TY - JOUR
T1 - High definition infrared spectroscopic imaging for lymph node histopathology
AU - Leslie, L. Suzanne
AU - Wrobel, Tomasz P.
AU - Mayerich, David
AU - Bindra, Snehal
AU - Emmadi, Rajyasree
AU - Bhargava, Rohit
N1 - Funding Information:
The work reported in this manuscript was funded in part by the National Institutes of Health via grant number 2R01EB009745. Partial funding was also received through the Beckman Postdoctoral Fellows Program to TPW. TPW acknowledges support from the Foundation for Polish Science through the START program.
Publisher Copyright:
© 2015 Leslie et al.
PY - 2015/6/3
Y1 - 2015/6/3
N2 - Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micronsized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.
AB - Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micronsized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.
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U2 - 10.1371/journal.pone.0127238
DO - 10.1371/journal.pone.0127238
M3 - Article
C2 - 26039216
AN - SCOPUS:84934927186
SN - 1932-6203
VL - 10
JO - PLoS One
JF - PLoS One
IS - 6
M1 - e0127238
ER -