Evidence map›Paper›PMID 30771216›Full record

ReviewLa Radiologia medica2019

New advances in MRI diagnosis of degenerative osteoarthropathy of the peripheral joints.

Federico Bruno, Francesco Arrigoni, Pierpaolo Palumbo, Raffaele Natella, Nicola Maggialetti, Alfonso Reginelli, Alessandra Splendiani, Ernesto Di Cesare, Luca Brunese, Giuseppe Guglielmi and 3 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in La Radiologia medica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Complement 3 and 4 impact in osteoarthritis.Biomarkers in medicine · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review of Quantitative Knee Articular Cartilage MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022
    Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
  20. 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

13 authors at 5 institutions in 1 country.

Federico BrunoDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Francesco ArrigoniDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Pierpaolo PalumboDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Raffaele NatellaDepartment of Precision Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Nicola MaggialettiDepartment Life and Health "V. Tiberio", University of Molise, Campobasso, Italy.
Alfonso ReginelliDepartment of Precision Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Alessandra SplendianiDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Ernesto Di CesareDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Luca BruneseDepartment Life and Health "V. Tiberio", University of Molise, Campobasso, Italy.
Giuseppe GuglielmiDepartment of Radiology, Scientific Institute "Casa Sollievo della Sofferenza" Hospital, University of Foggia, Foggia, Italy.
Andrea GiovagnoniDepartment of Radiology, Ospedali Riuniti, Università Politecnica delle Marche, Ancona, Italy.
Carlo MasciocchiDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy.
Antonio BarileDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio 1, 67100, L'Aquila, Italy. antonio.barile@cc.univaq.it.
University of L'Aquila · ITUniversity of Campania "Luigi Vanvitelli" · ITUniversity of Molise · ITMarche Polytechnic University · ITUniversity of Foggia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Degenerative osteoarthropathy is one of the leading causes of the pain and disability from musculoskeletal disease in the adult population. Magnetic resonance imaging (MRI) allows optimal visualization of all tissues involved in degenerative osteoarthritis disease process, mainly the articular cartilage. In addition to qualitative and semiquantitative morphologic assessment, several MRI-based advanced techniques have been developed to allow characterization and quantification of the biochemical cartilage composition. These include quantitative analysis and several compositional techniques (T1 and T2 relaxometry measurements and mapping, sodium imaging, delayed gadolinium-enhanced MRI of cartilage dGEMRIC, glycosaminoglycan-specific chemical exchange saturation transfer gagCEST, diffusion-weighted imaging DWI and diffusion tensor imaging DTI). These compositional MRI techniques may have the potential to serve as quantitative, reproducible, noninvasive and objective endpoints for OA assessment, particularly in diagnosis of early and pre-radiographic stages of the disease and in monitoring disease progression and treatment effects over time.

Indexed as

Contrast MediaDisease ProgressionHumansImaging, Three-DimensionalJoint DiseasesLower ExtremityMagnetic Resonance ImagingContrast MediaAdvanced imagingCartilageDWIMRIT2 mapping

Identifiers

PMID30771216
OpenAlexW2912731256

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.