149 Ion recmbination for ionisation chambers in the 60 MeV proton beam of CCO

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electron beams with energies as low as 6 MeV and that corrections are less than 1% for 9 to 20 MeV beams. 1.07 1.06 1.05 1.04 1.03~ 1.02101 1.00 0.99 0.98 0,97 0.96

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R. Parkkinen P. Sipila STUK Radiation in Health Care, Helsinki, Finland

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148 Verification of i m p l e m e n t a t i o n of the I A E A TRS 3 9 8 f o r e x t e r n a l b e a m s in Finland

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Rso(cm) 147 Models of the light o u t p u t f r o m scintillation crystals

P. Evans, A. Mosleh-Shirazi Institute of Cancer Research and Royal Marsden NHS Trust, Joint Physics Department Sutton, Surrey, UK Scinitillation crystals are used in high energy x-ray imaging application. An example is cesium iodide (CsI). CsI is a high quantum efficiency, high light yield material and may be used in electronic portal imaging (EPI). This work addresses the problem of estimating the light yield from CsI. Two models of the light yield of CsI were developed. The first is a Monte Carlo (MC) transport model, which models volume attenuation, scattering and absorption at Lambertian faces and Fresnel refraction at the CsI/air interface of the exit face. The second model is an analytical, model (AM) that describes these physical processes in terms of a light guide analogy. In the model the scintillation crystal is divided into 10 depth regions. Both models were used to calculate the light output from a range of parallelepiped crystals of area 1.5xl.5 and 3x3mm 2 and 1, 5, 10mm depth. Light output was calculated for a 2cm radius detector at the exit face (flat panel EPID) and at l m distance (camera based EPID). Firstly the light output as a function of depth of x-ray interaction in the CsI was determined. For the flat panel model, this is flat (to within 2%) for the l m m deep crystals and varies by a factor of 1.68 for the 10x3x3 and 5 x l . 5 x 1 . 5 cases and 5.41 for the 10xl.5×1.5 case: the light output increasing the closer to the exit face the x-ray interacts. For the camera based EPID model, the output is also flat for the 1 mm crystals. The variation for the thicker crystals was up to a factor of 3.69 for the 10x1.5x1.5 case. The light output in this case decreased for x-rays interacting closer to the exit face, showing that random scattering events from the Lambertian faces helped to increase the probability of optical photons travelling in the near straight ahead direction necessary to reach a 2cm diameter lens at 1 m distance. The MC and AM were found to agree to better than 5% for the fiat panel model and for all crystals but 10xl.5x1.5, which was within 8%. In conclusion two models have been developed that aJIow estimation of the optical photon signal from CsI scintillation crystals. The segmentation of the model into depth regions will allow calculation of the signal from a variety of radiotherapy beams without recalculation of the optical photon part each time. The use of the light guide model is also expected to allow calculation of light signal from a variety of crystal dimensions with minimal calculation. This is expected to facilitate optimisation of CsI crystal shape.

Purpose: A verification of an implementation of the TRS 398 was done to make sure of the fully understanding of the code of practice. Measurements of absorbed dose to water were carried out consecutively by both hospitals and the Finnish Radiation and Nuclear Safety Authority (STUK). A tolerance level for a deviation between the measurements was 0,7 % for photon beams and 1,5 % for electron beams. Methods: In Finland the IAEA TRS 398 was fully implemented during the year 2003 for all photon and electron beams. The TRS 398 was first introduced on annual meetings of the radiation therapy physicists. The STUK organized the implementation and verified it afterwards on site visits. The absorbed dose in photon beam was measured with Farmer type ionization chambers and in electron beams with plane parallel ionization chambers. Calibrations for Finnish chambers were done by Finnish SSDL (STUK). To compare possible deviations resulting from calibrations STUK made also a site visit to an university hospital in Sweden and made a comparison of consecutively measured absorbed doses. Results: The average difference of comparative absolute dose measurements in 52 photon beams in 2003-04 was 0,2 % (s.d. 0,4 % ) . The difference was at the same level as in years 1999-2002, when it was 0,4 % (s.d. 0,4 %). The results of comparative absolute dose measurements in 107 electron beams in years 2003-04 yielded 0,0 % average difference (s.d. 0,6 %). Earlier results from 1995-99 with 6°Co calibration (n = 136) according to TRS 277 yielded 0,8 % average difference (s.d. 1,4 %) and from 1999-2001 with electron beam calibration (n = 126) according to TRS 381 0,0 % average difference (s.d. 0,7 %). Conclusions: Finland was able to thoroughly implement the TRS 398 in one year period because of the long experience of site visits and effective groundwork in annual physicists meetings. The implementation was made at the site visits for both photon and electron beams and with collaboration with Finnish radiotherapy physicists it was agreed that only one code of practice is used. The results of comparative measurements of absorbed doses show that accuracy in determining the dose has kept at the excellent level after the implementation. In 5 photon beams the difference exceeded the 0,7 % tolerance limit and in electron beams only one deviation exceeded the 1,5 % limit. In electron beam dosimetry transition from the TRS 381 to TRS 398 has not been as big change as from the TRS 277 to TRS 381. 149 I o n r e c m b i n a t i o n for ionisation c h a m b e r s M e V p r o t o n b e a m of CCO

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R. Thomas 1, H. Palmans 1, A. Kacperek 2 iNational Physical Laboratory Radiation Dosimetry London, UK 2Clatterbridge centre for oncology, Douglas cyclotron, Wirral, UK Codes of practice for dosimetry of proton beams do not always give a clear recommendation on the determination of recombination correction factors for ionisation chambers. Recombination correction factors for ionisation chambers were measured in the low-energy clinical proton beam of the Clatterbridge Centre of Oncology (CCO) using data collected at different dose rates and operating the chambers over a range of polarising voltages. This approach allows investigation of the contributions to the correction factor from the initial and volume recombination. The results obtained from this method were Compared with the correction factor obtained using the extrapolation and two-

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Tuesday, September 27

voltage techniques. Two identical plane-parallel ionisation chambers were placed face to face: one used as a monitor, the other as the chamber under test. It was found that this method gave highly accurate results. This method should also be valid in high-energy photon and electron beam dosimetry although this has not yet been investigated. At a dose rate of 26 Gy/min, which is typical of those in clinical use for proton therapy at CCO, the recombination correction was found to be 0.8% and is thus a significant effect for reference dosimetry. Various considerations show that the beam should be treated as continuous and not pulsed radiation. Results for the volume recombination parameter for protons show consistency with values measured for photon beams. Initial recombination was found to be independent of beam quality. Only a small increase was observed at the distal edge of the Bragg peak, indicating a slight LET-dependence, which is however insignificant. For the CCO beam and similar ocular proton beams operating at high dose rates, the recombination correction can be overestimated by up to 1.5% if the recommendation from the IAEA TRS-398, which is only valid for pulsed beams, is followed. 150 Dosimetric implications of approximating u n c e r t a i n t i e s w i t h Gaussian distributions in Carlo based p r o s t a t e cancer t r e a t m e n t planning

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I. Cherty, K. Lam, J. Baiter, R. Ten Haken, D. McShan, H. Sandier, D. Litzenberg University of Michigan, Radiation Oncolog, Ann Arbor, MI, USA Objective: In a previous study, daily setup uncertainties were found to deviate from Gaussian distributions for a group of prostate cancer patients with implanted gold seed markers (Litzenberg et al. IJROBP, 2005 in press). Here we focus on dosimetric consequences of such setup uncertainties. The objectives of the study are: (1) To determine the dosimetric implications of including setup uncertainties in prostate cancer treatment planning, (2) To evaluate differences between treatment plans calculated using measured versus modeled (Gaussian distributed) setup errors. Methods: Setup uncertainties were incorporated into Monte Carlo (MC) based treatment planning using a fluence convolution method. Motion compensation is achieved by translating the static fluence by an offset determined from sampling the setup uncertainty probability density function (PDF). To evaluate the dose differences between setup uncertainties measured daily and those modeled over the course of treatment, plans were generated using actual setup measurements and a Gaussian model with p and c~calculated from setup errors of a given patient. For each plan the number of simulated particles was sufficiently large to produce CrPTV statistics of 1% . Benchmarking of the implementation was accomplished by comparing fluence convolved calculations with direct simulation, where the static dose distribution for each instance of the Gaussian PDF is independently recalculated. R e s u l t s / D i s c u s s i o n : In all cases, the magnitude of differences between static and motion compensated plans were larger for normal tissues relative to the prostate. DVHs for the rectum were in some instances significantly different when measured setup errors were included. Similar trends were observed in comparing plans computed with measured versus Gaussian setup uncertainty, although smaller in magnitude. In compensating for setup errors on a single instance of the patient geometry, MC based fluence convolution is able to finely sample a Gaussian PDF in a single calculation; a considerably more efficient approach than direct simulation. Conclusion: Incorporating setup uncertainties into treatment planning for the prostate may result in significantly different doses to the rectum. However, the

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differences between rectal DVHs from Gaussian models and measured setup errors are less in comparison. Dose coverage to the GTV was found to be uncompromised when adequate margin was used.

Supported by grants NIH PO1-CA59827 and R01-106770 151 A d o s i m e t r y model for e s t i m a t i n g the renal t o l e r a n c e of peptide labeled radionuclide t h e r a p y .

M. Koni/nenberq I, M. de Jong 2 1Mallinckrodt Medical BV R&D, Petten, The Netherlands 2Erasmus MC Nuclear, Medicine, Rotterdam, The Netherlands Radionuclide therapy with radiolabeled (9oy, 177Lu and ittIn) peptides (somatostatin analogs: Octreotide and Octreotate) are being performed at kidney doses well above the 20 Gy threshold for late damage without clear evidence for renal problems. Fractionation and low dose rates can explain a part of the increased tolerance. The influence of inhomogeneity in the radiation dose to the kidneys on renal tolerance is unknown. By calculating the dose distribution patterns for 9°ft 177Lu and ltlIn inside the kidney structures it will be possible to study partial volume irradiation effects. Dose distributions inside the kidneys have been calculated based on autoradiograhy data, identifying high peptide uptake in the medullary rays in the renal cortex. A voxelized version of the MIRD multicompartment kidney model was set up in MCNP4C. In the cortex the centre of the 3mm voxels were pierced by a 1.Tmm diameter cylinder representing the medullary rays (MR). Together with the 1.8ram thick source regions lining the medullae they form 40% of the total cortex volume. The activity was distributed according to the average surface distribution pattern found in ex-vivo ~ I n Octreoscan renal autoradiography patterns in 3 patients: 65% in the cortical MR, 6% in the cortex outside the MR and 29% in the medullae. The dose distribution inside the kidneys was calculated for the emission spectra of 9Oy, 177Lu and t~lIn. Isodose distributions and dose volume histograms were computed as well as average doses to the various source and target regions.was distributed according to the average surface distribution pattern found in ex-vivo 11tIn Octreoscan renal autoradiography patterns in 3 patients: 65% in the cortical MR, 6% in the cortex outside the MR and 2 9 % in the medullae. The dose distribution inside the kidneys was calculated for the emission spectra of 90y, t77Lu and t~In. Isodose distributions and dose volume histograms were computed as well as average doses to the various source and target regions.

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medulla 6.20E-4 3.46E-5 8.82E-5 cortex 4.65E-4 2.78E-5 7.38E-5 - medullary rays 5.12E-4 4.23E-5 1.45E-4 - remaining 3.75E-4 1.69E-5 2.11E-5 cortex MIRD kidney 5.00E-4 3.85E-5 8.02E-5 MIRD Cortex 6.28E-4 4.70E-5 1.17E-4 Table 1. S-values (in mGy/MBq.s) for autoradiography distribution The average absorbed dose S-values to the cortex are for 90Y and 177Lu comparable to the kidney MIRD S-values, but for ttlIn it is 28% lower. With an activity based on an average cortex dose of 27 Gy 9Oy has Os0 of 23Gy to a maximum of 30Gy in the medullary rays, in between the dose is maximally 20Gy and Ds0= 14Gy. t77Lu shows more extreme values: Dso= 51 Gy to maximally 55Gy in the MR and Dso= 7 Gy in between. With l ~ I n the y-ray component softens the values to: Dso= 40 Gy in the MR and Dso= 14 Gy in between. Conclusions: For short-ranged particle emitters like t77Lu and ~ I n the dose-sparing effect by inhomogeneous activity (and consequently dose) distribution is considerable. Also for