Solid state detectors such as avalanche photodiodes (APDs) are increasingly being used in PET detectors. One of the disadvantages of APDs is the strong decrease of their gain factor with increasing ambient temperature. The light yield of most scintillation crystals also decreases when ambient temperature is increased. Both effects lead to considerable temperature dependence of the performance of APD-based PET scanners. In this paper, the authors propose a model for this dependence and the performance of the LabPET8 APD-based small animal PET scanner is evaluated at different temperatures.
The model proposes that the effect of increasing temperature on the energy histogram of an APD-based PET scanner is a compression of the histogram along the energy axis. The energy histogram of the LabPET system was acquired at 21 °C and 25 °C to verify the validity of this model. Using the proposed model, the effect of temperature on system sensitivity was simulated for different detector temperature coefficients and temperatures. Subsequently, the effect of short term and long term temperature changes on the peak sensitivity of the LabPET system was measured. The axial sensitivity profile was measured at 21 °C and 24 °C following the NEMA NU 4-2008 standard. System spatial resolution was also evaluated. Furthermore, scatter fraction, count losses and random coincidences were evaluated at different temperatures. Image quality was also investigated.
As predicted by the model, the photopeak energy at 25 °C is lower than at 21 °C with a shift of approximately 6% per °C. Simulations showed that this results in an approximately linear decrease of sensitivity when temperature is increased from 21 °C to 24 °C and energy thresholds are constant. Experimental evaluation of the peak sensitivity at different temperatures showed a strong linear correlation for short term (2.32 kcps/MBq/°C = 12%/°C, R = −0.95) and long term (1.92 kcps/MBq/°C = 10%/°C , R = −0.96) temperature changes. Count rate evaluation showed that although the total count rate is consistently higher at 21 °C than at 24 °C for different source activity concentrations, this is mainly due to an increase in scattered and random coincidences. The peak total count rate is 400 kcps at both temperatures but is reached at lower activity at 21 °C. The peak true count rate is 138 kcps (at 100 MBq) at 21 °C and 180 kcps (at 125 MBq) at 24 °C. The peak noise equivalent count rate is also lower at 21 °C (70 kcps at 70 MBq) than at 24 °C (100 kcps at 100 MBq). At realistic activity levels, the scatter fraction is lower at higher temperatures, but at the cost of a strong decrease in true count rate.
A model was proposed for the temperature dependence of APD-based PET scanners and evaluated using the LabPET small animal PET scanner. System sensitivity and count rate performance are strongly dependent on ambient temperature while system resolution is not. The authors’ results indicate that it is important to assure stable ambient temperature to obtain reproducible results in imaging studies with APD-based PET scanners.
This research was supported by the European Union FP7 project SUBLIMA. Roel Van Holen is supported by the Research Foundation - Flanders, Belgium (FWO). Christian Vanhove is supported by the GROUP-ID consortium of Ghent University. The authors would like to thank Nick Van Laeken of the Department of Radiopharmacy at Ghent University for the synthesis of 11C. The authors declare that they have no conflict of interest.
I. INTRODUCTION II. MATERIALS AND METHODS II.A. Hardware II.B. Energy spectrum II.B.1. Theory II.B.2. Acquisition II.C. Sensitivity II.C.1. Simulation II.C.2. Short term variations II.C.3. Long term variations II.C.4. NEMA axial sensitivity profile II.D. Spatial resolution II.E. Scatter fraction, count losses, and random coincidences II.E.1. Energy histogram composition II.E.2. Count rate variation at stable temperature II.E.3. Temperature variation at constant low count rate II.F. Image quality III. RESULTS III.A. Energy histogram III.B. Sensitivity III.B.1. Simulation III.B.2. Short term variations III.B.3. Long term variations III.B.4. NEMA axial sensitivity profile III.C. Spatial resolution III.D. Scatter fraction, count losses, and random coincidences III.D.1. Energy histogram composition III.D.2. Count rate variation at stable temperature III.D.3. Temperature variation at constant low count rate III.E. Image quality IV. DISCUSSION V. CONCLUSION
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