Optical discrimination between malignant and benign breast lesions

Giovanna Quarto, Antonio Pifferi, Rinaldo Cubeddu, Francesca Ieva, Anna Maria Paganoni, Francesca Abbate, Enrico Cassano, Paola Taroni

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Time domain multi-wavelength (635 to 1060 nm) optical mammography was performed on 82 subjects with breast lesions (45 malignant and 38 benign lesions). A perturbative approach based on the high-order calculation of the pathlength of photons inside the lesion was applied to estimate differences between lesion and average healthy tissue of the same breast in terms of: i) absorption properties, and ii) concentration of the major tissue constituents (oxy- and deoxy-hemoglobin, water, lipid and collagen). The absorption difference Δμa between lesion and healthy tissue is significantly different for malignant vs. benign lesions at all wavelengths. Logistic regression fitted to the absorption data identifies 975 nm as the key wavelength to discriminate malignant from benign lesions. When the difference in tissue composition between lesion and healthy tissue is considered, malignant lesions are characterized by significantly higher collagen content than benign lesions. Also the best model for the discrimination of malignant lesions obtained applying regression logistic to tissue composition is based only on collagen. Including demographic information into the model improves its specificity.

Original languageEnglish
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISBN (Print)9781628417036
Publication statusPublished - 2015
EventDiffuse Optical Imaging V - Munich, Germany
Duration: Jun 23 2015Jun 25 2015


OtherDiffuse Optical Imaging V


  • breast cancer
  • optical mammography
  • time-resolved diffuse optical imaging
  • Tissue diagnostics

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


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