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The Crystal Clear Collaboration has developed a modular system for a small animal PET scanner (ClearPET). The modularity allows the assembly of scanners of different sizes and characteristics in order to satisfy the specific needs of the individual member institutions. The system performs depth of interaction detection by using a phoswich arrangement combining LSO and LuYAP scintillators which are coupled to Multichannel Photomultipliers (PMTs). For each PMT a free running 40 MHz ADC digitizes the signal and the complete scintillation pulse is sampled by an FPGA and sent with 20 MB/s to a PC for preprocessing. The pulse provides information about the gamma energy and the scintillator material which identifies the interaction layer. Furthermore, the exact pulse starting time is obtained from the sampled data. This is important as no hardware coincidence detection is implemented. All single events are recorded and coincidences are identified by software. The system in Jülich (ClearPET Neuro) is equipped with 10240 crystals on 80 PMTs. The paper will present an overview of the data acquisition system.
The ClearPET™ Neuro is the first full ring scanner within the Crystal Clear Collaboration (CCC). It consists of 80 detector modules allocated to 20 cassettes. LSO and LuYAP:Ce crystals in phoswich configuration in combination with position sensitive photomultiplier tubes are used to achieve high sensitivity and realize the acquisition of the depth of interaction (DOI) information. The complete system has been tested concerning the mechanical and electronical stability and interplay. Moreover, suitable corrections have been implemented into the reconstruction procedure to ensure high image quality. We present first results which show the successful operation of the ClearPET™ Neuro for artefact free and high resolution small animal imaging. Based on these results during the past few months the ClearPET™ Neuro System has been modified in order to optimize the performance.
The small animal PET scanners developed by the Crystal Clear Collaboration (ClearPETtrade) detect coincidences by analyzing timemarks which are attached to each event. The scanners are able to save complete single list mode data which allows analysis and modification of the timemarks after data acquisition. The timemarks are obtained from the digitally sampled detector pulses by calculating the baseline crossing of the rising edge of the pulse which is approximated as a straight line. But the limited sampling frequency causes a systematic error in the determination of the timemark. This error depends on the phase of the sampling clock at the time of the event. A statistical method that corrects these errors will be presented
Development of an optimized LSO/LuYAP phoswich detector head for the Lausanne ClearPET demonstrator
(2006)
This paper describes the LSO/LuYAP phoswich detector head developed for the ClearPET small animal PET scanner demonstrator that is under construction in Lausanne within the Crystal Clear Collaboration. The detector head consists of a dual layer of 8×8 LSO and LuYAP crystal arrays coupled to a multi-anode photomultiplier tube (Hamamatsu R7600-M64). Equalistion of the LSO/LuYAP light collection is obtained through partial attenuation of the LSO scintillation light using a thin aluminum deposit of 20-35 nm on LSO and appropriate temperature regulation of the phoswich head between 30°C to 60°C. At 511keV, typical FWHM energy resolutions of the pixels of a phoswich head amounts to (28±2)% for LSO and (25±2)% for LuYAP. The LSO versus LuYAP crystal identification efficiency is better than 98%. Six detector modules have been mounted on a rotating gantry. Axial and tangential spatial resolutions were measured up to 4 cm from the scanner axis and compared to Monte Carlo simulations using GATE. FWHM spatial resolution ranges from 1.3 mm on axis to 2.6 mm at 4 cm from the axis.
This work describes a procedure to yield attenuation maps from MR images which are used for the absorption correction (AC) of brain PET data. Such an approach could be mandatory for future combined PET and MRI scanners, which probably do not include a transmission facility. T1-weighted MR images were segmented into brain tissue, bone, soft tissue, and sinus; attenuation coefficients corresponding to elemental composition and density as well as to 511 keV photon energy were respectively assigned. Attenuation maps containing up to four compartments were created and forward projected into sinograms with attenuation factors which then were used for AC during reconstruction of FDG-PET data. The commonly used AC based on a radioactive (68Ge) transmission scan served as reference. The reconstructed radioactivity values obtained with the MRI-based AC were about 20% lower than those obtained with PET-based AC if the skull was not taken into account. Considering the skull the difference was still about 10%. Our investigations demonstrate the feasibility of a MRI-based AC, but revealed also the necessity of a satisfying delineation of bone thickness which tends to be underestimated in our first approach of T1-weighted MR image segmentation.