Different information X-ray CT X-ray computed tomography PET Positron emission tomography PET/CT Anatomy/ Form Metabolism/ Function Complementary Information (Wikipedia)

Simulation of X-ray CT and radiotherapy Robert L. Harrison University of Washington Medical Center Seattle, Washington, USA Supported in part by PHS grants CA42593 and CA126593 SimSET as platform for research

Nuclear Medicine Radiotherapy Radiology (www.imaginis.com) Step through what is meant by modular: photons are tracked through the phantom/object, then through the collimator/endplates, then through the detector. Various models are available for the collimators and detectors. Available for free download from our website. We also supply user support. (www.imaginis.com) (Stieber et al) (Wikipedia)

Simulation Comparison

National lab simulations • Simulate everything and anything. • Very slow.

Simulation Comparison

CT simulation

Analytic simulation In an analytic simulation we ‘do the integrals’. (Visible Human Project®) In an analytic simulation we ‘do the integrals’.

Beam-hardening X-ray tubes produce a range of energies. (Bushberg) X-ray tubes produce a range of energies. Lower energy photons are more easily scattered/absorbed. The x-ray beam gets ‘harder’ (a higher percentage high energy photons) as it passes through the object.

Scatter Collimation reduces scatter to acceptable levels. Scanners with larger detector areas do have problems.

Analytic CT simulation For every camera line-of-response, step a beam through the voxelized object. Steps can be constant size or to next boundary. At each step, reduce beam strength to account for attenuation. Can use the current voxel’s attenuation or interpolate. (De Man)

Other issues Partial volume (beam is not infinitely thin, several tissue types in voxel). Use finer discretization. Beam hardening. Simulate at several energies, then sum. Patient motion. Do a series of simulations at different positions. (De Man)

Radiotherapy simulation

Types of radiotherapy Photon irradiation. Other particle irradiation. Radioactive seed implantation.

Killing a tumor Radiotherapy attempts to maximize dose to tumors. minimize dose to normal tissues. (Heron)

Types of radiotherapy Photon irradiation.

Huge doses Organ Whole body LD50 Tumor Heart Liver Dose (Grays) 3-5 50- 40 30 (McGarry)

Fractionation Split dose into fractions to allow tissues to heal. 2 Gray/day, 5 days/week, 5-6 weeks. Normal tissue recovers more quickly. Most tumors have hypoxic/necrotic (low oxygen/dead) centers. Time for these areas to develop blood supply. (Stieber)

Dose tolerance (McGarry)

Multiple beams Multiple beams focused on tumor. Maximum dose occurs where beams converge. Dose to particularly sensitive organs can be avoided or reduced with beam placement. (www.impactscan.org)

Simulate dose deposited

Typical simulator Nucletron Oldelft Simulix-HQ

Virtual or CT simulation Software simulation of radiotherapy. Beginning to replace physical simulation for many situations. CT scan used for input data.

Radiation therapy vs. CT (www.impactscan.org)

Large bore

Virtual simulator Segments patient into organs. Allows user to specify beam intensity, shape, position. Keeps track of Total organ/tumor dose. Maximum organ dose. % organ over threshold dose Minimum tumor dose. % tumor under threshold dose. (www.impactscan.org)

Simulation features Semi-automatic anatomy/tumor definition. 3D visualization. Beam’s eye view. Field shaping. Dose histogramming. Symmetric or asymmetric dose margins. Fast.

Take away Simulation of x-ray CT and radiotherapy uses analytic simulation. Too many photons to track. Integrate % of beam escaping for CT. Integrate dose deposition for radiotherapy. X-ray CT produces density maps. Radiotherapy Treatment planning attempts to maximize the dose to tumor, minimize the dose to normal tissue. Dose tolerance of organs varies widely. Simulation used to optimize treatment. Hardware or software.

References J.T. Bushberg, The essential physics of medical imaging, Lippincott Williams & Wilkins, 2002. B. De Man et al, Metal Streak Artifacts in X-ray Computed Tomography: Simulation Study, IEEE Transactions on Nuclear Science, 46:3:691-696, 1999. K.P. George et al, Brain Imaging in Neurocommunicative Disorders, in Medical speech-language pathology: a practitioner's guide, ed. A.F. Johnson, Thieme, 1998. D.E. Heron et al, FDG-PET and PET/CT in Radiation Therapy Simulation and Management of Patients Who Have Primary and Recurrent Breast Cancer, PET Clin, 1:39–49, 2006. E.G.A. Aird and J. Conway, CT simulation for radiotherapy treatment planning, British J Radiology, 75:937-949, 2002. R. McGarry and A.T. Turrisi, Lung Cancer, in Handbook of Radiation Oncology: Basic Principles and Clinical Protocols, ed. B.G. Haffty and L.D. Wilson, Jones & Bartlett Publishers, 2008. R. Schmitz et al, The Physics of PET/CT Scanners, in PET and PET/CT: a clinical guide, ed. E. Lin and A. Alavi, Thieme, 2005. W.P. Segars and B.M.W. Tsui, Study of the efficacy of respiratory gating in myocardial SPECT using the new 4-D NCAT phantom, IEEE Transactions on Nuclear Science, 49(3):675-679, 2002. V.W. Stieber et al, Central Nervous System Tumors, in Technical Basis of Radiation Therapy: Practical Clinical Applications, ed. S.H. Levitt et al, Springer, 2008. P. Suetens, Fundamentals of medical imaging, Cambridge University Press, 2002. www.impactscan.org/slides/impactcourse/introduction_to_ct_in_radiotherapy