Designing and Improving Medical Imaging Systems by Monte Carlo Studies using GATE

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Designing and Improving Medical Imaging Systemsby Monte Carlo Studies using GATE

Institute of Neurosciences and Medicine (INM)Research Center Juelich

&Department of Mathematics and Natural Sciences

University of WuppertalGermany

Uwe Pietrzyk

ICATPP October 2009 U Pietrzyk - INM – FZ-Juelich - Germany Slide 2

Outline:

• Intro: Neuroscience in the Research Center Jülich

• Motivation: Why using Monte-Carlo Techniquesfor Simulation?

• Some Basics on Medical Imaging

• The Concept of GATE / GEANT4 / ROOT

• Examples of GATE Applications

• Summary & Demo


Outline:






• Summary & Demo


Institute of Neurosciences and MedicineArea for 9.4T MR/PET


Moving the Magnet for the 9.4T MR/PET Hybrid Scanner


9.4T MR/PET Hybrid Scanner / Magnet in place / PET-Module on site


Institute of Neurosciences and Medicine (INM)

Architectonics and brain functionProf. Dr. K. Amunts

Structural und Functional

Organisation of the Brain

Prof. Dr. K. Amunts

Cognitive Neurology

Prof. Dr. G.R. Fink

Physics of MedicalImaging

Prof. Dr. N.J. Shah

MR PhysicsProf. Dr. N.J. Shah

PETProf. Dr. H. Herzog

Brain tumoursProf. Dr. K.-J. Langen

Molecular Organisation of the Brain

Prof. Dr. K. Zilles

Transmitters-receptors

Prof. Dr. K. Zilles

Structureof Synapses

Prof. Dr. J. Lübke

Molecular Neuroimaging

Prof. Dr. A. Bauer

Functional neuronal circuits

Prof. Dr. D. Feldmeyer

System MedicineProf. Dr. Dr. P. A. Tass

NeurotechnologyPD Dr. C. Hauptmann

Neuromodulation

Prof. Dr. Dr. P. A. Tass

MathematicalNeuroscience

PD Dr. O.V. Popovych

RadionucleiDevelopmentDr. B. Scholten

Radio-pharmacology

Dr. D. Bier

RadiotracerDevelopment

Dr. D. Holschbach

RadiotracerProductionDr. J. Ermert

Dr. K. Hamacher

Nuclear Chemistry

Prof. Dr. H.H. Coenen

Ethics in theNeurosciences

Prof. Dr. D. Surma

Systems Biologyand

Neuroinformatics

N.N.

Multimodal ImageProcessing & Morphometry

Prof. Dr. U. Pietrzyk


Analysis of the structure and the functional processes of the brain at the organ level and at the cellular level. To understand the organisational principles of the brain.

To explore the mechanisms of the normal and pathological nervous system.

Development of new techniques for diagnosis and therapy for neurological and psychiatric diseases, e.g. demand-driven, deep brain stimulation, electrical or chemical neuromodulation.

Development of new methodologies for imaging the in vivo brain.


Highlights from the Research Programme

Molecular PET Imaging

Mechanisms of Cognitive Processes in Normals and Patients

Brain Pacemaker

3D Map of the Human BrainNew MR Methods

Neurodegenerative Diseases


• Ligands for the depiction of cerebral receptors

• Amino acids for the diagnosis of brain tumours

[18F]CPFPXAdenosin-A1 Rezeptors ligand

2-[18F]Fluorethyl-L-tyrosinLN-Amino acid transporter ligand

Highlights from the Research Programme


Outline:






• Summary & Demo


Interesting for studying the features of detection systems, which cannot be described analytically:

• How to estimate the acceptance of a multichannel detector for high energy photons?

• How to determine the contribution from scattered photons prior to calculate the tracer uptake in a certain Region of Interest (ROI) image analysis?

Motivation (1):

Why using MonteCarlo techniques to simulate Medical Imaging Devices?


Advantage:

Can describe very complex systems!!

Disadvantage:

Often requires considerable computation times!!

It is a statistically founded method, hence, bearsintrinsical errors!! Samples have to be sufficiently large!!

Motivation (2): MonteCarlo techniques – Advantages and Disadvantages!


Processing Pipeline:

From basic detector design

to reconstructed imagesandquantitative evaluation

Note: Such images are reliable only, if we can handleall corrections. Simulation is an essential support!

Motivation (3): MonteCarlo technique – an interesting option!


Outline:






• Summary & Demo


• The fundamental experimental setup

the main components

• Difference of functional and structural imaging:

PET and SPECT vs. CT and MRINuclear Medicine: Radiology:PET = Positron Emission Tomography CT= X-Ray Computed TomographySPECT= Single Photon Emission MRI= Magnetic Resonance Imaging Computed Tomography

Note: PET and SPECT are “counting experiments”!!

Some Basics on Medical Imaging


The Basic Principle of Imaging

Source (external)

Object (+ Source)

Selection / Definition using:

(a) Diaphragm; (b) Grid;

(c) Collimator;(d) Coincidence Circuit)

Detector

X

✓


Current Scene of Functional andStructural / Morphological Imaging

18

PET PET/CT CT

SPECT/CT

SPECTMRT

MR/PET

ImageFusion


Complementary Nature: example: MRI & PET

19

Note: Already today, PET is mostly available as a combined modality, namely PET/CT


Basics in Positron-Emission-Tomography (I)

20

Note Two co-linear photons No collimation!Need correction for scatter and attenuation!

Unknown tracer-distribution in an environment of unknown denstity

MRI

Detector Detector


Basics in Positron-Emission-Tomography (II)

212121

MRI

+ Imaging System: Detector with high resolution and high sensitivity

Scintillators (LSO / GSO, ...) coupled to PMT or APD fast electronics

+ highly specific tracers, „smart probes“; nano molar concentrations

+ suitable isotope: 18F (T1/2 109.8 min, avg. Ekin 0.242 MeV, range: FHWM 0.22 mm)+ precise image reconstruction incl. corrections

(a) 1×1×10mm LSO crystals,

(b) polyurethane grid and

(c) completed 12 × 12 scintillator array.A

D

BB

photomultipliers

scintillator

(511 keV)


Outline:






• Summary & Demo


The Goals of Simulation in Nuclear Medicine:

GGeant4 AApplication forTTomographic EEmission

Scanner Design

Protocol Optimization

Image Reconstruction

Data Analysis

Testing new algorithms

Scatter Correction

Quantification / Recovery


Two different Approaches:

General purpose simulation codes (GEANT4, EGS4, MCNP…) wide range of physics wide community of developers and users documentation, maintenance and support complexity speed

Dedicated simulation codes (PETsim, SimSET, Eidolon, SIMIND…) optimized for nuclear medical imaging applications (geometry, physics...) ease of use and fast development maintenance, upgrades


A Combined Approach (I):

25

• Realistic modeling of PET/SPECT experiments modeling of detectors, sources, patient movement (detector, patient) time-dependent processes (radioactive decay,

movement management, biological kinetics) • Ease-of-use• Fast• Long-term availability, support and training

PET/SPECT dedicated

developmentsGATEGATE

(by OpenGATE Collaboration)

(by GEANT4 Collaboration)


A Combined Approach (2):

26

• Based on GEANT4object Oriented Analysis & Designwide range of physics modelslong term availabilityupgrades, documentation & support

• Specific developments regarding to Nuclear medical imaging needs

material database, sources, readouttime and movement management

• Ease-of-use for non C++ programmersscripting commands to define all paramaters of the simulation (construction of the geometry, specification of the physical processes involved, of the sources...)


GATE structure (1):

General Scope

27

• Three different levels:• GEANT4 core

• Developer level framework and application

classes C++ programming

• User level sequence of scripting

commandsgeometry construction physical processes involvedsources (geometry, activity) movement (type, speed…) duration of the acquisition

User interface

Application classes

Framework

Geant4


GATE structure (2):

Geometry Construction A specific mechanism has been

developed to help the user construct easily a geometry scripting commands geometry = combination of

geometric volumes, like ‘russian dolls’


GATE structure (2):

Geometry Constructionworld

Source

Body Head

Scanner

Rsector

Crystal

LSO BGO


GATE structure (2):


Source

Body Head

Scanner

Rsector

Crystal

LSO BGO


GATE structure (3):

Two Complete Examples

Multi-ring PET

D. StrulIPHE Lausanne

Triple-head gamma camera

S. StaelensUni Ghent

D. StrulIPHE Lausanne


GATE structure (4):

Source Management

36

• Multiple sources controlled by source manager inserted via scripting complex geometries: customized GPS

(General Particle Source) Also: voxelized Sources, i.e. brain phantoms

• Optimized decay customized G4 Radioactive Decay Module (RDM) PET-specific sources


GATE structure (5):

Timing and Motion

• Simulation time– a clock models the passing of

time during experiments– the user defines the

experiment timing• Time-dependant objects

– updated when time changes– allows programming of

movement, tracer kinetics...


GATE structure (6):

Physical Processes

PHOTONSELECTRONS

Standard photoelectric effect LE Compton scattering

Standard Gamma conversion

Standard Ionisation

Standard Bremsstrahlung

LE photoelectric effect

Standard Compton scattering LE Rayleigh scattering

LE Gamma conversion

LE Ionisation

LE Bremsstrahlung

• Choices of processes via scripting commands:low energy, standard or inactive

• Cut settings


GATE structure (7):

Sensitive Detectors / Digitizer

Hits

Digis

Energyresponse

Spatialresponse

Centroidreadout

ThresholdElectronic

s Pre-programmed components

– Sensitive detectors– Trajectory analyser

Digitizer– Linear signal processing

chain– Modular: set-up via scripting


GATE structure (8):

Data Output Formats• Multiple parallel output channels:

ROOT (real-time display, storage in ROOT files for further analysis)

ASCII files Binary files, incl. voxelized formats Specific scanner formats (e.g Crystal Clear LMF…)(Find ROOT at http://root.cern.ch/drupal/)

GATE simulation Sinogram Reconstructed image


Background of GATE:

41

• OpenGATE Collaboration founded in 2002• http://opengatecollaboration.healthgrid.org• Spokespersons:

• Christian Morel (Lausanne / Marseille; till 2003)

• Irene Buvat (INMC, Orsay / Paris; from 2003)GATE: a simulation toolkit for PET and SPECT

Phys. Med. Biol. 49 (2004) 4543–4561

S Jan1, G Santin2,24, D Strul2,25, S Staelens3, K Assie4, D Autret5, S Avner6, R Barbier7, M Bardies5, P M Bloomfield8, D Brasse6, V Breton9, P Bruyndonckx10, I Buvat4, A F Chatziioannou11, Y Choi12, Y H Chung12, C Comtat1, D Donnarieix9,13, L Ferrer5, S J Glick14, C J Groiselle14, D Guez15, P-F Honore15, S Kerhoas-Cavata15,

A S Kirov16, V Kohli11, M Koole3, M Krieguer10, D J van der Laan17, F Lamare18, G Largeron7, C Lartizien19, D Lazaro9, M C Maas17, L Maigne9, F Mayet20, F Melot20, C Merheb15, E Pennacchio7, J Perez21, U Pietrzyk21, F R Rannou11,22, M Rey2, D R Schaart17, C R Schmidtlein16, L Simon2,26, T Y Song12, J-M Vieira2, D Visvikis18, R Van deWalle3, EWieers10,23 and C Morel2

http://opengatecollaboration.healthgrid.org/


Background of GATE:

42


Outline:


• Motivation: Why using MonteCarlo Techniquesfor Simulation?




• Summary & Demo


Clinical Example (I)

44

Estimating Scatter Contribution in Planar Gamma Camera Studieswith Iodine 131

A. Zakhnini (Diploma Thesis, University of Wuppertal)

GE Infinia 3/8’’ / HawkeyeHelios Clinic Wuppertal


Clinical Example (II)

45


A. Zakhnini (Diploma Thesis,

University of Wuppertal)

Lateral View



46




Lateral View



47




Lateral View


Simulating new Developments for PET in GATE (I)

48

LSO

LSO

Classic solution:Scintillator + PMT

Modern solution:Scintillator + APD

More Compact!

PMT: Size:10-50 mmGain: up to 10**6Risetime: 1 nsQE: 20 %

APD:Size:5x5 mm**2Gain: up to 200Risetime: 5 nsQE: 70 %


Simulating new Developments for PET in GATE (II)

49

• more compact PET• much less “dead space”

• higher sensitivity

APDHamamatsu

4x8 elements10.5x20.7 mm2

pixelizedscintillator block

monolithicscintillator block


Simulating new Developments for PET in GATE (III)

5050

Simulation of Optical Photons in a

monolithic detector

N. Kobert, PhD-study, FZ-Juelich / Uni Wuppertal

APD(4 x 4

Elements)

Crystal (wrapped in Teflon) full of optical

photons

Incident Gamma (511 keV)


Simulating new Developments for PET in GATE (IV)

5151 N. Kobert, PhD-study, FZ-Juelich / Uni Wuppertal


Simulating new Developments for PET in GATE (V)

5252 N. Kobert, PhD-study, FZ-Juelich / Uni Wuppertal


Simulating new Developments for PET in GATE (VI)

5353

Simulation of Optical Photons in a monolithic

detector

N. Kobert, PhD-study, FZ-Juelich / Uni Wuppertal

Difference: Gamma coordinates (x / y)and centroid of optical photons

Centroids of Optical Photons (x / y)

Deviation x Deviation y


Simulating new Developments for PET in GATE (VII)

5454

Simulation of ClearPET Neuro

at FZ Juelichwith

GATE v 5

-----

Dynamic Simulationincorporating Rotation

of Gantry


Simulating new Developments for PET in GATE (VIII)

5555

ClearPET Neuro: RAT study


Simulating new Developments for PET in GATE (IX)

5656

Simulation of ClearPET Neuro:Source Distribution of a Homogeneous Cylinder

Rat Study with ClearPET NeuroReconstruction with STIR


Acknowledgements

57

Special thanks to Markus Axer (INM-1, FZ-Juelich)Alexandra Hellerbach (INM-1, FZ-Juelich)Natalia Kobert (INM-1, FZ-Juelich)Jürgen Scheins (INM-4, FZ-Juelich)Karl Ziemons (ZEL, FZ-Juelich)

Hamid Zakhnini (University of Wuppertal)Klaus Gasthaus (Helios Clinic Wuppertal)

&

all Members of the OpenGATE Collaboration


Contact

58

Prof. Dr. Uwe Pietrzyk(Physicist)Deputy DirectorInstitute of Neurosciences and Medicine (INM-1)Structural and Functional Organization of the BrainGroup Leader: Multi Modality Image Processing and MorphometryResearch Center Juelich GmbH, GermanyE-Mail: [email protected]://www.fz-juelich.de/INM&Department of Mathematics and Natural SciencesUniversity of Wuppertal, Germany

mailto:[email protected]

http://www.fz-juelich.de/INM

Designing and Improving Medical Imaging Systems by Monte Carlo Studies using GATE

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