Nuclear Medicine and Biology
Volume 34, Issue 5 , Pages 483-492 , July 2007

An input function estimation method for FDG-PET human brain studies

  • Hongbin Guo

      Affiliations

    • Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804, USA
    • Corresponding Author InformationCorresponding author. Tel.: +1 480 965 8002; fax: +1 480 965 4160.
  • ,
  • Rosemary A. Renaut

      Affiliations

    • Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804, USA
  • ,
  • Kewei Chen

      Affiliations

    • Banner Alzheimer's Institute, Phoenix, AZ 85006, USA
    • Banner Good Samaritan Positron Emission Tomography Center, Phoenix, AZ 85006, USA

Received 29 January 2007 ,Revised 2 March 2007 ,Accepted 15 March 2007.

References 

  1. PET Working Group. PET Working Group: NIH/NIA neuroimaging initiative. URL http://www.nia.nih.gov/ResearchInformation/ExtramuralPrograms/NeuroscienceOfAging/Summary+%E2%80%93+PET+Working+Group.htm2005;
  2. Phelps ME, Huang S-C, Hoffman EJ, Selin CE, Kuhl D. Tomographic measurement of local cerebral glucose metabolic rate in man with (18F) fluorodeoxyglucose: validation of method. Ann Neurol. 1979;6:371–388
  3. Bentourkia M. Kinetic modeling of PET-FDG in the brain without blood sampling. Comp Med Imaging Graph. 2006;30:447–451
  4. Eberl S, Anayat AR, Fulton RR, Hooper PK, Fulham MJ. Evaluation of two population-based input functions for quantitative neurological FDG PET studies. Eur J Nucl Med. 1997;24:299–304
  5. Tsuchida T, Sadato N, Yonekura Y, Nakamura S, Takahashi N, Sugimoto K, et al. Noninvasive measurement of cerebral metabolic rate of glucose using standardized input function. J Nucl Med. 1999;40(9):1441–1445
  6. Riabkov DY, Bella EVRD. Estimation of kinetic parameters without input functions: analysis of three methods for multichannel blind identification. IEEE Trans Biomed Eng. 2002;49(11):1318–1327
  7. Feng DG, Wong K-P, Wu C-M, Siu W-C. A technique for extracting physiological parameters and the required input function simultaneously from PET image measurements: theory and simulation study. IEEE Trans Inf Technol Biomed. 1997;1(4):243–254
  8. Wong K-P, Feng D, Meikle SR, Fulham MJ. Simultaneous estimation of physiological parameters and the input function — in vivo PET data. IEEE Trans Inf Technol Biomed. 2001;5(1):67–76
  9. Chen K, Bandy D, Reiman E, Huang SC, Lawson M, Feng D, et al. Noninvasive quantification of the cerebral metabolic rate for glucose using positron emission tomography, 18F-fluorodeoxyglucose, the Patlak method, and an image-derived input function. J Cereb Blood Flow Metab. 1998;18:716–723
  10. Litton J-E. Input function in PET brain-studies using MRI defined arteries. J Comput Assit Tomogr. 1997;21(6):907–909
  11. Wahl LM, Asselin MC, Nahmias C. Regions of interest in the venous sinuses as input functions for quantitative PET. J Nucl Med. 1999;40(10):1666–1675
  12. Asselin MC, Cunningham VJ, Amano S, Gunn R, Nahmias C. Parametrically defined cerebral blood vessels as non-invasive blood input functions for brain PET studies. Phys Med Biol. 2004;49(6):1033–1054
  13. Guo H, Renaut RA, Chen K, Reiman E. Clustering huge data sets for parametric PET imaging. Biosystems. 2003;71(1–2):81–92
  14. Raichle ME, Martin WR, Herscovitch P, Mintun MA, Markham J. Brain blood flow measured with intravenous H215O: II. Implementation and validation. J Nucl Med. 1983;24:790–798
  15. Guo H, Renaut R, Chen K. Evaluating an alternative model for the input function in FDG-PET studies. URL http://math.la.asu.edu/~rosie/mypapers/nmbsupp.pdf2007;
  16. Sokolo L, Reivich M, Kennedy C, Rosiers MHD, Patlack CS, Pettigrew KD, et al. The [14C]-deoxyglucose method for the measurement of local cerebral glucose metabolism: theory procedures and normal values in the conscious and anesthetized albino rat. J Neurochem. 1977;28:897–916
  17. Huang S-C, Phelps ME, Hoffman EJ, Sideris K, Selin CJ, Kuhl DE. Noninvasive determination of local cerebral metabolic rate of glucose in man. Am J Physiol. 1980;238(E):69–82
  18. Zhou Y, Endres CJ, Brasic JR, Huang S-C, Wong DF. Linear regression with spatial constraint to generate parametric images of ligand-receptor dynamic PET studies with a simplified reference tissue model. NeuroImage. 2003;18(4):975–989
  19. The Mathworks . Optimization Toolbox user's guide. 2005;
  20. Wienhard K, Pawlik G, Herholz K, Wagner R, Heiss, W-D. Estimation of local cerebral utilization by positron emission tomography of 18F-2-fluoro-2-deoxy-d-glucose: a critical appraisal of optimization procedures, J Cereb Blood Flow Metab.
  21. Chen K, Huang S-C, Yu D-C. The effects of measurement errors in the plasma radioactivity curve on parameter estimation in positron emission tomography. Phys Med Biol. 1991;36(9):1183–1200
  22. Liptrot M, Adams KH, Martiny L, Pinborg LH, Lonsdale MN, Olsen NV, et al. Cluster analysis in kinetic modelling of the brain: a noninvasive alternative to arterial sampling. Neuroimage. 2004;21(2):483–493
  23. Sanabria-Bohorquez SM, Maes A, Dupont P, Bormans G, de Groot T, Coimbra A, et al. Image-derived input function for [11C]flumazenil kinetic analysis in human brain. Mol Imaging Biol. 2003;5(2):72–78

 This study was supported by the Arizona Center for Alzheimer's Disease Research and funded by the Arizona Department of Health Services and the National Institutes of Health (Grant No. EB 2553301).

PII: S0969-8051(07)00086-8

doi: 10.1016/j.nucmedbio.2007.03.008

Nuclear Medicine and Biology
Volume 34, Issue 5 , Pages 483-492 , July 2007