Publications by authors named "A Vergara-Gil"

Implementation of radiopharmaceutical therapy dosimetry varies depending on the clinical application, dosimetry protocol, software, and ultimately the operator. Assessing clinical dosimetry accuracy and precision is therefore a challenging task. This work emphasizes some pitfalls encountered during a structured analysis, performed on a single-patient dataset consisting of SPECT/CT images by various participants using a standard protocol and clinically approved commercial software.

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Purpose: Dosimetry is rarely performed for the treatment of differentiated thyroid cancer patients with Na[I]I (radioiodine), and information regarding absorbed doses delivered is limited. Collection of dosimetry data in a multi-centre setting requires standardised quantitative imaging and dosimetry. A multi-national, multi-centre clinical study was performed to assess absorbed doses delivered to normal organs for differentiated thyroid cancer patients treated with Na[I]I.

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Clinical dosimetry in molecular radiotherapy (MRT) is a multi-step procedure, prone to uncertainties at every stage of the dosimetric workflow. These are difficult to assess, especially as some are complex or even impossible to measure experimentally. The DosiTest project was initiated to assess the variability associated with clinical dosimetry, by setting up a 'virtual' multicentric clinical dosimetry trial based on Monte Carlo (MC) modelling.

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Purpose: Monte Carlo modelling of SPECT imaging in Molecular Radiotherapy can improve activity quantification. Until now, SPECT modelling with GATE only considered circular orbit (CO) acquisitions. This cannot reproduce auto-contour acquisitions, where the detector head moves close to the patient to improve image resolution.

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Purpose: Patient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations.

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