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Chen M, Xing J, Guo L. MRI-based Deep Learning Models for Preoperative Breast Volume and Density Assessment Assisting Breast Reconstruction. Aesthetic Plast Surg 2024:10.1007/s00266-024-04074-2. [PMID: 38806828 DOI: 10.1007/s00266-024-04074-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 04/09/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND The volume of the implant is the most critical element of breast reconstruction, so it is necessary to accurately assess the preoperative volume of the healthy and affected breasts and select the appropriate implant for placement. Accurate and automated methods for quantitative assessment of breast volume can optimize breast reconstruction surgery and assist physicians in clinical decision making. The aim of this study was to develop an artificial intelligence model for automated segmentation of the breast and measurement of volume. MATERIAL AND METHODS A total of 249 subjects undergoing breast reconstruction surgery were enrolled in this study. Subjects underwent preoperative breast MRI, and the breast region manually outlined by the imaging physician served as the gold standard for volume measurement by the automated segmentation model. In this study, we developed three automated algorithms for automatic segmentation of breast regions, including a simple alignment model, an alignment dynamic encoding model, and a deep learning model. The volumetric agreement between the three automated segmentation algorithms and the breast regions manually segmented by imaging physicians was evaluated by calculating the mean square error (MSE) and intragroup correlation coefficient (ICC), and the reproducibility of the automated segmentation of the breast regions was assessed by the test-retest step. RESULTS The three breast automated segmentation models developed in this study (simple registration model, dynamic programming model, and deep learning model) showed strong ICC with manual segmentation of the breast region, with MSEs of 1.124, 0.693, and 0.781, and ICCs of 0.975 (95% CI, 0.869-0.991), 0.986 (95% CI, 0.967-0.996), and 0.983 (95% CI, 0.961-0.992), respectively. Regarding the test-retest results of breast volume, the dynamic programming model performed the best with an MSE of 0.370 and an ICC of 0.993 (95% CI, 0.982-0.997), followed by the deep learning algorithm with an MSE of 0.741 and an ICC of 0.983 (95% CI, 0.956-0.993), and the simple registration algorithm with an MSE of 0.763 and an ICC of 0.982 (95% CI, 0.949-0.993). The reproducibility of the breast region segmented by the three automated algorithms was higher than that of manual segmentation by different radiologists. CONCLUSION The three automated breast segmentation algorithms developed in this study generate accurate and reliable breast regions, enable highly reproducible breast region segmentation and automated volume measurements, and provide a valuable tool for surgical selection of appropriate prostheses. NO LEVEL ASSIGNED This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Affiliation(s)
- Muzi Chen
- Department of Plastic and Reconstructive Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Jiahua Xing
- Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 33 Badachu Road, Shijingshan District, Beijing, 100144, China
| | - Lingli Guo
- Department of Plastic and Reconstructive Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
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Kerlikowske K, Chen S, Bissell MCS, Lee CI, Tice JA, Sprague BL, Miglioretti DL. Population Attributable Risk of Advanced-Stage Breast Cancer by Race and Ethnicity. JAMA Oncol 2024; 10:167-175. [PMID: 38060241 PMCID: PMC10704341 DOI: 10.1001/jamaoncol.2023.5242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/31/2023] [Indexed: 12/08/2023]
Abstract
Importance Advanced-stage breast cancer rates vary by race and ethnicity, with Black women having a 2-fold higher rate than White women among regular screeners. Clinical risk factors that explain a large proportion of advanced breast cancers by race and ethnicity are unknown. Objective To evaluate the population attributable risk proportions (PARPs) for advanced-stage breast cancer (prognostic pathologic stage IIA or higher) associated with clinical risk factors among routinely screened premenopausal and postmenopausal women by race and ethnicity. Design, Setting, and Participants This cohort study used data collected prospectively from Breast Cancer Surveillance Consortium community-based breast imaging facilities from January 2005 to June 2018. Participants were women aged 40 to 74 years undergoing 3 331 740 annual (prior screening within 11-18 months) or biennial (prior screening within 19-30 months) screening mammograms associated with 1815 advanced breast cancers diagnosed within 2 years of screening examinations. Data analysis was performed from September 2022 to August 2023. Exposures Heterogeneously or extremely dense breasts, first-degree family history of breast cancer, overweight/obesity (body mass index >25.0), history of benign breast biopsy, and screening interval (biennial vs annual) stratified by menopausal status and race and ethnicity (Asian or Pacific Islander, Black, Hispanic/Latinx, White, other/multiracial). Main Outcomes and Measures PARPs for advanced breast cancer. Results Among 904 615 women, median (IQR) age was 57 (50-64) years. Of the 3 331 740 annual or biennial screening mammograms, 10.8% were for Asian or Pacific Islander women; 9.5% were for Black women; 5.3% were for Hispanic/Latinx women; 72.0% were for White women; and 2.0% were for women of other races and ethnicities, including those who were Alaska Native, American Indian, 2 or more reported races, or other. Body mass index PARPs were larger for postmenopausal vs premenopausal women (30% vs 22%) and highest for postmenopausal Black (38.6%; 95% CI, 32.0%-44.8%) and Hispanic/Latinx women (31.8%; 95% CI, 25.3%-38.0%) and premenopausal Black women (30.3%; 95% CI, 17.7%-42.0%), with overall prevalence of having overweight/obesity highest in premenopausal Black (84.4%) and postmenopausal Black (85.1%) and Hispanic/Latinx women (72.4%). Breast density PARPs were larger for premenopausal vs postmenopausal women (37% vs 24%, respectively) and highest among premenopausal Asian or Pacific Islander (46.6%; 95% CI, 37.9%-54.4%) and White women (39.8%; 95% CI, 31.7%-47.3%) whose prevalence of dense breasts was high (62%-79%). For premenopausal and postmenopausal women, PARPs were small for family history of breast cancer (5%-8%), history of breast biopsy (7%-12%), and screening interval (2.1%-2.3%). Conclusions and Relevance In this cohort study among routinely screened women, the proportion of advanced breast cancers attributed to biennial vs annual screening was small. To reduce the number of advanced breast cancer diagnoses, primary prevention should focus on interventions that shift patients with overweight and obesity to normal weight.
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Affiliation(s)
- Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco
- General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco
| | - Shuai Chen
- Department of Public Health Sciences, University of California, Davis
| | - Michael C. S. Bissell
- Department of Public Health Sciences, University of California, Davis
- PicnicHealth, San Francisco, California
| | - Christoph I. Lee
- Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle
| | - Jeffrey A. Tice
- Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco
| | - Brian L. Sprague
- Departments of Surgery and Radiology, University of Vermont, Burlington
| | - Diana L. Miglioretti
- Department of Public Health Sciences, University of California, Davis
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle
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Bae SJ, Kim HJ, Kim HA, Ryu JM, Park S, Lee EG, Im SA, Jung Y, Park MH, Park KH, Kang SH, Park E, Kim SY, Lee MH, Kim LS, Lee A, Noh WC, Gwark S, Kim S, Jeong J. Breast density reduction as a predictor for prognosis in premenopausal women with estrogen receptor-positive breast cancer: an exploratory analysis of the updated ASTRRA study. Int J Surg 2024; 110:934-942. [PMID: 38000057 PMCID: PMC10871609 DOI: 10.1097/js9.0000000000000907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 11/02/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND While the relationship between mammographic breast density reduction (MDR) and endocrine therapy efficacy has been reported in estrogen receptor (ER)-positive breast cancer, it is still unclear in premenopausal women, especially in the case of adding ovarian function suppression (OFS) to antihormone therapy. The authors investigated the impact of MDR on prognosis stratified by treatment based on the updated results of the ASTRRA trial. MATERIALS AND METHODS The ASTRRA trial, a randomized phase III study, showed that adding OFS to tamoxifen (TAM) improved survival in premenopausal women with estrogen receptor-positive breast cancer after chemotherapy. The authors updated survival outcomes and assessed mammography before treatment and the annual follow-up mammography for up to 5 years after treatment initiation. Mammographic density (MD) was classified into four categories based on the Breast Imaging-Reporting and Data System. MDR-positivity was defined as a downgrade in MD grade on follow-up mammography up to 2 years after randomization, with pretreatment MD grade as a reference. RESULTS The authors evaluated MDR in 944 of the 1282 patients from the trial, and 813 (86.2%) had grade III or IV MD. There was no difference in the MDR-positivity rate between the two treatment groups [TAM-only group (106/476 (22.3%)) vs. TAM+OFS group (89/468 (19.0%)); P =0.217). MDR-positivity was significantly associated with better disease-free survival (DFS) in the TAM+OFS group (estimated 8-year DFS: 93.1% in MDR-positive vs. 82.0% in MDR-negative patients; HR: 0.37; 95% CI: 0.16-0.85; P =0.019), but not in the TAM-only group ( Pinteraction =0.039). MDR-positive patients who received TAM+OFS had a favorable DFS compared to MDR-negative patients who received only TAM (HR: 0.30; 95% CI: 0.13-0.70; P =0.005). CONCLUSION Although the proportion of MDR-positive patients was comparable between both treatment groups, MDR-positivity was independently associated with favorable outcomes only in the TAM+OFS group.
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Affiliation(s)
- Soong June Bae
- Department of Surgery, Gangnam Severance Hospital
- Institute for Breast Cancer Precision Medicine, Yonsei University College of Medicine
| | - Hee Jeong Kim
- Division of Breast, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine
| | - Hyun-Ah Kim
- Department of Surgery, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences
| | - Jai Min Ryu
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine
| | - Seho Park
- Division of Breast Surgery, Department of Surgery, Yonsei Cancer Center, Yonsei University College of Medicine
| | - Eun-Gyeong Lee
- Center for Breast Cancer, Research Institute and Hospital, National Cancer Center, Goyang, South Korea
| | - Seock-Ah Im
- Seoul National University Hospital, Cancer Research Institute, Seoul National University, College of Medicine
| | - Yongsik Jung
- Department of Surgery, Ajou University, School of Medicine, Suwon
| | - Min Ho Park
- Department of Surgery, Chonnam National University Medical School and Chonnam National University Hwasun Hospital, Gwangju
| | - Kyong Hwa Park
- Korea University Anam Hospital, Department of internal medicine, Division of Medical Oncology/Hematology
| | | | - Eunhwa Park
- Department of Surgery, Dong-A University Hospital, Dong-A University College of Medicine, Busan
| | - Sung Yong Kim
- Department of Surgery, Soonchunhyang University Cheonan Hospital, Cheonan
| | - Min Hyuk Lee
- Department of Surgery, Soonchunhyang University Hospital, Seoul
| | - Lee Su Kim
- Department of Surgery, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong
| | - Anbok Lee
- Department of Surgery, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong
| | - Woo Chul Noh
- Department of Surgery, Konkuk Universitiy Medical Center
| | - Sungchan Gwark
- Department of Surgery, Ewha Womans University College of Medicine, Ewha Womans University Mokdong Hospital
| | - Seonok Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center
| | - Joon Jeong
- Department of Surgery, Gangnam Severance Hospital
- Institute for Breast Cancer Precision Medicine, Yonsei University College of Medicine
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Behrens A, Fasching PA, Schwenke E, Gass P, Häberle L, Heindl F, Heusinger K, Lotz L, Lubrich H, Preuß C, Schneider MO, Schulz-Wendtland R, Stumpfe FM, Uder M, Wunderle M, Zahn AL, Hack CC, Beckmann MW, Emons J. Predicting mammographic density with linear ultrasound transducers. Eur J Med Res 2023; 28:384. [PMID: 37770952 PMCID: PMC10537934 DOI: 10.1186/s40001-023-01327-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments. METHODS We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high-frequency (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage mammographic density (PMD) was predicted by gray level bins using various regression models. RESULTS Gray level bins and PMD correlated to a certain extent. Spearman's ρ ranged from - 0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R2, 0.255). Overall, ultrasound images from the VOLUSON® 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms. CONCLUSIONS In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).
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Affiliation(s)
- Annika Behrens
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany.
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Eva Schwenke
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Paul Gass
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Lothar Häberle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
- Biostatistics Unit, Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Felix Heindl
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Katharina Heusinger
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Laura Lotz
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Hannah Lubrich
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Caroline Preuß
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Michael O Schneider
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Rüdiger Schulz-Wendtland
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Florian M Stumpfe
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Michael Uder
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Marius Wunderle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Anna L Zahn
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Carolin C Hack
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Julius Emons
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
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Edmonds CE, O'Brien SR, Conant EF. Mammographic Breast Density: Current Assessment Methods, Clinical Implications, and Future Directions. Semin Ultrasound CT MR 2023; 44:35-45. [PMID: 36792272 DOI: 10.1053/j.sult.2022.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening mammography. Given the risks associated with breast density, as well as ongoing efforts to stratify individual risk and personalize breast cancer screening and prevention, numerous studies have sought to better understand the factors that impact breast density, and to develop and implement reproducible, quantitative methods to assess mammographic density. Breast density assessments have been incorporated into risk assessment models to improve risk stratification. Recently, novel techniques for analyzing mammographic parenchymal complexity, or texture, have been explored as potential means of refining mammographic tissue-based risk assessment beyond breast density.
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Affiliation(s)
- Christine E Edmonds
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA.
| | - Sophia R O'Brien
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Emily F Conant
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA
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Shia WC, Lin LS, Wu HK, Chen CJ, Chen DR. Mammographic Density Reduction is Associated to the Prognosis in Asian Breast Cancer Patients Receiving Hormone Therapy. Cancer Control 2023; 30:10732748231160991. [PMID: 36866691 PMCID: PMC9989438 DOI: 10.1177/10732748231160991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023] Open
Abstract
INTRODUCTION Using mammographic density as a significant biomarker for predicting prognosis in adjuvant hormone therapy patients is controversial due to the conflicting results of recent studies. This study aimed to evaluate hormone therapy-induced mammographic density reduction and its association with prognosis in Taiwanese patients. METHODS In this retrospective study, 1941 patients with breast cancer were screened, and 399 patients with estrogen receptor-positive breast cancer who received adjuvant hormone therapy were enrolled. The mammographic density was measured using a fully automatic estimation procedure based on full-field digital mammography. The prognosis included relapse and metastasis during treatment follow-up. The Kaplan-Meier method and Cox proportional hazards model were used for disease-free survival analysis. RESULTS A mammographic density reduction rate >20.8%, measured preoperatively and after receiving hormone therapy from 12-18 months, was a significant threshold for predicting prognosis in patients with breast cancer. The disease-free survival rate was significantly higher in patients whose mammographic density reduction rate was >20.8% (P = .048). CONCLUSION This study's findings could help estimate the prognosis for patients with breast cancer and may improve the quality of adjuvant hormone therapy after enlarging the study cohort in the future.
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Affiliation(s)
- Wei-Chung Shia
- Molecular Medicine Laboratory, Department of Research, Changhua Christian Hospital, Changhua, Taiwan
| | - Li-Sheng Lin
- Department of Breast Surgery, 117821The Affiliated Hospital (Group) of Putian University, Putian, Fujian, China
| | - Hwa-Koon Wu
- Department of Medical Imaging, Changhua Christian Hospital, Changhua, Taiwan
| | - Chih-Jung Chen
- Department of Pathology and Laboratory Medicine, 40293Taichung Veterans General Hospital, Taichung, Taiwan.,Department of General Surgery, Changhua Christian Hospital, Changhua, Taiwan
| | - Dar-Ren Chen
- Department of General Surgery, Changhua Christian Hospital, Changhua, Taiwan
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Ying J, Cattell R, Zhao T, Lei L, Jiang Z, Hussain SM, Gao Y, Chow HHS, Stopeck AT, Thompson PA, Huang C. Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility. Vis Comput Ind Biomed Art 2022; 5:25. [PMID: 36219359 PMCID: PMC9554077 DOI: 10.1186/s42492-022-00121-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/21/2022] [Indexed: 11/07/2022] Open
Abstract
Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is desirable. In this study, we aimed to develop a highly reproducible and accurate whole-breast segmentation algorithm for the generation of reproducible BD measures. Three datasets of volunteers from two clinical trials were included. Breast MR images were acquired on 3 T Siemens Biograph mMR, Prisma, and Skyra using 3D Cartesian six-echo GRE sequences with a fat-water separation technique. Two whole-breast segmentation strategies, utilizing image registration and 3D U-Net, were developed. Manual segmentation was performed. A task-based analysis was performed: a previously developed MR-based BD measure, MagDensity, was calculated and assessed using automated and manual segmentation. The mean squared error (MSE) and intraclass correlation coefficient (ICC) between MagDensity were evaluated using the manual segmentation as a reference. The test-retest reproducibility of MagDensity derived from different breast segmentation methods was assessed using the difference between the test and retest measures (Δ2-1), MSE, and ICC. The results showed that MagDensity derived by the registration and deep learning segmentation methods exhibited high concordance with manual segmentation, with ICCs of 0.986 (95%CI: 0.974-0.993) and 0.983 (95%CI: 0.961-0.992), respectively. For test-retest analysis, MagDensity derived using the registration algorithm achieved the smallest MSE of 0.370 and highest ICC of 0.993 (95%CI: 0.982-0.997) when compared to other segmentation methods. In conclusion, the proposed registration and deep learning whole-breast segmentation methods are accurate and reliable for estimating BD. Both methods outperformed a previously developed algorithm and manual segmentation in the test-retest assessment, with the registration exhibiting superior performance for highly reproducible BD measurements.
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Affiliation(s)
- Jia Ying
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Renee Cattell
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
- Department of Radiation Oncology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Tianyun Zhao
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Lan Lei
- Department of Medicine, Northside Hospital Gwinnett, Lawrenceville, GA, 30046, USA
- Program of Public Health, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Zhao Jiang
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Shahid M Hussain
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Yi Gao
- Department of Biomedical Informatics, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China
| | | | - Alison T Stopeck
- Department of Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Patricia A Thompson
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY, 11794, USA
- Department of Medicine, Cedar Sinai Cancer, Cedars Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Chuan Huang
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA.
- Department of Radiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA.
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY, 11794, USA.
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Chalfant JS, Hoyt AC. Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications. JOURNAL OF BREAST IMAGING 2022; 4:357-370. [PMID: 38416979 DOI: 10.1093/jbi/wbac028] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Indexed: 03/01/2024]
Abstract
Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.
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Affiliation(s)
- James S Chalfant
- David Geffen School of Medicine at University of California, Los Angeles, Department of Radiological Sciences, Santa Monica, CA, USA
| | - Anne C Hoyt
- David Geffen School of Medicine at University of California, Los Angeles, Department of Radiological Sciences, Santa Monica, CA, USA
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Use of a convolutional neural network-based mammographic evaluation to predict breast cancer recurrence among women with hormone receptor-positive operable breast cancer. Breast Cancer Res Treat 2022; 194:35-47. [PMID: 35575954 DOI: 10.1007/s10549-022-06614-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 04/18/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE We evaluated whether a novel, fully automated convolutional neural network (CNN)-based mammographic evaluation can predict breast cancer relapse among women with operable hormone receptor (HR)-positive breast cancer. METHODS We conducted a retrospective cohort study among women with stage I-III, HR-positive unilateral breast cancer diagnosed at Columbia University Medical Center from 2007 to 2017, who received adjuvant endocrine therapy and had at least two mammograms (baseline, annual follow-up) of the contralateral unaffected breast for CNN analysis. We extracted demographics, clinicopathologic characteristics, breast cancer treatments, and relapse status from the electronic health record. Our primary endpoint was change in CNN risk score (range, 0-1). We used two-sample t-tests to assess for difference in mean CNN scores between patients who relapsed vs. remained in remission, and conducted Cox regression analyses to assess for association between change in CNN score and breast cancer-free interval (BCFI), adjusting for known prognostic factors. RESULTS Among 848 women followed for a median of 59 months, there were 67 (7.9%) breast cancer relapses (36 distant, 25 local, 6 new primaries). There was a significant difference in mean absolute change in CNN risk score from baseline to 1-year follow-up between those who relapsed vs. remained in remission (0.001 vs. - 0.022, p = 0.030). After adjustment for prognostic factors, a 0.01 absolute increase in CNN score at 1-year was significantly associated with BCFI, hazard ratio = 1.05 (95% Confidence Interval 1.01-1.09, p = 0.011). CONCLUSION Short-term change in the CNN-based breast cancer risk model on adjuvant endocrine therapy predicts breast cancer relapse, and warrants further evaluation in prospective studies.
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Acheampong T, Lee Argov EJ, Terry MB, Rodriguez CB, Agovino M, Wei Y, Athilat S, Tehranifar P. Current regular aspirin use and mammographic breast density: a cross-sectional analysis considering concurrent statin and metformin use. Cancer Causes Control 2022; 33:363-371. [PMID: 35022893 DOI: 10.1007/s10552-021-01530-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 11/25/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE The nonsteroidal anti-inflammatory drug aspirin is an agent of interest for breast cancer prevention. However, it is unclear if aspirin affects mammographic breast density (MBD), a marker of elevated breast cancer risk, particularly in the context of concurrent use of medications indicated for common cardiometabolic conditions, which may also be associated with MBD. METHODS We used data from the New York Mammographic Density Study for 770 women age 40-60 years old with no history of breast cancer. We evaluated the association between current regular aspirin use and MBD, using linear regression for continuous measures of absolute and percent dense areas and absolute non-dense area, adjusted for body mass index (BMI), sociodemographic and reproductive factors, and use of statins and metformin. We assessed effect modification by BMI and reproductive factors. RESULTS After adjustment for co-medication, current regular aspirin use was only positively associated with non-dense area (β = 18.1, 95% CI: 6.7, 29.5). Effect modification by BMI and parity showed current aspirin use to only be associated with larger non-dense area among women with a BMI ≥ 30 (β = 28.2, 95% CI: 10.8, 45.7), and with lower percent density among parous women (β = -3.3, 95% CI: -6.4, -0.3). CONCLUSIONS Independent of co-medication use, current regular aspirin users had greater non-dense area with stronger estimates for women with higher BMI. We found limited support for an association between current aspirin use and mammographically dense breast tissue among parous women.
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Affiliation(s)
- Teofilia Acheampong
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Erica J Lee Argov
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, 1130 St Nicholas Ave, New York, NY, 10032, USA
| | - Carmen B Rodriguez
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Mariangela Agovino
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Ying Wei
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA.,Department of Biostatistics, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Shweta Athilat
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA
| | - Parisa Tehranifar
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th street, New York, NY, 10032, USA. .,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, 1130 St Nicholas Ave, New York, NY, 10032, USA.
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11
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Atakpa EC, Thorat MA, Cuzick J, Brentnall AR. Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review. Cochrane Database Syst Rev 2021; 10:CD013091. [PMID: 34697802 PMCID: PMC8545623 DOI: 10.1002/14651858.cd013091.pub2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Endocrine therapy is effective at preventing or treating breast cancer. Some forms of endocrine therapy have been shown to reduce mammographic density. Reduced mammographic density for women receiving endocrine therapy could be used to estimate the chance of breast cancer returning or developing breast cancer in the first instance (a prognostic biomarker). In addition, changes in mammographic density might be able to predict how well a woman responds to endocrine therapy (a predictive biomarker). The role of breast density as a prognostic or predictive biomarker could help improve the management of breast cancer. OBJECTIVES To assess the evidence that a reduction in mammographic density following endocrine therapy for breast cancer prevention in women without previous breast cancer, or for treatment in women with early-stage hormone receptor-positive breast cancer, is a prognostic or predictive biomarker. SEARCH METHODS We searched the Cochrane Breast Cancer Group Specialised Register, CENTRAL, MEDLINE, Embase, and two trials registers on 3 August 2020 along with reference checking, bibliographic searching, and contact with study authors to obtain further data. SELECTION CRITERIA We included randomised, cohort and case-control studies of adult women with or without breast cancer receiving endocrine therapy. Endocrine therapy agents included were selective oestrogen receptor modulators and aromatase inhibitors. We required breast density before start of endocrine therapy and at follow-up. We included studies published in English. DATA COLLECTION AND ANALYSIS We used standard methodological procedures expected by Cochrane. Two review authors independently extracted data and assessed risk of bias using adapted Quality in Prognostic Studies (QUIPS) and Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. We used the GRADE approach to evaluate the certainty of the evidence. We did not perform a quantitative meta-analysis due to substantial heterogeneity across studies. MAIN RESULTS Eight studies met our inclusion criteria, of which seven provided data on outcomes listed in the protocol (5786 women). There was substantial heterogeneity across studies in design, sample size (349 to 1066 women), participant characteristics, follow-up (5 to 14 years), and endocrine therapy agent. There were five breast density measures and six density change definitions. All studies had at least one domain as at moderate or high risk of bias. Common concerns were whether the study sample reflected the review target population, and likely post hoc definitions of breast density change. Most studies on prognosis for women receiving endocrine therapy reported a reduced risk associated with breast density reduction. Across endpoints, settings, and agents, risk ratio point estimates (most likely value) were between 0.1 and 1.5, but with substantial uncertainty. There was greatest consistency in the direction and magnitude of the effect for tamoxifen (across endpoints and settings, risk ratio point estimates were between 0.3 and 0.7). The findings are summarised as follows. Prognostic biomarker findings: Treatment Breast cancer mortality Two studies of 823 women on tamoxifen (172 breast cancer deaths) reported risk ratio point estimates of ~0.4 and ~0.5 associated with a density reduction. The certainty of the evidence was low. Recurrence Two studies of 1956 women on tamoxifen reported risk ratio point estimates of ~0.4 and ~0.7 associated with a density reduction. There was risk of bias in methodology for design and analysis of the studies and considerable uncertainty over the size of the effect. One study of 175 women receiving an aromatase inhibitor reported a risk ratio point estimate of ~0.1 associated with a density reduction. There was considerable uncertainty about the effect size and a moderate or high risk of bias in all domains. One study of 284 women receiving exemestane or tamoxifen as part of a randomised controlled trial reported risk ratio point estimates of ~1.5 (loco-regional recurrence) and ~1.3 (distance recurrence) associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the size of the effects. The certainty of the evidence for all recurrence endpoints was very low. Incidence of a secondary primary breast cancer Two studies of 451 women on exemestane, tamoxifen, or unknown endocrine therapy reported risk ratio point estimates of ~0.5 and ~0.6 associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the effect size. The certainty of the evidence was very low. We were unable to find data regarding the remaining nine outcomes prespecified in the review protocol. Prevention Incidence of invasive breast cancer and ductal carcinoma in situ (DCIS) One study of 507 women without breast cancer who were receiving preventive tamoxifen as part of a randomised controlled trial (51 subsequent breast cancers) reported a risk ratio point estimate of ~0.3 associated with a density reduction. The certainty of the evidence was low. Predictive biomarker findings: One study of a subset of 1065 women from a randomised controlled trial assessed how much the effect of endocrine therapy could be explained by breast density declines in those receiving endocrine therapy. This study evaluated the prevention of invasive breast cancer and DCIS. We found some evidence to support the hypothesis, with a risk ratio interaction point estimate ~0.5. However, the 95% confidence interval included unity, and data were based on 51 women with subsequent breast cancer in the tamoxifen group. The certainty of the evidence was low. AUTHORS' CONCLUSIONS There is low-/very low-certainty evidence to support the hypothesis that breast density change following endocrine therapy is a prognostic biomarker for treatment or prevention. Studies suggested a potentially large effect size with tamoxifen, but the evidence was limited. There was less evidence that breast density change following tamoxifen preventive therapy is a predictive biomarker than prognostic biomarker. Evidence for breast density change as a prognostic treatment biomarker was stronger for tamoxifen than aromatase inhibitors. There were no studies reporting mammographic density change following endocrine therapy as a predictive biomarker in the treatment setting, nor aromatase inhibitor therapy as a prognostic or predictive biomarker in the preventive setting. Further research is warranted to assess mammographic density as a biomarker for all classes of endocrine therapy and review endpoints.
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Affiliation(s)
- Emma C Atakpa
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Mangesh A Thorat
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- Breast Services, Guy's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Jack Cuzick
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Adam R Brentnall
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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12
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Thorén L, Eriksson M, Lindh JD, Czene K, Bergh J, Eliasson E, Hall P, Margolin S. Impact of systemic adjuvant therapy and CYP2D6 activity on mammographic density in a cohort of tamoxifen-treated breast cancer patients. Breast Cancer Res Treat 2021; 190:451-462. [PMID: 34570302 PMCID: PMC8558195 DOI: 10.1007/s10549-021-06386-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/06/2021] [Indexed: 11/27/2022]
Abstract
PURPOSE Change in mammographic density has been suggested to be a proxy of tamoxifen response. We investigated the effect of additional adjuvant systemic therapy and CYP2D6 activity on MD change in a cohort of tamoxifen-treated pre- and postmenopausal breast cancer patients. METHODS Swedish breast cancer patients (n = 699) operated 2006-2014, genotyped for CYP2D6, having at least three months postoperative tamoxifen treatment, a baseline, and at least one follow-up digital mammogram were included in the study. Other systemic adjuvant treatment included chemotherapy, goserelin, and aromatase inhibitors. Change in MD, dense area, was assessed using the automated STRATUS method. Patients were stratified on baseline characteristics, treatments, and CYP2D6 activity (poor, intermediate, extensive, and ultrarapid). Relative density change was calculated at year 1, 2, and 5 during follow-up in relation to treatments and CYP2D6 activity. RESULTS Mean relative DA decreased under the follow-up period, with a more pronounced MD reduction in premenopausal patients. No significant effect of chemotherapy, aromatase inhibitors, goserelin, or CYP2D6 activity on DA change was found. DA did not revert to baseline levels after tamoxifen discontinuation. CONCLUSION Our results indicate that other systemic adjuvant therapy does not further reduce MD in tamoxifen-treated breast cancer patients. We could not confirm the previously suggested association between CYP2D6 activity and MD reduction in a clinical setting with multimodality adjuvant treatment. No rebound effect on MD decline after tamoxifen discontinuation was evident.
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Affiliation(s)
- Linda Thorén
- Department of Clinical Science and Education at Södersjukhuset, Karolinska Institutet, Stockholm, Sweden. .,Department of Oncology, Södersjukhuset, Stockholm, Sweden.
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonatan D Lindh
- Department of Laboratory Medicine, Clinical Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonas Bergh
- Department of Oncology-Pathology, Karolinska Institutet and Breast Cancer Center, Cancer Theme, Karolinska University Hospital, Karolinska Comprehensive Cancer Center, Stockholm, Sweden
| | - Erik Eliasson
- Department of Laboratory Medicine, Clinical Pharmacology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Per Hall
- Department of Oncology, Södersjukhuset, Stockholm, Sweden.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Margolin
- Department of Clinical Science and Education at Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.,Department of Oncology, Södersjukhuset, Stockholm, Sweden
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13
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Quantitative Breast Density in Contrast-Enhanced Mammography. J Clin Med 2021; 10:jcm10153309. [PMID: 34362092 PMCID: PMC8348046 DOI: 10.3390/jcm10153309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 11/16/2022] Open
Abstract
Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.
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14
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Rustagi AS, Scott CG, Winham SJ, Brandt KR, Norman AD, Jensen MR, Shepherd JA, Hruska C, Heine JJ, Pankratz VS, Kerlikowske K, Vachon CM. Association of Daily Alcohol Intake, Volumetric Breast Density, and Breast Cancer Risk. JNCI Cancer Spectr 2021; 5:pkaa124. [PMID: 33733051 PMCID: PMC7952225 DOI: 10.1093/jncics/pkaa124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/30/2020] [Accepted: 11/29/2020] [Indexed: 12/04/2022] Open
Abstract
High alcohol intake and breast density increase breast cancer (BC) risk, but their interrelationship is unknown. We examined whether volumetric density modifies and/or mediates the alcohol-BC association. BC cases (n = 2233) diagnosed from 2006 to 2013 in the San Francisco Bay area had screening mammograms 6 or more months before diagnosis; controls (n = 4562) were matched on age, mammogram date, race or ethnicity, facility, and mammography machine. Logistic regression was used to estimate alcohol-BC associations adjusted for age, body mass index, and menopause; interaction terms assessed modification. Percent mediation was quantified as the ratio of log (odds ratios [ORs]) from models with and without density measures. Alcohol consumption was associated with increased BC risk (2-sided Ptrend = .004), as were volumetric percent density (OR = 1.45 per SD, 95% confidence interval [CI] = 1.36 to 1.56) and dense volume (OR = 1.30, 95% CI = 1.24 to 1.37). Breast density did not modify the alcohol-BC association (2-sided P > .10 for all). Dense volume mediated 25.0% (95% CI = 5.5% to 44.4%) of the alcohol-BC association (2-sided P = .01), suggesting alcohol may partially increase BC risk by increasing fibroglandular tissue.
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Affiliation(s)
- Alison S Rustagi
- Department of Medicine, University of California at San Francisco, San Francisco, CA, USA
| | - Christopher G Scott
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stacey J Winham
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Aaron D Norman
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Matthew R Jensen
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - John A Shepherd
- Department of Epidemiology, University of Hawaii, Honolulu, HI, USA
| | - Carrie Hruska
- Division of Medical Physics, Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - John J Heine
- Cancer Epidemiology Department, MCC, Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Vernon S Pankratz
- Department of Internal Medicine and Biochemistry, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Karla Kerlikowske
- Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California at San Francisco, San Francisco, CA, USA
| | - Celine M Vachon
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
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15
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Kanbayti IH, Rae WID, McEntee MF, Ekpo EU. Mammographic density changes following BC treatment. Clin Imaging 2021; 76:88-97. [PMID: 33578136 DOI: 10.1016/j.clinimag.2021.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 12/03/2020] [Accepted: 01/04/2021] [Indexed: 11/19/2022]
Abstract
BACKGROUND Mammographic density (MD) reduction is associated with lower risk of breast cancer (BC) recurrence and may be used as a marker of treatment outcome; however, trends in MD following BC therapies and the factors associated with such trends are poorly understood. The aim of this study was to investigate MD changes following BC treatment and the factors associated with these changes. METHODS A total of 226 BC-affected patients who received BC treatments were examined. MD was assessed by the Laboratory for individualized Radiodensity Assessment (LIBRA) software. A Wilcoxon ranked signed test was used to investigate the differences in MD before and after treatment and median independent test to assess the associated factors. RESULTS Significant differences in MD between baseline and follow-up mammograms were observed for all MD measures: percent density (p ≤ 0.005), dense area (p ≤ 0.004), and nondense area (p ≤ 0.02). After adjustment, these differences were more pronounced among younger at BC diagnosis (p ≤ 0.001), premenopausal (p ≤ 0.003), and obese women (p ≤ 0.05). Changes in MD were evident regardless of the treatment regimen. MD reduction was observed among patients with high baseline MD (p < 0.001), younger at BC diagnosis (p ≤ 0.04), premenopausal (p < 0.001), and normal body mass index (p = 0.04). Patients who experienced an increase in nondense area had high percent density at baseline (p ≤ 0.001). CONCLUSION Two different MD changes were observed over time: MD increase and decrease. Baseline MD, menopausal status, age at BC diagnosis, and body mass index influenced these changes.
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Affiliation(s)
- Ibrahem H Kanbayti
- Diagnostic Radiography Technology Department, Faculty of Applied Medical Sciences, King Abdul-Aziz University, Saudi Arabia; Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Medicine and Health, The University of Sydney, Australia.
| | - William I D Rae
- Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Medicine and Health, The University of Sydney, Australia
| | - Mark F McEntee
- Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Medicine and Health, The University of Sydney, Australia; Department of Medicine Roinn na Sláinte, UG 12 Áras Watson, Brookfield Health Sciences |T12 AK54, Ireland
| | - Ernest U Ekpo
- Medical Image Optimisation and Perception Group (MIOPeG), Faculty of Medicine and Health, The University of Sydney, Australia; Orange Radiology, Laboratories and Research Centre, Calabar, Nigeria
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Mohammed G, Mousa NA, Talaat IM, Ibrahim H, Saber-Ayad M. Breast Cancer Risk with Progestin Subdermal Implants: A Challenge in Patients Counseling. Front Endocrinol (Lausanne) 2021; 12:781066. [PMID: 34975755 PMCID: PMC8719328 DOI: 10.3389/fendo.2021.781066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/23/2021] [Indexed: 11/27/2022] Open
Abstract
There is a steady global rise in the use of progestin subdermal implants, where use has increased by more than 20 times in the past two decades. BC risk has been reported with the older progestin only methods such as oral pills, injectables, and intrauterine devices, however, little is known about the risk with subdermal implants. In this review, we aim to update clinicians and researchers on the current evidence to support patient counseling and to inform future research directions. The available evidence of the association between the use of progestin subdermal implants and BC risk is discussed. We provide an overview of the potential role of endogenous progesterone in BC development. The chemical structure and molecular targets of synthetic progestins of relevance are summarized together with the preclinical and clinical evidence on their association with BC risk. We review all studies that investigated the action of the specific progestins included in subdermal implants. As well, we discuss the potential effect of the use of subdermal implants in women at increased BC risk, including carriers of BC susceptibility genetic mutations.
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Affiliation(s)
- Ghada Mohammed
- Clinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates
- *Correspondence: Ghada Mohammed, ; Noha A. Mousa,
| | - Noha A. Mousa
- Clinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates
- *Correspondence: Ghada Mohammed, ; Noha A. Mousa,
| | - Iman M. Talaat
- Clinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates
- Department of Pathology, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Haya Ibrahim
- Clinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates
| | - Maha Saber-Ayad
- Clinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates
- Department of Medical Pharmacology, College of Medicine, Cairo University, Cairo, Egypt
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17
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Brentnall AR, Warren R, Harkness EF, Astley SM, Wiseman J, Fox J, Fox L, Eriksson M, Hall P, Cuzick J, Evans DG, Howell A. Mammographic density change in a cohort of premenopausal women receiving tamoxifen for breast cancer prevention over 5 years. Breast Cancer Res 2020; 22:101. [PMID: 32993747 PMCID: PMC7523310 DOI: 10.1186/s13058-020-01340-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 09/10/2020] [Indexed: 01/13/2023] Open
Abstract
Background A decrease in breast density due to tamoxifen preventive therapy might indicate greater benefit from the drug. It is not known whether mammographic density continues to decline after 1 year of therapy, or whether measures of breast density change are sufficiently stable for personalised recommendations. Methods Mammographic density was measured annually over up to 5 years in premenopausal women with no previous diagnosis of breast cancer but at increased risk of breast cancer attending a family-history clinic in Manchester, UK (baseline 2010-2013). Tamoxifen (20 mg/day) for prevention was prescribed for up to 5 years in one group; the other group did not receive tamoxifen and were matched by age. Fully automatic methods were used on mammograms over the 5-year follow-up: three area-based measures (NN-VAS, Stratus, Densitas) and one volumetric (Volpara). Additionally, percentage breast density at baseline and first follow-up mammograms was measured visually. The size of density declines at the first follow-up mammogram and thereafter was estimated using a linear mixed model adjusted for age and body mass index. The stability of density change at 1 year was assessed by evaluating mean squared error loss from predictions based on individual or mean density change at 1 year. Results Analysis used mammograms from 126 healthy premenopausal women before and as they received tamoxifen for prevention (median age 42 years) and 172 matched controls (median age 41 years), with median 3 years follow-up. There was a strong correlation between percentage density measures used on the same mammogram in both the tamoxifen and no tamoxifen groups (all correlation coeficients > 0.8). Tamoxifen reduced mean breast density in year 1 by approximately 17–25% of the inter-quartile range of four automated percentage density measures at baseline, and from year 2, it decreased further by approximately 2–7% per year. Predicting change at 2 years using individual change at 1 year was approximately 60–300% worse than using mean change at 1year. Conclusions All measures showed a consistent and large average tamoxifen-induced change in density over the first year, and a continued decline thereafter. However, these measures of density change at 1 year were not stable on an individual basis.
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Affiliation(s)
- Adam R Brentnall
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Ruth Warren
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Elaine F Harkness
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK
| | - Susan M Astley
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK.,Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M20 4BX, UK
| | - Julia Wiseman
- Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK
| | - Jill Fox
- Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK
| | - Lynne Fox
- Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jack Cuzick
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - D Gareth Evans
- Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK.,Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M20 4BX, UK.,NW Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Anthony Howell
- Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK. .,Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M20 4BX, UK. .,Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK.
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18
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Lian J, Li K. A Review of Breast Density Implications and Breast Cancer Screening. Clin Breast Cancer 2020; 20:283-290. [DOI: 10.1016/j.clbc.2020.03.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 02/10/2020] [Accepted: 03/12/2020] [Indexed: 12/15/2022]
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Bissell MCS, Kerlikowske K, Sprague BL, Tice JA, Gard CC, Tossas KY, Rauscher GH, Trentham-Dietz A, Henderson LM, Onega T, Keegan THM, Miglioretti DL. Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status. Cancer Epidemiol Biomarkers Prev 2020; 29:2048-2056. [PMID: 32727722 DOI: 10.1158/1055-9965.epi-20-0358] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 06/01/2020] [Accepted: 07/22/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Overweight/obesity and dense breasts are strong breast cancer risk factors whose prevalences vary by race/ethnicity. The breast cancer population attributable risk proportions (PARP) explained by these factors across racial/ethnic groups are unknown. METHODS We analyzed data collected from 3,786,802 mammography examinations (1,071,653 women) in the Breast Cancer Surveillance Consortium, associated with 21,253 invasive breast cancers during a median of 5.2 years follow-up. HRs for body mass index (BMI) and breast density, adjusted for age and registry were estimated using separate Cox regression models by race/ethnicity (White, Black, Hispanic, Asian) and menopausal status. HRs were combined with observed risk-factor proportions to calculate PARPs for shifting overweight/obese to normal BMI and shifting heterogeneously/extremely dense to scattered fibroglandular densities. RESULTS The prevalences and HRs for overweight/obesity and heterogeneously/extremely dense breasts varied across races/ethnicities and menopausal status. BMI PARPs were larger for postmenopausal versus premenopausal women (12.0%-28.3% vs. 1.0%-9.9%) and nearly double among postmenopausal Black women (28.3%) than other races/ethnicities (12.0%-15.4%). Breast density PARPs were larger for premenopausal versus postmenopausal women (23.9%-35.0% vs. 13.0%-16.7%) and lower among premenopausal Black women (23.9%) than other races/ethnicities (30.4%-35.0%). Postmenopausal density PARPs were similar across races/ethnicities (13.0%-16.7%). CONCLUSIONS Overweight/obesity and dense breasts account for large proportions of breast cancers in White, Black, Hispanic, and Asian women despite large differences in risk-factor distributions. IMPACT Risk prediction models should consider how race/ethnicity interacts with BMI and breast density. Efforts to reduce BMI could have a large impact on breast cancer risk reduction, particularly among postmenopausal Black women.
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Affiliation(s)
- Michael C S Bissell
- Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis, California.
| | - Karla Kerlikowske
- General Internal Medicine Section, Department of Veteran Affairs and Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
| | - Brian L Sprague
- Department of Surgery, Office of Health Promotion Research, Larner College of Medicine at the University of Vermont and University of Vermont Cancer Center, Burlington, Vermont
| | - Jeffery A Tice
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
| | - Charlotte C Gard
- Department of Economics, Applied Statistics, and International Business, New Mexico State University, Las Cruces, New Mexico
| | - Katherine Y Tossas
- Department of Health Behavior and Policy, School of Medicine, Virginia Commonwealth University, Richmond, Virginia
| | - Garth H Rauscher
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, Illinois
| | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Louise M Henderson
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Tracy Onega
- Department of Biomedical Data Science, Dartmouth College, Lebanon, New Hampshire
| | - Theresa H M Keegan
- Center for Oncology Hematology Outcomes Research and Training (COHORT) and Division of Hematology and Oncology, University of California Davis School of Medicine, Sacramento, California
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20
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Mammographic density changes during neoadjuvant breast cancer treatment: NeoDense, a prospective study in Sweden. Breast 2020; 53:33-41. [PMID: 32563178 PMCID: PMC7375568 DOI: 10.1016/j.breast.2020.05.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 05/26/2020] [Accepted: 05/30/2020] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVES To assess if mammographic density (MD) changes during neoadjuvant breast cancer treatment and is predictive of a pathological complete response (pCR). METHODS We prospectively included 200 breast cancer patients assigned to neoadjuvant chemotherapy (NACT) in the NeoDense study (2014-2019). Raw data mammograms were used to assess MD with a fully automated volumetric method and radiologists categorized MD using the Breast Imaging-Reporting and Data System (BI-RADS), 5th Edition. Logistic regression was used to calculate odds ratios (OR) for pCR comparing BI-RADS categories c vs. a, b, and d as well as with a 0.5% change in percent dense volume adjusting for baseline characteristics. RESULTS The overall median age was 53.1 years, and 48% of study participants were premenopausal pre-NACT. A total of 23% (N = 45) of the patients accomplished pCR following NACT. Patients with very dense breasts (BI-RADS d) were more likely to have a positive axillary lymph node status at diagnosis: 89% of the patients with very dense breasts compared to 72% in the entire cohort. A total of 74% of patients decreased their absolute dense volume during NACT. The likelihood of accomplishing pCR following NACT was independent of volumetric MD at diagnosis and change in volumetric MD during treatment. No trend was observed between decreasing density according to BI-RADS and the likelihood of accomplishing pCR following NACT. CONCLUSIONS The majority of patients decreased their MD during NACT. We found no evidence of MD as a predictive marker of pCR in the neoadjuvant setting.
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21
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Johnson HM, Shivalingappa H, Irish W, Wong JH, Muzaffar M, Verbanac K, Vohra NA. Race May Not Impact Endocrine Therapy-Related Changes in Breast Density. Cancer Epidemiol Biomarkers Prev 2020; 29:1049-1057. [PMID: 32098892 DOI: 10.1158/1055-9965.epi-19-1066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 12/03/2019] [Accepted: 02/21/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Reduction in breast density may be a biomarker of endocrine therapy (ET) efficacy. Our objective was to assess the impact of race on ET-related changes in volumetric breast density (VBD). METHODS This retrospective cohort study assessed longitudinal changes in VBD measures in women with estrogen receptor-positive invasive breast cancer treated with ET. VBD, the ratio of fibroglandular volume (FGV) to breast volume (BV), was measured using Volpara software. Changes in measurements were evaluated using a multivariable linear mixed effects model. RESULTS Compared with white women (n = 191), black women (n = 107) had higher rates of obesity [mean ± SD body mass index (BMI) 34.5 ± 9.1 kg/m2 vs. 30.6 ± 7.0 kg/m2, P < 0.001] and premenopausal status (32.7% vs. 16.7%, P = 0.002). Age- and BMI-adjusted baseline FGV, BV, and VBD were similar between groups. Modeled longitudinal changes were also similar: During a follow-up of 30.7 ± 15.0 months (mean ± SD), FGV decreased over time in premenopausal women (slope = -0.323 cm3; SE = 0.093; P = 0.001), BV increased overall (slope = 2.475 cm3; SE = 0.483; P < 0.0001), and VBD decreased (premenopausal slope = -0.063%, SE = 0.011; postmenopausal slope = -0.016%, SE = 0.004; P < 0.0001). Race was not significantly associated with these longitudinal changes, nor did race modify the effect of time on these changes. Higher BMI was associated with lower baseline VBD (P < 0.0001). Among premenopausal women, VBD declined more steeply for women with lower BMI (time × BMI, P = 0.0098). CONCLUSIONS Race does not appear to impact ET-related longitudinal changes in VBD. IMPACT Racial disparities in estrogen receptor-positive breast cancer recurrence and mortality may not be explained by differential declines in breast density due to ET.
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Affiliation(s)
- Helen M Johnson
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina
| | - Hitesh Shivalingappa
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina.,Department of Anesthesiology and Perioperative Medicine, Penn State Health Milton S. Hershey Medical Center, Hershey, Pennsylvania
| | - William Irish
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina
| | - Jan H Wong
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina
| | - Mahvish Muzaffar
- Division of Hematology Oncology, Department of Internal Medicine, East Carolina University Brody School of Medicine, Greenville, North Carolina
| | - Kathryn Verbanac
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina
| | - Nasreen A Vohra
- Department of Surgery, East Carolina University Brody School of Medicine, Greenville, North Carolina.
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22
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Environmental Influences on Mammographic Breast Density in California: A Strategy to Reduce Breast Cancer Risk. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16234731. [PMID: 31783496 PMCID: PMC6926682 DOI: 10.3390/ijerph16234731] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 12/17/2022]
Abstract
State legislation in many U.S. states, including California, mandates informing women if they have dense breasts on screening mammography, meaning over half of their breast tissue is comprised of non-adipose tissue. Breast density is important to interpret screening sensitivity and is an established breast cancer risk factor. Environmental chemical exposures may play an important role in this, especially during key windows of susceptibility for breast development: in utero, during puberty, pregnancy, lactation, and the peri-menopause. There is a paucity of research, however, examining whether environmental chemical exposures are associated with mammographic breast density, and even less is known about environmental exposures during windows of susceptibility. Now, with clinical breast density scoring being reported routinely for mammograms, it is possible to find out, especially in California, where there are large study populations that can link environmental exposures during windows of susceptibility to breast density. Density scores are now available throughout the state through electronic medical records. We can link these with environmental chemical exposures via state-wide monitoring. Studying the effects of environmental exposure on breast density may provide valuable monitoring and etiologic data to inform strategies to reduce breast cancer risk.
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23
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Involution of Breast Lobules, Mammographic Breast Density and Prognosis Among Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer Patients. J Clin Med 2019; 8:jcm8111868. [PMID: 31689948 PMCID: PMC6912285 DOI: 10.3390/jcm8111868] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 10/17/2019] [Accepted: 10/22/2019] [Indexed: 11/23/2022] Open
Abstract
Mammographic breast density (MD) reflects breast fibroglandular content. Its decline following adjuvant tamoxifen treated, estrogen receptor (ER)-positive breast cancer has been associated with improved outcomes. Breast cancers arise from structures termed lobules, and lower MD is associated with increased age-related lobule involution. We assessed whether pre-treatment involution influenced associations between MD decline and risk of breast cancer-specific death. ER-positive tamoxifen treated patients diagnosed at Kaiser Permanente Northwest (1990-2008) were defined as cases who died of breast cancer (n = 54) and matched controls (remained alive over similar follow-up; n = 180). Lobule involution was assessed by examining terminal duct lobular units (TDLUs) in benign tissues surrounding cancers as TDLU count/mm2, median span and acini count/TDLU. MD (%) was measured in the unaffected breast at baseline (median 6-months before) and follow-up (median 12-months after tamoxifen initiation). TDLU measures and baseline MD were positively associated among controls (p < 0.05). In multivariable regression models, MD decline (≥10%) was associated with reduced risk of breast cancer-specific death before (odds ratio (OR): 0.41, 95% CI: 0.18-0.92) and after (OR: 0.41, 95% CI: 0.18-0.94) adjustment for TDLU count/mm2, TDLU span (OR: 0.34, 95% CI: 0.14-0.84), and acini count/TDLU (OR: 0.33, 95% CI: 0.13-0.81). MD decline following adjuvant tamoxifen is associated with reduced risk of breast cancer-specific death, irrespective of pre-treatment lobule involution.
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Fabian CJ, Nye L, Powers KR, Nydegger JL, Kreutzjans AL, Phillips TA, Metheny T, Winblad O, Zalles CM, Hagan CR, Goodman ML, Gajewski BJ, Koestler DC, Chalise P, Kimler BF. Effect of Bazedoxifene and Conjugated Estrogen (Duavee) on Breast Cancer Risk Biomarkers in High-Risk Women: A Pilot Study. Cancer Prev Res (Phila) 2019; 12:711-720. [PMID: 31420361 PMCID: PMC6774863 DOI: 10.1158/1940-6207.capr-19-0315] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 07/29/2019] [Accepted: 08/09/2019] [Indexed: 11/16/2022]
Abstract
Interventions that relieve vasomotor symptoms while reducing risk for breast cancer would likely improve uptake of chemoprevention for perimenopausal and postmenopausal women. We conducted a pilot study with 6 months of the tissue selective estrogen complex bazedoxifene (20 mg) and conjugated estrogen (0.45 mg; Duavee) to assess feasibility and effects on risk biomarkers for postmenopausal breast cancer. Risk biomarkers included fully automated mammographic volumetric density (Volpara), benign breast tissue Ki-67 (MIB-1 immunochemistry), and serum levels of progesterone, IGF-1, and IGFBP3, bioavailable estradiol and testosterone. Twenty-eight perimenopausal and postmenopausal women at increased risk for breast cancer were enrolled: 13 in cohort A with baseline Ki-67 < 1% and 15 in cohort B with baseline Ki-67 of 1% to 4%. All completed the study with > 85% drug adherence. Significant changes in biomarkers, uncorrected for multiple comparisons, were a decrease in mammographic fibroglandular volume (P = 0.043); decreases in serum progesterone, bioavailable testosterone, and IGF-1 (P < 0.01), an increase in serum bioavailable estradiol (P < 0.001), and for women from cohort B a reduction in Ki-67 (P = 0.017). An improvement in median hot flash score from 15 at baseline to 0 at 6 months, and menopause-specific quality-of-life total, vasomotor, and sexual domain scores were also observed (P < 0.001). Given the favorable effects on risk biomarkers and patient reported outcomes, a placebo-controlled phase IIB trial is warranted.
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Affiliation(s)
- Carol J Fabian
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Lauren Nye
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Kandy R Powers
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Jennifer L Nydegger
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Amy L Kreutzjans
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Teresa A Phillips
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Trina Metheny
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Onalisa Winblad
- Department of Diagnostic Radiology, University of Kansas Medical Center, Kansas City, Kansas
| | - Carola M Zalles
- Department of Pathology, Boca Raton Hospital, Boca Raton, Florida
| | - Christy R Hagan
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas
| | - Merit L Goodman
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Center, Kansas City, Kansas
| | - Byron J Gajewski
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas
| | - Devin C Koestler
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas
| | - Prabhakar Chalise
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas
| | - Bruce F Kimler
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas.
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Engmann NJ, Scott C, Jensen MR, Winham SJ, Ma L, Brandt KR, Mahmoudzadeh A, Whaley DH, Hruska CB, Wu FF, Norman AD, Hiatt RA, Heine J, Shepherd J, Pankratz VS, Miglioretti DL, Kerlikowske K, Vachon CM. Longitudinal Changes in Volumetric Breast Density in Healthy Women across the Menopausal Transition. Cancer Epidemiol Biomarkers Prev 2019; 28:1324-1330. [PMID: 31186265 DOI: 10.1158/1055-9965.epi-18-1375] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 04/18/2019] [Accepted: 06/03/2019] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Mammographic breast density declines during menopause. We assessed changes in volumetric breast density across the menopausal transition and factors that influence these changes. METHODS Women without a history of breast cancer, who had full field digital mammograms during both pre- and postmenopausal periods, at least 2 years apart, were sampled from four facilities within the San Francisco Mammography Registry from 2007 to 2013. Dense breast volume (DV) was assessed using Volpara on mammograms across the time period. Annualized change in DV from pre- to postmenopause was estimated using linear mixed models adjusted for covariates and per-woman random effects. Multiplicative interactions were evaluated between premenopausal risk factors and time to determine whether these covariates modified the annualized changes. RESULTS Among the 2,586 eligible women, 1,802 had one premenopausal and one postmenopausal mammogram, 628 had an additional perimenopausal mammogram, and 156 had two perimenopausal mammograms. Women experienced an annualized decrease in DV [-2.2 cm3 (95% confidence interval, -2.7 to -1.7)] over the menopausal transition. Declines were greater among women with a premenopausal DV above the median (54 cm3) versus below (DV, -3.5 cm3 vs. -1.0 cm3; P < 0.0001). Other breast cancer risk factors, including race, body mass index, family history, alcohol, and postmenopausal hormone therapy, had no effect on change in DV over the menopausal transition. CONCLUSIONS High premenopausal DV was a strong predictor of greater reductions in DV across the menopausal transition. IMPACT We found that few factors other than premenopausal density influence changes in DV across the menopausal transition, limiting targeted prevention efforts.
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Affiliation(s)
| | | | | | | | - Lin Ma
- University of California, San Francisco, California
| | | | | | | | | | | | | | | | | | | | - V Shane Pankratz
- University of New Mexico Health Sciences Center, Albuquerque, New Mexico
| | - Diana L Miglioretti
- University of California, Davis, California.,Kaiser Permanente Washington Health Research Institute, Seattle, Washington
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A Review of the Role of Augmented Intelligence in Breast Imaging: From Automated Breast Density Assessment to Risk Stratification. AJR Am J Roentgenol 2019; 212:259-270. [DOI: 10.2214/ajr.18.20391] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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27
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Eriksson L, He W, Eriksson M, Humphreys K, Bergh J, Hall P, Czene K. Adjuvant Therapy and Mammographic Density Changes in Women With Breast Cancer. JNCI Cancer Spectr 2019; 2:pky071. [PMID: 31360886 PMCID: PMC6649795 DOI: 10.1093/jncics/pky071] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 09/23/2018] [Accepted: 11/15/2018] [Indexed: 12/11/2022] Open
Abstract
Background Tamoxifen decreases mammographic density. Whether compliance affects this relationship is unclear as is the relationship between other types of adjuvant treatment and changes in mammographic density. Methods This prospective cohort study included 2490 women diagnosed with breast cancer during 2001-2015 in Sweden. Mammographic density was assessed within 3 months of diagnosis and 6-36 months post diagnosis. Logistic regression was performed to study the association between each respective adjuvant treatment and mammographic density reduction (annual dense area decrease >15%). Results Intention-to-treat analyses using treatment information from the regional cancer registries showed that tamoxifen-treated patients more frequently experienced mammographic density reductions compared with nontreated patients (odds ratio [OR] = 1.58, 95% confidence interval [CI] = 1.25 to 1.99), as did chemotherapy-treated patients (OR = 1.28, 95% CI = 1.06 to 1.54). For chemotherapy, the association was mainly seen in premenopausal women. Neither aromatase inhibitors nor radiotherapy was associated with density change. Tamoxifen use based on prescription and dispensation data from the Swedish Prescribed Drug Register showed that users were more likely to have density reductions compared with nonusers (adjusted OR = 2.24, 95% CI = 1.40 to 3.59). Moreover, among tamoxifen users, tamoxifen continuers were more likely than discontinuers to experience density reductions (adjusted OR = 1.50, 95% CI = 1.04 to 2.17). Conclusions Our results indicate that adherence influences the association between tamoxifen and mammographic density reduction. We further found that chemotherapy was associated with density reductions and propose that this is largely secondary to chemotherapy-induced ovarian failure.
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Affiliation(s)
| | - Wei He
- Correspondence to: Wei He, PhD, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12 A, Stockholm 171 77, Sweden (e-mail: )
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28
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Mullooly M, Gierach GL. The Potential for Mammographic Breast Density Change as a Biosensor of Adjuvant Tamoxifen Therapy Adherence and Response. JNCI Cancer Spectr 2018; 2:pky072. [PMID: 30746510 PMCID: PMC6357814 DOI: 10.1093/jncics/pky072] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 11/21/2018] [Indexed: 01/09/2023] Open
Affiliation(s)
| | - Gretchen L Gierach
- Correspondence to: Gretchen L. Gierach, PhD, MPH, Division of Cancer Epidemiology and Genetics and Division of Cancer Prevention, National Cancer Institute, 9609 Medical Center Drive, Rm 7E-102, Bethesda, MD 20892 (e-mail: )
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Atakpa EC, Thorat MA, Cuzick J, Brentnall AR. Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review. Hippokratia 2018. [DOI: 10.1002/14651858.cd013091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Emma C Atakpa
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London; Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine; Charterhouse Square London UK EC1M 6BQ
| | - Mangesh A Thorat
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London; Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine; Charterhouse Square London UK EC1M 6BQ
| | - Jack Cuzick
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London; Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine; Charterhouse Square London UK EC1M 6BQ
| | - Adam R Brentnall
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London; Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine; Charterhouse Square London UK EC1M 6BQ
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30
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Masala G, Assedi M, Sera F, Ermini I, Occhini D, Castaldo M, Pierpaoli E, Caini S, Bendinelli B, Ambrogetti D, Palli D. Can Dietary and Physical Activity Modifications Reduce Breast Density in Postmenopausal Women? The DAMA Study, a Randomized Intervention Trial in Italy. Cancer Epidemiol Biomarkers Prev 2018; 28:41-50. [PMID: 30068518 DOI: 10.1158/1055-9965.epi-18-0468] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 07/06/2018] [Accepted: 07/27/2018] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Few randomized trials have been carried out to evaluate the effect of lifestyle modifications on mammographic breast density (MBD). The randomized 2 × 2 factorial Diet, physical Activity and MAmmography trial aimed to evaluate whether MBD can be reduced in postmenopausal women with high baseline MBD by a 24-month dietary and/or physical activity (PA) interventions. METHODS We randomized healthy postmenopausal women, attending the Florence (Italy) mammographic screening program, ages 50 to 69 years, nonsmokers, with MBD > 50% and no recent hormone therapy, to (i) a dietary intervention focused on plant foods, with a low glycemic load, low in saturated fats and alcohol; (ii) a PA intervention combining daily moderate intensity activities and one weekly supervised session of more strenuous activity; (iii) both interventions; (iv) general recommendations. We evaluated changes in MBD based on Volpara estimates comparing baseline and follow-up digital mammograms by an intention-to-treat-analysis. RESULTS MBD measures were available for 226 participants. An interaction emerged between treatments and thus we run analyses by arms. A decrease in volumetric percent density emerged for women in the dietary intervention (ratio 0.91; 95% CI, 0.86-0.97; P = 0.002) and in the PA intervention arm (0.93; 95% CI, 0.87-0.98; P = 0.01) in comparison with controls. No clear effect emerged in the double intervention arm. CONCLUSIONS This intervention trial suggests that a 24-month dietary or PA intervention may reduce MBD in postmenopausal women. IMPACT A modification of dietary habits or an increase in PA in postmenopausal women may reduce MBD. Further studies are needed to confirm these findings for planning breast cancer preventive strategies.
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Affiliation(s)
- Giovanna Masala
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.
| | - Melania Assedi
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Francesco Sera
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.,Department of Social and Environmental Health Research (SEHR), Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Ilaria Ermini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Daniela Occhini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Maria Castaldo
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Elena Pierpaoli
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.,Breast Cancer Screening Branch, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Saverio Caini
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Benedetta Bendinelli
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Daniela Ambrogetti
- Breast Cancer Screening Branch, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Domenico Palli
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
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Cuzick J. Progress in preventive therapy for cancer: a reminiscence and personal viewpoint. Br J Cancer 2018; 118:1155-1161. [PMID: 29681616 PMCID: PMC5943239 DOI: 10.1038/s41416-018-0039-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 11/14/2017] [Accepted: 01/26/2018] [Indexed: 02/06/2023] Open
Abstract
Prophylactic drug treatment with aspirin, statins and anti-hypertensive agents has had a major impact on the incidence of cardiovascular disease and is now well established. Progress in therapeutic cancer prevention has been much slower; only recently have effective agents been clearly established. Breast cancer has led the way and endocrine agents used to treat it-notably tamoxifen and the aromatase inhibitors-have now been shown to have a substantial preventive effect as well. However, these agents carry some toxicity and thus identifying high-risk women who are likely to benefit most is a key priority. In contrast, the ability of low-dose aspirin to prevent about one-third of colorectal, gastric, and oesophageal cancers, combined with its much lower toxicity profile, make it attractive for a much larger proportion of the general population. Vaccination against the human papilloma virus is also a preventive intervention with large benefits for the whole population. Here I recall my involvement in these initiatives and offer a personal viewpoint on what has been achieved and what remains to be done.
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Affiliation(s)
- Jack Cuzick
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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Vaginal estrogen and mammogram results: case series and review of literature on treatment of genitourinary syndrome of menopause (GSM) in breast cancer survivors. Menopause 2018. [PMID: 29533365 DOI: 10.1097/gme.0000000000001079] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To examine mammographic density before and after at least 1 year of vaginal estrogen use in a small cohort of healthy postmenopausal women and women with a personal history of breast cancer. METHODS We extracted data via chart review of patients from a single practitioner's menopause specialty clinic in Baltimore, MD. Mammographic change was primarily determined via the Bi-RADS scoring system, including the Bi-RADS density score. In addition, we conduct a narrative review of the current literature on the usage of local estrogen therapy, and systemic and local alternatives in the treatment of genitourinary syndrome of menopause (GSM) in breast cancer survivors. RESULTS Twenty healthy postmenopausal women and three breast cancer survivors fit our inclusion criteria. Amongst these two groups, we did not find an increase in mammographic density after at least 1 year and up to 18 years of local vaginal estrogen. Ospemifene use in one patient did not appear to be associated with any change in Bi-RADS score. Our narrative review found little data on the effects of vaginal estrogen therapy or newer alternative systemic therapies such as ospemifene on mammographic density. CONCLUSIONS Low-dose vaginal estrogen use for 1 or more years in a small cohort of women with GSM did not appear to be associated with any changes in breast density or Bi-RADS breast cancer risk scores in the majority of study participants, including three breast cancer survivors. Larger long-term controlled clinical trials should be conducted to examine the effects of low-dose vaginal estrogen on mammographic density in women with and without a personal history of breast cancer. Furthermore, relative efficacy and risk of vaginal estrogen compared with other forms of treatment for GSM should also be studied in long-term trials.
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Vinnicombe SJ. Breast density: why all the fuss? Clin Radiol 2017; 73:334-357. [PMID: 29273225 DOI: 10.1016/j.crad.2017.11.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 11/17/2017] [Indexed: 01/06/2023]
Abstract
The term "breast density" or mammographic density (MD) denotes those components of breast parenchyma visualised at mammography that are denser than adipose tissue. MD is composed of a mixture of epithelial and stromal components, notably collagen, in variable proportions. MD is most commonly assessed in clinical practice with the time-honoured method of visual estimation of area-based percent density (PMD) on a mammogram, with categorisation into quartiles. The computerised semi-automated thresholding method, Cumulus, also yielding area-based percent density, is widely used for research purposes; however, the advent of fully automated volumetric methods developed as a consequence of the widespread use of digital mammography (DM) and yielding both absolute and percent dense volumes, has resulted in an explosion of interest in MD recently. Broadly, the importance of MD is twofold: firstly, the presence of marked MD significantly reduces mammographic sensitivity for breast cancer, even with state-of-the-art DM. Recognition of this led to the formation of a powerful lobby group ('Are You Dense') in the US, as a consequence of which 32 states have legislated for mandatory disclosure of MD to women undergoing mammography. Secondly, it is now widely accepted that MD is in itself a risk factor for breast cancer, with a four-to sixfold increased relative risk in women with PMD in the highest quintile compared to those with PMD in the lowest quintile. Consequently, major research efforts are underway to assess whether use of MD could provide a major step forward towards risk-adapted, personalised breast cancer prevention, imaging, and treatment.
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Affiliation(s)
- S J Vinnicombe
- Cancer Research, School of Medicine, Level 7, Mailbox 4, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, UK.
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Abstract
Developments in breast cancer treatment have resulted in reduction in breast cancer mortality in the developed world. However incidence continues to rise and greater use of preventive interventions including the use of therapeutic agents is needed to control this burden. High quality evidence from 9 major trials involving more than 83000 participants shows that selective oestrogen receptor modulators (SERMs) reduce breast cancer incidence by 38%. Combined results from 2 large trials with 8424 participants show that aromatase inhibitors (AIs) reduce breast cancer incidence by 53%. These benefits are restricted to prevention of ER positive breast cancers. Restricting preventive therapy to high-risk women improves the benefit-harm balance and many guidelines now encourage healthcare professionals to discuss preventive therapy in these women. Further research is needed to improve our risk-prediction models for the identification of high risk women for preventive therapy with greater accuracy and to develop surrogate biomarkers of response. Long-term follow-up of the IBIS-I trial has provided valuable insights into the durability of benefits from preventive therapy, and underscores the need for such follow up to fully evaluate other agents. Full utilisation of preventive therapy also requires greater knowledge and awareness among both doctors and patients about benefits, harms and risk factors. Healthcare professionals should routinely discuss preventive therapy with women at high-risk of breast cancer.
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Affiliation(s)
- Mangesh A Thorat
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom
| | - Jack Cuzick
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom.
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Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad. Diagnostics (Basel) 2017; 7:diagnostics7020030. [PMID: 28561776 PMCID: PMC5489950 DOI: 10.3390/diagnostics7020030] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 05/22/2017] [Accepted: 05/24/2017] [Indexed: 12/14/2022] Open
Abstract
Mammographic breast density (MBD) has been proven to be an important risk factor for breast cancer and an important determinant of mammographic screening performance. The measurement of density has changed dramatically since its inception. Initial qualitative measurement methods have been found to have limited consistency between readers, and in regards to breast cancer risk. Following the introduction of full-field digital mammography, more sophisticated measurement methodology is now possible. Automated computer-based density measurements can provide consistent, reproducible, and objective results. In this review paper, we describe various methods currently available to assess MBD, and provide a discussion on the clinical utility of such methods for breast cancer screening.
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Johansson H, von Tiedemann M, Erhard K, Heese H, Ding H, Molloi S, Fredenberg E. Breast-density measurement using photon-counting spectral mammography. Med Phys 2017; 44:3579-3593. [DOI: 10.1002/mp.12279] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Revised: 03/12/2017] [Accepted: 03/23/2017] [Indexed: 11/09/2022] Open
Affiliation(s)
- Henrik Johansson
- Philips Health Systems; Mammography Solutions; Torshamnsgatan 30A 164 40 Kista Sweden
| | - Miriam von Tiedemann
- Philips Health Systems; Mammography Solutions; Torshamnsgatan 30A 164 40 Kista Sweden
| | - Klaus Erhard
- Philips Research; Röntgenstrasse 24-26 22335 Hamburg Germany
| | - Harald Heese
- Philips Research; Röntgenstrasse 24-26 22335 Hamburg Germany
| | - Huanjun Ding
- Department of Radiological Sciences; University of California; Irvine CA 92697 USA
| | - Sabee Molloi
- Department of Radiological Sciences; University of California; Irvine CA 92697 USA
| | - Erik Fredenberg
- Philips Health Systems; Mammography Solutions; Torshamnsgatan 30A 164 40 Kista Sweden
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