Evidence map›Paper›PMID 31541526›Full record

ArticleJournal of applied clinical medical physics2019

Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom.

Richard Y Wu, Amy Y Liu, Tyler D Williamson, Jinzhong Yang, Paul G Wisdom, Xiaorong R Zhu, Steven J Frank, Clifton D Fuller, Gary B Gunn, Song Gao

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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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

10 authors.

Richard Y WuDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Amy Y LiuDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Tyler D WilliamsonDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jinzhong YangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Paul G WisdomDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Xiaorong R ZhuDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Steven J FrankDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Clifton D FullerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Gary B GunnDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Song GaoDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS CA016672NIH HHS
6 · The paper itself

Abstract

purposeKilo-voltage cone-beam computed tomography (CBCT) is widely used for patient alignment, contour propagation, and adaptive treatment planning in radiation therapy. In this study, we evaluated the accuracy of deformable image registration (DIR) for CBCT under various imaging protocols with different noise and patient dose levels.

methodsA physical phantom previously developed to facilitate end-to-end testing of the DIR accuracy was used with Varian Velocity v4.0 software to evaluate the performance of image registration from CT to CT, CBCT to CT, and CBCT to CBCT. The phantom is acrylic and includes several inserts that simulate different tissue shapes and properties. Deformations and anatomic changes were simulated by changing the rotations of both the phantom and the inserts. CT images (from a head and neck protocol) and CBCT images (from pelvis, head and "Image Gently" protocols) were obtained with different image noise and dose levels. Large inserts were filled with Mobil DTE oil to simulate soft tissue, and small inserts were filled with bone materials. All inserts were contoured before the DIR process to provide a ground truth contour size and shape for comparison. After the DIR process, all deformed contours were compared with the originals using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Both large and small volume of interests (VOIs) for DIR volume selection were tested by simulating a DIR process that included whole patient image volume and clinical target volumes (CTV) only (for CTVs propagation).

resultsFor cross-modality DIR registration (CT to CBCT), the DSC were >0.8 and the MDA were <3 mm for CBCT pelvis, and CBCT head protocols. For CBCT to CBCT and CT to CT, the DIR accuracy was improved relative to the cross-modality tests. For smaller VOIs, the DSC were >0.8 and MDA <2 mm for all modalities.

conclusionsThe accuracy of DIR depends on the quality of the CBCT image at different dose and noise levels.

Indexed as

AlgorithmsPhantoms, ImagingCone-Beam Computed TomographyHead and Neck NeoplasmsHumansImage Processing, Computer-AssistedOrgans at RiskQuality Assurance, Health CareRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedTomography, X-Ray Computedadaptive planCBCT image registrationdeformable image registrationdeformable phantom

Identifiers

PMID31541526
PMCPMC6806467

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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.