Relationships between material properties and CT scan data of cortical bone with and without metastatic lesions
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Updated: Sep 25, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Published on: August 16, 2020
Tadashi S Kaneko1, Marina R Pejcic, Jamshid Tehranzadeh
1Department of Orthopaedic Surgery, University of California, Irvine, CA 92697, USA.
Abstract:
Breast, prostate, lung, and other cancers can metastasize to bone and lead to pathological fracture. To lay the groundwork for new clinical techniques for assessing the risk of pathological fracture, we identified relationships between density measured using quantitative computed tomography (rhoQCT), longitudinal mechanical properties, and ash density (rhoAsh) of cortical bone from femoral diaphyses with and without metastatic lesions from breast, prostate, and lung cancer (bone with metastases from six donors; bone without metastases from one donor with cancer and two donors without cancer). Moderately strong linear relationships between rhoQCT and elastic modulus, strength, and rhoAsh were found for bone with metastases (0.73
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