Evidence map›Paper›PMID 40512695›Full record

ArticlePloS one2025

Same-model and cross-model variability in knee cartilage thickness measurements using 3D MRI systems.

Hisako Katano, Haruka Kaneko, Eiji Sasaki, Naofumi Hashiguchi, Kanto Nagai, Muneaki Ishijima, Yasuyuki Ishibashi, Nobuo Adachi, Ryosuke Kuroda, Makoto Tomita and 2 more

Abstract read
In one paragraph

Article in PloS one, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Hisako KatanoCenter for Stem Cell and Regenerative Medicine, Institute of Science Tokyo, Tokyo, Japan.
Haruka KanekoDepartment of Medicine for Orthopedics and Motor Organ, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Eiji SasakiDepartment of Orthopaedic Surgery, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan.
Naofumi HashiguchiDepartment of Orthopaedic Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Kanto NagaiDepartment of Orthopaedic Surgery, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.ORCID https://orcid.org/0000-0002-8996-0299
Muneaki IshijimaDepartment of Medicine for Orthopedics and Motor Organ, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Yasuyuki IshibashiDepartment of Orthopaedic Surgery, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan.
Nobuo AdachiDepartment of Orthopaedic Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Ryosuke KurodaDepartment of Orthopaedic Surgery, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Makoto TomitaSchool of Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
Jun MasumotoMedical System Research & Development Center, Fujifilm Corporation, Tokyo, Japan.ORCID https://orcid.org/0000-0003-0492-0106
Ichiro SekiyaCenter for Stem Cell and Regenerative Medicine, Institute of Science Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0003-1671-5054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMagnetic Resonance Imaging (MRI) based three-dimensional analysis of knee cartilage has evolved to become fully automatic. However, when implementing these measurements across multiple clinical centers, scanner variability becomes a critical consideration. Our purposes were to quantify and compare same-model variability (between repeated scans on the same MRI system) and cross-model variability (across different MRI systems) in knee cartilage thickness measurements using MRI scanners from five manufacturers, as analyzed with a specific 3D volume analysis software.

methodsTen healthy volunteers (eight males and two females, aged 22-60 years) underwent two scans of their right knee on 3T MRI systems from five manufacturers (Canon, Fujifilm, GE, Philips, and Siemens). The imaging protocol included fat-suppressed spoiled gradient echo and proton density weighted sequences. Cartilage regions were automatically segmented into 7 subregions using a specific deep learning-based 3D volume analysis software. This resulted in 350 measurements for same-model variability and 2,800 measurements for cross-model variability.

resultsFor same-model variability, 82% of measurements showed variability ≤0.10 mm, and 98% showed variability ≤0.20 mm. For cross-model variability, 51% showed variability ≤0.10 mm, and 84% showed variability ≤0.20 mm. The mean same-model variability (0.06 ± 0.05 mm) was significantly lower than cross-model variability (0.11 ± 0.09 mm) (p < 0.001).

conclusionThis study demonstrates that knee cartilage thickness measurements exhibit significantly higher variability across different MRI systems compared to repeated measurements on the same system, when analyzed using this specific software. This finding has important implications for multi-center studies and longitudinal assessments using different MRI systems and highlights the software-dependent nature of such variability assessments.

Indexed as

Cartilage, ArticularImaging, Three-DimensionalKnee JointMagnetic Resonance ImagingAdultFemaleHealthy VolunteersHumansMaleMiddle AgedYoung Adult

Identifiers

PMID40512695
PMCPMC12165388

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.