Evidence map›Paper›PMID 25471948›Full record

ArticleMedical physics2014

Accuracy of surface registration compared to conventional volumetric registration in patient positioning for head-and-neck radiotherapy: a simulation study using patient data.

Youngjun Kim, Ruijiang Li, Yong Hum Na, Rena Lee, Lei Xing

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Medical physics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
    Article
  4. Review
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  12. Evaluation of cone-beam computed tomography image quality assurance for Vero4DRT system.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology
    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

5 authors at 2 institutions in 2 countries.

Youngjun KimDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305 and Center for Bionics, Korea Institute of Science and Technology, Seoul 136-791, South Korea.
Ruijiang LiDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305.
Yong Hum NaDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305.
Rena LeeDepartment of Radiation Oncology, Ewha Womans University School of Medicine, Seoul 158-710, South Korea.
Lei XingDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305.
Stanford University · USEwha Womans University · KR

Funding

Computational Tools for Next Generation Volumetric Cone Beam Computed TomographyR01EB016777 · NIBIB · STANFORD UNIVERSITY · PI XING, LEI · 2013 to 2016
$2.1M
NIBIB NIH HHS R01 EB016777NIBIB NIH HHS R01EB016777
6 · The paper itself

Abstract

purpose3D optical surface imaging has been applied to patient positioning in radiation therapy (RT). The optical patient positioning system is advantageous over conventional method using cone-beam computed tomography (CBCT) in that it is radiation free, frameless, and is capable of real-time monitoring. While the conventional radiographic method uses volumetric registration, the optical system uses surface matching for patient alignment. The relative accuracy of these two methods has not yet been sufficiently investigated. This study aims to investigate the theoretical accuracy of the surface registration based on a simulation study using patient data.

methodsThis study compares the relative accuracy of surface and volumetric registration in head-and-neck RT. The authors examined 26 patient data sets, each consisting of planning CT data acquired before treatment and patient setup CBCT data acquired at the time of treatment. As input data of surface registration, patient's skin surfaces were created by contouring patient skin from planning CT and treatment CBCT. Surface registration was performed using the iterative closest points algorithm by point-plane closest, which minimizes the normal distance between source points and target surfaces. Six degrees of freedom (three translations and three rotations) were used in both surface and volumetric registrations and the results were compared. The accuracy of each method was estimated by digital phantom tests.

resultsBased on the results of 26 patients, the authors found that the average and maximum root-mean-square translation deviation between the surface and volumetric registrations were 2.7 and 5.2 mm, respectively. The residual error of the surface registration was calculated to have an average of 0.9 mm and a maximum of 1.7 mm.

conclusionsSurface registration may lead to results different from those of the conventional volumetric registration. Only limited accuracy can be achieved for patient positioning with an approach based solely on surface information.

Indexed as

AlgorithmsComputer SimulationCone-Beam Computed TomographyHeadHead and Neck NeoplasmsHumansImaging, Three-DimensionalModels, BiologicalNeckPatient PositioningPhantoms, ImagingRadiotherapy, Image-Guided

Identifiers

PMID25471948
PMCPMC4235652
OpenAlexW2068096908

What OpenQuestion holds

Textmetadata
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.