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Publisher: Peytchinski Publishing Ltd.
ISSN: 1312-773X (Online)
Issue: 2024, vol. 30, issue4
Subject Area: Public Health
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DOI: 10.5272/jimab.2024304.5786
Published online: 03 October 2024
Reviw article
J of IMAB. 2024 Oct-Dec;30(4):5786-5788
THE ROLE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN KNEE OSTEOARTHRITIS
Petya Subeva
, Mariya Gramatikova,
Department of Kinesitherapy, Faculty of Public Health, Healthcare and Sports, South-West University "Neofit Rilski" Blagoevgrad, Bulgaria.
ABSTRACT:
Purpose: The purpose of the study is to examine available scientific sources related to the role and potential of artificial intelligence in osteoarthritis of the knee joint.
Materials/Methods: Method of deduction (analysis of literary sources). To achieve the goal, available scientific data on the role and potential of artificial intelligence application in knee OA were studied and analyzed.
Results: The following innovations related to the use of artificial intelligence in knee osteoarthritis (OA) were reviewed: artificial intelligence (AI) software - named KOALA™ and DL AI software - MediAI-OA. KOALA™ is software that provides metric evaluations of knee joint imaging. Standardized quantitative measurements of morphological features such as joint gap width and joint gap area on knee radiographs reduce errors in diagnosis. The new DL software, MediAI-OA, demonstrated good success rates in analyzing knee OA characteristics, Kellgren-Lawrence (KL) grading (which is used to classify the severity of knee OA), and OA diagnosis comparable to that of experienced orthopedists and radiologists.
Discussion: Diagnostic imaging is a vital tool for visualization. Imaging methods such as radiography, magnetic resonance (MR), computed tomography (CT), and ultrasound play critical roles in OA diagnosis. Additionally, vibro- and phono arthrography serve as alternative diagnostic tools. The most commonly used imaging method is magnetic resonance imaging, which has been found to underestimate the extent of osteochondral lesions. This can lead to inadequate and incomplete diagnoses. Artificial intelligence can serve as a strategic element in addressing these limitations in radiographic knee OA diagnosis.
Conclusion: Artificial intelligence has the potential to advance the field of radiology by enhancing efficiency, accuracy, and precision in the radiographic diagnosis of knee osteoarthritis.
Keywords: Artificial Intelligence, Osteoarthritis (OA), Knee Joint, Gonarthrosis, Software,
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Please cite this article as: Subeva P, Gramatikova M. The role potential of artificial intelligence in knee osteoarthritis. J of IMAB. 2024 Oct-Dec;30(4):5786-5788. [Crossref - 10.5272/jimab.2024304.5786]
Correspondence to: Petya Subeva - PhD Student, Department of Kinesitherapy, Faculty of Public Health, Health Care, and Sports, South-West University "Neofit Rilski" – Blagoevgrad; 66, Ivan Mihailov Str., 2700 Blagoevgrad, Bulgaria; E-mail: petqsubevaa1995@abv.bg
REFERENCES:
1. Varghese J. Artificial Intelligence in Medicine: Chances and Challenges for Wide Clinical Adoption. Visc Med. 2020 Dec;36(6):443-449. [PubMed]
2. Fiste O, Gkiozos I, Charpidou A, Syrigos NK. Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC. Cancers (Basel). 2024 Feb 19;16(4):831. [PubMed]
3. Korteling JEH, van de Boer-Visschedijk GC, Blankendaal RAM, Boonekamp RC, Eikelboom AR. Human- versus Artificial Intelligence. Front Artif Intell. 2021 Mar 25;4:622364. [PubMed]
4. Kann BH, Hosny A, Aerts HJWL. Artificial intelligence for clinical oncology. Cancer Cell. 2021 Jul 12;39(7):916-927. [PubMed]
5. Neubauer M, Moser L, Neugebauer J, Raudner M, Wondrasch B, Führer M, et al. Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings. J Clin Med. 2023 Jan 17;12(3):744. [PubMed]
6. Katz JN, Arant KR, Loeser RF. Diagnosis and Treatment of Hip and Knee Osteoarthritis: A Review. JAMA. 2021 Feb 9;325(6):568-578. [PubMed]
7. Smolle MA, Goetz C, Maurer D, Vielgut I, Novak M, Zier G, et al. Artificial intelligence-based computer-aided system for knee osteoarthritis assessment increases experienced orthopaedic surgeons' agreement rate and accuracy. Knee Surg Sports Traumatol Arthrosc. 2023 Mar;31(3):1053-1062. [PubMed]
8. Yoon JS, Yon CJ, Lee D, Lee JJ, Kang CH, Kang SB, Lee NK, et al. Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis. BMC Musculoskelet Disord. 2023; 24:869. [Crossref]
9. Garwood ER, Tai R, Joshi G, Watts V GJ. The Use of Artificial Intelligence in the Evaluation of Knee Pathology. Semin Musculoskelet Radiol. 2020 Feb;24(1):21-29. [PubMed]
Received: 15 April 2024
Published online: 03 October 2024