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Updated: Feb 5, 2026

Author Spotlight: Developing a Rat Model for Weight-Bearing Intervention to Investigate Osteonecrosis of the Femoral Head
Published on: September 27, 2024
Biomechanical bearing-based typing method for osteonecrosis of the femoral head: ABC typing
Zhennan Zhang1, Tong Yu1, Limin Xie1
1Department of Orthopedics, Guanganmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, P.R. China.
Abstract:
Type classification of osteonecrosis of the femoral head (ONFH) is important for collapse prediction in ONFH, which depends on a complexity of factors. At present, most typing is based on single factors, including the location or size of the necrosis, or the bone repair capacity after ONFH, and is therefore limited. The present study proposes an 'ABC' method for ONFH typing based on biomechanics and the stress distribution characteristics of the femoral head's bone trabeculae. In total, 132 ONFH patients (223 hips) were enrolled at Guanganmen Hospital (Beijing, China). Each of the hip joints included was subjected to computerized tomography and/or magnetic resonance imaging. The images with the maximum necrotic area in the coronal femoral head were selected, and the femoral head's maximum transverse diameter was divided into three pillars (A, B and C, from the outside to the inside) according to a 3:4:3 diameter ratio. ONFH was typed according to the number of pillars involved in the necrosis. Differences in the collapse rate of different ONFH types, and the correlation between the theoretical collapse risk and the observed collapse rate was analysed. The ONFH types significantly differed in their collapse rate (χ2=76.93, P<0.001) in the following order: A-C (88.6%)>AB (74.1%)>BC (52.4%)>A (50%)>B (9.5%)>C (0%). The collapse risk was significantly correlated with the collapse rate (correlation coefficient R=1). The types A-C and AB had high collapse rates/risks, whereas types B and C had a satisfactory prognosis. The ABC typing proposed in the present study is thus suitable for collapse risk prediction in ONFH. Type classification using this method may provide a valuable reference for selecting regimens for ONFH treatment.
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