We characterize a compact MR-compatible PET insert for simultaneous preclinical PET/MRI. Although specifically designed with the strict size constraint to fit inside the 114-mm inner diameter of the BGA-12S gradient coil used in the BioSpec 70/20 and 94/20 series of small-animal MRI systems, the insert can easily be installed in any appropriate MRI scanner or used as a stand-alone PET system. The insert consists of a ring of 16 detector-blocks each made from depth-of-interaction-capable dual-layer-offset arrays of cerium-doped lutetium-yttrium oxyorthosilicate crystals read out by silicon photomultiplier arrays. Scintillator crystal arrays are made from 22 × 10 and 21 × 9 crystals in the bottom and top layers, respectively, with respective layer thicknesses of 6 and 4 mm, arranged with a 1.27-mm pitch, resulting in a useable field of view 28 mm long and about 55 mm wide. Spatial resolution ranged from 1.17 to 1.86 mm full width at half maximum in the radial direction from a radial offset of 0-15 mm. With a 300- to 800-keV energy window, peak sensitivity was 2.2% and noise-equivalent count rate from a mouse-sized phantom at 3.7 MBq was 11.1 kcps and peaked at 20.8 kcps at 14.5 MBq. Phantom imaging showed that features as small as 0.7 mm could be resolved. F-FDG PET/MR images of mouse and rat brains showed no signs of intermodality interference and could excellently resolve substructures within the brain. Because of excellent spatial resolvability and lack of intermodality interference, this PET insert will serve as a useful tool for preclinical PET/MR.

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A full-ring PET insert consisting of 16 PET detector modules was designed and constructed to fit within the 114 mm diameter gradient bore of a Bruker 7 T MRI. The individual detector modules contain two silicon photomultiplier (SiPM) arrays, dual-layer offset LYSO crystal arrays, and high-definition multimedia interface (HDMI) cables for both signal and power transmission. Several different RF shielding configurations were assessed prior to construction of a fully assembled PET insert using a combination of carbon fibre and copper foil for RF shielding. MR-compatibility measurements included field mapping of the static magnetic field (B ) and the time-varying excitation field (B) as well as acquisitions with multiple pulse sequences: spin echo (SE), rapid imaging with refocused echoes (RARE), fast low angle shot (FLASH) gradient echo, and echo planar imaging (EPI). B field maps revealed a small degradation in the mean homogeneity (+0.1 ppm) when the PET insert was installed and operating. No significant change was observed in the B field maps or the image homogeneity of various MR images, with a 9% decrease in the signal-to-noise ratio (SNR) observed only in EPI images acquired with the PET insert installed and operating. PET detector flood histograms, photopeak amplitudes, and energy resolutions were unchanged in individual PET detector modules when acquired during MRI operation. There was a small baseline shift on the PET detector signals due to the switching amplifiers used to power MRI gradient pulses. This baseline shift was observable when measured with an oscilloscope and varied as a function of the gradient duty cycle, but had no noticeable effect on the performance of the PET detector modules. Compact front-end electronics and effective RF shielding led to minimal cross-interference between the PET and MRI systems. Both PET detector and MRI performance was excellent, whether operating as a standalone system or a hybrid PET/MRI.

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Positron emission tomography (PET) is a non-invasive imaging technique which utilizes positronemitting radiopharmaceuticals (PERs) to characterize biological processes in tissues of interest. A PET scanner is usually composed of multiple scintillation crystal detectors placed in a ring so as to capture coincident photons from a position annihilation. These detectors require a crystal lookup table (CLUT) to map the detector response to the crystal of interaction. These CLUTs must be accurate, lest events get mapped to the wrong crystal of interaction degrading the final image quality. This work describes an automated algorithm, for CLUT generation, focused around Gaussian Mixture Models (GMM) with Thin Plate Splines (TPS). The algorithm was tested with flood image data collected from 16 detectors. The method maintained at least 99.8% accuracy across all tests. This method is considerably faster than manual techniques and can be adapted to different detector configurations.iii Acknowledgements