Agent-based modelling of tumour spheroid growth and treatment

Malignant neoplasms are one of the top causes of death in all developed countries around the world and account for almost one quarter of all deaths. An individual cell based computational model with strong connections to the experimental data through lattice free, newtonian interaction could be used to validate experimental results and eventually make predictions guiding further experiments. This model was build as a part of the thesis and shall be extended to the modelling of the effects of ionic radition on the vascularised tumour as a possible treatment for inoperable tumours.Im Rahmen dieser Diplomarbeit wurde eine, von der individuellen Zelle ausgehende, agentenbasierte Computersimulation des Wachstums eines multizellulären Tumorsphäroiden entwickelt. Die theoretische Behandlung des Tumorwachstums ist von großem Interesse, da ein realistisches Modell dazu dienen kann, Experimente in silico zu simulieren. Dies bietet nicht nur zeitliche und finanzielle Vorteile gegenüber der tatsächlichen Durchführung der Experimente, sondern muss auch von einem ethischen Standpunkt aus bevorzugt werden, da Simulationen Laborversuche an Tieren oder klinische Tests an Probanden teilweise ersetzen können. Die Simulationsumgebung, welche als Teil dieser Diplomarbeit entwickelt wurde, ist in der Programmiersprache C++ erstellt, um durch die verwendung von Objekten und Klassen eine maximale Erweiterbarkeit im Hinblick auf zukünftige Untersuchungen zu gewährleisten. Eine starke experimentelle Anbindung ist durch die gitterfreie, kräftebasierte Interaktion der Zellagenten gegeben. Die Tumordynamik inklusive Zellbewegung, Zellzyklus und Diffusion von Nährstoffen wurde als Multiskalenproblem erfasst. Um eine realistische Simulation zu erstellen, muss die Zelle als das zu simulierende Objekt zuerst abstrahiert werden. Dabei geht es um die realitätsgetreue Abbildung der biophysikalisch relevanten Eigenschaften einer Zelle auf ein mathematisches Modell. Mechanismen der Zelle, die für eine realistische Erforschung der Onkogenese im Modell entscheident sind, müssen im Modellansatz implementiert werden. In erster Näherung kann eine Zelle als viskoelastische, adhäsive Kugel betrachtet werden. Folgt man dieser Betrachtungsweise so sind etablierte Interaktionsmodelle wie zum Beispiel das Johnson-Kendall-Roberts Modell anwendbar, um die Wechselwirkung zwischen Zellen realistisch zu beschreiben. Zur Bestimmung der Zellnachbarschaft wurde eine kinetische und dynamische Delaunay-Triangulation verwendet, welche es ermöglicht, auf elegante und effiziente Weise die Nachbarschaftsbeziehungen im Gewebe zu erfassen, sowie durch ihre Dualität zur Voronoi-Zerlegung Zellvolumina und -kontaktflächen zu berechnen. Die aus dem Johson-Kendall-Roberst Modell resultierenden Kräfte der Zellinteraktion wurden in einer überdämpften Näherung integriert, wie sie für Zellen in dichtem Gewebe anwendbar ist. Hierzu wurden numerischen Algorithmen für die Stabilisierung und effizientere Simulation der entstehenden Zelldynamik entwickelt (lokale und globale adaptive Zeitschrittweite). Die Einführung eines Zellzyklus und der dazugehörigen Mechanismen für die Zellagenten ermöglicht die realistische Simulation des Gewebewachstums. Voraussetzung dafür war, das die Dynamik der Nährstoffe für den Zellmetabolismus erfasst werden konnte. Zur Modellierung der zugrunde liegenden Reaktions-Diffusionssysteme löslicher Nährstoffe wird der "alternating-direction implicit"-Algorithmus (ADI) angewandt. Weiterhin wurde ein fortschrittlicher Algorithmus für die Zytokinese in agentenbasierten Simulationen eingeführt, der entscheidende Laufzeitvorteile durch eine realistischere Dynamik der Zellen während der Mitose mit sich bringt. Ein implementiertes Modell für die mechanische Proliferationshemmung infolge eines zu hohen Zelldrucks wurde mit der Wirkung eines nährstoffbasierten Mechanismus verglichen. Das Wachstum eines multizellulären Tumorsphäroiden konnte im Verlauf der Arbeit auf der Basis von experimentell ermittelten Größen für die Zellagenten in silico modelliert werden. Dabei wurde ein Vergleich der erzielten Ergebnisse mit experimentellen Resultaten durchgeführt. Sowohl für das Problem der Zellsortierung aufgrund differentieller Adhäsion als auch für das avaskuläre Tumorwachstum, stimmten die Ergebnisse des Modells mit den experimentellen Resultaten überein. Erste Simulatioinen der Bestrahlung eines Tumors in silico zeigten Effekte wie z.B. die Arretierung am G2=M-Kontrollpunkt, die qualitativ wie quantitativ mit experimentellen Beobachtungen übereinstimmen. Als Reaktion der Tumordynamik auf partielle Bestrahlung des Gewebes wurden verschiedene Phänomene beobachtet, die für weitere Untersuchungen von Interesse sind. Dazu zählen Effekte wie z.B. die Resynchronisierung des Zellzyklus und ein exzessives Tumorwachstum nach erfolgter Bestrahlung. Die Übereinstimmung der erzielten Ergebnisse zeigt, dass das entwickelte Modell auf die Simulation von komplexeren Effekten der Tumorbestrahlung mit Schwerionen ausgedehnt werden kann. Eine angestrebte Nutzung ist die Simulation der Bestrahlungsprozesse mit dem Ziel, die verwendeten Protokolle zu optimieren und damit die Effektiviät der Strahlentherapie zu erhöhen

Change Detection from Extensive Time-Series

Due to the repeat-pass orbit of the TerraSAR-X mission, time series exploitation is an outstanding capability with a wide range of possible applications. In comparison to electro-optical systems, a space borne radar images radiometry is hardly influenced by atmospheric conditions resulting in highly robust change information between image pairs. Nevertheless, other radar-specific imaging effects like noise, side lobes or interference are rather disadvantageous for image processing. Especially in urban environment the visual interpretation of radar signatures depicts a challenging task even for experienced radar image analysts. The processing of extensive time series allows a significant de-speckling that can be used e.g. for a more robust change detection

Galileo In-Situ Dust Measurements in Jupiter's Gossamer Rings

During its late orbital mission at Jupiter the Galileo spacecraft made two passages through the giant planet's gossamer ring system. The impact-ionization dust detector on board successfully recorded dust impacts during both ring passages and provided the first in-situ measurements from a dusty planetary ring. In all, a few thousand dust impacts were counted with the instrument accumulators during both ring passages, but only a total of 110 complete data sets of dust impacts were transmitted to Earth. Detected particle sizes range from about 0.2 to 5 micron, extending the known size distribution by an order of magnitude towards smaller particles than previously derived from optical imaging (Showalter et al. 2008). The grain size distribution increases towards smaller particles and shows an excess of these tiny motes in the Amalthea gossamer ring compared to the Thebe ring. The size distribution for the Amalthea ring derived from our in-situ measurements for the small grains agrees very well with the one obtained from images for large grains. Our analysis shows that particles contributing most to the optical cross-section are about 5 micron in radius, in agreement with imaging results. The measurements indicate a large drop in particle flux immediately interior to Thebe's orbit and some detected particles seem to be on highly-tilted orbits with inclinations up to 20 deg.Comment: 13 figures, 4 tables, submitted to Icaru

Sample return of interstellar matter (SARIM)

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In silico optimisation of cancer treatment schedules

The central goal of this investigation is to describe the dynamic reaction of a multicellular tumour spheroid to treatment with radiotherapy. A focus will be on the triggered dynamic cell cycle reaction in the spheroid and how it can be employed within fractionated radiation schedules. An agent-based model for cancer cells is employed which features inherent cell cycle progression and reactions to environmental conditions. Cells are represented spatially by a weighted, dynamic and kinetic Voronoi/Delaunay model which also provides for the identification of cells in contact within the multicellular aggregate. Force-based interaction between cells will lead to rearrangement in response to proliferation and can induce cell quiescence via a mechanism of pressure-induced contact inhibition. The evolution of glucose and oxygen concentration inside the tumour spheroid is tracked in a diffusion solver in correspondence to in vitro or in vivo boundary conditions and a corresponding local nutrient uptake by single cells. Radiation effects are implemented based on the measured single cell survival in the linear-quadratic model. The survival probability will be affected by the radiosensitivity of the current cycle phase and the local oxygen concentration. Quiescent cells will reduce the effective dose they receive as a consequence of their increased radioresistance. The radiation model includes a fast response to fatal DNA damage through cell apoptosis and a slow response via cell loss due to misrepair during the radiation-induced G2-block. A simplified model for drug delivery in chemotherapy is implemented. The model can describe the growth dynamics of spheroids in accordance to experimental data, including total number of cells, histological structure and cell cycle distribution. Investigations of possible mechanisms for growth saturation reveal a critical dependence of tumour growth on the shedding rate of cells from the surface. In response to a dose of irradiation, a synchronisation of the cell cycle progression within the tumour is observed. This will lead to cyclic changes in the overall radiation sensitivity of the tumour which are quantified using an enhancement measure in comparison to the expected radiosensitivity of he tumour. A transient strong peak in radiosensitivity enhancement is observed after administration of irradiation. Mechanisms which influence the peak timing and development are systematically investigated, revealing quiescence and reactivation of cells to be a central mechanism for the enhancement. Direct redistribution of cells due to different survival in cell cycle phases, re-activation of quiescent cells in response to radiation-induced cell death and blocking of DNA damaged cells at the G2/M checkpoint are identified as the main mechanisms which contribute to a synchronisation and determine the radiosensitivity increase. A typical time scale for the development of radiosensitivity and the relaxation of tumours to a steady-state after irradiation is identified, which is related to the typical total cell cycle time. A range of clinical radiotherapy schedules is tested for their performance within the simulation and a systematic comparison with alternative delivery schedules is performed, in order to identify schedules which can most effectively employ the described transient enhancement effects. In response to high-dose schedules, a dissolution of the tumour spheroid into smaller aggregates can be observed which is a result of the loss of integrity in the spheroid that is associated with high cell death via apoptosis. Fractionated irradiation of spheroids with constant dose per time unit but different inter-fraction times clearly reveals optimal time-intervals for radiation, which are directly related to the enhancement response of the tumour. In order to test the use of triggered enhancement effects in tumours, combinations of trigger- and effector doses are examined for their performance in specific treatment regimens. Furthermore, the automatic identification and triggering in response to high enhancement periods in the tumour is analysed. While triggered schedules and automatic schedules both yield a higher treatment efficiency in comparison to conventional schedules, treatment optimisation is a revealed to be a global problem, which cannot be sufficiently solved using local optimisation only. The spatio-temporal dynamics of hypoxia in the tumour are studied in response to irradiation. Microscopic, diffusion-induced reoxygenation dynamics are demonstrated to be on a typical time-scale which is in the order of fractionation intervals. Neoadjuvant chemotherapy with hydroxyurea can yield a drastic improvement of radiosensitivity via cell cycle synchronisation and specific toxicity against radioresistant S-phase cells. The model makes clear predictions of radiation schedules which are especially effective as a result of triggered cell cycle-based radiosensitivity enhancement. Division of radiation into trigger and effector doses is highly effective and especially suited to be combined with adjuvant chemotherapy in order to limit regrowth of cells

Image Fusion of Different Spaceborne SAR Sensors for Change Detection

Change detection by spaceborne high resolution synthetic aperture radar (SAR) images is a very powerful tool for reconnaissance tasks, as this is largely uninfluenced by weather conditions or the time of the day and additionally doesn’t violate sovereign rights. The use of different spaceborne SAR sensors would reduce the revisit time of a region of interest considerably, allowing a denser monitoring. Unfortunately, different sensors mean different system parameters like frequency, resolution or aspect angle, commonly leading to higher false-alarm rates in the change detection. Nevertheless, this paper demonstrates a successful image fusion of Radarsat-2 and TerraSAR-X data

A simulation-based approach towards automatic target recognition of high resolution space-borne radar signatures

Specific imaging effects that are caused mainly by the range measurement principle of a radar device, its much lower frequency range as compared to the optical spectrum, the slanted imaging geometry and certainly the limited spatial resolution complicates the interpretation of radar signatures very strongly. Especially the coherent image formation which causes unwanted speckle noise aggravates the problem of visually recognizing target objects. Fully automatic approaches with acceptable false alarm rates are therefore an even harder challenge. At the Microwaves and Radar Institute of the German Aerospace Center (DLR) the development of methods to implement a robust overall processing workflow for automatic target recognition (ATR) out of high resolution synthetic aperture radar (SAR) image data is under progress. The heart of the general approach is to use time series exploitation for the former detection step and simulation based signature matching for the subsequent recognition. This paper will show the overall ATR chain as a proof of concept and will go into more detail for the part of simulation based recognition. Focusing on space borne sensors, the all-day and -weather capabilities of radar systems coupled with their high resolution capacity through the SAR principle, provides an ideal instrument for remote sensing. Especially the performance of change detection by using repeat-pass image acquisitions over long periods of time is outstanding if compared to optical sensors. The first important step for ATR is to detect potential targets from the image data, which already is a complicated task when using only single image acquisitions. Automatically detecting candidates for targets from multiple image acquisitions can be done in a much more robust way. Additional to the illustration of this detection approach, thoughts on the incorporation of other a priori information sources e.g. digital surface models, maps and optical reference data will be given. After extracting potential target signatures the final decision of classification is performed by a simulation based recognition method. After selecting available 3D model data that come into question for the extracted candidate, signatures are estimated with very efficient self-developed simulation techniques. Afterwards, prominent scattering centers are extracted from the simulated and real signatures by sophisticated filter methods. Feature-based and correlation-based methods will be compared in the final recognition step. The proof of concept will be illustrated on data takes of an airport scene, through operating the TerraSAR-X satellite in its staring spotlight imaging mode, giving high resolution signatures with a range resolution around half a meter and a cross-range resolution around a quarter of a meter. It will be shown that for large-scale aircrafts, a promising performance in recognition can be achieved without using usual machine learning approaches

Depth-of-Focus Issues on Spaceborne Very High Resolution SAR

Higher resolutions mean a more complex challenge on the SAR imaging not only in dealing with an at least quadratically growing data amount, but the more with stronger conditions on the focusing of the SAR image. In this study the defocusing effect is evaluated quantitatively by measuring the resulting resolution of a simulated ideal point scatterer depending on its height distance to the focusing plane. The simulations indicate a linear dependence of the depth-of-focus on the square of the nominal cross range resolution

Spatio-temporal dynamics of hypoxia during radiotherapy

Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment