Evidence map›Paper›PMID 25641500›Full record

ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2015

Classification of histologically scored human knee osteochondral plugs by quantitative analysis of magnetic resonance images at 3T.

Vanessa A Lukas, Kenneth W Fishbein, Ping-Chang Lin, Michael Schär, Erika Schneider, Corey P Neu, Richard G Spencer, David A Reiter

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 15 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

8 authors at 6 institutions in 1 country.

Vanessa A LukasLaboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, 3001 S. Hanover Street, Baltimore, Maryland.
Kenneth W Fishbein
Ping-Chang Lin
Michael Schär
Erika Schneider
Corey P Neu
Richard G Spencer
David A Reiter
National Institute on Aging · USNational Institutes of Health · USCleveland Clinic · USHoward University · USPhilips (United States) · USPurdue University West Lafayette · US

Funding

Improving Sensitivity and Specificity of Parametric MRI Assessment of CartilageZIAAG000922 · NIA · NATIONAL INSTITUTE ON AGING · PI SPENCER, RICHARD · 2009 to 2017
$6.3M
Probing Osteoarthritis Pathogenesis by Noninvasive Imaging of Cartilage StrainR01AR063712 · NIAMS · UNIVERSITY OF COLORADO · PI NEU, COREY P · 2013 to 2023
$4.7M
Intramural NIH HHS Z99 AG999999NIAMS NIH HHS R01 AR063712
6 · The paper itself

Abstract

This work evaluates the ability of quantitative MRI to discriminate between normal and pathological human osteochondral plugs characterized by the Osteoarthritis Research Society International (OARSI) histological system. Normal and osteoarthritic human osteochondral plugs were scored using the OARSI histological system and imaged at 3 T using MRI sequences producing T1 and T2 contrast and measuring T1, T2, and T2* relaxation times, magnetization transfer, and diffusion. The classification accuracies of quantitative MRI parameters and corresponding weighted image intensities were evaluated. Classification models based on the Mahalanobis distance metric for each MRI measurement were trained and validated using leave-one-out cross-validation with plugs grouped according to OARSI histological grade and score. MRI measurements used for classification were performed using a region-of-interest analysis which included superficial, deep, and full-thickness cartilage. The best classifiers based on OARSI grade and score were T1- and T2-weighted image intensities, which yielded accuracies of 0.68 and 0.75, respectively. Classification accuracies using OARSI score-based group membership were generally higher when compared with grade-based group membership. MRI-based classification--either using quantitative MRI parameters or weighted image intensities--is able to detect early osteoarthritic tissue changes as classified by the OARSI histological system. These findings suggest the benefit of incorporating quantitative MRI acquisitions in a comprehensive clinical evaluation of OA.

Indexed as

AdultAgedBone and BonesCartilage, ArticularFemaleHumansKnee JointMagnetic Resonance ImagingMaleMiddle AgedOsteoarthritis, Kneecartilage matrixclassificationimagingosteoarthritisquantitative MRI

Identifiers

PMID25641500
PMCPMC5875433
OpenAlexW1877666346

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.