Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling.
J Mol Neurosci
; 73(7-8): 587-597, 2023 Aug.
Article
en En
| MEDLINE
| ID: mdl-37462853
ABSTRACT
The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Sustancia Blanca
/
Glioma
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Mol Neurosci
Asunto de la revista:
BIOLOGIA MOLECULAR
/
NEUROLOGIA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Irán