Evidence map›Paper›PMID 37408663›Full record

ArticleEuropean journal of radiology open2023

Utility of contrast-enhanced 3D STIR FLAIR imaging for evaluating pituitary adenomas at 3 Tesla.

Iichiro Osawa, Keita Nagawa, Yuki Hara, Hirokazu Shimizu, Sayuri Tanaka, Eito Kozawa

Abstract read
In one paragraph

Article in European journal of radiology open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

6 authors.

Iichiro OsawaDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.
Keita NagawaDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.
Yuki HaraDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.
Hirokazu ShimizuDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.
Sayuri TanakaDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.
Eito KozawaDepartment of Radiology, Saitama Medical University Hospital, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To assess the usefulness of contrast-enhanced 3D STIR FLAIR imaging for evaluation of pituitary adenomas. Methods: Patients with pituitary adenomas underwent MR examinations including contrast-enhanced 3D STIR FLAIR and 2D T1-weighted (T1W) imaging. We subjectively compared the two techniques in terms of 10 categories. In addition, images were rated by side-by-side comparisons into three outcomes: 3D STIR FLAIR imaging superior, equal, or 2D T1W imaging superior. Additionally, the added value of 3D STIR FLAIR imaging for adenoma detection over conventional MR imaging was assessed. Results: Twenty-one patients were included in this study. 3D STIR FLAIR imaging offered significantly better images than 2D T1W imaging in terms of three categories, including overall visualization of the cranial nerves in the cavernous sinus (mean 4.0 vs. 2.8, Conclusion: 3D STIR FLAIR imaging improved overall lesion conspicuity compared to 2D T1W imaging. We suggest that 3D STIR FLAIR imaging is recommended as a supplemental technique when pituitary adenomas are invisible or equivocal on conventional imaging.

Indexed as

3D STIR FLAIRMagnetic resonance imagingPituitary adenomaPituitary glandT1-weighted imaging

Identifiers

PMID37408663
PMCPMC10319169

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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.