Proton therapy monitoring: spatiotemporal emission reconstruction with prompt gamma timing and implementation with PET detectors

Pennazio, Francesco; Ferrero, Veronica; D'Onghia, Grazia; Garbolino, S.; Fiorina, Elisa; Villarreal, Oscar Ariel Martì; Milián, Félix Más; Monaco, V.; Monti, V.; Patera, Alessandra; Werner, J.; Wheadon, R.; Rafecas, M.

doi:10.1088/1361-6560/ac5765

Cited by 27 publications

(27 citation statements)

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“…All spatio-temporal emission distributions were reconstructed here with a binning of 50 ps (0-5 ns) and 0.25 cm (−20-20 cm). For a full description of the algorithm, refer to [16].…”

Section: The Ser-pgt Model: a Quick Recapmentioning

confidence: 99%

“…Focusing on the Prompt-Gamma-Timing (PGT) technique, the measurement of the Time-Of-Flight (TOF), i.e. the difference between the detection time of prompt photons and the delivery time of primary protons, is exploited to gain information about the beam [13][14][15][16]. The TOF distribution depends on the prompt photon emission points and emission times, whose cumulative distribution is related to the average motion of the primary particles inside the target.…”

Section: Introductionmentioning

confidence: 99%

“…In an attempt to propose a solution to the long-standing issue of how to reach an optimized, fast patient-tailored treatment planning, we recently introduced a reconstruction procedure with which to assess the primary particle range from PGT measurements [16]. The procedure, called Spatio-temporal Emission Reconstruction (SER-PGT), outputs a 2D-distribution of the emission of prompt photons in the space-time domain.…”

Section: Introductionmentioning

confidence: 99%

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Estimating the stopping power distribution during proton therapy: A proof of concept

et al. 2022

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Objective: We introduce a new treatment verification technique to estimate the primary particle’s stopping power from prompt gamma timing measurements in proton therapy.Approach: The starting point is the Spatio-temporal Emission Recostruction technique, which provides the time-depth distribution of the emitted prompt photons with a multiple Prompt-Gamma Timing detector setup based on Lanthanum Bromide crystals. A dedicated formalism based on an analytical approximation of the stopping power is developed to obtain the desired information. Its performance is evaluated in a proof of concept configuration via Monte Carlo simulations of monochromatic proton beams impinging on a homogeneous PMMA phantom.Main Results: Results indicate stopping power estimations as good as 3.8% with respect to NIST values, and range estimations within 0.3 cm (standard deviation), when considering 250 ps FWHM timing resolution.Significance: The current study shows, for the first time, the feasibility of evaluating the stopping power of primary beams with a technique that can be performed in-vivo, opening up new possibilities in the field of treatment verification and therapy optimization.

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“…All spatio-temporal emission distributions were reconstructed here with a binning of 50 ps (0-5 ns) and 0.25 cm (−20-20 cm). For a full description of the algorithm, refer to [16].…”

Section: The Ser-pgt Model: a Quick Recapmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimating the stopping power distribution during proton therapy: A proof of concept

et al. 2022

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“…The spatial, temporal and energy distributions of prompt gamma-rays have been shown to correlate strongly with the Bragg peak position in the patient [4]. As a light-weight, collimator-free technique, that can be easily integrated into existing systems, prompt gamma-ray timing (PGT) [5] has gained increasing interest for this purpose in recent years [6][7][8]. A longer proton range translates into a longer time-offlight of the particles.…”

Section: Introductionmentioning

confidence: 99%

Multivariate statistical modelling to improve particle treatment verification: Implications for prompt gamma-ray timing

Schellhammer

Wiedkamp²,

Löck³

et al. 2022

Front. Phys.

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We present an improved method for in-vivo proton range verification by prompt gamma-ray timing based on multivariate statistical modelling. To this end, prompt gamma-ray timing distributions acquired during pencil beam irradiation of an acrylic glass phantom with air cavities of different thicknesses were analysed. Relevant distribution features were chosen using forward variable selection and the Least Absolute Shrinkage and Selection Operator (LASSO) from a feature assortment based on recommendations of the Image Biomarker Standardisation Initiative. Candidate models were defined by multivariate linear regression and evaluated based on their coefficient of determination R2 and root mean square error RMSE. The newly developed models showed a clearly improved predictive power (R2 > 0.7) compared to the previously used models (R2 < 0.5) and allowed for the identification of introduced air cavities in a scanned treatment field. These results demonstrate that elaborate statistical models can enhance prompt gamma-ray based treatment verification and increase its potential for routine clinical application.

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“…This topic will not be described in this review. Additionally, proton therapy-specific adaptive strategies or possibilities, such as in vivo dosimetry using prompt gamma measurements [ 16 ], will not be discussed in this review.…”

Section: Introductionmentioning

confidence: 99%

Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer

Ridder

Raaijmakers

Pameijer

et al. 2022

Cancers

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In recent years, MRI-guided radiotherapy (MRgRT) has taken an increasingly important position in image-guided radiotherapy (IGRT). Magnetic resonance imaging (MRI) offers superior soft tissue contrast in anatomical imaging compared to computed tomography (CT), but also provides functional and dynamic information with selected sequences. Due to these benefits, in current clinical practice, MRI is already used for target delineation and response assessment in patients with head and neck squamous cell carcinoma (HNSCC). Because of the close proximity of target areas and radiosensitive organs at risk (OARs) during HNSCC treatment, MRgRT could provide a more accurate treatment in which OARs receive less radiation dose. With the introduction of several new radiotherapy techniques (i.e., adaptive MRgRT, proton therapy, adaptive cone beam computed tomography (CBCT) RT, (daily) adaptive radiotherapy ensures radiation dose is accurately delivered to the target areas. With the integration of a daily adaptive workflow, interfraction changes have become visible, which allows regular and fast adaptation of target areas. In proton therapy, adaptation is even more important in order to obtain high quality dosimetry, due to its susceptibility for density differences in relation to the range uncertainty of the protons. The question is which adaptations during radiotherapy treatment are oncology safe and at the same time provide better sparing of OARs. For an optimal use of all these new tools there is an urgent need for an update of the target definitions in case of adaptive treatment for HNSCC. This review will provide current state of evidence regarding adaptive target definition using MR during radiotherapy for HNSCC. Additionally, future perspectives for adaptive MR-guided radiotherapy will be discussed.

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Proton therapy monitoring: spatiotemporal emission reconstruction with prompt gamma timing and implementation with PET detectors

Cited by 27 publications

References 50 publications

Estimating the stopping power distribution during proton therapy: A proof of concept

Estimating the stopping power distribution during proton therapy: A proof of concept

Multivariate statistical modelling to improve particle treatment verification: Implications for prompt gamma-ray timing

Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer

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