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Bone · 2026

New local trabecular support ranks formation-labelled transitions: An image-derived framework for bone adaptation in human distal-tibia based on HR-pQCT.

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Liu Zihao, Li Simin, Silberschmidt Vadim V

Аннотация

Longitudinal HR-pQCT scans can identify mineralised-tissue gains and losses after image registration, but whether baseline trabecular architecture can rank the locations of subsequent image-derived transitions remains unclear. This study tested whether surface-conditioned local trabecular support can rank subsequent formation-labelled transitions directly from baseline images and whether a longitudinal axial-prolate neighbourhood provides additional information beyond the isotropic local support. Baseline and 6-month distal-tibia HR-pQCT scans of nine postmenopausal women are analysed, giving 18 side-level image pairs. The analysis is restricted to baseline surface-marrow voxels, defined as marrow voxels sharing a face with baseline bone. A spherical support count provides an isotropic local-BV/TV-equivalent baseline. The proposed axial-prolate operator counts baseline bone voxels within an ellipsoidal neighbourhood, with its long axis aligned with the scanner's z-axis. Ranking performance is evaluated using leave-one-subject-out ROC-AUC. The obtained results indicate that the spherical local support ranks subsequent formation-labelled transitions above chance, showing that an isotropic local bone amount already contains prospective surface-conditioned information. The axial-prolate operator further improves this process. Matched-volume comparisons show that both anisotropy and longitudinal orientation contribute to this gain, while local-BV/TV-stratified analyses indicate that the directional signal is not fully reducible to the isotropic local bone amount. These findings establish an image-derived framework for ranking trabecular formation-labelled transitions from the baseline architecture alone. The distal-tibia application indicates that site-informed directional kernels can refine the general local-support framework. External validation is required to determine whether the kernel scale and alignment should be recalibrated for other anatomical sites and populations.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты