We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Tumor Heterogeneity of Breast Cancer Assessed with Computed Tomography Texture Analysis: Association with Disease-Free Survival and Clinicopathological Prognostic Factor.
- Authors
Yoo, Hyeongyu; Cho, Kyu Ran; Song, Sung Eun; Cho, Yongwon; Jung, Seung Pil; Sung, Kihoon
- Abstract
Breast cancer is a heterogeneous disease, and computed tomography texture analysis (CTTA), which reflects the tumor heterogeneity, may predict the prognosis. We investigated the usefulness of CTTA for the prediction of disease-free survival (DFS) and prognostic factors in patients with invasive breast cancer. A total of 256 consecutive women who underwent preoperative chest CT and surgery in our institution were included. The Cox proportional hazards model was used to determine the relationship between textural features and DFS. Logistic regression analysis was used to reveal the relationship between textural features and prognostic factors. Of 256 patients, 21 (8.2%) had disease recurrence over a median follow-up of 60 months. For the prediction of shorter DFS, higher histological grade (hazard ratio [HR], 6.12; p < 0.001) and lymphovascular invasion (HR, 2.93; p = 0.029) showed significance, as well as textural features such as lower mean attenuation (HR, 4.71; p = 0.003) and higher entropy (HR, 2.77; p = 0.036). Lower mean attenuation showed a correlation with higher tumor size, and higher entropy showed correlations with higher tumor size and Ki-67. In conclusion, CTTA-derived textural features can be used as a noninvasive imaging biomarker to predict shorter DFS and prognostic factors in patients with invasive breast cancer.
- Subjects
TEXTURE analysis (Image processing); PROGRESSION-free survival; PROGNOSIS; COMPUTED tomography; BREAST cancer
- Publication
Diagnostics (2075-4418), 2023, Vol 13, Issue 23, p3569
- ISSN
2075-4418
- Publication type
Article
- DOI
10.3390/diagnostics13233569