Evidence map›Paper›PMID 34313914›Full record

ArticleInternational journal of computer assisted radiology and surgery2021

Three-dimensional ultrasound for knee osteophyte depiction: a comparative study to computed tomography.

Valeria Vendries, Tamas Ungi, Jordan Harry, Manuela Kunz, Jana Podlipská, Les MacKenzie, Gabriel Venne

Open access · hybridAbstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

4 citing papers in PubMed, 6 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

7 authors at 3 institutions in 3 countries.

Valeria VendriesAnatomical Sciences Program and Department of Biomedical and Molecular Sciences, Queens University, Kingston, ON, K7L3 N6, Canada. v.vendries@leeds.ac.uk.ORCID http://orcid.org/0000-0001-9195-6312
Tamas UngiSchool of Computing, Queen's University, Kingston, ON, K7L 3N6, Canada.
Jordan HarryAnatomical Sciences Program and Department of Biomedical and Molecular Sciences, Queens University, Kingston, ON, K7L3 N6, Canada.
Manuela KunzSchool of Computing, Queen's University, Kingston, ON, K7L 3N6, Canada.
Jana PodlipskáResearch Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
Les MacKenzieAnatomical Sciences Program and Department of Biomedical and Molecular Sciences, Queens University, Kingston, ON, K7L3 N6, Canada.
Gabriel VenneDepartment of Anatomy and Cell Biology, McGill University, Montreal, QC, H3A 0G4, Canada.
Queen's University · CAMcGill University · CAUniversity of Oulu · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOsteophytes are common radiographic markers of osteoarthritis. However, they are not accurately depicted using conventional imaging, thus hampering surgical interventions that rely on pre-operative images. Studies have shown that ultrasound (US) is promising at detecting osteophytes and monitoring the progression of osteoarthritis. Furthermore, three-dimensional (3D) ultrasound reconstructions may offer a means to quantify osteophytes. The purpose of this study was to compare the accuracy of osteophyte depiction in the knee joint between 3D US and conventional computed tomography (CT).

methodsEleven human cadaveric knees were pre-screened for the presence of osteophytes. Three osteoarthritic knees were selected, and then, 3D US and CT images were obtained, segmented, and digitally reconstructed in 3D. After dissection, high-resolution structured light scanner (SLS) images of the joint surfaces were obtained. Surface matching and root mean square (RMS) error analyses of surface distances were performed to assess the accuracy of each modality in capturing osteophytes. The RMS errors were compared between 3D US, CT and SLS models.

resultsAverage RMS error comparisons for 3D US versus SLS and CT versus SLS models were 0.87 mm ± 0.33 mm (average ± standard deviation) and 0.95 mm ± 0.32 mm, respectively. No statistical difference was found between 3D US and CT. Comparative observations of imaging modalities suggested that 3D US better depicted osteophytes with cartilage and fibrocartilage tissue characteristics compared to CT.

conclusionUsing 3D US can improve the depiction of osteophytes with a cartilaginous portion compared to CT. It can also provide useful information about the presence and extent of osteophytes. Whilst algorithm improvements for automatic segmentation and registration of US are needed to provide a more robust investigation of osteophyte depiction accuracy, this investigation puts forward the potential application for 3D US in routine diagnostic evaluations and pre-operative planning of osteoarthritis.

Indexed as

Osteoarthritis, KneeOsteophyteHumansKnee JointTomography, X-Ray ComputedUltrasonography3D ultrasoundComputed tomographyOsteoarthritisOsteophyteStructured light scanner

Identifiers

PMID34313914
PMCPMC8580923
OpenAlexW3183812399

What OpenQuestion holds

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LicenceCC BY
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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.