Work

Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis☆

Year: 2025

Type: article

Abstract: = 0.955). Interestingly, the compliances of the predicted and ground truth structures demonstrated nearly identical linear relationships with the lesion volumes. In summary, we have demonstrated that bone deterioration could be proficiently predicted using machine learning in our preclinical dataset, suggesting the importance of large longitudinal clinical imaging datasets in fracture risk assessment for cancer bone metastasis.

Source: Mechanobiology in Medicine

DOI: 10.1016/j.mbm.2025.100130

Authors: Shubo Wang, Tiankuo Chu, Murtaza Wasi, Rosa M. Guerra, Xu Yuan, Liyun Wang

Institution: University of Delaware

Language: English

Topic: Management of metastatic bone disease

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,600