ArticleScientific reports2024
Development and validation of a practical solution for detecting motion artefacts in the EOS X-ray system.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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
2 citing papers in PubMed.
- Analysis of sagittal alignment changes in the spine-pelvis joint in sitting and standing positions after long- or short-segment fixation to the pelvis for lumbar degenerative diseases.Journal of orthopaedic surgery and research · 2025Article
- Artificial intelligence-assisted analysis of musculoskeletal imaging-A narrative review of the current state of machine learning models.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The EOS™2D/3D system is a low-dose, 3D imaging system that utilizes two perpendicular X-ray beams to create simultaneous frontal and lateral images of the body. This is a useful modality to assess spinal pathologies. However, due to the slow imaging acquisition time up to 25 s, motion artifacts (MA) frequently occur. These artifacts may not be distinguishable from pathological findings, such as scoliosis, and may impair the diagnostic process. The aim of this study was to design a method to detect MA in EOS X-ray. We retrospectively analyzed EOS imaging from 40 patients wearing a radiopaque reference device during imaging. We drew a straight vertical line along the reference device. We measured deviations from it to quantify MA, presenting these findings through descriptive statistics. For a subset of patients with high MA, acquisitions were repeated after giving specific instructions to stand still. For these patients, we compared MA between the two acquisitions. In our study, a substantial proportion of patients exhibited MA ≥ 1 mm, with 80% in frontal projections and 87.9% in lateral projections. In the subjects who received a second acquisition, MA was significantly lower in the second images. Our method allows for a precise detection of MA on EOS images through a simple, yet reliable solution. Our method may improve the reliability of spine measurements, and reduce the risk of wrong diagnosis due to low imaging quality.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.