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Flatley, Robert; Stafford, Daniel

doi:10.5260/cca.199527

Cited by 2 publications

(4 citation statements)

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“…Grevillot et al (2011) used a percentage range difference, which at low energies could misrepresent the uncertainty. In our calibration, we assumed a uniform hit registration across scoring volumes and applied a standard deviation of a uniform distribution (Illowsky 2020). With this assumption, 0.3  mm range difference uncertainty is within what can be obtained from experimental measurements.…”

Section: Discussionmentioning

confidence: 99%

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A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Tjelta,

Fjæra,

Ytre-Hauge

et al. 2023

Phys. Med. Biol.

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Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated. Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating LET, variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results. The PBPs ranges were within ±0.3 mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the most considerable differences for the lung tumor patient.Significance. A procedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans. 

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Section: Discussionmentioning

confidence: 99%

“…(Illowsky 2020) and are the limit for range implemented. The assumption was a uniform hit registration across the scoring voxel.…”

mentioning

confidence: 99%

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Tjelta,

Fjæra,

Ytre-Hauge

et al. 2023

Phys. Med. Biol.

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“…According to statistical theory [11], [12], [13], if E1, E2 and En be independent events, the probabilities of those events are P1, P2 and Pn. Since the probability that event E1 happens is P1, then the probability that it does not happen is 1 -P1.…”

Section: E Probability Of Failure (Pof) Determinationmentioning

confidence: 99%

“…Thus, if there are i input events, each assigned with a probability of occurrence Pi, then the probability POR that any i events' occurring is given by [9], [11]:…”

Section: E Probability Of Failure (Pof) Determinationmentioning

confidence: 99%

Implementación del modelo tríada de riesgos, para determinar la probabilidad de falla en ductos: caso corrosión externa

Betancur-Ríos,

Rojas-Cataño

2022

Científica

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En este documento se describe y se trata un caso de aplicación en la industria de transporte de hidrocarburos por ductos del denominado algoritmo probabilístico de la tríada de riesgos discutido por Kent Muhlbauer (o algoritmo del Modelo de Referencia de Riesgo Cuantitativo), para establecer la probabilidad de falla (PoF) de un evento, en particular de la amenaza corrosión externa. El modelo utiliza matemática probabilística para combinar las variables y capturar tanto los impactos individuales como la acumulación de efectos menores, a través de las compuertas lógicas OR y AND. El uso de estas compuertas lógicas en modelos de riesgos representa una mejora evidente sobre la mayoría de los métodos más antiguos, ya que permite obtener una mejor representación de la forma en que se comportan los parámetros que materializan una amenaza. En este modelo, las variables que afectan la PoF se agrupan en tres categorías o elementos: exposición, mitigación y resistencia, que se representan en función de la amenaza o mecanismo de daño potencial al cual está sujeto el activo en estudio. Luego de obtener el valor de PoF, este se contrasta con los valores numéricos asociados con la probabilidad de falla en la Tabla 4.2 de API RP 581, se cruza con los resultados de CoF y de este modo se obtiene un ranking de riesgo que permite optimizar los recursos al aplicarlos a los activos de mayor riesgo. Se presentan los resultados luego de aplicarlos a la amenaza corrosión externa.

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Cited by 2 publications

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A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Implementación del modelo tríada de riesgos, para determinar la probabilidad de falla en ductos: caso corrosión externa

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