Corpus callosum diffusion tensor imaging and volume measures are associated with disease severity in pediatric Niemann-Pick disease type C1.

BACKGROUND

Niemann-Pick disease type C1 is a neurodegenerative lysosomal storage disorder. Without a highly effective treatment, biomarkers of severity would be beneficial for prognostication and testing new interventions. Diffusion tensor imaging has shown microstructural abnormalities in adults with Niemann-Pick disease type C1. This is the first study to apply diffusion tensor imaging and volume analysis to evaluate the corpus callosum in a pediatric and adolescent population of patients with Niemann-Pick disease type C1. We hypothesized that the callosal fractional anisotropy, volume, and cross-sectional area will negatively correlate with NPC severity score.

METHODS

Thirty-nine individuals with Niemann-Pick disease type C1 aged 1-21.9 years (mean = 11.1; S.D. = 6.1), and each received one magnetic resonance imaging examination. Severity score were obtained by examination and clinical observation. An atlas-based automated approach was used to measure fractional anisotropy, cross-sectional area, and volume. For comparative analysis and validation of this atlas-based approach, one midsagittal image was chosen and the corpus callosum manually traced to obtain cross-sectional area. Statistical analyses were applied to study the relationships between imaging and clinical severity.

RESULTS

For patients with Niemann-Pick disease type C1, lower corpus callosum fractional anisotropy, volume, and cross-sectional area significantly correlate with higher severity score. Severity subdomain analysis revealed ambulation, speech, seizures, and incontinence have the strongest relationships with callosal measures. Comparison of atlas-based processing and manual tracing techniques demonstrated validity for the automated method.

CONCLUSIONS

For individuals with Niemann-Pick disease type C1, the corpus callosum measures correlate with clinical severity. These findings reveal promise for the discovery of new imaging biomarkers for this disorder.