Evidence map›Paper›PMID 34619830›Full record

ArticleRadiation oncology journal2021

Use of GammaPlan convolution algorithm for dose calculation on CT and cone-beam CT images.

Prabhakar Ramachandran, Ben Perrett, Orrie Dancewicz, Venkatakrishnan Seshadri, Catherine Jones, Akash Mehta, Matthew Foote

Abstract read
In one paragraph

Article in Radiation oncology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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5 · Who and what money

Authors and funding

7 authors.

Prabhakar RamachandranDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Ben PerrettDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Orrie DancewiczDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Venkatakrishnan SeshadriDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Catherine JonesDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Akash MehtaDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.
Matthew FooteDepartment of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to assess the suitability of using cone-beam computed tomography images (CBCTs) produced in a Leksell Gamma Knife (LGK) Icon system to generate electron density information for the convolution algorithm in Leksell GammaPlan (LGP) Treatment Planning System (TPS). MATERIALS AND

methodsA retrospective set of 30 LGK treatment plans generated for patients with multiple metastases was selected in this study. Both CBCTs and fan-beam CTs were used to provide electron density data for the convolution algorithm. Plan quality metrics such as coverage, selectivity, gradient index, and beam-on time were used to assess the changes introduced by convolution using CBCT (convCBCT) and planning CT (convCT) data compared to the homogeneous TMR10 algorithm.

resultsThe mean beam-on time for TMR10 and convCBCT was found to be 18.9 ± 5.8 minutes and 21.7 ± 6.6 minutes, respectively. The absolute mean difference between TMR10 and convCBCT for coverage, selectivity, and gradient index were 0.001, 0.02, and 0.0002, respectively. The calculated beam-on times for convCBCT were higher than the time calculated for convCT treatment plans. This is attributed to the considerable variation in Hounsfield values (HU) dependent on the position within the field of view.

conclusionThe artifacts from the CBCT's limited field-of-view and considerable HU variation need to be taken into account before considering the use of convolution algorithm for dose calculation on CBCT image datasets, and electron data derived from the onboard CBCT should be used with caution.

Indexed as

Brain metastasesComputed tomographyCone beam computed tomographyGamma knife radiosurgeryRadiation dosage

Identifiers

PMID34619830
PMCPMC8497862

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