Browsing by Author "Ucar, Murat"

Now showing 1 - 3 of 3

Ciprofloxacin-Ceftriaxone Combination Prophylaxis for Prostate Biopsy; Infective Complications
(2015) Ozorak, Alper; Hoscan, Mustafa Burak; Soyupek, Sedat; Oksay, Taylan; Guzel, Ahmet; Ozturk, Sefa Alperen; Capkin, Tahsin; Ucar, Murat; Kosar, Alim; A-8837-2018
Aim: To present our clinical experience about infective complications due to ultrasound guided transrectal prostate biopsy under ciprofloxacin plus third-generation cephalosporin (Ceftriaxone) combination prophylaxis. Material and Method: The 1193 patients that used combination of ceftriaxone 1 g intramuscular 1 hour before biopsy and ciprofloxacin 500 mg twice a day for 5 days after biopsy were included to study. Before biopsy, urine analysis and urinary cultures were not performed routinely. Serious infective complications such as acute prostatitis and urosepsis, causing microorganisms were evaluated. Results: Serious infective complications occurred in (1.3%) 16 patients. Fifteen of them had acute prostatitis and urine culture results were positive in 10/15 patients for Escherichia coli. The strains were uniformly resistant to ciprofloxacin. Only 1 patient had urosepsis and his blood and urine cultures demonstrated extended-spectrum beta-lactamase-producing (ESBL) Escherichia coli also resistant to ciprofloxacin. Antibiotic treatment-related side effects were not observed in any patient. Discussion: Although there is not a certain procedure, ciprofloxacin is the most common used antibiotic for transrectal prostate biopsy prophylaxis. On the other hand, the incidence of ciprofloxacin resistant Escherichia coli strain is increasing. Thus, new prophylaxis strategies have to be discussed. Ceftriaxone plus ciprofloxacin prophylaxis is safe and can be useable option for prophylaxis of prostate biopsy.
Is Preoperative Neutrophil Lymphocyte Ratio a Reliable Prognostic Parameter for Localized Prostate Cancer?
(2017) Ipekci, Tumay; Tunckiran, Ahmet; Yuksel, Mustafa; Ucar, Murat; Kozacioglu, Zafer; Akman, Ramazan Yavuz; 0000-0001-7303-7064; 0000-0002-2755-0526; V-6440-2019; AAB-2986-2020; AAD-3028-2020
Objective: In spite of all efforts, prostate cancer is still the 2nd highest cause of cancer-related deaths in men. For this reason new developments are needed in diagnosis, treatment and follow-up of prostate cancer. Neutrophil/lymphocyte (N/L) ratio is a cheap and effective parameter used for research into many solid tumors; but there are not enough studies on the reliability of this parameter in prostate cancer. In this study we researched the efficacy of N/L ratio in localized prostate cancer. Materials and Methods: Between March 9, 2012 and April 23, 2017, the data of 140 patients who underwent radical prostatectomy with localized prostate cancer were screened retrospectively. The patients' ages, preoperative prostate specific antigen (PSA) and N/L ratio, pathologic stage, pathologic Gleason score, tumor volume, lymph node involvement, surgical margin positivity and presence or absence of 3rd month biochemical recurrence were noted. The correlations between N/L ratio with age, PSA, pathologic parameters, surgical margin positivity and biochemical recurrence were investigated. Results: The mean age of patients was 63.0 +/- 5.9 years, mean PSA value was 10.8 +/- 8.5 ng/mL and mean N/L ratio was 2.5 +/- 1.9. There was no correlation found between N/L ratio and PSA, pathologic stage, Gleason score, lymph node involvement, tumor volume, surgical margin positivity and biochemical recurrence (p>0.05). Conclusion: In our study investigating 140 patients with localized prostate cancer, we did not identify any correlation between N/L ratio and PSA, surgical stage and Gleason score, surgical margin positivity, and 3rd month biochemical recurrence. When the literature is investigated, it appears that N/L ratio is effective for metastatic prostate cancer. To provide a more accurate judgment of the role of N/L ratio in localized prostate cancer, there is a need for new studies with broader patient series.
A Novel Deep Learning Algorithm for the Automatic Detection of High-Grade Gliomas on T2-Weighted Magnetic Resonance I mages: A Preliminary Machine Learning Study
(2020) Atici, Mehmet Ali; Sagiroglu, Seref; Celtikci, Pinar; Ucar, Murat; Borcek, Alp Ozgun; Emmez, Hakan; Celtikci, Emrah; 0000-0002-1655-6957; 31608975
AIM: To propose a convolutional neural network (CNN) for the automatic detection of high-grade gliomas (HGGs) on T2-weighted magnetic resonance imaging (MRI) scans. MATERIAL and METHODS: A total of 3580 images obtained from 179 individuals were used for training and validation. After random rotation and vertical flip, training data was augmented by factor of 10 in each iteration. In order to increase data processing time, every single image converted into a Jpeg image which has a resolution of 320x320. Accuracy, precision and recall rates were calculated after training of the algorithm. RESULTS: Following training, CNN achieved acceptable performance ratios of 0.854 to 0.944 for accuracy, 0.812 to 0.980 for precision and 0.738 to 0.907 for recall. Also, CNN was able to detect HGG cases even though there is no apparent mass lesion in the given image. CONCLUSION: Our preliminary findings demonstrate; currently proposed CNN model achieves acceptable performance results for the automatic detection of HGGs on T2-weighted images.