Evidence map›Paper›PMID 31134316›Full record

ArticleClinical neuroradiology2020

MRI of Pediatric Orbital Masses: Role of Quantitative Diffusion-weighted Imaging in Differentiating Benign from Malignant Lesions.

Alok Jaju, Karen Rychlik, Maura E Ryan

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Article in Clinical neuroradiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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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

3 authors.

Alok JajuDepartment of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, 225 E. Chicago Ave, 60611, Chicago, IL, USA. ajaju@luriechildrens.org.ORCID http://orcid.org/0000-0001-5025-3709
Karen RychlikStanley Manne Children's Research Institute, Ann and Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, 225 E. Chicago Ave, 60611, Chicago, IL, USA.
Maura E RyanDepartment of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, 225 E. Chicago Ave, 60611, Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo systematically evaluate the utility of different magnetic resonance imaging (MRI) features, including quantitative diffusion-weighted imaging, in differentiating benign from malignant pediatric orbital masses.

methodsThe use of MRI in 40 pediatric patients with orbital masses was retrospectively reviewed. Multiple subjective and objective MRI parameters, including lesion mean apparent diffusion coefficient (ADC) values and lesion-to-thalamus ADC ratio were recorded. Bivariate analysis was done to identify parameters that were significantly different between benign and malignant subgroups. Receiver operating curves were used to establish optimal cut-off values for lesion mean ADC and lesion-to-thalamus ADC ratio for predicting benign versus malignant lesions.

resultsLesion mean ADC, lesion-to-thalamus ADC ratio and extent of contrast enhancement showed statistically significant differences between the two subgroups. For distinguishing benign from malignant lesions, a lesion mean ADC cut-off value of 1.14 × 10

conclusionQuantitative diffusion-weighted imaging can be a useful adjunct in characterizing pediatric orbital masses by MRI, and thus help in clinical decision making.

Indexed as

ChildChild, PreschoolContrast MediaDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingFemaleHumansInfantMagnetic Resonance ImagingMaleOrbital NeoplasmsRetrospective StudiesSensitivity and SpecificityContrast MediaADCDWIMRIOrbital massesPediatric

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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.