TY - JOUR
T1 - Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts
AU - Wang, Hui
AU - van der Velden, Bas H.M.
AU - Verburg, Erik
AU - Bakker, Marije F.
AU - Pijnappel, Ruud M.
AU - Veldhuis, Wouter B.
AU - van Gils, Carla H.
AU - Gilhuijs, Kenneth G.A.
N1 - Funding Information:
Supported by KWF Kankerbestrijding (grant no. UU-2014-7151). The DENSE trial is financially supported by the University Medical Center Utrecht (project number: UMCU DENSE), the Netherlands Organization for Health Research and Development (ZonMw, project no. ZONMW‐200320002‐UMCU and ZonMw Preventie 50‐53125‐98‐014), the Dutch Cancer Society (KWF Kankerbestrijding, project number c), the Dutch Pink Ribbon/A Sister’s Hope (project no, Pink Ribbon‐10074), Pharmaceuticals Bayer, Radiology (project number BSP‐DENSE), and Stichting Kankerpreventie Midden-West.
Funding Information:
Supported by KWF Kankerbestrijding (grant no. UU-2014-7151). The DENSE trial is financially supported by the University Medical Center Utrecht (project number: UMCU DENSE), the Netherlands Organization for Health Research and Development (ZonMw, project no. ZONMW‐200320002‐UMCU and ZonMw Preventie 50‐53125‐98‐014), the Dutch Cancer Society (KWF Kankerbestrijding, project number c), the Dutch Pink Ribbon/A Sister’s Hope (project no, Pink Ribbon‐10074), Pharmaceuticals Bayer, Radiology (project number BSP‐DENSE), and Stichting Kankerpreventie Midden-West. The authors thank the registration team of the Netherlands Comprehensive Cancer Organisation for the collection of data for the Netherlands Cancer Registry.
Publisher Copyright:
© RSNA, 2023.
PY - 2023/8
Y1 - 2023/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85166784646&partnerID=8YFLogxK
U2 - 10.1148/radiol.222841
DO - 10.1148/radiol.222841
M3 - Article
C2 - 37552061
AN - SCOPUS:85166784646
SN - 0033-8419
VL - 308
JO - Radiology
JF - Radiology
IS - 2
M1 - e222841
ER -