• Contusions bias cortical thickness estimates after traumatic brain injury. • Lesion-related bias affects cross-sectional and longitudinal measures. • Lesion masking can attenuate cross-sectional cortical thickness bias. • Lesion-aware preprocessing may improve TBI neuroimaging biomarkers. Traumatic brain injury (TBI) is characterized by both focal and diffuse pathology. Automated cortical thickness estimation is widely used to quantify structural brain changes following TBI; however, the impact of focal pathology such as contusions on cortical thickness estimates in TBI remains unknown. We evaluated lesion-induced bias in cortical thickness under three lesion-handling strategies in 86 TRACK-TBI participants with MRI at 2 weeks and 6 months post-injury. Cortical thickness was estimated using the ANTsNetCT longitudinal pipeline with the default pipeline (No Masking), masking lesion voxels from summarization (Atlas Masking), and masking lesion voxels from cortical thickness estimation (Full Masking). Cross-sectional and longitudinal cortical thickness in unilaterally lesioned regions were compared with their contralesional homologues using linear mixed-effects models. The effectiveness of each lesion handling strategy was then evaluated using nonparametric bootstrap analyses to test whether bias was systematically present across all regions. At 2 weeks post-injury, six cortical regions demonstrated significant lesion-associated bias. Collectively across all regions, bias was observed in the No Masking and Atlas-Masking approaches. This bias was significantly attenuated in the Fully Masked approach. Longitudinally, the unmasked data also showed significant lesion-related differences in cortical thickness change across multiple temporal and frontal regions, with persistent effects in the Atlas- and Full Masking approaches. Contusions appear to introduce cross-sectional and longitudinal bias in cortical thickness estimates, inflating cross-sectional values and potentially exaggerating atrophy longitudinally. Excluding lesion voxels from tissue probability maps attenuates cross-sectional bias, providing a baseline that improves accuracy and interpretation of neuroimaging biomarkers in TBI.
Brennan et al. (Fri,) studied this question.