Deep learning based quantification of the accelerated brain aging rate in glioma patients after radiotherapy

Author:

Huisman Selena I.ORCID,van der Boog Arthur T.J.ORCID,Cialdella FiaORCID,Verhoeff Joost J.C.ORCID,David SzabolcsORCID

Abstract

AbstractBackground and purposeChanges of healthy appearing brain tissue after radiotherapy have been previously observed, however, they remain difficult to quantify. Due to these changes, patients undergoing radiotherapy may have a higher risk of cognitive decline, leading to a reduced quality of life. The experienced tissue atrophy is similar to the effects of normal aging in healthy individuals. We propose a new way to quantify tissue changes after cranial RT as accelerated brain aging using the BrainAGE framework.Materials and methodsBrainAGE was applied to longitudinal MRI scans of 32 glioma patients, who have undergone radiotherapy. Utilizing a pre-trained deep learning model, brain age is estimated for all patients’ pre-radiotherapy planning and follow-up MRI scans to get a quantification of the changes occurring in the brain over time. Saliency maps were extracted from the model to spatially identify which areas of the brain the deep learning model weighs highest for predicting age. The predicted ages from the deep learning model were used in a linear mixed effects model to quantity aging and aging rates for patients after radiotherapy.ResultsThe linear mixed effects model resulted in an accelerated aging rate of 2.78 years per year, a significant increase over a normal aging rate of 1 (p < 0.05, confidence interval (CI) = 2.54-3.02). Furthermore, the saliency maps showed numerous anatomically well-defined areas, e.g.: Heschl’s gyrus among others, determined by the model as important for brain age prediction.ConclusionWe found that patients undergoing radiotherapy are affected by significant radiation-induced accelerated aging, with several anatomically well-defined areas contributing to this aging. The estimated brain age could provide a method for quantifying quality of life post-radiotherapy.HighlightsUp to 3 times accelerated aging after radiotherapy. // Anatomically well-defined areas for brain age prediction. // Quantifying quality of life after radiotherapy.

Publisher

Cold Spring Harbor Laboratory

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