Development of high performance single photon emission computed tomography systems for simultaneous nuclear molecular imaging and magnetic resonance imaging

Abstract

Simultaneous nuclear molecular imaging (NMI) and magnetic resonance imaging (MRI) have great potential for pre-clinical and clinical applications, especially for cell imaging in brain cancer models. We have pursued an intensive research effort to develop high-performance single-photon emission computed tomography (SPECT) systems for simultaneous NMI/MRI. This kind of system has sub-mm and even higher resolving power that allows a matched resolution for SPECT and MRI to visualize details about cell retention and migration, and provides a significant improvement of system sensitivity, even comparable with the sensitivity of positron emission tomography (PET), enabling detection of a small number of cells. The first key step to develop a high-performance SPECT system was building the first generation MR- compatible SPECT, called MRC-SPECT-I, which was a stationary full-ring system, consisting of forty MR- compatible, energy-resolved, photon-counting, and highly-pixelated CdTe semiconductor detectors. Preliminary studies demonstrated the system ability to track as few as 400 neural stem cells in a mouse brain with a sub-500 µm resolution. Although the MRC-SPECT-I was a state-of-the-art SPECT system, to further improve SPECT performance for simultaneous NMI and MRI, an inverted compound-eye (ICE) gamma-ray camera was proposed here for SPECT imaging applications and experimentally verified through a prototype system. The MRC-SPECT-II was designed utilizing 24 ICE gamma camera modules and consisted of more than 1,500 micro-pinhole cameras. The simulation results verified that the MRC-SPECT-II system was more than ten times as sensitive as conventional SPECT systems were while retaining a sub-500 µm resolving capability. Combining the high sensitivity of the SPECT system and the high soft tissue contrast and temporal resolution of MRI, simultaneous SPECT/MRI provides an attractive platform for functional and cell imaging of a wide range of disease models, such as cancers and neurodegenerative diseases.