Reverse engineering the clearance rate of cerebrospinal fluid as a biomarker for early diagnosis of Alzheimer's Disease

There is an imperative need for early diagnosis of Alzheimer's Disease in our aging world today. Early intervention efforts from early diagnosis have shown to be successful in reducing mortality rates. Based on recent research findings that support the causal relationship between abnormally slow clearance of toxic brain protein and neurodegeneration, there is a great interest in better understanding the dynamics of cerebrospinal fluid (CSF) that serves to remove brain waste product. Currently, noninvasive in-vivo human methods are limited; therefore, most existing results originate from animal models. One promising new in-vivo approach consists of probing the kinetics of radioactive contrast material (radiotracer) using dynamic PET imaging. Such approach requires extensive image processing, typically based on the traditional compartmental modeling. We develop an alternative model based on computational fluid dynamics (CFD) that resolves spatial transport of the PET contrast agent. Both methods estimate turnover time, whose true value is unknown. This study provides a comparative analysis of these two modeling approaches using quantitative and qualitative investigation of patient characteristics: age, ventricle volume, body mass index (BMI), amyloid-β and tau accumulation, and Apolipoprotein E (APOE) genotype.