Trabecular bone texture detected by plain radiography is associated with MRI-defined osteophytes in finger joints of women without radiographic osteoarthritis

Radiomics signature of osteoarthritis: Current status and perspective

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.

Association between radiographic hand osteoarthritis and bone microarchitecture in a population-based sample

Background

Subchondral bone plays an important role in the pathogenesis of radiographic osteoarthritis (OA). However, the bony changes that occur in hand OA (HOA) are much less understood. This study aimed to describe the association between radiographic HOA and high-resolution peripheral quantitative computed tomography (HRpQCT) measures of the hand and radius in a population-based sample.

Methods

A total of 201 participants (mean age 72, 46% female) from the Tasmanian Older Adult Cohort (TASOAC) study underwent HRpQCT assessment of the 2nd distal and proximal interphalangeal (DIP, PIP), 1st carpometacarpal (CMC) joint, and distal radius. Radiographic HOA was assessed at the 2nd DIP, PIP joints, and the 1st CMC joint using the OARSI atlas.

Results

Proximal osteophyte and joint space narrowing (JSN) scores were consistently more strongly associated with HRpQCT measures compared to the distal site with positive associations for indices of bone size (total and trabecular bone area and cortical perimeter but inconsistent for cortical area) and negative associations for volumetric bone mineral density (vBMD). There was a decrease in trabecular number and bone volume fraction with increasing osteophyte and JSN score as well as an increase in trabecular separation and inhomogeneity. Osteophyte and JSN scores in the hand were not associated with HRpQCT measures at the distal radius.

Conclusions

This hypothesis generating data suggests that bone size and trabecular disorganization increase with both osteophyte formation and JSN (proximal more than distal), while local vBMD decreases. This process appears to be primarily at the site of pathology rather than nearby unaffected bone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-022-02907-6.

Osteoarthritis year in review 2019: imaging

OBJECTIVE

To provide a narrative review of original articles on osteoarthritis (OA) imaging published between April 1, 2018 and March 30, 2019.

METHODS

All original research articles on OA imaging published in English between April 1, 2018 and March 30, 2019 were identified using a PubMed database search. The search terms of "Osteoarthritis" or "OA" were combined with the search terms "Radiography", "X-Rays", "Magnetic Resonance Imaging", "MRI", "Ultrasound", "US", "Computed Tomography", "Dual Energy X-Ray Absorptiometry", "DXA", "DEXA", "CT", "Nuclear Medicine", "Scintigraphy", "Single-Photon Emission Computed Tomography", "SPECT", "Positron Emission Tomography", "PET", "PET-CT", or "PET-MRI". Articles were reviewed to determine relevance based upon the following criteria: 1) study involved human subjects with OA or risk factors for OA and 2) study involved imaging to evaluate OA disease status or OA treatment response. Relevant articles were ranked according to scientific merit, with the best publications selected for inclusion in the narrative report.

RESULTS

The PubMed search revealed a total of 1257 articles, of which 256 (20.4%) were considered relevant to OA imaging. Two-hundred twenty-six (87.1%) articles involved the knee joint, while 195 (76.2%) articles involved the use of magnetic resonance imaging (MRI). The proportion of published studies involving the use of MRI was higher than previous years. An increasing number of articles were also published on imaging of subjects with joint injury and on deep learning application in OA imaging.

CONCLUSION

MRI and other imaging modalities continue to play an important role in research studies designed to better understand the pathogenesis, progression, and treatment of OA.