Download - Ronald Boellaard [email protected]
Molecular Imaging using Positron Emission Tomography:
Assessment of (neuro-)receptor changes with PET
Ronald [email protected]
Even voorstellen (mini CV)• Ronald Boellaard• Huidige functie: klinisch fysicus en UHD bij de afdeling
Nucleaire Geneeskunde, VUmc, A’dam
• Vooropleiding:- VWO (Gym-β), 1987- Exp.Natuurkunde (en Biologie), 1994- AIO/promovendus op het NKI (afdeling RT) , 1998- opleiding klin.fys. Op VUmc, 2001- klin.fys./UHD op VUmc – tot heden
• Klinische of Medische Fysica = toegepaste fysica
Presentation• General introduction NM and PET• Physics and principles of PET
- general introduction- overview of (neuro-receptor) tracers- positron emission and coincidence detection
• PET pharmacokinetic analysis- principles of kinetic modelling- generation of parametric images
• SPM example of assessment of (neuro-) receptor change
EmissionTomography
Physiology Imaging
Biochemistry Quantification
Pharmacokinetics Flexibility
NM & Positron Emission Tomography
The spectrum of medical imaging Jones, 1996
Structure/anatomy X-ray/CT/MRI
Physiology US, SPECT, PET, MRI/S
Metabolism PET, MRS
Drug distribution PET
Molecular pathways PET
Molecular targets PET, SPECT
Clinical Applications Clinical Applications • Oncology
• Cardiology
• Neurology / Psychiatry
• Pneumology
• Nephrology
......
• Oncology
• Cardiology
• Neurology / Psychiatry
• Pneumology
• Nephrology
......
Very basic principle of nuclear medicine and PET
• Inject radiopharmaceutical (single photon or positron emitter labelled to a drug)
• Use gamma or PET camera to:- evaluate distribution of radiopharmaceutical at some time after injection
- evaluatie uptake, retention and washout of radiopharmaceutical = dynamic or kinetic information
I. Qualitative analysis of PET studies“qualitative/visual inspection”
Examples of FDG whole body scans
Purpose: staging, unknown primary
II. Semi-quantitative analysis of PET studies“standard uptake values (SUV)”
SUV is the uptake of a radiopharmaceutical, normalised to the injected doseand body weight (or lean body mass or body surface area etc)
regions of interest analysis: Average uptake (Bq/cc) in e.g. tumor
Purpose: diagnosis (benign/malignant), prognosis, response monitoring, definition of RT treatment volumes,…
CTI / Siemens HR+ PET scanner RDS 111 15O-cyclotron
Department of Nuclear Medicine and PET Research
location ‘hospital’
Department of Nuclear Medicine and PET Research
location ‘Radionuclide Centre’
HRRT PET scannerGMP lab with 6 hot cells
The High Resolution Research Tomograph (HRRT) PET scanner
HRRTCPS Research
• 8 panel detector heads
• 60.000 LSO crystals
• 1 crystal = 2.1 x 2.1 x 7.5 mm
• 1 billion lines of response
• Cs-137 singles transmission
• 3D only, no septa
• Only 10 scanners in the world (up to now 4 operational)
[11C]-Verapamil for imaging Pgp (Blood Brain Barrier Research)
mdr1a(-/-)/1b(-/-) KO mouse
mdr1a+/+/1b(+/+)WT mouse
Figure A: HR+, 7 mm resolution
Figure B: HRRT, 2.5 mm resolution
Figure A: HR+, 7 mm resolution
Figure B: HRRT, 2.5 mm resolution
0.0
5000.0
10000.0
15000.0
20000.0
25000.0
30000.0
[Bq/
cc]
0.0
5000.0
10000.0
15000.0
20000.0
25000.0
30000.0
[Bq/
cc]
Figure A: HR+, 7 mm resolution
Figure B: HRRT, 2.5 mm resolution
HRRT upcoming protocols: Clinical Comparison with HR+:
A STUDY IN NORMAL SUBJECTS USING THE TRACERS [11C]RACLOPRIDE, [11C]FLUMAZENIL AND [18F]FP-b-CIT.
HRRT upcoming protocols: Clinical Comparison with HR+:
A STUDY IN NORMAL SUBJECTS USING THE TRACERS [11C]RACLOPRIDE, [11C]FLUMAZENIL AND [18F]FP-b-CIT.
Isotope production
Nuclear reactions t1/2
18F (p,n) 110 min
11C (p,a) 20 min
13N (p,a) 10 min
15O (p,n) 2 min
GMP- LAB
Current Tracers [11C][11C]Flumazenil
central type benzodiazepine receptor
(R)-[11C]PK11195 activated microglia
[11C]Raclopride D2/D3
(R) -[11C]Verapamil PgP in BBB
[11C]R116301 NK1 receptor
[11C] PIB amyloid
A B
Current Tracers [18F]
[18F]FP-CITdopamine transporter
[18F]MPPF5HT1a receptor
[18F]FDDNPamyloid
[18F]FLTproliferation
[18F]Prolineaminoacid
[18F]FDG glucose metabolism
Current Tracers[15O]
[15O]H2Operfusion
[15O]O2 oxygen consumption
[15O]CO blood volume
OXYGEN EXTRACTION FRACTION
CBF CMRO OEFCBF CMRO OEF
Presentation• General introduction NM and PET• Physics and principles of PET
- principles- overview of (neuro-receptor) tracers- positron emission and coincidence detection
• PET pharmacokinetic analysis- principles of kinetic modelling- generation of parametric images
• SPM example of assessment of (neuro-) receptor change
Positron emission
511 keV fotonen
positron annihilates with electron
Annihilation produces 2 photons of 511 keV which are sent out in opposite directions
Positron emission detection
Positron emission tomography is based on the simultaneous (coincidence) detection of both annihilation photons
PET
radio-nuclide: positron emitter -> 2 photons
acquisition: coincidence-detection
coincidence processor
PET image reconstruction
ProjectionsProjections
ImageImage
ReconstructionReconstruction
PET scanner acquires projection
reconstruction of activity distribution in patient
PET Image reconstruction
FilteredBackprojection
IterativeReconstruction
Results patients (2)Example images, early frame, poor statistics, ‘fully converged’
FBP NAW-OSEM WLS-nn SP-OS-(W)LS
Presentation• General introduction NM and PET• Physics and principles of PET
- principles- overview of (neuro-receptor) tracers- positron emission and coincidence detection
• PET pharmacokinetic analysis- principles of kinetic modelling- generation of parametric images
• SPM example of assessment of (neuro-) receptor change
Tracer Kinetic Modelling
Tracer Model:
Purpose:
Method:
Mathematical description of thefate of the tracer in the humanbody, in particular in the organunder study
To quantify functional entitiesgiven the distribution ofRadioactivity (over time)
Divide possible distribution oftracer in a limited number ofdiscrete compartments
Brain
FDG uptake as function of time
T=0
T=60min
pharmacokinetic modelling
Dynamic scanParametric image representingbinding of tracer in tissue
Purpose: generation of image representing distribution of PET pharmacokinetic parameter: glucose consumption, DNA synthesis, perfusion etc etc.
Uptake, retention and washout of radiopharmaceutical
• Used radiopharm. (=tracer)
• Supply of tracer in arterial blood (= input function)
• “Physiology” of tumor/organ, which can be quantified using a PET-pharmacokinetic model
Shape and amplitude of time activity curve depends on:
Dynamic PET scanspharmacokinetic analysis
• dynamic scans consist of 20 to 40 sequential acquisitions during a 60 min period
• dynamic scans provide info on the variation of the activity(=pharmaceutical) in an organ/tumor as function of time
• dyn. scans are made to study and quantify the “functional or physiological” behaviour of the organ of interest (glucose and oxygen consumption, blood flow, blood volume, neuroreceptor density)
PET scan
Bolus injector
Bolustoediening bij dyn. (Ex) scans
Loodpot met activiteit
Veneuze inspuiting
Bloodsampler
detectorpompwaste
Analysis of dynamic PET scansInput function
0
50
100
150
200
250
0 2 4 6 8 10
Tijd (min)
Blo
od
ac
tiv
ity
(k
Bq
/cc
) 1022 keV
511 keV
manual samples
Input function also needs to be corrected for metabolites and plasma/blood ratio’s
Blood FreeBound
(or metabolizedor trapped)
Example of Two Tissue Compartment Model
Tissue
PET
Analyse van dynamische PET scanskinetische analyse
0.0E+00
1.0E+04
2.0E+04
3.0E+04
4.0E+04
0 20 40 60 80Tijd (min)
Ac
t.co
nc.
(Bq
/cc
)
0
50
100
150
200
250
0 2 4 6 8 10
Tijd (min)
Blo
od
ac
tiv
ity
(k
Bq
/cc) 1022 keV
511 keV
manual samples
K1
k2
k3
k4Cf CbCa
Quantitative value of apharmacokineticparameter, such as:-glucose comsumption-Perfusion-DNA synthesis-Hypoxia
Overview of ‘common’ pharmacokinetic models
Plasma input models
• Single tissue compartment model (1TC-R)
• Single tissue compartment model (1TC-Ir)
• Irreversible two tissue compartment model (2TC-Ir)
• Reversible two tissue compartment model (2TC-R)
Reference tissue input models
• Simplified reference tissue model
• Full reference tissue model
Reversible single tissue compartment model with plasma input
Blood
Tissue
PET
K1
k2
K1=E x F, E=extraction and F=flow=perfusionVd= K1/k2 = volume of distribution
Irreversible single tissue compartment model with plasma input
Blood
Tissue
PET
K1
K1=E x F, E=extraction and F=flow=perfusion
Irreversible two tissue compartment model with plasma input
k3Blood
Tissue
PET
K1
k2
K1=E x F, E=extraction and F=flow=perfusionKi= K1 x k3/(k2+k3)
FreeBound/
metabolized/trapped
Reversible two tissue compartment model with plasma input
Blood
Tissue
PET
K1
k2
K1=E x F, E=extraction and F=flow=perfusionBP=k3/k4 (sum of specific and ‘slow’ non-specific bindingVd= K1/k2 x (1+BP)
Free Bound
k3
k4
Reference tissue models
A reference tissue time activity curve (TAC) is used as input in stead of plasma input
R1=K1/k2=K1’/k2’=relative flow distributionBP=k3/k4=‘specific’ binding
Presentation
• Physics and principles of PET- general introduction- overview of (neuro-receptor) tracers- positron emission and coincidence detection
• PET pharmacokinetic analysis- principles of kinetic modelling- generation of parametric images
• SPM example of assessment of (neuro-) receptor change
Parametric pharmacokinetic modelling
Dynamic scanParametric image representingbinding of tracer in tissue
Purpose: generation of image representing distribution of PET pharmacokinetic parameter: glucose consumption, DNA synthesis, perfusion etc etc.
PET pharmacokinetic parametric methods
• Parametric=pixelwise=voxelwise, i.e. calculation/modeling is performed per pixel/voxel
• A 3D PET image (volume) consists of ~106 voxels
• Ergo, parametric methods need to be fast
• Most parametric methods use ‘tricks’ to gain computational speed (linearisation,basis function method, (multi-) linear plots)
• Parametric methods are fast calculations performed for each voxel (independently).
Parametric kinetic modelling(1) basis function and linear methods
Blood flow model example
Cb, CpK1
k2
Ct
CtkCpKdt
dCt21
2 solutions for differential equation:- convolution:
- linearization:
Theory
CtkCbKdt
dCt21
tkpt eCKC 2
1 tVF
pdeCF )/(
tpt CkCkC 21
Theory(Basis function method)
bbtVF
bbROI CVeCFVC d )/()1(
tVFb
deC )/(
Theory(Basis function method)
1. Determine F and Va for each basis function using linear least
squares fitting (GLM)
2. Calculate sum of weighted squared difference (Xsqr) for each basis function, F and Va
3. Minimum amongst Xsqr provides ‘best fit’ for F, Va and basis function (=F/Vd)
aatVF
aaROI CVeCFVC d )/()1(
Theory(linearization, linear least squares)
soeeeeROI
ROI
V
k
k
tCbtCttCp
tCbtCttCp
tC
tC
2
11111
)()()(
.....................
)()()(
)(
.......
)(
Y = X (+ ) =X-1Y in theory, but not possible due to noise
LS solution (GLM):=[XTX]-1XTY
Results – Clinical evaluationExamples of parametric CBF images –
various method
BFM GLLS LLS
Examples of parametric images
B C D
E F G
A
A=LoganC=Ichise 1D=Ichise 2E=Ref.LoganF=RPM1G=RPM2
Each voxel value represents the value for a pharmacokinetic parameter (Vd or BP)
Presentation• General introduction NM and PET• Physics and principles of PET
- principles- overview of (neuro-receptor) tracers- positron emission and coincidence detection
• PET pharmacokinetic analysis- principles of kinetic modelling- generation of parametric images
• SPM example of assessment of (neuro-) receptor change
Example of use of parametric PET data for SPM analysis
PET studiesDynamic [11C](R)-PK11195 PET studies of 10 young and 10 elderly healthy control subjects.
Scans were acquired in 3D mode using an HR+ scanner (Siemens). A neuro-insert was used for additional shielding for outside field of view activity.
Kinetic modellingParametric binding potential (BP) images were generated using Ichise linearisation of the simplified reference tissue models using a cerebellum time activity curve as reference tissue input.
Example of PK11195 BP image
Difference between anatomical VOI and SPM
Yellow = Thalamus (& pulvinar) VOI defined on MRIRed = SPM VOI
Effect of VOI method on observed changes in PK11195 binding
-0.05
0.05
0.15
0.25
ANA (A1) PVE (A2) BP>0 (D1) BP-Man (D2) SPM* p>0.01(D3)
VOI method
BP
Young
Old
SPM based on parametric PET data
• SPM might be used to more precisely locate areas of interest and to avoid that VOI are “contaminated” with regions without change.
• Data driven VOI provide a higher sensitivity for assessing (changes in) receptor binding.
• A drawback of data driven VOI, however, is that they depend on the data being used. Both sample size and statistical quality will affect size and shape of the VOI.
• Consequently, data driven VOI strategies may be less reproducible across studies and subjects than anatomically based VOI.