ArticleMedical physics2025
Automatic, machine-agnostic, convolution-based beam, and fluence modeling for Monte Carlo independent dose calculation.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundMonte Carlo (MC)-based independent dose calculation is increasingly sought after for plan- and delivery-specific quality assurance (QA) in modern radiotherapy because of its high accuracy. It is particularly valuable for online adaptive radiotherapy, where measurement-based QA solutions are impractical. However, challenges related to beam modeling, commissioning, and plan/delivery-specific fluence calculation have hindered its widespread clinical adoption. PURPOSE: We propose a generic, automated, convolution-based beam and fluence modeling method for MC dose calculation, assuming zero or very limited knowledge of the linear accelerator (LINAC) head, with all necessary information derived from water phantom measurements. Instead of conventional particle transport through beam modulation devices (the phase space-based approach), we developed a direct convolution-based method to model the effects of beam modulation devices on output factors and fluence for downstream particle transport in the patient's body.
methodsThe measurement data necessary for the beam model include the percent depth dose (PDD) profile of a reference field (typically 10 × 10 cm
resultsCompared to reference beam data, our calculations achieved average gamma passing rates of over 97% using the 2%/2 mm criteria. Compared to a sample of 20 clinical plans calculated by the treatment planning systems (TPS) across different beam modalities and treatment machines, our calculated dose achieved gamma passing rates of over 97% using the 3%/2 mm criteria with an average calculation time of less than 1 min.
conclusionsThe proposed machine-agnostic, convolution-based beam, and fluence modeling approach enabled efficient automatic commissioning for a wide range of clinical external photon beam machines. The fluence map-based dose calculation approached sub-minute dose calculation efficiency for arbitrary treatment plans. The proposed method has the potential to accelerate the adoption of MC calculation-based QA for online adaptive radiotherapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.