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Cancer Therapy and Imaging Cancer Therapy and Imaging Rob Edgecock STFC Rutherford Appleton Laboratory.

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Presentation on theme: "Cancer Therapy and Imaging Cancer Therapy and Imaging Rob Edgecock STFC Rutherford Appleton Laboratory."— Presentation transcript:

1 Cancer Therapy and Imaging Cancer Therapy and Imaging Rob Edgecock STFC Rutherford Appleton Laboratory

2 Imaging and Dosimetry Imaging and Dosimetry What else do we need to know for radiotherapy?  Where the tumour is (exactly)  The structure of the patient  Optimum treatment  Correct dose is delivered Imaging Treatment planning Dosimetry

3 Imaging Imaging Four main techniques X-rays

4 Imaging Imaging Four main techniques X-rays More absorption by denser objects, e.g. bones - appear lighter Less absorption by less dense objects - appear darker

5 Imaging Imaging Four main techniques CT Scan: Computerised (Axial) Tomography X-rays source and detector rotate Thousands of images taken 3Dish image built by computer Very common technique as very fast

6 Imaging Imaging Four main techniques CT Scan: Computerised (Axial) Tomography Much bigger dose than X-rays!

7 Imaging Imaging Four main techniques Molecular imaging: PET and SPECT Load tumour/organ with radiopharmaceutical. Detect products from decay. Positron Emission Tomography Single Photon Emission Computed Tomography

8 Imaging Imaging Four main techniques PET Scan: Most accurate tumour location Not so good for surroundings

9 Imaging Imaging Four main techniques SPECT: uses a gamma emitter directly Gamma detectors rotate. Make 2D images. 3D reconstructed offline. Resolution not as good as PET.

10 Imaging Imaging Four main techniques MRI Scan: Magnetic Resonance Imaging Magnetic field lines up atoms. Different atoms absorb different RF frequencies. Very good for soft tissues (exploits hydrogen in water).

11 Imaging Imaging Four main techniques are (sort of) complementary None is ideal Can lead to incorrectly defined margins Results from 11 student oncologists. Areas inside lines would be treated.

12 Imaging Imaging Situation is improved by combining techniques E.g. CT + PET Still significant room for improvement Results from 11 student oncologists. Areas inside lines would be treated.

13 Treatment Planning Treatment Planning Takes images, etc Uses software to determine best treatment plan Best position, angle, no. of fields, energies, etc Depends on image quality, knowledge of tissue, etc Tumour motion TimescaleEffectPossible solution SecondsBreathingGating; averaging MinutesPatient motionMarkers DayPatient position; food & liquidMarkers; re-scan Week “ “ “ “Markers; re-scan Reduced precision of beam delivery – larger area

14 Dosimetry Dosimetry Verify correct dose delivered to tumour ”In-vivo” dosimetry preferred.....but not actually in-vivo! Catheter dosimeterWireless dosimeter

15 Contributions from Particle Physics Contributions from Particle Physics Improved accelerators for radiotherapy  hard to improve on linacs for X-rays  but.......... Laptop 1MeV electron prototype Big sister being tested

16 Contributions from Particle Physics Contributions from Particle Physics Fixed Field Alternating Gradient accelerator Cyclotron-like Synchrotron-like Combines features of cyclotrons and synchrotrons Interesting for X-ray radiotherapy But.....particularly interesting for hadron therapy..........plus particle physics, power generation, etc

17 Hadron Therapy Requirements  Proton up to carbon beams; 250 MeV to 400MeV/u  Rapid cycling: ~500-1000Hz  Rapid energy variation from accelerator  Gantries  Reliability  “Small” cost  Small size Used currently:  Cyclotrons: protons; SC understudy for carbon  Synchrotrons: protons and carbon

18 Requirements CyclotronSynchrotronFFAG Protons & carbonYes(ish)Yes Rapid cyclingYesNoYes Variable energyNoYes Cost and size – S/CYesNoYes GantriesYes ReliabilityYesNo(ish)Yes FFAGs very interesting Most interesting type – no machine ever built So we’ve built one – called EMMA

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20 EMMA EMMA = proof-of-principle machine Electrons from 10 to 20MeV Use ALICE as injector 42 magnetic “cells” Built on 7 girders

21 EMMA Works! Full experimental programme started. First results published in Nature Physics.

22 PAMELA

23 PAMELA

24 PAMELA Recondensing cryocooler Insulating vacuum chamber 4k Helium vessel Magnets Magnet support structure 40k Radiation shield 40k Inner radiation shield D F F Next step: prototyping of main components: - ring magnets - RF cavities - extraction magnets Positive funding signs

25 Contributions from Particle Physics Contributions from Particle Physics Improved PET imaging:  better tumour location  verification that treatment in correct place

26 ToF PET ToF PET Standard PET:  best tumour locator  but essentially 2D  software required  worse resolution & long time ToF PET  3D  better image & shorter time Detector Tomograph Ring

27 ToF PET ToF PET Conventional500 ps1.2 ns300 ps700 ps Phantom (1:2:3 body:liver:tumor) PP techniques being tried Target ~50ps, but v. difficult Projects to improve other techniques underway Achieved Commercially available

28 Contributions from Particle Physics Contributions from Particle Physics In-vivo dosimetry  smaller device - possible to leave in?  lower power consumption  additional functionality at later date RF UNIT PWR UNIT RAD UNIT RF receiver Radiation Source Implantable micro unit Concept of in-vivo dosimetry

29 Contributions from Particle Physics Contributions from Particle Physics In-vivo dosimetry  smaller device - possible to leave in?  lower power consumption  additional functionality at later date Low power electronic Radiation Sensor Antenna 1000μm Thin film battery on the back side Silicon chip

30 Contributions from Particle Physics Contributions from Particle Physics Data storage and analysis:  creating framework for clinical data  including long term follow-up  help strengthen case  provide info for improvements Patient modelling  no two patients the same  treatment planning includes modelling of beam  PP techniques and codes being tried  PP measurements of interactions for models

31 Conclusions Knowledge from PP being applied in various areas Strong priority in the UK One discussed here Cancer therapy  data storage and analysis  modelling  detector development  accelerator design


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