Estimation of mammographic density on an interval scale by transillumination breast spectroscopy.

Transillumination breast spectroscopy (TiBS) uses nonionizing optical radiation to gain information about breast tissue morphological and structural properties. TiBS spectra are obtained from 232 women and compared to mammographic density (MD) quantified using Cumulus. The ability of TiBS to estimate MD is assessed using partial least-squares (PLS) regression methods, which requires TiBS spectra as input (X) and Cumulus MD as target (Y) data. Multiple PLS models are considered to determine the optimal processing technique(s) for the input (X) and target (Y) data. For each model, the association between TiBS estimated MD (Y) and Cumulus MD (Y) is established using Spearman's rank correlation and linear regression analysis. The model that best estimates MD has the fewest assumptions regarding target (Y) and spectral (X) processing. The Spearman's correlation coefficient between predicted MD and Cumulus MD for this model is 0.88, with a regression slope (beta) of 0.93 (95% CI 0.83-1.02) and an R(2) of 0.78. The approximation of individual MD was within 10% of Cumulus MD for the majority of women (80%), without stratification on age, body mass index (BMI), and menopausal status. TiBS provides an alternative to mammography assessed MD enabling frequent and earlier use of MD as a risk marker in preventive oncology.

[1]  G. Sakorafas,et al.  Risk estimation for breast cancer development; a clinical perspective. , 2002, Surgical oncology.

[2]  B. Tromberg,et al.  Non-invasive measurements of breast tissue optical properties using frequency-domain photon migration. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[3]  K. Viswanath,et al.  The communications revolution and cancer control , 2005, Nature Reviews Cancer.

[4]  N. Boyd,et al.  Macronutrient intake and change in mammographic density at menopause: results from a randomized trial. , 1999, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[5]  V. McCormack,et al.  Breast Density and Parenchymal Patterns as Markers of Breast Cancer Risk: A Meta-analysis , 2006, Cancer Epidemiology Biomarkers & Prevention.

[6]  M. Onis The use of anthropometry in the prevention of childhood overweight and obesity , 2004, International Journal of Obesity.

[7]  Lothar Lilge,et al.  Non-ionizing near-infrared radiation transillumination spectroscopy for breast tissue density and assessment of breast cancer risk. , 2004, Journal of biomedical optics.

[8]  J. Giammarco,et al.  Bulk optical properties of healthy female breast tissue , 2002, Physics in medicine and biology.

[9]  E. Fishell,et al.  Radio-free America: what to do with the waste. , 1994, Environmental health perspectives.

[10]  Albert Cerussi,et al.  Noninvasive functional optical spectroscopy of human breast tissue , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[11]  N. Boyd,et al.  Effects at two years of a low-fat, high-carbohydrate diet on radiologic features of the breast: results from a randomized trial. Canadian Diet and Breast Cancer Prevention Study Group. , 1997, Journal of the National Cancer Institute.

[12]  B. Geller,et al.  A prospective study of breast cancer risk using routine mammographic breast density measurements. , 2004, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[13]  A. Kratz,et al.  Prostate-specific antigen and the early diagnosis of prostate cancer. , 2002, American journal of clinical pathology.

[14]  M. Myers Blood pressure measurement and the guidelines: a proposed new algorithm for the diagnosis of hypertension. , 2004, Blood pressure monitoring.

[15]  Jennifer A Harvey,et al.  Quantitative assessment of mammographic breast density: relationship with breast cancer risk. , 2004, Radiology.

[16]  B. Tromberg,et al.  Sources of absorption and scattering contrast for near-infrared optical mammography. , 2001, Academic radiology.

[17]  Norman Boyd,et al.  Mammographic breast density and cancer risk: The radiological view , 2005, Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology.

[18]  N. Boyd,et al.  Mammographic density and the risk and detection of breast cancer. , 2007, The New England journal of medicine.

[19]  M. Ferrari,et al.  Identification and Quantification of Intrinsic Optical Contrast for Near‐infrared Mammography , 1998, Photochemistry and photobiology.

[20]  N. Boyd,et al.  Mammographic densities and breast cancer risk. , 1998, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[21]  K. Viswanath Science and society: the communications revolution and cancer control. , 2005, Nature reviews. Cancer.

[22]  A. Miller,et al.  Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. , 1995, Journal of the National Cancer Institute.

[23]  R. Jong,et al.  Assessing breast tissue density by transillumination breast spectroscopy (TIBS): an intermediate indicator of cancer risk. , 2007, The British journal of radiology.

[24]  H Key,et al.  Optical attenuation characteristics of breast tissues at visible and near-infrared wavelengths. , 1991, Physics in medicine and biology.

[25]  N F Boyd,et al.  Breast cancer risk and measured mammographic density , 1998, European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation.

[26]  J. Wolfe,et al.  Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. , 1987, AJR. American journal of roentgenology.

[27]  R. Bowden,et al.  Assessing risk using different cholesterol-screening methods. , 2004, Public health.

[28]  A. Oza,et al.  Mammographic parenchymal patterns: a marker of breast cancer risk. , 1993, Epidemiologic reviews.

[29]  B. Rimer,et al.  Public education and cancer control. , 2005, Seminars in oncology nursing.