Browsing by Author "Toprak, Serdar Ferit"

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The Long-Term Results of Suture and Graft Techniques Used To Increase Tip Projection and Rotation in Open Technique Septorhinoplasty
(2022) Erdem, Tamer; Toprak, Serdar Ferit; Can, Sermin; Bayındır, Tuba
Background: In this study, we aimed to evaluate the long-term results of suture and graft techniques used to increase tip projection and rotation in Open Technique Septorhinoplasty. Methods: In this study, the data of 89 patients who underwent Open Technique Septorhinoplasty were analysed retrospectively. The patients were divided into groups 1,2,3,4 and 5 according to the suture and graft techniques used. Preoperative and postoperative photographs of all patients included in the study at the 1st, 3rd, 6th, 12th, 36th and 60th months were analyzed. To measure and compare these techniques, tip projection and rotation losses were measured on all photographs using a computer program called Imagej. Results: A statistically significant increase was found between the preoperative mean Nasolabial Angle (NLA), Type Angle (TA), Byrd–Hobar Method (BHM) and Nasofacial Angle (NFsA) measurement values and the measurement values at 36th months postoperatively in Groups 1 and 4 (p < 0.05). In Group 2, a statistically significant increase was found between preoperative mean NLA, TA and BHM measurement values and postoperative 36th month measurement values (p < 0.05). In group 1 only, there was a statistically significant difference between the preoperative mean TA, BHM, Simons Method (SM), Goode Method (GM) and Powell-Modified Baum Method (PMBM) measurement values and the postoperative measurement values at 60th months (p < 0.05). Conclusions: Our results showed that suture techniques were more effective on projection and rotation than graft techniques in the long term.
Automated Mucormycosis Diagnosis from Paranasal CT Using ResNet50 and ConvNeXt Small
(MDPI, 2025) Toprak, Serdar Ferit; Dedeoglu, Serkan; Kozan, Gunay; Ayral, Muhammed; Can, Sermin; Turk, Omer; Akdag, Mehmet
Purpose: Mucormycosis is a life-threatening fungal infection, where rapid diagnosis is critical. We developed a deep learning approach using paranasal computed tomography (CT) images to test whether mucormycosis can be detected automatically, potentially aiding or expediting the diagnostic process that traditionally relies on biopsy. Methods: In this retrospective study, 794 CT images (from patients with mucormycosis, nasal polyps, or normal findings) were analyzed. Images were resized and augmented for training. Two transfer learning models (ResNet50 and ConvNeXt Small) were fine-tuned to classify images into the three categories. We employed a 70/30 train-test split (with five-fold cross-validation) and evaluated performance using accuracy, precision, recall, F1-score, and confusion matrices. Results: The ConvNeXt Small model achieved 100% accuracy on the test set (precision/recall/F1-score = 1.00 for all classes), while ResNet50 achieved 99.16% accuracy (precision approximate to 0.99, recall approximate to 0.99). Cross-validation yielded consistent results (ConvNeXt accuracy similar to 99% across folds), indicating no overfitting. An ablation study confirmed the benefit of transfer learning, as training ConvNeXt from scratch led to lower accuracy (similar to 85%) Conclusions: Our findings demonstrate that deep learning models can accurately and non-invasively detect mucormycosis from CT scans, potentially flagging suspected cases for prompt treatment. These models could serve as rapid screening tools to complement standard diagnostic methods (histopathology), although we emphasize that they are adjuncts and not replacements for biopsy. Future work should validate these models on external datasets and investigate their integration into clinical workflows for earlier intervention in mucormycosis.
Hoarseness, Quality of Life, and Social Anxiety: A Case-Control Study
(MDPI, 2025) Donmezdil, Suleyman; Toprak, Serdar Ferit
Hoarseness is a common voice symptom that can impair communication and lead to psychosocial difficulties. It has been hypothesized that chronic hoarseness may contribute to elevated social anxiety. This study aimed to assess the impact of hoarseness on quality of life and social anxiety in affected individuals. Thirty-eight patients with chronic hoarseness (voice disorders) and 40 matched healthy controls were evaluated in a prospective case-control study. Quality of life was measured using the WHOQOL-BREF questionnaire (Physical, Psychological, Social, and Environmental domains). Social anxiety was assessed with the Liebowitz Social Anxiety Scale (LSAS), and general anxiety and depression with the Hospital Anxiety and Depression Scale (HADS). Group scores were compared using appropriate statistical tests, and effect sizes with 95% confidence intervals were calculated. Patients with hoarseness had significantly lower Psychological Health and Social Relationships scores on the WHOQOL-BREF than controls (p < 0.01 for both; large effect sizes), indicating worse quality of life in these domains. Physical Health and Environmental domain scores did not differ between groups. The hoarseness group also showed higher social anxiety: LSAS total scores and Social Interaction subscale scores were significantly greater than those of controls (p < 0.01 and p < 0.05, respectively; moderate-to-large effects), whereas the Performance Anxiety subscale was similar between groups. By contrast, HADS anxiety and depression scores did not differ significantly between patients and controls. Notably, mean HADS scores in both groups fell in the mild (borderline) range rather than the normal range. Chronic hoarseness is associated with reduced quality of life in emotional and social domains and with increased social anxiety symptoms, but not with elevated general anxiety or depression. These findings underscore the need to address psychosocial factors, particularly social anxiety, in the clinical management of patients with voice disorders.