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Vaupel P, Piazena H. Strong correlation between specific heat capacity and water content in human tissues suggests preferred heat deposition in malignant tumors upon electromagnetic irradiation. Int J Hyperthermia 2022; 39:987-997. [DOI: 10.1080/02656736.2022.2067596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022] Open
Affiliation(s)
- Peter Vaupel
- Department of Radiation Oncology, University Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
- German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Helmut Piazena
- Department of Anesthesiology and Operative Intensive Care Medicine, Charité - Universitätsmedizin Berlin, Corporative Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
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Martin L, Saha S, Linton L, Taylor M, Zhu J, Chavez S, Stanisz G, Minkin S, Boyd N. Dietary Fiber, Insulin and Breast Tissue Composition at Age 15-18: A Cross-Sectional Study. Nutr Cancer 2022; 74:2946-2954. [PMID: 35243935 DOI: 10.1080/01635581.2022.2047738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Risk of breast cancer in adult life is influenced by body size and height in childhood, but the mechanisms responsible for these associations are currently unknown. We carried out research to determine if, at age 15-18, measures of dietary intake were associated with body size, hormones, and with variations in breast tissue composition that in adult life are associated with risk of breast cancer. METHODS In a cross-sectional study of 766 healthy Caucasian women aged 15-18, we measured percent breast water (PBW), total breast water and fat by magnetic resonance (MR), and assessed dietary intake using a validated food frequency questionnaire. We also measured height, weight, skin-fold thicknesses and waist-to-hip ratio, and in fasting blood assayed glucose and insulin. RESULTS After adjustment for age, measures of body size, and energy intake, dietary fiber (insoluble and total fiber) and insulin were associated positively and significantly with PBW. CONCLUSIONS Dietary fiber and fasting insulin were associated with breast tissue measures. These data suggest a potential approach to breast cancer prevention.
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Affiliation(s)
- Lisa Martin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sudipta Saha
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Monica Taylor
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Jie Zhu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sofia Chavez
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Greg Stanisz
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Salomon Minkin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Norman Boyd
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Hooshmand S, Reed WM, Suleiman ME, Brennan PC. A review of screening mammography: The benefits and radiation risks put into perspective. J Med Imaging Radiat Sci 2021; 53:147-158. [PMID: 34969620 DOI: 10.1016/j.jmir.2021.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 12/01/2021] [Accepted: 12/01/2021] [Indexed: 12/28/2022]
Abstract
INTRODUCTION/BACKGROUND In medical imaging a benefit to risk analysis is required when justifying or implementing diagnostic procedures. Screening mammography is no exception and in particular concerns around the use of radiation to help diagnose cancer must be addressed. METHODS The Medline database and various established reports on breast screening and radiological protection were utilised to explore this review. RESULTS/DISCUSSION The benefit of screening is well argued; the ability to detect and treat breast cancer has led to a 91% 5-year survival rate and 497 deaths prevented from breast cancer amongst 100,000 screened women. Subsequently, screening guidelines by various countries recommend annual, biennial or triennial screening from ages somewhere between 40-74 years. Whilst the literature presents different perspectives on screening younger and older women, the current evidence of benefit for screening women <40 and ≥75 years is currently not strong. The radiation dose and associated risk delivered to each woman for a single examination is dependent upon age, breast density and breast thickness, however the average mean glandular dose is around 2.5-3 mGy, and this would result in 65 induced cancers and 8 deaths per 100,000 women over a screening lifetime from 40-74 years. This results in a ratio of lives saved to deaths from induced cancer of 62:1. CONCLUSION Therefore, compared to the potential mortality reduction achievable with screening mammography, the risk is small.
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Affiliation(s)
- Sahand Hooshmand
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia.
| | - Warren M Reed
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
| | - Mo'ayyad E Suleiman
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
| | - Patrick C Brennan
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
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Jiménez T, García-Pérez J, van der Haar R, Alba MÁ, Lucas P, Sierra MÁ, de Larrea-Baz NF, Salas-Trejo D, Llobet R, Martínez I, Pino MN, Alguacil J, González-Galarzo MC, Martínez-Cortés M, Pérez-Gómez B, Pollán M, Lope V. Occupation, occupational exposures and mammographic density in Spanish women. ENVIRONMENTAL RESEARCH 2021; 195:110816. [PMID: 33524328 DOI: 10.1016/j.envres.2021.110816] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 01/25/2021] [Accepted: 01/25/2021] [Indexed: 06/12/2023]
Abstract
INTRODUCTION Mammographic density (MD), the proportion of radiologically dense breast tissue, is a strong risk factor for breast cancer. Our objective is to investigate the influence of occupations and occupational exposure to physical, chemical, and microbiological agents on MD in Spanish premenopausal women. METHODS This is a cross-sectional study based on 1362 premenopausal workers, aged 39-50, who attended a gynecological screening in a breast radiodiagnosis unit of Madrid City Council. The work history was compiled through a personal interview. Exposure to occupational agents was evaluated using the Spanish job-exposure matrix MatEmESp. MD percentage was assessed using the validated semi-automated computer tool DM-Scan. The association between occupation, occupational exposures, and MD was quantified using multiple linear regression models, adjusted for age, educational level, body mass index, parity, previous breast biopsies, family history of breast cancer, energy intake, use of oral contraceptives, smoking, and alcohol consumption. RESULTS Although no occupation was statistically significantly associated with MD, a borderline significant inverse association was mainly observed in orchard, greenhouse, nursery, and garden workers (β = -6.60; 95% confidence interval (95%CI) = -14.27; 1.07) and information and communication technology technicians (β = -7.27; 95%CI = -15.37; 0.84). On the contrary, a positive association was found among technicians in art galleries, museums, and libraries (β = 8.47; 95%CI = -0.65; 17.60). Women occupationally exposed to fungicides, herbicides, and insecticides tended to have lower MD. The percentage of density decreased by almost 2% for every 5 years spent in occupations exposed to the mentioned agents. CONCLUSIONS Although our findings point to a lack of association with the occupations and exposures analyzed, this study supports a deeper exploration of the role of certain occupational agents in MD, such as pesticides.
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Affiliation(s)
- Tamara Jiménez
- Department of Preventive Medicine, Public Health and Microbiology, Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Javier García-Pérez
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain.
| | | | - Miguel Ángel Alba
- Área de Higiene Industrial, Quirón Prevención, S.L.U., Barcelona, Spain
| | - Pilar Lucas
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - María Ángeles Sierra
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Nerea Fernández de Larrea-Baz
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Dolores Salas-Trejo
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain; Valencian Breast Cancer Screening Program, General Directorate of Public Health, València, Spain; Centro Superior de Investigación en Salud Pública CSISP, FISABIO, València, Spain
| | - Rafael Llobet
- Institute of Computer Technology, Universitat Politècnica de València, València, Spain
| | - Inmaculada Martínez
- Valencian Breast Cancer Screening Program, General Directorate of Public Health, València, Spain; Centro Superior de Investigación en Salud Pública CSISP, FISABIO, València, Spain
| | - Marina Nieves Pino
- Servicio de Prevención y Promoción de la Salud, Madrid Salud, Ayuntamiento de Madrid, Madrid, Spain
| | - Juan Alguacil
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain; Centro de Investigación en Recursos Naturales, Salud y Medio Ambiente (RENSMA), Universidad de Huelva, Huelva, Spain
| | - Mª Carmen González-Galarzo
- Department of Developmental and Educational Psychology, University of Valencia, Valencia, Spain; Center for Research in Occupational Disease, Universitat Pompeu Fabra, Barcelona, Spain
| | - Mercedes Martínez-Cortés
- Servicio de Prevención y Promoción de la Salud, Madrid Salud, Ayuntamiento de Madrid, Madrid, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
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Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net. Acad Radiol 2019; 26:1526-1535. [PMID: 30713130 DOI: 10.1016/j.acra.2019.01.012] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 01/03/2019] [Accepted: 01/13/2019] [Indexed: 12/17/2022]
Abstract
RATIONALE AND OBJECTIVES Breast segmentation using the U-net architecture was implemented and tested in independent validation datasets to quantify fibroglandular tissue volume in breast MRI. MATERIALS AND METHODS Two datasets were used. The training set was MRI of 286 patients with unilateral breast cancer. The segmentation was done on the contralateral normal breasts. The ground truth for the breast and fibroglandular tissue (FGT) was obtained by using a template-based segmentation method. The U-net deep learning algorithm was implemented to analyze the training set, and the final model was obtained using 10-fold cross-validation. The independent validation set was MRI of 28 normal volunteers acquired using four different MR scanners. Dice Similarity Coefficient (DSC), voxel-based accuracy, and Pearson's correlation were used to evaluate the performance. RESULTS For the 10-fold cross-validation in the initial training set of 286 patients, the DSC range was 0.83-0.98 (mean 0.95 ± 0.02) for breast and 0.73-0.97 (mean 0.91 ± 0.03) for FGT; and the accuracy range was 0.92-0.99 (mean 0.98 ± 0.01) for breast and 0.87-0.99 (mean 0.97 ± 0.01) for FGT. For the entire 224 testing breasts of the 28 normal volunteers in the validation datasets, the mean DSC was 0.86 ± 0.05 for breast, 0.83 ± 0.06 for FGT; and the mean accuracy was 0.94 ± 0.03 for breast and 0.93 ± 0.04 for FGT. The testing results for MRI acquired using four different scanners were comparable. CONCLUSION Deep learning based on the U-net algorithm can achieve accurate segmentation results for the breast and FGT on MRI. It may provide a reliable and efficient method to process large number of MR images for quantitative analysis of breast density.
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García-Pérez J, Pollán M, Pérez-Gómez B, González-Sánchez M, Cortés Barragán RA, Maqueda Blasco J, González-Galarzo MC, Alba MÁ, van der Haar R, Casas S, Vicente C, Medina P, Ederra M, Santamariña C, Moreno MP, Casanova F, Pedraz-Pingarrón C, Moreo P, Ascunce N, García M, Salas-Trejo D, Sánchez-Contador C, Llobet R, Lope V. Occupation and mammographic density: A population-based study (DDM-Occup). ENVIRONMENTAL RESEARCH 2017; 159:355-361. [PMID: 28843166 DOI: 10.1016/j.envres.2017.08.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 07/21/2017] [Accepted: 08/14/2017] [Indexed: 06/07/2023]
Abstract
INTRODUCTION High mammographic density is one of the main risk factors for breast cancer. Although several occupations have been associated with breast cancer, there are no previous occupational studies exploring the association with mammographic density. Our objective was to identify occupations associated with high mammographic density in Spanish female workers. METHODS We conducted a population-based cross-sectional study of occupational determinants of high mammographic density in Spain, based on 1476 women, aged 45-68 years, recruited from seven screening centers within the Spanish Breast Cancer Screening Program network. Reproductive, family, personal, and occupational history data were collected. The latest occupation of each woman was collected and coded according to the 1994 National Classification of Occupations. Mammographic density was assessed from the cranio-caudal mammogram of the left breast using a semi-automated computer-assisted tool. Association between mammographic density and occupation was evaluated by using mixed linear regression models, using log-transformed percentage of mammographic density as dependent variable. Models were adjusted for age, body mass index, menopausal status, parity, smoking, alcohol intake, educational level, type of mammography, first-degree relative with breast cancer, and hormonal replacement therapy use. Screening center and professional reader were included as random effects terms. RESULTS Mammographic density was higher, although non-statistically significant, among secondary school teachers (eβ = 1.41; 95%CI = 0.98-2.03) and nurses (eβ = 1.23; 95%CI = 0.96-1.59), whereas workers engaged in the care of people (eβ = 0.81; 95%CI = 0.66-1.00) and housewives (eβ = 0.87; 95%CI = 0.79-0.95) showed an inverse association with mammographic density. A positive trend for every 5 years working as secondary school teachers was also detected (p-value = 0.035). CONCLUSIONS Nurses and secondary school teachers were the occupations with the highest mammographic density in our study, showing the latter a positive trend with duration of employment. Future studies are necessary to confirm if these results are due to chance or are the result of a true association whose causal hypothesis is, for the moment, unknown.
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Affiliation(s)
- Javier García-Pérez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Mario González-Sánchez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | | | - Jerónimo Maqueda Blasco
- Instituto Nacional de Seguridad e Higiene en el Trabajo, Ministerio de Empleo y Seguridad Social, Madrid, Spain.
| | | | - Miguel Ángel Alba
- Área de Higiene Industrial, PREMAP Seguridad y Salud S.L.U., Barcelona, Spain.
| | | | - Silvia Casas
- Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain.
| | - Cándida Vicente
- Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain.
| | - Pilar Medina
- Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain.
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain.
| | - Carmen Santamariña
- Galicia Breast Cancer Screening Program, Regional Authority of Health, Galicia Regional Government, Corunna, Spain.
| | - María Pilar Moreno
- Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain.
| | - Francisco Casanova
- Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain.
| | - Carmen Pedraz-Pingarrón
- Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain.
| | - Pilar Moreo
- Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain.
| | - Nieves Ascunce
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain.
| | - Montse García
- Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain.
| | - Dolores Salas-Trejo
- Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain.
| | - Carmen Sánchez-Contador
- Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain.
| | - Rafael Llobet
- Institute of Computer Technology, Universitat Politècnica de València, Valencia, Spain.
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
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Chen JH, Liao F, Zhang Y, Li Y, Chang CJ, Chou CP, Yang TL, Su MY. 3D MRI for Quantitative Analysis of Quadrant Percent Breast Density: Correlation with Quadrant Location of Breast Cancer. Acad Radiol 2017; 24:811-817. [PMID: 28131498 DOI: 10.1016/j.acra.2016.12.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Revised: 12/21/2016] [Accepted: 12/22/2016] [Indexed: 01/20/2023]
Abstract
RATIONALE AND OBJECTIVES Breast cancer occurs more frequently in the upper outer (UO) quadrant, but whether this higher cancer incidence is related to the greater amount of dense tissue is not known. Magnetic resonance imaging acquires three-dimensional volumetric images and is the most suitable among all breast imaging modalities for regional quantification of density. This study applied a magnetic resonance imaging-based method to measure quadrant percent density (QPD), and evaluated its association with the quadrant location of the developed breast cancer. MATERIALS AND METHODS A total of 126 cases with pathologically confirmed breast cancer were reviewed. Only women who had unilateral breast cancer located in a clear quadrant were selected for analysis. A total of 84 women, including 47 Asian women and 37 western women, were included. An established computer-aided method was used to segment the diseased breast and the contralateral normal breast, and to separate the dense and fatty tissues. Then, a breast was further separated into four quadrants using the nipple and the centroid as anatomic landmarks. The tumor was segmented using a computer-aided method to determine its quadrant location. The distribution of cancer quadrant location, the quadrant with the highest QPD, and the proportion of cancers occurring in the highest QPD were analyzed. RESULTS The highest incidence of cancer occurred in the UO quadrant (36 out of 84, 42.9%). The highest QPD was also noted most frequently in the UO quadrant (31 out of 84, 36.9%). When correlating the highest QPD with the quadrant location of breast cancer, only 17 women out of 84 (20.2%) had breast cancer occurring in the quadrant with the highest QPD. CONCLUSIONS The results showed that the development of breast cancer in a specific quadrant could not be explained by the density in that quadrant, and further studies are needed to find the biological reasons accounting for the higher breast cancer incidence in the UO quadrant.
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Griesenauer RH, Weis JA, Arlinghaus LR, Meszoely IM, Miga MI. Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation. Phys Med Biol 2017; 62:4756-4776. [PMID: 28520556 DOI: 10.1088/1361-6560/aa700a] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test-retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91-0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows.
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Affiliation(s)
- Rebekah H Griesenauer
- Department of Biomedical Engineering, Vanderbilt University, 5824 Stevenson Center, Nashville, TN 37235, United States of America. Vanderbilt Institute in Surgery and Engineering (VISE), Nashville, TN, United States of America
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Chan S, Chen JH, Li S, Chang R, Yeh DC, Chang RF, Yeh LR, Kwong J, Su MY. Evaluation of the association between quantitative mammographic density and breast cancer occurred in different quadrants. BMC Cancer 2017; 17:274. [PMID: 28415974 PMCID: PMC5392962 DOI: 10.1186/s12885-017-3270-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 04/05/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To investigate the relationship between mammographic density measured in four quadrants of a breast with the location of the occurred cancer. METHODS One hundred and ten women diagnosed with unilateral breast cancer that could be determined in one specific breast quadrant were retrospectively studied. Women with previous cancer/breast surgery were excluded. The craniocaudal (CC) and mediolateral oblique (MLO) mammography of the contralateral normal breast were used to separate a breast into 4 quadrants: Upper-Outer (UO), Upper-Inner (UI), Lower-Outer (LO), and Lower-Inner (LI). The breast area (BA), dense area (DA), and percent density (PD) in each quadrant were measured by using the fuzzy-C-means segmentation. The BA, DA, and PD were compared between patients who had cancer occurring in different quadrants. RESULTS The upper-outer quadrant had the highest BA (37 ± 15 cm2) and DA (7.1 ± 2.9 cm2), with PD = 20.0 ± 5.8%. The order of BA and DA in the 4 separated quadrants were: UO > UI > LO > LI, and almost all pair-wise comparisons showed significant differences. For tumor location, 67 women (60.9%) had tumor in UO, 16 (14.5%) in UI, 7 (6.4%) in LO, and 20 (18.2%) in LI quadrant, respectively. The estimated odds and the 95% confidence limits of tumor development in the UO, UI, LO and LI quadrants were 1.56 (1.06, 2.29), 0.17 (0.10, 0.29), 0.07 (0.03, 0.15), and 0.22 (0.14, 0.36), respectively. In these 4 groups of women, the order of quadrant BA and DA were all the same (UO > UI > LO > LI), and there was no significant difference in BA, DA or PD among them (all p > 0.05). CONCLUSIONS Breast cancer was most likely to occur in the UO quadrant, which was also the quadrant with highest BA and DA; but for women with tumors in other quadrants, the density in that quadrant was not the highest. Therefore, there was no direct association between quadrant density and tumor occurrence.
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Affiliation(s)
- Siwa Chan
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.,Department of Medical Imaging, Tzu Chi General Hospital, Taichung, Taiwan.,Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jeon-Hor Chen
- Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA. .,Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung, Taiwan. .,John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California Irvine, No. 164, Irvine Hall, Irvine, CA, 92697-5020, USA.
| | - Shunshan Li
- Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Rita Chang
- Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Darh-Cherng Yeh
- Breast Cancer Center, Tzu Chi General Hospital, Taichung, Taiwan
| | - Ruey-Feng Chang
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Lee-Ren Yeh
- Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung, Taiwan
| | - Jessica Kwong
- Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA
| | - Min-Ying Su
- Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA, USA
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Linton L, Taylor M, Dunn S, Martin L, Chavez S, Stanitz G, Huszti E, Minkin S, Boyd N. Associations of Serum Levels of Sex Hormones in Follicular and Luteal Phases of the Menstrual Cycle with Breast Tissue Characteristics in Young Women. PLoS One 2016; 11:e0163865. [PMID: 27716810 PMCID: PMC5055356 DOI: 10.1371/journal.pone.0163865] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 09/15/2016] [Indexed: 11/18/2022] Open
Abstract
Background In previous work in young women aged 15–30 years we measured breast water and fat using MR and obtained blood for hormone assays on the same day in the follicular phase of the menstrual cycle. Only serum growth hormone levels and sex hormone binding globulin (SHBG) were significantly associated with percent breast water after adjustment for covariates. The sex hormones estradiol, progesterone and testosterone were not associated with percent water in the breast in the follicular phase of the menstrual cycle. In the present study we have examined the association of percent breast water with serum levels of sex hormones in both follicular and luteal phase of the menstrual cycle. Methods In 315 healthy white Caucasian young women aged 15–30 with regular menstrual cycles who had not used oral contraceptives or other hormones in the previous 6 months, we used MR to determine percent breast water, and obtained blood samples for hormone assays within 10 days of the onset of the most recent menstrual cycle (follicular phase) of the cycle on the same day as the MR scan, and a second blood sample on days 19–24 of the cycle. Serum progesterone levels of > = 5 mmol/L in days 19–24 were used to define the 225 subjects with ovulatory menstrual cycles, whose data are the subject of the analyses shown here. Results SHBG was positively associated with percent water in both follicular and luteal phases of the menstrual cycle. Total and free estradiol and total and free testosterone were not associated with percent water in the follicular phase, but in young women with ovulatory cycles, were all negatively associated with percent water in the luteal phase. Conclusions Our results from young women aged 15–30 years add to the evidence that the extent of fibroglandular tissue in the breast that is reflected in both mammographic density and breast water is associated positively with higher serum levels of SHBG, but not with higher levels of sex hormones.
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Affiliation(s)
- Linda Linton
- Campbell Family Institute for Breast Cancer Research, Toronto, ON, Canada
| | - Monica Taylor
- Campbell Family Institute for Breast Cancer Research, Toronto, ON, Canada
| | - Sheila Dunn
- Family Practice Health Centre, Women’s College Hospital, Toronto, ON, Canada
| | - Lisa Martin
- Campbell Family Institute for Breast Cancer Research, Toronto, ON, Canada
| | - Sonia Chavez
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Greg Stanitz
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Ella Huszti
- Campbell Family Institute for Breast Cancer Research, Toronto, ON, Canada
| | - Salomon Minkin
- Princess Margaret Cancer Centre, and Imaging Research, Toronto, ON, Canada
| | - Norman Boyd
- Campbell Family Institute for Breast Cancer Research, Toronto, ON, Canada
- * E-mail:
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Chau A, Hua J, Taylor D. Analysing breast tissue composition with MRI using currently available short, simple sequences. Clin Radiol 2016; 71:287-92. [DOI: 10.1016/j.crad.2015.11.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Revised: 11/18/2015] [Accepted: 11/24/2015] [Indexed: 11/17/2022]
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Methodology for Morphometric Analysis of Modern Human Contralateral Premolars. J Comput Assist Tomogr 2016; 40:617-25. [DOI: 10.1097/rct.0000000000000417] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Boyd NF, Li Q, Melnichouk O, Huszti E, Martin LJ, Gunasekara A, Mawdsley G, Yaffe MJ, Minkin S. Evidence that breast tissue stiffness is associated with risk of breast cancer. PLoS One 2014; 9:e100937. [PMID: 25010427 PMCID: PMC4091939 DOI: 10.1371/journal.pone.0100937] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 06/02/2014] [Indexed: 11/18/2022] Open
Abstract
Background Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. Methods Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. Results After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. Conclusion An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.
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Affiliation(s)
- Norman F. Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
- * E-mail:
| | - Qing Li
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Olga Melnichouk
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Ella Huszti
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Lisa J. Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Anoma Gunasekara
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Gord Mawdsley
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Martin J. Yaffe
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Salomon Minkin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
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