Leaf sequencing algorithms for segmented multileaf collimation

Kamath, Srijit; Sahni, Sartaj; Li, Jonathan; Palta, Jatinder; Ranka, Sanjay

doi:10.1088/0031-9155/48/3/303

Cited by 74 publications

(104 citation statements)

References 17 publications

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“…However, because this method is labor intensive and because the intention of this work was to evaluate the implemented segmentation algorithm, such modifications were not included in our analysis. It was already reported 23 , 24 that the segmentation algorithm (11) implemented in KonRad, is one of the most efficient methods concerning the number of MUs. However, concerning the number of beam segments no such observation was made previously.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the KonRad IMRT and XiO treatment planning systems

Reitz

Miften

2008

J Applied Clin Med Phys

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Reducing the treatment time for IMRT patients is highly desirable. The objective of this work was to evaluate the new clinical Siemens KonRad inverse treatment planning system (TPS) and compare it to the CMS XiO TPS with special emphasis on the segmentation efficiency. For head and neck, liver and prostate cancer patients, step‐and‐shoot IMRT plans were designed using both CMS XiO and Siemens KonRad TPS. Number, direction and energy of beams used were the same in the plans from both systems for each treatment site. The plans were optimized to achieve the same clinical objectives concerning dose to the target volume and to the relevant organs‐at‐risk (OARs). The number of intensity levels were minimized until the clinical objectives could not be achieved anymore. Dose‐volume histograms (DVHs), mean and maximum doses were compared, as well as the number of beam segments and monitor units (MUs). The beams of each plan were delivered individually on a MapCheck device to verify the agreement between calculations and measurements to be less than 3%–3 mm distance‐to‐agreement. Plans optimized with KonRad resulted in fewer segments and lower number of MUs and therefore reduced delivery time on average by 28% or 3.6 min, while achieving similar dose distributions. CMS XiO plans exhibited a slightly steeper dose fall‐off outside the target volumes; however the difference was not clinically significant. DVHs to OARs were comparable. All calculated dose distributions passed the 3%–3 mm verification check.PACS numbers: 87.55.D

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Section: Discussionmentioning

confidence: 99%

Comparison of the KonRad IMRT and XiO treatment planning systems

Reitz

Miften

2008

J Applied Clin Med Phys

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“…An alternative optimality proof of the sweep algorithm can be found in Kamath et al (2003). Their methodology is based on analyzing the left and right leaf trajectories for each row A m , m ∈ M. These trajectory functions are at the focus of research in dynamic MLC models.…”

Section: Unconstrained Dt Problemmentioning

confidence: 99%

“…Figure 2 illustrates an example with row A m = (2, 3, 3, 5, 2, 2, 4, 4), the representation of each entry a mn as rod, and the corresponding trajectories. By proving that the step size of the left leaf trajectory in any position n is an upper bound on the number of MUs of any other feasible decompositions, Kamath et al (2003) establish the optimality of the decomposition delivered by their algorithm SINGLEPAIR for the case of single row DT problems. In combination with Lemma 2.1, this yields the optimality of their solution algorithm MULTIPAIR for the unconstrained DT problem, which is, again, a validity proof of the sweep algorithm.…”

Section: Unconstrained Dt Problemmentioning

confidence: 99%

“…In combination with Lemma 2.1, this yields the optimality of their solution algorithm MULTIPAIR for the unconstrained DT problem, which is, again, a validity proof of the sweep algorithm. The same bounding argument as in Kamath et al (2003) is used by Engel (2005) in his TNMU algorithm (total number of monitor units). Instead of using trajectories, he bases his work directly on the M × (N + 1) difference matrix…”

Section: Unconstrained Dt Problemmentioning

confidence: 99%

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Decomposition of matrices and static multileaf collimators: a survey

Ehrgott

Hamacher

Nußbaum

Optimization in Medicine

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Multileaf Collimators (MLC) consist of (currently 20-100) pairs of movable metal leaves which are used to block radiation in Intensity Modulated Radiation Therapy (IMRT). The leaves modulate a uniform source of radiation to achieve given intensity profiles. The modulation process is modeled by the decomposition of a given non-negative integer matrix into a non-negative linear combination of matrices with the (strict) consecutive ones property.In this paper we review some results and algorithms which can be used to minimize the time a patient is exposed to radiation (corresponding to the sum of coefficients in the linear combination), the set-up time (corresponding to the number of matrices used in the linear combination), and other objectives which contribute to an improved radiation therapy.

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“…Such algorithms are in use in existing radiotherapy equipment. Moreover, researchers have studied the mathematical structure of these problems to improve algorithm design or to establish the optimality of an algortihm (Ahuja and Hamacher, 2004;Baatar et al, 2004;Kamath et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

The influence of dose grid resolution on beam selection strategies in radiotherapy treatment design

Acosta

Ehrgott

Holder

et al.

Optimization in Medicine

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. (2008). The influence of dose grid resolution on beam selection strategies in radiotherapy treatment design. In C. J. S. Alves, P. M. Pardalos, & L. N. Vicente (Eds.), Springer AbstractThe design of a radiotherapy treatment includes the selection of beam angles (geometry problem), the computation of a fluence pattern for each selected beam angle (intensity problem), and finding a sequence of configurations of a multilef collimator to deliver the treatment (realization problem). While many mathematical optimization models and algorithms have been proposed for the intensity problem and (to a lesser extent) the realization problem, this is not the case for the geometry problem. In clinical practice, beam directions are manually selected by a clinician and are typically based on the clinician's experience. Solving the beam selection problem optimally is beyond capability of current optimization algorithms and software. However, heuristic methods have been proposed. In this paper we compare various heuristic approaches on a clinical case. In particular, we study the influence of dose point resolution on the performance of these heuristics. We also compare the solutions obtained by the heuristics with those achieved by a clinician using a commercial planning system.

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Leaf sequencing algorithms for segmented multileaf collimation

Cited by 74 publications

References 17 publications

Comparison of the KonRad IMRT and XiO treatment planning systems

Comparison of the KonRad IMRT and XiO treatment planning systems

Decomposition of matrices and static multileaf collimators: a survey

The influence of dose grid resolution on beam selection strategies in radiotherapy treatment design

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