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Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts.
Wang, Hui; van der Velden, Bas H M; Verburg, Erik; Bakker, Marije F; Pijnappel, Ruud M; Veldhuis, Wouter B; van Gils, Carla H; Gilhuijs, Kenneth G A.
Afiliación
  • Wang H; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • van der Velden BHM; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • Verburg E; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • Bakker MF; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • Pijnappel RM; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • Veldhuis WB; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • van Gils CH; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
  • Gilhuijs KGA; From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
Radiology ; 308(2): e222841, 2023 08.
Article en En | MEDLINE | ID: mdl-37552061
ABSTRACT
Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies Límite: Female / Humans / Middle aged Idioma: En Revista: Radiology Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies Límite: Female / Humans / Middle aged Idioma: En Revista: Radiology Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos