Publication: Biologically Guided Gamma Knife Dose Painting for Recurrent High-Grade Gliomas: A Retrospective Study Using Functional MRI Techniques
| dc.contributor.author | SEYİTHANOĞLU M. H. | |
| dc.contributor.author | YURTSEVER İ. | |
| dc.contributor.author | Gundag Papaker M. | |
| dc.contributor.author | Mutluer A. S. | |
| dc.contributor.author | Dundar T. T. | |
| dc.contributor.author | Kitis S. | |
| dc.contributor.author | Akdur K. | |
| dc.contributor.author | MAYADAĞLI A. | |
| dc.date.accessioned | 2025-12-31T21:37:32Z | |
| dc.date.issued | 2025-12-03 | |
| dc.description.abstract | BACKGROUND This study examines the efficacy of biologically guided dose painting in Gamma Knife stereotactic radiosurgery (GKSRS) to improve radiographic response in patients with recurrent high-grade gliomas by increasing radiation dosage in functionally active tumor subregions identified through magnetic resonance spectroscopy (MRS) and T1-weighted perfusion magnetic resonance imaging (T1-PMRI). MATERIAL AND METHODS In this single-arm cohort of patients (n=23) with recurrent high-grade glioma, all patients previously treated with surgery, chemotherapy, and fractionated radiotherapy underwent GKSRS. Functional imaging (MRS and T1-weighted PMRI) delineated metabolically active (\"aggressive\") and less active (\"passive\") tumor regions. A modified radiosurgery plan prescribed 18 Gy to aggressive and 15 Gy to passive zones. For intra-patient comparison, a uniform-dose plan (plan 1, 16 Gy) was generated but not delivered. All statistical analyses were performed in Python 3.11 (SciPy-v1.11, statsmodels-v0.14, lifelines-v0.28) executed in Visual Studio Code 1.88 (Microsoft). RESULTS Across 23 patients, plan 2 vs plan 1 showed no significant change in whole-brain mean dose (P=0.716), integral dose (P=0.792), or V12 (P=0.583). Among 11 patients with follow-up imaging, K-trans decreased significantly (median, -18%; P=0.028; Wilcoxon) with a trend for initial area under the gadolinium concentration-time curve (IAUC; median, -22%; P=0.031 for table; overall P=0.08 for initial under curve analysis). Higher baseline K-trans correlated with greater K-trans reduction (r=-0.84, P=0.0012). CONCLUSIONS Using advanced MRI techniques (accounting for K-trans and IAUC on T1-PMRI, and MRS) to determine aggressive zones in salvage treatment for recurrent high-grade gliomas, and then focusing radiotherapy on these zones, can increase Gamma Knife efficiency without increasing the morbidity rate. | |
| dc.identifier.citation | SEYİTHANOĞLU M. H., YURTSEVER İ., Gundag Papaker M., Mutluer A. S., Dundar T. T., Kitis S., Akdur K., MAYADAĞLI A., "Biologically Guided Gamma Knife Dose Painting for Recurrent High-Grade Gliomas: A Retrospective Study Using Functional MRI Techniques", Medical science monitor : international medical journal of experimental and clinical research, cilt.31, 2025 | |
| dc.identifier.doi | 10.12659/msm.949489 | |
| dc.identifier.issn | 1643-3750 | |
| dc.identifier.pubmed | 41332119 | |
| dc.identifier.scopus | 105023593007 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105023593007&origin=inward | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12645/41537 | |
| dc.identifier.volume | 31 | |
| dc.identifier.wos | WOS:001632626700001 | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Tıp | |
| dc.subject | Sağlık Bilimleri | |
| dc.subject | Temel Tıp Bilimleri | |
| dc.subject | Medicine | |
| dc.subject | Health Sciences | |
| dc.subject | Fundamental Medical Sciences | |
| dc.subject | Klinik Tıp (Med) | |
| dc.subject | Klinik Tıp | |
| dc.subject | Tıp Genel & Dahili | |
| dc.subject | Clinical Medicine (Med) | |
| dc.subject | Clinical Medicine | |
| dc.subject | Medicine General & Internal | |
| dc.subject | Genel Tıp | |
| dc.subject | General Medicine | |
| dc.title | Biologically Guided Gamma Knife Dose Painting for Recurrent High-Grade Gliomas: A Retrospective Study Using Functional MRI Techniques | |
| dc.type | article | |
| dspace.entity.type | Publication | |
| local.avesis.id | ce4ddf4a-3a6c-49ba-86d3-0906003e7719 |
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