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Öğe Fokal Asimetrik Meme Dansitelerinin Değerlendirilmesinde Tomosentezin Tanıya Katkısı(2023) Güçlü, Derya; Naldemir, İbrahim Feyyaz; Unlu, Elif Nisa; Onbas, OmerAmaç: Bu çalışma ile mamografik incelemelerde fokal asimetrik dansite saptanan ve ek tetkik gerektiren olgularda tomosentezin tanıya katkısını araştırmak amaçlanmıştır. Gereç ve Yöntemler: Hastanemiz Radyoloji Anabilim Dalı Meme Görüntüleme Ünitesine Şubat 2020-Haziran 2022 tarihleri arasında tarama ya da tanısal amaçlı dijital mamografi tetkiki yapılan ve fokal asimetrik meme dansitesi saptanan 56 olguya, ek olarak tomosentez inceleme yapıldı ve bulgular BI-RADS kullanılarak sınıflandırıldı. Hasta yaşı, meme paterni, fokal asimetik dansite bulunan meme ve kadranı kaydedildi. Sonrasında tamamlayıcı ve altın standart tetkik olarak bilateral meme ultrasonografi incelemesi yapılarak bulgular kaydedildi. Bulgular: Dijital mamografi görüntüleme sonucunda fokal asimetrik dansite nedeniyle BI-RADS 0 olarak değerlendirilen 56 kadın olgunun ortalama yaşları 51,5 ± 8,1’dir. %12,5’i (n=7) A tipi, %42,9’u (n=24) B tipi, %41,1’i (n=23) C tipi, %3,6’sı (n=2) D tipi meme paternine sahiptir. Fokal asimetrik dansitelerin % 44,6’sı (n=25) sağ, %55,4’ü (n=31) sol memede saptanmıştır. Dijital tomosentez incelemelerinin değerlendirilmesinde, olguların % 41,1’i (n=23) BI-RADS 1, % 16,1’i (n=9) BI-RADS 2, % 21,4’ü (n=12) BI-RADS 3, 21,4’ü (n=12) BI-RADS 4 olarak sınıflanmıştır. Ultrasonografik incelemede hastaların %42,9’u (n=24) asimetrik fibroglandüler doku, %17,9’u (n=10) olası benign lezyon, % 19,6’sı (n=11) ise malign lezyon olarak değerlendirilmiştir. Histopatolojik inceleme önerilen 12 hastanın ikisi stromal fibrozis, diğer 10’u ise biri lobüler olmak üzere invaziv meme karsinomu olarak değerlendirilmiştir. Sonuç: Bu çalışma mamografik incelemeler ile morfolojisi değerlendirilemeyen ve ek tetkik gerektiren fokal asimetrik dansitelerde tomosentezin tanısal önemini vurgulamaktadır. Tomosentez, son dekatta kullanımı giderek artan ve parankime süperpoze lezyonlarda yaşanabilecek tanı güçlüklerini çözebilecek görece yeni bir tekniktir.Öğe Gender Classification Using Parameters Obtained from the Dens Axis with Machine Learning Algorithms and Multilayer Perceptron Classifier(Dubai Iranian Hosp, 2025) Harmandaoglu, Oguzhan; Secgin, Yusuf; Kaya, Seren; Ozturk, Oguzhan; Senol, Deniz; Onbas, OmerBackground and Objectives: Due to the difficulties associated with the separation, damage, cremation, and commingling of skeletal remains, it is of great importance in forensic medicine to assess the accuracy and reliability of sex estimates derived from different skeletal components. For this purpose, this study aimed to classify gender using machine learning (ML) algorithms and a multilayer perceptron classifier (MLPC) based on morphometric data of the dens axis obtained from computed tomography (CT) images. Methods: Retrospectively, measurements were taken from CT images of 300 male and 300 female individuals aged between 18-65 years, including dens axis height (DAH), anteroposterior (APDDA) and anterosuperior lengths (ASDDA), dens axis angle (DAA), clivodental angle (CDA), and Boogard angle (BOO). Machine learning models such as Extra Tree Classifier (ETC), Random Forest (RF), Decision Tree (DT), Gaussian Naive Bayes (GaussianNB), k-Nearest Neighbors (k-NN), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and Logistic Regression (LR) were used. MLPC was chosen as artificial neural networks (ANN) model. Results: Significant differences were found between genders in all dens axis parameters except BOO (p<0.05). The highest accuracy rate in ML algorithm modeling was found to be 0.80 with LDA, RF, k-NN algorithms, and MLPC. The parameter with the highest impact on gender classification was the dens axis anterosuperior length. Conclusion: It was found that the parameters obtained from the dens axis using MLCP and ML algorithms have sufficient accuracy rates the classification of sex. It was concluded that in forensic medicine, in cases of deterioration, loss, and deficiencies in bone sources for biological identity determination, the morphometric features of the dens axis can be considered for gender prediction.Öğe Long-term Outcomes of Children with Myelomeningocele and the Quality of Life in Survivors(Duzce Univ, Fac Medicine, 2024) Cakmak, Hatice Mine; Onbas, Omer; Tuncer, Cengiz; Kocabay, Kenan; Kilic, Guven; Zamur, Cagatay; Sav, Nadide MelikeObjective: Myelomeningocele, a condition that causes chronic health conditions and diminished quality of life, affects not just the children but also their families. Therefore, we comprehensively evaluated the data of 101 children with MMC (myelomeningocele) and aimed to compare the quality of life between children with MMC and their siblings. It is crucial to understand that children with MMS have a diminished quality of life with social and behavioral aspects and health issues, which can be emotionally challenging for them and their families. Methods: In this retrospective study, we collected data from electronic files, ensuring a comprehensive and accurate representation of the participants' medical history. To measure the quality of life, we used the KIDSCREEN 10 instrument, a widely recognized and validated tool in pediatric research. Results: Of the 101 children, 93 were survivors. Comparing the survivors (n=93) with their siblings, survivors had lower HRQoL (health-related quality of life) scores in subdimensions of physical well-being (p<0.001), relationships with family (p<0.001) Aand friends (p<0.001), Aschool performance and attention (p<0.001). On the other hand, the psychological wellness score was higher in survivors than in siblings (p<0.001). Most 44 (43.5%) had average mental capacity. The HRQoL score, a measure of the impact of health conditions on a person's overall well-being, was lower in the Chiari type 2 group than in the other survivors (p=0.035). Serum and folic acid levels did not correlate with HRQoL measures. Conclusions: This study illuminates the quality of life measures in MMC survivors and the Chiari type 2 group and utilizes new MRI findings, which provide groundbreaking insights into the health conditions and well-being of these populations. These findings are of utmost importance for medical professionals, researchers, and healthcare providers specializing in pediatric care and neurology, as they can significantly impact the treatment and care of these patients.Öğe Pankreatik Nöroendokrin Karsinomda Paraneoplastik Ciddi Sensorimotor Aksonal Polinöropati: Vaka Sunumu ve Literatür Taraması(2022) Akbaş, Türkay; Kantarcıoğlu Coşkun, Sinem; Torun, Serkan; Öztürk, Ayhan; Eşbah, Onur; Onbas, OmerAmaç: Paraneoplastik nörolojik sendromlar (PNSs), kanser öncesi veya kanser sırasında gelişen, sinir sisteminin herhangi bir kısmını etkileyen çeşitli nörolojik hastalıkları içermektedir. Vaka: Yetmiş sekiz yaşında erkek hastanın üç yıl önce üst ekstremitelerde ağrı ve yanma hissi şikayetleri başlamış ve kısa süre sonra kas güçsüzlüğü eklenmiş. Bir yıl önce de alt ekstremitelerde benzer şikayetler ortaya çıkmış. Yoğun bakım ünitesine pnömoni tansıyla yatırılan hastanın yatış esnasında bilinci açık, fakat kuadriplejik ve modifiye Rankin skoru 5 idi. Abdomen bilgisayarlı tomografi karaciğer ve pankreasta kitle lezyonlarının olduğunu gösterdi. Lezyonyonlardan alınan biyopsiler pankreas orjinli küçük hücreli nöroendokrin karsinom olarak raporlandı. Elektrofizyolojik testler ciddi sensorimotor aksonal polinöropati ile uyumluluk gösteriyordu Diğer polinöropati nedenleri dışlandıktan sonra, hastaya paraneoplastik sensorimotor aksonal polinöropati tanısı konuldu. Hastanın fonksiyonel kapasitesi düşük olduğundan palyatif tedavi planlandı. Sonuç: PNS’li hastalarda uygun tedavinin başlanması için erken kanser tanısının konulması önem arz etmektedir.Öğe Sex estimation based on frontal sinus computed tomography images using machine learning and artificial neural networks(Taylor & Francis Ltd, 2025) Kaya, Seren; Harmandaoglu, Oguzhan; Ozturk, Oguzhan; Secgin, Yusuf; Senol, Deniz; Onbas, OmerDue to its anatomical uniqueness, the frontal sinus (FS) shows significant inter-individual differences by ancestry, age, and sex, making it useful for preliminary identification processes. This study aims to estimate sex using machine learning (ML) algorithms and artificial neural networks (ANN) applied to morphometric data from FS computed tomography (CT) images. This retrospective study analysed CT scans of 338 females and 338 males aged 18-65. FS measurements comprised sinus floor anteroposterior length, volume, area, height, depth, width, and anterior wall thickness (AWT). Sex estimation was performed using several ML algorithms, including Linear Discriminant Analysis, Quadratic Discriminant Analysis, Logistic Regression, Extra Trees Classifier, Decision Tree, Random Forest, k-Nearest Neighbours, and Gaussian Naive Bayes. Additionally, a multilayer perceptron classifier, representing ANN models, was utilized. The highest classification accuracy (94%) was achieved by the Logistic Regression model. According to the SHapley Additive exPlanations analysis, the two most influential parameters were identified as the right and left AWT, respectively. This study, with a comparatively large sample size, found that all morphometric FS parameters - especially AWT - hold significant potential in forensic identification. ML- and ANN-based models showed high classification accuracy, surpassing previous studies. These findings may guide future research involving diverse populations and regions.Öğe Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks(Bmc, 2025) Secgin, Yusuf; Kaya, Seren; Harmandaoglu, Oguzhan; Ozturk, Oguzhan; Senol, Deniz; Onbas, Omer; Yilmaz, NihatBackgroundThe skull is highly durable and plays a significant role in sex determination as one of the most dimorphic bones. The facial canal (FC), a clinically significant canal within the temporal bone, houses the facial nerve. This study aims to estimate sex using morphometric measurements from the FC through machine learning (ML) and artificial neural networks (ANNs).Materials and methodsThe study utilized Computed Tomography (CT) images of 200 individuals (100 females, 100 males) aged 19-65 years. These images were retrospectively retrieved from the Picture Archiving and Communication Systems (PACS) at D & uuml;zce University Faculty of Medicine, Department of Radiology, covering 2021-2024. Bilateral measurements of nine temporal bone parameters were performed in axial, coronal, and sagittal planes. ML algorithms including Quadratic Discriminant Analysis (QDA), Linear Discriminant Analysis (LDA), Decision Tree (DT), Extra Tree Classifier (ETC), Random Forest (RF), Logistic Regression (LR), Gaussian Naive Bayes (GaussianNB), and k-Nearest Neighbors (k-NN) were used, alongside a multilayer perceptron classifier (MLPC) from ANN algorithms.ResultsExcept for QDA (Acc 0.93), all algorithms achieved an accuracy rate of 0.97. SHapley Additive exPlanations (SHAP) analysis revealed the five most impactful parameters: right SGAs, left SGAs, right TSWs, left TSWs and, the inner mouth width of the left FN, respectively.ConclusionsFN-centered morphometric measurements show high accuracy in sex determination and may aid in understanding FN positioning across sexes and populations. These findings may support rapid and reliable sex estimation in forensic investigations-especially in cases with fragmented craniofacial remains-and provide auxiliary diagnostic data for preoperative planning in otologic and skull base surgeries. They are thus relevant for surgeons, anthropologists, and forensic experts.Clinical trial numberNot applicable.Öğe Shear wave elastography and T2*mapping in the detection of early-stage trochlear cartilage damage(Sage Publications Ltd, 2023) Kaplan, Meral; Guclu, Derya; Unlu, Elif Nisa; Ogul, Hayri; Onbas, OmerBackground The presence of degenerative changes in joint cartilage is one of the major features in osteoarthritis. Purpose To investigate the contribution of shear wave elastography and T2* mapping to the early diagnosis of femoral trochlear cartilage damage. Material and Methods A total of 30 individuals whose trochlear cartilage structure was evaluated as normal in conventional magnetic resonance imaging (MRI) sequences (control group) were prospectively compared with 30 patients who had early-stage cartilage damage findings on conventional MRI (study group), by performing B-mode ultrasonography, shear wave elastography, and T2* mapping. Cartilage thickness, shear wave, and T2* mapping measurements were recorded. Results After evaluating B-mode ultrasound and conventional MRI sequences, cartilage thickness was found to be significantly higher in the study group on both B-mode ultrasound and MRI. Shear wave velocity values of the study group (medial condyle [MC] 4.65 & PLUSMN; 1.11 m/sn, intercondylar [IC] 4.74 & PLUSMN; 1.20 m/sn, and lateral condyle [LC] 5.42 & PLUSMN; 1.48 m/sn) were observed to be significantly lower than the control group (MC 5.60 & PLUSMN; 0.77 m/sn, IC 5.85 & PLUSMN; 0.96 m/sn, and LC 5.63 & PLUSMN; 1.05 m/sn) (P < 0.05). T2* mapping values were significantly higher in the study group (MC 32.38 & PLUSMN; 4.04 ms, IC 35.78 & PLUSMN; 4.85 ms, and LC 34.04 & PLUSMN; 3.40 ms) than that of the control group (MC 28.07 & PLUSMN; 3.29 ms, IC 30.63 & PLUSMN; 3.45 ms, and LC 29.02 & PLUSMN; 3.24 ms). Conclusion Shear wave elastography and T2* mapping are reliable methods for evaluating early-stage trochlear cartilage damage.Öğe Visual assessment of cerebrospinal fluid flow dynamics using 3D T2-weighted SPACE sequence-based classification system(Sage Publications Ltd, 2024) Naldemir, Ibrahim Feyyaz; Karaman, Ahmet Kursat; Ogul, Hayri; Onbas, OmerBackground: Flow-related signal void artifacts can be visualized on the T2-weighted (T2W) three-dimensional sampling perfection with application-optimized contrast (3D-SPACE) sequence. Flow void artifacts in the cerebral aqueduct and the fourth ventricle can provide information about cerebrospinal fluid (CSF) flow dynamics. Purpose: In this study, we aimed to test the performance of the T2W 3D-SPACE sequence in assessing the CSF flow in the aqueduct and/or fourth ventricle. Material and Methods: A total of 137 patients (age range = 3-89 years) who underwent CSF flow study were included. The amount of signal loss on T2W 3D-SPACE due to flow in the aqueduct and fourth ventricle was assessed and graded using a 4-point scale of 0 (absence of flow void) to 3 (signal void filling the aqueduct and entire fourth ventricle). A correlation was then sought between the quantitative values obtained by phase-contrast magnetic resonance imaging (PC-MRI) and the amount of signal void in the 3D-SPACE sequence. Results: At the aqueduct level, there was a statistically significant difference in the forward flow velocity and the flow volume among different grades (all P < 0.001). In the grade 3 group, CSF peak systolic flow velocity and mean flow volume were found to be significantly higher than in the other grades (P < 0.001). The mean aqueduct area in the grade 0 group was found to be significantly different from that in the other classes (P < 0.001). Conclusion: The amount of signal loss in the fourth ventricle observed on T2W 3D-SPACE is correlated with the peak systolic velocity and flow volume measured quantitatively in PC-MRI.
