Person: KİTİŞ, SERKAN
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Publication Open Access Relationship Between Degeneration or Sagittal Balance With Modic Changes in the Cervical Spine(2021-01-27T00:00:00Z) Kitiş, SERKAN; Çevik, Serdar; Kaplan, Atilla; Yılmaz, Hakan; Katar, Salim; Cömert, Serhat; Ünsal, Ülkün; KİTİŞ, SERKANObjective: This study evaluates the relationship between degenerative and Modic changes (MCs) in the cervical spine and compares the results with the cervical sagittal balance parameters. Methods: We retrospectively reviewed 275 patients with neck pain who applied to our outpatient clinic and underwent cervical magnetic resonance imaging (MRI) and cervical anteroposterior (AP)/lateral (Lat) X-ray radiography between January 2016 and January 2018. The clinics, demographic information, and radiological findings of the patients were examined. Modic changes, disc degeneration, and facet degeneration (FD) were examined by cervical MRI, and T1 slope and Cobb angle were measured by cervical AP/Lat X-ray radiography. These results were compared to evaluate their relations with each other. Results: No relationship between the presence or absence of degenerative changes (Modic changes, facet degeneration, and disc degeneration) and sagittal balance parameters (T1 slope and Cobb angle) was found. However, when each cervical segment was examined separately, facet degeneration at the C4-C5 level and Modic changes at the C3-C4, C4-C5, and C6-C7 levels were statistically significant with the Cobb angles, and the Modic changes at the C3-C4 level and disc degeneration at the C2-C3 level were found to be significant with T1 slope values. Conclusions: Our findings indicate that MCs increased with decreased cervical curvature, increasing disc and facet degeneration, although the causal mechanisms are not clear.Publication 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 Erken Dönem Subaraknoid Kanamanın Serum Endotelin ve von Willebrand Faktörü Üzerindeki Etkisinin Klinik ve Radyolojik Parametrelerle Korelasyonu(2020-09-01T00:00:00Z) Kitiş, Serkan; Gundag, Meliha; Güler, Eray Metin; KİTİŞ, SERKAN; GUNDAG, MELİHAPublication Metadata only Meningiomlara Genel Bakış(2020-07-01T00:00:00Z) Kitiş, Serkan; KİTİŞ, SERKANPublication Metadata only Spinal tümörler nedeniyle ameliyat edilen 101 hastanın retrospektif kohort analizi: Tek merkez deneyimi(2020-08-01T00:00:00Z) Kitiş, Serkan; Gundag, Meliha; KİTİŞ, SERKAN; GUNDAG, MELİHAPublication Metadata only Chiari Type 1 malformation: CSF flow dynamics and morphology in the posterior fossa and craniocervical junction and correlation of these findings with syrinx formation.(2022-06-22T00:00:00Z) Yilmaz, T F; Toprak, H; Sari, L; Oz, I I; Kitis, S; Kaya, A; Alkan, ALPAY; TOPRAK, HÜSEYİN; KİTİŞ, SERKAN; ALKAN, ALPAYPublication Metadata only Meningiomlara Genel Bakış(2020-07-01T00:00:00Z) Kitiş, Serkan; KİTİŞ, SERKANPublication Metadata only McFARLANE RAT DORSAL CİLT FLEP MODELİNDE AMNİOMAX’IN NEKROZ ÖNLEYİCİ ETKİSİNİN ARAŞTIRILMASI(2020-07-01T00:00:00Z) Dündar, Tolga Turan; Yıldız, Kemalettin; Tosuner, Zeynep; Mihrapoğlu, Semih Lütfi; Kitiş, Serkan; DÜNDAR, TOLGA TURAN; YILDIZ, KEMALETTİN; KİTİŞ, SERKANPublication Open Access Clinical Evaluation of Decompressive Craniectomy in Malignant Middle Cerebral Artery Infarction using 3D Area and Volume Calculations(2021-07-01T00:00:00Z) Kitiş, Serkan; Çevik, Serdar; Köse, Kevser B.; Baygül, Arzu; Cömert, Serhat; Ünsal, Ülkün Ü.; Gündağ Papaker, Meliha; KİTİŞ, SERKAN; GUNDAG, MELİHAObjective: We aimed to measure the craniectomy area using three-dimensional (3D) anatomic area and volume calculations to demonstrate that it can be an effective criterion for evaluating survival and functional outcomes of patients with malignant middle cerebral artery (MCA) infarction. Material and methods: The patients diagnosed with malignant ischemic stroke between 2013 and 2018, for which they underwent surgery due to deterioration in their neurological function, were retrospectively reviewed. Radiological images of all patients were evaluated; total brain tissue volume, ischemic brain tissue volume, total calvarial bone area, and decompression bone area were measured using 3D anatomical area and volume calculations. Results: In total, 45 patients (27 males and 18 females) had been treated with decompressive craniectomy (DC). The removed bone area was found to be significantly related to the outcome in patients with MCA infarction. The average decompression bone area and mean bone removal rate for patients who died after DC were 112 ± 27 cm2 and 20%, whereas these values for surviving patients were 149 ± 29 cm2 and 26% (P = 0.001), respectively. At the 6-month follow-up, the average decompression bone area and mean bone removal rate for patients with severe disability were 126 ± 30 cm2 and 22.2%, whereas these values for patients without severe disability were 159 cm2 ± 26 and 28.4% (P = 0.001), respectively. Conclusion: In patients with malignant MCA infarction, the decompression area is associated with favorable functional outcomes, first, survival and second, 6-month modified Rankin scale score distribution after craniectomy.