A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium

The aim of this study is to test whether sex prediction can be made by using machine learning algorithms (ML) with parameters taken from computerized tomography (CT) images of cranium and mandible skeleton which are known to be dimorphic. CT images of the cranium skeletons of 150 men and 150 women were included in the study. 25 parameters determined were tested with different ML algorithms. Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), F1 score (F1), Matthews correlation coefficient (Mcc) values were included as performance criteria and Minitab 17 package program was used in descriptive statistical analyses. p <= 0.05 value was considered as statistically significant. In ML algorithms, the highest prediction was found with 0.90 Acc, 0.80 Mcc, 0.90 Spe, 0.90 Sen, 0.90 F1 values as a result of LR algorithms. As a result of confusion matrix, it was found that 27 of 30 males and 27 of 30 females were predicted correctly. Acc ratios of other MLs were found to be between 0.81 and 0.88. It has been concluded that the LR algorithm to be applied to the parameters obtained from CT images of the cranium skeleton will predict sex with high accuracy

Giant Vertebral Notochordal Rest: Magnetic Resonance and Diffusion Weighted Imaging Findings

A giant vertebral notochordal rest is a newly described, benign entity that is easily confused with a vertebral chordoma. As microscopic notochordal rests are rarely found in adult autopsies, the finding of a macroscopic vertebral lesion is a new entity with only seven previously presented cases. We report here radiological findings, including diffusion weighted images, of a patient with a giant notochordal remnant confined to the L5 vertebra, with an emphasis on its distinction from a chordoma

Comparison of long-term kidney functions after radical nephrectomy and simple nephrectomy

Objective To determine if there is a difference in proceeding to CKD between patients who had undergone radical nephrectomy (RN) and simple nephrectomy (SN) for different indications by comparing the short- and long-term renal function. Materials and Methods We retrospectively analyzed the records of all patients who underwent nephrectomy (either for malign or benign indications) in our clinic between January 2007 and September 2017. The patients were divided into 2 groups according the type of surgery: 1) Radical nephrectomy Group, 2) Simple Nephrectomy Group. Renal function was evaluated with Glomerular Filtration Rate (GFR) calculated using the MDRD formula. Results A total of 276 patients were included in the study. There were 202 patients in RN Group and 74 patients in SN Group. The mean age of the patients in RN Group and SN Group were age 59,2 ± 11,5 and 49,9 ± 15,1 years, respectively (p = 0.001). GFR levels of patients in RN Group versus SN Group were as follows: Preoperative period: 84.9 vs. 81 mL/min/1.73 m2; postoperative 1st day: 60.5 vs. 84.4 mL/min/1.73 m2, postoperative 1st month 58.9 vs. 76 mL/min/1.73 m2, postoperative 1st year: 59.5 vs. 74.1 mL/min/1.73 m2; at last control 60.3 and 76.1 mL/min/1.73 m2. While preoperative GFR was found to be similar in two groups (p = 0.26), postoperative GFR values were found to be significantly lower in Group RN (p < 0.001). In comparison of the decrease in GFR in two groups at last follow-up, significantly higher decrease was observed in RN Group, 29% vs. 6%, (p < 0.05). Conclusion The decrease in GFR exists more common and intensive after RN compared to SN. In long-term, compensation mechanisms that develop after sudden nephron loss like radical nephrectomy deteriorates kidney function more than gradual nephron loss as in benign etiologies which indicates simple nephrectomy

Effect of surgical experience and spine subspecialty on the reliability of the {AO} Spine Upper Cervical Injury Classification System

OBJECTIVE The objective of this paper was to determine the interobserver reliability and intraobserver reproducibility of the AO Spine Upper Cervical Injury Classification System based on surgeon experience (&lt; 5 years, 5–10 years, 10–20 years, and &gt; 20 years) and surgical subspecialty (orthopedic spine surgery, neurosurgery, and "other" surgery). METHODS A total of 11,601 assessments of upper cervical spine injuries were evaluated based on the AO Spine Upper Cervical Injury Classification System. Reliability and reproducibility scores were obtained twice, with a 3-week time interval. Descriptive statistics were utilized to examine the percentage of accurately classified injuries, and Pearson’s chi-square or Fisher’s exact test was used to screen for potentially relevant differences between study participants. Kappa coefficients (κ) determined the interobserver reliability and intraobserver reproducibility. RESULTS The intraobserver reproducibility was substantial for surgeon experience level (&lt; 5 years: 0.74 vs 5–10 years: 0.69 vs 10–20 years: 0.69 vs &gt; 20 years: 0.70) and surgical subspecialty (orthopedic spine: 0.71 vs neurosurgery: 0.69 vs other: 0.68). Furthermore, the interobserver reliability was substantial for all surgical experience groups on assessment 1 (&lt; 5 years: 0.67 vs 5–10 years: 0.62 vs 10–20 years: 0.61 vs &gt; 20 years: 0.62), and only surgeons with &gt; 20 years of experience did not have substantial reliability on assessment 2 (&lt; 5 years: 0.62 vs 5–10 years: 0.61 vs 10–20 years: 0.61 vs &gt; 20 years: 0.59). Orthopedic spine surgeons and neurosurgeons had substantial intraobserver reproducibility on both assessment 1 (0.64 vs 0.63) and assessment 2 (0.62 vs 0.63), while other surgeons had moderate reliability on assessment 1 (0.43) and fair reliability on assessment 2 (0.36). CONCLUSIONS The international reliability and reproducibility scores for the AO Spine Upper Cervical Injury Classification System demonstrated substantial intraobserver reproducibility and interobserver reliability regardless of surgical experience and spine subspecialty. These results support the global application of this classification system

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Optimization of operating variables for production of ultra-fine talc in a stirred mill. Specific surface area investigations

Due to its properties such as chemical inertness, softness, whiteness, high thermal conductivity, low electrical conductivity and adsorption properties talc has wide industrial applications in paper, cosmetics, paints, polymer, ceramics, refractory materials and pharmaceutical. The demand for ultra-fine talc is emerging which drives the mineral industry to produce value added products. In this study, it was investigated how certain grinding parameters such as mill speed, ball filling ratio, powder filling ratio and grinding time of dry stirred mill affect grindability of talc ore (d97=127 μm). A series of laboratory experiments using a 24 full factorial design was conducted to determine the optimal operational parameters of a stirred mill in order to minimize the specific surface area. The main and interaction effects on the volume specific surface area (SV, m2.cm−3) of the ground product were evaluated using the Yates analysis. Under the optimal conditions at the stirrer speed of 600 rpm, grinding time of 20 min, sample mass of 5% and ball ratio of 70%, the resulting talc powder had larger volume specific surface area (i.e., 3.48 m2.cm−3) than the starting material (i.e., 1.84 m2.cm−3)

Analysis of the correlation between thyroid hormones and thyroid volume by gender: A volumetric computed tomography study

The aim of this study was to evaluate the correlation between triiodothyronine (T3), thyroxine (T4), and thyroid-stimulating hormone (TSH) hormones and thyroid gland volume with volumetric analysis performed by using computed tomography (CT) images. In this retrospective study, IV contrasted thoracic CT images taken for different indications between 2019 January and 2020 January were scanned from the archive system of the hospital. 67 (31F, 36M) individuals chosen randomly among patients whose CT results were reported as normal and who had taken thyroid hormone tests within the past week were included in the study. Images in Digital Imaging and Communications in Medicine format were transferred to the personal work station program (Horos Medical Image Viewer). By using the Region of Interest (ROI) console in the current program, a three dimensional model was obtained by drawing the border of the thyroid gland in sections varying between 15 and 25. Volume values of this three-dimensional model and TSH, T3, T4 values of the individuals were compared. While no correlation was found between thyroid gland volume and T3 and T4 hormones, a negative significant correlation was found with TSH. In terms of gender, thyroid gland volume, T3, T4 values were found to be statistically significantly higher in women when compared with men (p&le;0.05). TSH value was found to be higher in women when compared with men (p=0.005). No statistically significant difference was found in T4 value (p=0.057). Radio-anatomical volumetric data of the thyroid gland presented in this study and its correlation with thyroid functions will be beneficial to clinicians working in the field in both internal and surgical medicine branches and will also guide future studies. [Med-Science 2022; 11(2.000): 810-3

Gender prediction with the parameters obtained from pelvis computed tomography images and machine learning algorithms

Introduction: In the skeletal system, the most dimorphic bones employed for postmortem gender prediction include the bones in the pelvic skeleton. Bone measurements are usually conducted with cadaver bones. Computed tomography (CT) is an increasingly popular method due to its ease of use, reconstruction opportunities, and lower impact of age bias and provides a modern data source. Even when parameters obtained with different or same bones are missing, machine learning (ML) algorithms allow the use of statistical methods to predict gender. This study was carried out in order to obtain high accuracy in estimating gender with the pelvis skeleton by integrating ML algorithms, which are used extensively in the field of engineering, in the field of health. Material and Methods: In the present study, pelvic CT images of 300 healthy individuals (150 females, 150 males) between the ages of 25 and 50 (the mean female age = 40, the mean male age = 37) were transformed into orthogonal images, and landmarks were placed on promontory, iliac crest, sacroiliac joint, anterior superior iliac spine, anterior inferior iliac spine, terminal line, obturator foramen, greater trochanter, lesser trochanter, femoral head, femoral neck, body of femur, ischial tuberosity, acetabulum, and pubic symphysis, and coordinates of these regions were obtained. Four groups were formed based on various angle and length combinations obtained from these coordinates. These four groups were analyzed with ML algorithms such as Logistic Regression, Linear Discriminant Analysis (LDA), Random Forest, Extra Trees Classifier, and ADA Boost Classifier. Results: In the analysis, it was determined that the highest accuracy was 0.96 (sensitivity 0.95, specificity 0.97, Matthew's Correlation Coefficient 0.93) with LDA. Discussion and Conclusion: The use of length and angle measurements obtained from the pelvis showed that the LDA model was effective in estimating gender

Gender prediction with parameters obtained from pelvis computed tomography images and decision tree algorithm

Gender prediction is among the most critical topics in forensic medicine and anthropology since it is the basis of identity (height, weight, ancestry, age). Today, osteometry which is a low-cost, easily accessible method that requires no expertise is preferred when compared to DNA technology, which has several disadvantages such as high cost, accessibility, laboratory facilities, and expert personnel requirements. The Computed Tomography (CT) method, which is little affected by orientation and provides reconstruction opportunities, was selected instead of traditional methods for osteometry. This study aims to predict high and accurate gender with the Decision Tree (DT) algorithms used in the field of health recently. In the present study, CT images of 300 individuals (150 females, 150 males) without a pathology on the pelvic skeleton and between the ages of 25 and 50 were transformed into orthogonal form, landmarks were placed on promontorium, sacroiliac joint, iliac crest, terminal line, anterior superior iliac spine, anterior inferior iliac spine, greater trochanter, obturator foramen, lesser trochanter, femoral head, femoral neck, the body of femur, ischial tuberosity, acetabulum, and pubic symphysis, and the coordinates of these landmarks were determined. Then, parameters such as angle and length were obtained with various combinations. These parameters were analyzed with the DT algorithm.The analysis conducted with the DT algorithm revealed that accuracy (Acc) was 0.93, sensitivity was 0.95, specificity was 0.90, and the Matthews correlation coefficient was 0.86 for the pelvic skeleton. It was observed that the accuracy was quite high and more realistic when determined with the DT algorithm. In conclusion, the DT algorithm with multiple parameters and samples on pelvic CT images could improve the Acc of gender prediction. [Med-Science 2021; 10(2.000): 356-61

Macrodystrophia lipomatosa of the foot: A case report.

Macrodystrophia lipomatosa is a sporadic, nonhereditary developmental anomaly and a rare form of congenital localized gigantism. It is characterized by the proliferation of all the mesenchymal elements of a digit or digits, and a disproportionate increase of fibroadipose tissue involving the nerve sheath, muscle, periosteum and bone marrow. In the present study, a 9-month-old boy was referred to Gazi University Hospital (Ankara, Turkey) with congenital unilateral enlargement of the right forefoot, particularly involving the second and third toes. X-ray and magnetic resonance imaging (MRI) scans were performed in order to assess the skeletal structures. The present study described the characteristic imaging features, with an emphasis on the MRI findings, of this rare congenital form of gigantism