A Novel Method for the Evaluation of Uncertainty in Dose–Volume Histogram Computation (original) (raw)
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Journal of Applied Clinical Medical Physics, 2010
A Histogram Analysis in Radiation Therapy (HART) program was primarily developed to increase the efficiency and accuracy of dose-volume histogram (DVH) analysis of large quantities of patient data in radiation therapy research. The program was written in MATLAB to analyze patient plans exported from the treatment planning system (Pinnacle 3) in the American Association of Physicists in Medicine/ Radiation Therapy Oncology Group (AAPM/RTOG) format. HART-computed DVH data was validated against manually extracted data from the planning system for five head and neck cancer patients treated with the intensity-modulated radiation therapy (IMRT) technique. HART calculated over 4000 parameters from the differential DVH (dDVH) curves for each patient in approximately 10-15 minutes. Manual extraction of this amount of data required 5 to 6 hours. The normalized root mean square deviation (NRMSD) for the HART-extracted DVH outcomes was less than 1%, or within 0.5% distance-to-agreement (DTA). This tool is supported with various user-friendly options and graphical displays. Additional features include optimal polynomial modeling of DVH curves for organs, treatment plan indices (TPI) evaluation, plan-specific outcome analysis (POA), and spatial DVH (zDVH) and dose surface histogram (DSH) analyses, respectively. HART is freely available to the radiation oncology community.
Margins for geometric uncertainty around organs at risk in radiotherapy
Radiotherapy and Oncology, 2002
Background and purpose: ICRU Report 62 suggests drawing margins around organs at risk (ORs) to produce planning organ at risk volumes (PRVs) to account for geometric uncertainty in the radiotherapy treatment process. This paper proposes an algorithm for drawing such margins, and compares the recommended margin widths with examples from clinical practice and discusses the limitations of the approach. Method: The use of the PRV defined in this way is that, despite the geometric uncertainties, the dose calculated within the PRV by the treatment planning system can be used to represent the dose in the OR with a certain confidence level. A suitable level is where, in the majority of cases (90%), the dose-volume histogram of the PRV will not under-represent the high-dose components in the OR. In order to provide guidelines on how to do this in clinical practice, this paper distinguishes types of OR in terms of the tolerance doses relative to the prescription dose and suggests appropriate margins for serial-structure and parallel-structure ORs. Results: In some instances of large and parallel ORs, the clinician may judge that the complication risk in omitting a margin is acceptable. Otherwise, for all types of OR, systematic, treatment preparation uncertainties may be accommodated by an OR ! PRV margin width of 1.3S. Here, S is the standard deviation of the combined systematic (treatment preparation) uncertainties. In the case of serial ORs or small, parallel ORs, the effects of blurring caused by daily treatment execution errors (set-up and organ motion) should be taken into account. Near a region of high dose, blurring tends to shift the isodoses away from the unblurred edge as shown on the treatment planning system by an amount that may be represented by 0.5s. This margin may be used either to increase or to decrease the margin already calculated for systematic uncertainties, depending upon the size of the tolerance dose relative to the detailed planned dose distribution. Where the detailed distribution is unknown before the OR is delineated, then the overall margin for serial or small parallel ORs should be 1.3S 1 0.5s. Examples are given where the application of this algorithm leads to margin widths around ORs similar to those in use clinically. Conclusions: Using PRVs is appropriate both for forward and inverse planning. Dose-volume histograms of PRVs for serial-and parallelstructure ORs require careful interpretation. Nevertheless, use of the proposed algorithms for drawing margins around both serial and parallel ORs can alert the dosimetrist/radiation oncologist to the possibility of high-dose complications in individual treatment plans, which might be missed if no such margins were drawn.
Acta Oncologica, 2000
OBJECTIVE: The present study was aimed at comparing conformal and non-conformal radiotherapy plans designed for patients with prostate cancer, by analyzing radiation doses in target volumes and organs at risk. MATERIALS AND METHODS: Radiotherapy plans for 40 patients with prostate cancer were analyzed. Conformal, conformal isocentric and non-conformal plans utilizing the source-surface distance were simulated for each of the patients for comparison of radiation dose in target volumes and organs at risk. For comparison purposes, dose-volume histograms for target volumes and organs at risk were analyzed. RESULTS: Median doses were significantly lower in the conformal planning, with 25%, 40% and 60% volumes in the rectum and 30% and 60% in the bladder. The median doses were significantly lower in the conformal planning analyzing the right and left coxofemoral joints. Maximum, mean and median doses in the clinical target volume and in the planned target volume were significantly higher in the conformal planning. CONCLUSION: The present study has demonstrated that the conformal radiotherapy planning for prostate cancer allows the delivery of higher doses to the target volume and lower doses to adjacent healthy tissues.
International Journal of Radiation Oncology*Biology*Physics, 2007
Purpose: To formulate uncertainty-based stopping criteria for Monte Carlo (MC) calculations of intensity-modulated radiotherapy and intensity-modulated arc therapy patient dose distributions and evaluate their influence on MC simulation times and dose characteristics. Methods and Materials: For each structure of interest, stopping criteria were formulated as follows: s rel # s rel,tol or Ds rel # D lim s rel,tol within $95% of the voxels, where s rel represents the relative statistical uncertainty on the estimated dose, D. The tolerated uncertainty (s rel,tol ) was 2%. The dose limit (D lim ) equaled the planning target volume (PTV) prescription dose or a dose value related to the organ at risk (OAR) planning constraints. An intensity-modulated radiotherapy-lung, intensity-modulated radiotherapy-ethmoid sinus, and intensity-modulated arc therapy-rectum patient case were studied. The PTV-stopping criteria-based calculations were compared with the PTV+OAR-stopping criteria-based calculations. Results: The MC dose distributions complied with the PTV-stopping criteria after 14% (lung), 21% (ethmoid), and 12% (rectum) of the simulation times of a 100 million histories reference calculation, and increased to 29%, 44%, and 51%, respectively, by the addition of the OAR-stopping criteria. Dose-volume histograms corresponding to the PTV-stopping criteria, PTV+OAR-stopping criteria, and reference dose calculations were indiscernible. The median local dose differences between the PTV-stopping criteria and the reference calculations amounted to 1.4% (lung), 2.1% (ethmoid), and 2.5% (rectum). Conclusions: For the patient cases studied, the MC calculations using PTV-stopping criteria only allowed accurate treatment plan evaluation. The proposed stopping criteria provided a flexible tool to assist MC patient dose calculations. The structures of interest and appropriate values of s rel,tol and D lim should be selected for each patient individually according to the clinical treatment planning goals. Ó 2007 Elsevier Inc.
Gamma histograms for radiotherapy plan evaluation
Radiotherapy and Oncology, 2006
Background and purpose: The technique known as the 'g evaluation method' incorporates pass-fail criteria for both distance-to-agreement and dose difference analysis of 3D dose distributions and provides a numerical index (g) as a measure of the agreement between two datasets. As the g evaluation index is being adopted in more centres as part of treatment plan verification procedures for 2D and 3D dose maps, the development of methods capable of encapsulating the information provided by this technique is recommended.
Uncertainties in the measurement of relative doses in radiotherapy
Polish Journal of Medical Physics and Engineering, 2021
Both the measurement of the dose and the measurement of its distribution, like any other measurements, are subject to measurement uncertainties. These uncertainties affect all dose calculations and dose distributions in a patient’s body during treatment planning in radiotherapy. Measurement uncertainty is not a medical physicist’s error, but an inevitable element of their work. Planning the dose distribution in a patient’s body, we often try to reduce it in the volume of critical organs (OaR - Organ at Risk) or increase the minimum dose in the PTV region by a few percent. It is believed that the measurement uncertainty should be taken into account in these calculations at the stage of treatment planning. The paper presents the method of calculating the measurement uncertainty for different physical quantities in radiotherapy as percentage depth dose, profile function and output factor, due to the fact that these quantities have a particular impact on the calculated dose distribution...
Physics in Medicine and Biology, 2015
A fast algorithm is constructed to facilitate dose calculation for a large number of randomly sampled treatment scenarios, each representing a possible realisation of a full treatment with geometric, fraction specific displacements for an arbitrary number of fractions. The algorithm is applied to construct a dose volume coverage probability map (DVCM) based on dose calculated for several hundred treatment scenarios to enable probabilistic evaluation of a treatment plan. For each treatment scenario, the algorithm calculates the total dose by perturbing a precalculated dose, separately for the primary and scatter dose components, for the nominal conditions. The ratio of the scenario specific accumulated fluence, and the average fluence for infinite number of fractions is used to perturb the pre-calculated dose. Irregularities in the accumulated fluence may cause numerical instabilities in the ratio, which is mitigated by regularisation through convolution with a dose pencil kernel. Compared to full dose calculations the algorithm demonstrates a speedup factor of ~1000. The comparisons to full calculations show 99% gamma index (2%/2mm) pass rate for a single highly modulated beam in a virtual water phantom subject to setup errors during five fractions. The gamma comparison show 100% pass rate in a moving tumour irradiated by a single beam in a lung-like virtual phantom. DVCM iso-probability lines computed with the fast algorithm, and with full dose calculations for each fraction, for a hypo-fractionated prostate case treated with rotational arc therapy treatment were almost indistinguishable.