2009 IEEE Nuclear Science Symposium Conference Record M13-27 MR Compatible Brain PET Using Tileable GAPD Arrays Jin Ho Jung, Yong Choi, Member, IEEE, Key Jo Hong, Ji Hoon Kang, Wei Hu, Byung Jun Min, Yoon Suk Huh, Seung Han Shin, Hyun Keong Lim, Dae Shik Kim, and Han Byul Jin Abstract– The aim of this study is to develop a MR compatible PET that is insertable to MRI and allows simultaneous PET and MR imaging of human brain. The brain PET having 72 detector modules arranged in a ring of 330 mm diameter was designed. Each PET module composed of 4 × 4 matrix of 3 mm × 3 mm × 20 mm LYSO crystals coupled to a tileable 4 × 4 array Geigermode avalanche photodiode (GAPD) and designed to locate between RF and gradient coils. Signals of the each module were transferred to preamplifiers using flexible flat cable of 3 m long, and then sent to a position decoder circuit (PDC), which outputs digital address and an analog pulse of the one interacted channel from preamplifier signals. The PDC outputs were fed into FPGAembedded DAQ boards. The analog signal was digitized, and arrival time and energy of the signal were calculated and stored. All electronics were located outside MR bore to minimize signal interference between PET and MR. Basic performance of the PET components and cross-compatibilities of the PET module and MR were evaluated. Imaging performance of the designed brain PET was investigated using Monte Carlo simulation and experimental measurement. The degradation of PET performance caused by the 3 m long cable and the PDC was negligibly small. No obvious differences of the PET module performance measured inside/outside MR bore were observed. The SNR of various MR sequence phantom images acquired with/without the PET module were also similar. Activity distribution patterns of hot-rod phantoms were well imaged without distortion, and rods down to a diameter of 3.5 mm were resolved in both simulation and experiment. Gray and white matter of the Hoffman brain phantom was also well imaged. Preliminary experimental results demonstrate that MR compatible high quality PET imaging is feasible using the GAPD arrays, electronics, signal processing method and MR insertable PET design schemes developed in this study. development of combined PET/MR, which is a useful tool for both functional and anatomic imaging [1],[2]. The purposed of this study is to design and fabricate a MR compatible PET system that is insertable to MRI and allows simultaneous PET and MR imaging of human brain. The performance the designed PET was estimate using Monte Carlo simulation method. The cross-compatibility of the PET module based on Geiger-mode avalanche photodiode (GAPD) arrays and MRI was evaluated. The performance of prototype PET consisting of 72 PET modules and signal processing components was also evaluated. II. MATERIALS AND METHODS A. MR Compatible Brain PET Design and Fabrication 1) PET detector module PET detector module consisted of a LYSO (Sinoceramics, Shanghai, China) scintillator blocks coupled to a 4 × 4 array GAPDs (SensL, Cork, Ireland). The scintillator block composed of 4 × 4 matrix of 3 mm × 3 mm × 20 mm crystals. The individual crystal elements were mechanically polished on all sides and optically isolated with a 0.3 mm white epoxy resin. Each pixel of the GAPD array had a 2.85 mm × 2.85 mm sensitive area and a 3.3 mm pitch. The scintillator was directly coupled to the GAPD without optical-coupling material. Each PET detector module was encapsulated from light. I. INTRODUCTION is a useful imaging modality to provide functional Pinformation about a specific organ or body system. PET, ET however, provides relatively poor spatial resolution and also limited anatomic information. A combined PET/CT has been utilized to overcome the limitation of PET using anatomic information provided by CT. However, CT has low soft-tissue contrast and lead to additional radiation exposure compared with MRI. Recently, there has been great interest on the This study was supported by a grant of the Mid-Term Industrial Technology Development Program, the Ministry of Knowledge Economy (10024198), by a grant of the Industrial Source Technology Development Programs, the Ministry of Knowledge Economy (10030029), and by a grant of the Radiation Technology Development Program through the Korea Science and Engineering Foundation funded by the Ministry of Education, Science and Technology (2007-00321), Republic of Korea. The authors are with the Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135710, Korea (e-mail: ychoi@skku.edu). 9781-4244-3962-1/09/$25.00 ©2009 IEEE Fig. 1. 4 × 4 matrix LYSO crystals and a 4 × 4 array GAPD used to construct PET detector module. 2) Analog and digital signal processing The signals of the each module were fed into 16 channel preamplifiers using flexible flat cable of 3 m long, as shown in Fig. 2(b). Then, the preamplified signals were sent to a position decoder circuit (PDC), which readout channel address and analog pulse of the channel interacted with coincidence event among 64 preamplified signals transmitted from 4 detector modules. Fig. 3 illustrates configuration of position decoder circuit. The output signals from the PDC were fed into VHS-ADC Virtex-4 boards (Lyrtech, Quebec, Canada) with free-running 3556 analog to digital converters and field programmable gate array (FPGA). Algorithm to calculate arrival time and energy of the digitized signal was programmed in the FPGA. Processed signals were stored in a list mode format. Fig. 2. PET detector module and preamplifier connected using FFC of 300 cm long. Fig. 4. Brain PET system consisting of PET detector, analog and digital electronics. Fig. 3. Configuration of position decoder circuit. Fig. 5. Location of the PET detector and electronics inside MRI. 3) Brain PET system The brain PET system consisted of 72 detector modules arranged in a ring of 330 mm diameter, 72 preamplifiers, 18 PDCs and 3 DAQ boards, as shown in Fig. 4. PET detectors were located between RF and gradient coils. All electronics including preamplifiers were located outside MR bore to minimize the signal interference between MR and PET. Fig. 5 illustrates the location of the PET detector and electronics inside MRI. B. Performance Estimation of the Brain PET Using Monte Carlo Simulation The spatial resolution over the FOV was estimated by simulating the point source as a function of source location using Geant4 application for tomographic emission (GATE). Imaging performance of hot-rod phantom filled with 13 MBq F-18 radioactive source and 3D digital Hoffman brain phantom filled with 96 MBq were also estimated, as shown in Fig. 6. Fig. 6. Brain PET detector and 3D digital Hoffman brain phantom simulated to estimate the PET imaging performance. C. Basic Performance Evaluation of PET Components 1) Effect of cable length between detector module and preamplifier on PET performance Two PET detector modules were constructed and located at the opposite side each other and separated by 10 mm. A 0.2 MBq Na-22 point source was placed at the center between them. The signals of the PET detector modules were transferred to preamplifiers using a 10 cm or 300 cm FFC. Energy and timing spectra were measured. 2) Performance evaluation of PET with and without position decoder circuit Two PET detector modules were constructed and located at the opposite side each other and separated by 10 mm. A 0.2 MBq Na-22 point source was placed at the center between them. Energy and timing spectra were acquired with and without position decoder circuit. 3557 D. Cross-compatibility of the PET module and MR Two PET detector modules were located at the opposite side each other, and a 0.2 MBq Na-22 point source was placed at the center. Each PET module was encapsulated from light. Energy and timing resolutions of a pair of PET detectors were measured. Same experiments were performed with gradient echo (GE) or spin echo (SE) sequences running after inserting them into the bore of a 7T MRI (Bruker, Ettlingen, Germany). MR cylinder phantom (10 mm diameter, 50 mm length) was filled with CuSO4 and placed at the isocenter, as shown in Fig. 7. The phantom images were acquired with and without the PET module while running GE or SE sequences. phantom was well simulated. Fig. 10 shows tomographic images of hot-rod and Hoffman brain phantoms. Fig. 9. Spatial resolution as a function of source position. Fig. 10. Tomographic images of Hot-rod phantom (left) and software Hoffman brain phantom (right) acquired using GATE simulation. Fig. 7. MR phantom (CuSO4) used to evaluate the cross-compatibility of the PET module and MR. E. Performance Measurement of the Prototype PET The prototype brain PET consisting of 72 detector modules was constructed. Hot-rod and Hoffman brain phantoms were filled with 74 MBq and 55 MBq, respectively. Total coincidence counts of hot-rod and Hoffman brain phantoms acquired using developed electronics were 1.0 and 6.8 million, respectively. All phantom images were reconstructed using a 2D FBP. Normalization and random correction were performed to improve image quality. B. Basic Performance Evaluation of PET Components 1) Effect of cable length between detector module and preamplifier on PET performance Average energy resolutions were 20.1±4.1% and 20.8±3.1% by using 10 cm and 300 cm cable, respectively. The timing resolutions were 1.8 ns and 1.9 ns by using 10 cm and 300 cm cable, respectively. Fig. 11 illustrates energy and timing spectra acquired with a 10 cm and 300 cm FFC. Fig. 11. Energy (left) and timing (right) spectra acquired with a 10 cm (gray) and 300 cm (black) FFC. Fig. 8. The prototype brain PET consisting of 72 detector modules. Each detector module was independently encapsulated from light. III. RESULTS A. Performance Estimation of the Brain PET Using Monte Carlo Simulation Radial resolution of the brain PET was degraded from 3.3 mm to 6.1 mm, at a 100 mm off-center, as illustrated in Fig. 9. The rods down to a diameter of 3.5 mm were clearly resolved in hot-rod phantom image. Activity distribution pattern between white and gray matter in the software Hoffman brain 2) Performance evaluation of PET with and without position decoder circuit The difference of energy resolutions measured with and without the PDC was negligibly small. As shown in Table I, the timing resolutions were 2.4 ns and 1.9 ns in the detector modules with and without the PDC, respectively. 3558 Table I. Energy and timing resolution measured with PDC without PDC. C. Cross-compatibility of PET Module and MR As shown in Table II and III, no significant degradation of PET performance caused by MR was observed. Distortion of MR phantom image caused by PET detector module was not found. Table II. Energy and timing resolutions according to PET position and to applied MR sequences. timing resolution was decreased from 1.9 ns to 2.4 ns by using the PDC because length of signal transmission line according to the location of input channel on printed circuit board was different. Nevertheless, the measured timing resolution was comparable to that of commercial small animal PET (<2 ns) [8,9] and human PET (<6 ns) [10]. The GATE simulation results on the spatial resolutions across the FOV indicate that depth of interaction information needs to be considered to improve the degradation of spatial resolution at off-center of FOV. Currently, timing improvement and scatter correction are being implemented to improve the quality of the brain PET image. Additionally, mechanics and magnetic shielding to operate the prototype brain PET inside MR bore are being designed. REFERENCES [1] Table III. Effect of PET insert on MR phantom images. D. Performance Measurement of the Prototype PET Activity distribution patterns of hot-rod and Hoffman brain phantoms were successfully acquired, as illustrated in Fig. 12. The rods down to a diameter of 3.5 mm were resolved in hotrod phantom image. Activity distribution pattern between white and gray matter in Hoffman Brain phantom was well imaged. Fig. 12. Tomographic images of Hot-rod phantom (left) and 3D Hoffman brain phantom (right) acquired using the prototype PET. C. Catana, Y. Wu, M. S. Judenhofer, J. Qi, B. J. Pichler, and S. R. Cherry, “Simultaneous acquisition of multislice PET and MR images: Initial results with a MR-compatible PET scanner,” J. Nucl. Med., vol. 47, pp. 1968-1976, 2006. [2] R. Grazioso, N. Zhanga, J. Corbeil, M. Schmand, R. Ladebeck, M. Vester, et al., “APD-based PET detector for simultaneous PET/MR imaging,” Nucl. Instr. Meth., vol. A569, pp. 301-305, 2006. [3] W. Hu, Y. Choi, J. Jung, K. Hong, J. Kang, B. Min, et al., "A FPGAbased high speed multi-channel simultaneous signal acquisition method for positron emission tomography," IEEE NSS-MIC, M05-334, 2009. [4] W. Hu, Y. Choi, J. Jung, K. Hong, J. Kang, B. 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Choi, et al., “The ClearPETTM project: development of a 2nd generation high-performance small animal PET scanner,” Nucl. Instr. Meth., vol. A 537, pp. 307–311, 2005. [10] J.L. Humm, A. Rosenfeld, A. Del Guerra, “From PET detectors to PET scanners,” Eur. J. Nucl. Med. Mol. Imaging, vol. 30, pp. 1574–1597, 2003. IV. DISCUSSION AND CONCLUSION In this study, a MR insertable brain PET consisting of 72 detector modules based on GAPD array was designed and constructed. PET images were successfully acquired using the developed prototype PET. The results of this study demonstrated that the designed PET detector module has good MR compatibility. Minimal interference between PET and MRI was observed. The cross compatibility was improved by using the 300 cm FFC. The degradation of PET performance by the 300 cm cable was negligibly small. The coincidence 3559