Evidence map›Paper›PMID 26632036›Full record

Trial reportMedical physics2015

Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

Xenia Fave, Dennis Mackin, Jinzhong Yang, Joy Zhang, David Fried, Peter Balter, David Followill, Daniel Gomez, A Kyle Jones, Francesco Stingo and 2 more

Open access · greenAbstract readClinical Trial
In one paragraph

Trial report in Medical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 5 pooled it
11.9field-weighted citation impact, top 1% 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

92 citing papers in PubMed, 5 syntheses or guidelines pooled it, 174 citations in OpenAlex.

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  4. Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018
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32 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Xenia FaveDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030.
Dennis MackinDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
Jinzhong YangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
Joy ZhangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
David FriedDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030.
Peter BalterDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
David FollowillDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
Daniel GomezDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
A Kyle JonesDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
Francesco StingoDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
Jonas FontenotMary Bird Perkins Cancer Center, 4950 Essen Lane, Baton Rouge, Louisiana 70809.
Laurence CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030.
The University of Texas MD Anderson Cancer Center · USMary Bird Perkins Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
IROC: Enhancing local enrolling site radiological data capture capabilities for NCTN trialsU24CA180803 · NCI · AMERICAN COLLEGE OF RADIOLOGY · PI Thomas J. FitzGerald, MICHAEL V KNOPP · 2014 to 2026
$116.2M
Development of a tool to extract quantitative image features and predict outcomeR03CA178495 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI COURT, LAURENCE E · 2013 to 2014
$158k
NCI NIH HHS P30 CA016672NCI NIH HHS R03 CA178495NCI NIH HHS R03CA178495-01NCI NIH HHS U24 CA180803
6 · The paper itself

Abstract

purposeIncreasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment.

methodsTest-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rank correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features' interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set.

resultsOf the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol were kept consistent, 4-13 of these 37 features passed our criteria for reproducibility more than 50% of the time, depending on the manufacturer-protocol combination. Almost all of the features changed substantially when scatter material was added around the phantom. For the dense cork, 23 features passed in the thoracic scans and 11 features passed in the head scans when the differences between one and two layers of scatter were compared. Using the same test for the shredded rubber, five features passed the thoracic scans and eight features passed the head scans. Motion substantially impacted the reproducibility of the features. With 4 mm of motion, 12 features from the entire volume and 14 features from the center slice measurements were reproducible. With 6-8 mm of motion, three features (Laplacian of Gaussian filtered kurtosis, gray-level nonuniformity, and entropy), from the entire volume and seven features (coarseness, high gray-level run emphasis, gray-level nonuniformity, sum-average, information measure correlation, scaled mean, and entropy) from the center-slice measurements were considered reproducible.

conclusionsSome radiomics features are robust to the noise and poor image quality of CBCT images when the imaging protocol is consistent, relative changes in the features are used, and patients are limited to those with less than 1 cm of motion.

Indexed as

Carcinoma, Non-Small-Cell LungCone-Beam Computed TomographyHumansMotionPhantoms, ImagingPlant StructuresRadiography, ThoracicReproducibility of ResultsRespirationRetrospective StudiesRubberRubber

Identifiers

PMID26632036
PMCPMC5148115
OpenAlexW2165927297

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.