ANALYSIS OF PET STUDIES Turku PET Centre 2001-05-07 V Oikonen PET Raw Data (sinogram) Results Parametric Sinogram PET Image Parametric Image Regional TACs.

Slides:



Advertisements
Similar presentations
CHAPTER II UNDERSTANDING BIOCHEMICAL SYSTEM FOR PATHWAYS RECONSTRUCTION Hiren Karathia (Ph.D- System Biology and Bioinformatics) Supervisor: Dr. Rui Alves.
Advertisements

Variability of PET-PIB retention measurements due to different scanner performance in multi-site trials Jean-Claude Rwigema Chet Mathis Charles Laymon.
Fund BioImag : Two compartment modeling 1.What is compartmental modeling ? 2.How can tracer kinetics be mathematically described ? 3.How do 2-deoxyglucose.
Drug ? RESPONSE altering their biochemical &/or biophysical activity  Depress  Activate  Replace  Irritate  Destroy PHARMACODYNAMICS  Absorb 
PLASMA INPUT AND METABOLITE FRACTION MODELS TPCMOD0009 Models for plasma metabolite correction TPCMOD0010.
ANALYSIS OF PET STUDIES PET Basics Course 2006 Turku PET Centre Vesa Oikonen
Quantification of [ 11 C]FLB 457 binding in the human brain with PET before and after PVE correction Judit Sóvágó Karolinska Institutet Department of Clinical.
Applications of wavelets in PET modelling - a literature survey.
PET basics II How to get numbers? Modeling for PET Turku PET Centre
MODELLING AND PARAMETER ESTIMATION IN PET Vesa Oikonen Turku PET Centre
Concepts for discussion 1.synopses – don’t overdo it 2.how comfortable were you with Wagner paper, Mintun, Farde? 3.non-specific vs specific binding 4.how.
Q: What is this dog thinking about?. He’s thinking about two things: 1. Saturable processes. 2. Solving the FDG model.
Brain… The Final Frontier…. Lets go on a “Fantastic Voyage” Blood Flow Metabolism Permeability Receptor Binding Gene Expression Neurotransmission Transmitter.
What are some of the issues in choosing bolus vs bolus+infusion? Which one predicts equilibrium coefficients? Which one achieves equilibrium? Which one.
BASIC MODELS IN DIAGNOSTICS
Analysis of PET studies Calculation of parametric images Turku PET Centre Vesa Oikonen.
VISUALIZING ALL THE FITS: Evaluating The Quality And Precision Of Parametric Images Created From Direct Reconstruction Of PET Sinogram Data Evan D. Morris.
Two-compartment model
One-compartment open model: Intravenous bolus administration
Measurement of liver blood flow using [ 15 O]H 2 O and PET Literature review 7 th Modelling Workshop in Turku PET Centre, 20 th October 2005 Turku PET.
Laplace transformation
Week 4 - Biopharmaceutics and Pharmacokinetics
Pharmacokinetics Based on the hypothesis that the action of a drug requires presence of a certain concentration in the fluid bathing the target tissue.
Modeling Systems and Processes Anthony McGoron, PhD Associate Professor Department of Biomedical Engineering Florida International University.
Coincidence to Image: PET Imaging Jennifer White Marketing Manager SNS Workshop October 13, 2003.
H. Koivunoro1, E. Hippelänen1, I. Auterinen2, L. Kankaanranta3, M
Pharmacology Department
Nuclear Medicine Quality control.
The General Concepts of Pharmacokinetics and Pharmacodynamics Hartmut Derendorf, PhD University of Florida.
EuroMedIm Irène Buvat - May Quantification in emission tomography: challenges, solutions, performance and impact Irène Buvat U678 INSERM,
Receptor Occupancy estimation by using Bayesian varying coefficient model Young researcher day 21 September 2007 Astrid Jullion Philippe Lambert François.
Enzyme Kinetics and Inhibition
PET Module Ana Beatriz Solana, MS Qu Tian (Teresa), MS Instructor: Dr. Charles Laymon.
Touqeer Ahmed Ph.D. Atta-ur-Rahman School of Applied Bioscience, National University of Sciences and Technology 21 st October, 2013.
RESPONSE altering their biochemical &/or biophysical activity  Depress  Activate  Replace  Irritate  Destroy PHARMACODYNAMICS  Absorb  Distribute.
Enzyme Inhibition C483 Spring Questions 1. An inhibitor binds to a site other than the active site of the enzyme. Which statement below correlates.
The General Concepts of Pharmacokinetics and Pharmacodynamics
Continuous intravenous infusion (one-compartment model)
Pharmacology Department
MYOCARDIAL BLOOD FLOW WITH [ 15 O]H 2 O PET: ERROR ESTIMATES Turku PET Centre Vesa Oikonen TPC.
A.B.Madhan Kumar Mentor: Dr. Charles M. Laymon Department of Radiology
Linearized models in PET Vesa Oikonen Turku PET Centre – Modelling workshop Modelling workshop
CHAPTER 5: MEMBRANES.
Turku PET Centre EXTRACTING ARTERIAL BLOOD CURVE FROM PET IMAGE - UPDATE Abdominal aorta in [ 15 O]H 2 O studies.
Comparison of methodologies for the assessment of dopamine receptor binding in subregions of the striatum Functional Neuroimaging Lab School of Psychology.
GENERATION OF PARAMETRIC IMAGES PROSPECTS PROBLEMS Vesa Oikonen Turku PET Centre
The General Concepts of Pharmacokinetics and Pharmacodynamics
Receptor Theory & Toxicant-Receptor Interactions Richard B. Mailman.
Objectives Compartment Modeling of Drugs Models describing drug concentration-time profiles Multi-compartment Models.
Basics of Perfusion Imaging With Dynamic Contrast MRI Larry Panych, PhD Brigham and Women’s Hospital.
Diffusion of Carbon Dioxide from the Peripheral Tissue Cells into the Capillaries and from the Pulmonary Capillaries into the Alveoli.
Pharmacokienetic Principles (2): Distribution of Drugs
Physiology for Engineers
Pharmacology Phone Number: (203)
Volume 132, Issue 2, Pages (February 2007)
Volume 139, Issue 3, Pages e6 (September 2010)
Isotope production Nuclear reactions t1/2 18F (p,n) 110 min
D.6: Transport of respiratory gases
Conventional Reconstruction Followed by Kinetic Modelling
OK. What if we don’t care about the kinetics of a particular tracee molecule (e.g., glucose). Rather, we care about counting up the number of one type.
Pharmaceutics 2.
Pharmacokinetics: Drug Distribution and Drug Reservoirs
Pharmacokinetics: Drug Distribution and Drug Reservoirs
Specific Recognition of Macroscopic Objects by the Cell Surface: Evidence for a Receptor Density Threshold Revealed by Micrometric Particle Binding Characteristics 
Model Part – Yiming Weng
Volume 132, Issue 2, Pages (February 2007)
Biopharmaceutics Chapter-6
αβ T Cell Receptor Ligand-Specific Oligomerization Revisited
αβ T Cell Receptor Ligand-Specific Oligomerization Revisited
Presentation transcript:

ANALYSIS OF PET STUDIES Turku PET Centre V Oikonen PET Raw Data (sinogram) Results Parametric Sinogram PET Image Parametric Image Regional TACs + Blood Data Reconstruction Model CalculationsReconstruction Model Calculations Drawing Regions Drawing Regions SPM

BLOOD DATA Venous Bolus Infusion Arterial Time-Activity Curve (TAC) tt Mixing in Plasma Volume Exchange with Interstitial Volume Exchange with intracellular Volume Time Delay

BLOOD vs PLASMA Tracer Persists in Red Blood Cells (RBC) [ 15 O]O 2 [ 15 O]CO Blood Plasma c t Note that the metabolite of [ 15 O]O 2 is [ 15 O]H 2 O, which is in equilibrium between plasma and RBC C Blood = HCR*C RBC

BLOOD vs PLASMA Tracer Persists in Plasma [ 11 C]Palmitate [ 18 F]FTHA [Carbonyl- 11 C]WAY Blood Plasma c t C Blood = (1-HCR)*C Plasma Note that one of the labeled metabolites of palmitate is [ 11 C]CO 2, which penetrates RBC membrane

BLOOD vs PLASMA Tracer Penetrates RBC Membrane Instantly [ 15 O]H 2 O [ 11 C]FETNIM [ 18 F]CFT [ 11 C]HED [ 11 C]FLB-457 [ 11 C]MP4A Blood Plasma c t C Blood = HCR*C RBC + (1-HCR)*C Plasma Note that the concentration may be different in RBC and in plasma. Note that a labeled metabolite may not penetrate RBC membrane.

BLOOD vs PLASMA Tracer Penetrates RBC Membrane Slowly [ 18 F]FDOPA [ 11 C]Methionine [ 18 F]FDG Blood Plasma c t Note that the concentration may be different in RBC and in plasma. Note that a labeled metabolite may not penetrate RBC membrane. C Blood = HCR*C RBC + (1-HCR)*C Plasma

METABOLITES IN PLASMA

PET DATA ”input””output” Authentic tracer concentration available in arterial blood Concentration in tissue measured by PET scanner Perfusion Endothelial permeability Vascular volume fraction Transport across cell membranes Specific binding to receptors Non-specific binding Enzyme activity

MODEL CALCULATIONS ”black box” BLOOD or PLASMA TAC TISSUE TAC -sinogram or -image or -regional RESULTS (model parameters) MODEL

MODEL CALCULATIONS ”Garbage In-garbage Out” Paradigm PERFECT MODEL GARBAGE MODEL GARBAGE DATA PERFECT DATA GARBAGE RESULTS GARBAGE RESULTS

COMPARTMENTAL MODEL C P = concentration of tracer in plasma C F = free tracer in brain C B = receptor bound tracer C NS = non-specifically bound tracer K 1 -k 6 = rate constants; the fraction of tracer that is leaving compartment in time unit

DISTRIBUTION VOLUME Constant Infusion of Tracer after equilibrium is achieved Bolus Infusion of Tracer

DISTRIBUTION VOLUME Receptor Model Binding Potential: B’ max = density (concentration) of free receptors K d = dissociation rate constant

RECEPTOR DENSITY and affinity to the ligand

DISTRIBUTION VOLUME Distribution Volume Ratio DV in reference region: Reference region = (brain) region which has no receptors, i.e. region with no specific binding, i.e. region where k 3 =0 and B max =0, and thus BP=0 Distribution Volume Ratio:

LOGAN ANALYSIS Plasma Input Distribution volume = Slope of the Logan plot Distribution volume Ratio = Ratio of slopes of the ROI and reference region Logan J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol 2000;27:

LOGAN ANALYSIS Reference Region Input Distribution volume Ratio = Slope of the Logan plot calculated using reference region input Logan J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol 2000;27: BP = DVR - 1

LOGAN ANALYSIS Summary For reversible binding Linearity of the plot must be checked Plasma/Reference region input Result: DV or DVR Easily applied to image or sinogram data

SIMPLIFIED REFERENCE TISSUE MODEL Only for tracers with simple kinetics No plasma samples nor metabolite analysis Result: BP and R 1 Easily applied to image data with RPM Could be applied to sinogram data Lammertsma AA, Hume SP. Simplified reference tissue model for PET receptor studies. NeuroImage 1996;4:

RATIO METHOD BP = (ROI - REF) / REF Region-of-interest (ROI) to reference region ratio correlates with density of available receptors

GJEDDE-PATLAK ANALYSIS ”Irreversible” uptake ARTERIAL PLASMA IRREVERSIBLE COMPARTMENT(S)

GJEDDE-PATLAK ANALYSIS Graphical Analysis Plot is linear after the tracer concentration in plasma and in reversible compartments are in equilibrium Slope of the linear phase of plot is the uptake (influx) rate constant K i Unit of K i is min -1, or (mL tissue/mL plasma)min -1 Patlak CS, Blasberg RG. Graphical evaluation of blood-to- brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab 1985;5: Logan J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol 2000;27:

GJEDDE-PATLAK ANALYSIS Metabolic Rate of Glucose Glucose Glucose- 6- Phosphate Glucose K1K1 k3k3 k2k2 k4k4 [ 18 F]FDG [ 18 F]FDG - 6- Phosphate [ 18 F]FDG K* 1 k* 3 k* 2 k* 4 Lumped constant (LC) corrects for the different affinities of transporters and hexokinase to glucose and FDG Influx rate constant: Unit of MR glu :

GJEDDE-PATLAK ANALYSIS Summary For irreversible uptake Linearity of the plot must be checked Plasma/Reference region input Result: K i (influx rate constant) Easily applied to image or sinogram data

RETENTION INDEX ”one-sample Patlak plot” Requirements for data: -one late-time PET frame (static image), C T -TAC of authentic tracer from beginning, C P

PERFUSION Kety-Schmidt: change in tissue concentration is equal to the difference between arterial and venous concentrations (C A and C V ) multiplied by blood flow, f For [ 15 O]H 2 O:

PERFUSION Autoradiography Procedure: 1.Bolus [ 15 O]H 2 O infusion 2.Arterial blood sampling 3.Static Imaging (90 or 250 s) 4.Blood and PET TACs corrected for radioactive decay 5.Correction for time delay 6.Blood TAC corrected for dispersion 7.Calculation of look-up table using measured and corrected blood TAC 8.Image pixel values are replaced by flow values from the look-up table Look-up Table