Evidence map›Paper›PMID 31830984›Full record

Trial reportBMC musculoskeletal disorders2019

Diagnostic performance of 3D-multi-Echo-data-image-combination (MEDIC) for evaluating SLAP lesions of the shoulder.

Felix Wuennemann, Laurent Kintzelé, Felix Zeifang, Michael W Maier, Iris Burkholder, Marc-André Weber, Hans-Ulrich Kauczor, Christoph Rehnitz

Abstract readClinical Trial
In one paragraph

Trial report in BMC musculoskeletal disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

8 authors.

Felix WuennemannDiagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. felix.wuennemann@med.uni-heidelberg.de.ORCID http://orcid.org/0000-0002-1904-907X
Laurent KintzeléDiagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Felix ZeifangCenter for Orthopedics, Trauma Surgery and Spinal Cord Injury, University Hospital Heidelberg, Schlierbacher Landstraße 200A, 69118, Heidelberg, Germany.
Michael W MaierCenter for Orthopedics, Trauma Surgery and Spinal Cord Injury, University Hospital Heidelberg, Schlierbacher Landstraße 200A, 69118, Heidelberg, Germany.
Iris BurkholderDepartment of Nursing and Health, University of Applied Sciences of the Saarland, Malstatter Straße 17, 66117, Saarbruecken, Germany.
Marc-André WeberInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Ernst-Heydemann-Straße 6, 18057, Rostock, Germany.
Hans-Ulrich KauczorDiagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Christoph RehnitzDiagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuperior labral anterior to posterior (SLAP) lesions remain a clinical and diagnostic challenge in routine (non-arthrographic) MR examinations of the shoulder. This study prospectively evaluated the ability of 3D-Multi-Echo-Data-Image-Combination (MEDIC) compared to that of routine high resolution 2D-proton-density weighted fat-saturated (PD fs) sequence using 3 T-MRI to detect SLAP lesions using arthroscopy as gold standard.

methodsSeventeen consecutive patients (mean age, 51.6 ± 14.8 years, 11 males) with shoulder pain underwent 3 T MRI including 3D-MEDIC and 2D-PD fs followed by arthroscopy. The presence or absence of SLAP lesions was evaluated using both sequences by two independent raters with 4 and 14 years of experience in musculoskeletal MRI, respectively. During arthroscopy, SLAP lesions were classified according to Snyder's criteria by two certified orthopedic shoulder surgeons. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 3D-MEDIC and 2D-PD fs for detection of SLAP lesions were calculated with reference to arthroscopy as a gold standard. Interreader agreement and sequence correlation were analyzed using Cohen's kappa coefficient. Figure 1 demonstrates the excellent visibility of a proven SLAP lesion using the 3D-MEDIC and Fig. 2 demonstrates a false-positive case.

resultsArthroscopy revealed SLAP lesions in 11/17 patients. Using 3D-MEDIC, SLAP lesions were diagnosed in 14/17 patients by reader 1 and in 13/17 patients by reader 2. Using 2D-PD fs, SLAP lesions were diagnosed in 11/17 patients by reader 1 and 12/17 patients for reader 2. Sensitivity, specificity, PPV, and NPV of 3D-MEDIC were 100.0, 50.0, 78.6, and 100.0% for reader 1; and 100.0, 66.7, 84.6, and 100% for reader 2, respectively. Sensitivity, specificity, PPV, and NPV of 2D-PD fs were 90.9, 83.3, 90.9, and 83.3% for reader 1 and 100.0, 83.3, 91.7, and 100.0% for reader 2. The combination of 2D-PD fs and 3D-MEDIC increased specificity from 50.0 to 83.3% for reader 1 and from 66.7 to 100.0% for reader 2. Interreader agreement was almost perfect with a Cohen's kappa of 0.82 for 3D-MEDIC and 0.87 for PD fs.

conclusionsWith its high sensitivity and NPV, 3D-MEDIC is a valuable tool for the evaluation of SLAP lesions. As the combination with routine 2D-PD fs further increases specificity, we recommend incorporation of 3D-MEDIC as an additional sequence in conventional shoulder protocols in patients with non-specific shoulder pain.

Indexed as

Imaging, Three-DimensionalAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedProspective StudiesShoulder InjuriesArthroscopyMEDICMRIShoulderSLAP lesions

Identifiers

PMID31830984
PMCPMC6909556

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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.