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Journals / Sakarya Tıp Dergisi / 2026 / Volume: 9 Issue: 2

A new method for discriminating cerebellar tumors from each other: algorithmic approach

Serebellar Tümörleri Birbirinden Ayırt Etmek İçin Yeni Bir Yöntem: Algoritmik Yaklaşım

Osman Melih Topcuoğlu(Yeditepe Üniversitesi Tıp Fakültesi)0000-0002-4008-3395
Pages
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Publication Date
2019-06-28
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

Conclusion: CT in adults might be differentiated from each other by using some MR imaging clues and patient characteristics.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: To evaluate the MR imaging findings of the cerebellar tumors (CT) in adults and to make an algorithm to discriminate these tumors from each other.
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Key Findings & Data:Brain MRs and patient records were evaluated for pathological diagnosis, imaging findings and Ki-67 labeling index.
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Conclusion & Impact:Conclusion: CT in adults might be differentiated from each other by using some MR imaging clues and patient characteristics.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Apparent diffusion coefficient · cerebellum · cerebellar tumors

Abstract

Objective: To evaluate the MR imaging findings of the cerebellar tumors (CT) in adults and to make an algorithm to discriminate these tumors from each other. Materials and Methods: A dult patients with CT who were treated surgically were included. Brain MRs and patient records were evaluated for pathological diagnosis, imaging findings and Ki-67 labeling index. The apparent diffusion coefficient (ADC) values of the tumors and centrum semiovale (CS) and the ratio of each other were noted. Kruskal-Wallis test was used for comparison. Results: 100 adults (45 women, 55 men with a mean age of 46.6 ± 15.6 years) with pathologically proven CT were included. Tumors were divided into five groups as: a. primitive neuro-ectodermal tumor (PNET) + medulloblastoma ( MB), b. grade 3+4 gliomas, c. grade 1+2 gliomas, d. metastasis (MET) and e. lymphoma. The ratio of the mean ADC (x10 -3 mm 2 /s) of the tumor to those of CS was 1.21 ± 0.22, 1.38 ± 0.93, 1.98 ± 0.69, 1.48 ± 0.45 and 1.25 ± 0.11 for PNET&MBs, grade 3+4 gliomas, grade 1+2 gliomas, METs and lymphomas, respectively. Significant difference was detected between grade 1+2 gliomas and PNET&MB ( P =0.018), MET ( P =0.004) and lymphoma ( P =0.002). Conclusion: CT in adults might be differentiated from each other by using some MR imaging clues and patient characteristics.

Özet

Amaç: Erişkinlerde serebellar tümörlerin (ST) MR görüntüleme bulgularını inceleyip birbirlerinden ayrım için algoritmik yaklaşım oluşturabilmek. Gereç ve Yöntemler: Çalışmaya, cerrahi olarak tedavi edilmiş ST’li erişkin hastalar dahil edildi . Beyin MR’ları ve hasta kayıtları patolojik tanı, görüntüleme bulguları ve Ki-67 indeksi açısından tarandı. Tümöre ve sentrum semiovale (SS)’ye ait görünür difüzyon katsayıları (GDK) ile birbirlerine oranları hesaplandı. Karşılaştırma için Kruskal-Wallis testi kullanıldı. Bulgular: Çalışmaya yaş ortalaması 46.6 ± 15.6 yıl olan 100 (45 kadın, 55 erkek) ST’li hasta dahil edildi. Tümörler 5 gruba ayrıldı: a. primitif nöroektodermal tumor (PNET)+medulloblastom (MB) b . evre 3+4 gliomlar, c. evre 1+2 gliomlar, d. metastaz (MET) ve e. lenfoma. PNET&MB, evre 3+4 gliomlar, evre1+2 gliomlar, MET and lenfomalara ait ortalama ST/SS GDK (x10 -3 mm 2 /s) değerleri sıraıyla1.21 ± 0.22, 1.38 ± 0.93, 1.98 ± 0.69, 1.48 ± 0.45 and 1.25 ± 0.11. Evre 1+2 gliomlar ve PNET&MB’ler ( P =0.018), MET ( P =0.004) ve lenfomalar ( P =0.002) arasında anlamlı fark vardı. Sonuç: Erişkinde ST’ler bazı MR ipuçları ve hasta özellikleri ile birbirlerinden ayırt edilebilir.

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Cite This Article

Topcuoğlu, O. M. (2019). A new method for discriminating cerebellar tumors from each other: algorithmic approach. Sakarya Tıp Dergisi, Volume: 9 Issue: 2. https://doi.org/10.31832/smj.471978

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