Integrated applications of imaging examinations and deep learning for early knee osteoarthritis

doi:10.3877/cma.j.issn.1674-134X.2026.01.012

Abstract

Abstract:

This review aimed to sort out the current development status of imaging examination techniques for early knee degenerative disease (knee osteoarthritis) and the integrated application of these techniques with artificial intelligence deep learning technology, so as to provide references for the optimization of clinical diagnosis and relevant academic research. By searching two English literature databases, relevant research literatures were collected using appropriate keywords; after excluding duplicate, low-relevance, and low-quality literatures, 46 high-quality literatures were finally selected for systematic analysis. Clinically common imaging examination techniques each have their own characteristics and can help detect some lesion features in the early stage of the disease, while some novel imaging techniques can capture subtle changes of lesions more accurately. The combination of deep learning technology with these imaging examinations has exhibited good performance in automatically identifying lesion locations, judging disease severity, and predicting disease progression trends, which significantly improves the efficiency and accuracy of diagnosis. However, the related technologies currently still have problems such as insufficient generalization ability and the need for improved standardization. Imaging examination techniques for early knee degenerative disease are continuously developing, and their integration with deep learning provides a new path for precise and efficient disease assessment in clinical practice. In the future, it is necessary to further optimize the stability and clinical adaptability of the technologies to promote their wider application in clinical practice.

Key words: Osteoarthritis, knee, Diagnostic imaging, Deep learning, Early diagnosis

Haibo Xie, Zhiwen Wang, Heng Li. Integrated applications of imaging examinations and deep learning for early knee osteoarthritis[J]. Chinese Journal of Joint Surgery(Electronic Edition), 2026, 20(01): 97-103.

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URL: https://zhgjwkzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1674-134X.2026.01.012

https://zhgjwkzz.cma-cmc.com.cn/EN/Y2026/V20/I01/97

Figures/Tables 5

Figure 1 Flow chart for literature retrieval and screening

Figure 2 Radiographs of patients with KOA（knee osteoarthritis）. A is full-length anteroposterior radiograph of both lower extremities at standing position, showing genu varum of both knees with narrowing of the medial joint space (red arrows); B is lateral radiograph of the right knee at weight-bearing position, yellow arrows reveal osteophyte formation at the marginal ends of the bone and green arrow is pointing subchondral bone sclerosis; C is anteroposterior radiograph of the right knee at weight-bearing position, blue arrow demonstrates tapering of the intercondylar eminence and red arrow shows the medial joint space narrowing

Figure 3 MRI with diffusion-weighted imaging of the right knee (3.0T). A is sagittal image of T1WI, showing cartilage wear and subchondral bone sclerosis (blue arrow), as well as osteophyte formation at the patella and bony ends (red arrows); B is sagittal image of T2WI, green arrow showing a tear of the posterior horn of the medial meniscus (linear hyperintense foci extending to the articular surface), and yellow arrows showing bone marrow edema in the medial femoral condyle (patchy hyperintense foci); C is coronal image of T2WI, showing edema of the anterior cruciate ligament with poor visualization (white arrow), and the joint space narrowing (purple arrow); D is axial image of T2WI, showing patellofemoral joint malalignment with unequal joint space width (orange arrow), focal abnormal hyperintense foci are visible at the site, and the signal intensity of the peripheral soft tissues is inhomogeneous

Figure 4 Musculoskeletal color doppler ultrasound, showing the sonograms, local blood flow signals and blood flow spectra of the musculoskeletal region

Figure 5 Musculoskeletal ultrasound elastography imagesNote: the left part is grayscale sonogram of the musculoskeletal region, and the right part is elastography image of the corresponding regions (with tissue stiffness differentiated by color), which simultaneously display the elastic quality index and other parameters

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