Evidence map›Paper›PMID 41400065›Full record

ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2026

Multi-Spectral MRI-Based Radiomic Features Can Classify Femoral Loosening in Patients With Total Hip Arthroplasty.

Jack Consolini, Kevin M Koch, Elizabeth G Koretsky, Hollis G Potter, Matthew F Koff

Abstract read
In one paragraph

Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jack ConsoliniDepartment of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.ORCID 0000-0001-9237-4867
Kevin M KochDepartment of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.ORCID 0000-0003-4490-9761
Elizabeth G KoretskyDepartment of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.ORCID 0009-0005-9742-1892
Hollis G PotterDepartment of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.ORCID 0000-0002-9111-6388
Matthew F KoffDepartment of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.ORCID 0000-0001-6969-0183

Funding

The Ability of MRI to Detect Adverse Local Tissue Reaction and Implant Integration as a Function of Hip Implant ModularityR01AR064840 · NIAMS · HOSPITAL FOR SPECIAL SURGERY · PI KOFF, MATTHEW F., POTTER, HOLLIS G. · 2013 to 2023
$5.0M
NIAMS NIH HHS R01 AR064840
6 · The paper itself

Abstract

Total hip arthroplasty (THA) is the most successful treatment for end-stage joint degeneration; however, implant loosening remains a common reason for revision and its detection on radiography can be challenging. Three-dimensional multi-spectral magnetic resonance imaging (3D-MSI-MRI) enables imaging near metal implants and combining this with radiomics may enhance detection of loosening. In this cohort study, 3D MSI-MRI acquisitions were obtained from 76 patients with THA, including 36 symptomatic patients with confirmed femoral component loosening and 40 asymptomatic patients. Periprosthetic trabecular bone of the femoral stem was segmented and divided into Gruen zones. Two-dimensional overlapping patches (12 × 12 mm

Indexed as

Arthroplasty, Replacement, HipFemurMagnetic Resonance ImagingProsthesis FailureAdultAgedAged, 80 and overFemaleHip ProsthesisHumansImaging, Three-DimensionalMaleMiddle AgedRadiomicslooseningMRIradiomicstotal hip arthroplasty

Identifiers

PMID41400065
PMCPMC13602130

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.