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Dive into the research topics where Catarina Veiga is active.

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Featured researches published by Catarina Veiga.


International Journal of Radiation Oncology Biology Physics | 2016

First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer

Catarina Veiga; Guillaume Janssens; Ching-Ling Teng; Thomas Baudier; L. Hotoiu; Jamie R. McClelland; Gary J. Royle; Liyong Lin; Lingshu Yin; James M. Metz; Timothy D. Solberg; Zelig Tochner; Charles B. Simone; J McDonough; Boon-Keng Kevin Teo

PURPOSE An adaptive proton therapy workflow using cone beam computed tomography (CBCT) is proposed. It consists of an online evaluation of a fast range-corrected dose distribution based on a virtual CT (vCT) scan. This can be followed by more accurate offline dose recalculation on the vCT scan, which can trigger a rescan CT (rCT) for replanning. METHODS AND MATERIALS The workflow was tested retrospectively for 20 consecutive lung cancer patients. A diffeomorphic Morphon algorithm was used to generate the lung vCT by deforming the average planning CT onto the CBCT scan. An additional correction step was applied to account for anatomic modifications that cannot be modeled by deformation alone. A set of clinical indicators for replanning were generated according to the water equivalent thickness (WET) and dose statistics and compared with those obtained on the rCT scan. The fast dose approximation consisted of warping the initial planned dose onto the vCT scan according to the changes in WET. The potential under- and over-ranges were assessed as a variation in WET at the targets distal surface. RESULTS The range-corrected dose from the vCT scan reproduced clinical indicators similar to those of the rCT scan. The workflow performed well under different clinical scenarios, including atelectasis, lung reinflation, and different types of tumor response. Between the vCT and rCT scans, we found a difference in the measured 95% percentile of the over-range distribution of 3.4 ± 2.7 mm. The limitations of the technique consisted of inherent uncertainties in deformable registration and the drawbacks of CBCT imaging. The correction step was adequate when gross errors occurred but could not recover subtle anatomic or density changes in tumors with complex topology. CONCLUSIONS A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.


International Journal of Particle Therapy , 2 (2) pp. 404-414. (2015) | 2015

Cone-Beam Computed Tomography and Deformable Registration-Based “Dose of the Day” Calculations for Adaptive Proton Therapy

Catarina Veiga; Jailan Alshaikhi; Richard Amos; A Lourenço; Marc Modat; Sebastien Ourselin; Gary J. Royle; Jamie R. McClelland

Abstract Purpose: The aim of this work was to evaluate the feasibility of cone-beam computed tomography (CBCT) and deformable image registration (DIR)–based “dose of the day” calculations for adaptive proton therapy. Methods: Intensity-modulated radiation therapy (IMRT) and proton therapy plans were designed for 3 head and neck patients that required replanning, and hence had a replan computed tomography (CT). Proton plans were generated for different beam arrangements and optimizations: intensity modulated proton therapy and single-field uniform dose. We used an in-house DIR software implemented at our institution to generate a deformed CT, by warping the planning CT onto the daily CBCT. This CBCT had a similar patient geometry to the replanned CT. Dose distributions on the replanned CT were considered the gold standard for “dose of the day” calculations, and were compared with doses on deformed CT (our method) and directly on the calibrated CBCT and rigidly aligned planning CT (alternative methods) in t...


medical image computing and computer assisted intervention | 2015

Robust CT Synthesis for Radiotherapy Planning: Application to the Head and Neck Region

Ninon Burgos; Manuel Jorge Cardoso; Filipa Guerreiro; Catarina Veiga; Marc Modat; Jamie R. McClelland; Antje-Christin Knopf; Shonit Punwani; David Atkinson; Simon R. Arridge; Brian F. Hutton; Sebastien Ourselin

In this work, we propose to tackle the problem of magnetic resonance (MR)-based radiotherapy treatment planning in the head & neck area by synthesising computed tomography (CT) from MR images using an iterative multi-atlas approach. The proposed method relies on pre-acquired pairs of non-rigidly aligned T2-weighted MRI and CT images of the neck. To synthesise a pseudo CT, all the MRIs in the database are first registered to the target MRI using a robust affine followed by a deformable registration. An initial pseudo CT is obtained by fusing the mapped atlases according to their morphological similarity to the target. This initial pseudo CT is then combined with the target MR image in order to improve both the registration and fusion stages and refine the synthesis in the bone region.


Biomedical Physics & Engineering Express | 2017

A comprehensive evaluation of the accuracy of CBCT and deformable registration based dose calculation in lung proton therapy

Catarina Veiga; Guillaume Janssens; Thomas Baudier; L. Hotoiu; Sébastien Brousmiche; Jamie R. McClelland; Ching-Ling Teng; Lingshu Yin; Gary J. Royle; Boon-Keng Kevin Teo

The uncertainties in water equivalent thickness (WET) and accuracy of dose estimation using a virtual CT (vCT), generated from deforming the planning CT (pCT) onto the daily cone-beam CT (CBCT), were comprehensively evaluated in the context of lung malignancies and passive scattering proton therapy. The validation methodology utilized multiple CBCT datasets to generate the vCTs of twenty lung cancer patients. A correction step was applied to the vCTs to account for anatomical modifications that could not be modeled by deformation alone. The CBCT datasets included a regular CBCT (rCBCT) and synthetic CBCTs created from the rCBCT and rescan CT (rCT), which minimized the variation in setup between the vCT and the gold-standard image (i.e., rCT). The uncertainty in WET was defined as the voxelwise difference in WET between vCT and rCT, and calculated in 3D (planning target volume, PTV) and 2D (distal and proximal surfaces). The uncertainty in WET based dose warping was defined as the difference between the warped dose and a forward dose recalculation on the rCT. The overall root mean square (RMS) uncertainty in WET was 3.6 ± 1.8, 2.2 ± 1.4 and 3.3 ± 1.8 mm for the distal surface, proximal surface and PTV, respectively. For the warped dose, the RMS uncertainty of the voxelwise dose difference was 6% ± 2% of the maximum dose (%mD), using a 20% cut-off. The rCBCT resulted in higher uncertainties due to setup variability with the rCT; the uncertainties reported with the two synthetic CBCTs were similar. The vCT followed by a correction step was found to be an accurate alternative to rCT.


Radiotherapy and Oncology | 2017

Long term radiological features of radiation-induced lung damage

Catarina Veiga; David Landau; Jamie R. McClelland; Jonathan A. Ledermann; David J. Hawkes; Sam M. Janes; Anand Devaraj

PURPOSE To describe the radiological findings of radiation-induced lung damage (RILD) present on CT imaging of lung cancer patients 12 months after radical chemoradiation. MATERIAL AND METHODS Baseline and 12-month CT scans of 33 patients were reviewed from a phase I/II clinical trial of isotoxic chemoradiation (IDEAL CRT). CT findings were scored in three categories derived from eleven sub-categories: (1) parenchymal change, defined as the presence of consolidation, ground-glass opacities (GGOs), traction bronchiectasis and/or reticulation; (2) lung volume reduction, identified through reduction in lung height and/or distortions in fissures, diaphragm, anterior junction line and major airways anatomy, and (3) pleural changes, either thickening and/or effusion. RESULTS Six patients were excluded from the analysis due to anatomical changes caused by partial lung collapse and abscess. All remaining 27 patients had radiological evidence of lung damage. The three categories, parenchymal change, shrinkage and pleural change were present in 100%, 96% and 82% respectively. All patients had at least two categories of change present and 72% all three. GGOs, reticulation and traction bronchiectasis were present in 44%, 52% and 37% of patients. CONCLUSIONS Parenchymal change, lung shrinkage and pleural change are present in a high proportion of patients and are frequently identified in RILD. GGOs, reticulation and traction bronchiectasis are common at 12 months but not diagnostic.


Physics in Medicine and Biology | 2018

Toward adaptive radiotherapy for lung patients: feasibility study on deforming planning CT to CBCT to assess the impact of anatomical changes on dosimetry

A J Cole; Catarina Veiga; U Johnson; Derek D’Souza; N K Lalli; Jamie R. McClelland

Abstract Changes in lung architecture during a course of radiotherapy can alter the planned dose distribution to the extent that it becomes clinically unacceptable. This study aims to validate a quantitative method of determining whether a replan is required during the course of conformal radiotherapy. The proposed method uses deformable image registration (DIR) to flexibly map planning CT (pCT) data to the anatomy of online CBCT images. The resulting deformed CT (dCT) images are used as a basis for assessing the effect of anatomical change on dose distributions. The study used retrospective data from a sample of seven replanned lung patients. The settings of an in-house, open-source DIR algorithm were first optimised for CT-to-CBCT registrations of the anatomy of the thorax. Using these optimised parameters, each patient’s pCT was deformed to the CBCT acquired immediately before the replan. Registration accuracy was rigorously validated both geometrically and dosimetrically to confirm that the dCTs could reliably be used to inform replan decisions. A retrospective evaluation of the changes in dose delivered over time was then carried out for a single patient to demonstrate the clinical application of the proposed method. The geometric analysis showed good agreement between deformed structures and those same structures manually outlined on the CBCT images. Results were consistently better than those achieved with rigid-only registration. In the dosimetric analysis, dose distributions derived from the dCTs were found to match closely to the ‘gold standard’ replan CT (rCT) distributions across dose volume histogram and absolute dose difference measures. The retrospective analysis of serial CBCTs of a single patient produced reliable quantitative assessment of the dose delivery. Had the proposed method been available at the time of treatment, it would have enabled a more objective replan decision. DIR is a valuable clinical tool for dose recalculation in adaptive radiotherapy protocols for lung cancer patients.


Medical Physics | 2014

Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT‐to‐CBCT deformable registration for “dose of the day” calculations

Catarina Veiga; Jamie R. McClelland; Syed Moinuddin; A Lourenço; Kate Ricketts; James Annkah; Marc Modat; Sebastien Ourselin; D D'Souza; Gary J. Royle


Medical Physics | 2015

Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm

Catarina Veiga; A Lourenço; Syed Mouinuddin; Marcel van Herk; Marc Modat; Sebastien Ourselin; Gary J. Royle; Jamie R. McClelland


Medical Physics | 2015

Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer.

Albert K. Hoang Duc; Gemma Eminowicz; Ruheena Mendes; Swee‐Ling Wong; Jamie R. McClelland; Marc Modat; M. Jorge Cardoso; Alex F. Mendelson; Catarina Veiga; Timor Kadir; D D'Souza; Sebastien Ourselin


Archive | 2016

First clinical investigation of CBCT and deformable registration for adaptive proton therapy of lung cancer

Catarina Veiga; Guillaume Janssens; Ching-Ling Teng; Thomas Baudier; L. Hotoiu; Jamie R. McClelland; Gary J. Royle; Liyong Lin; Lingshu Yin; James M. Metz; Timothy D. Solberg; Zelig Tochner; Charles B. Simone; J McDonough; Boon-Keng Kevin Teo

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Gary J. Royle

University College London

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David J. Hawkes

University College London

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Marc Modat

University College London

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Tom Doel

University College London

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A Lourenço

University College London

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Guillaume Janssens

Université catholique de Louvain

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