Evidence map›Paper›PMID 33683440›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2021

Evaluating the effect of a post-processing algorithm in detection of annular fissure on MR imaging.

Rami W Eldaya, Matthew S Parsons, Hilary L P Orlowski, Martin N Reis, Aseem Sharma

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In one paragraph

Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

2 citing papers in PubMed, 3 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

5 authors at 1 institution in 1 country.

Rami W EldayaMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, St. Louis, MO, 63110, USA. rami.eldaya@wustl.edu.
Matthew S ParsonsMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, St. Louis, MO, 63110, USA.
Hilary L P OrlowskiMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, St. Louis, MO, 63110, USA.
Martin N ReisMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, St. Louis, MO, 63110, USA.
Aseem SharmaMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, St. Louis, MO, 63110, USA.
Mallinckrodt (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeVisualization of annular fissures on MRI is becoming increasingly important but remains challenging. Our purpose was to test whether an image processing algorithm could improve detection of annular fissures. MATERIALS AND

methodsIn this retrospective study, two neuroradiologists identified 56 IVDs with annular fissures and 97 IVDs with normal annulus fibrosus in lumbar spine MRIs of 101 patients (58 M, 43 F; age ± SD 15.1 ± 3.0 years). Signal intensities of diseased and normal annulus fibrosus, and contrast-to-noise ratio between them on sagittal T2-weighted images were calculated before and after processing with a proprietary software. Effect of processing on detection of annular fissures by two masked neuroradiologists was also studied for IVDs with Pfirrmann grades of ≤ 2 and > 2.

resultsMean (SD) signal baseline intensities of diseased and normal annulus fibrosus were 57.6 (23.3) and 24.4 (7.8), respectively (p < 0.001). Processing increased (p < 0.001) the mean (SD) intensity of diseased annulus to 110.6 (47.9), without affecting the signal intensity of normal annulus (p = 0.14). Mean (SD) CNR between the diseased and normal annulus increased (p < 0.001) from 11.8 (14.1) to 29.6 (29.1). Both masked readers detected more annular fissures after processing in IVDs with Pfirrmann grade of ≤ 2 and > 2, with an apparent increased sensitivity and decreased specificity using predefined image-based human categorization as a reference standard.

conclusionsImage processing improved CNR of annular fissures and detection rate of annular fissures. However, further studies with a more stringent reference standard are needed to assess its effect on sensitivity and specificity.

Indexed as

Annulus FibrosusIntervertebral DiscAlgorithmsHumansImage Processing, Computer-AssistedLumbar VertebraeMagnetic Resonance ImagingRetrospective StudiesAnnular fissureCorrelative image enhancement CIELumbar spineMRI

Identifiers

PMID33683440
OpenAlexW3133680429

What OpenQuestion holds

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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.