Association of Brain and Ventricular Boundary Shift Integral Measurements with CSF Biomarkers: A Case-Control Study.

AIMS: This study seeks to examine the relationship between cerebrospinal fluid (CSF) biomarkers (Aβ1-42, Phospho-Tau181p, Total-Tau) and brain volumetric changes measured by Brain Shift Integral (BSI) in Alzheimer's disease (AD) spectrum. We explore the potential of BSI as a complementary, non-invasive tool for early diagnosis and progression monitoring of AD.

BACKGROUND

AD is a neurodegenerative disorder marked by amyloid plaques and tau tangles, leading to cognitive decline. CSF biomarkers are key indicators of AD pathology, but their integration with imaging metrics like BSI could enhance early diagnosis. BSI quantifies brain volume changes via MRI, offering valuable insights into neurodegeneration across the AD spectrum.

OBJECTIVES

The current study explores the use of BSI and CSF biomarkers for the early detection of Alzheimer's disease.

METHODS

This study utilized data from the ADNI database, including CSF biomarkers (Aβ1-42, t-tau, ptau181) and BSI measurements from baseline and month 24 visits. Spearman correlations were performed to assess associations between biomarkers and brain volumetric changes. Linear regression models were used to examine the predictive value of biomarkers on BSI, controlling for potential confounders.

RESULTS

A total of 239 participants were included in the study, comprising 94 cognitively normal (CN) individuals, 104 with mild cognitive impairment (MCI), and 41 with AD. Significant negative correlations were observed between Aβ1-42 and both BBSI and VBSI in MCI at baseline (p=0.013) and 24 months (p=0.018), as well as between Aβ1-42 and VBSI in CN at baseline (p=0.039) and 24 months (p=0.033). In MCI, p-tau181 was positively correlated with BBSI (p=0.013) and VBSI (p=0.030) at baseline and with BBSI at 24 months (p=0.013). Linear regression analysis confirmed that Aβ1-42 and p-tau181 significantly predicted BSI measures in MCI (R2=0.141-0.173, p<0.05), while Aβ1-42 was a significant predictor of VBSI in CN (R2=0.156-0.166, p<0.01). No significant associations were found in AD.

DISCUSSION: This study underscores the role of CSF biomarkers-particularly Aβ1-42 and p-tau181-in detecting early brain atrophy across the Alzheimer's disease spectrum, with limited utility in advanced stages. The findings highlight the importance of early intervention and support the integration of CSF biomarkers and BSI as diagnostic tools for monitoring disease progression and staging.

CONCLUSION

The application of the BSI is pivotal for monitoring brain volume alterations and their association with CSF biomarkers.