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Real‐time detection of breast cancer at the cellular level
Author(s) -
Carver Gary E.,
Locknar Sarah A.,
Weaver Donald L.,
Stein Janet L.,
Stein Gary S.
Publication year - 2019
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.27451
Subject(s) - autofluorescence , multispectral image , ex vivo , human breast , pixel , breast cancer , instrumentation (computer programming) , computer science , biomedical engineering , in vivo , translation (biology) , computer vision , artificial intelligence , medicine , cancer , fluorescence , optics , chemistry , biology , physics , biochemistry , microbiology and biotechnology , messenger rna , gene , operating system
Novel optoelectronic instrumentation has been developed for the multispectral imaging of autofluorescence emitted by metabolic fluorophores. The images resolve individual cells while spectra are collected for each pixel in the images. These datacubes are generated at a rate of 10 per second—fast enough for surgical guidance. The data is processed in real time to provide a single color‐coded image to the surgeon. To date, the system has been applied to fresh, ex vivo, human surgical specimens and has distinguished breast cancer from benign tissue. The approach is applicable to in vivo measurements of surgical margins and needle‐based optical biopsies. Ongoing work demonstrates that the system has great potential for translation to a hand‐held probe with high sensitivity and specificity.