Evidence map›Paper›PMID 28834556›Full record

ArticleMedical physics2017

Deterministic direct aperture optimization using multiphase piecewise constant segmentation.

Dan Nguyen, Daniel O'Connor, Dan Ruan, Ke Sheng

Abstract read
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
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6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Dose prediction with deep learning for prostate cancer radiation therapy: Model adaptation to different treatment planning practices.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2020
    Article
  3. Article
  4. Article
  5. Many-isocenter optimization for robotic radiotherapy.Physics in medicine and biology · 2020
    Article
  6. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Dan NguyenDepartment of Radiation Oncology, University of Los Angeles California, Los Angeles, CA, USA.
Daniel O'ConnorDepartment of Radiation Oncology, University of Los Angeles California, Los Angeles, CA, USA.
Dan RuanDepartment of Radiation Oncology, University of Los Angeles California, Los Angeles, CA, USA.
Ke ShengDepartment of Radiation Oncology, University of Los Angeles California, Los Angeles, CA, USA.

Funding

Development of a versatile robotic radiation therapy systemR44CA183390 · NCI · RADIABEAM TECHNOLOGIES, LLC · PI SHENG, KE, YONEMOTO, JAY · 2017 to 2024
$5.8M
Motion Management of Pancreatic Cancer in MRI-Guided RadiotherapyR01CA188300 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SHENG, KE · 2015 to 2019
$1.7M
(NCI) Developing an Intermediate Energy Linac for Robotic RadiotherapyR43CA183390 · NCI · RADIABEAM TECHNOLOGIES, LLC · PI BOUCHER, SALIME · 2015 to 2016
$265k
NCI NIH HHS R01 CA188300NCI NIH HHS R43 CA183390NCI NIH HHS R44 CA183390
6 · The paper itself

Abstract

purposeDirect aperture optimization (DAO) attempts to incorporate machine constraints in the inverse optimization to eliminate the post-processing steps in fluence map optimization (FMO) that degrade plan quality. Current commercial DAO methods utilize a stochastic or greedy approach to search a small aperture solution space. In this study, we propose a novel deterministic direct aperture optimization that integrates the segmentation of fluence map in the optimization problem using the multiphase piecewise constant Mumford-Shah formulation.

methodsThe Mumford-Shah based direct aperture optimization problem was formulated to include an L2-norm dose fidelity term to penalize differences between the projected dose and the prescribed dose, an anisotropic total variation term to promote piecewise continuity in the fluence maps, and the multiphase piecewise constant Mumford-Shah function to partition the fluence into pairwise discrete segments. A proximal-class, first-order primal-dual solver was implemented to solve the large scale optimization problem, and an alternating module strategy was implemented to update fluence and delivery segments. Three patients of varying complexity-one glioblastoma multiforme (GBM) patient, one lung (LNG) patient, and one bilateral head and neck (H&N) patient with 3 PTVs-were selected to test the new DAO method. For each patient, 20 non-coplanar beams were first selected using column generation, followed by the Mumford-Shah based DAO (DAO

resultsDAO

conclusionsA novel deterministic direct aperture optimization formulation was developed and evaluated. It combines fluence map optimization and the multiphase piecewise constant Mumford-Shah segmentation into a unified framework, and the resulting optimization problem can be solved efficiently. Compared to the widely and commercially used simulated annealing DAO approach, it showed comparable dosimetry behavior for simple plans, and substantially improved OAR sparing, PTV coverage, PTV homogeneity, high dose spillage, and conformity for the more complex head and neck plan.

Indexed as

Radiotherapy, Intensity-ModulatedHumansNeoplasmsRadiotherapy Planning, Computer-Assisteddirect aperture optimizationpiecewise constant segmentation

Identifiers

PMID28834556
PMCPMC5689109

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.