Deep learning radiomics under multimodality explore association between muscle/fat and metastasis and survival in breast cancer patients.

Publisher: Oxford University Press Country of Publication: England NLM ID: 100912837 Publication Model: Print Cited Medium: Internet ISSN: 1477-4054 (Electronic) Linking ISSN: 14675463 NLM ISO Abbreviation: Brief Bioinform Subsets: MEDLINE

Publication: Oxford : Oxford University Press
Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000-

Breast Neoplasms*/pathology ; Deep Learning*; Humans ; Female ; Tomography, X-Ray Computed/methods ; Cohort Studies ; Muscles/pathology

Sarcopenia is correlated with poor clinical outcomes in breast cancer (BC) patients. However, there is no precise quantitative study on the correlation between body composition changes and BC metastasis and survival. The present study proposed a deep learning radiomics (DLR) approach to investigate the effects of muscle and fat on distant metastasis and death outcomes in BC patients. Image feature extraction was performed on 4th thoracic vertebra (T4) and 11th thoracic vertebra (T11) on computed tomography (CT) image levels by DLR, and image features were combined with clinical information to predict distant metastasis in BC patients. Clinical information combined with DLR significantly predicted distant metastasis in BC patients. In the test cohort, the area under the curve of model performance on clinical information combined with DLR was 0.960 (95% CI: 0.942-0.979, P < 0.001). The patients with distant metastases had a lower pectoral muscle index in T4 (PMI/T4) than in patients without metastases. PMI/T4 and visceral fat tissue area in T11 (VFA/T11) were independent prognostic factors for the overall survival in BC patients. The pectoralis muscle area in T4 (PMA/T4) and PMI/T4 is an independent prognostic factor for distant metastasis-free survival in BC patients. The current study further confirmed that muscle/fat of T4 and T11 levels have a significant effect on the distant metastasis of BC. Appending the network features of T4 and T11 to the model significantly enhances the prediction performance of distant metastasis of BC, providing a valuable biomarker for the early treatment of BC patients.
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NCC201908B09 National Cancer Center Climb Plan; LBH-Z15100 Heilongjiang Provincial Postdoctoral Funding Project

Keywords: BC; DLR; distant metastasis; multimodality; muscle/fat; overall survival

Date Created: 20221005 Date Completed: 20221123 Latest Revision: 20221212

20250114

10.1093/bib/bbac432

36198668