RESUMO
Positron emission tomography (PET) has become an essential clinical tool for diagnosing neurodegenerative diseases with abnormal accumulation of proteins like amyloid-ß or tau. Despite many attempts, it has not been possible to develop an appropriate radioligand for imaging aggregated α-synuclein in the brain for diagnosing, e.g., Parkinson's Disease. Access to a large animal model with α-synuclein pathology would critically enable a more translationally appropriate evaluation of novel radioligands. We here establish a pig model with cerebral injections of α-synuclein preformed fibrils or brain homogenate from postmortem human brain tissue from individuals with Alzheimer's disease (AD) or dementia with Lewy body (DLB) into the pig's brain, using minimally invasive surgery and validated against saline injections. In the absence of a suitable α-synuclein radioligand, we validated the model with the unselective amyloid-ß tracer [11C]PIB, which has a high affinity for ß-sheet structures in aggregates. Gadolinium-enhanced MRI confirmed that the blood-brain barrier was intact. A few hours post-injection, pigs were PET scanned with [11C]PIB. Quantification was done with Logan invasive graphical analysis and simplified reference tissue model 2 using the occipital cortex as a reference region. After the scan, we retrieved the brains to confirm successful injection using autoradiography and immunohistochemistry. We found four times higher [11C]PIB uptake in AD-homogenate-injected regions and two times higher uptake in regions injected with α-synuclein-preformed-fibrils compared to saline. The [11C]PIB uptake was the same in non-injected (occipital cortex, cerebellum) and injected (DLB-homogenate, saline) regions. With its large brain and ability to undergo repeated PET scans as well as neurosurgical procedures, the pig provides a robust, cost-effective, and good translational model for assessment of novel radioligands including, but not limited to, proteinopathies.
RESUMO
Clinical positron emission tomography (PET) research is costly and entails exposing participants to radioactivity. Researchers should therefore aim to include just the number of subjects needed to fulfill the purpose of the study. In this tutorial we show how to apply sequential Bayes Factor testing in order to stop the recruitment of subjects in a clinical PET study as soon as enough data have been collected to make a conclusion. By using simulations, we demonstrate that it is possible to stop a study early, while keeping the number of erroneous conclusions low. We then apply sequential Bayes Factor testing to a real PET data set and show that it is possible to obtain support in favor of an effect while simultaneously reducing the sample size with 30%. Using this procedure allows researchers to reduce expense and radioactivity exposure for a range of effect sizes relevant for PET research.