Intensity modulated radiation therapy with field rotation—a time-varying fractionation study

Dink, Delal; Langer, Márk; Rardin, Ronald L.; Pekny, Joseph F.; Reklaitis, Gintaras V.; Saka, Behlul

doi:10.1007/s10729-012-9190-2

Cited by 5 publications

(9 citation statements)

References 54 publications

(59 reference statements)

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“…Treatment information could easily be attached to such a database and previous tumors could be simulated for treatment plans as well. Research [12] has shown that using multiple beam angle sets over a series of treatments has the potential to improve outcomes. Unlike previous work that focused on finding a single best angle set, by sorting, we can find multiple good angle sets; these would allow for a greater distribution of angles to be used with time-varying plans.…”

Section: Discussionmentioning

confidence: 99%

Data mining to aid beam angle selection for intensity-modulated radiation therapy

Price

Golden

Wasil

et al. 2014

Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

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Research on the beam angle optimization problem for intensitymodulated radiation therapy (IMRT) has focused on developing optimization approaches to obtain a single highquality angle set for each patient. In this paper, we propose a population-based method to aid the beam angle selection process with the goal of significantly improving the efficiency of the process while identifying high-quality angle sets. We use a database of approximately 2,700 IMRT treatment plans for 10 patients with locally advanced head and neck cancer to train three data mining techniques (linear regression, neural networks, and k-nearest neighbor) to rank treatment plans based on potential quality. Using 5-fold cross-validation, we train our models to rank a list of 54 new beam angle plans (for a total of 50 lists) and then fully evaluate a set of the most promising plans. Our models can, choosing only three plans out of 54, correctly identify at least one of the top three plans up to 76% of the time. Furthermore, 34% of the time we find the top plan. By sorting the plans prior to full evaluation, we are able to find the better plans faster.

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Section: Discussionmentioning

confidence: 99%

Data mining to aid beam angle selection for intensity-modulated radiation therapy

Price

Golden

Wasil

et al. 2014

Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

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“…For intensity-modulated x-ray therapy (IMXT), approaches have been developed to allow for a large number of beams in the entire treatment while limiting the number of beams in a single fraction. Dink et al 16 proposed a field rotation method, in which multiple sets of coplanar beams were interchanged between fractions using a mixed integer linear program. Results showed an improvement of dose objectives based on this time-varying method.…”

Section: Introductionmentioning

confidence: 99%

Fraction‐variant beam orientation optimization for intensity‐modulated proton therapy

O’Connor

Ruan

et al. 2020

Medical Physics

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Purpose: To achieve a superior balance between dosimetry and the delivery efficiency of intensitymodulated proton therapy (IMPT) using as few beams as possible in a single fraction, we optimally vary beams in different fractions. Methods: In the optimization, 400~800 feasible noncoplanar beams were included in the candidate pool. For each beam, the doses of all scanning spots covering the target volume and a margin were calculated. The fraction-variant beam orientation optimization (FVBOO) problem was formulated to include three terms: two quadratic dose fidelity terms to penalize the deviation of planning target volume fractional dose and organs at risk (OAR) cumulative doses from prescription, respectively; an L2,1/2-norm group sparsity term to control the number of active beams per fraction to between 1 and 4. The Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was applied to solve this problem. FVBOO was tested on a patient with base-of-skull (BOS) tumor of 5 fractions (5f) and 30 fractions (30f) with an average number of active beams per fraction varying between 4 and 1. In addition, one bilateral head-and-neck (H&N) patient, and one esophageal cancer (ESG) patient of 30f were tested with about three active beams per fraction. The results were compared with IMPT plans that use fixed beams in each fraction. The fixed beams were selected using the group sparsity term with a fraction-invariant BOO (FIBOO) constraint. Results: Varying beams were chosen in either the 5f or 30f FVBOO plans. While similar number of beams per fraction was selected as the FIBOO plan, the FVBOO plans were able to spare the OARs better, with an average reduction of [Dmean, Dmax] from the FIBOO plans by [0.85, 2.08] Relative Biological Effective Gy (GyRBE) in the 5f plan and [1.87, 4.06] GyRBE in the 30f plans. While reducing the number of beams per fraction in the BOS patient, a three-beam/fraction 5f FVBOO plan performs comparably as the four-beam FIBOO plan and a two-beam/fraction 30f FVBOO plan still provides superior dosimetry. Conclusion: Fraction-variant beam orientation optimization allows the utilization of a larger beam solution space for superior dose distribution in IMPT while maintaining a practical number of beams in each fraction.

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“…IMRT with field rotation was studied in (Dink et al 2012), which first partitions a set of coplanar candidate beams into M disjoint subsets S 1 , …, S M , with each subset consisting of evenly spaced beams, and then assigns one of these M subsets to each treatment fraction. The particular subset that is selected varies from fraction to fraction.…”

Section: Introductionmentioning

confidence: 99%

Fraction-variant beam orientation optimization for non-coplanar IMRT

O’Connor

Nguyen

et al. 2018

Phys. Med. Biol.

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Conventional beam orientation optimization (BOO) algorithms for IMRT assume that the same set of beam angles is used for all treatment fractions. In this paper we present a BOO formulation based on group sparsity that simultaneously optimizes non-coplanar beam angles for all fractions, yielding a fraction-variant (FV) treatment plan. Beam angles are selected by solving a multi-fraction fluence map optimization problem involving 500-700 candidate beams per fraction, with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using the fast iterative shrinkage-thresholding algorithm. Our FV BOO algorithm is used to create five-fraction treatment plans for digital phantom, prostate, and lung cases as well as a 30-fraction plan for a head and neck case. A homogeneous PTV dose coverage is maintained in all fractions. The treatment plans are compared with fraction-invariant plans that use a fixed set of beam angles for all fractions. The FV plans reduced OAR mean dose and D values on average by 3.3% and 3.8% of the prescription dose, respectively. Notably, mean OAR dose was reduced by 14.3% of prescription dose (rectum), 11.6% (penile bulb), 10.7% (seminal vesicle), 5.5% (right femur), 3.5% (bladder), 4.0% (normal left lung), 15.5% (cochleas), and 5.2% (chiasm). D was reduced by 14.9% of prescription dose (right femur), 8.2% (penile bulb), 12.7% (proximal bronchus), 4.1% (normal left lung), 15.2% (cochleas), 10.1% (orbits), 9.1% (chiasm), 8.7% (brainstem), and 7.1% (parotids). Meanwhile, PTV homogeneity defined as D /D improved from .92 to .95 (digital phantom), from .95 to .98 (prostate case), and from .94 to .97 (lung case), and remained constant for the head and neck case. Moreover, the FV plans are dosimetrically similar to conventional plans that use twice as many beams per fraction. Thus, FV BOO offers the potential to reduce delivery time for non-coplanar IMRT.

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Intensity modulated radiation therapy with field rotation—a time-varying fractionation study

Cited by 5 publications

References 54 publications

Data mining to aid beam angle selection for intensity-modulated radiation therapy

Data mining to aid beam angle selection for intensity-modulated radiation therapy

Fraction‐variant beam orientation optimization for intensity‐modulated proton therapy

Fraction-variant beam orientation optimization for non-coplanar IMRT

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