TY - JOUR
T1 - Infrared spectroscopic imaging for histopathologic recognition
AU - Fernandez, Daniel C.
AU - Bhargava, Rohit
AU - Hewitt, Stephen M.
AU - Levin, Ira W.
N1 - 1Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892-0520, USA. 2Tissue Array Research Program, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892-4605, USA. 3Present address: Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, New York 10029, USA. 4These authors contributed equally to this work. Correspondence should be addressed to I.W.L. ([email protected]).
PY - 2005
Y1 - 2005
N2 - The process of histopathology, comprising tissue staining and morphological pattern recognition, has remained largely unchanged for over 140 years. Although it is integral to clinical and research activities, histopathologic recognition remains a time-consuming, subjective process to which only limited statistical confidence can be assigned because of inherent operator variability. Although immunohistochemical approaches allow limited molecular detection, significant challenges remain in using them for quantitative, automated pathology. Vibrational spectroscopic approaches, by contrast, directly provide nonperturbing molecular descriptors, but a practical spectroscopic protocol for histopathology is lacking. Here we couple high-throughput Fourier transform infrared (FTIR) spectroscopic imaging of tissue microarrays with statistical pattern recognition of spectra indicative of endogenous molecular composition and demonstrate histopathologic characterization of prostatic tissue. This automated histologic segmentation is applied to routine archival tissue samples, incorporates well-defined tests of statistical significance and eliminates any requirement for dyes or molecular probes. Finally, we differentiate benign from malignant prostatic epithelium by spectroscopic analyses.
AB - The process of histopathology, comprising tissue staining and morphological pattern recognition, has remained largely unchanged for over 140 years. Although it is integral to clinical and research activities, histopathologic recognition remains a time-consuming, subjective process to which only limited statistical confidence can be assigned because of inherent operator variability. Although immunohistochemical approaches allow limited molecular detection, significant challenges remain in using them for quantitative, automated pathology. Vibrational spectroscopic approaches, by contrast, directly provide nonperturbing molecular descriptors, but a practical spectroscopic protocol for histopathology is lacking. Here we couple high-throughput Fourier transform infrared (FTIR) spectroscopic imaging of tissue microarrays with statistical pattern recognition of spectra indicative of endogenous molecular composition and demonstrate histopathologic characterization of prostatic tissue. This automated histologic segmentation is applied to routine archival tissue samples, incorporates well-defined tests of statistical significance and eliminates any requirement for dyes or molecular probes. Finally, we differentiate benign from malignant prostatic epithelium by spectroscopic analyses.
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U2 - 10.1038/nbt1080
DO - 10.1038/nbt1080
M3 - Article
C2 - 15793574
AN - SCOPUS:20544435588
SN - 1087-0156
VL - 23
SP - 469
EP - 474
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 4
ER -