Viable tumor cell density after neoadjuvant chemotherapy assessed using deep learning model reflects the prognosis of osteosarcoma.

ABSTRACT: Prognosis after neoadjuvant chemotherapy (NAC) for osteosarcoma is generally predicted using manual necrosis-rate assessments; however, necrosis rates obtained in these assessments are not reproducible and do not adequately reflect individual cell responses. We aimed to investigate whether viable tumor cell density assessed using a deep-learning model (DLM) reflects the prognosis of osteosarcoma. Seventy-one patients were included in this study. Initially, the DLM was trained to detect viable tumor cells, following which it calculated their density. Patients were stratified into high and low-viable tumor cell density groups based on DLM measurements, and survival analysis was performed to evaluate disease-specific survival and metastasis-free survival (DSS and MFS). The high viable tumor c

SUBMITTER: Kawaguchi K 

PROVIDER: S-EPMC10803362 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature