Yue Ma1, Aidi Liu1, Avice M O'Connell2, Yueqiang Zhu1, Haijie Li1, Peng Han1, Lu Yin1, Hong Lu1, Zhaoxiang Ye3. 1. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China. 2. Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, 14623, USA. 3. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China. yezhaoxiang@163.com.
Abstract
OBJECTIVES: To investigate the association of contrast-enhanced cone beam breast CT (CE-CBBCT) features, immunohistochemical (IHC) receptors, and molecular subtypes in breast cancer. METHODS: In this retrospective study, patients who underwent preoperative CE-CBBCT and received complete IHC results were analyzed. CE-CBBCT features were evaluated by two radiologists. Observer reproducibility and feature reliability were assessed. The association between CE-CBBCT features, IHC receptors, and molecular subtypes was analyzed using the chi-square, Mann-Whitney, and Kruskal-Wallis tests. Multivariate logistic regression was performed to assess the ability of combined imaging features to discriminate molecular subtypes. ROC curve was used to evaluate prediction performance. RESULTS: A total of 240 invasive cancers identified in 211 women were enrolled. Molecular subtypes of breast cancer were significantly associated with focality number of lesions, lesion type, tumor size, lesion density, internal enhancement pattern, degree of lesion enhancement (ΔHU), mass shape, spiculation, calcifications, calcification distribution, and increased peripheral vascularity of lesion (all p < 0.005), some of which also helped to differentiate IHC receptor status. A multivariate logistic regression model showed that tumor size (odds ratio, OR = 1.244), mass shape (OR = 0.311), spiculation (OR = 0.159), and internal enhancement pattern (OR = 0.227) were associated with differentiation between luminal and non-luminal subtypes (AUC = 0.809). Combined CE-CBBCT features, including lesion type (OR = 0.118), calcifications (OR = 0.181), and ΔHU (OR = 0.962), could be significant indicators of triple-negative versus HER-2-enriched subtypes (AUC = 0.913). CONCLUSIONS: CE-CBBCT features have the potential to help predict IHC receptor status and distinguish molecular subtypes of breast cancer, which could in turn help to develop individual treatment decisions and prognosis predictions. KEY POINTS: • A total of 11 CE-CBBCT features were associated with molecular subtypes, some of which also helped to differentiate IHC receptor status. • Tumor size, irregular mass shape, spiculation, and internal enhancement pattern could help identify luminal subtype. • Lesion type, calcification, and ΔHU could be significant indicators of HER-2- enriched versus triple-negative breast cancers.
OBJECTIVES: To investigate the association of contrast-enhanced cone beam breast CT (CE-CBBCT) features, immunohistochemical (IHC) receptors, and molecular subtypes in breast cancer. METHODS: In this retrospective study, patients who underwent preoperative CE-CBBCT and received complete IHC results were analyzed. CE-CBBCT features were evaluated by two radiologists. Observer reproducibility and feature reliability were assessed. The association between CE-CBBCT features, IHC receptors, and molecular subtypes was analyzed using the chi-square, Mann-Whitney, and Kruskal-Wallis tests. Multivariate logistic regression was performed to assess the ability of combined imaging features to discriminate molecular subtypes. ROC curve was used to evaluate prediction performance. RESULTS: A total of 240 invasive cancers identified in 211 women were enrolled. Molecular subtypes of breast cancer were significantly associated with focality number of lesions, lesion type, tumor size, lesion density, internal enhancement pattern, degree of lesion enhancement (ΔHU), mass shape, spiculation, calcifications, calcification distribution, and increased peripheral vascularity of lesion (all p < 0.005), some of which also helped to differentiate IHC receptor status. A multivariate logistic regression model showed that tumor size (odds ratio, OR = 1.244), mass shape (OR = 0.311), spiculation (OR = 0.159), and internal enhancement pattern (OR = 0.227) were associated with differentiation between luminal and non-luminal subtypes (AUC = 0.809). Combined CE-CBBCT features, including lesion type (OR = 0.118), calcifications (OR = 0.181), and ΔHU (OR = 0.962), could be significant indicators of triple-negative versus HER-2-enriched subtypes (AUC = 0.913). CONCLUSIONS:CE-CBBCT features have the potential to help predict IHC receptor status and distinguish molecular subtypes of breast cancer, which could in turn help to develop individual treatment decisions and prognosis predictions. KEY POINTS: • A total of 11 CE-CBBCT features were associated with molecular subtypes, some of which also helped to differentiate IHC receptor status. • Tumor size, irregular mass shape, spiculation, and internal enhancement pattern could help identify luminal subtype. • Lesion type, calcification, and ΔHU could be significant indicators of HER-2- enriched versus triple-negative breast cancers.
Entities:
Keywords:
Breast neoplasms; Cone beam computed tomography; Immunohistochemistry; Semantics