Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study.

ABSTRACT: Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635-1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (ei

SUBMITTER: Taroni P 

PROVIDER: S-EPMC5238417 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature