A multiobjective gradient-based dose optimization algorithm for external beam conformal radiotherapy

Cotrutz, C.; Lahanas, Michael; Kappas, Constantin; Baltas, Dimos

doi:10.1088/0031-9155/46/8/309

Cited by 99 publications

(70 citation statements)

References 19 publications

(19 reference statements)

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“…A recent focus of interest is multiobjective (MO) optimization, first introduced in (Cotrutz et al, 2001), which results in a representative set of Pareto-efficient solutions for various conflicting optimization objectives. Craft et al (Craft et al, 2005) showed how to find the Pareto-efficient space of solutions for MO optimization, and developed an interface for the planner to examine the way the tradeoffs change when the optimization parameters are altered.…”

Section: Tunable Parameters In Imrt Objective Functionsmentioning

confidence: 99%

Reduced-order parameter optimization for simplifying prostate IMRT planning

Radke

Happersett

et al. 2007

Phys. Med. Biol.

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Abstract.Intensity-modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time manually adjusting IMRT optimization parameters such as dose limits and costlet weights in order to obtain a clinically acceptable plan. In this paper, we describe two main advances that simplify the parameter adjustment process for five-field prostate IMRT planning. First, we report the results of a sensitivity analysis that quantifies the effect of each hand-tunable parameter of the IMRT cost function on each clinical objective and the overall quality of the resulting plan. Second, we show that a recursive random search over the 6 most sensitive parameters as an outer loop in IMRT planning can quickly and automatically determine parameters for the cost function that lead to a plan meeting the clinical requirements. Our experiments on a 10-patient dataset show that for 70% of the cases, we can automatically determine a plan in 10 minutes (on the average) that is either clinically acceptable or requires only minor adjustment by the planner. The outer loop optimization can be easily integrated into a traditional IMRT planning system.

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Section: Tunable Parameters In Imrt Objective Functionsmentioning

confidence: 99%

Reduced-order parameter optimization for simplifying prostate IMRT planning

Radke

Happersett

et al. 2007

Phys. Med. Biol.

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“…This means that IMRT and IMPT cannot be exploited to their full potential owing to limitations with inverse planning [58]. The concept of multi-objective Pareto optimisation (often known as MCO) has been introduced into radiotherapy treatment planning to overcome these problems [59]. A Pareto optimal treatment plan is not a single plan but a database of plans where each one represents a Pareto optimal solution which cannot be improved without worsening at least one other parameter [58].…”

Section: Optimisation Functions For Robust Proton Planningmentioning

confidence: 99%

Treatment planning optimisation in proton therapy

McGowan¹,

Burnet²,

Lomax³

2013

BJR

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ABSTRACT. The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions. The ability to create and deliver the ideal treatment plan, where the target volume receives 100% of the prescribed dose and normal tissue receives 0%, is the holy grail of radiation therapy [1]. It is, however, impossible to achieve this perfect balance. Instead, multiple trade-offs are required to achieve a clinically acceptable plan, so the problem becomes one of optimisation. There are many factors that can affect how ''optimised'' a patient's treatment can be. This review focuses on the challenges of proton therapy plan optimisation, particularly in regard to range uncertainties, and how to incorporate them into the plan evaluation and verification process.The nature of proton therapy makes the aim of cure without complications potentially more achievable, owing to the highly localised deposition of dose in the characteristic Bragg peak [2]. This relates predominantly to the ability to deliver high doses of radiation close to normal tissue structures, which would be dose limiting in conventional X-ray treatments, and to the finite range of protons, which results in a reduced integral dose to surrounding normal tissues.From a clinical perspective, the exact role of proton therapy has yet to be defined. However, for childhood cancers, proton therapy delivers a lower dose to tissues around the tumour than X-rays, resulting in less growth disturbance and l...

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“…is the structure-specific the importance factor. The values of the importance factors were determined empirically [27][28][29][30][31]. D?…”

Section: Bevd-guided Beam Orientation Optimizationmentioning

confidence: 99%

“…This Concept Award was awarded to the principal investigator (PI) for the period of July 1, 2001 June 30,2002. Because of the late arrival of the postdoctoral fellow (Dr. David Y. Yang) for this project, we have filed a no-cost extension to June 31, 2003 (see attached Assistance Agreement).…”

Section: Introductionmentioning

confidence: 99%

Combining Electron With Intensity Modulated Photon Beams for Breast Cancer

Liu¹

2003

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A multiobjective gradient-based dose optimization algorithm for external beam conformal radiotherapy

Cited by 99 publications

References 19 publications

Reduced-order parameter optimization for simplifying prostate IMRT planning

Reduced-order parameter optimization for simplifying prostate IMRT planning

Treatment planning optimisation in proton therapy

Combining Electron With Intensity Modulated Photon Beams for Breast Cancer

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