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Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis.
Xiao, Jennifer; Rahbar, Habib; Hippe, Daniel S; Rendi, Mara H; Parker, Elizabeth U; Shekar, Neal; Hirano, Michael; Cheung, Kevin J; Partridge, Savannah C.
Affiliation
  • Xiao J; Department of Radiology, University of Washington, Seattle, WA, USA.
  • Rahbar H; Department of Radiology, University of Washington, Seattle, WA, USA.
  • Hippe DS; Breast Imaging, Seattle Cancer Care Alliance, Seattle, WA, USA.
  • Rendi MH; Department of Radiology, University of Washington, Seattle, WA, USA.
  • Parker EU; Department of Pathology, University of Washington, Seattle, WA, USA.
  • Shekar N; Department of Pathology, University of Washington, Seattle, WA, USA.
  • Hirano M; Department of Radiology, University of Washington, Seattle, WA, USA.
  • Cheung KJ; Department of Radiology, University of Washington, Seattle, WA, USA.
  • Partridge SC; Department of Medicine, Division of Medical Oncology, University of Washington, Seattle, WA, USA.
NPJ Breast Cancer ; 7(1): 42, 2021 Apr 16.
Article in En | MEDLINE | ID: mdl-33863924
Angiogenesis is a critical component of breast cancer development, and identification of imaging-based angiogenesis assays has prognostic and treatment implications. We evaluated the association of semi-quantitative kinetic and radiomic breast cancer features on dynamic contrast-enhanced (DCE)-MRI with microvessel density (MVD), a marker for angiogenesis. Invasive breast cancer kinetic features (initial peak percent enhancement [PE], signal enhancement ratio [SER], functional tumor volume [FTV], and washout fraction [WF]), radiomics features (108 total features reflecting tumor morphology, signal intensity, and texture), and MVD (by histologic CD31 immunostaining) were measured in 27 patients (1/2016-7/2017). Lesions with high MVD levels demonstrated higher peak SER than lesions with low MVD (mean: 1.94 vs. 1.61, area under the receiver operating characteristic curve [AUC] = 0.79, p = 0.009) and higher WF (mean: 50.6% vs. 22.5%, AUC = 0.87, p = 0.001). Several radiomics texture features were also promising for predicting increased MVD (maximum AUC = 0.84, p = 0.002). Our study suggests DCE-MRI can non-invasively assess breast cancer angiogenesis, which could stratify biology and optimize treatments.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: NPJ Breast Cancer Year: 2021 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: NPJ Breast Cancer Year: 2021 Document type: Article Affiliation country: United States Country of publication: United States