Evaluation of Tracer Kinetic Models for Analysis of [18F]FDDNP Studies

PurposeDifferent pharmacokinetic methods for [18F]FDDNP studies were evaluated using both simulations and clinical data.ProceduresMethods included two-tissue reversible plasma (2T4k), simplified reference tissue input (SRTM), and a modified 2T4k models. The latter included an additional compartment for metabolites (2T1M). For plasma input models, binding potential, BPND, was obtained both directly (=k3/k4) and indirectly (using volume of distribution ratios).ResultsFor clinical data, 2T1M was preferred over 2T4k according to Akaike criterion. Indirect BPND using 2T1M correlated better with SRTM then direct BPND. Fairly constant volume of distribution of metabolites was found across brain and across subjects, which was strongly related to bias in BPND obtained from SRTM as seen in simulations. Furthermore, in simulations, SRTM showed constant bias with best precision if metabolites entered brain.ConclusionsSRTM is the method of choice for quantitative analysis of [18F]FDDNP even if it is unclear whether labeled metabolites enter the brain.

[1]  Ronald Boellaard,et al.  Characteristics of a new fully programmable blood sampling device for monitoring blood radioactivity during PET , 2001, European Journal of Nuclear Medicine.

[2]  Roger N. Gunn,et al.  Tracer Kinetic Modeling of the 5-HT1AReceptor Ligand [carbonyl-11C]WAY-100635 for PET , 1998, NeuroImage.

[3]  Nelleke Tolboom,et al.  Multi-input spectral analysis for assessing cerebral uptake of labelled metabolites: Validation and application to [11C]PIB and [18F]FDDNP studies , 2007 .

[4]  Ronald Boellaard,et al.  Validation of a multiwell gamma-counter for measuring high-pressure liquid chromatography metabolite profiles. , 2004, Journal of nuclear medicine technology.

[5]  C. C. Watson,et al.  New, faster, image-based scatter correction for 3D PET , 1999, 1999 IEEE Nuclear Science Symposium. Conference Record. 1999 Nuclear Science Symposium and Medical Imaging Conference (Cat. No.99CH37019).

[6]  G Brix,et al.  Performance evaluation of a whole-body PET scanner using the NEMA protocol. National Electrical Manufacturers Association. , 1997, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[7]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease: Report of the NINCDS—ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease , 2011, Neurology.

[8]  P. Thompson,et al.  PET of brain amyloid and tau in mild cognitive impairment. , 2006, The New England journal of medicine.

[9]  R. Myers,et al.  Quantitation of Carbon‐11‐labeled raclopride in rat striatum using positron emission tomography , 1992, Synapse.

[10]  Michel Defrise,et al.  Exact and approximate rebinning algorithms for 3-D PET data , 1997, IEEE Transactions on Medical Imaging.

[11]  Ronald Boellaard,et al.  Optimization algorithms and weighting factors for analysis of dynamic PET studies , 2006, Physics in medicine and biology.

[12]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[13]  G. Small,et al.  Localization of neurofibrillary tangles and beta-amyloid plaques in the brains of living patients with Alzheimer disease. , 2002, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[14]  Sung-Cheng Huang,et al.  Visualizing pathology deposits in the living brain of patients with Alzheimer's disease. , 2006, Methods in enzymology.

[15]  Sung-Cheng Huang,et al.  Comparison of simplified methods for quantitative analysis of [18F]FDDNP PET data , 2007, 2007 IEEE Nuclear Science Symposium Conference Record.

[16]  N. Volkow,et al.  Distribution Volume Ratios without Blood Sampling from Graphical Analysis of PET Data , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[17]  Olaf B. Paulson,et al.  MR-based automatic delineation of volumes of interest in human brain PET images using probability maps , 2005, NeuroImage.

[18]  J. Morris,et al.  Current concepts in mild cognitive impairment. , 2001, Archives of neurology.

[19]  A. Lammertsma,et al.  Simplified Reference Tissue Model for PET Receptor Studies , 1996, NeuroImage.

[20]  S. Gunn,et al.  Positron Emission Tomography Compartmental Models , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[21]  Nelleke Tolboom,et al.  Peripheral metabolism of [(18)F]FDDNP and cerebral uptake of its labelled metabolites. , 2008, Nuclear medicine and biology.

[22]  M. Bobinski,et al.  Frequency of Stages of Alzheimer-Related Lesions in Different Age Categories , 1997, Neurobiology of Aging.

[23]  Gerald Q. Maguire,et al.  Comparison and evaluation of retrospective intermodality brain image registration techniques. , 1997, Journal of computer assisted tomography.

[24]  V. Kepe,et al.  Exploring a Mathematical Model for the Kinetics of β-Amyloid Molecular Imaging Probes through a Critical Analysis of Plaque Pathology , 2006, Molecular Imaging and Biology.

[25]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease , 1984, Neurology.

[26]  D J Brooks,et al.  Comparison of Methods for Analysis of Clinical [11C]Raclopride Studies , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[27]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[28]  A. Windhorst,et al.  Synthesis of 2-(1,1-dicyanopropen-2-yl)-6-(2-[18F]-fluoroethyl)-methylamino-naphthalene ([18F]FDDNP). , 2008, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.