Abstract
The Siemens Biograph Vision 600 is the latest generation of PET/CT from Siemens Healthineers and the first to use silicon photomultipliers as the light-sensing mechanism in the detector. The PET detector consists of four 5 × 5 arrays of 3.2 × 3.2 LSO crystals completely covered by a 1.6 cm × 1.6 cm array of 16 SiPMs. Of these detectors, 128 are incorporated into a module. Of the modules, 19 are used to form an 82-cm-diameter detector ring. The axial dimension of the ring is 26.3 cm. Spatial resolution reconstructed by filtered back projection is 3.7 mm both transaxially and axially. The system sensitivity is 16 cps/kBq. The time resolution is 214 picoseconds. The time resolution in conjunction with the 26.3 cm axial length increases the effective sensitivity by a factor of 3.9 over the previous generation PET/CT. Improving the effective sensitivity has the potential to enable more sophisticated clinical applications. Along with conventional static imaging, the system includes dynamic imaging such as myocardial blood flow and a parametric application allowing whole-body Patlak imaging.
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References
Melcher CL, Schweitzer JS. Cerium-doped lutetium oxyorthosilicate: a fast, efficient new scintillator. IEEE Trans Nucl Sci. 1992;NS-39(4):502–5.
Cho S, Mintzer R. Silicon-photomultiplier TOF-PET Detector IEEE NSS-MIC, Atlanta M-07-1.
Vandenberghe S, et al. Fast reconstruction of 3D time-of-flight PET data by axial rebinning and transverse mashing. Phys Med Biol. 2006;51:1603–21.
Panin VY, Defrise M, Casey ME. Restoration of fine azimuthal sampling of measured TOF projection data. In: 2010 IEEE nuclear science symposium conference record (NSS/MIC). IEEE; 2010.
Panin VY, Aykac M, Hong I. TOF data compression on high time resolution clinical scanner. In: 2018 IEEE nuclear science symposium, Sydney.
Comtat C, et al. OS-EM-3-D reconstruction strategies for the ECAT HRRT. In: 2004 IEEE NSS MIC conf. rec., vol. 6. Rome; Oct. 2004. p. 3492–96.
Hudson HM, Larkin RS. Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging. 1994;13(4):601–9.
Panin VY, et al. Fully 3-D PET reconstruction with system matrix derived from point source measurements. IEEE Trans Med Imaging. 2006;25(7):907–21.
Rahmim A, Qi J, Sossi V. Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls. Med Phys. 2013;40(6):064301.
Defrise M, Casey ME, Michel C, Conti M. Fourier rebinning of time-of-flight PET data. Phys Med Biol. 2005;50(12):2749–63.
Panin VY. Monotonic iterative algorithms for crystal efficiencies estimation from normalization data and single rates estimation from compressed random coincidence data. In: 2013 nuclear science symposium, Seoul.
Aykac M, Panin V, Bal H. Crystal-based deadtime correction for Siemens next generation SiPM based PET/CT scanner. In: 2017 IEEE nuclear science symposium, Atlanta.
Watson CC. New, faster, image-based scatter correction for 3-D PET. IEEE Trans Nucl Sci. 2000;47(1):1587–94.
Watson CC. Extension of single scatter simulation to scatter correction of time-of-flight PET. IEEE Trans Nucl Sci. 2007;54:1679–86.
Carney JP, Townsend DW, Rappoport V, Bendriem B. Method for transforming CT images for attenuation correction in PET/CT imaging. Med Phys. 2006;33(4):976–83.
Panin VY, Smith AM, Hu J, Kehren F, Casey ME. Continuous bed motion on clinical scanner: design, data correction, and reconstruction. Phys Med Biol. 2014;59:6153–74.
van Sluis J, de Jong J, Schaar J, Noordzij W, van Snick P, Derckx R, Borra R, Willemsen A, Boellaard R. Performance characteristics of the digital Biograph Vision PET/CT system. J Nucl Med. 2019;60:1031–6.
Reddin J, Scheuermann J, Bharkhada D, Smith A, Casey M, Conti M, Karp J. Performance evaluation of the SiPM based Siemens Biograph Vision PET/CT System. In: 2018 IEEE nuclear science symposium, Sydney.
Moses WW. Fundamental limits of spatial resolution in PET. Nucl Instrum Methods Phys Res A. 2011;648(Supplement 1):S236–40.
NEMA Standards Publication NU 2-2008. Performance measurements of small animal positron emission tomographs. Rosslyn: National Electrical Manufacturers Association; 2008.
NEMA Standards Publication NU 2-2018. Performance measurements of positron emission tomographs (PET). Rosslyn: National Electrical Manufacturers Association; 2018.
Strother SC, Casey ME, Hoffman EJ. Measuring PET scanner sensitivity: relating countrates to image signal-to-noise ratios using noise equivalent counts. IEEE Trans Nucl Sci. 1990;37(2):783–8.
Budinger TF. Time-of-flight positron emission tomography: status relative to conventional PET. J Nucl Med. 1983;24(1):73–8.
Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med. 2007;48(6):932–45.
Dahlbom M, et al. Methods for improving image quality in whole body PET scanning. IEEE Trans Nucl Sci. 1992;39(4):1079–83.
Dahlbom M, Reed J, Young J. Implementation of true continuous 2D/3D whole body PET scanning. In: IEEE nuclear science symposium conference record. Lyon; 2000.
Brasse D, et al. Continuous bed motion acquisition on a whole body combined PET/CT system. In: 2002 IEEE nuclear science symposium conference record; 2002.
Townsend DW, et al. Continuous bed motion acquisition for an LSO PET/CT scanner. In: IEEE nuclear science symposium. Rome; 2004.
Newport DF, et al. Continuous tomography bed motion data processing apparatus and method. Google Patents; 2005.
Burbar Z, et al. Continuous bed motion data processing for a resolution LSO PET/CT scanner. In: 2005 IEEE nuclear science symposium conference record; 2005.
Schatka I, et al. A randomized, double-blind, crossover comparison of novel continuous bed motion versus traditional bed position whole-body PET/CT imaging. Eur J Nucl Med Mol Imaging. 2016;43(4):711–7.
Rausch I, et al. Performance evaluation of the Biograph mCT Flow PET/CT system according to the NEMA NU2-2012 standard. EJNMMI Phy. 2015;2(1):26.
Osborne DR, et al. Quantitative and qualitative comparison of continuous bed motion and traditional step and shoot PET/CT. Am J Nucl Med Mol Imaging. 2015;5(1):56–64.
Saha GB. Basics of PET imaging : physics, chemistry, and regulations. 2nd ed. New York: Springer; 2010. xiv, 241 p.
Weissleder R, et al. Molecular imaging: principles and practice. Shelton: PMPH USA; 2010.
Acuff SN, Osborne D. Clinical workflow considerations for implementation of continuous-bed-motion PET/CT. J Nucl Med Technol. 2016;44(2):55–8.
van Elmpt W, et al. Optimal gating compared to 3D and 4D PET reconstruction for characterization of lung tumours. Eur J Nucl Med Mol Imaging. 2011;38(5):843–55.
Hong I, et al. The strategy of elastic motion corrections. In: IEEE nuclear science symposium conference record; 2013.
van der Vos CS, et al. Improving the spatial alignment in PET/CT using amplitude-based respiration-gated PET and respiration-triggered CT. J Nucl Med. 2015;56(12):1817–22.
Osborne DR, et al. 90Y liver radioembolization imaging using amplitude-based gated PET/CT. Clin Nucl Med. 2017;42(5):373–4.
Phelps ME, et al. Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-D-glucose: validation of method. Ann Neurol. 1979;6(5):371–88.
Morris ED, Endres CJ, Schmidt KC, Christian BT, Muzic RF Jr, Fisher RE, Kinetic Modeling in Positron Emission Tomography, in Emission Tomography: The Fundimentals of PET and SPECT. 2004;499–540.
Kinahan PE, Fletcher JW. Positron emission tomography-computed tomography standardized uptake values in clinical practice and assessing response to therapy. Semin Ultrasound CT MR. 2010;31(6):496–505.
Osborne DR, Acuff S. Whole-body dynamic imaging with continuous bed motion PET/CT. Nucl Med Commun. 2016;37(4):428.
Karakatsanis NA, Garibotto V, Rager O and Zaidi H, Continuous bed motion Vs. step-and-shoot acquisition on clinical whole-body dynamic and parametric PET imaging. In: 2015 IEEE nuclear science symposium and medical imaging conference (NSS/MIC). San Diego; CA, 2015, pp. 1–6.
Chen K, et al. Noninvasive quantification of the cerebral metabolic rate for glucose using positron emission tomography, 18F-fluoro-2-deoxyglucose, the Patlak method, and an image-derived input function. J Cereb Blood Flow Metab. 1998;18(7):716–23.
Zanotti-Fregonara P, et al. Image-derived input function for brain PET studies: many challenges and few opportunities. J Cereb Blood Flow Metab. 2011;31(10):1986–98.
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Casey, M.E., Osborne, D.R. (2020). Siemens Biograph Vision 600. In: Zhang, J., Knopp, M. (eds) Advances in PET. Springer, Cham. https://doi.org/10.1007/978-3-030-43040-5_6
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