Browsing by Author "Rocha, Humberto"
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- Advantage of beam angle optimization in head-and-neck IMRT: Patient specific analysisPublication . Ventura, Tiago; Lopes, Maria do Carmo; Rocha, Humberto; Costa Ferreira, Brígida; Dias, JoanaRadiation therapy (RT) main purpose is to eliminate, in a controlled way, all tumor cells sparing as much as possible the normal tissues. Intensity Modulated Radiation Therapy (IMRT) is becoming the standard treatment technique in RT. Beam angle optimization (BAO) has potential to confer more quality to IMRT inverse planning process compared to manual trial and error approaches. In this study, the BAO advantages in head-and-neck patients are highlighted, using a patient specific analysis. Fluence optimization was done with Erasmus-iCycle multicriterial engine and BAO optimization was performed using two different algorithms: a combinatorial iterative algorithm and an algorithm based on a pattern search method. Plan assessment and comparison was performed with the graphical tool SPIDERplan. Among a set of forty studied nasopharynx cancer cases, three patients have been select for the specific analysis presented in this work. BAO presented plan quality improvements when beam angular optimized plans were compared with the equidistant beam angle solution and when plans based on non-coplanar beams geometries were compared with coplanar arrangements. Improvement in plan quality with a reduced number of beams was also achieved, in one case. For all cases, BAO generated plans with higher target coverage and better sparing of the normal tissues
- Automated fluence map optimization based on fuzzy inference systemsPublication . Dias, Joana; Rocha, Humberto; Ventura, Tiago; BC Ferreira; Lopes, Maria do CarmoThe planning of an intensity modulated radiation therapy treatment requires the optimization of the fluence intensities. The fluence map optimization (FMO) is many times based on a nonlinear continuous programming problem, being necessary for the planner to define a priori weights and/or lower bounds that are iteratively changed within a trial-and-error procedure until an acceptable plan is reached. In this work, the authors describe an alternative approach for FMO that releases the human planner from trial-and-error procedures, contributing for the automation of the planning process.
- Automated Radiotherapy Treatment Planning Using Fuzzy Inference SystemsPublication . Dias, Joana; Rocha, Humberto; Ventura, Tiago; Costa Ferreira, Brigida; Lopes, Maria do CarmoRadiotherapy is one of the treatments available for cancer patients, aiming to irradiate the tumor while preserving healthy structures. The planning of a treatment is a lengthy trial and error procedure, where treatment parameters are iteratively changed and the delivered dose is calculated to see whether it complies with the desired medical prescription. In this paper, a procedure based on fuzzy inference systems (FIS) for automated treatment planning is developed, allowing the calculation of high quality treatment plans without requiring human intervention. The procedure is structured in two different phases, incorporating the automatic selection of the best set of equidistant beam irradiation directions by an enumeration procedure. The developed method is extensively tested using ten head-and-neck cancer cases.
- Beam angle optimization in IMRT: are we really optimizing what matters?Publication . Rocha, Humberto; Dias, Joana Matos; Ventura, Tiago; BC Ferreira; Lopes, Maria do CarmoIntensity‐modulated radiation therapy (IMRT) is a modern radiotherapy modality that uses a multileaf collimator to enable the irradiation of the patient with nonuniform maps of radiation from a set of distinct beam irradiation directions. The aim of IMRT is to eradicate all cancerous cells by irradiating the tumor with a prescribed dose while simultaneously sparing, as much as possible, the neighboring tissues and organs. The optimal choice of beam irradiation directions—beam angle optimization (BAO)—can play an important role in IMRT treatment planning by improving organ sparing and tumor coverage, increasing the treatment plan quality. Typically, the BAO search is guided by the optimal value of the fluence map optimization (FMO)—the problem of obtaining the most appropriate radiation intensities for each beam direction. In this paper, a new score to guide the BAO search is introduced and embedded in a parallel multistart derivative‐free optimization framework that is detailed for the extremely challenging continuous BAO problem. For the set of 10 clinical nasopharyngeal tumor cases considered, treatment plans obtained for optimized beam directions clearly outperform the benchmark treatment plans obtained considering equidistant beam directions typically used in clinical practice. Furthermore, treatment plans obtained considering the proposed score clearly improve the quality of the plans resulting from the use of the optimal value of the FMO problem to guide the BAO search.
- Clinical validation of a graphical method for radiation therapy plan quality assessmentPublication . Ventura, Tiago; Dias, Joana; Khouri, Leila; Netto, Eduardo; Soares, André; Costa Ferreira, Brigida; Rocha, Humberto; Lopes, Maria do CarmoBackground: This work aims at clinically validating a graphical tool developed for treatment plan assessment, named SPIDERplan, by comparing the plan choices based on its scoring with the radiation oncologists (RO) clinical preferences. Methods: SPIDERplan validation was performed for nasopharynx pathology in two steps. In the first step, three ROs from three Portuguese radiotherapy departments were asked to blindly evaluate and rank the dose distributions of twenty pairs of treatment plans. For plan ranking, the best plan from each pair was selected. For plan evaluation, the qualitative classification of ‘Good’, ‘Admissible with minor deviations’ and ‘Not Admissible’ were assigned to each plan. In the second step, SPIDERplan was applied to the same twenty patient cases. The tool was configured for two sets of structures groups: the local clinical set and the groups of structures suggested in international guidelines for nasopharynx cancer. Group weights, quantifying the importance of each group and incorporated in SPIDERplan, were defined according to RO clinical preferences and determined automatically by applying a mixed linear programming model for implicit elicitation of preferences. Intra- and inter-rater ROs plan selection and evaluation were assessed using Brennan-Prediger kappa coefficient. Results: Two-thirds of the plans were qualitatively evaluated by the ROs as ‘Good’. Concerning intra- and inter-rater variabilities of plan selection, fair agreements were obtained for most of the ROs. For plan evaluation, substantial agreements were verified in most cases. The choice of the best plan made by SPIDERplan was identical for all sets of groups and, in most cases, agreed with RO plan selection. Differences between RO choice and SPIDERplan analysis only occurred in cases for which the score differences between the plans was very low. A score difference threshold of 0.005 was defined as the value below which two plans are considered of equivalent quality. Conclusion: Generally, SPIDERplan response successfully reproduced the ROs plan selection. SPIDERplan assessment performance can represent clinical preferences based either on manual or automatic group weight assignment. For nasopharynx cases, SPIDERplan was robust in terms of the definitions of structure groups, being able to support different configurations without losing accuracy.
- Comparison of Combinatorial and Continuous Frameworks for the Beam Angle Optimization Problem in IMRTPublication . Rocha, Humberto; Dias, Joana; Ventura, Tiago; Costa Ferreira, Brigida; do Carmo Lopes, MariaRadiation therapy (RT) is used nowadays for the majority of cancer patients. A technologically advanced type of RT is IMRT – intensity-modulated radiation therapy. With this RT modality the cancerous cells of the patient can be irradiated using non-uniform radiation maps delivered from different beam directions. Although non-uniform radiation maps allow, by themselves, an enhanced sparing of the neighboring healthy organs while properly irradiating the tumor with the prescribed dose, selection of appropriate irradiation directions play a decisive role on these conflicting tasks: deliver dose to the tumor while preventing (too much) dose to be deposited in the surrounding tissues. This paper focus on the problem of choosing the best set of irradiation directions, known as beam angle optimization (BAO) problem. Two completely different mathematical formulations of this problem can be found in the literature. A combinatorial formulation, widely used and addressed by many different algorithms and strategies, and a continuous formulation proposed by the authors and addressed by derivative-free algorithms. In this paper, a comparison of two of the most successful strategies to address each one of these formulations is done resorting to a set of ten clinical nasopharyngeal tumor cases already treated at the Portuguese Institute of Oncology of Coimbra.
- Comparison of two beam angular optimization algorithms guided by automated multicriterial IMRTPublication . Ventura, Tiago; Rocha, Humberto; Costa Ferreira, Brigida; Dias, Joana; Lopes, Maria do CarmoTo compare two beam angle optimization (BAO) algorithms for coplanar and non-coplanar geometries in a multicriterial optimization framework.
- A derivative-free multistart framework for an automated noncoplanar beam angle optimization in IMRTPublication . Rocha, Humberto; Dias, Joana; Ventura, Tiago; BC Ferreira; Lopes, Maria do CarmoThe inverse planning of an intensity-modulated radiation therapy (IMRT) treatment requires decisions regarding the angles used for radiation incidence, even when arcs are used. The possibility of improving the quality of treatment plans by an optimized selection of the beam angle incidences-beam angle optimization (BAO)-is seldom done in clinical practice. The inclusion of noncoplanar beam incidences in an automated optimization routine is even more unusual. However, for some tumor sites, the advantage of considering noncoplanar beam incidences is well known. This paper presents the benefits of using a derivative-free multistart framework for the optimization of the noncoplanar BAO problem.
- Dose-response to different radiochemotherapy regimens in locally advanced pancreatic cancerPublication . Costa Ferreira, Brígida; Dias, Joana; Gomes, Adriana; Mavroidis, Panayiotis; Rocha, HumbertoConformal radiation therapy (RT) delivered concomitantly with chemotherapy including 5-fluorouracil (5-FU) or Gemcitabine (GEM) is a common treatment for patients with unresectable locally advanced pancreatic tumors. In this study, the Poisson model describing tumor response to these two treatment options was derived. Clinical data was retrieved from reports pub lished from 1990 to 2015. Dosimetric and clinical data from 1196 patients treated with RT with concurrent 5-FU or GEM were gathered. RT doses ranging from 3.6–64.8 Gy, delivered in fractions of 1.2–8 Gy, were converted to a 2 Gy fractionation scheme using the Biological Effective Dose concept. The param eters of the Poisson-Linear-Quadratic-Time model were derived using genetic algorithm optimization to minimize the least-square fitting error and a local search was then made using the maximum likelihood method. The goodness of the fit was assessed using the Pearson v2 -test. For RT+5-FU, D50 was 59.8 Gy, c was 1.3, a/b was 3.2, Tpot was 18.6 days and Tk was 25.0 days. For RT+GEM, D50 was 54.5 Gy, c was 1.4, a/b was 4.6, Tpot was 34.2 days and Tk was 37.2 days. As expected, RT+GEM showed higher efficacy than RT+5-FU. A RT dose-response effect was obtained showing that treatment strategies allowing a dose-escalation in pancreas tumors should be investigated
- Feature selection in small databases: A medical-case studyPublication . Soares, Inês; Dias, Joana; Rocha, Humberto; Lopes, Maria do Carmo; Costa Ferreira, BrigidaPredictions made by using machine learning classification models are recurrent in many research fields for a variety of reasons. In some cases, feature selection can effi- ciently improve the accuracy of classifications, while reducing the computational requirements. However, some predictive studies are characterized by a high dimensionality or based on small datasets.