Publications by authors named "Daniel Sanchez-Parcerisa"

Particle therapy (PT) represents a significant advancement in cancer treatment, precisely targeting tumor cells while sparing surrounding healthy tissues thanks to the unique depth-dose profiles of the charged particles. Furthermore, their linear energy transfer and relative biological effectiveness enhance their capability to treat radioresistant tumors, including hypoxic ones. Over the years, extensive research has paved the way for PT's clinical application, and current efforts aim to refine its efficacy and precision, minimizing the toxicities.

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Background: Recent proposals of high dose rate plans in protontherapy as well as very short proton bunches may pose problems to current beam monitor systems. There is an increasing demand for real-time proton beam monitoring with high temporal resolution, extended dynamic range and radiation hardness. Plastic scintillators coupled to optical fiber sensors have great potential in this context to become a practical solution towards clinical implementation.

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Ultra-high dose rate (UHDR) irradiation regimes have the potential to spare normal tissue while keeping equivalent tumoricidal capacity than conventional dose rate radiotherapy (CONV-RT). This has been called the FLASH effect. In this work, we present a new simulation framework aiming to study the production of radical species in water and biological media under different irradiation patterns.

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Range verification of clinical protontherapy systems via positron-emission tomography (PET) is not a mature technology, suffering from two major issues: insufficient signal from low-energy protons in the Bragg peak area and biological washout of PET emitters. The use of contrast agents including O, Zn or Cu, isotopes with a high cross section for low-energy protons in nuclear reactions producing PET emitters, has been proposed to enhance the PET signal in the last millimeters of the proton path. However, it remains a challenge to achieve sufficient concentrations of these isotopes in the target volume.

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Passive dosimetry with radiochromic films is widely used in proton radiotherapy, both in clinical and scientific environments, thanks to its simplicity, high spatial resolution and dose-rate independence. However, film under-response for low-energy protons, the so-called linear-energy transfer (LET) quenching, must be accounted and corrected for. We perform a meta-analysis on existing film under-response data with EBT, EBT2 and EBT3 GAFchromic™ films and provide a common framework to integrate it, based on the calculation of dose-averaged LET in the active layer of the films.

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Proton therapy has advantages and pitfalls comparing with photon therapy in radiation therapy. Among the limitations of protons in clinical practice we can selectively mention: uncertainties in range, lateral penumbra, deposition of higher LET outside the target, entrance dose, dose in the beam path, dose constraints in critical organs close to the target volume, organ movements and cost. In this review, we combine proposals under study to mitigate those pitfalls by using individually or in combination: (a) biological approaches of beam management in time (very high dose rate "FLASH" irradiations in the order of 100 Gy/s) and (b) modulation in space (a combination of mini-beams of millimetric extent), together with mechanical approaches such as (c) rotational techniques (optimized in partial arcs) and, in an effort to reduce cost, (d) gantry-less delivery systems.

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Proton radiotherapy has the potential to provide state-of-the-art dose conformality in the tumor area, reducing possible adverse effects on surrounding organs at risk. However, uncertainties in the exact location of the proton Bragg peak inside the patient prevent this technique from achieving full clinical potential. In this context, verification of the range of protons in patients is key to reduce uncertainty margins.

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Purpose: Clinical treatment planning protocols for protons recommend a uniform value radiobiological effectiveness (RBE) of protons of 1.1 throughout the treatment field, despite evidence from in-vitro and animal studies that proton RBE increases with linear energy transfer (LET), causing tissues placed distally to the target location to receive a presumably higher biological dose than estimated. While several voices in the medical physics community have advocated for variable RBE-based optimization, the uncertainties in RBE models have prevented its implementation in clinical practice, since an overestimation of RBE could cause significant target underdosage.

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Open-source, MATLAB-based treatment planning systems FoCa and matRAD were used in a pilot project for training prospective medical physicists and postgraduate physics students in treatment planning and beam modeling techniques for proton therapy. In the four exercises designed, students learnt how proton pencil beams are modeled and how dose is calculated in three-dimensional voxelized geometries, how pencil beam scanning plans (PBS) are constructed, the rationale behind the choice of spot spacing in patient plans, and the dosimetric differences between photon IMRT and proton PBS plans. Sixty students of two courses participated in the pilot project, with over 90% of satisfactory rating from student surveys.

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Purpose: Analytical algorithms have a limited accuracy when modeling very heterogeneous tumor sites. This work addresses the performance of a hybrid dose optimizer that combines both Monte Carlo (MC) and pencil beam (PB) dose engines to get the best trade-off between speed and accuracy for proton therapy plans.

Methods: The hybrid algorithm calculates the optimal spot weights (w) by means of an iterative optimization process where the dose at each iteration is computed by using a precomputed dose influence matrix based on the conventional PB plus a correction term c obtained from a MC simulation.

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The development of rotational proton therapy plans based on a pencil-beam-scanning (PBS) system has been limited, among several other factors, by the energy-switching time between layers, a system-dependent parameter that ranges between a fraction of a second and several seconds. We are investigating mono- and bi-energetic rotational proton modulated arc therapy (PMAT) solutions that would not be affected by long energy switching times. In this context, a systematic selection of the optimal proton energy for each arc is vital.

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