AIM: To demonstrate the use of grid technology to produce a database of mammograms and supporting patient data, specifically using breast density as a biomarker of risk for breast cancer, for epidemiological purposes. METHOD: The cohort comprised 1737 women from the UK and Italy, aged 28-87 years, mean 54.7 years, who underwent mammography after giving consent to the use of their data in the project. Information regarding height, weight, and exposure data (mAs and kV) was recorded. The computer program Generate-SMF was applied to all films in the database to measure breast volume, dense breast volume, and thereby percentage density. Visual readings of density using a six-category classification system were also available for 596 women. RESULTS: The UK and Italian participants were similar in height, but the UK women were significantly heavier with a slightly higher body mass index (BMI), despite being younger. Both absolute and percentage breast density were significantly higher in the Udine cohort. Images from the medio-lateral projection (MLO) give a significantly lower percentage density than cranio-caudal (CC) images (p<0.0001). Total breast volume is negatively associated with percentage density, as are BMI and age (p<0.0001 for all), although 80% of the variability in percentage density remains unexplained. CONCLUSION: The study offers proof of principle that confederated databases generated using Grid technology provide a useful and adaptable environment for large quantities of image, numerical, and qualitative data suitable for epidemiological research using the example of mammographic density as a biomarker of risk for breast cancer.
AIM: To demonstrate the use of grid technology to produce a database of mammograms and supporting patient data, specifically using breast density as a biomarker of risk for breast cancer, for epidemiological purposes. METHOD: The cohort comprised 1737 women from the UK and Italy, aged 28-87 years, mean 54.7 years, who underwent mammography after giving consent to the use of their data in the project. Information regarding height, weight, and exposure data (mAs and kV) was recorded. The computer program Generate-SMF was applied to all films in the database to measure breast volume, dense breast volume, and thereby percentage density. Visual readings of density using a six-category classification system were also available for 596 women. RESULTS: The UK and Italian participants were similar in height, but the UK women were significantly heavier with a slightly higher body mass index (BMI), despite being younger. Both absolute and percentage breast density were significantly higher in the Udine cohort. Images from the medio-lateral projection (MLO) give a significantly lower percentage density than cranio-caudal (CC) images (p<0.0001). Total breast volume is negatively associated with percentage density, as are BMI and age (p<0.0001 for all), although 80% of the variability in percentage density remains unexplained. CONCLUSION: The study offers proof of principle that confederated databases generated using Grid technology provide a useful and adaptable environment for large quantities of image, numerical, and qualitative data suitable for epidemiological research using the example of mammographic density as a biomarker of risk for breast cancer.
Authors: Joanne F Dorgan; Catherine Klifa; John A Shepherd; Brian L Egleston; Peter O Kwiterovich; John H Himes; Kelley Gabriel; Linda Horn; Linda G Snetselaar; Victor J Stevens; Bruce A Barton; Alan M Robson; Norman L Lasser; Snehal Deshmukh; Nola M Hylton Journal: Breast Cancer Res Date: 2012-07-13 Impact factor: 6.466
Authors: Sara Lindström; Celine M Vachon; Jingmei Li; Jajini Varghese; Deborah Thompson; Ruth Warren; Judith Brown; Jean Leyland; Tina Audley; Nicholas J Wareham; Ruth J F Loos; Andrew D Paterson; Johanna Rommens; Darryl Waggott; Lisa J Martin; Christopher G Scott; V Shane Pankratz; Susan E Hankinson; Aditi Hazra; David J Hunter; John L Hopper; Melissa C Southey; Stephen J Chanock; Isabel dos Santos Silva; JianJun Liu; Louise Eriksson; Fergus J Couch; Jennifer Stone; Carmel Apicella; Kamila Czene; Peter Kraft; Per Hall; Douglas F Easton; Norman F Boyd; Rulla M Tamimi Journal: Nat Genet Date: 2011-01-30 Impact factor: 38.330
Authors: Stephen W Duffy; Iris D Nagtegaal; Susan M Astley; Maureen G C Gillan; Magnus A McGee; Caroline R M Boggis; Mary Wilson; Ursula M Beetles; Miriam A Griffiths; Anil K Jain; Jill Johnson; Rita Roberts; Heather Deans; Karen A Duncan; Geeta Iyengar; Pam M Griffiths; Jane Warwick; Jack Cuzick; Fiona J Gilbert Journal: Breast Cancer Res Date: 2008-07-23 Impact factor: 6.466