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1.
Phys Med Biol ; 69(11)2024 May 14.
Artigo em Inglês | MEDLINE | ID: mdl-38663410

RESUMO

Objective. This study characterized optically-stimulated luminescent dosimeter (OSLD) nanoDots for use in a therapeutic carbon beam using the Imaging and Radiation Oncology Core (IROC) framework for remote output verification.Approach. The absorbed dose correction factors for OSLD (fading, linearity, beam quality, angularity, and depletion), as defined by AAPM TG 191, were characterized for carbon beams. For the various correction factors, the effect of linear energy transfer (LET) was examined by characterizing in both a low and high LET setting.Main results. Fading was not statistically different between reference photons and carbon, nor between low and high LET beams; thus, the standard IROC-defined exponential function could be used to characterize fading. Dose linearity was characterized with a linear fit; while low and high LET carbon linearity was different, these differences were small and could be rolled into the uncertainty budget if using a single linearity correction. A linear fit between beam quality and dose-averaged LET was determined. The OSLD response at various angles of incidence was not statistically different, thus a correction factor need not be applied. There was a difference in depletion between low and high LET irradiations in a primary carbon beam, but this difference was small over the standard five readings. The largest uncertainty associated with the use of OSLDs in carbon was because of thekQcorrection factor, with an uncertainty of 6.0%. The overall uncertainty budget was 6.3% for standard irradiation conditions.Significance. OSLD nanoDot response was characterized in a therapeutic carbon beam. The uncertainty was larger than for traditional photon applications. These findings enable the use of OSLDs for carbon absorbed dose measurements, but with less accuracy than conventional OSLD audit programs.


Assuntos
Carbono , Carbono/química , Carbono/uso terapêutico , Radiometria/métodos , Transferência Linear de Energia , Incerteza , Dosimetria por Luminescência Estimulada Opticamente/métodos , Dosagem Radioterapêutica , Humanos
2.
Med Phys ; 51(7): 5154-5158, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38598230

RESUMO

PURPOSE: As carbon ion radiotherapy increases in use, there are limited phantom materials for heterogeneous or anthropomorphic phantom measurements. This work characterized the radiological clinical equivalence of several phantom materials in a therapeutic carbon ion beam. METHODS: Eight materials were tested for radiological material-equivalence in a carbon ion beam. The materials were computed tomography (CT)-scanned to obtain Hounsfield unit (HU) values, then irradiated in a monoenergetic carbon ion beam to determine relative linear stopping power (RLSP). The corresponding HU and RLSP for each phantom material were compared to clinical carbon ion calibration curves. For absorbed dose comparison, ion chamber measurements were made in the center of a carbon ion spread-out Bragg peak (SOBP) in water and in the phantom material, evaluating whether the material perturbed the absorbed dose measurement beyond what was predicted by the HU-RLSP relationship. RESULTS: Polyethylene, solid water (Gammex and Sun Nuclear), Blue Water (Standard Imaging), and Techtron HPV had measured RLSP values that agreed within ±4.2% of RLSP values predicted by the clinical calibration curve. Measured RLSP for acrylic was 7.2% different from predicted. The agreement for balsa wood and cork varied between samples. Ion chamber measurements in the phantom materials were within 0.1% of ion chamber measurements in water for most materials (solid water, Blue Water, polyethylene, and acrylic), and within 1.9% for the rest of the materials (balsa wood, cork, and Techtron HPV). CONCLUSIONS: Several phantom materials (Blue Water, polyethylene, solid water [Gammex and Sun Nuclear], and Techtron HPV) are suitable for heterogeneous phantom measurements for carbon ion therapy. Low density materials should be carefully characterized due to inconsistencies between samples.


Assuntos
Radioterapia com Íons Pesados , Imagens de Fantasmas , Radioterapia com Íons Pesados/instrumentação , Calibragem , Tomografia Computadorizada por Raios X , Humanos
3.
Neurooncol Adv ; 4(1): vdac058, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35664554

RESUMO

Background: Stereotactic radiosurgery (SRS) is a common treatment for intracranial lesions. This work explores the state of SRS treatment delivery to characterize current treatment accuracy based on treatment parameters. Methods: NCI clinical trials involving SRS rely on an end-to-end treatment delivery on a patient surrogate (credentialing phantom) from the Imaging and Radiation Oncology Core (IROC) to test their treatment accuracy. The results of 1072 SRS phantom irradiations between 2012 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom performance. The following categories were evaluated in terms of how they predicted outcomes: year of irradiation, TPS algorithm, machine model, energy, and delivered field size. Results: Overall, only 84.6% of irradiations have met the IROC/NCI acceptability criteria. Pass rate has remained constant over time, while dose calculation accuracy has slightly improved. Dose calculation algorithm (P < .001), collimator (P = .024), and field size (P < .001) were statistically significant predictors of pass/fail. Specifically, pencil beam algorithms and cone collimators were more likely to be associated with failing phantom results. Random forest modeling identified the size of the field as the most important factor for passing or failing followed by algorithm. Conclusion: Constant throughout this retrospective study, approximately 15% of institutions fail to meet IROC/NCI standards for SRS treatment. In current clinical practice, this is particularly associated with smaller fields that yielded less accurate results. There is ongoing need to improve small field dosimetry, beam modeling, and QA to ensure high treatment quality, patient safety, and optimal clinical trials.

4.
Phys Med Biol ; 66(15)2021 07 30.
Artigo em Inglês | MEDLINE | ID: mdl-34252894

RESUMO

Microdosimetry is an important tool for assessing energy deposition distributions from ionizing radiation at cellular and cellular nucleus scales. It has served as an input parameter for multiple common mathematical models, including evaluation of relative biological effectiveness (RBE) of carbon ion therapy. The most common detector used for microdosimetry is the tissue-equivalent proportional counter (TEPC). Although it is widely applied, TEPC has various inherent uncertainties. Therefore, this work quantified the magnitude of TEPC measurement uncertainties and their impact on RBE estimates for therapeutic carbon beams. Microdosimetric spectra and frequency-, dose-, and saturation-corrected dose-mean lineal energy (****) were calculated using the Monte Carlo toolkit Geant4 for five monoenergetic and three spread-out Bragg peak carbon beams in water at every millimeter along the central beam axis. We simulated the following influences on these spectra from eight sources of uncertainty: wall effects, pulse pile-up, electronics, gas pressure, W-value, gain instability, low energy cut-off, and counting statistics. Statistic uncertainty was quantified as the standard deviation of perturbed values for each source. Bias was quantified as the difference between default lineal energy values and the mean of perturbed values for each systematic source. Uncertainties were propagated to RBE using the modified microdosimetric kinetic model (MKM). Variance introduced by statistic sources iny¯Fandy¯Daveraged 3.8% and 3.4%, respectively, and 1.5% iny*across beam depths and energies. Bias averaged 6.2% and 7.3% iny¯Fandy¯D,and 4.8% iny*.These uncertainties corresponded to 1.2 ± 0.9% on average in RBEMKM. The largest contributors to variance and bias were pulse pile-up and wall effects. This study established an error budget for microdosimetric carbon measurements by quantifying uncertainty inherent to TEPC measurements. It is necessary to understand how robust the measurement of RBE model input parameters are against this uncertainty in order to verify clinical model implementation.


Assuntos
Carbono , Radiometria , Método de Monte Carlo , Eficiência Biológica Relativa , Incerteza
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