Evidence map›Paper›PMID 36995913›Full record

ArticleJournal of applied clinical medical physics2023

In-vivo quality assurance of dynamic tumor tracking (DTT) for liver SABR using EPID images.

Maryam Rostamzadeh, Kurt Luchka, Roy Ma, Mitchell Liu, Emma Dunne, Marie-Laure Camborde, Tania Karan, Ante Mestrovic, Alanah Bergman

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Maryam RostamzadehDepartment of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
Kurt LuchkaMedical Physics Department, BC Cancer-Vancouver, Vancouver, Canada.
Roy MaRadiation Oncology Department, BC Cancer-Vancouver, Vancouver, Canada.
Mitchell LiuRadiation Oncology Department, BC Cancer-Vancouver, Vancouver, Canada.
Emma DunneRadiation Oncology Department, BC Cancer-Vancouver, Vancouver, Canada.
Marie-Laure CambordeMedical Physics Department, BC Cancer-Vancouver, Vancouver, Canada.
Tania KaranMedical Physics Department, BC Cancer-Vancouver, Vancouver, Canada.ORCID https://orcid.org/0000-0002-9243-9672
Ante MestrovicMedical Physics Department, BC Cancer-Vancouver, Vancouver, Canada.
Alanah BergmanMedical Physics Department, BC Cancer-Vancouver, Vancouver, Canada.ORCID https://orcid.org/0000-0003-0546-7681

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess dynamic tumor tracking (DTT) target localization uncertainty for in-vivo marker-based stereotactic ablative radiotherapy (SABR) treatments of the liver using electronic-portal-imaging-device (EPID) images. The Planning Target Volume (PTV) margin contribution for DTT is estimated.

methodsPhantom and patient EPID images were acquired during non-coplanar 3DCRT-DTT delivered on a Vero4DRT linac. A chain-code algorithm was applied to detect Multileaf Collimator (MLC)-defined radiation field edges. Gold-seed markers were detected using a connected neighbor algorithm. For each EPID image, the absolute differences between the measured center-of-mass (COM) of the markers relative to the aperture-center (Tracking Error, (E PHANTOM STUDY: An acrylic cube phantom implanted with gold-seed markers was irradiated with non-coplanar 3DCRT-DTT beams and EPID images collected. Patient Study: Eight liver SABR patients were treated with non-coplanar 3DCRT-DTT beams. All patients had three to four implanted gold-markers. In-vivo EPID images were analyzed.

resultsPhantom Study: On the 125 EPID images collected, 100% of the markers were identified. The average ± SD of E

conclusionsMarker-based DTT uncertainty can be evaluated in-vivo on a field-by-field basis using EPID images. This information can contribute to PTV margin calculations for DTT.

Indexed as

NeoplasmsRadiosurgeryRadiotherapy, ConformalHumansLiverPhantoms, ImagingRadiometryRadiotherapy DosageRadiotherapy Planning, Computer-Assisteddetection algorithmdynamic tumor trackingEPIDmarker detectionposition verification

Identifiers

PMID36995913
PMCPMC10338758

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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.