Computer Aided Orthopaedic Surgery: Incremental Shift or Paradigm Change?
Abstract
Computer Aided Orthopaedic Surgery (CAOS) is now about 25 years old. Unlike Neurosurgery, Computer Aided Surgery has not become the standard of care in Orthopaedic Surgery. In this paper, we provide the technical and clinical context raised by this observation in an attempt to elucidate the reasons for this state of affairs. We start with a brief outline of the history of CAOS, review the main CAOS technologies, and describe how they are evaluated. We then identify some of the current publications in the field and present the opposing views on their clinical impact and their acceptance by the orthopaedic community worldwide. We focus on total knee replacement surgery as a case study and present current clinical results and contrasting opinions on CAOS technologies. We then discuss the challenges and opportunities for research in medical image analysis in CAOS and in musculoskeletal radiology. We conclude with a suggestion that while CAOS acceptance may be more moderate than that of other fields in surgery, it still has a place in the arsenal of useful tools available to orthopaedic surgeons.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Navigation systems are not widely adopted due to high purchase price despite limited versatility, increased procedural time and cost, and potential for disruptions to surgical workflows due to line-of-sight occlusions or other system complications.
“Unfortunately, navigation systems are not widely adopted due to, among other things, high purchase price despite limited versatility, increased procedural time and cost, and potential for disruptions to surgical workflows due to line-of-sight occlusions or other system complications (Picard et al., 2014; Joskowicz and Hazan, 2016).”
From The Impact of Machine Learning on 2D/3D Registration for Image-Guided Interventions: A Systematic Review and Perspective (2021) · cites this paper as Joskowicz and Hazan, 2016
The citation lists haven’t been fetched yet
References 17 · Cited by 58
- Authors
- Joskowicz, L., & Hazan, E. J.
- Affiliations
- Instituto Nacional de Rehabilitación (MX)
- Venue
- Medical Image Analysis
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 33
- Pages
- 84-90
- ISSN
- 1361-8415 (ISSN-L)
- OpenAlex
- W2468467035
- Cited by
- 58
- References
- 17
- Citations by year
- 2025: 6 · 2024: 4 · 2023: 7 · 2022: 9 · 2021: 4 · 2020: 6 · 2019: 11 · 2018: 9 · 2017: 1 · 2016: 1
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Image Analysis (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Surgery › Total Knee Arthroplasty Outcomes
- Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- total knee arthroplasty, surgical navigation, musculoskeletal radiology
- MeSH terms
- Diagnostic Imaging, Humans, Orthopedics, Surgery, Computer-Assisted
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review