Simulation and visualization of dose uncertainties due to interfractional organ motion

Maleike, Daniel; Unkelbach, Jan; Oelfke, Uwe

doi:10.1088/0031-9155/51/9/009

Cited by 40 publications

(36 citation statements)

References 12 publications

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“…The methodology they proposed does not account for the inter-sample variability. In radiation oncology applications, tolerance and prediction intervals were used to summarize dose uncertainties and organ motion for optimized treatment delivery [33] and for dose planning [34]. We do not know of any previous application of tolerance limits to summarize experimental evaluation of image registration.…”

Section: Discussionmentioning

confidence: 99%

Application of Tolerance Limits to the Characterization of Image Registration Performance

Fedorov

Wells

Kikinis

et al. 2014

IEEE Trans. Med. Imaging

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Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach results in a concise summary of the probability of registration failure, while accounting for the variability in the test data. The (β, γ) tolerance limit can be interpreted as a value of the input parameter that leads to successful registration outcome in at least 100β% of cases with the 100γ% confidence. The utility of the methodology is illustrated by summarizing the performance of a deformable registration algorithm evaluated in three different experimental setups of increasing complexity. Our examples are based on clinical data collected during MRI-guided prostate biopsy registered using publicly available deformable registration tool. The results indicate that the proposed methodology can be used to generate concise graphical summaries of the experiments, as well as a probabilistic estimate of the registration outcome for a future sample. Its use may facilitate improved objective assessment, comparison and retrospective stress-testing of deformable.

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Section: Discussionmentioning

confidence: 99%

Application of Tolerance Limits to the Characterization of Image Registration Performance

Fedorov

Wells

Kikinis

et al. 2014

IEEE Trans. Med. Imaging

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“…It was assumed that the motion PDF has three components, including axes of motion in the left–right (LR), anterior–posterior (AP), and superior–inferior (SI) directions, and the motion probability was based on the normal distribution with a standard deviation. The magnitudes of intrafraction motion for the CTV [18], rectum [14], and bladder [15] in the three axes (SI, LR, and AP) were used in the reports in the respective references and are summarized in Table 1. The values given for the CTV and rectum are two standard deviations, and those for the bladder are maximums.…”

Section: Methodsmentioning

confidence: 99%

Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy

et al. 2017

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This study evaluated a method for prostate intensity-modulated radiation therapy (IMRT) based on edge-enhanced (EE) intensity in the presence of intrafraction organ deformation using the data of 37 patients treated with step-and-shoot IMRT. On the assumption that the patient setup error was already accounted for by image guidance, only organ deformation over the treatment course was considered. Once the clinical target volume (CTV), rectum, and bladder were delineated and assigned dose constraints for dose optimization, each voxel in the CTV derived from the DICOM RT-dose grid could have a stochastic dose from the different voxel location according to the probability density function as an organ deformation. The stochastic dose for the CTV was calculated as the mean dose at the location through changing the voxel location randomly 1000 times. In the EE approach, the underdose region in the CTV was delineated and optimized with higher dose constraints that resulted in an edge-enhanced intensity beam to the CTV. This was compared to a planning target volume (PTV) margin (PM) approach in which a CTV to PTV margin equivalent to the magnitude of organ deformation was added to obtain an optimized dose distribution. The total monitor units, number of segments, and conformity index were compared between the two approaches, and the dose based on the organ deformation of the CTV, rectum, and bladder was evaluated. The total monitor units, number of segments, and conformity index were significantly lower with the EE approach than with the PM approach, while maintaining the dose coverage to the CTV with organ deformation. The dose to the rectum and bladder were significantly reduced in the EE approach compared with the PM approach. We conclude that the EE approach is superior to the PM with regard to intrafraction organ deformation.

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“…The advantage of this technique is that errors are no longer restricted to rigid body translations. Unkelbach et al [14][15][16][17] also developed a PWDDtype approach to PTP, based on optimization of the dose expectation ͑first moment͒. They noted that optimizing the average dose can lead to unsatisfactory doses in some cases.…”

Section: Introductionmentioning

confidence: 99%

Coverage optimized planning: Probabilistic treatment planning based on dose coverage histogram criteria

et al. 2010

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This work ͑i͒ proposes a probabilistic treatment planning framework, termed coverage optimized planning ͑COP͒, based on dose coverage histogram ͑DCH͒ criteria; ͑ii͒ describes a concrete proofof-concept implementation of COP within the PINNACLE treatment planning system; and ͑iii͒ for a set of 28 prostate anatomies, compares COP plans generated with this implementation to traditional PTV-based plans generated with planning criteria approximating those in the high dose arm of the Radiation Therapy Oncology Group 0126 protocol. Let D v denote the dose delivered to fractional volume v of a structure. In conventional intensity modulated radiation therapy planning, D v has a unique value derived from the static ͑planned͒ dose distribution. In the presence of geometric uncertainties ͑e.g., setup errors͒ D v assumes a range of values. The DCH is the complementary cumulative distribution function of D v . DCHs are similar to dose volume histograms ͑DVHs͒. Whereas a DVH plots volume v versus dose D, a DCH plots coverage probability Q versus D. For a given patient, Q is the probability ͑i.e., percentage of geometric uncertainties͒ for which the realized value of D v exceeds D. PTV-based treatment plans can be converted to COP plans by replacing DVH optimization criteria with corresponding DCH criteria. In this approach, PTVs and planning organ at risk volumes are discarded, and DCH criteria are instead applied directly to clinical target volumes ͑CTVs͒ or organs at risk ͑OARs͒. Plans are optimized using a similar strategy as for DVH criteria. The specific implementation is described. COP was found to produce better plans than standard PTV-based plans, in the following sense. While target OAR dose tradeoff curves were equivalent to those for PTV-based plans, COP plans were able to exploit slack in OAR doses, i.e., cases where OAR doses were below their optimization limits, to increase target coverage. Specifically, because COP plans were not constrained by a predefined PTV, they were able to provide wider dosimetric margins around the CTV, by pushing OAR doses up to, but not beyond, their optimization limits. COP plans demonstrated improved target coverage when averaged over all 28 prostate anatomies, indicating that the COP approach can provide benefits for many patients. However, the degree to which slack OAR doses can be exploited to increase target coverage will vary according to the individual patient anatomy. The proof-of-concept COP implementation investigated here utilized a probabilistic DCH criteria only for the CTV minimum dose criterion. All other optimization criteria were conventional DVH criteria. In a mature COP implementation, all optimization criteria will be DCH criteria, enabling direct planning control over probabilistic dose distributions. Further research is necessary to determine the benefits of COP planning, in terms of tumor control probability and/or normal tissue complication probabilities.

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Simulation and visualization of dose uncertainties due to interfractional organ motion

Cited by 40 publications

References 12 publications

Application of Tolerance Limits to the Characterization of Image Registration Performance

Application of Tolerance Limits to the Characterization of Image Registration Performance

Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy

Coverage optimized planning: Probabilistic treatment planning based on dose coverage histogram criteria

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