ArticleOsteoarthritis imaging2024
3D bone shape from CT-scans provides an objective measure of osteoarthritis severity: Data from the IMI-APPROACH study.
Article in Osteoarthritis imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Exploring Artificial Intelligence in Orthopedic Surgery: A Review of Perception, Decision, and Execution Systems.Sensors (Basel, Switzerland) · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Decisions regarding total knee arthroplasty are usually made using a patient's own assessment of pain and the structural disposition of the joint as seen on plain film radiographs. Pain severity can fluctuate, and radiographs can be misleading, with the apparent joint status affected by anatomical orientation. An important component of the surgical management of knee osteoarthritis (OA) is the timing of surgical intervention: knee arthroplasty performed too early in the course of the disease may increase the need for revision surgery. Femoral 3D bone shape (B-score) from MR images is an objective measure of OA severity and has been correlated with current and future risk of pain. We aimed to derive the B-score from CT images and compare it against the B-score derived from MR images. We used baseline and 24-month image data from the IMI-APPROACH 2-year prospective cohort study, comprising pairs of CT and MR images taken for each subject-timepoint. The femur was automatically segmented in both CT and MR modalities using an active appearance model, a machine-learning method, to measure the B-score. Linear regression was used to test for correlation between measures. Limits of agreement and bias were tested using Bland-Altman analysis. CT-MR pairs of the same knee were available from 424 participants (78 % women). B-scores from CT and MR were strongly correlated (CCC = 0.980) with negligible bias of 0.0106 (95 % CI: -0. 0281, +0.0493). The strong correlation and small B-score bias suggests that B-scores may be measured reliably using CT images. Since CT images are used in planning robot-assisted knee arthroplasty, with further study B-scores derived from CT surgical planning images could in principle provide a useful objective input to deciding the appropriateness, timing and type of knee arthroplasty.
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Registered trials
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 Socratic graph.