This study reports the optical characterization and quantitative oximetry of human breast cancer using spectrally-resolved images collected with a broadband, continuous-wave optical mammography instrument. On twenty-six cancer patients, we collected two-dimensional optical mammograms and created maps of the concentrations of hemoglobin, water, and lipids, as well as the oxygen saturation of hemoglobin. For each cancerous breast, we analyzed the difference between the tumor region (as identified by x-ray and optical mammography) and the remainder of breast tissue. With respect to the surrounding tissue, we found that cancer regions have significantly higher concentrations of total hemoglobin (+2.4 ± 0.4 μM) and water (+7 ± 1% v/v), and significantly lower lipid concentration (8 ± 2% v/v) and oxygen saturation of hemoglobin (5 ± 1%). We also found a significant correlation between the tumor optical contrast and the grade of breast cancer as quantified by the Nottingham histologic score; this demonstrates how optical signatures may be representative of metabolic and morphological features, as well as the aggressive potential of the tumor.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4363570 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0117322 | PLOS |
Clin Imaging
November 2024
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK; Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, UK. Electronic address:
J Biomed Opt
November 2024
HTW - University of Applied Sciences Berlin, Faculty I - Health Electronics, Biomedical Electronics and Applied Research (BEAR) Labs, Berlin, Germany.
Significance: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.
Aim: We aim to quantitatively evaluate the classification of cancer-positive versus cancer-negative patients using ML methods on raw transmission time series data from bilateral breast scans during subjects' rest.
Comput Biol Med
December 2024
Department of Computer Engineering, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, 7516913817, Iran.
Breast cancer ranks as the second most prevalent cancer in women, recognized as one of the most dangerous types of cancer, and is on the rise globally. Regular screenings are essential for early-stage treatment. Digital mammography (DM) is the most recognized and widely used technique for breast cancer screening.
View Article and Find Full Text PDFRadiology
October 2024
From the Departments of Medical Imaging (J.J.J.G., S.D.V., I.S.) and IQ Health (M.J.M.B.), Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands (K.M.D.); Department of Radiology and Nuclear Medicine, Haga Teaching Hospital, Den Haag, the Netherlands (J.K.v.R.); Department of Radiology, Gelre Hospitals, Apeldoorn, the Netherlands (A.F.v.R.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (J.B.H.); Department of Radiology, Diakonessenhuis, Utrecht, the Netherlands (D.B.N.); Department of Radiology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands (L.E.M.D.); Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, Calif (C.K.A.); Department of Psychology, University of Nevada, Reno, Nev (M.A.W.); Dutch Expert Centre for Screening, Nijmegen, the Netherlands (M.J.M.B., I.S.); and Technical Medicine Center, University of Twente, Enschede, the Netherlands (I.S.).
JAAPA
October 2024
Elyse Watkins is an associate professor and associate program director in the Doctor of Medical Science in Healthcare Leadership program at Northeastern University in Boston, Mass. Toni Jackson is director of didactic education and an assistant professor in the PA program at Wake Forest University in Winston-Salem, N.C., and practices at Carolina Eye Associates in Greensboro, N.C. The authors have disclosed no potential conflicts of interest, financial or otherwise.
Extremely dense breasts can be an independent risk factor for breast cancer. A new FDA rule requires that patients be notified of their breast density and the possible benefits of additional imaging to screen for breast cancer. Clinicians should be cognizant of the data about breast cancer risk, breast density, and recommendations to change screening techniques if patients, particularly premenopausal females, have extremely dense breasts but no other known risk factors.
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