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    The effect of the intercondylar notch width index on anterior cruciate ligament injuries : A study on groups with unilateral and bilateral ACL injury
    (Acta Medica Belgica, 2015) Gormeli, Cemile Ayse; Gormeli, Gokay; Ozturk, Burak Yagmur; Ozdemir, Zeynep; Kahraman, Aysegul Sagir; Yildirim, Okan; Gozukara, Harika
    Background : To evaluate the relationship of the intercondylar notch width with unilateral and bilateral ACL injury by using MR images. Materials and Methods : The intercondylar notch width index was measured on the MR images of 18 patients with a bilateral ACL injury, 38 patients with a unilateral ACL injury and 53 healthy subjects with a normal ACL and the results of all groups were compared with each other. Results : The mean NWI values were 0,227 (+/- 0.008) in bilateral injured; 0,245 (+/- 0.009) in unilateral injured and 0,272 (+/- 0.01) in control groups and 0,251(+/- 0.01) in unaffected side of the unilateral group. There were statistically significant differences in intercondylar notch width index (NWI) values between all groups and there was a significant difference between the affected and the unaffected sides in group with unilateral ACL injury. A cutoff value of 0.25 for NWI gave an odds ratio of 26.5 for bilateral and 3.23 for unilateral ACL injuries. Conclusions : The finding that NWI is significantly narrowed in patients with bilateral and unilateral ACL tears compared with the healthy controls suggest a relationship between a narrow NWI and an increased risk of ACL injury. The patients with a narrow NWI should also be screened contralaterally for assessment of ACL injury risk on the other knee. So, specialized training programmes for the people with narrow NWI can be prepared for preventing ACL injuries.
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    Evaluation of Vertebral Artery Involvement by Doppler Sonography in Patients With Behcet Disease
    (Wiley, 2014) Tasolar, Sevgi; Dogan, Metin; Tasolar, Hakan; Kahraman, Aysegul; Kamisli, Suat; Dogan, Adil; Yildirim, Okan
    Objectives-Neurologic lesions in Behcet disease are most frequently observed in areas supplied by the vertebrobasilar system. We aimed to evaluate possible vertebral artery involvement by Doppler sonography in patients with Behcet disease. Methods-Forty-five patients with Behcet disease and 29 healthy volunteers had Doppler sonography of the vertebral arteries. Patients were grouped according to neurologic examination and magnetic resonance imaging findings as follows: group 1, Behcet disease without neurologic involvement; group 2, neuro-Behcet disease; and group 3, control. Results were assessed with a 95% confidence interval. Results-The main findings of our study were as follows: (1) total vertebral artery volume flow was significantly lower in the patient groups than the control group (P < .05); (2) total volume flow was lower in group 2 than group 1, although the difference was not statistically significant; (3) peak systolic and end-diastolic velocity values were significantly lower in the patient groups than the control group; (4) right and left mean volume values were lower in group 2; and (5) resistive and pulsatility index values for the left vertebral artery were significantly higher in group 2, but no statistically significant differences were found in the resistive and pulsatility index values for the right vertebral artery. Conclusions-Doppler sonography of the vertebral arteries in Behcet disease shows alterations that may aid in the diagnosis and treatment of this condition.
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    Factors Affecting eGFR Slope of Renal Transplant Patients During the First 2 Years
    (Elsevier Science Inc, 2019) Atay, Feyza Firat; Taskapan, Hulya; Berktas, Bayram; Yildirim, Okan; Dogan, Murat; Piskin, Turgut
    Purpose. In healthy individuals, glomerular filtration rate decreases by 1 mL/min/y after a peak level of 125.0 mL/min has been reached in adulthood. Any reduction greater than this is a progressive slope (slope more negative than 1 mL/min/y, stable [-1 to +1]), or an improvable slope if it shows more of an increase, that is, greater than +1.0 mL/min/y). The aim of the study was to determine the factors affecting estimated glomerular filtration rate (eGFR) slope during the first 2 years of renal transplant in patients with negative pretransplant panel-reactive antibody. Materials and Methods. The characteristics of 59 renal transplant patients, such as age, sex, etiology, and 2 years of laboratory data, were collected retrospectively. For each patient, the eGFR decline rate (slope) (mL/min-1/1.73 m(2)-1/y-1) was determined by linear regression analysis using all calculated eGFR values over the study period. Findings. Of 59 patients, 7 (11.8%) had a progressive slope, 22 (37.2%) had a stable slope, and 30 (50.8%) had an improvable slope. The first-year mean tacrolimus level was lower in patients with progressive slope than in the patients with stable slope and improvable slope (P < .022). The determinants of eGFR slope in multiple regression analysis were post-transplant hypertension (beta = 0.393; P = .002) and the first-year mean tacrolimus level (beta = 0.320; P =.01), whereas age, serum albumin, and 2-year mean tacrolimus level did not reach the level of significance. Conclusion. Keeping tacrolimus levels high in the first year to prevent eGFR declining is important.
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    Swin-PHOG-LPQ: An accurate computed tomography images classification model using Swin architecture with handcrafted features
    (Elsevier Sci Ltd, 2023) Kaya, Davut; Gurbuz, Sukru; Yildirim, Okan; Akbal, Erhan; Dogan, Sengul; Tuncer, Turker
    Background and aim: Computed tomography (CT) image classification has been the subject of intense research in the area of biomedical image classification with the objective of developing intelligent disorder detection models. In this paper, we aim to detect three disorders in lung CT images: hemothorax, contusion, and pneumothorax. Deep learning models are particularly effective for computer vision tasks. Thus our second goal is to propose a new hand-modeled image classification model that achieves high performance using the shifted windows (swin) architecture.Materials and Methods: We collected a new lung CT image dataset containing four classes - hemothorax, contusion, pneumothorax, and control - with 2730 CT images. Our proposed swin architecture-based CT image classification model is designed to extract features from patches using the Pyramidal histogram-oriented gradient (PHOG) and local phase quantization (LPQ) methods for directional and textural features. We utilized an iterative neighborhood component analysis (INCA) feature selector for feature selection and classified the chosen features using the k-nearest neighbors (kNN) classifier with 10-fold cross-validation. Finally, majority voting was employed to obtain the final classification.Results: Our proposed Swin-PHOG-LPQ achieved a classification accuracy of 95.53%. We also evaluated our model on two publicly available CT image datasets and achieved classification accuracies of 95.31% and 97.63%, respectively.Conclusion: The high classification accuracies obtained by our proposed Swin-PHOG-LPQ model demonstrate its efficacy in detecting the three disorders in lung CT images.