A multicenter study: habitat imaging and radiomics to guide precision and individualized surgical treatment in chronic osteomyelitis

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Authors: Qiyu Jia, Junna Wang, Jie Lin, Rongyu Zhang, Abudusalamu Alimujiang, Qiankun Jin, Jian Guo, Xi Wang, Jun Zhang, Ziyi Xu, Meng Zhao, Zengru Xie
+2 more Chuang Ma, Hao Zheng
Cited by: 0
References: 35

Abstract

BACKGROUND: Chronic osteomyelitis poses major challenges in orthopaedic practice due to its complex and unpredictable disease progression. Effective treatment requires complete removal of necrotic and infected bone tissue. Surgeons often face two opposing risks: inadequate resection, potentially leading to infection recurrence, and excessive resection, which can cause irreversible bone damage and functional loss. Precise intraoperative localisation of lesions is therefore crucial; however, accurate localisation and quantification of intralesional heterogeneity remain difficult to achieve with conventional imaging techniques. METHODS: To address these limitations, we developed a novel approach that integrates habitat imaging and radiomics to improve diagnostic accuracy and guide surgical management for chronic osteomyelitis. Using magnetic resonance imaging, we segmented lesions into sub-regions (habitats) using K-means clustering, enabling detailed assessment of various lesion microenvironments. We extracted radiomic features, including geometric, intensity and texture attributes, from each habitat and incorporated them into a diagnostic model using advanced feature selection techniques. RESULTS: The model demonstrated strong diagnostic performance, with an area under the curve of 0.983 in the training set and 0.894 in the validation set. It identified potential osteomyelitis lesions that were not visually apparent, providing precise guidance for surgical debridement while minimising healthy bone destruction. Radiomic features related to lesion shape and texture were particularly important for imaging-based diagnosis of osteomyelitis. CONCLUSIONS: The findings highlight the diagnostic value of integrating habitat imaging and radiomics in chronic osteomyelitis, significantly enhancing diagnostic accuracy and supporting personalised surgical interventions. This approach advances precision medicine and may be applicable to other complex diseases requiring detailed lesion analysis and individualised treatment strategies.

Fields of Study & Subjects

Radiomics and Machine Learning in Medical Imaging Orthopedic Infections and Treatments Infectious Diseases and Tuberculosis

Publication details

Journal / source
BMC Medical Imaging
Volume
26
Issue
1
Pages
97–97
Publication date
27 January 2026
Language
EN