Evidence map›Paper›PMID 30896047›Full record

ArticleMedical physics2019

Technical Note: Density correction to improve CT number mapping in thoracic deformable image registration.

Jinzhong Yang, Yongbin Zhang, Zijian Zhang, Lifei Zhang, Peter Balter, Laurence Court

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 4 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

6 authors at 3 institutions in 2 countries.

Jinzhong YangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Yongbin ZhangProton Therapy Center, University of Cincinnati Medical Center, Liberty Township, OH, USA.
Zijian ZhangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Lifei ZhangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Peter BalterDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Laurence CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
The University of Texas MD Anderson Cancer Center · USUniversity of Cincinnati · USXiangya Hospital Central South University · CN

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Cancer Prevention Research Institute of Texas (CPRIT) RP110562NCI NIH HHS P30 CA016672NIH HHS P30CA016672
6 · The paper itself

Abstract

purposeTo improve the accuracy of computed tomography (CT) number mapping inside the lung in deformable image registration with large differences in lung volume for applications in vertical CT imaging and adaptive radiotherapy.

methodsThe deep inspiration breath hold (DIBH) CT image and the end of exhalation (EE) phase image in four-dimensional CT of 14 thoracic cancer patients were used in this study. Lung volumes were manually delineated. A Demons-based deformable registration was first applied to register the EE CT to the DIBH CT for each patient, and the resulting deformation vector field deformed the EE CT image to the DIBH CT space. Given that the mass of the lung remains the same during respiration, we created a mass-preserving model to correlate lung density variations with volumetric changes, which were characterized by the Jacobian derived from the deformation field. The Jacobian determinant was used to correct the lung CT numbers transferred from the EE CT image. The absolute intensity differences created by subtracting the deformed EE CT from the DIBH CT with and without density correction were compared.

resultsThe ratio of DIBH CT to EE CT lung volumes was 1.6 on average. The deformable registration registered the lung shape well, but the appearance of voxel intensities inside the lung was different, demonstrating the need for density correction. Without density correction, the mean and standard deviation of the absolute intensity difference between the deformed EE CT and the DIBH CT inside the lung were 54.5 ± 45.5 for all cases. After density correction, these numbers decreased to 18.1 ± 34.9, demonstrating greater accuracy. The cumulative histogram of the intensity difference also showed that density correction improved CT number mapping greatly.

conclusionDensity correction improves CT number mapping inside the lung in deformable image registration for difficult cases with large lung volume differences.

Indexed as

Four-Dimensional Computed TomographyRadiography, ThoracicBreath HoldingHumansImage Processing, Computer-AssistedRetrospective StudiesThoracic Neoplasmsdeformable image registrationdensity correctionJacobianlung cancer

Identifiers

PMID30896047
PMCPMC6510598
OpenAlexW2923539922

What OpenQuestion holds

Textmetadata
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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.