Search

Purpose Recent advances in radiation therapy have provided the possibility of combining different modalities in different parts of the treatment. The purpose of this study was the determination of the parameters D 50 and γ for the prostate adenocarcinoma using different radiobiological models, when proton and photon beams are combined. Material and Methods In this study 100 patients, who were treated for prostate cancer at the Academic Hospital in Uppsala, Sweden from 2002 to 2006, were used. The patients were treated with a conventional photon beam configuration to a dose of 50 Gy in 2 Gy fractions. Additionally, a proton boost of 20 Gy in 5 Gy fractions was applied. The photon and protondoses were corrected for the fractionation effects using the BED (biologically effective dose) concept. In the calculation of the protondose, we considered RBE=1.1. For each patient, the clinical treatment outcome (follow‐up of 24 months) and the 3D dose distribution delivered to the target were available. The best estimates of the parameters D 50 and γ of the Binomial, Poisson and Probit models were determined by applying a maximum likelihood fitting. Results Of the 100 patients, 94 had tumor control (94.0%) whereas 6 patients had treatment failure (6.0%). The mean doses in the prostate in these two groups of patients were 72.97Gy and 62.60Gy, respectively. The estimated values of the parameters for the Poisson and Binomial models are D 50=49.6Gy (68%CI=47.1–51.9Gy) and γ=2.25 (68%CI=1.83–2.75), whereas for the Probit model they are D 50=47.3Gy (68%CI=45.1–49.4Gy) and γ=1.31 (68%CI=1.11–1.52). Conclusions The estimated parameters are able to describe the dose‐response relation of prostate adenocarcinoma. Since there are very limited data on radiation therapy using combinations of photon and proton beams, the determined parameters can be useful in estimating the expected clinical outcome during treatment planning and perform optimization of the delivered treatment.

Purpose The purpose of this study was the determination of the parameters D 50 and γ for the rectum and penile bulb using different radiobiological models, when proton and photon beams are combined. Material and Methods In this study, 98 patients were included with localized adenocarcinoma of the prostate. The patients were treated with a conventional photon beam configuration to a dose of 50 Gy in 2 Gy fractions. Additionally, a proton boost of 20 Gy in 5 Gy fractions was applied. In some patients, the distance between prostate and rectum was increased during proton therapy by retraction of the rectum in the dorsal direction by the use of a cylindrical rod of Perspex inside the rectum. In the calculation of the protondose, we considered RBE=1.1. The best estimates of the parameters D 50 and γ of the Binomial, Poisson and Probit models were determined by applying a maximum likelihood fitting. Results 33 of the patients produced rectal dysfunction (33.7%). The analysis shows that the treatment plans with rectal retraction significantly reduces the dose in the rectum and as a consequence the responders of the treatment (27.3% vs. 36.9% with and without the rod, respectively). The estimated parameters values for the Poisson and Binomial models are D 50=61.2Gy (68%CI=57.5–65.2Gy) and γ =0.8 (68%CI=0.6–1.0) for the rectum. The estimated values for the Probit model are D 50=60.5Gy (68%CI=56.9–64.1Gy) and γ=1.0 (68%CI=0.7–1.3) for the rectum. Of the 89 patients used in the penile bulb analysis, 25 had sexual dysfunction (28.1%) with mean doses for the responders and non‐responders of 55.5 Gy and 54.2 Gy, respectively. Conclusions The additional use of the cylindrical rod in the protontreatment appears to reduce rectal side effects. The determined parameters can be useful in estimating the expected clinical outcome during treatment planning and perform optimization of the delivered treatment.

From a mathematical point of view, radiation therapy planning is in principle an inverse problem. This is because with a given target volume one wants to find the optimal combination of incident beams. More exactly, the planning process should answer the question: for a given target volume and location of surrounding organs at risk, which configuration and shape of the incident beams are best for controlling tumor growth and minimizing damage to normal tissues? At least on assumption that the geometric and radiobiological properties of the tumor and of the patient are known, it should be possible to find the optimal irradiation technique [1]. Classical radiation therapy planning, however, is essentially a forward process: for a given configuration of the incident beams and associated patient geometry, what does the dose distribution in the target volume and surrounding normal tissues look like? Conventional therapy planning is therefore by necessity a trial-and-error process in which gradually improved dose plans may be found by iteratively testing an increasing number of beam configurations. However, inverse therapy planning results directly in an optimized dose plan for a given irradiation technique. Optimal incident beams in this context generally mean those beams that deposit the smallest possible dose in normal tissues outside the tumor. Recent general solutions to this inverse problem have the potential of greatly improving the dose delivery, especially in the treatment of large, complex, or deep-seated target volumes. However, they rely on the assumption that the best possible dose distribution in the target volume can be specified by the prescribing physician.

Purpose: BioSuite is a program developed to help clinicians to identify cases eligible for dose escalation and/or altered fractionation and to quantify this potential using biological models of normal tissue and tumour response to EBRT. Materials: BioSuite consists in a single executable file developed in C++. The input data are DVHs from a TPS (Philips Pinnacle) as well as a more general DVH format. Plans are defined by parameters such as the number of fractions or a default prescription dose. These DVHs are in turn associated with an endpoint defined by a biological model and a set of parameters. From these models (LKB, Relative Seriality and enhanced LQ Poisson TCP), evaluation of NTCP or TCP can be performed forwardly or inversely. The forward evaluation is made in real-time as the operator modifies plan or endpoint parameters. The inverse evaluation (or optimisation) finds the "dose multiplication factor" (DMP) rescaling the DVH or number of fractions of a given size which take the complication risk to a prior set level. An "isotoxic optimisation" can also be done, which consists of computing for a fraction-number range the highest DMP (and thus TCP) for a constant NTCP. An upper TCP limit can be set (e.g. 99%) to avoid excessive doses in particular cases. The operator can finally generate dose-response curves to visually assess plan quality. Isotoxic optimisation was applied to 33 plans from our institution whose DVHs were exported to BIOSUITE. Results: For most of these plans, scope for dose escalation and/or altered fractionation was found, suggesting these patients were "undertreated". In cases with a very small tumour and consequently small volume of irradiated normal tissue, the models implemented in BioSuite suggested treatments very similar to those currently done in SBRT i.e. TCP close to 100% for as low as 3 fractions. Serial organ DVHs in the plan can drastically affect the BIOSUITE fractionation strategy, making hypofractionation no longer viable.

Purpose The majority of complications occur in patients with large AVM volumes being treated with high doses. For large intracranial arteriovenous malformations, the special characteristics of high ionization density light ion beams offer several advantages over photon and proton beams for high dose stereotactic radiation therapy. These include a better depth dose‐distribution in tissue, negligible lateral scattering, a sharper penumbra, a steep dose fall‐off beyond the Bragg peak and a higher probability of vascular response. Material and Methods Peripheral doses and dose volume histograms (DVHs) of large AVMs were collected from different centers. Based on these data and using a maximum likelihood fitting, dose‐response parameters were derived for the Binomial model. A comparison was performed for different radiation modalities taking also into account their radiobiological differences. Results Light ion Bragg peak dose delivery has the precision required for treating very large AVMs, as well as for delivering extremely sharp focused beams to irregular lesions. For stereotactic radiosurgery with light ions, a better angiographic obliteration rate was observed. Furthermore, a lower complication rate and lower white matter necrosis was simultaneously achieved, which composed a more favorable overall clinical outcome. In patients treated by helium ion beams, a sharper dose‐response gradient was observed, which is probably related to a more homogenous radiosensitivity of the AVM nidus to ion beamradiation.Conclusion Based on this study of linear energy transfer of different therapeuticion beams19 (H, He, Li, C), Helium or Lithium ions may be most suitable for AVM's up to 10 cm3 and for larger AVMs Lithium to carbon ions may be more appropriate. The unique physical characteristics of light ion beams are of considerable advantage for the treatment of AVMs located in front of or adjacent to sensitive and functionally important brain structures.

Purpose: Significant discrepancies in dose delivery can contribute to underdosage of the tumor or overdosage of normal tissue. To study the impact of patient positioning and internal organ motion in breast cancerradiotherapy, the setup and breathing uncertainties characterizing three different irradiation techniques are employed. Method and Materials: Fifteen breast cancer patients (5 resected with negative nodes (R−), 5 resected with positive nodes (R+) and 5 ablated), who were treated with three different irradiation techniques are examined. The positioning uncertainties in the anteroposterior (AP) and the craniocaudal (CC) directions are approximated by Gaussian distributions and breathing is assumed to be linear. The combined frequency distributions of the positioning and breathing distributions are obtained by convolution. The three radiation techniques are compared by using the complication‐free tumorcontrol probability, P + and the biologically effective uniform dose (BEUD). Results: For the R− case, at the optimum dose levels of the two dose distributions, the P + values are 97.9% and 97.3%, respectively. The respective total control probabilities, P B are 99.3% and 99.1%, whereas the corresponding total complication probabilities, P I are 1.4% and 1.8%. For the R+ case, the P + values are 94.2% and 93.0%, respectively. The P B values are 97.5% and 96.3%, whereas the P I values are 3.3% and 3.3%. For the Ablation case, the P + values are 96.9% and 89.4%, respectively. The P B values are 99.0% and 96.5%, whereas the P I values are 2.1% and 7.2%. In this case, for lungradiation pneumonitis Grade 1–2 the P + values would change to 69.3% and 37.7%, respectively. Conclusion: The combined effects of positioning uncertainties and breathing motion can introduce a significant deviation between the planned and delivered dose distributions to the lung in breast cancerradiotherapy. This inaccuracy in the delivered dose may lead to a significant underestimation of the expected lung complications.

Purpose: In order to estimate better the clinical effectiveness of the Helical Tomotherapy and MLC‐based IMRT radiation modalities a radiobiological assessment was performed. This was achieved by employing additional physical and radiobiological criteria. Method and Materials: Two brain and cranio‐spinal cancers were investigated. For each cancer type, a linac MLC‐based step‐and‐shoot IMRT plan and a Helical Tomotherapy plan were developed. The treatment plans of the MLC‐based IMRT were developed on the Philips treatment planning station (Pinnacle 7.6 software release), whereas the dedicated Tomotherapy treatment planning station was used for the HT plans. The different treatment plans were compared using dosimetric criteria and the biologically effective uniform dose (BEUD) together with the complication‐free tumor control probability (P +). Results: The applied plan evaluation method shows that in the braincancer case the HT treatment gives similar results with the MLC‐based IMRT (P + of 66.0% and 63.4%, respectively). The total control probabilities, P B are 79.5% and 76.6%, whereas the total complication probabilities, P I are 13.4% and 13.1%. In both cases, the dose limiting tissue is the Speech Area. In the cranio‐spinal cancer case, the HT treatment plan is much better than the MLC‐based IMRT plan with P + values of 84.1% and 28.4%, respectively. The P B values are 86.4% and 51.3%, whereas the P I values are 2.3% and 23.0%. In the case of HT, the lung is the dose limiting tissue (1.7%) whereas in the case of MLC‐based IMRT the dose limiting tissues are the lung (8.1%) and the left kidney (14.2%). Conclusion: Both MLC based‐IMRT and HT are suitable for treating often large PTVs while minimizing the volume of the organs at risk receiving high dose. However, in certain more complex clinical cases the HT radiation modality may show clearly better properties in producing very conformal and clinically effective dose distributions.

Purpose: Regularization techniques for determining the optimal dose distribution have been proposed because the dose distributions produced by different IMRTtreatment planningoptimization algorithms are highly non‐uniform in the target volume. In the present work, an analysis is made about the relation of the DVH gradient and the dose to the PTV and normal tissues.Method and Materials: In this study, two head & neck and prostate cancer cases treated with IMRT were employed. Three different dose distributions were obtained by using a dose‐basedoptimization technique, an EUD‐based optimization without regularization of non‐uniformity and an EUD‐based optimization using a variational regularization technique. The clinical effectiveness of the three dose distributions was investigated by using the complication‐free tumor control probability, P + and the biologically effective uniform dose.Results: In the head & neck case, for the dose‐basedoptimization, the P + value is 32.9%, the total control probability P B is 79.6% and the total complication probability P I is 49.0%. For the EUD‐based no‐reg optimization, the P + value is 56.4%, the P B value is 71.9% and the P I value is 15.5%. For the EUD‐based reg optimization, the P + value is 67.3%, the P B value is 87.4% and the P I value is 20.1%. In the prostate case, for the dose‐basedoptimization, the P + value is 94.8%, the P B value is 97.8% and the P I value is 3.0%. For the EUD‐based no‐reg optimization, the P + value is 86.0%, the P B value is 97.3% and the P I value is 11.3%. For the EUD‐based reg optimization, the P + value is 95.3%, the P B value is 98.4% and the P I value is 3.1%. Conclusion: The radiobiological comparison shows that the EUD‐based optimization with regularization gives better results than the EUD‐based optimization without regularization and dose‐basedoptimization in both clinical cases, which indicates better clinical effectiveness.

Purpose: The aim of this study is to determine the parameters that describe the dose‐response relations of spinal cord regarding the endpoints of radiation myelopathy in the thoracic and cervical parts. This can be critical information since spinal cord is known for its serial behaviour. Method and Materials: In the present study, the clinical data of 43 patients treated for lungcarcinoma and 248 patients treated for head and neck cancer are analyzed. The two datasets were fitted by the relative seriality model regarding thoracic and cervical spinal cord radiation myelitis. The respective best estimates of the model parameters were determined together with their 68% confidence intervals by applying the maximum likelihood method to fit the clinical data. Results: The parameter values of D 50 = 75.5 Gy , γ = 1.13, s = 36.0, describe the dose‐response relation of thoracic myelopathy, whereas the dose‐response relation of cervical myelopathy can be adequately described by the parameters D 50 = 55.9 Gy , γ = 6.88, s = 0.13. Regarding the cervical radiation myelopathy, 10 of the 12 responders had received a uniform dose in the whole circumference of the irradiated vertebrae (83.3%). Furthermore, only 18 of the 248 patients had received a uniform dose in the anterior and posterior parts of the irradiated vertebrae. 10 of those 18 patients (55.6%) showed complications. Conclusion: The high relative seriality, s value of the thoracic part and the quite low s value of the cervical part are the major findings of the present analysis. According to our observations, when a larger portion of cervical spinal cord was irradiated, considerably more patients showed cervical myelopathy. This indicates that the manifestation of radiation myelitis is clearly related with a dose cutoff and volume effect in the cervical part of spinal cord.

Purpose: In radiotherapy for breast cancer, it is very important to estimate the expected lung complications. In this study, it is examined whether the Dose Mass Histogram (DMH) concept can be better associated with the expected lung complications than the widely used Dose Volume Histogram (DVH) concept. Method and Mataerials: The problem was investigated theoretically by applying two hypothetical dose distributions (Gaussian and Semi‐Gaussian shaped) on two lungs of uniform and varying densities. Furthermore, a group of breast cancer patients was used to clinically quantify the difference between DVHs and DMHs. These patients were treated with resection and irradiation with two tangential fields. The influence of the deviation between DVHs and DMHs on the clinical endpoint of radiation pneumonitis is estimated by using the Relative Seriality and LKB models. The biological equivalent of the corresponding difference in their mean doses was estimated by the Biologically Effective Uniform Dose (BEUD) and Equivalent Uniform Dose (EUD) concepts, respectively. Results: The relation of the DVHs and DMHs varies depending on the underlying cell density distribution and the applied dose distribution. The range of their deviation in terms of expected clinical outcome was large both for the theoretical and the clinical studies. For the group of patients, according to the DVH, lung receives 9.82 Gy, whereas according to the DMH it receives 8.06 Gy (1.76 Gy difference). Interpreting these figures in terms of lung response, DVH gives 0.30% probability for lung complications compared to 0.10% given by DMH for the Relative Seriality model. Similarly, for the LKB model the corresponding values are 2.62% and 1.85%, respectively. Conclusion: Concluding, the expected lung complications appear to be overestimated when using the DVH concept, whereas the effectiveness of the dose distribution is closer related to the radiation effects when using the DMH concept.

Purpose: The aim of this study is to calculate the average penetration depth, zav , and detour factors of 10–10 000 eV electrons in water using an in‐house Monte Carlo track structure code. These low electrons are known to be the most toxic in sense of radiation damage and the calculation of their true depth of penetration and energy depositions is required in areas such as radiation therapy, to be able to calculate the correlation between ion tracks and the potential cell damage. Method and Materials: The CSDA‐range largely overestimates the range of electrons of energies between 10–10000 eV because of the high amount of elastic scattering. Up to 50% of the interactions can be elastic for energies below 100 eV. This phenomena will shorten the longitudinal distribution, average penetration depth zav , but @@ elongate the transverse distribution 〈x 2 +y 2 〉 av . Several definition of the detour factor can be found in the literature. In this work is the detour factor defined as in ICRU (1993): d = z av /r o , were ro is the CSDA‐range. The zav is computed according to: z av = 1 N Σz abs , were N is the number of histories and zabs is the depth of absorption of every primary electron.ro is calculated by integrating the stopping power, which is extracted from the MC track structure code. Results: The calculated zav is shorter for low energies compared to Wilson et al(2004) and slightly higher for energies around 10 keV. zav is substantially shorter than the calculated CSDA‐range for energies below 1 keV, which results in a small Detour factor. The sigmoid shape of the Detour curve decompose at very low energies around 10 eV due to a drastically reduction of the ionization cross section and a still increasing elastic cross section. Conclusion: The results show that the CSDA‐range should be used with caution at these low energies.

In inverse radiotherapy planning, the traditional dose planning sequence is reversed. This makes it possible to calculate the optimal incident beam profiles required to produce the desired dose distribution in the target volume by solving an integral equation with an iterative algorithm. The major advantage, compared with conventional treatment planning, is that the trial and error part is avoided, and replaced by a deterministic calculation of the optimal treatment plan. In the present paper this algorithm is briefly described and compared with experimental results and an analytical inversion formula which is valid for a cylindrical geometry. The experiments were performed with non-homogeneous beams shaped with compensators designed using the algorithm. The agreement between the experimental results and the predictions of the algorithm are quite good, generally within about 5%. The differences are caused by discretization noise due to the finite resolution of the calculation matrix, imperfections in the experimental situation, and by the assumption of spatial invariant dose distribution kernels.

Purpose: Due to the highly conformal distributions that can be obtained with intensity modulated radiation therapy(IMRT), any discrepancy between the intended and delivered distributions would likely affect the clinical outcome. Consequently, there is a need for a measure that would quantify those differences in terms of a change in the expected clinical outcome. Material and Methods: To evaluate such a measure, the case of a cervix cancer was used where the bladder and rectum, are proximal and partially overlapping with the internal target volume. A solid phantom simulating the pelvic anatomy was fabricated and a treatment plan was developed to deliver the prescribed dose to the phantom. The phantom was then irradiated with films positioned in several transverse planes. The racetrack microtron at 50MV was used in the treatment planning and delivery processes. The dose distribution delivered was analyzed based on the film measurements and compared against the treatment plan. The differences in the measurements were evaluated using both physical and biological criteria. Results: For the computerized treatment plan, the maximum value of P + was 84.1%, for a mean dose to the ITV of D = 93.3Gy, associated relative standard deviation σ D /D = 16.8% and biologically effective uniform dose,D ITV of 89.2 Gy. The delivereddose distribution from all the beams produced a P + value of 77.0% for D ITV = 93.2 Gy , σ D /D = 19.0% and D ITV of 83.5 Gy. Discussion and Conclusions: Whereas the physical comparison of dose distributions can assess the geometric accuracy of delivery, it does not reflect the clinical impact of any measured dose discrepancies. With highly conformal IMRT, the accuracy of the patient setup and treatmentdelivery, are critical for the success of the treatment. A method is proposed to evaluate the precision of the delivered plan based on changes in complication and control rates as they relate to uncertainties in dosedelivery.

Purpose: Presently, the radiobiological parameters of the different tumours and normal tissues are typically not taken into account during dose prescription and optimization of a treatment plan. In this study, to investigate a more comprehensive treatment plan evaluation, the biologically effective uniform dose (D) is applied together with the complication‐free tumour control probability (P +). Material and Methods: Three different cancer types at different anatomical sites were investigated: head & neck, lung and prostate cancers. For each cancer type, a linac MLC‐based step‐and‐shoot IMRT plan and a Helical Tomotherapy plan were developed. By using D as the common prescription point of the treatment plans and plotting the tissue response probabilities vs. D for a range of prescription doses, a number of plan trials can be compared based on radiobiological measures. Results: The applied plan evaluation method shows that in the head & neck cancer case the HT treatment gives better results than the MLC‐based IMRT (P + of 62.2% and 46.0%, D to the internal target volume (ITV) of 72.3Gy and 70.7Gy, respectively). In the lungcancer and prostate cancer cases, the MLC‐based IMRT plans are better. For the lungcancer case, the HT and MLC‐based IMRT plans give a P + of 66.9% and 72.9%, D to the ITV of 64.0Gy and 66.9Gy, respectively. Similarly, for the prostate cancer case, the two radiation modalities give a P + of 68.7% and 72.2%, D to the ITV of 86.0Gy and 85.9Gy, respectively. Discussion and Conclusions: Both MLC based‐IMRT and HT can encompass the often large ITV required while they minimize the volume of the organs at risk receiving high dose. There may exist clinical cases, which may look dosimetrically similar but in radiobiological terms may be quite different. In such situations, traditional dose based evaluation tools can be complemented by the use of P + − D diagrams to compare treatment plans.

Biological treatment optimization aim at improving radiation therapy by accounting for the radiobiological tumour and normal tissues response properties when optimizing the dose delivery. Generally traditional methods, using only dosimetrical measures, disregard the nonlinear radiation response of different tumours and normal tissues. The accumulated knowledge on tissue response to radiation, in the form of more accurate dose response relations, cell survival models and their associated biological parameters, alongside with the tools for biological treatment plan optimization, has allowed the present investigation on the potential merits of biologically based treatment optimization in radiation therapy.With a more widespread implementation of intensity modulated radiation therapy in the clinic, there is an increasing demand for faster and safer treatment delivery techniques. In this thesis biological treatment plan optimization, using the probability to achieve complication free tumour control as the quantifier for treatment outcome, was applied to radiation therapy of early breast cancer and advanced cervix cancer. It is shown that very conformal dose distributions can generally be produced with 3 or 4 optimally orientated coplanar intensity modulated beams, without having clinically significant losses in treatment outcome from the optimal dose distribution.By using exhaustive search methods, the optimal coplanar beam directions for intensity modulated photon beams for early breast cancer and the optimal non-coplanar directions for an advanced cervix cancer were investigated. Although time consuming, exhaustive search methods have the advantage of revealing most features involving interactions between a small number of beams and how this may influence the treatment outcome. Thus phase spaces may serve as a general database for selecting an almost optimal treatment configuration for similar patients. Previous knowledge acquired with physically optimized uniform beam radiation therapy may not apply when intensity modulated biological optimization is used. Thus unconventional treatment directions were sometimes found.

Purpose: To describe software for biological optimization of fractionated IMRT where the fluence profiles are not restricted to be identical for all fractions and to investigate the impact of fractionated time-dependent response functions on the optimization result. Method and Materials: If the fluence profiles of all beams in every fraction are optimized the number of variables is proportional to the number of fractions. Each new fraction consumes memory and slows down the optimization. In order to reduce the number of variables similar fractions are assigned to the same fraction group. The same fluence profile is delivered for every fraction in a fraction group. To test the method the Poisson-LQ model is extended with a time-dependent bi-exponential repair model. Results: In all tests the NTCP was minimized while the TCP was kept constant. If the time between consecutive fractions is long enough to cause complete repair there is not much gain in optimizing several fraction groups. In the case of incomplete repair, the NTCP was reduced by assigning Monday morning and Friday afternoon to a second fraction group. Adding more fraction groups did not improve the response significantly. Conclusion: The use of fraction groups enables an efficient implementation of IMRT-optimization of a fractionated treatment and makes it possible to study time-dependent biological models. In the case of Poisson-LQ with repair, two fraction groups can improve the biological response. This is only true in the case of incomplete repair and the impact of the fractionation depends on the repair half times. Conflict of Interest: Some of the authors are employees and some are stock owners of the submitting company.

Radiotherapeutic computed tomography is a powerful technique to generate anatomical transversal tomograms of the patient in treatment position by using the therapy beam from the treatment unit. For this purpose the treatment unit has to be equipped with a detector array that can detect the beam transmitted through the patient and a computer that analyzes the data and performs the back projection. When the treatment unit uses scanned elementary photon beams, the only practical technique available for generating high quality high energy photon beams, the operation principle and, to some extent, the image quality is similar to that of a 3rd generation CT-scanner. The optimum choice of detection geometry and type of radiation detectors for radiotherapeutic computed tomography particularly at high photon energies are discussed indicating the merits of BGO (bismuthgermanate) or CWO (cadmiumtungstate) photo diod arrays. The first tomographic images of a thorax phantom at an acceleration potential of 50 MV using such detectors are presented. The image contrast is similar to that for 300 kV X rays mainly because the considerable influence of pair production at 50 MV. Line spread and modulation transfer functions are presented indicating a resolution of the order of two millimeters using a crystal thickness of 5 mm. The advantages with radiotherapeutic computed tomography, beside forming a new general communication channel between different diagnostic techniques, dose planning, and radiation delivery, are the elimination of position errors and the provision of exact attenuation data for dose planning.

In order to fully utilize the dose distributional advantages of pions, protons and heavy ions it is important to cover the target volume as well as possible by Bragg peaks and avoid irradiating surrounding organs at risk. The most general way to achieve this goal is by modulation of the range of the beam so that its Bragg peak falls exclusively in the target volume. This could only be achieved using a threedimensional scanning technique where an elementary pencil beam is scanned not only transverse to the central axis of the beam, but also along the longitudinal or depth axis which is approximately parallel to the central axis (cf. Fig. 1). The transverse scanning could be performed by an electromagnetic or mechanical scanning system whereas the longitudinal scanning could be done using variable energy extraction from the accelerator. Alternatively a variable beam energy absorber could be used in the treat

Traditionally, the shaping of non-uniform dose distributions has been performed by using wedges or compensating filters. The advent of high resolution multileaf collimators may largely eliminate the need for material attenuators for modification of the beam. This is achieved by a new technique for the shaping of arbitrary dose distributions by dynamic motion of the collimator leaves. By employing narrow elementary slit beams that correspond to the smallest possible opening of the multileaf collimator, the optimal density of such slit beams, i.e. opening density, can be determined automatically using a newly developed inversion algorithm. The present method has two major advantages (1) internal structures in the field can be created, controlled solely by steering the collimator leaves, (2) the opening density determined by the algorithm never gives rise to underdosage: this is important from a radiobiological point of view.