Advances in biomathematical modeling for PET neuroreceptor imaging.

The quantitative application of PET neuroreceptor imaging to study pathophysiology, diagnostics and drug development has continued to benefit from associated advances in biomathematical imaging methodology. We review some of these advances with particular focus on multi-modal image processing, tracer kinetic modeling, occupancy studies and discovery and development of novel radioligands.:

[1]  Thomas Beyer,et al.  PET/CT scanners: a hardware approach to image fusion. , 2003, Seminars in nuclear medicine.

[2]  E. Hoffman,et al.  Tomographic measurement of local cerebral glucose metabolic rate in humans with (F‐18)2‐fluoro‐2‐deoxy‐D‐glucose: Validation of method , 1979, Annals of neurology.

[3]  Osama Mawlawi,et al.  Imaging Human Mesolimbic Dopamine Transmission with Positron Emission Tomography: I. Accuracy and Precision of D2 Receptor Parameter Measurements in Ventral Striatum , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[4]  R N Gunn,et al.  Toward an improved prediction of human in vivo brain penetration , 2008, Xenobiotica; the fate of foreign compounds in biological systems.

[5]  A. Sauter,et al.  Combined PET/MR Imaging — Technology and Applications , 2010, Technology in cancer research & treatment.

[6]  Nelleke Tolboom,et al.  Image-derived input functions for PET brain studies , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[7]  R. S. J. Frackowiak,et al.  Dose dependent occupancy of central dopamine D2 receptors by the novel neuroleptic CP-88,059-01: a study using positron emission tomography and11C-raclopride , 2005, Psychopharmacology.

[8]  David J. Schlyer,et al.  Graphical Analysis of Reversible Radioligand Binding from Time—Activity Measurements Applied to [N-11C-Methyl]-(−)-Cocaine PET Studies in Human Subjects , 1990, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[9]  R Gomeni,et al.  Adaptive‐Optimal Design in PET Occupancy Studies , 2010, Clinical pharmacology and therapeutics.

[10]  D W Townsend,et al.  Physical principles and technology of clinical PET imaging. , 2004, Annals of the Academy of Medicine, Singapore.

[11]  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.

[12]  Mark Slifstein,et al.  Translational characterization of [11C]GSK931145, a PET ligand for the glycine transporter type 1 , 2011, Synapse.

[13]  Mark Lubberink,et al.  Off-line motion correction methods for multi-frame PET data , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[14]  C S Patlak,et al.  Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data , 1983, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  Mark Slifstein,et al.  Relationships between radiotracer properties and image quality in molecular imaging of the brain with positron emission tomography. , 2003, Molecular imaging and biology : MIB : the official publication of the Academy of Molecular Imaging.

[16]  Mark Slifstein,et al.  Measuring Drug Occupancy in the Absence of a Reference Region: The Lassen Plot Re-Visited , 2010, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[17]  Yun Zhou,et al.  Using a reference tissue model with spatial constraint to quantify [11C]Pittsburgh compound B PET for early diagnosis of Alzheimer's disease , 2007, NeuroImage.

[18]  Michael Brady,et al.  A Biomathematical Modeling Approach to Central Nervous System Radioligand Discovery and Development , 2009, Journal of Nuclear Medicine.

[19]  Stefano Zamuner,et al.  Prediction of Repeat-Dose Occupancy from Single-Dose Data: Characterisation of the Relationship between Plasma Pharmacokinetics and Brain Target Occupancy , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[20]  Lewis B. Sheiner,et al.  Simultaneous vs. Sequential Analysis for Population PK/PD Data I: Best-Case Performance , 2003, Journal of Pharmacokinetics and Pharmacodynamics.

[21]  V J Cunningham,et al.  Compartmental Analysis of Diprenorphine Binding to Opiate Receptors in the Rat in vivo and its Comparison with Equilibrium Data in vitro , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[22]  Vincent J. Cunningham,et al.  Parametric Imaging of Ligand-Receptor Binding in PET Using a Simplified Reference Region Model , 1997, NeuroImage.

[23]  R. Myers,et al.  Long-term trans-synaptic glial responses in the human thalamus after peripheral nerve injury , 2001, Neuroreport.

[24]  MR-DTI and PET multimodal imaging of dopamine release within subdivisions of basal ganglia , 2011 .

[25]  Richard E Carson,et al.  Noise Reduction in the Simplified Reference Tissue Model for Neuroreceptor Functional Imaging , 2002, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[26]  M. Mintun,et al.  A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography , 1984, Annals of neurology.

[27]  G. Sedvall,et al.  Quantitative analysis of D2 dopamine receptor binding in the living human brain by PET. , 1986, Science.

[28]  Xiao Jin,et al.  Accuracy of head motion compensation for the HRRT: Comparison of methods , 2009, 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC).

[29]  Arno Klein,et al.  Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration , 2009, NeuroImage.

[30]  Roger N Gunn,et al.  Parametrically defined cerebral blood vessels as non-invasive blood input functions for brain PET studies. , 2004, Physics in medicine and biology.

[31]  Daniel Rueckert,et al.  Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation , 2010, NeuroImage.

[32]  Jonathan M. Links,et al.  Imaging dopamine receptors in the human brain by positron tomography , 1983 .

[33]  M. Laruelle,et al.  11C-GSK189254: A Selective Radioligand for In Vivo Central Nervous System Imaging of Histamine H3 Receptors by PET , 2009, Journal of Nuclear Medicine.

[34]  Roger Fulton,et al.  The design and implementation of a motion correction scheme for neurological PET. , 2003, Physics in medicine and biology.

[35]  Mark Jenkinson,et al.  Imaging dopamine receptors in humans with [11C]-(+)-PHNO: Dissection of D3 signal and anatomy , 2011, NeuroImage.

[36]  Jeih-San Liow,et al.  Image-Derived Input Function for Human Brain Using High Resolution PET Imaging with [11C](R)-rolipram and [11C]PBR28 , 2011, PloS one.

[37]  Alexander Hammers,et al.  Three‐dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe , 2003, Human brain mapping.

[38]  J. S. Duncan,et al.  Benzodiazepine Receptor Quantification in vivo in Humans Using [11C]Flumazenil and PET: Application of the Steady-State Principle , 1995, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[39]  Robert B. Innis,et al.  Strategies to Improve Neuroreceptor Parameter Estimation by Linear Regression Analysis , 2002, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[40]  F E Turkheimer,et al.  [11C](R)-PK11195 positron emission tomography imaging of activated microglia in vivo in Rasmussen’s encephalitis , 1999, Neurology.

[41]  Alan A. Wilson,et al.  Evaluation of 11C-GSK189254 as a Novel Radioligand for the H3 Receptor in Humans Using PET , 2010, Journal of Nuclear Medicine.

[42]  J R Chretien,et al.  Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. , 1998, Journal of drug targeting.

[43]  Ciprian Catana,et al.  MRI-Assisted PET Motion Correction for Neurologic Studies in an Integrated MR-PET Scanner , 2011, The Journal of Nuclear Medicine.

[44]  Jae Kyeong Jeong,et al.  Modeling of Brain D2 Receptor Occupancy‐Plasma Concentration Relationships with a Novel Antipsychotic, YKP1358, Using Serial PET Scans in Healthy Volunteers , 2007, Clinical pharmacology and therapeutics.

[45]  M. Laruelle.  Imaging Synaptic Neurotransmission with in Vivo Binding Competition Techniques: A Critical Review , 2000, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[46]  Kewei Chen,et al.  Image-Derived Input Function for Brain PET Studies: Many Challenges and Few Opportunities , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[47]  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.

[48]  S. Kety,et al.  THE NITROUS OXIDE METHOD FOR THE QUANTITATIVE DETERMINATION OF CEREBRAL BLOOD FLOW IN MAN: THEORY, PROCEDURE AND NORMAL VALUES. , 1948, The Journal of clinical investigation.

[49]  D L Hill,et al.  Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. , 1997, Medical physics.

[50]  S. Haber,et al.  Imaging Human Mesolimbic Dopamine Transmission with Positron Emission Tomography. Part II: Amphetamine-Induced Dopamine Release in the Functional Subdivisions of the Striatum , 2003, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[51]  Julian C. Matthews,et al.  Kinetic analysis of neuroreceptor binding using PET , 2004 .

[52]  Stephen M. Smith,et al.  A Bayesian model of shape and appearance for subcortical brain segmentation , 2011, NeuroImage.

[53]  Hartmut Derendorf,et al.  Modeling of Pharmacokinetic/Pharmacodynamic (PK/PD) Relationships: Concepts and Perspectives , 1999, Pharmaceutical Research.

[54]  T. Jones,et al.  Spectral Analysis of Dynamic PET Studies , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[55]  Lars H. Pinborg,et al.  [123I]Epidepride binding to cerebellar dopamine D2/D3 receptors is displaceable: Implications for the use of cerebellum as a reference region , 2007, NeuroImage.

[56]  Roger N Gunn,et al.  Positron Emission Tomography Compartmental Models: A Basis Pursuit Strategy for Kinetic Modeling , 2002, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

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