Evidence map›Paper›PMID 35118788›Full record

ArticleJournal of applied clinical medical physics2022

Offline generator for digitally reconstructed radiographs of a commercial stereoscopic radiotherapy image-guidance system.

John A Charters, Pascal Bertram, James M Lamb

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. 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
0.3field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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 citations in OpenAlex.

  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

3 authors at 2 institutions in 2 countries.

John A ChartersDepartment of Radiation Oncology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California, USA.
Pascal BertramBrainlab AG, Munich, Germany.
James M LambDepartment of Radiation Oncology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California, USA.
University of California, Los Angeles · USBrainlab (Germany) · DE

Funding

AHRQ HHS R01 HS026486
6 · The paper itself

Abstract

purposeImage-guided radiotherapy (IGRT) research sometimes involves simulated changes to patient positioning using retrospectively collected clinical data. For example, researchers may simulate patient misalignments to develop error detection algorithms or positioning optimization algorithms. The Brainlab ExacTrac system can be used to retrospectively "replay" simulated alignment scenarios but does not allow export of digitally reconstructed radiographs (DRRs) with simulated positioning variations for further analysis. Here we describe methods to overcome this limitation and replicate ExacTrac system DRRs by using projective geometry parameters contained in the ExacTrac configuration files saved for every imaged subject.

methodsTwo ExacTrac DRR generators were implemented, one with custom MATLAB software based on first principles, and the other using libraries from the Insight Segmentation and Registration Toolkit (ITK). A description of perspective projections for DRR rendering applications is included, with emphasis on linear operators in real projective space

resultsManual landmarks selected between the corresponding DRR generators across patient and phantom images have an average displacement of 1.15 mm. For elastix image registrations, we found that absolute value vertical and horizontal translations were 0.18 and 0.35 mm on average, respectively. Rigid rotations were within 0.002 degrees.

conclusionCustom and ITK-based algorithms successfully reproduce ExacTrac DRRs and have the distinctive advantage of incorporating any desired 6D couch position. An open-source repository is provided separately for users to implement in IGRT patient positioning research.

Indexed as

RadiosurgeryRadiotherapy, Image-GuidedHumansPhantoms, ImagingRadiotherapy Planning, Computer-AssistedRetrospective StudiesDRRExacTracIGRTITKprojective geometry

Identifiers

PMID35118788
PMCPMC8906216
OpenAlexW4210562683

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.