Your browser doesn't support javascript.
loading
The impact of using weight estimated from mammographic images vs self-reported weight on breast cancer risk calculation.
Nair, Kalyani P; Harkness, Elaine F; Gadde, Soujanya; Lim, Yit Y; Maxwell, Anthony J; Moschidis, Emmanouil; Foden, Philip; Cuzick, Jack; Brentnall, Adam; Evans, D Gareth; Howell, Anthony; Astley, Susan M.
Afiliación
  • Nair KP; University of Manchester Medical School, Oxford Road, Manchester, UK.
  • Harkness EF; Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Stopford Building, Manchester, M13 9PT, UK.
  • Gadde S; Nightingale and Prevent Breast Cancer Centre, University Hospital of South Manchester, Manchester, M23 9LT, UK.
  • Lim YY; The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK, M23 9LT.
  • Maxwell AJ; Nightingale and Prevent Breast Cancer Centre, University Hospital of South Manchester, Manchester, M23 9LT, UK.
  • Moschidis E; Nightingale and Prevent Breast Cancer Centre, University Hospital of South Manchester, Manchester, M23 9LT, UK.
  • Foden P; Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Stopford Building, Manchester, M13 9PT, UK.
  • Cuzick J; Nightingale and Prevent Breast Cancer Centre, University Hospital of South Manchester, Manchester, M23 9LT, UK.
  • Brentnall A; The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK, M23 9LT.
  • Evans DG; Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Christie Hospital, Withington, Manchester, M20 4QL, UK.
  • Howell A; Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Stopford Building, Manchester, M13 9PT, UK.
  • Astley SM; The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK, M23 9LT.
Proc SPIE Int Soc Opt Eng ; 101342017 Mar 03.
Article en En | MEDLINE | ID: mdl-34925706
Personalised breast screening requires assessment of individual risk of breast cancer, of which one contributory factor is weight. Self-reported weight has been used for this purpose, but may be unreliable. We explore the use of volume of fat in the breast, measured from digital mammograms. Volumetric breast density measurements were used to determine the volume of fat in the breasts of 40,431 women taking part in the Predicting Risk Of Cancer At Screening (PROCAS) study. Tyrer-Cuzick risk using self-reported weight was calculated for each woman. Weight was also estimated from the relationship between self-reported weight and breast fat volume in the cohort, and used to re-calculate Tyrer-Cuzick risk. Women were assigned to risk categories according to 10 year risk (below average <2%, average 2-3.49%, above average 3.5-4.99%, moderate 5-7.99%, high ≥8%) and the original and re-calculated Tyrer-Cuzick risks were compared. Of the 716 women diagnosed with breast cancer during the study, 15 (2.1%) moved into a lower risk category, and 37 (5.2%) moved into a higher category when using weight estimated from breast fat volume. Of the 39,715 women without a cancer diagnosis, 1009 (2.5%) moved into a lower risk category, and 1721 (4.3%) into a higher risk category. The majority of changes were between below average and average risk categories (38.5% of those with a cancer diagnosis, and 34.6% of those without). No individual moved more than one risk group. Automated breast fat measures may provide a suitable alternative to self-reported weight for risk assessment in personalized screening.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proc SPIE Int Soc Opt Eng Año: 2017 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proc SPIE Int Soc Opt Eng Año: 2017 Tipo del documento: Article Pais de publicación: Estados Unidos