Evidence map›Paper›PMID 34373188›Full record

ArticleZeitschrift fur medizinische Physik2022

Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy.

Philipp Aumüller, Andreas Rothfuss, Martin Polednik, Yasser Abo-Madyan, Michael Ehmann, Frank A Giordano, Sven Clausen

Erratum issuedAbstract read
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Article in Zeitschrift fur medizinische Physik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Philipp AumüllerDepartment of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany. Electronic address: philipp.aumueller@medma.uni-heidelberg.de.
Andreas RothfussFraunhofer IPA, Mannheim, Germany.
Martin PolednikDepartment of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany.
Yasser Abo-MadyanDepartment of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany.
Michael EhmannDepartment of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany.
Frank A GiordanoDepartment of Radiation Oncology, University Hospital Bonn, University of Bonn, Germany.
Sven ClausenDepartment of Radiation Oncology, University Medical Centre Mannheim, University Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRobotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.

methodsWe investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the "greedy optimizer". The "remove-seed algorithm" reduces the number of seeds in the high dose regions. The "depth-optimizer" varies the insertion depth of the needles. The "coverage-optimizer" locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D

resultsThe path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1%=2.9Gy, 1mm showed a pass rate of 98.5%. The dose parameters were V100=99.1±0.3%, V150=76.4±2.5%, V200=44.5±5.5% and D90=125.9±3.6Gy and 10.7±1.3 needles with 34.0±0.8 seeds were used. The median of the TPS total running time was 4.4minutes.

conclusionsThe TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy.

Indexed as

BrachytherapyRobotic Surgical ProceduresAlgorithmsNeedlesRadiotherapy DosageRadiotherapy Planning, Computer-AssistedBrachytherapyInverse optimizationLDRPath planningRoboticSeeds

Identifiers

PMID34373188
PMCPMC9948865

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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.