Academic Radiology
Volume 15, Issue 11 , Pages 1376-1389 , November 2008

Automated 11C-PiB Standardized Uptake Value Ratio

  • Parnesh Raniga, BE

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia
    • Corresponding Author InformationAddress correspondence to: P.R.
    • ,
  • Pierrick Bourgeat, PhD

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • ,
  • Jurgen Fripp, BE

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • ,
  • Oscar Acosta, PhD

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • ,
  • Victor L. Villemagne, MD

      Affiliations

    • Department of Nuclear Medicine and Centre for PET, and Department of Medicine, University of Melbourne, Austin Hospital, Melbourne, VIC, Australia
    • The Mental Health Research Institute, University of Melbourne, Parkville, VIC, Australia
    • ,
  • Christopher Rowe, MD

      Affiliations

    • Department of Nuclear Medicine and Centre for PET, and Department of Medicine, University of Melbourne, Austin Hospital, Melbourne, VIC, Australia
    • ,
  • Colin L. Masters, MD

      Affiliations

    • The Mental Health Research Institute, University of Melbourne, Parkville, VIC, Australia
    • Centre for Neurosciences, University of Melbourne, Parkville, VIC, Australia
    • ,
  • Gareth Jones, BSc

      Affiliations

    • Department of Nuclear Medicine and Centre for PET, and Department of Medicine, University of Melbourne, Austin Hospital, Melbourne, VIC, Australia
    • ,
  • Graeme O'Keefe, PhD

      Affiliations

    • Department of Nuclear Medicine and Centre for PET, and Department of Medicine, University of Melbourne, Austin Hospital, Melbourne, VIC, Australia
    • ,
  • Olivier Salvado, PhD

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • ,
  • Sébastien Ourselin, PhD

      Affiliations

    • CSIRO Preventative Health National Research Flagshift ICTC, The Australian e-Health Research Centre-BioMedIA, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
    • Centre for Medical Image Computing, University College London, London, United Kingdom

Received 29 February 2008 ,Accepted 9 July 2008.

References 

  1. Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann Neurol. 2004;55:306–319
  2. Agdeppa ED, Kepe V, Liu J, et al. Binding characteristics of radiofluorinated 6-dialkylamino-2-naphthylethylidene derivatives as positron emission tomography imaging probes for beta-amyloid plaques in Alzheimer's disease. J Neurosci. 2001;21:1–5
  3. Verhoeff NP, Wilson AA, Takeshita S, et al. In-vivo imaging of Alzheimer disease beta-amyloid with [11C]SB-13 PET. Am J Geriat Psychiatry. 2004;12:584–595
  4. Rowe CC, Ackerman U, Browne W, et al. Imaging of amyloid β in Alzheimer's disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol. 2008;7:129–135
  5. Price JC, Klunk WE, Lopresti J, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. B. J Cereb Blood Flow Metab. 2005;25:1528–1547
  6. Jons PH, Ernst M, Hankerson J, et al. Follow-up of radial arterial catheterization for positron emission tomography studies. Hum Brain Mapp. 1997;5:119–123
  7. Logan J, Fowler JS, Volkow ND, et al. Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(-)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab. 1990;10:740–747
  8. Logan J, Fowler JS, Volkow ND, et al. Distribution volume ratios without blood sampling from graphical analysis of PET data. J Cereb Blood Flow Metab. 1996;16:834–840
  9. Lopresti BJ, Klunk WE, Mathis CA, et al. Simplified quantification of Pittsburgh compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med. 2005;46:1959–1972
  10. Joachim C, Morris J, Selkoe D. Diffuse senile plaques occur commonly in the cerebellum in Alzheimer's disease. Am J Pathol. 1989;135:309–319
  11. Rowe CC, Ng S, Ackermann U, et al. Imaging beta-amyloid burden in aging and dementia. Neurology. 2007;68:1718–1725
  12. Lockhart A, Lamb J, Osredkar T, et al. PIB is a non-specific imaging marker of amyloid-beta (Abeta) peptide-related cerebral amyloidosis. Brain. 2007;130:2607–2615
  13. Edison P, Archer HA, Hinz R, et al. Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study. Neurology. 2007;68:501–508
  14. Fagan AM, Mintun MA, Mach RH, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol. 2006;59:512–519
  15. Kemppainen NM, Aalto S, Wilson IA, et al. PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology. 2007;68:1603–1606
  16. Yasuno F, Hasnine AH, Suhara T, et al. Template-based method for multiple volumes of interest of human brain PET images. NeuroImage. 2002;16:577–586
  17. Mykkänen J, Tohka J, Luoma J, et al. Automatic extraction of brain surface and mid-sagittal plane from PET images applying deformable models. Comput Methods Programs Biomed. 2005;79:1–17
  18. Tohka J. Surface extraction from volumetric images using deformable meshes: a comparative study. In: 2002;p. 350–364In: European Conference on Computer Vision–ECCV 2002. Copenhagen, Denmark May 28–31, 2002.
  19. Chen JL, Gunn SR, Nixon MS, et al. Markov random field models for segmentation of PET images. In: 2001;p. 468–474In: Information processing in Medical Imaging, 17th International Conference, IPMI. Davis, CA, June 18–22, 2001.
  20. Wong DP, Feng D, Meikle SR, et al. Segmentation of dynamic PET images using cluster analysis. IEEE Trans Nucl Sci. 2002;49:200–207
  21. Brankov JG, Galatsanos NP, Yang Y, et al. Segmentation of dynamic PET or fMRI images based on a similarity metric. IEEE Trans Nucl Sci. 2003;50:1410–1414
  22. Koivistoinen H, Tohka J, Ruotsalainen U. Comparison of pattern classification methods in segmentation of dynamic PET brain images. 6th Nordic Signal Processing Symposium, IEEE. 2004;73–76
  23. Browne J, de Pierro A. A row-action alternative to the EM algorithm for maximizing likelihood in emission tomography. IEEE Trans Med Imaging. 1996;15:687–699
  24. Folstein MF, Folstein SE, McHugh PR. Mini-mental state (A practical method for grading the cognitive state of patients for the clinician). J Psychiatr Res. 1975;12:189–198
  25. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43:2412–2414
  26. Raniga P, Bourgeat P, Villemagne V, et al. Spline based inhomogeneity correction for [11]C-PIB PET segmentation using expectation maximization. In:  Ayache N,  Ourselin S,  Maeder A editor. Medical image computing and computer-assisted intervention—MICCAI 2007 LNCS. 4791:Berlin, Germany: Springer; 2007;p. 228–235
  27. Aston JAD, Cunningham VJ, Asselin MC, et al. Positron emission tomography partial volume correction: estimation and algorithms. J Cereb Blood Flow Metab. 2002;22:1019–1034
  28. Lamare F, Turzo A, Bizais Y, et al. Validation of a Monte Carlo simulation of the Philips Allegro/GEMINI PET systems using GATE. Phys Med Biol. 2006;51:943–962
  29. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc. 1977;39:1–38
  30. Mazziotta J, Toga A, Evans A, et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos Trans R Soc Lond B Biol Sci. 2001;356:1293–1322
  31. Ourselin S, Roche A, Subsol G, et al. Reconstructing a 3D structure from serial histological sections. Image Vision Computing. 2001;19:25–31
  32. Kang Y, Engelke K, Kalender WA. Interactive 3D editing tools for image segmentation. Med Image Anal. 2004;8:35–46
  33. Ibanez L, Schroeder W, Ng L, et al. The ITK Software Guide, Kitware, Inc.. http://www.itk.org/ItkSoftwareGuide.pdf2nd ed, 2005. Accessed December 15, 2007.
  34. Van Leemput K, Maes F, Vandermeulen D, et al. Automated model-based tissue classification of MR images of the brain. IEEE Trans Med Imaging. 1999;18:897–908
  35. Dice L. Measures of the amount of ecologic association between species. Ecology. 1945;26:297–302
  36. Kim J, Cai W, Feng D, et al. Segmentation of VOI from multidimensional dynamic PET images by integrating spatial and temporal features. IEEE Trans Info Technol Biomed. 2006;10:637–646
  37. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage. 2002;15:273–289
  38. Development Core Team, R:a language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria). http://www.R-project.orgAccessed January 4, 2008.
  39. Metz CE, Herman BA, Roe CA. Statistical comparison of two ROC-curve estimates obtained from partially-paired datasets. Med Decis Making. 1998;18:110–121
  40. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed.. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988;
  41. Rosnow RL, Rosenthal R. Computing contrasts, effect sizes, and counternulls on other people's published data: general procedures for research consumers. Psychol Meth. 1996;1:331–340

1 This research was funded by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Preventative Health Flagship (http://www.csiro.au/csiro/channel/pchcp.html).

PII: S1076-6332(08)00398-X

doi: 10.1016/j.acra.2008.07.006

Academic Radiology
Volume 15, Issue 11 , Pages 1376-1389 , November 2008

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