Changes in cortical thickness and volume after cranial radiation treatment: A systematic review

Mesri

Bodiut

et al. 2019

Preprint

Self Cite

Background and purpose: Radiation-induced changes in brain tissue may relate to post-radiotherapy (RT) cognitive decline. Our aim is to investigate changes of the brain microstructural properties after exposure to radiation during clinical protocols of RT using diffusion MRI (dMRI). Methods and Materials: The susceptibility of tissue changes to radiation was investigated in a clinically heterogenic cohort (age, pathology, tumor location, type of surgery) consisting of 121 scans of 18 patients (10 females). The imaging dataset included 18 planning CTs and 103 dMRI scans (range 2-14, median = 6 per patient) assessing pre-operative, post-operative pre-RT and post-RT states. Diffusion tensor imaging (DTI) metrics were estimated from all scans for a region-of-interest based linear relation analysis between mean dose and change in DTI metrics, while partial volume effects were regressed out. Results: The largest regional dose dependency with mean diffusivity appear in the white matter of the frontal pole in the left hemisphere by an increase of 2.61 %/(Gy x year). Full brain-wise, pooled results for white matter show fractional anisotropy to decrease by 0.85 %/(30Gy x year); mean diffusivity increase by 9.17 %/(30Gy x year); axial diffusivity increase by 7.30%/(30Gy x year) and radial diffusivity increases by 10.63%/(30Gy x year). Conclusions: White matter is susceptible to radiation with some regional variability where diffusivity metrics demonstrate the largest relative sensitivity. This suggests that dMRI is a promising tool in assessing microstructural changes after RT, which can help in understanding treatment-induced cognitive decline.

Section: Discussionmentioning

confidence: 99%

Dose-dependent degeneration of non-cancerous brain tissue in post-radiotherapy patients: A diffusion tensor imaging study

Mesri

Bodiut

et al. 2019

Preprint

Self Cite

“…All imaging data was processed with Statistical Parametric Mapping (SPM12, v7487) [20], Computational Anatomy Toolbox (CAT12.6 r1450) [21], and in-house algorithms developed in MATLAB (Mathworks, Natick, Massachusetts, USA). Image processing was done in concordance to our own previously published criteria [3], amended for the current research question. More detailed image processing methods can be found in our previous work [4].…”

Section: Image Processingmentioning

confidence: 99%

“…With the advent of high-resolution brain imaging, the interest in morphological changes after RT has increased. The cerebral cortex has been shown to be susceptible to radiation-induced thinning, especially in areas associated with cognitive functioning [3][4][5][6]. Thinning rates are found to be dose-dependent, meaning that a higher dose leads to a further diminished cortex.…”

Section: Introductionmentioning

confidence: 99%

Dose-dependent volume loss in subcortical deep grey matter structures after cranial radiotherapy

Nagtegaal

Clinical and Translational Radiation Oncology

Philippens

et al. 2021

Self Cite

“…With the advent of high-resolution brain imaging, the interest in morphological changes after RT has increased. The cerebral cortex has been shown to be susceptible to radiation-induced thinning, especially in areas associated with cognitive functioning [3][4][5][6]. Thinning rates are found to be dosedependent, meaning that a higher dose leads to a further diminished cortex.…”

Section: Introductionmentioning

confidence: 99%

Dose-dependent volume loss in subcortical deep grey matter structures after cranial radiotherapy

Nagtegaal

Philippens

et al. 2020

Preprint

Self Cite

Background and purpose The relation between radiotherapy (RT) dose to the brain and morphological changes in healthy tissue has seen recent increased interest. There already is evidence for changes in the cerebral cortex and white matter, as well as selected subcortical grey matter (GM) structures. We studied this relation in all deep GM structures, to help understand the aetiology of post-RT neurocognitive symptoms. Materials and methods We selected 31 patients treated with RT for glioma. Pre-RT and post-RT 3D T1 MRIs were automatically segmented, and the changes in volume of the following structures were assessed: amygdala, nucleus accumbens, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus. The volumetric changes were related to the mean RT dose received by each structure. Hippocampal volumes were entered into a population-based nomogram to estimate hippocampal age. Results A significant relation between RT dose and volume loss was seen in all examined structures, except the caudate nucleus. The volume loss rates ranged from 0.16-1.37 %/Gy, corresponding to 4.9-41.2% per 30 Gy. Hippocampal age, as derived from the nomogram, was seen to increase by a median of 11 years. Conclusion Almost all subcortical GM structures are susceptible to radiation-induced volume loss, with more volume loss being observed with increasing dose. Volume loss of these structures is associated with neurological deterioration, including cognitive decline, in neurodegenerative diseases. To support a causal relationship between radiation-induced deep GM loss and neurocognitive functioning in glioma patients, future studies are needed that directly correlate volumetrics to clinical outcomes.