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Ciardo D.,Oncology and Radiotherapy Institute | Peroni M.,Polytechnic of Milan | Riboldi M.,Polytechnic of Milan | Riboldi M.,Bioengineering Unit | And 6 more authors.
Technology in Cancer Research and Treatment | Year: 2013

Deformable image registration provides a robust mathematical framework to quantify morphological changes that occur along the course of external beam radiotherapy treatments. As clinical reliability of deformable image registration is not always guaranteed, algorithm regularization is commonly introduced to prevent sharp discontinuities in the quantified deformation and achieve anatomically consistent results. In this work we analyzed the influence of regularization on two different registration methods, i.e. B-Splines and Log Domain Diffeomorphic Demons, implemented in an open-source platform. We retrospectively analyzed the simulation computed tomography (CTsim) and the corresponding re-planning computed tomography (CTrepl) scans in 30 head and neck cancer patients. First, we investigated the influence of regularization levels on hounsfield units (HU) information in 10 test patients for each considered method. Then, we compared the registration results of the open-source implementation at selected best performing regularization levels with a clinical commercial software on the remaining 20 patients in terms of mean volume overlap, surface and center of mass distances between manual outlines and propagated structures. The regularized B-Splines method was not statistically different from the commercial software. The tuning of the regularization parameters allowed open-source algorithms to achieve better results in deformable image registration for head and neck patients, with the additional benefit of a framework where regularization can be tuned on a patient specific basis. © Adenine Press (2013). Source


Seregni M.,Polytechnic of Milan | Pella A.,Polytechnic of Milan | Riboldi M.,Polytechnic of Milan | Riboldi M.,Bioengineering Unit | And 6 more authors.
Physica Medica | Year: 2013

The purpose of this study was to develop and assess the performance of a tumor tracking method designed for application in radiation therapy. This motion compensation strategy is currently applied clinically only in conventional photon radiotherapy but not in particle therapy, as greater accuracy in dose delivery is required.We proposed a tracking method that exploits artificial neural networks to estimate the internal tumor trajectory as a function of external surrogate signals. The developed algorithm was tested by means of a retrospective clinical data analysis in 20 patients, who were treated with state of the art infra-red motion tracking for photon radiotherapy, which is used as a benchmark. Integration into a hardware platform for motion tracking in particle therapy was performed and then tested on a moving phantom, specifically developed for this purpose.Clinical data show that a median tracking error reduction up to 0.7 mm can be achieved with respect to state of the art technologies. The phantom study demonstrates that a real-time tumor position estimation is feasible when the external signals are acquired at 60 Hz.The results of this work show that neural networks can be considered a valuable tool for the implementation of high accuracy real-time tumor tracking methodologies. © 2011 Associazione Italiana di Fisica Medica. Source


Mairani A.,Centro Nazionale Of Adroterapia Oncologica | Bohlen T.T.,Heidelberg Ion Beam Therapy Center | Bohlen T.T.,CERN | Dokic I.,University of Heidelberg | And 4 more authors.
International Journal of Radiation Biology | Year: 2013

Purpose: An approach for describing cell killing with sparsely ionizing radiation in normoxic and hypoxic conditions based on the initial number of randomly distributed DNA double-strand breaks (DSB) is proposed. An extension of the model to high linear energy transfer (LET) radiation is also presented. Materials and methods: The model is based on the probabilities that a given DNA giant loop has one DSB or at least two DSB. A linear combination of these two classes of damage gives the mean number of lethal lesions. When coupled with a proper modelling of the spatial distribution of DSB from ion tracks, the formalism can be used to predict cell response to high LET radiation in aerobic conditions. Results: Survival data for sparsely ionizing radiation of cell lines in normoxic/hypoxic conditions were satisfactorily fitted with the proposed parametrization. It is shown that for dose ranges up to about 10 Gy, the model describes tested experimental survival data as good as the linear-quadratic model does. The high LET extension yields a reasonable agreement with data in aerobic conditions. Conclusions: A new survival model has been introduced that is able to describe the most relevant features of cellular dose-response postulating two damage classes. © 2013 Informa UK, Ltd. Source


Peroni M.,Polytechnic of Milan | Ciardo D.,Oncology and Radiotherapy Institute | Spadea M.F.,University of Catanzaro | Riboldi M.,Polytechnic of Milan | And 8 more authors.
International Journal of Radiation Oncology Biology Physics | Year: 2012

Purpose: The purpose of this work was to develop and validate an efficient and automatic strategy to generate online virtual computed tomography (CT) scans for adaptive radiation therapy (ART) in head-and-neck (HN) cancer treatment. Method: We retrospectively analyzed 20 patients, treated with intensity modulated radiation therapy (IMRT), for an HN malignancy. Different anatomical structures were considered: mandible, parotid glands, and nodal gross tumor volume (nGTV). We generated 28 virtualCT scans by means of nonrigid registration of simulation computed tomography (CTsim) and cone beam CT images (CBCTs), acquired for patient setup. We validated our approach by considering the real replanning CT (CTrepl) as ground truth. We computed the Dice coefficient (DSC), center of mass (COM) distance, and root mean square error (RMSE) between correspondent points located on the automatically segmented structures on CBCT and virtualCT. Results: Residual deformation between CTrepl and CBCT was below one voxel. Median DSC was around 0.8 for mandible and parotid glands, but only 0.55 for nGTV, because of the fairly homogeneous surrounding soft tissues and of its small volume. Median COM distance and RMSE were comparable with image resolution. No significant correlation between RMSE and initial or final deformation was found. Conclusion: The analysis provides evidence that deformable image registration may contribute significantly in reducing the need of full CT-based replanning in HN radiation therapy by supporting swift and objective decision-making in clinical practice. Further work is needed to strengthen algorithm potential in nGTV localization. © 2012 Elsevier Inc. Source


Tessonnier T.,Centro Nazionale Of Adroterapia Oncologica | Tessonnier T.,Joseph Fourier University | Mairani A.,Centro Nazionale Of Adroterapia Oncologica | Cappucci F.,Centro Nazionale Of Adroterapia Oncologica | And 6 more authors.
Applied Radiation and Isotopes | Year: 2014

The integration of Monte Carlo (MC) transport codes into a particle therapy facility could be more easily achieved thanks to dedicated software tools. MC approach has been applied to several purposes at CNAO (Centro Nazionale di Adroterapia Oncologica), such as database generation for the treatment planning system, quality assurance calculations and biologically related simulations. In this paper we describe another application of the MC code and its tools by analyzing the impact of the dose delivery and range uncertainties on patient dose distributions. © 2013 Elsevier Ltd. Source

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