The sharp dose gradients which are possible in intensity modulated proton therapy (IMPT) not only offer the possibility of generating excellent target coverage while sparing neighbouring organs at risk, but can also lead to treatment plans which are very sensitive to uncertainties in treatment variables such as the range of individual Bragg peaks. We developed a method to account for uncertainties of treatment variables in the optimization based on a worst case dose distribution. The worst case dose distribution is calculated using several possible realizations of the uncertainties. This information is used by the objective function of the inverse treatment planning system to generate treatment plans which are acceptable under all considered realizations of the uncertainties. The worst case optimization method was implemented in our in-house treatment planning software KonRad in order to demonstrate the usefulness of this approach for clinical cases. In this paper, we investigated range uncertainties, setup uncertainties and a combination of both uncertainties. Using our method the sensitivity of the resulting treatment plans to these uncertainties is considerably reduced.

BackgroundRoots are vital to plants for soil exploration and uptake of water and nutrients. Root performance is critical for growth and yield of plants, in particular when resources are limited. Since roots develop in strong interaction with the soil matrix, tools are required that can visualize and quantify root growth in opaque soil at best in 3D. Two modalities that are suited for such investigations are X-ray Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Due to the different physical principles they are based on, these modalities have their specific potentials and challenges for root phenotyping. We compared the two methods by imaging the same root systems grown in 3 different pot sizes with inner diameters of 34 mm, 56 mm or 81 mm.ResultsBoth methods successfully visualized roots of two weeks old bean plants in all three pot sizes. Similar root images and almost the same root length were obtained for roots grown in the small pot, while more root details showed up in the CT images compared to MRI. For the medium sized pot, MRI showed more roots and higher root lengths whereas at some spots thin roots were only found by CT and the high water content apparently affected CT more than MRI. For the large pot, MRI detected much more roots including some laterals than CT.ConclusionsBoth techniques performed equally well for pots with small diameters which are best suited to monitor root development of seedlings. To investigate specific root details or finely graduated root diameters of thin roots, CT was advantageous as it provided the higher spatial resolution. For larger pot diameters, MRI delivered higher fractions of the root systems than CT, most likely because of the strong root-to-soil contrast achievable by MRI. Since complementary information can be gathered with CT and MRI, a combination of the two modalities could open a whole range of additional possibilities like analysis of root system traits in different soil structures or under varying soil moisture.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-015-0060-z) contains supplementary material, which is available to authorized users.

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A new open-source software project is presented, JEMRIS, the Jü lich Extensible MRI Simulator, which provides an MRI sequence development and simulation environment for the MRI community. The development was driven by the desire to achieve generality of simulated three-dimensional MRI experiments reflecting modern MRI systems hardware. The accompanying computational burden is overcome by means of parallel computing. Many aspects are covered that have not hitherto been simultaneously investigated in general MRI simulations such as parallel transmit and receive, important offresonance effects, nonlinear gradients, and arbitrary spatiotemporal parameter variations at different levels. The latter can be used to simulate various types of motion, for instance. The JEMRIS user interface is very simple to use, but nevertheless it presents few limitations. MRI sequences with arbitrary waveforms and complex interdependent modules are modeled in a graphical user interface-based environment requiring no further programming. This manuscript describes the concepts, methods, and performance of the software. Numerical simulation of MRI experiments, based on the Bloch equation, is an essential tool for a variety of different research directions. In the field of pulse sequence optimization, e.g., for artifact detection and elimination, simulations allow one to differentiate between effects arising principally from MRI physics and those due to hardware imperfections. Another prominent application is the design of specialized radiofrequency (RF) pulses. In general, the interpretation and validation of experimental results benefits from comparisons to simulated data. Many more applications possibly add to this list, not to forget that controlled numerical MRI experiments are also valuable for educational purposes.In its most general form, numerical simulation of an MRI experiment is a demanding task. This is due to the fact that a huge spin ensemble has to be simulated in order to obtain realistic results. To overcome this, several published approaches reduce the problem size in different ways. The most prominent method is to consider analytical solutions of the problem (1-3). In cases of simultaneous RF excitation and time-varying gradient fields, no general analytical solution exists and, thus, the important field of selective excitation cannot be studied with analytical approaches. In the past, numerical solutions have also been considered (4,5) but hardware and software architectures pertaining at that time limited simulations to small spin systems with reduced flexibility in setup and extensibility of the numerical experiments. Apart from the computational demand, the complexity of the MRI imaging sequence is also an obstacle. A multipurpose MRI simulation environment should provide functionality for rapid-sequence prototyping; otherwise, it will be of limited interest only. However, providing an easy-to-use framework should by no means increase the internal complexity thereof. This would reduce the possibility of extending and...