The effects of radiotherapy treatment uncertainties on the delivered dose distribution and tumour control probability (original) (raw)
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Tolerances in setup and dosimetric errors in the radiation treatment of breast cancer
International Journal of Radiation Oncology*Biology*Physics, 1993
Purpose: Treatment failure in radiation therapy, as well as unexpected complications, can be associated with set up changes or variations that can cause deviations from the prescribed radiation dose distribution both inside and outside the target volume. The effect of various deviations from the planned setup on the delivery of the prescribed radiation dose to the desired treatment volume was studied. Methods and Materials: Adding a second simulation was investigated as means of minimizing setup changes on treatment. The first simulation was used for planning the treatment and the second simulation was essentially a mock treatment. Dosimetric evaluations based on dose volume histograms were analyzed for each deviation in the setup. Results: In 95% of the patients, the frequency of the changes in the setup parameters between the second simulation and the treatment setup were reduced significantly from the changes that occurred between the first simulation and the second simulation. The changes in isocenter coordinates up to +l.O cm have minimal effects (f2%) on the dose distributions. Gantry angle variations up to +4" produce a change of less than fS% in the dose distribution within the target volume. However, this angular variation resulted in additional tissue irradiation outside of the desired treatment field (about 10 cm3 for a large patient). A gantry angle variation of +6" can change the volume of tissue that receives the prescribed dose by at least tlO%. In addition, such a change can increase the volume of tissue outside the desired treatment field that is irradiated. Conclusion: It is concluded that individually, deviations in one of the parameters from the planned setup of +l.O cm in isocenter position and +4" in gantry angle do not produce significant deviations from the planned dose distribution. However, a significant change in dose distribution is observed if the setup parameters are concurrently changed. A second simulation may minimize the deviations of the treatment setup from the planned setup and maximize the precision in dose delivery to the target volume.
Dosimetric Precision Requirements in Radiation Therapy
Acta Oncologica, 1984
Based on simple radiobiologic models the effect of the true distribution of absorbed dose in therapy beams on the response of uniform tumor volumes are investigated. Under assumption that the dose variation in the beam is small it is shown that the response of the tumor to radiation is determined by the mean dose to the tumor volume. Quantitative expressions are also given for the loss in tumor control probability as a function of the degree of dose variations around the mean dose level. When the dose variations are large the minimum tumor dose is best related to tumor control. It is finally shown that high tumor control rates can only be achieved with a very high accuracy in dose delivery. If the normalized dose response gradient is higher than 3, as is frequently the case, the relative standard deviation of mean dose in the target volume should be less than 3 per cent to achieve an absolute standard deviation in tumor control probability of less than 10 per cent.
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...
International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, 2017
A radiotherapy treatment margin formula has been analytically derived when a standard deviation (SD) of systematic positioning errors Σ is relatively small compared to an SD of random positioning errors σ. The margin formula for 0 ≤ Σ ≤ σ was calculated by linearly interpolating two boundaries at Σ = 0 and Σ = σ, assuming that the van Herk margin approximation of k 1 Σ + k 2 σ is valid at Σ = σ. It was shown that a margin formula for 0 ≤ Σ ≤ σ may be approximated by k 1 σ + k 2 Σ, leading to a more general form of k 1 max(Σ,σ) + k 2 min(Σ,σ) which is a piecewise linear approximation for any values of Σ and σ.
Ideal spatial radiotherapy dose distributions subject to positional uncertainties
Physics in Medicine and Biology, 2006
In radiotherapy a common method used to compensate for patient setup error and organ motion is to enlarge the clinical target volume (CTV) by a 'margin' to produce a 'planning target volume' (PTV). Using weighted power loss functions as a measure of performance for a treatment plan, a simple method can be developed to calculate the ideal spatial dose distribution (one that minimizes expected loss) when there is uncertainty. The spatial dose distribution is assumed to be invariant to the displacement of the internal structures and the whole patient. The results provide qualitative insights into the suitability of using a margin at all, and (if one is to be used) how to select a 'good' margin size. The common practice of raising the power parameters in the treatment loss function, in order to enforce target dose requirements, is shown to be potentially counter-productive. These results offer insights into desirable dose distributions and could be used, in conjunction with well-established inverse radiotherapy planning techniques, to produce dose distributions that are robust against uncertainties.
Evaluation of the effect of random setup errors on dose delivery in Intensity Modulated Radiotherapy
Polish Journal of Medical Physics and Engineering, 2020
Aim: To conduct a study on the effect of random setup errors inpatient for dose delivery in Intensity Modulated Radiotherapy plans using Octavius 4D phantom.Materials and methods: 11 patients with cancer of H&N were selected for this study. An IMRT plan was created for each patient. The IMRT quality assurance plans were transferred to Mosaiq workstation in a linear accelerator. These plans were delivered at the reference treatment position. Subsequently, the QA plans were delivered on the Octavius 4D phantom after introducing errors in various translational and rotational directions. The setup inaccuracies introduced varied from 1 mm to 5 mm along X, Y. These setup uncertainties were then introduced along X and Y direction simultaneously in equal measures. Similarly, IMRT plans were delivered also after introducing roll and yaw rotation of 1, 2 and 3 degrees in phantom. The deviation of gamma indices at all these positions was analyzed with respect to the reference setup position.Re...
Medical & Biological Engineering & Computing, 2010
In this study, we introduce a novel simulation technique to incorporate delineation errors into radiotherapy treatment margins and combine them with organ motion and set-up errors to investigate the cumulative dosimetric effects in different tumour sites. The effects of applying patient realignment correction protocols for radical treatments of prostate, lung and brain tumours were also modelled. Simulations were based on data from measurements using image-guidance techniques, including the use of fiducial markers in prostate and breathing correction techniques for the lung. The use of different sizes of planning target volume (PTV) margins was also evaluated. The prostate clinical target volumes’ V99% showed up to 3.2% improvement with reduction in treatment uncertainties. For the lung plans, the V99% increased by up to an average of 10% with increase in treatment margin size from 0.5 to 1.5 cm. This improvement was, however, at the detriment of the dose delivered to the critical organs where the maximum dose received by the spinal cord increased by up to 0.5 Gy per fraction. These results were used to deduce the possible margin reductions and dose escalation achievable with reduced uncertainties.
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.
2003
To evaluate the impact of interobserver variability in the contouring of gross tumor volumes (GTVs) and clinical target volumes (CTVs) on the global geometric accuracy in radiation therapy. Material and Methods: In a review of the currently available literature, the magnitude of interobserver variability is analyzed, causes and consequences are discussed. Uncertainties due to inconsistencies in contouring are related to other sources of geometric errors, particularly patient positioning and organ motion. Results: Interobserver variability is a major -for some tumor locations probably the largest -factor contributing to geometric inaccuracy. Causes are multifactorial and include image-and observer-related factors, such as the subjective interpretation of image information. Conclusion: Consequences to reduce interobserver variability are proposed, among others the selection of adequate imaging modalities, intensified radiologic training, and the use of telecommunication tools.
A new method for optimum dose distribution determination taking tumour mobility into account
Physics in Medicine and Biology, 1996
A method for determining the optimum dose distribution in the planning target volume is proposed when target volumes are deliberately enlarged to account for tumour mobility in external beam radiotherapy. The optimum dose distribution is a dose distribution that will result in an acceptable level of tumour control probability (TCP) in most of the arising cases of tumour dislocation. An assumption is made that the possible shifts of the tumour are subject to a Gaussian distribution with mean zero and known variance. The idea of a reduced (mean in ensemble) tumour cell density is introduced. On this basis, the target volume and dose distribution in it are determined. The tumour control probability as a function of the shift of the tumour has been calculated. The Monte Carlo method has been used to simulate TCP distributions corresponding to tumour mobility characterized by different variances. The obtained TCP distributions are independent of the variance of the mobility because the dose distribution in the planning target volume is prescribed so that the mobility variance is taken into account. For simplicity a one-dimensional model is used but three-dimensional generalization can be done.