A leading design concept for NASA’s upcoming planet-finding space telescope involves placing an occulter 72,000 km in front of a 4-m telescope. The purpose of the occulter is to block the bright starlight thereby enabling the telescope to take pictures of planets orbiting the blocked star. Unfortunately, diffraction effects prevent a simple circular occulter from providing a sufficiently dark s...

Introduction: The incidence of breast cancer increases with the rate of 1-2% at the world. Radiation therapy is one of the available choices for breast cancer treatment. The single isocentre half-beam block technique is considered as a standard technique to avoid hot and cold spots within the PTV. The major advantage of half beam technique is that the both contralateral breast...

We consider the effects of parameter uncertainty on the optimal radiation schedule in the context of the linear-quadratic model. Our interest arises from the observation that if interpatient variations in normal tissues and tumor sensitivities to radiation or sparing factor of the organ at risk (OAR) are not accounted for during radiation scheduling, the performance of the therapy may be strong...

OBJECTIVE Concomitant chemo-radiotherapy after modified radical mastectomy for breast cancer is an effective means of achieving high survival rates. In this study different radiotherapy optimization regimens are compared to assess their effectiveness and toxicity rates. PATIENTS AND METHODS 112 patients with modified radical mastectomy participated, and were randomly assigned to one of three ...

Radiotherapy plays an increasingly important role in cancer treatment, and medical imaging plays an increasingly important role in radiotherapy. Magnetic resonance imaging (MRI) is poised to be a major component in the development towards more e ective radiotherapy treatments with fewer side e ects. This thesis attempts to contribute in realizing this potential. Radiotherapy planning requires s...

We propose a hybrid multiobjective (MO) evolutionary optimization algorithm (MOEA) for intensity modulated radiotherapy inverse planning and apply it to optimize the number of incident beams, their orientations and intensity profiles. The algorithm produces a set of efficient solutions, which represent different clinical tradeoffs and contains information such as variety of dose distributions a...

Intensity modulated radiation therapy (IMRT) is one of the most innovative techniques in oncological radiotherapy, allowing to conform the dose delivery to the tumoral target, preserving the normal tissue. The high number of parameters involved in the IMRT treatment planning requires an automated approach to the beam modulation. Such optimization process consists in the search of the global min...

PURPOSE To develop a clinically viable mathematical model that quantitatively predicts tumor volume change during radiotherapy in order to provide treatment response assessment for prognosis, treatment plan optimization, and adaptation. METHOD AND MATERIALS The correction factors containing hypoxia, DNA single strand breaks, potentially lethal damage, and other factors were used to develop an...

We are interested in fundamental decision and design problems in human-machine collaboration and skill-augmentation, with a focus on healthcare. Inference and optimization in healthcare are often hard multi-stage stochastic models, but we explore efficient reformulations and heuristics with guarantees. Specifically, we have studied algorithmically grounded solutions for integration of autonomy ...

A model of combined antiangiogenic therapy and radiotherapy of tumors is proposed and analyzed. The model is a modified Hahnfeldt model (proposed by d’Onofrio and Gandolfi) and we discuss its properties including its asymptotic behaviour under constant and periodic therapy. Then we propose an optimization problem in the final horizon which leads to the optimal treatment protocols. We find neces...