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

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, high-resolution 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

Trajectories of Cognitive Symptoms in Sick-Listed Cancer Survivors

Many non-central nervous system (CNS) cancer survivors experience cognitive symptoms, which may affect their self-perceived work ability. Little is known about trajectories of self-perceived cognitive functioning in cancer survivors in the period after work disability assessment. Therefore, we evaluated: (1) trajectories of self-reported cognitive functioning, in cancer survivors with work capacity, (2) differences in trajectories of self-reported cognitive functioning between three work disability groups, and (3) explanatory factors of trajectories of self-reported cognitive functioning. Participants (n = 206) were assessed on self-reported cognitive functioning at three time points between two and four years after first day of sick leave. A statistically significant improvement in cognitive functioning was found in the total group (β = 4.62, SE = 0.91, p < 0.001). When comparing cancer survivors in different work disability groups, similar trajectories of cognitive functioning were observed. Fatigue was the only factor found to be associated with the reported trajectory (β = -0.23, SE = 0.086, p = 0.08). Self-perceived cognitive functioning scores remained considerably lower than the mean score of the general Dutch population, indicating that cognitive symptoms are a persistent problem in sick-listed cancer survivors and that evidence-based treatment options are warranted