Evidence map›Paper›PMID 37453304›Full record

ArticleClinical imaging2023

Radiologic reporting of MRI-proven thoracolumbar epidural metastases on body CT: 12-Year single-institution experience.

Lauren Kim, Divya Narayanan, Jiamin Liu, Puskar Pattanayak, Evrim Turkbey, Thomas C Shen, W Marston Linehan, Peter A Pinto, Ronald M Summers

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

Article in Clinical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

9 authors at 3 institutions in 1 country.

Lauren KimImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
Divya NarayananImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
Jiamin LiuImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
Puskar PattanayakImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
Evrim TurkbeyImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
Thomas C ShenImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States.
W Marston LinehanCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.
Peter A PintoCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.
Ronald M SummersImaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, United States. Electronic address: rms@nih.gov.
National Institutes of Health Clinical Center · USCenter for Cancer Research · USNational Cancer Institute · US

Funding

Computer Aided Detection for Radiologic ImagesZ01CL040004 · CLC · CLINICAL CENTER · PI SUMMERS, RONALD M. · 2003 to 2008
$41k
Computer Aided Detection for Radiologic ImagesZIACL040004 · CLC · CLINICAL CENTER · PI SUMMERS, RONALD M. · 2009 to 2025
$0k
Imaging Sciences Training ProgramZIECL090017 · CLC · CLINICAL CENTER · PI FRANK, JOSEPH · 2009 to 2015
$0k
Intramural NIH HHS Z01 CL040004Intramural NIH HHS ZIE CL090017
6 · The paper itself

Abstract

RATIONALE AND

objectivesMetastatic epidural masses are an important radiological finding. The purpose of this study is to determine factors associated with non-reporting of thoracolumbar epidural metastases on body CT. MATERIALS AND

methodsIn a study population of 166 patients from a single institution over a 12-year period, 293 body CT examinations were identified which were performed within 30 days before or after a spine MRI diagnosis of epidural metastasis. Associations were sought between patient diagnosis, CT examination characteristics, reporting radiologist (n = 17), and lesion characteristics with respect to whether an epidural metastasis was reported on CT.

resultsIn retrospective consensus review comprised of 3 radiologists, epidural metastases reported on spine MRI were clearly visible in 80.5% (236/293) of body CT examinations, however 65.3% (154/236) of the body CT reports omitted reporting their presence, even in cases where there was a preceding MRI diagnosis within 30 days (65.4%, 74/113). The identity of the reporting radiologist was statistically significantly associated with the accurate diagnostic reporting of epidural metastasis on body CT (p = 0.04). The only lesion features which were statistically significantly associated with CT reporting were lesion volume (p = 0.03) on noncontrast CT, and lesion volume (p = 0.006) and percentage of spinal canal stenosis (p = 0.001) on intravenous contrast-enhanced CT. The presence or absence of intravenous contrast was not significantly associated with CT reporting (p = 1.0).

conclusionUsing spine MRI as the reference standard for the presence of epidural tumor, the majority of body CT reports omit describing thoracolumbar epidural metastases which are clearly visible in retrospect.

Indexed as

Magnetic Resonance ImagingTomography, X-Ray ComputedHumansRetrospective StudiesBody computed tomographyEpiduralMetastasesSpinal cordSpine

Identifiers

PMID37453304
PMCPMC10528163
OpenAlexW4383497693

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.