Temperature dependence of the LabPET small-animal PET scanner

INTRODUCTION In quantitative PET imaging it is important to correct for all image-degrading effects, for example detector efficiency variation. Detector efficiency variation depends on the stability of detector efficiency when operating conditions vary within normal limits. As the efficiency of APD-based light detection strongly depends on ambient temperature, temperature-dependent detector efficiency normalization may be needed in APD-based PET scanners. We have investigated the temperature dependence of the LabPET APD-based small-animal PET scanner. MATERIALS AND METHODS First a simulation study was performed to evaluate the effect of different APD temperature coefficients on the temperature dependence of scanner sensitivity. Five experiments were also performed. First the immediate effect of temperature changes on scanner sensitivity was evaluated. Second, the effect of temperature changes that have stabilized for a few hours was investigated. In a third experiment the axial sensitivity profile was acquired at 21 degrees C and 24 degrees C. Next, two acquisitions of the NEMA image quality phantom (at 21 degrees C and 23 degrees C) were performed and absolute quantification was done based on normalization scans acquired at the correct and incorrect temperature. Finally, the feasibility of maintaining a constant room temperature and the stability of the scanner sensitivity under constant room temperature was evaluated. RESULTS Simulations showed that the relation between temperature-dependent APD gain changes and scanner sensitivity is quite complex. A temperature deviation leading to a 1 % change in APD gain corresponds to a much larger change in scanner sensitivity due to the shape of the energy histogram. In the first and second experiment a strong correlation between temperature and scanner sensitivity was observed. Changes of 2.24 kcps/MBq and 1.64 kcps/MBq per degrees C were seen for immediate and stabilized temperature changes respectively. The NEMA axial sensitivity profile also showed a decrease in sensitivity at higher temperature. The quantification experiment showed that a larger quantification error (up to 13%) results when a normalization scan acquired at the incorrect temperature is used. In the last experiment, temperature variability was 0.19 degrees C and counts varied by 10.2 Mcts (1.33%). CONCLUSION The sensitivity of the LabPET small-animal PET scanner strongly depends on room temperature. Therefore, room temperature should be kept as stable as possible and temperature-dependent detector efficiency normalization should be used. However, with constant room temperature excellent scanner stability is observed. Temperature should be kept constant within 0.5 degrees C and weekly normalization scans are recommended

Attenuation correction for TOF-PET with a limited number of stationary coincidence line-sources

INTRODUCTION Accurate attenuation correction remains a major issue in combined PET/MRI. We have previously presented a method to derive the attenuation map by performing a transmission scan using an annulus-shaped source placed close to the edge of the FOV of the scanner. With this method, simultaneous transmission and emission data acquisition is possible as transmission data can be extracted using Time-of-Flight (TOF) information. As this method is strongly influenced by photon scatter and dead time effects, its performance depends on the accuracy of the correction techniques for these effects. In this work we present a new approach in which the annulus source is replaced with a limited number of line-sources positioned at 35 cm from the center of the FOV. By including the location of the line sources into the algorithm, the extraction of true transmission data can be improved. The setup was validated with simulations studies and evaluated with a phantom study acquired on the LaBr3-based TOF-PET scanner installed at UPENN. MATERIALS AND METHODS First we performed GATE simulations using the digital NCAT phantom. The phantom was segmented into bone, lung and soft-tissue and injected with 6.5 Mbq/kg 18F-FDG. Simultaneous transmission/emission scans of 3 minutes were simulated using 6, 12 and 24 18F-FDG line sources with a total activity of 0.5 mCi. To obtain the attenuation map, the transmission data is first extracted using TOF information. To reduce misclassification of prompt emission data as transmission data, only events on LORs, which pass within a radial distance of 1 cm from at least one line source, are accepted. The attenuation map is then reconstructed using an iterative gradient descent approach. As a proof of concept, the method was evaluated on the LaBr3-based TOF PET scanner using an anthropomorphic torso phantom injected with 2mCi of 18F-FDG. 24 line-sources of 20μCi each were fixed to a wooden template at the back of the scanner. Simultaneous transmission/emission scans were acquired using 24 line sources. RESULTS Simulation results demonstrate that the fraction of scattered emission events classified as transmission data was reduced from 4.32% with the annulus source to 2.29%, 1.25% and 0.63% for the 24, 12 and 6 line sources respectively. The fraction of misclassified true emission events was reduced from 1.10% to 0.42%, 0.24% and 0.13% respectively. Only in case of 6 line sources, the attenuation maps showed severe artifacts. Compared to the classification solely based on TOF-information, preliminary experimental results indicate an improvement in the accuracy of the attenuation coefficients of 10.44%, 0.12% and 5.09% for soft-tissue, lung and bone tissue respectively. CONCLUSION The proposed method can be used for attenuation correction in sequential or simultaneous TOF-PET/MRI systems. The PET transmission and emission data are acquired simultaneously so no acquisition time for attenuation correction is lost in PET or MRI. Attenuation maps with higher accuracy can be obtained by including information about the location of the line-sources. However, at least 12 line sources are needed to avoid severe artifacts

Design of a realistic PET-CT-MRI phantom

The validation of the PET image quality of new PET-MRI systems should be done against the image quality of currently available PET-CT systems. This includes the validation of new attenuation correction methods. Such validation studies should preferentially be done using a phantom. There are currently no phantoms that have a realistic appearance on PET, CT and MRI. In this work we present the design and evaluation of such a phantom. The four most important tissue types for attenuation correction are air, lung, soft tissue and bone. An attenuation correction phantom should therefore contain these four tissue types. As it is difficult to mimic bone and lung on all three modalities using a synthetic material, we propose the use of biological material obtained from cadavers. For the lung section a lobe of a pig lung was used. It was excised and inflated using a ventilator. For the bone section the middle section of a bovine femur was used. Both parts were fixed inside a PMMA cylinder with radius 10 cm. The phantom was filled with 18F-FDG and two hot spheres and one cold sphere were added. First a PET scan was acquired on a PET-CT system. Subsequently, a transmission measurement and a CT acquisition were done on the same system. Afterwards, the phantom was moved to the MRI facility and a UTE-MRI was acquired. Average CT values and MRI R 2 values in bone and lung were calculated to evaluate the realistic appearance of the phantom on both modalities. The PET data was reconstructed with CT-based, transmission-based and MRI-based attenuation correction. The activity in the hot and cold spheres in the images reconstructed using transmission-based and MRI-based attenuation correction was compared to the reconstructed activity using CT-based attenuation correction. The average CT values in lung and bone were -630 HU and 1300 HU respectively. The average R 2 values were 0.7 ms -1 and 1.05 ms -1 respectively. These values are comparable to the values observed in clinical data sets. Transmission-based and MRI-based attenuation correction yielded an average difference with CT- based attenuation correction in the hot spots of -22 % and -8 %. In the cold spot the average differences were +3 % and -8 %. The construction of a PET-CT-MRI phantom was described. The phantom has a realistic appearance on all three modalities. It was used to evaluate two attenuation correction methods for PET-MRI scanners

Absolute quantification for small-animal PET

Quantification is important in preclinical PET studies. To achieve absolute quantification, an accurate reconstruction algorithm is necessary. Such an algorithm includes corrections for different effects such as geometric sensitivity of the scanner, detection efficiency, attenuation, scatter and random coincidences. In this work we present a method for performing absolute quantification on the LabPET system. All acquisitions were done on a GE Triumph system. This tri-modality system consists of a micro-PET (LabPET), micro-CT (X-O) and micro-SPECT (X-SPECT) scanner. Three PET scans were done. In the first scan 5 vials with different activity concentrations of F-18-FDG were scanned. The total activity inside the scanner was 80 MBq. The second scan was performed after 4 hours when the total activity in the scanner had decayed to 20 MBq. In the third scan 3 vials and 1 sphere were scanned with a total activity of 20 MBq. Before each PET scan a micro-CT scan was acquired. Point sources with a known activity were placed inside the field of view. The counts obtained in these point sources are used to obtain a correction factor for absolute sensitivity. Reconstruction was done using a 3D ML-EM reconstruction with micro-CT based attenuation correction. VOIs were drawn over the vials and the sphere in the reconstructed images. The total activity in the VOIs was calculated using the correction factor for absolute sensitivity. It was compared to the activity measured in a dose calibrator. The average quantification error was 56 %, 6.4 % and 0.6 % for the first, second and third scan. The high error in the first scan is explained by count rate effects, as 80 MBq can be considered a high activity level for this system. The feasibility of absolute quantification on the LabPET system was demonstrated. When the count rate is below 20 MBq absolute quantification is possible with an average quantification error smaller than 6.4 %

Determination of the resolution limit of a whole body PET scanner using monte carlo simulations

We studied the resolution limit that can be obtained for a whole body PET scanner. The results were obtained using a Monte Carlo based simulation program. The influence of two parameters was investigated: the crystal pixel size and the number of layers used for Depth-Of-Interaction (DOI) correction