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Comparison of surgical approaches to the hippocampal formation with artificial intelligence
(2025-12-01) DÜNDAR T. T.; KURT PEHLİVANOĞLU M.; EKER A. G.; Albayrak N. B.; Mutluer A. S.; YURTSEVER İ.; DOĞAN İ.; Duru N.; Ture U.
The relatively complex functional anatomy of the mediobasal temporal region makes surgical approaches to this area challenging. Several studies describe various surgical approaches, along with their combinations and modifications, to reach lesions of this region. Some of these surgical approaches have been compared using artificial intelligence-based approaches that can be predicted, classified, and analyzed for complex data. Several surgical approaches, such as anterior transsylvian, trans-superior temporal sulcus, trans-middle temporal gyrus, subtemporal-transparahippocampal, presigmoid-retrolabyrinthine, supratentorial-infraoccipital, and paramedian supracerebellar-transtentorial, were selected for comparison. Magnetic resonance images (MRIs) were taken according to the criteria specified by the Radiology Department. With an open-source software tool, volumetric data from cranial MRIs were segmented and anatomical structures in the main regions were reconstructed. The Q-learning algorithm was used to find pathways similar to these standard surgical pathways. The Q-learning scores among the selected pathways are as follows: anterior transsylvian (Q_A) = 31.01, trans-superior temporal sulcus (Q_B) = 25.00, trans-middle temporal gyrus (Q_C) = 28.92, subtemporal-transparahippocampal (Q_D) = 23.51, presigmoid- retrolabyrinthine (Q_E) = 27.54, supratentorial-infraoccipital (Q_F) = 27.2, and paramedian supracerebellar-transtentorial (Q _G) = 21.04. The Q-value score for the supracerebellar transtentorial approach was the highest among the examined approaches and therefore optimal. A difference was also found between the total risk score of all points with pathways drawn by clinicians and the total risk scores of the pathways formed and followed by Q-learning. Artificial intelligence-based approaches may significantly contribute to the success of the surgical approaches examined. Furthermore, artificial intelligence can contribute to clinical outcomes in both preoperative surgical planning and intraoperative technical equipment-assisted neurosurgery. However, further studies with more detailed data are needed for more sensitive results.
Comparison of conventional and modified sling suture techniques in free gingival graft operations-a randomized controlled clinical trial
(2025-12-01) SHAKILIYEVA S.; Sahin D.; GÜNPINAR Ş.; GÜRSEL M.
Background The aim of this study was to investigate the effects of conventional suture (CS) and modified sling suture (MSS) techniques, applied in free gingival graft (FGG) surgery using gingival unit graft (GUT) and conventional graft (CG) techniques, on clinical parameters and graft dimensions. Methods 52 individuals having Cairo Type 2 (RT2) and Type 3 (RT3) gingival recessions in mandibular anterior were divided into four groups as (a) GUT + MSS (n = 13), (b) GUT + CS (n = 13), (c) CG + MSS (n = 13) and (d) CG + CS (n = 13). Keratinized tissue width (KTW), relative gingival recession height (rGRH), and relative vestibule depth (rVD) measurements were recorded using a digital caliper and UNC 15 periodontal probe. Dimensional changes (Delta) of the graft surface area (GSA) was determined by ImageJ software. All measurements were done at baseline, 1st and 3rd months. Results It was determined that the increase in KTW in the 1st and 3rd months in GUT + CS group was significantly higher than GUT + MSS group (p < 0.05). There was no statistically significant difference in Delta rVD and Delta rGRH values between the groups. When Delta GSA (mm2) values were compared between the groups, the decrease in the 1st and 3rd months in the CG + MSS group was found to be significantly higher than the GUT + MSS and GUT + CS groups (p < 0.05). Conclusion Within the limits of this study, it can be concluded that keratinized tissue can be obtained successfully with both GUT or CG techniques in FGG surgery, on the other hand, regardless of the suture technique, GUT showed less graft shrinkage than CG.
Osteoloji
(Güneş Kitabevi, 2025-12-01) Arifoğlu Y.
A cross-sectional study on ChatGPT's alignment with clinical practice guidelines in musculoskeletal rehabilitation
(2025-12-01) SAFRAN E.; YILDIRIM S.
BackgroundAI models like ChatGPT have the potential to support musculoskeletal rehabilitation by providing clinical insights. However, their alignment with evidence-based guidelines needs evaluation before integration into physiotherapy practice.ObjectiveTo evaluate the performance of ChatGPT (GPT-4 model) in generating responses to musculoskeletal rehabilitation queries by comparing its recommendations with evidence-based clinical practice guidelines (CPGs).DesignThis study was designed as a cross-sectional observational study.MethodsTwenty questions covering disease information, assessment, and rehabilitation were developed by two experienced physiotherapists specializing in musculoskeletal disorders. The questions were distributed across three anatomical regions: upper extremity (7 questions), lower extremity (9 questions), and spine (4 questions). ChatGPT\"s responses were obtained and evaluated independently by two raters using a 5-point Likert scale assessing relevance, accuracy, clarity, completeness, and consistency. Weighted kappa values were calculated to assess inter-rater agreement and consistency within each category.ResultsChatGPT\"s responses received the highest average score for clarity (4.85), followed by accuracy (4.62), relevance (4.50), and completeness (4.20). Consistency received the lowest score (3.85). The highest agreement (weighted kappa = 0.90) was observed in the disease information category, whereas rehabilitation displayed relatively lower agreement (weighted kappa = 0.56). Variability in consistency and moderate weighted kappa values in relevance and clarity highlighted areas requiring improvement.ConclusionsThis study demonstrates ChatGPT\"s potential in providing guideline-aligned information in musculoskeletal rehabilitation. However, due to observed limitations in consistency, completeness, and the ability to replicate nuanced clinical reasoning, its use should remain supplementary rather than as a primary decision-making tool. While it performed better in disease information, as evidenced by higher inter-rater agreement and scores, its performance in the rehabilitation category was comparatively lower, highlighting challenges in addressing complex, nuanced therapeutic interventions. This variability in consistency and domain-specific reasoning underscores the need for further refinement to ensure reliability in complex clinical scenarios.Clinical trial numberNot applicable.