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Thomas Bortfeld

Publications and source records attributed to Thomas Bortfeld.

14 recordsLinked to original sources

Effects of motion on the total dose distribution.

The success of highly target-conformal treatments such as intensity-modulated radiotherapy (IMRT) can be compromised by motion of the inner organs and random patient setup errors. This article gives an overview of different studies that looked at the effect of organ motion and setup errors on radiation therapy dose distributions, both from a qualitative and quantitative point of view. The qualitative findings are generally applicable (ie, case independent). It is found that motion always leads to a blurring of the dose distribution. In addition, there are so-called interplay effects if the treatment delivery involves moving parts, such as multileaf collimators. After a large number of fractions, the interplay effects lead to a normal distribution of the dose value around the average blurred value. Thirdly, organ motion can also cause a spatial deformation of the dose distribution. Quantitatively it has been found that both deformation and interplay effects appear to be small (in the order of 1%-2%) in many typical clinical cases. The dominant effect is the blurring of the dose distribution, which is, in essence, independent of the treatment technique, and is not more pronounced in IMRT than in more conventional treatment techniques. However, because in IMRT there is a tendency to reduce or compromise target margins, the blurring has potentially a bigger effect on the outcome of IMRT, unless precision dose delivery techniques (such as gated or motion-synchronized beams) are used. An alternative to the use of margins is to do the planning based on blurred dose distributions.

Humans↗

Monitor unit calculations for range-modulated spread-out Bragg peak fields.

We derive, from first principles, a model to predict the output factors for spread-out Bragg peak proton fields (SOBP). The model is based on the simple observation that the output factor is the ratio of SOBP plateau dose to the dose measured in the ionization reference chamber. The latter, in turn, equates to the entrance dose of the SOBP corrected for inverse square. We use a theoretical derivation of this ratio to establish the relationship between the output factor and the distal range and modulation width of the SOBP. In addition, the theoretical derivation reduces the dependence on the distal range and modulation width into a single factor r = (R - M)/M. We compare the theoretical derivation against measurements obtained at the Northeast Proton Therapy Facility for output factors for clinical fields. The agreement between measurements and prediction is 2.9%.

Calibration↗

An experimental investigation on intra-fractional organ motion effects in lung IMRT treatments.

Respiration-induced tumour motion can potentially compromise the use of intensity-modulated radiotherapy (IMRT) as a dose escalation tool for lung tumour treatment. We have experimentally investigated the intra-fractional organ motion effects in lung IMRT treatments delivered by multi-leaf collimator (MLC). An in-house made motor-driven platform, which moves sinusoidally with an amplitude of 1 cm and a period of 4 s, was used to mimic tumour motion. Tumour motion was simulated along cranial-caudal direction while MLC leaves moved across the patient from left to right, as in most clinical cases. The dose to a point near the centre of the tumour mass was measured according to geometric and dosimetric parameters from two five-field lung IMRT plans. For each field, measurement was done for two dose rates (300 and 500 MU min(-1)), three MLC delivery modes (sliding window, step-and-shoot with 10 and 20 intensity levels) and eight equally spaced starting phases of tumour motion. The dose to the measurement point delivered from all five fields was derived for both a single fraction and 30 fractions by randomly sampling from measured dose values of each field at different initial phases. It was found that the mean dose to a moving tumour differs slightly (<2-3%) from that to a static tumour. The variation in breathing phase at the start of dose delivery results in a maximum variation around the mean dose of greater than 30% for one field. The full width at half maximum for the probability distribution of the point dose is up to 8% for all five fields in a single fraction, but less than 1-2% after 30 fractions. In general, lower dose rate can reduce the motion-caused dose variation and therefore might be preferable for lung IMRT when no motion mitigation techniques are used. From the two IMRT cases we studied where tumour motion is perpendicular to MLC leaf motion, the dose variation was found to be insensitive to the MLC delivery mode.

Biophysical Phenomena↗

Beam delivery sequencing for intensity modulated proton therapy.

Methods of beam fluence sequencing for intensity modulated proton therapy (IMPT) using the beam scanning technique are presented. Proton beam weight maps optimized by the treatment planning system (TPS) for a discrete set of regularly spaced narrow pencil beams were interpolated, using convolution with various kernel functions, to simulate continuous beam scanning on a raster pattern. Expected dose distributions at the proton Bragg peak range were then calculated and compared to those planned by the TPS, to evaluate the discrepancy due to the differences between the treatment planning and delivery approaches. An iteratively optimized adjustment was applied to the simulated continuous beam fluence profiles to reduce such discrepancy. Calculation showed that by accounting for the specifics of the scanning method, the planned dose distribution on the target may be reproduced to within 0.5% of the maximum target dose, given the pencil beam spacing smaller or equal to the beam sigma is used for treatment planning. For the beam weight maps generated using a spot spacing larger than sigma, a substantial reduction in the calculated dose discrepancy may be attained by applying an iterative adjustment of fluence profiles obtained by interpolating over artificially expanded set of beam spots.

Biophysical Phenomena↗

Development and clinical application of a fast superposition algorithm in radiation therapy.

BACKGROUND AND PURPOSE: Dose calculation algorithms play a central role for the optimization and verification of treatment plans in radiation therapy. Complex treatment techniques like intensity modulated radiotherapy (IMRT) require accurate and fast dose algorithms especially for clinical cases which involve severe tissue inhomogeneities. For these cases the standard dose engine in current treatment planning systems--the convolution of photon pencil beams--usually fails to predict the dose with the required accuracy. The role of more accurate but time consuming dose calculations like superposition algorithms or Monte Carlo simulations in clinical practice is under investigation at several therapy centers. PATIENTS AND METHODS: The paper presents the design, implementation and the first application of a superposition algorithm in a clinical setting at the German Cancer Research Center (DKFZ). It first describes in detail how the superposition algorithm is adapted to the dose delivery system at DKFZ in terms of standard dosimetric data. Then details of the implementation of the algorithm are given with a focus on various methods for the reduction of dose computation times. Next, the algorithm is evaluated in various experiments with dosimetric phantoms. These studies are employed for the development of time efficient sampling strategies of the elemental dose kernels. Finally, the algorithm is applied to dose calculations of clinical cases with tumors adjacent to lung tissue. RESULTS: Severe differences in dose coverage of the tumors and dose burden of the surrounding tissues in comparison to standard pencil beam calculations are observed. A standard 4-7 beam plan in a convenient dose grid (approximately 3 mm in each direction) is calculated in about 30 min on a Pentium 4 (1.9 GHz) applying the superposition algorithm described here.

Algorithms↗

From physical dose constraints to equivalent uniform dose constraints in inverse radiotherapy planning.

Optimization algorithms in inverse radiotherapy planning need information about the desired dose distribution. Usually the planner defines physical dose constraints for each structure of the treatment plan, either in form of minimum and maximum doses or as dose-volume constraints. The concept of equivalent uniform dose (EUD) was designed to describe dose distributions with a higher clinical relevance. In this paper, we present a method to consider the EUD as an optimization constraint by using the method of projections onto convex sets (POCS). In each iteration of the optimization loop, for the actual dose distribution of an organ that violates an EUD constraint a new dose distribution is calculated that satisfies the EUD constraint, leading to voxel-based physical dose constraints. The new dose distribution is found by projecting the current one onto the convex set of all dose distributions fulfilling the EUD constraint. The algorithm is easy to integrate into existing inverse planning systems, and it allows the planner to choose between physical and EUD constraints separately for each structure. A clinical case of a head and neck tumor is optimized using three different sets of constraints: physical constraints for all structures, physical constraints for the target and EUD constraints for the organs at risk, and EUD constraints for all structures. The results show that the POCS method converges stable and given EUD constraints are reached closely.

Algorithms↗

Optimization of beam parameters and treatment planning for intensity modulated proton therapy.

One of the objectives of the ongoing research and development work at the Northeast Proton Therapy Center (NPTC) in Boston is to perform optimized intensity modulated proton therapy (IMPT) treatments. Such treatments may be delivered by magnetically scanning a narrow proton pencil beam across the target volume, while both the scanning speed and the intensity of the beam are modulated. Localization of the proton dose in space allows one to yield dose distributions that are highly conformal to the target volume, thus minimizing the dose delivered to the surrounding healthy tissue. The aim of the current research is to determine technically optimal and clinically relevant specifications for the scanned beam delivery system, which is being developed in collaboration with Ion Beam Applications (IBA); and to create a link between the treatment planning and the beam delivery. IMPT treatment planning is performed for patient cases treated at the NPTC, with KonRad Pro software developed at the German Cancer Research Center (DKFZ). For the IMPT delivery, the proton intensity maps, optimized for discrete pencil beam spots, need to be translated into continuous scanning patterns. At the same time it is necessary to minimize the discrepancy between the planned and delivered doses which may result from such conversion, as well as from the technical limitations of the delivery system. Possibilities have been investigated for improving the proton dose conformity by optimizing the beam and scanning nozzle parameters, and by taking the specifics and limitations of the system into account in the treatment planning stage.

Chordoma↗

When should systematic patient positioning errors in radiotherapy be corrected?

One way to reduce patient set-up errors in radiotherapy is to measure the position during the first N treatment fractions, and to do an unconditional correction of the set-up position once at the (N + 1)th fraction. This strategy is known as the 'no action level' protocol. The question is when to do the correction, i.e. what is the optimum value of N? We determine N by minimizing the expectation value of the total quadratic set-up error taken over all fractions. A central assumption that we make is that there is no time trend in the patient set-up. The result is a simple formula for the value of N, which is proportional to the square root of the total number of fractions, and to the ratio of the execution (delivery) error and preparation error. We also provide a formula for cases where the measurement error is not negligible. For typical cases the optimum value is N = 4. Because the optimum is shallow, the exact choice of N is uncritical.

Humans↗

Effects of intra-fraction motion on IMRT dose delivery: statistical analysis and simulation.

There has been some concern that organ motion, especially intra-fraction organ motion due to breathing, can negate the potential merit of intensity-modulated radiotherapy (IMRT). We wanted to find out whether this concern is justified. Specifically, we wanted to investigate whether IMRT delivery techniques with moving parts, e.g., with a multileaf collimator (MLC), are particularly sensitive to organ motion due to the interplay between organ motion and leaf motion. We also wanted to know if, and by how much, fractionation of the treatment can reduce the effects. We performed a statistical analysis and calculated the expected dose values and dose variances for volume elements of organs that move during the delivery of the IMRT. We looked at the overall influence of organ motion during the course of a fractionated treatment. A linear-quadratic model was used to consider fractionation effects. Furthermore, we developed software to simulate motion effects for IMRT delivery with an MLC, with compensators, and with a scanning beam. For the simulation we assumed a sinusoidal motion in an isocentric plane. We found that the expected dose value is independent of the treatment technique. It is just a weighted average over the path of motion of the dose distribution without motion. If the treatment is delivered in several fractions, the distribution of the dose around the expected value is close to a Gaussian. For a typical treatment with 30 fractions, the standard deviation is generally within 1% of the expected value for MLC delivery if one assumes a typical motion amplitude of 5 mm (1 cm peak to peak). The standard deviation is generally even smaller for the compensator but bigger for scanning beam delivery. For the latter it can be reduced through multiple deliveries ('paintings') of the same field. In conclusion, the main effect of organ motion in IMRT is an averaging of the dose distribution without motion over the path of the motion. This is the same as for treatments with conventional beams. Additional effects that are specific to the IMRT delivery technique appear to be relatively small, except for the scanning beam.

Computer Simulation↗

Inverse treatment planning and stereotactic intensity-modulated radiation therapy (IMRT) of the tumor and lymph node levels for nasopharyngeal carcinomas. Description of treatment technique, plan comparison, and case study.

PURPOSE: Inverse treatment planning and intensity-modulated radiation therapy (IMRT) promise advantages in the treatment of tumors of the head and neck region. Currently published studies use IMRT only in the treatment of the primary tumor. In these studies, the lymph nodes of the neck were treated using conventional techniques. The feasibility of an IMRT technique which allows treatment of the complete target volume, including the primary tumor and lymph nodes, without a beam split is described. PATIENT AND METHOD: For inverse treatment planning, the KonRad planning system was used. The primary as well as the secondary PTV (bilateral lymph node levels) were treated with one intensity-modulated primary plan. To increase the dose in the primary PTV and suspicious lymph nodes, an intensity-modulated boost plan was performed. The "step and shoot" IMRT technique was used. A plan comparison between the described IMRT approach and an IMRT approach using a split-beam technique was performed focusing on the treatment time. A patient with a carcinoma of the nasopharynx was treated with curative intent by a combined radiochemotherapy. RESULTS: The median total dose to the primary PTV was 70 Gy, to suspicious lymph nodes > or = 66.0 Gy, and to the secondary PTV 52 Gy. The defined maximum doses to the organs at risk were not exceeded, and the median dose to the protected parotid gland amounted to 21 Gy. Comparison of the treatment time between both IMRT approaches revealed only a slightly shorter treatment time (1-3 min) for the split-beam IMRT technique without considering the remaining conventional treatment parts of the split-beam IMRT technique. The patient achieved a complete response, and 18 months after treatment no signs of recurrent disease are visible. CONCLUSIONS: IMRT allows the treatment of the target volumes with high doses combined with an excellent sparing of the organs at risk. The IMRT approach presented here makes the treatment of the whole target volume with a single-beam arrangement feasible and does not increase the treatment time compared to a split-beam IMRT technique. Treatment time was comparable to a conventional three-field technique combined with electrons. This IMRT technique can prevent over- or underdosage at field matchlines in the head and neck region and, moreover, is able to spare parotid glands and therefore better avoid xerostomia compared to conventional techniques.

Algorithms↗

Report of a study on IMRT planning strategies for ethmoid sinus cancer.

AIM: This communication reviews the planning strategies and dose statistics of nine IMRT plans generated for a complex head and neck case. PATIENT AND METHOD: An ethmoid sinus cancer case was sent as an IMRT planning task to all participants of the ESTRO course on "IMRT and Other Conformal Techniques in Practice", held in Amsterdam in June 2001. RESULTS: Nine IMRT plans were generated for the case, the majority of the plans generated with commercial planning systems. The number of beam incidences ranged between four and eleven, while five of the nine beam setups were coplanar. The planning target volume dose homogeneity was inversely correlated with the degree of sparing of the surrounding organs at risk. CONCLUSION: IMRT strategies for complex head and neck cases, such as ethmoid sinus cancer, can be strikingly different in various aspects, such as beam setup, total number of segments, PTV dose coverage and dose statistics for organs at risks.

Adenocarcinoma↗

Characterization of dose distributions through the max and mean dose concept.

A new approach for the determination of the equivalent uniform dose (EUD) for inhomogeneously irradiated normal organs is developed and tested. The EUD is calculated as a linear combination of the maximum and the mean dose: EUD = alphaDmax + (1 - alpha)D. We call this the max & mean model. The values of alpha are determined by a fit to the Emami tables for complication levels of 5% and 50%. The predictions of the max & mean model are compared with the Emami tables for different treatment volume fractions. The quality of the fit is also compared with the well-known power-law EUD model. The max & mean model makes it possible to make useful predictions of the EUD for organs having an organization anywhere between serial and parallel. The model can be fitted to the Emami tables within the same error range as the widely used power-law model (about 10%) and can be integrated into linear multicriteria optimization algorithms for planning of intensity-modulated radiotherapy.

Dose Fractionation, Radiation↗

Parker weights revisited.

The short-scan case in fan-beam computed tomography requires the introduction of a weighting function to handle redundant data. Parker introduced such a weighting function for a scan over pi plus the opening angle of the fan. In this article we derive a general class of weighting functions for arbitrary scan angles between pi plus fan angle and 2pi (over-scan). These weighting functions lead to mathematically exact reconstructions in the continuous case. Parker weights are a special case of a weighting function that belongs to this class. It will be shown that Parker weights are not generally the best choice in terms of noise reduction, especially when there is considerable over-scan. We derive a new weighting function that has a value of 0.5 for most of the redundant data and is smooth at the boundaries.

Algorithms↗

Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices.

In inverse planning for intensity-modulated radiotherapy, the dose calculation is a crucial element limiting both the maximum achievable plan quality and the speed of the optimization process. One way to integrate accurate dose calculation algorithms into inverse planning is to precalculate the dose contribution of each beam element to each voxel for unit fluence. These precalculated values are stored in a big dose calculation matrix. Then the dose calculation during the iterative optimization process consists merely of matrix look-up and multiplication with the actual fluence values. However, because the dose calculation matrix can become very large, this ansatz requires a lot of computer memory and is still very time consuming, making it not practical for clinical routine without further modifications. In this work we present a new method to significantly reduce the number of entries in the dose calculation matrix. The method utilizes the fact that a photon pencil beam has a rapid radial dose falloff, and has very small dose values for the most part. In this low-dose part of the pencil beam, the dose contribution to a voxel is only integrated into the dose calculation matrix with a certain probability. Normalization with the reciprocal of this probability preserves the total energy, even though many matrix elements are omitted. Three probability distributions were tested to find the most accurate one for a given memory size. The sampling method is compared with the use of a fully filled matrix and with the well-known method of just cutting off the pencil beam at a certain lateral distance. A clinical example of a head and neck case is presented. It turns out that a sampled dose calculation matrix with only 1/3 of the entries of the fully filled matrix does not sacrifice the quality of the resulting plans, whereby the cutoff method results in a suboptimal treatment plan.

Algorithms↗