Evidence map›Paper›PMID 29869174›Full record

ArticleEuropean radiology2018

CT perfusion imaging of lung cancer: benefit of motion correction for blood flow estimates.

Lisa L Chu, Robert J Knebel, Aryan D Shay, Jonathan Santos, Ramsey D Badawi, David R Gandara, Friedrich D Knollmann

Abstract read
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In one paragraph

Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 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

7 authors at 1 institution in 1 country.

Lisa L ChuDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA.
Robert J KnebelDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA.
Aryan D ShayDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA.
Jonathan SantosDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA.
Ramsey D BadawiDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA.
David R GandaraDepartment of Internal Medicine, Division of Hematology and Oncology, University of California Davis Medical Center, Sacramento, CA, USA.
Friedrich D KnollmannDepartment of Radiology, University of California Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA. fknollmann@ucdavis.edu.ORCID http://orcid.org/0000-0001-6730-4090
University of California Davis Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. MATERIALS AND

methodsThe institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics.

resultsThe 95% limits of agreement of intra-observer reproducibility for observer 1 improved from -84.4%, 65.3% before motion correction to -33.8%, 30.3% after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from -151%, 96% to -49 %, 36 % (r = 0.87 and 0.95, p < 0.0001 for both). The 95% limits of agreement of inter-observer reproducibility improved from -168%, 154% to -17%, 25%.

conclusionThe use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. KEY POINTS: • Tumor blood flow estimates in advanced lung cancer show significant variability. • Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer. • Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.

Indexed as

AdultAgedAlgorithmsCarcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsMaleMiddle AgedMotionNeovascularization, PathologicObserver VariationPerfusion ImagingProspective StudiesRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsCancerDiagnostic imagingLungPerfusion imagingTomography, x-ray computed

Identifiers

PMID29869174
OpenAlexW2806796895

What OpenQuestion holds

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Registered trials

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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.