The goal of this project is to develop both hardware and software to demonstrate the ground breaking capabilities of a new single photon radionuclide (SPR) imaging technique with the potential for >1000 times gain in sensitivity and >100 times gain in volumetric spatial resolution compared to clinical SPECT imaging using parallel-hole collimators. We refer to our new imaging methodology as mechanical flux manipulation (MFM). MFM utilizes high resolution pixelated detectors, high bandwidth data acquisition electronics and a novel image reconstruction methodology utilizing detector flux information to achieve target performance goals of >50% detection efficiency for photons impinging an MFM detector and <2 mm reconstructed image resolution. MFM is a SPR tomographic imaging technique. The two main features that differentiate MFM from traditional SPECT are collimator-less detectors and the use of flux-probability distributions versus line of response (LOR) counts to reconstruct images. MFM rejects the notion that the direction of every detected photon must be known in order to accurately reconstruct images from a single photon radionuclide emitting object. Instead, MFM collects flux information on a crystal by crystal basis and records how the flux to each crystal is altered by moving a mechanical attenuator (MA) between the emission object and the detector. Using flux information, the incident direction of each detected photon is not required for image reconstruction. MFM is further differentiated from SPECT in that it uses fully 3D image reconstruction rather than stacks of 2D data. While MFM will support general single photon tomographic imaging protocols, the focus of this Phase I proposal is to demonstrate feasibility for human brain imaging. This project is consists of three specific aims. The first aim is to extend and validate the SimSET Monte Carlo simulation tool to simulate an MFM scanner including real-world effects. The main component of this extension is to be able to simulate continuous MA motion. An additional sub-aim is to fabricate a prototype MA assembly and fully functional pixelated detector panel to collect experimental data with which to validate the SimSET Monte Carlo software tools. The second aim of the project is to expand the MFM image reconstruction software to 3D and to incorporate all corrections to support quantitative imaging. Extending to fully 3D image reconstruction will require significantly more computing resources and optimization of the algorithms so that the code can run efficiently. One of the sub-aims is to implement the reconstruction software using GPU processors. The third aim is to use the validated Monte Carlo tools from specific aim 1 and the fully 3D image reconstruction code developed in aim 2 to optimize the design of a MFM imaging system for high resolution human brain imaging. After successful completion of this project, we will seek additional funding to build a prototype MFM system to support <2...