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Title: Equivalent Dose Determination Using Components of IRSL Decay Curves

Abstract

To determine the equivalent dose (ED) using conventional methods any part (or all) of the optically stimulated luminescence (OSL) decay curve can be chosen as representative luminescence signal. Recently several studies investigated the shape of OSL decay curves and showed that the luminescence emission can be decomposed into fast, medium and slow components. From this point, in this work, the ED values determined using multiple aliquots process (MAAD)for geological sample were recalculated taking into account for these components from their IRSL decay curves and the results were compared. The IRSL decay curves were decomposed using a simple fitting procedure. The ED was obtained using IRSL components and compared with those obtained by standard methods.

Authors:
;  [1]
  1. Gazi University, Faculty of Arts and Sciences, Ankara (Turkey)
Publication Date:
OSTI Identifier:
21057187
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 899; Journal Issue: 1; Conference: 6. international conference of the Balkan Physical Union, Istanbul (Turkey), 22-26 Aug 2006; Other Information: DOI: 10.1063/1.2733269; (c) 2007 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; COMPARATIVE EVALUATIONS; DOSE EQUIVALENTS; DOSIMETRY; INFRARED RADIATION; PHOTOLUMINESCENCE; RADIOACTIVITY

Citation Formats

Tanir, G., and Boeluekdemir, M. H. Equivalent Dose Determination Using Components of IRSL Decay Curves. United States: N. p., 2007. Web. doi:10.1063/1.2733269.
Tanir, G., & Boeluekdemir, M. H. Equivalent Dose Determination Using Components of IRSL Decay Curves. United States. doi:10.1063/1.2733269.
Tanir, G., and Boeluekdemir, M. H. Mon . "Equivalent Dose Determination Using Components of IRSL Decay Curves". United States. doi:10.1063/1.2733269.
@article{osti_21057187,
title = {Equivalent Dose Determination Using Components of IRSL Decay Curves},
author = {Tanir, G. and Boeluekdemir, M. H.},
abstractNote = {To determine the equivalent dose (ED) using conventional methods any part (or all) of the optically stimulated luminescence (OSL) decay curve can be chosen as representative luminescence signal. Recently several studies investigated the shape of OSL decay curves and showed that the luminescence emission can be decomposed into fast, medium and slow components. From this point, in this work, the ED values determined using multiple aliquots process (MAAD)for geological sample were recalculated taking into account for these components from their IRSL decay curves and the results were compared. The IRSL decay curves were decomposed using a simple fitting procedure. The ED was obtained using IRSL components and compared with those obtained by standard methods.},
doi = {10.1063/1.2733269},
journal = {AIP Conference Proceedings},
number = 1,
volume = 899,
place = {United States},
year = {Mon Apr 23 00:00:00 EDT 2007},
month = {Mon Apr 23 00:00:00 EDT 2007}
}
  • Purpose: Accurate modeling of rectal complications based on dose-volume histogram (DVH) data are necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different equivalent uniform dose (EUD)-based and dose-volume-based normal tissue complication probability (NTCP) models to rectal wall DVHs and follow-up data for 319 prostate cancer patients to identify the dosimetric factors most predictive for Grade {>=} 2 rectal bleeding. Methods and Materials: Data for 319 patients treated at the William Beaumont Hospital with three-dimensional conformal radiotherapy (3D-CRT) under an adaptive radiotherapy protocol were used for this study. The following models were considered: (1) Lyman modelmore » and (2) logit-formula with DVH reduced to generalized EUD (3) serial reconstruction unit (RU) model (4) Poisson-EUD model, and (5) mean dose- and (6) cutoff dose-logistic regression model. The parameters and their confidence intervals were determined using maximum likelihood estimation. Results: Of the patients, 51 (16.0%) showed Grade 2 or higher bleeding. As assessed qualitatively and quantitatively, the Lyman- and Logit-EUD, serial RU, and Poisson-EUD model fitted the data very well. Rectal wall mean dose did not correlate to Grade 2 or higher bleeding. For the cutoff dose model, the volume receiving > 73.7 Gy showed most significant correlation to bleeding. However, this model fitted the data more poorly than the EUD-based models. Conclusions: Our study clearly confirms a volume effect for late rectal bleeding. This can be described very well by the EUD-like models, of which the serial RU- and Poisson-EUD model can describe the data with only two parameters. Dose-volume-based cutoff-dose models performed wor0008.« less
  • Purpose: To demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination. Methods and Materials: Patients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD wasmore » calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate {>=}20% were plotted. Results: The 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD. Conclusions: The atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.« less
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