The effect of tumor shape irregularity on Gamma Knife treatment plan quality and treatment outcome: an analysis of 234 vestibular schwannomas.

Autor: Sümer E; Institute of Biomedical Engineering, Boğaziçi University, Kandilli Campus, Rasathane Cad, 34684, Üsküdar, Istanbul, Turkey., Tek E; Department of Radiation Oncology, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Türe OA; Department of Radiation Oncology, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Şengöz M; Department of Neurosurgery, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Dinçer A; Department of Radiology, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Özcan A; Department of Electrical and Electronics Engineering, Boğaziçi University, Istanbul, Turkey., Pamir MN; Department of Neurosurgery, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Özduman K; Department of Neurosurgery, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey., Ozturk-Isik E; Institute of Biomedical Engineering, Boğaziçi University, Kandilli Campus, Rasathane Cad, 34684, Üsküdar, Istanbul, Turkey. esin.ozturk@boun.edu.tr.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2022 Dec 17; Vol. 12 (1), pp. 21809. Date of Electronic Publication: 2022 Dec 17.
DOI: 10.1038/s41598-022-25422-9
Abstrakt: The primary aim of Gamma Knife (GK) radiosurgery is to deliver high-dose radiation precisely to a target while conforming to the target shape. In this study, the effects of tumor shape irregularity (TSI) on GK dose-plan quality and treatment outcomes were analyzed in 234 vestibular schwannomas. TSI was quantified using seven different metrics including volumetric index of sphericity (VioS). GK treatment plans were created on a single GK-Perfexion/ICON platform. The plan quality was measured using selectivity index (SI), gradient index (GI), Paddick's conformity index (PCI), and efficiency index (EI). Correlation and linear regression analyses were conducted between shape irregularity features and dose plan indices. Machine learning was employed to identify the shape feature that predicted dose plan quality most effectively. The treatment outcome analysis including tumor growth control and serviceable hearing preservation at 2 years, were conducted using Cox regression analyses. All TSI features correlated significantly with the dose plan indices (P < 0.0012). With increasing tumor volume, vestibular schwannomas became more spherical (P < 0.05) and the dose plan indices varied significantly between tumor volume subgroups (P < 0.001 and P < 0.01). VioS was the most effective predictor of GK indices (P < 0.001) and we obtained 89.36% accuracy (79.17% sensitivity and 100% specificity) for predicting PCI. Our results indicated that TSI had significant effects on the plan quality however did not adversely affect treatment outcomes.
(© 2022. The Author(s).)
Databáze: MEDLINE
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