Person: KİTİŞ, SERKAN
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Publication Metadata only NÖROFİBROMATOZİS TİP-1’Lİ BİR HASTADA EKZOFİTİK DEV HÜCRELİ GLİOBLASTOMA: OLGU SUNUMU(2017-04-02) GUNDAG, MELİHA; KİTİŞ, SERKAN; SEYİTHANOĞLU, MEHMET HAKAN; DÜNDAR, TOLGA TURAN; GUNDAG, MELİHA; KİTİŞ, SERKAN; SEYİTHANOĞLU, MEHMET HAKAN; DÜNDAR, TOLGA TURANPublication Metadata only Disk materyallerindeki oksidatif stress disk herniasyonunda önemli bir faktör müdür?(2016-03-27) Taşpınar, Özgür; AYDIN, TEOMAN; SEYİTHANOĞLU, MEHMET HAKAN; KESKİN, YAŞAR; Kepekçi, Müge; GÜLER, ERAY METİN; KİTİŞ, SERKAN; DÜNDAR, TOLGA TURAN; AYDIN, TEOMAN; SEYİTHANOĞLU, MEHMET HAKAN; KESKİN, YAŞAR; GÜLER, ERAY METİN; KİTİŞ, SERKAN; DÜNDAR, TOLGA TURANPublication Metadata only VENTRİKÜLO-PERİTONEAL ŞANTIN GEÇ KOMPLİKASYONU: DÖRT OLGUDA PERİTONEAL KATETERİN ANAL PROLAPSUSU(2011-04-26) SEYİTHANOĞLU, MEHMET HAKAN; GUNDAG, MELİHA; DOGAN, KAZIM; KİTİŞ, SERKAN; öztürk, şeref; DÜNDAR, TOLGA TURAN; Çevik, Serdar; SEYİTHANOĞLU, MEHMET HAKAN; GUNDAG, MELİHA; KİTİŞ, SERKAN; DÜNDAR, TOLGA TURANPublication Metadata only Anevrizmatik subaraknoid kanama sonrası prognostik faktör olarak platelet volüm indeksinin değerlendirilmesi(2019-09-01) Dündar, Tolga Turan; DÜNDAR, TOLGA TURAN; KİTİŞ, SERKAN; YURTSEVER, İSMAİLPublication Metadata only BRAIN TUMOR TREATMENT AND NANOTECNOLOGY(2017-11-08) DÜNDAR, TOLGA TURAN; SEYİTHANOĞLU, MEHMET HAKAN; GUNDAG, MELİHA; gökoğlu, abdulkerim; KİTİŞ, SERKAN; Özek, ERDİNÇ; Abdallah, Anas; Doğan, İhsan; Mutluer, Ahmet Serdar; DÜNDAR, TOLGA TURAN; SEYİTHANOĞLU, MEHMET HAKAN; GUNDAG, MELİHA; KİTİŞ, SERKANPublication Open Access Investigation of Brain Impairment Using Diffusion-Weighted and Diffusion Tensor Magnetic Resonance Imaging in Experienced Healthy Divers.(2018-11-17) SEYITHANOĞLU, MEHMET HAKAN; ABDALLAH, ANAS ABDELRAHIM SA; Dündar, TOLGA TURAN; KITIŞ, SERKAN; ARALAŞMAK, AYŞE; Gündağ, Papaker; SASANI, H; SEYİTHANOĞLU, MEHMET HAKAN; ABDALLAH, ANAS ABDELRAHıM SA; DÜNDAR, TOLGA TURAN; KİTİŞ, SERKAN; ARALAŞMAK, AYŞE; GUNDAG, MELİHABackground: The aim of this study was to understand the changes of decompression illness in healthy divers by comparing diffusion-weighted (DWI) and diffusion tensor MRI findings among healthy professional divers and healthy non-divers with no history of diving. Material/Methods: A total of 26 people were recruited in this prospective study: 11 experienced divers with no history of neurological decompression disease (cohort) and 15 healthy non-divers (control). In all study subjects, we evaluated apparent diffusion coefficient (ADC) and type of diffusion tensor metric fractional anisotropy (FA) values of different brain locations (e.g., frontal and parieto-occipital white matter, hippocampus, globus pallidus, putamen, internal capsule, thalamus, cerebral peduncle, pons, cerebellum, and corpus callosum). Results: ADC values of hippocampus were high in divers but low in the control group; FA values of globus pallidus and putamen were lower in divers compared to the control group. DWI depicted possible changes due to hypoxia in different regions of the brain. Statistically significant differences in ADC values were found in hypoxia, particularly in the hippocampus (p=0.0002), while FA values in the globus pallidus and putamen were statistically significant (p=0.015 and p=0.031, respectively). We detected forgetfulness in 6 divers and deterioration in fine-motor skills in 2 divers (p=0.002 and p=0.17, respectively). All of them were examined using neuro-psychometric tests. Conclusions: Repeated hyperbaric exposure increases the risk of white matter damage in experienced healthy divers without neurological decompression illness. The hippocampus, globus pallidus, and putamen are the brain areas responsible for memory, learning, navigation, and fine-motor skills and are sensitive to repeated hyperbaric exposurePublication Metadata only ÇERÇEVESİZ NÖRONAVİGASYON YARDIMLI BEYİN BİOPSİSİ:GÜVENLİĞİ,EFEKTİVİTESİ VE TECRÜBEMİZ(2017-03-29) ÖZEK, ERDİNÇ; SEYİTHANOĞLU, MEHMET HAKAN; KİTİŞ, SERKAN; DÜNDAR, TOLGA TURAN; TEKİN, ABDURRAHİM; HATİBOĞLU, MUSTAFA AZİZ; ÖZEK, ERDİNÇ; SEYİTHANOĞLU, MEHMET HAKAN; KİTİŞ, SERKAN; DÜNDAR, TOLGA TURAN; TEKİN, ABDURRAHIM; HATİBOĞLU, MUSTAFA AZİZPublication Metadata only Evaluating the p-STAT3 and PHH-3 Expressions in WHO Grade I Benign Meningiomas(2018-01-25) HATİBOĞLU, MUSTAFA AZİZ; ABDALLAH, ANAS ABDELRAHIM SA; TOSUNER, ZEYNEP; Akdağ, Halil; ÖZEK, ERDİNÇ; DÜNDAR, TOLGA TURAN; KİTİŞ, SERKAN; GUNDAG, MELİHA; SEYİTHANOĞLU, MEHMET HAKAN; TEKİN, ABDURRAHİM; HATİBOĞLU, MUSTAFA AZİZ; ABDALLAH, ANAS ABDELRAHıM SA; TOSUNER, ZEYNEP; ÖZEK, ERDİNÇ; DÜNDAR, TOLGA TURAN; KİTİŞ, SERKAN; GUNDAG, MELİHA; SEYİTHANOĞLU, MEHMET HAKAN; TEKİN, ABDURRAHIMPublication Open Access Machine Learning-Based Surgical Planning for Neurosurgery: Artificial Intelligent Approaches to the Cranium(2022-04-01T00:00:00Z) Dündar, Tolga Turan; Yurtsever, İsmail; Kurt Pehlivanoğlu, Meltem; Yıldız, Uğur; Eker, Ayşegül; Demir, Mehmet Ali; Mutluer, Ahmet Serdar; Tektaş, Recep; Kazan, Mevlude Sila; Kitiş, Serkan; Gokoglu, Abdulkerim; Doğan, İhsan; Duru, Nevcihan; DÜNDAR, TOLGA TURAN; YURTSEVER, İSMAİL; KİTİŞ, SERKANObjectives: Artificial intelligence (AI) applications in neurosurgery have an increasing momentum as well as the growing number of implementations in the medical literature. In recent years, AI research define a link between neuroscience and AI. It is a connection between knowing and understanding the brain and how to simulate the brain. The machine learning algorithms, as a subset of AI, are able to learn with experiences, perform big data analysis, and fulfill human-like tasks. Intracranial surgical approaches that have been defined, disciplined, and developed in the last century have become more effective with technological developments. We aimed to define individual-safe, intracranial approaches by introducing functional anatomical structures and pathological areas to artificial intelligence. Methods: Preoperative MR images of patients with deeply located brain tumors were used for planning. Intracranial arteries, veins, and neural tracts are listed and numbered. Voxel values of these selected regions in cranial MR sequences were extracted and labeled. Tumor tissue was segmented as the target. Q-learning algorithm which is a model-free reinforcement learning algorithm was run on labeled voxel values (on optimal paths extracted from the new heuristic-based path planning algorithm), then the algorithm was assigned to list the cortico-tumoral pathways that aim to remove the maximum tumor tissue and in the meantime that functional anatomical tissues will be least affected. Results: The most suitable cranial entry areas were found with the artificial intelligence algorithm. Cortico-tumoral pathways were revealed using Q-learning from these optimal points. Conclusions: AI will make a significant contribution to the positive outcomes as its use in both preoperative surgical planning and intraoperative technique equipment assisted neurosurgery, its use increasedPublication Metadata only Comparison of TOF MRA, Contrast-Enhanced MRA and Subtracted CTA from CTP in Residue Evaluation of Treated Intracranial Aneurysms(2018-01-01) Dundar, TOLGA TURAN; Kits, Serkan; Ozdemir, HÜSEYİN; Seyithanoglu, MEHMET HAKAN; Uysal, Omer; Toprak, HÜSEYİN; Ozek, ERDİNÇ; Alkan, ALPAY; DÜNDAR, TOLGA TURAN; ARALAŞMAK, AYŞE; ÖZDEMİR, HÜSEYIN; SEYİTHANOĞLU, MEHMET HAKAN; UYSAL, ÖMER; TOPRAK, HÜSEYİN; KİTİŞ, SERKAN; ÖZEK, ERDİNÇ; ALKAN, ALPAYAIM: To compare effectiveness of contrast-enhanced magnetic resonance angiography (CE-MRA), 3D-Time-of-flight magnetic resonance angiography (3D-TOF-MRA) and subtracted computed tomography angiography from computed tomography perfusion (sub-CTA) in residue evaluation of intracranial aneurysms treated either with coiling or clipping.
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