NeuroExplorer: Ultra-high Performance Human Brain PET Imager for Highly-resolved In Vivo Imaging of Neurochemistry

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Research applications of brain Positron Emission Tomography (PET) have been in place for over 40 years. The combination of quantitative PET systems with novel radiotracers has led to a numerous imaging para- digms to understand normal brain physiology including neurotransmitter dynamics and receptor pharmacology at rest and during activation. Brain-dedicated PET systems offer important advantages over currently available PET systems in terms of sensitivity and resolution. However, the state-of-the-art for brain PET has not progressed beyond the 20-year-old HRRT. Therefore, there is a compelling need to build the next generation of brain PET systems for human studies. This proposal brings together a highly experienced collaborative team from Yale, UC Davis, and United Imaging Healthcare America (UIHA). to develop the next generation NeuroEXPLORER (NX) PET system with the following Aims. Specific Aim 1: Design and Build the NeuroEXPLORER: In 2 years, we will complete the design and build the NX system. The design includes high performance LYSO-SiPM blocks with small detectors, 4-mm depth-of-interaction, 250 ps time-of-flight resolution, and axial length of ~50 cm, paired with CT for attenuation correction. This design will produce a factor of 10 greater effective sensitivity than the HRRT and practical resolution of 1.5-2 mm in the human brain. The system will include built-in real-time state-of-art motion tracking cameras and will be tested using novel phantom experiments to assess the full-range of operation to validate the dramatic improvement in small- region precision and accuracy. Specific Aim 2: Algorithm Development for Fully-Quantitative Brain PET. We will develop the novel algorithms for this system. Using EXPLORER experience. we will implement reconstruction algorithms to produce dynamic images with uniform ultra-high resolution in space and time, Extending Yale’s HRRT motion correction experience, we will develop camera-based motion detection and correction algorithms to deliver ultra-high resolution human brain images. Using the carotid artery shape and geometry, we will develop methods to accurately measure blood activity to be compared to human arterial data with the goal to permit kinetic modeling without arterial sampling. We will develop noise reduction methods with machine learning to reduce dose for studying health brains and to eliminate the need for the CT scan for attenuation correction. Specific Aim 3: Human Paradigm Demonstration. With human subjects, we will evaluate specific imaging paradigms to demonstrate the effectiveness of the NX system: 1) demonstration of the dramatic sensitivity increase (with a direct comparison to the HRRT) and its impact on detection of pharmacologic effects, 2) leveraging high sensitivity to reliably measure uptake in small nuclei; and 3) opening new frontiers of imaging neurotransmitter dynamics, including dopamine and opioid release. The ultimate goal is a fully functioning and characterized system that dramatically expands the scope of brain PET protocols and applications.