Evidence map›Paper›PMID 31808307›Full record

ArticleJournal of applied clinical medical physics2020

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom.

Richard Y Wu, Amy Y Liu, Jinzhong Yang, Tyler D Williamson, Paul G Wisdom, Lawrence Bronk, Song Gao, David R Grosshan, David C Fuller, Gary B Gunn and 2 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

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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

12 authors at 1 institution in 1 country.

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.
Jinzhong YangDepartment 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.
Paul G WisdomDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Lawrence BronkDepartment of Radiation Physics, 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.
David R GrosshanDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
David C 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.
X Ronald 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.
The University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeMagnetic resonance imaging (MRI) has gained popularity in radiation therapy simulation because it provides superior soft tissue contrast, which facilitates more accurate target delineation compared with computed tomography (CT) and does not expose the patient to ionizing radiation. However, image registration errors in commercial software have not been widely reported. Here we evaluated the accuracy of deformable image registration (DIR) by using a physical phantom for MRI. METHODS AND MATERIALS: We used the "Wuphantom" for end-to-end testing of DIR accuracy for MRI. This acrylic phantom is filled with water and includes several fillable inserts to simulate various tissue shapes and properties. Deformations and changes in anatomic locations are simulated by changing the rotations of the phantom and inserts. We used Varian Velocity DIR software (v4.0) and CT (head and neck protocol) and MR (T1- and T2-weighted head protocol) images to test DIR accuracy between image modalities (MRI vs CT) and within the same image modality (MRI vs MRI) in 11 rotation deformation scenarios. Large inserts filled with Mobil DTE oil were used to simulate fatty tissue, and small inserts filled with agarose gel were used to simulate tissues slightly denser than water (e.g., prostate). Contours of all inserts were generated before DIR to provide a baseline for contour size and shape. DIR was done with the MR Correctable Deformable DIR method, and all deformed contours were compared with the original contours. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were used to quantitatively validate DIR accuracy. We also used large and small regions of interest (ROIs) during between-modality DIR tests to simulate validation of DIR accuracy for organs at risk (OARs) and propagation of individual clinical target volume (CTV) contours.

resultsNo significant differences in DIR accuracy were found for T1:T1 and T2:T2 comparisons (P > 0.05). DIR was less accurate for between-modality comparisons than for same-modality comparisons, and was less accurate for T1 vs CT than for T2 vs CT (P < 0.001). For between-modality comparisons, use of a small ROI improved DIR accuracy for both T1 and T2 images.

conclusionThe simple design of the Wuphantom allows seamless testing of DIR; here we validated the accuracy of MRI DIR in end-to-end testing. T2 images had superior DIR accuracy compared with T1 images. Use of small ROIs improves DIR accuracy for target contour propagation.

Indexed as

AlgorithmsPhantoms, ImagingHead and Neck NeoplasmsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleProstatic NeoplasmsRadiotherapy DosageRadiotherapy Planning, Computer-Assisteddeformable image registrationdeformable phantomMR multimodality image registration

Identifiers

PMID31808307
PMCPMC6964753
OpenAlexW2994272516

What OpenQuestion holds

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LicenceCC BY
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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.