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.

A distinctive abnormality of diffusion tensor imaging parameters in the fornix of patients with bipolar II disorder

Diffusion tensor imaging (DTI) studies have revealed a changed integrity in the white matter of bipolar disorder. However, only a few investigations have examined bipolar II disorder (BP-II). A cross-sectional study was conducted to compare thirty-eight patients with BP-II (mean age = 38.26 years, F/M = 19/19) with thirty-eight age- and gender-matched healthy controls (mean age = 34.45 years, F/M = 18/20). Tract Based Spatial Statistics (TBSS) analysis of the fractional anisotropy (FA) was done with age, gender and education years as covariates, then a complementary atlas-based region-of-interest (ROI) analysis including the axial diffusivity (AD) and radial diffusivity (RD) was conducted to obtain further information. The patients with BP-II showed a significant decrease in FA in the corpus callosum (commissure fibers), fornix (association fibers) and right anterior corona radiata (projection fibers) compared to the controls. Moreover, a significant increase in the RD was observed in all of the fibers of the BP-II patients, while the AD significantly increased only in the fornix of the patients. Thus, in addition to the abnormal integrity of the commissure and projection fibers, the present study suggested an involvement of the limbic association fibers in the pathophysiology of BP-II induced by a distinctive neuropathology.

Individual differences in left parietal white matter predict math scores on the Preliminary Scholastic Aptitude Test

Mathematical skills are of critical importance, both academically and in everyday life. Neuroimaging research has primarily focused on the relationship between mathematical skills and functional brain activity. Comparatively few studies have examined which white matter regions support mathematical abilities. The current study uses diffusion tensor imaging (DTI) to test whether individual differences in white matter predict performance on the math subtest of the Preliminary Scholastic Aptitude Test (PSAT). Grades 10 and 11 PSAT scores were obtained from 30 young adults (ages 17-18) with wide-ranging math achievement levels. Tract based spatial statistics was used to examine the correlation between PSAT math scores, fractional anisotropy (FA), radial diffusivity (RD) and axial diffusivity (AD). FA in left parietal white matter was positively correlated with math PSAT scores (specifically in the left superior longitudinal fasciculus, left superior corona radiata, and left corticospinal tract) after controlling for chronological age and same grade PSAT critical reading scores. Furthermore, RD, but not AD, was correlated with PSAT math scores in these white matter microstructures. The negative correlation with RD further suggests that participants with higher PSAT math scores have greater white matter integrity in this region. Individual differences in FA and RD may reflect variability in experience dependent plasticity over the course of learning and development. These results are the first to demonstrate that individual differences in white matter are associated with mathematical abilities on a nationally administered scholastic aptitude measure.