Informatics and medicine--from molecules to populations.

OBJECTIVES: To clarify challenges and research topics for informatics in health and to describe new approaches for interdisciplinary collaboration and education. METHODS: Research challenges and possible solutions were elaborated by scientists of two universities using an interdisciplinary approach, in a series of meetings over several months. RESULTS AND CONCLUSION: In order to translate scientific results from bench to bedside and further into an evidence-based and efficient health system, intensive collaboration is needed between experts from medicine, biology, informatics, engineering, public health, as well as social and economic sciences. Research challenges can be attributed to four areas: bioinformatics and systems biology, biomedical engineering and informatics, health informatics and individual healthcare, and public health informatics. In order to bridge existing gaps between different disciplines and cultures, we suggest focusing on interdisciplinary education, taking an integrative approach and starting interdisciplinary practice at early stages of education.

Current status of medical technology.

BACKGROUND: Medical Technology (MT) provides innovative instrumentation and methods designed for the purpose of improving prevention, diagnostics, therapy and rehabilitation. MT rooting in science, engineering and the biosciences is characterized by its inter- and transdisciplinarity. METHOD: The current status of MT is described emphasizing the five aspects: (1) review of milestones, (2) the impact of MT on the health care system, (3) the economic significance of MT, (4) the financial resources dedicated to research and development in MT, and (5) the challenges for education and training in MT. The material used is a government issued survey on the situation of MT in Germany, data of health care authorities and congress reports from World Conference on Medical Physics and Biomedical Engineering 2005. RESULTS: The following fields of MT have emerged in recent years and will dominate future development: BioMEMOS, imaging technology, minimally invasive surgery, computer assisted diagnosis, therapy and treatment monitoring, e-health/telemedicine/ networking, and medical engineering for regenerative medicine. Development of MT is driven by the following facts, (1) early and individualized diagnosis enables better treatment, (2) MT enhances cost effectiveness in health care, (3) MT is an economic factor based on fast innovation cycles, a roughly 50% export share and a 6% growth rate in turnover during the last 10 years. A downward tendency of the domestic MT market is a challenge for appropriate measures in improving both the economic and the academic infrastructure, in particular by targeted actions to support research and education. CONCLUSION: The impact of MT on prevention, diagnostics, therapy and rehabilitation is significant and still increasing. Due to a wide spreading in all medical areas, the high innovation rate, and the potential to improve health care, MT is considered one of the key technologies even in the future.

Treatment simulation approaches for the estimation of the distributions of treatment quality parameters generated by geometrical uncertainties.

Geometric uncertainties arise during treatment planning and treatment and mean that dose-dependent parameters such as EUD are random variables with a patient specific probability distribution. Treatment planning with highly conformal treatment techniques such as intensity modulated radiation therapy requires new evaluation tools which allow us to estimate this influence of geometrical uncertainties on the probable treatment dose for a planned dose distribution. Monte Carlo simulations of treatment courses with recalculation of the dose according to the daily geometric errors are a gold standard for such an evaluation. Distribution histograms which show the relative frequency of a treatment quality parameter in the treatment simulations can be used to evaluate the potential risks and chances of a planned dose distribution. As treatment simulations with dose recalculation are very time consuming for sufficient statistical accuracy, it is proposed to do treatment simulations in the dose parameter space where the result is mainly determined by the systematic and random component of the geometrical uncertainties. Comparison of the parameter space simulation method with the gold standard for prostate cases and a head and neck case shows good agreement as long as the number of fractions is high enough and the influence of tissue inhomogeneities and surface curvature on the dose is small.

Adapting inverse planning to patient and organ geometrical variation: algorithm and implementation.

Image guided radiotherapy has the potential to improve both tumour control and normal tissue sparing by including temporal patient specific geometry information into the adaptive planning process. In this study we present a practical method of image guided adaptive inverse planning based on computed tomography (CT) and portal image feedback during the treatment course. The method is based on a general description of the radiotherapy optimization problem subject to dynamic geometrical variations of the patient/organs. We will demonstrate the feasibility of off-line image feedback into the inverse planning process with the example of three prostate cancer patients. CT and portal images acquired during the early course of the treatment are used to predict the geometrical variation distribution of a patient and to re-optimize the treatment plan accordingly. We will study the convergence of the optimization problem with respect to the number of image measurements and adaptive feedback loops.

Non-coplanar beam direction optimization for intensity-modulated radiotherapy.

An algorithm for the optimization of the direction of intensity-modulated beams is presented. Although the global optimum dose distribution cannot be predicted, usually a large number of equivalent beam configurations exists. This degeneracy facilitates beam direction optimization (BDO) through a number of possible approximations and because the target set of good beam configurations is very large. Usually, the target volume is accessible through a finite number of paths of little resistance, which are defined by the properties of the objective function and the global optimum dose distribution. Since these paths can be occupied by a finite number of beams, it is reasonable to assume that a minimum number of beams for a configuration that is degenerate to the global optimum exists. Efficiency of the BDO will be characterized by detecting this degeneracy threshold. Beam configurations are altered by adding and deleting beams. A fast exhaustive (up to 3500 non-coplanar orientations) search finds beam directions that improve a configuration. Redundant beams of a configuration can be identified by a fast criterion based on second-order derivative information of the objective function. This offers a fast means of iteratively substituting redundant beams from a configuration. Inferior stationary states can be evaded by adding more beams than the desired number to the current configuration, followed by the subsequent cancellation of superfluous beams. The significance of BDO is examined in a coplanar and a non-coplanar test case. The existence of a threshold number for the minimum configuration and its dependence on the complexity of the problem are shown. BDO outperforms manual configurations and equispaced coplanar beam arrangements in both example cases.

Potential and limitations of the automatic detection of fiducial markers using an amorphous silicon flat-panel imager.

Amorphous silicon electronic portal imaging devices (a-Si EPIDs) allow fast acquisition of high resolution portal images (PI). A visualization of organ movement for adaptive image-guided radiotherapy (IGRT) can be reached by implantation and automatic detection of fiducial markers. A method of automatic detection has been developed for fiducial spherical tungsten markers on PIs, acquired with an a-Si flat-panel imager. The detection method consists of a 2D Mexican hat filter (MHF), whose parameters are tuned to the particular marker signal. The high selectivity of this filter allows a reliable and precise detection of tungsten markers down to a diameter of 1.5 mm. The presented method allows fast, automatic and unsupervised detection of markers. Inevitably, the detection is hampered by image background (bone structures, etc) and noise. A detection success rate higher than 95% was reached, analysing PIs of patients with markers fixed on their skin. Furthermore, this approach to automatic marker detection can also be generalized to elliptic MHFs for the detection of cylindrical markers. The accuracy and detection probability of this method may allow accurate and fast online localization of the considered organ.

Estimation of a radiation time prolongation factor for intensity-modulated radiotherapy.

In general, the deposition of a given target dose requires a longer radiation time for intensity-modulated photon beams (IMBs) than for unmodulated beams. Hence, the routine use of intensity-modulated radiotherapy (IMRT) has repercussions both on the exposure of the patient to scatter and institutional radiation safety. A rule of thumb is presented to assess the maximum prolongation of radiation time for a case class in an idealized setting using static superimposed field segments. The method considers only the degree to which risk structures have to be blocked to meet specified dose restrictions.

On the degeneracy of the IMRT optimization problem.

One approach to the computation of photon IMRT treatment plans is the formulation of an optimization problem with an objective function that derives from an objective density. An investigation of the second-order properties of such an objective function in a neighborhood of the minimizer opens an intuitive access to many traits of this approach. A general finding is that only a small subset of the parameter space has nonzero curvature, while the objective function is entirely flat in a neighborhood of the minimizer in most directions. The dimension of the subspace of vanishing curvature serves as a measure for the degeneracy of the solution. This finding is important both for algorithm design and evaluation of the mathematical model of clinical intuition, expressed by the objective function. The structure of the subspace of great curvature is found to be imposed on the problem by conflicts between objectives of target and critical structures. These conflicts and their corresponding modes of resolution form a common trait between all reasonable treatment plans of a given case. The high degree of degeneracy makes the use of a conjugate gradient optimization algorithm particularly favorable since the number of iterations to convergence is equivalent to the number of different eigenvalues of the curvature tensor and is hence independent from the number of optimization parameters. A high level of degeneracy of the fluence profiles implies that it should be possible to stipulate further delivery-related conditions without causing severe deterioration of the dose distribution.

Tools for the analysis of dose optimization: II. Sensitivity analysis.

Dose optimization requires that the treatment goals be specified in a meaningful manner, but also that alterations to the specification lead to predictable changes in the resulting dose distribution. Within the framework of constrained optimization, it is possible to devise a tool that quantifies the impact on the objective of target volume coverage of any change to a dosimetric constraint of normal tissue or target dose homogeneity. This sensitivity analysis relies on properties of the Lagrange function that is associated with the constrained optimization problem, but does not depend on the method used to solve this problem. It is useful particularly in cases with multiple target volumes and critical normal structures, where constraints and objectives can interact in a non-intuitive manner.

Tools for the analysis of dose optimization: I. Effect-volume histogram.

With the advent of dose optimization algorithms, predominantly for intensity-modulated radiotherapy (IMRT), computer software has progressed beyond the point of being merely a tool at the hands of an expert and has become an active, independent mediator of the dosimetric conflicts between treatment goals and risks. To understand and control the internal decision finding as well as to provide means to influence it, a tool for the analysis of the dose distribution is presented which reveals the decision-making process performed by the algorithm. The internal trade-offs between partial volumes receiving high or low doses are driven by functions which attribute a weight to each volume element. The statistics of the distribution of these weights is cast into an effect-volume histogram (EVH) in analogy to dose-volume histograms. The analysis of the EVH reveals which traits of the optimum dose distribution result from the defined objectives, and which are a random consequence of under- or misspecification of treatment goals. The EVH can further assist in the process of finding suitable objectives and balancing conflicting objectives. If biologically inspired objectives are used, the EVH shows the distribution of local dose effect relative to the prescribed level.

Investigation of photon beam output factors for conformal radiation therapy--Monte Carlo simulations and measurements.

The purpose of this study was to investigate beam output factors (OFs) for conformal radiation therapy and to compare the OFs measured with different detectors with those simulated with Monte Carlo methods. Four different detectors (diode, diamond, pinpoint and ionization chamber) were used to measure photon beam OFs in a water phantom at a depth of 10 cm with a source-surface distance (SSD) of 100 cm. Square fields with widths ranging from 1 cm to 15 cm were observed; the OF for the different field sizes was normalized to that measured at a 5 cm x 5 cm field size at a depth of 10 cm. The BEAM/EGS4 program was used to simulate the exact geometry of a 6 MV photon beam generated by the linear accelerator, and the DOSXYZ-code was implemented to calculate the OFs for all field sizes. Two resolutions (0.1 cm and 0.5 cm voxel size) were chosen here. In addition, to model the detector four kinds of material, water, air, graphite or silicon, were placed in the corresponding voxels. Profiles and depth dose distributions resulting from the simulation show good agreement with the measurements. Deviations of less than 2% can be observed. The OF measured with different detectors in water vary by more than 35% for 1 cm x 1 cm fields. This result can also be found for the simulated OF with different voxel sizes and materials. For field sizes of at least 2 cm x 2 cm the deviations between all measurements and simulations are below 3%. This demonstrates that very small fields have a bad effect on dosimetric accuracy and precision. Finally, Monte Carlo methods can be significant in determining the OF for small fields.

[Verification of a fast Monte Carlo dose calculation algorithm by EGSnrc using the statistical separation method]. / Verifikation eines schnellen Monte-Carlo-Dosisberechnungsverfahrens durch EGSnrc anhand der statistischen Separationsmethode.

The recently developed XVMC code, a fast Monte Carlo (MC) algorithm to calculate the dose of photon and electron beams in treatment planning, was compared to EGSnrc, an enhanced version of the well-known EGS4 system. Because of the numerous and accurate verification measurements, this system can be considered as golden standard. The comparison was performed using phantoms consisting of water, lung tissue and bone. Dose profile and difference distributions showed good agreement within the accuracy requirements. Because deviations between the results of two MC algorithms are caused by systematic errors and statistical fluctuations, a separation method was used to quantify the systematic discrepancies. Using this method, it could be shown that there was good agreement between the three dimensional dose distributions, calculated with XVMC and EGSnrc, if maximum systematic deviation of 2% are accepted.

[Monte Carlo simulation of a dynamic multileaf collimator:implementation and applications]. / Monte-Carlo-Simulation von Multileafkollimatoren mit gekrümmten Lamellenenden.

A model for the simulation of the accelerator heads of two identical linear accelerators was designed at the University Hospital of Tübingen, using the BEAM program developed at the National Research Council of Canada. Both linear accelerators are equipped with multileaf collimators (MLCs) and backup jaws (y-direction) with curved leaf-ends. The accelerator models were divided into two parts. The first part consisted of target, primary collimator, flattening filter, monitor chamber, and mirror. After the Monte Carlo simulation of these parts, the phase-space characteristics below the mirror were stored in a file and used as source for the second part of the accelerator head (jaw, MLC). The electron source was assumed to deliver a gaussian energy spectrum, with parallel direction to the beam axis. With this electron source, there was good agreement between the measured and simulated depth dose curves in water, with difference < 2%. A new module was created for the BEAM program to simulate backup jaws, while the standard MLCQ module from BEAM was used to simulate a MLC with curved leaf-ends. As a result, MLCs and backup jaws with curved leaf-ends make the shoulder of the y-profile higher than the straight-end MLCs.

[Foundations of the Monte Carlo method for dose calculation in radiotherapy]. / Grundlagen der Monte-Carlo-Methode für die Dosisberechnung in der Strahlentherapie.

Monte Carlo (MC) methods applied in dose calculation are based on fundamental principles of radiation interaction with matter. In contrast to other methods, the accuracy of dose calculation achievable with MC depends only on the determination of the beam quality and the interaction coefficients. Using MC techniques it is possible to predict the dose for clinical photon and electron beams with an accuracy of > +/- 2%. Especially for inhomogeneous regions like head, neck, and lung, the MC technique can significantly improve the accuracy compared to conventional algorithms. Therefore, in the present paper the basic features of the MC method are reviewed in the context of treatment planning in radiation therapy. The main shortcoming in the past, i.e., that MC algorithms are too slow to be acceptable for clinical purposes, could be solved by using faster computers and by introducing new variance reduction (VR) techniques. These techniques decrease the statistical fluctuations without increasing the number of particle histories. Therefore, MC calculation times in the order of a few minutes are possible. A brief overview of VR methods is provided.

Compensators for IMRT--an investigation in quality assurance.

Intensity modulated radiotherapy (IMRT) allows dose distributions which adequately consider organs at risk (OAR) and dose homogeneity to the target volume. This is practically reached by conforming the beam profiles to the shape of the planning target volume (PTV), by shaping the fluence with multileaf collimators (MLC) or compensators. Though compensator production is time consuming and seems less convenient than the use of MLC, compensators offer much easier quality assurance. In this study the effects of certain simplifications of compensator production were studied. Compensators were produced and ionization chamber measurements in a water phantom and film measurements in a solid phantom were performed to verify the compensators. The results of the measurements were compared to the fluence distributions given by the planning system. The measurements were meant to show how realistic the investigated simplifications were, and to reveal a suitable and reliable testing method for compensators. Monte-Carlo calculations employing the EGS 4 Code were further performed to support the measurements.

Film dosimetric verification of the Voxel Monte Carlo (VMC) algorithm with electron beam dose distributions.

Monte Carlo (MC) methods have the potential to predict radiation-therapy doses more accurately than any conventional technique, but normal MC simulations are very time consuming. Therefore, a fast MC code (Voxel Monte Carlo; VMC) was developed especially for radiation therapy purposes and experiments with the comparable precision were performed to demonstrate its accuracy. In the present study the dose distributions measured with film dosimetry in a cylindrical phantom were compared with calculations derived by VMC. The phantom consisted of 18 circular shaped PMMA slabs with a diameter of 20 cm and a thickness of approx. 1 cm. The films were placed between the slabs, and the whole phantom was irradiated with electron beams of different energies (6 MeV, 10 MeV, 18 MeV). The measured optical density distributions were then converted into dose distributions using characteristic curves of the film. Taking into account experimental uncertainties and statistical calculation fluctuations, agreement was found between measurements and VMC simulations with a maximal deviation of 3 mm on isodose curves for 18 MeV.

A variable fluence step clustering and segmentation algorithm for step and shoot IMRT.

A step and shoot sequencer was developed that can be integrated into an IMRT optimization algorithm. The method uses non-uniform fluence steps and is adopted to the constraints of an MLC. It consists of a clustering, a smoothing and a segmentation routine. The performance of the algorithm is demonstrated for eight mathematical profiles of differing complexity and two optimized profiles of a clinical prostate case. The results in terms of stability, flexibility, speed and conformity fulfil the criteria for the integration into the optimization concept. The performance of the clustering routine is compared with another previously published one (Bortfeld et al 1994 Int. J. Radiat. Oncol. Biol. Ph.vs. 28 723-30) and yields slightly better results in terms of mean and maximum deviation between the optimized and the clustered protile. We discuss the specific attributes of the algorithm concerning its integration into the optimization concept.

Intensity modulated irradiation of a thorax phantom: comparisons between measurements, Monte Carlo calculations and pencil beam calculations.

The present study investigates the application of compensators for the intensity modulated irradiation of a thorax phantom. Measurements are compared with Monte Carlo and standard pencil beam algorithm dose calculations. Compensators were manufactured to produce the intensity profiles that were generated from the scientific version of the KonRad IMRT treatment-planning system for a given treatment plan. The comparison of dose distributions calculated with a pencil beam algorithm, with the Monte Carlo code EGS4 and with measurements is presented. By measurements in a water phantom it is demonstrated that the method used to manufacture the compensators reproduces the intensity profiles in a suitable manner. Monte Carlo simulations in a water phantom show that the accelerator head model used for simulations is sufficient. No significant overestimations of dose values inside the target volume by the pencil beam algorithm are found in the thorax phantom. An overestimation of dose values in lung by the pencil beam algorithm is also not found. Expected dose calculation errors of the pencil beam algorithm are suppressed, because the dose to the low density region lung is reduced by the use of a non-coplanar beam arrangement and by intensity modulation.