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Review
. 2024 Mar 16:45:100-106.
doi: 10.1016/j.jot.2023.10.003. eCollection 2024 Mar.

Radiomics signature of osteoarthritis: Current status and perspective

Tianshu Jiang  1 , Sing-Hin Lau  1 , Jiang Zhang  2 , Lok-Chun Chan  1 , Wei Wang  1 , Ping-Keung Chan  3 , Jing Cai  2 , Chunyi Wen  1
Affiliations
Review

Radiomics signature of osteoarthritis: Current status and perspective

Tianshu Jiang et al. J Orthop Translat. .

Abstract

Osteoarthritis (OA) is one of the fast-growing disability-related diseases worldwide, which has significantly affected the quality of patients' lives and brings about substantial socioeconomic burdens in medical expenditure. There is currently no cure for OA once the bone damage is established. Unfortunately, the existing radiological examination is limited to grading the disease's severity and is insufficient to precisely diagnose OA, detect early OA or predict OA progression. Therefore, there is a pressing need to develop novel approaches in medical image analysis to detect subtle changes for identifying early OA development and rapid progressors. Recently, radiomics has emerged as a unique approach to extracting high-dimensional imaging features that quantitatively characterise visible or hidden information from routine medical images. Radiomics data mining via machine learning has empowered precise diagnoses and prognoses of disease, mainly in oncology. Mounting evidence has shown its great potential in aiding the diagnosis and contributing to the study of musculoskeletal diseases. This paper will summarise the current development of radiomics at the crossroads between engineering and medicine and discuss the application and perspectives of radiomics analysis for OA diagnosis and prognosis.

The translational potential of this article: Radiomics is a novel approach used in oncology, and it may also play an essential role in the diagnosis and prognosis of OA. By transforming medical images from qualitative interpretation to quantitative data, radiomics could be the solution for precise early OA detection, progression tracking, and treatment efficacy prediction. Since the application of radiomics in OA is still in the early stages and primarily focuses on fundamental studies, this review may inspire more explorations and bring more promising diagnoses, prognoses, and management results of OA.

Keywords: Data mining; Medical image analysis; Osteoarthritis; Radiomics.

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Conflict of interest statement

A conflict of interest occurs when an individual's objectivity is potentially compromised by a desire for financial gain, prominence, professional advancement or a successful outcome. The Editors of the Journal of Orthopaedic Translation strive to ensure that what is published in the Journal is as balanced, objective and evidence-based as possible. Since it can be difficult to distinguish between an actual conflict of interest and a perceived conflict of interest, the Journal requires authors to disclose all and any potential conflicts of interest.

Figures

Image 1
Graphical abstract
Figure 1
Figure 1
Overview of radiomics analysis framework.
See this image and copyright information in PMC

References

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