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Coimbra, Portugal

Rocha H.,INESCC | Dias J.M.,FEUC | Ferreira B.C.,University of Aveiro | Lopes M.C.,IPOC FG
Journal of Global Optimization | Year: 2013

The selection of appropriate radiation incidence directions in radiation therapy treatment planning is important for the quality of the treatment plan, both for appropriate tumor coverage and for better organ sparing. The objective of this paper is to discuss the benefits of using radial basis functions within a pattern search methods framework in the optimization of the highly non-convex beam angle optimization (BAO) problem. Pattern search methods are derivative-free optimization methods that require few function value evaluations to converge and have the ability to avoid local entrapment. These two characteristics gathered together make pattern search methods suited to address the BAO problem. The pattern search methods framework is composed by a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and assures convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Radial basis functions are used and tested in this step both to influence the quality of the local minimizer found by the method and to obtain a better coverage of the search space in amplitude. A set of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of using this approach in the optimization of the BAO problem. © 2012 Springer Science+Business Media New York. Source


Ferreira A.F.,University of Lisbon | Ribeiro L.A.,INESCC | Ribeiro L.A.,University of Coimbra | Batista A.P.,National Laboratory of Energy and Geology | And 7 more authors.
Bioresource Technology | Year: 2013

Are microalgae a potential energy source for biofuel production? This paper presents the laboratory results from a Nannochloropsis sp. microalga biorefinery for the production of oil, high-value pigments, and biohydrogen (bioH2). The energy consumption and CO2 emissions involved in the whole process (microalgae cultivation, harvest, dewater, mill, extraction and leftover biomass fermentation) were evaluated. An economic evaluation was also performed. Oil was obtained by soxhlet (SE) and supercritical fluid extraction (SFE). The bioH2 was produced by fermentation of the leftover biomass. The oil production pathway by SE shows the lowest value of energy consumption, 177-245MJ/MJprod, and CO2 emissions, 13-15kgCO2 /MJprod. Despite consuming and emitting c.a. 20% more than the SE pathway, the oil obtained by SFE, proved to be more economically viable, with a cost of 365€/kgoil produced and simultaneously extracting high-value pigments. The bioH2 as co-product may be advantageous in terms of product yield or profit. © 2013 Elsevier Ltd. Source


Rocha H.,INESCC | Dias J.M.,INESCC | Ferreira B.C.,IPOC FG | Ferreira B.C.,University of Aveiro | And 2 more authors.
Mathematical and Computer Modelling | Year: 2012

The intensity modulated radiation therapy (IMRT) treatment planning problem is usually divided into three smaller problems that are solved sequentially: the geometry problem, intensity problem, and realization problem. That division has the consequence of causing a plan quality deterioration arising from the transition between the intensity problem and the realization problem. Typically, on the beamlet-based approach, after the optimal beamlet intensities are determined, they are discretized over a range of values using a distance criterion (rounding). However, that decision criterion is not appropriate and we present empirical evidence that this can lead to a significant deterioration of the treatment plan quality regardless of the model used to tackle the intensity problem. We propose a combinatorial optimization approach and a probabilistic binary tabu search algorithm to enable an improved transition from optimized to delivery fluence maps in IMRT by minimizing the deterioration of the treatment plan quality and improving organ sparing at the same time. Four head and neck clinical examples were used to test the ability of the proposed formulation and resolution method to obtain improved plans compared to the usual rounding procedure. The results obtained present a clear improvement of the treatment plan quality both in terms of target coverage and also in terms of parotid sparing. © 2011 Elsevier Ltd. Source


Rocha H.,INESCC | Dias J.M.,INESCC | Ferreira B.C.,IPOC FG | Do Carmo Lopes M.,IPOC FG
IFMBE Proceedings | Year: 2015

The fluence map optimization (FMO) problem is one of the most studied problems in intensity-modulated radiation therapy treatment planning. Although many approaches have shown to yield good solutions to the FMO problem, the optimal solutions obtained ensure that the resulting treatment is the best possible with respect to the weighting parameters of the formulation used. Since the ‘optimal’ weighting scheme is unknown, the choice of the weight parameters is typically a long trial-and-error process until a satisfactory solution is achieved. Moreover, for selecting the best irradiating directions, it is not clear how traditional trial-and-error parameter tuning should be incorporated or managed. A two-stage programming approach is proposed to reduce the dependency of the optimal solutions on the weight parameters and simultaneously improve the overall plan quality. This approach is yet another step towards automated generation of treatment plans which will result in breakthrough developments in radiation therapy care. © Springer International Publishing Switzerland 2015. Source


Rocha H.,INESCC | Dias J.M.,INESCC | Ferreira B.C.,IPOC FG | Lopes M.C.,IPOC FG
IFMBE Proceedings | Year: 2014

The beam angle optimization (BAO) problem remains an important and challenging problem in intensity-modulated radiation therapy (IMRT) treatment planning. BAO consists on the selection of appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance organs sparing and to improve tumor coverage. This is a very difficult global optimization problem since it is a highly non-convex continuous optimization problem with many local minima. Many conventional BAO approaches are based on single-beam metrics to solve a relaxed combinatorial formulation of the BAO problem. Typically, the quality of the solutions obtained is not simply related to the final value of an objective function but rather judged by dose-volume histograms or considering a set of physical dose metrics. For that reason, and also due to the fact that the global optimum value is unknown, it is difficult to perceive, in medical physics point of view, how good a solution is or how much could it be improved. In a mathematical point of view, it is difficult to acknowledge how far a solution is from the global optimum. The objective of this paper is to present the difficulties in obtaining near global optimum solutions for the BAO problem, particularly when using single-beam approaches considering discrete subsets of all possible beam angles. The benefits of using a derivative-free approach for a continuous formulation of the BAO problem are discussed using a retrospective treated case of head-and-neck tumor at the Portuguese Institute of Oncology of Coimbra. © Springer International Publishing Switzerland 2014. Source

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