Measuring decline in white matter integrity after systemic treatment for breast cancer: omitting skeletonization enhances sensitivity

Abstract

Chemotherapy for non-central nervous system cancers is associated with abnormalities in brain structure and function. Diffusion tensor imaging (DTI) allows for studying in vivo microstructural changes in brain white matter. Tract-based spatial statistics (TBSS) is a widely used processing pipeline in which DTI data are typically normalized to a generic DTI template and then 'skeletonized' to compensate for misregistration effects. However, this approach greatly reduces the overall white matter volume that is subjected to statistical analysis, leading to information loss. Here, we present a re-analysis of longitudinal data previously analyzed with standard TBSS (Menning et al., BIB 2018, 324-334). For our current approach, we constructed a pipeline with an optimized registration method in Advanced Normalization Tools (ANTs) where DTI data are registered to a study-specific, highresolution T1 template and the skeletonization step is omitted. In a head to head comparison, we show that with our novel approach breast cancer survivors who had received chemotherapy plus or minus endocrine therapy (BC + SYST, n = 26) showed a global decline in overall FA that was not present in breast cancer survivors who did not receive systemic therapy (BC-SYST, n = 23) or women without a cancer diagnosis (no cancer controls, NC, n = 30). With the standard TBSS approach we did not find any group differences. Moreover, voxel-based analysis for our novel pipeline showed a widespread decline in FA in the BC + SYST compared to the NC group. Interestingly, the BC-SYST group also showed a decline in FA compared to the NC group, although in much less voxels. These results were not found with the standard TBSS approach. We demonstrate that a modified processing pipeline makes DTI data more sensitive to detecting changes in white matter integrity in non-CNS cancer patients after treatment, particularly chemotherapy.

Potential Molecular Biomarkers of Central Nervous System Damage in Breast Cancer Survivors

“…Previously, it was assumed that adjuvant chemotherapy exerts a direct toxic effect on oligodendrocytes and CNS progenitor cells that cause brain damage, and therefore the term “Chemical Brain” or “Chemobrain” was created [ 19 ]. However, later changes in the integrity of the white matter were also found after other treatment regimens including radiotherapy, chemotherapy and, therefore, the term was changed to “cancer-related cognitive impairment” [ 20 , 21 ]. Several theories exist to try to explain the mechanisms of the treatment-related brain damage, but the etiology of the CNS damages is most likely multifactorial.…”

Brain morphological alterations and their correlation to tumor differentiation and duration in patients with lung cancer after platinum chemotherapy

“…In addition, some studies have explored the biological mechanism of the cognitive effects of chemotherapy drugs in small animals ( 9 , 10 ). Neuroimaging plays an important role in neuropathology mechanistic research ( 11 , 12 ), and with the development of magnetic resonance imaging (MRI) techniques, the detection of related morphological changes has become more convenient and contributed to understand some of chemotherapy-related cognitive impairment (CRCI) ( 13 – 15 ). An increasing number of neuroimaging studies have shown that the pathological cognitive symptoms of patients are particularly related to the altered structure of gray matter (GM) and abnormal brain volume, although the relationship between brain aging in patients with CRCI and biomarkers of neuroimaging is still only the tip of the iceberg ( 16 ).…”

Fatigue and resting-state functional brain networks in breast cancer patients treated with chemotherapy

“…Several studies have described neurotoxicity associated with chemotherapy agents. Neuroimaging studies have characterized diffuse structural changes in the brain following chemotherapy, such as significant white matter integrity changes and widespread abnormalities in gray matter volume [11][12][13][14][15][16]. Task-based functional MRI (fMRI) has demonstrated functional abnormalities in brain areas associated with cognitive function [17,18].…”