increase in organ size. We aimed to provide percentile charts of solid intraabdominal organ sizes by age for Turkish children on contrast-enhanced computed tomography images and reveal relative size ratios. MATERIALS AND METHODS: A total of 800 abdominal computed tomography examinations of otherwise healthy children (468 males, 332 females) were enrolled. The transverse diameter and lengths of both liver lobes, the thickness of the pancreas, width and length of the spleen, and anteroposterior diameters and lengths of both kidneys were measured. Differences in mean diameters among ages were compared with the analysis of variance test. Pearson's correlation was assessed to depict the association of size with age and waist circumference. RESULTS: Percentile charts for all measured size parameters that presented statistically significant positive correlations with age and waist circumference were provided. There were constant ratios of the right liver lobe to the left liver lobe (1.9 ± 0.37), right liver lobe to the right kidney (1.56 ± 0.26), left to the right kidney (1.03 ± 0.09), and spleen to the left kidney (1 ± 0.2) lengths in every age groups. Age (years)-dependant regression equation for waist circumference (mm) was depicted as "22 × age + 408." CONCLUSION: Age-based percentile charts of solid intraabdominal organ diameters along with relative organ size ratios were provided.

Scat-NET: COVID-19 diagnosis with a CNN model using scattergram images.

The acute respiratory syndrome COVID-19 disease, which is caused by SARS-CoV-2, has infected many people over a short time and caused the death of more than 2 million people. The gold standard in detecting COVID-19 is to apply the reverse transcription polymerase chain reaction (RT-PCR) test. This test has low sensitivity and produces false results of approximately 15%-20%. Computer tomography (CT) images were checked as a result of suspicious RT-PCR tests. If the virus is not infected in the lung, the virus is not observed on CT lung images. To overcome this problem, we propose a 25-depth convolutional neural network (CNN) model that uses scattergram images, which we call Scat-NET. Scattergram images are frequently used to reveal the numbers of neutrophils, eosinophils, basophils, lymphocytes and monocytes, which are measurements used in evaluating disease symptoms, and the relationships between them. To the best of our knowledge, using the CNN together with scattergram images in the detection of COVID-19 is the first study on this subject. Scattergram images obtained from 335 patients in total were classified using the Scat-NET architecture. The overall accuracy was 92.4%. The most striking finding in the results obtained was that COVID-19 patients with negative RT-PCR tests but positive CT test results were positive. As a result, we emphasize that the Scat-NET model will be an alternative to CT scans and could be applied as a secondary test for patients with negative RT-PCR tests.

Covid-19: Correlation of Early Chest Computed Tomography Findings With the Course of Disease.

OBJECTIVE: To investigate the role of chest computed tomography (CT) examinations acquired early after initial onset of symptoms in predicting disease course in coronavirus disease 2019. METHODS: Two hundred sixty-two patients were categorized according to intensive care unit (ICU) admission, survival, length of hospital stay, and reverse transcriptase-polymerase chain reaction positivity. Mean time interval between the onset of symptoms and CT scan was 5.2 ± 2.3 days. Groups were compared using Student t test, Mann-Whitney U, and Fisher exact tests. RESULTS: In the ICU (+) and died groups, crazy paving (64% and 57.1%), bronchus distortion (68% and 66.7%), bronchiectasis-bronchiolectasis (80% and 76.2%), air trapping (52% and 52.4%) and mediastinal-hilar lymph node enlargement (52% and 52.4%) were significantly more encountered (P < 0,05). These findings were correlated with longer hospital stays (P < 0.05). There were no differences between reverse transcriptase-polymerase chain reaction-positive and -negative patients except bronchiectasis-bronchiolectasis. CONCLUSION: Computed tomography examinations performed early after the onset of symptoms may help in predicting disease course and planning of resources, such as ICU beds.

Normative values of thymus in healthy children; stiffness by shear wave elastography.

PURPOSE: Thymus grows after birth, reaches maximal size after the first few years and involutes by puberty. Because of the postnatal developmental and involutional duration, we aimed toinvestigate normal stiffness values of mediastinal thymus by shear wave elastography (SWE) in different age groups of children and discuss imaging findings of thymus. METHODS: We prospectively examined 146 children (90 girls, 56 boys) who underwent a thyroid or neck ultrasound examination. All subjects underwent ultrasound and SWE evaluation of mediastinal thymus by parasternal and suprasternal approach. We subdivided the subjects based on the ages as 0 to 2 months (group 1), >2 to 6 months (group 2); >6 months to 2 years (group 3), >2 to 5 years (group 4), >5 to 8 years (group 5), and greater than 8 years old (group 6).We investigated differences of mean shear wave elasticity (kPa) and shear wave velocity (m/sec) values among age groups and the association of SWE values with age, body mass index (BMI), height, and weight of the patients. RESULTS: Medians and ranges of age, height, weight, and BMI were 24 (2-84) months, 85 (55-120) cm, 12(4.55-22) kg, 15.37 (13.92-17.51) kg/m2, 11 (2.64-23.15) cc, respectively. Mean shear wave elasticity of thymus when all participants were included was 6.76±1.04 kPa. Differences of mean elasticity values among age groups and also gender groups were not statistically significant. There were highly significant negative correlations among age (r:0.3), height (r:0.26), weight (r:0.3) with elasticity and also velocity values (p<0.001). The thymus elasticity is negatively correlated with age. CONCLUSION: Quantitative evaluation of the thymus by SWE provides normative stiffness values based on age and gender groups. The thymus elasticity decreases with increased age, height and weight.

Discrimination of ß-thalassemia and iron deficiency anemia through extreme learning machine and regularized extreme learning machine based decision support system.

The symptoms of Iron Deficiency Anemia (IDA) and ß-thalassemia (ß-TT) disease are similar and the distinction between them is time consuming and costly. There are several indices used to differentiate IDA from ß-thalassemia disease. Complete Blood Count (CBC) is a rapid, inexpensive and accessible test for the diagnosis of anemia and is used as a primary test. However, since CBC cannot fully distinguish between IDA and ß-thalassemia, more advanced testing is required. These tests are not available in small centers and are performed on higher-cost devices. Moreover, it is important to differentiate between anemia and ß-thalassemia medically for two reasons (IDA). First, if a patient with ß-Thalassemia is diagnosed with IDA, the patient is given unnecessary iron supplementation as a result of the treatment, which is recommended by the doctor. Secondly, when the patient with ß-thalassemia is diagnosed with IDA, children will have ß-thalassemia patients in marriages. A decision support system to distinguish between ß-Thalassemia and IDA has been developed. Logistic Regression, K-Nearest Neighbours, Support Vector Machine, Extreme Learning Machine and Regularized Extreme Learning Machine classification algorithms were used in the proposed system. Classification performance was evaluated with Accuracy, sensitivity, f-measure, Specificty parameters using Hemoglobin, RBC, HCT, MCV, MCH, MCHC and RDW parameters obtained from 342 patients. 96.30% accuracy for female, 94.37% for male, and 95.59% in co-evaluation of male and female patients were obtained.

Association Between Anxiety, Depression, and Salivary Cortisol Levels in Patients with Recurrent Aphthous Stomatitis.

OBJECTIVE: Recurrent aphthous stomatitis (RAS) is the most common ulcerative disease of the oral mucosa that commonly affects the general population. The objective of this study was to conduct a research in assesing the relationship between psychological disorders including anxiety, depression and salivary cortisol levels in patients with RAS. METHODS: Thirty-nine patients suffering from minor RAS were enrolled in the study after obtaining an informed consent. The control group consisted of 25 age and gender matched healthy individuals. All subjects were evaluated by using both psychological tests (Hamilton's anxiety rating scale [HARS] and Hamilton's depression rating scale [HDRS]) and physiological testing instrument (salivary cortisol level). RESULTS: While no statistical difference was found between the patients with RAS and controls for both salivary cortisol levels and anxiety, there was statisticaly significant difference between the groups for depression. CONCLUSION: There was no significant increase in salivary cortisol levels in patients with active disease when compared to the healthy subjects. But we found that depression scale values were significantly higher in patients with RAS.

Monofilament gillnet selectivity parameters for European chub (Leuciscus cephalus L.1758) in Atikhisar Reservoir, Canakkale, Turkey.

Selectivity parameters of gillnets used for fish catching are very important for fisheries management in lakes. The main purpose of the present study was to estimate the selectivity parameters of monofilament gill nets mesh size of 56, 64 and 72 mm (stretched mesh size) used for European chub (Leuciscus cephalus L.1758) in Atikhisar Reservoir, Canakkale, Turkey. The indirect method proposed by Holt was used for the estimation of the selectivity parameters. The common selection factors and common standard deviation of monofilament gill nets were determined as 4.25 and 2.37, respectively. For sustainable fisheries of European chub, the minimum mesh size of monofilament gill nets must be greater than 47 mm stretched mesh size.