Comparison between model-based RSA and an AI-based CT-RSA: an accuracy study of 30 patients.

Background and purpose -- Radiostereometry (RSA) is the current gold standard for evaluating early implant migration. CT-based migration analysis is a promising method, with fewer handling requirements compared with RSA and no need for implanted bone-markers. We aimed to evaluate agreement between a...

Full description

Bibliographic Details
Published in:Acta Orthopaedica Vol. 95; pp. 39 - 47
Main Authors: CHRISTENSSON, Albin, NEMATI, Hassan M., FLIVIK, Gunnar
Format: research tables/charts Journal Article
Published: Medical Journals Sweden AB 2024
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183125062&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 183125062
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        17453674
        1BVL
      jtl: Acta Orthopaedica
      issn: 17453674
      maglogo: N
    pubinfo:
      dt: 2024
      vid: 95
      pid: 59195
      pub: Medical Journals Sweden AB
    artinfo:
      ui:
        183125062
        183125062
        183125062
        10.2340/17453674.2024.35749
        183125062
      ppf: 39
      ppct: 8
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Comparison between model-based RSA and an AI-based CT-RSA: an accuracy study of 30 patients.
      aug:
        au:
          CHRISTENSSON, Albin
          NEMATI, Hassan M.
          FLIVIK, Gunnar
        affil: Department of Orthopedics, Skåne University Hospital, Clinical Sciences, Lund University, Lund
      sug:
        subj:
          Arthroplasty, Replacement, Hip
          Foreign-Body Migration Radiography
          Artificial Intelligence
          Tomography, X-Ray Computed
          Radiostereometric Analysis Methods
          Human
          Funding Source
          Male
          Female
          Middle Age
          Aged
          Surgical Patients
          Osteoarthritis, Hip Surgery
          Descriptive Statistics
          Confidence Intervals
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Background and purpose -- Radiostereometry (RSA) is the current gold standard for evaluating early implant migration. CT-based migration analysis is a promising method, with fewer handling requirements compared with RSA and no need for implanted bone-markers. We aimed to evaluate agreement between a new artificial intelligence (AI)-based CT-RSA and model-based RSA (MBRSA) in measuring migration of cup and stem in total hip arthroplasty (THA). Patients and methods -- 30 patients with THA for primary osteoarthritis (OA) were included. RSA examinations were performed on the first postoperative day, and at 2 weeks, 3 months, 1, 2, and 5 years after surgery. A low-dose CT scan was done at 2 weeks and 5 years. The agreement between the migration results obtained from MBRSA and AI-based CT-RSA was assessed using Bland-Altman plots. Results -- Stem migration (y-translation) between 2 weeks and 5 years, for the primary outcome measure, was -0.18 (95% confidence interval [CI] -0.31 to -0.05) mm with MBRSA and -0.36 (CI -0.53 to -0.19) mm with AIbased CT-RSA. Corresponding proximal migration of the cup (y-translation) was 0.06 (CI 0.02-0.09) mm and 0.02 (CI -0.01 to 0.05) mm, respectively. The mean difference for all stem and cup comparisons was within the range of MBRSA precision. The AI-based CT-RSA showed no intraor interobserver variability. Conclusion -- We found good agreement between the AI-based CT-RSA and MBRSA in measuring postoperative implant migration. AI-based CT-RSA ensures user independence and delivers consistent results.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N