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Article Topographic Radioanatomical Analysis of the Singular Canal: Computed Tomography Study(Wolters Kluwer Medknow Publications, 2024) Demir, Berin Tugtag; Koksal, Ali; Cankal, FatihPurpose: The singular canal (SC) is where the singular nerve, a branch of the inferior vestibular nerve, which carries afferent information from the posterior semicircular canal (PSCC), passes and is important in the surgical approach of the presigmoid retrolabyrinthine. This study was carried out to evaluate the visibility of the SC on standard computed tomography (CT) images, its distance to the surrounding structures, and to investigate the variations of its anatomy and its relationship with the meatus acusticus internus.Materials and Methods: The study was carried out retrospectively using images of 194 temporal bones on temporal bone CT scans of 44 men and 53 women aged 18-65. In the study, various measurements were made, especially the presence of the SC, its length, its angle with the internal acoustic canal (IAC), and the distance between the internal acoustic pore (IAP) and the singular foramen. In addition, the presence of the high jugular bulb and PSCC dehiscence images were investigated.Results: The SC was detected in 85.1% of the analyzed images. The mean canal length was 3.93 +/- 1.22 mm, the angle between the SC and the IAC was 22.68 degrees +/- 3.60 degrees, and the distance between the SC and the IAP was 7.70 +/- 0.83 mm. While no difference was found between the sides, it was determined that the length and diameter of the SC did not differ according to gender.Conclusion: Detailed morphometric analysis of the SC and a thorough understanding of its relationship with the IAC, vestibulum, and PSCC will help to accurately define the posterior and lateral borders of the dissection for this region.Article Citation - WoS: 4Citation - Scopus: 3Assessment of Pulmonary Arterial Hemodynamic and Vascular Changes by Pulmonary Pulse Transit Time in Patients With Human Immunodeficiency Virus Infection(Wolters Kluwer Medknow Publications, 2021) Erdol, Mehmet Akif; Acar, Burak; Ertem, Ahmet Goktug; Karanfil, Mustafa; Yayla, Cagri; Demirtas, Koray; Akcay, Adnan BurakIntroduction: Pulmonary arterial hypertension and human immunodeficiency virus (HIV) infection is a well-known association. Pulmonary pulse transit time (pPTT) is a recent echocardiographic marker that might be used for evaluation of pulmonary arterial stiffness (PAS) in patients with HIV infection. We aimed to investigate whether pPTT elevated in patients with HIV infection compared to healthy controls and its association with echocardiographic indices of right ventricular functions. Materials and Methods: Fifty HIV (+) patients from infectious disease outpatient clinics and fifty age- and sex-matched HIV (-) healthy volunteers were enrolled in this study. pPTT was measured from pulmonary vein flow velocity as the time interval between the R-wave in the electrocardiography and corresponding peak late systolic was then calculated as the mean from two separate pw-Doppler measurements. Results: pPTT, tricuspid annular peak systolic excursion (TAPSE) and right ventricle fractional area change (FAC) were significantly lower in patients with HIV than control patients (177.1 +/- 34.9 vs. 215.7 +/- 35.7 msn, P < 0.001; 2.33 +/- 0.28 vs. 2.19 +/- 0.22, P = 0.039; 45 [4.25] vs. 41.1 [4.0], P = 0.032, respectively). pPTT was positively correlated with FAC, TAPSE and cluster of differentiation 4 count (r = 0.210; P = 0.036, r = 0.256; P = 0.041, r = 0.304; P = 0.044, respectively). Conclusion: Our study showed that pPTT, TAPSE, and right ventricle FAC levels were lower in patients with HIV infection. pPTT is an important predictor in patients with HIV expected to develop pulmonary vascular pathology.Article Evaluation of Diaphragmatic Omental Hernias by Radiology: a Prevalence Study(Wolters Kluwer Medknow Publications, 2022) Cankal, Fatih; Demir, Berin T.; Koksal, AliINTRODUCTION: This study aimed to describe the radiological features of omental hernias originating from the diaphragm and their localization on the diaphragm, examine their relationship with the thoracic and abdominal organs, and present guiding data to clinicians in operational planning. MATERIALS AND METHODS: This study was obtained as a result of retrospective scanning of the images of 824 patients aged 18-65 who applied for thorax and/or upper abdomen computerized tomography (CT). The patients' thorax and upper abdomen regions were examined in detail and divided into two groups of individuals with and without hernias. Hernia types, content, localization, and effect types of patients with hernia were recorded and analyzed separately. RESULTS: Diaphragmatic hernia was detected in 197 (23.9%) of 824 patients. While 50.8% of these patients were female, 49.2% were male. Of the patients diagnosed with diaphragmatic hernia, 49.2% (n = 97) had Morgagni hernia, 30.5% (n = 60) had Bochdalek hernia, and 17.8% had hiatal hernia. While Morgagni hernia had anterior localization in 82.5%, Bochdalek hernia was generally localized on the left side (75.8%), and hiatal hernias were sliding type with a rate of 84.2%. The highest effect was observed in Bochdalek hernias (71.1%). Omental tissue (59.4%) was observed most frequently in Morgagni hernias, while stomach content (91.9%) was found to be the highest in hiatal hernias (P < 0.05). DISCUSSION-CONCLUSION: Diaphragmatic omental hernias are rare. The rarity, as well as the uncertain and nonspecific presentations, contributes to the retard in diagnosis. Commonly, the presentation in the adult age group is that of recurrent chest infection and rarely with gastroesophageal reflux and esophagitis. Physicians caring for these patients should be aware of this, and a high index of suspicion is recommended to obviate delay in diagnosis with its associated morbidity. We think the radiological features of diaphragmatic hernias should be detailed in determining and applying the optimal treatment approach. In addition, contrary to what was thought, we found that the prevalence of diaphragmatic hernia in our population is higher than that reported in the literature.Article Citation - WoS: 9Citation - Scopus: 11Using Deep Learning Approaches for Coloring Silicone Maxillofacial Prostheses: a Comparison of Two Approaches(Wolters Kluwer Medknow Publications, 2023) Kurt, Meral; Kurt, Zuhal; Isik, SahinAim: This study aimed to compare the performance of two deep learning algorithms, attention-based gated recurrent unit (GRU), and the artificial neural networks (ANNs) algorithm for coloring silicone maxillofacial prostheses. Settings and Design: This was an in vitro study. Materials and Methods: A total of 21 silicone samples in different colors were produced with four pigments (white, yellow, red, and blue). The color of the samples was measured with a spectrophotometer, then the LFNx01, aFNx01, and bFNx01 values were recorded. The relationship between the LFNx01, aFNx01, and bFNx01 values of each sample and the amount of each pigment in the compound of the same sample was used as the training dataset, entered into each algorithm, and the prediction models were obtained. While generating the prediction model for each sample, the data of the corresponding sample assigned as the target color were excluded. LFNx01, aFNx01, and bFNx01 values of each target sample were entered into the obtained models separately, and recipes indicating the ratios for mixing the four pigments were predicted. The mean absolute error (MAE) and root mean square error (RMSE) values between the original recipe used in the production of each silicone and the recipe created by both prediction models for the same silicone were calculated. Statistical Analysis Used: Data were analyzed with the Student t-test (alpha=0.05). Results: The mean RMSE values and MAE values for the ANN algorithm (0.029 & PLUSMN; 0.0152 and 0.045 & PLUSMN; 0.0235, respectively) were found significantly higher than the attention-based GRU model (0.001 & PLUSMN; 0.0005 and 0.002 & PLUSMN; 0.0008, respectively) (P < 0.001). Conclusions: Attention-based GRU model provided better performance than the ANN algorithm with respect to the MAE and RMSE values.
