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Infrared spectroscopic imaging for histopathologic recognition

Abstract

The process of histopathology, comprising tissue staining and morphological pattern recognition, has remained largely unchanged for over 140 years1. 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 variability2,3. 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 descriptors4, but a practical spectroscopic protocol for histopathology is lacking. Here we couple high-throughput Fourier transform infrared (FTIR) spectroscopic imaging5 of tissue microarrays6 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 significance7 and eliminates any requirement for dyes or molecular probes. Finally, we differentiate benign from malignant prostatic epithelium by spectroscopic analyses.

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Figure 1: Chemical staining and infrared spectroscopic characterization of prostate tissue.
Figure 2: Histology model and automated classification.
Figure 3: High-throughput validation of automated, objective tissue classification.
Figure 4: Adenocarcinoma prediction for samples.

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Acknowledgements

We thank Kimberly Tuttle for technical assistance in preparing tissue microarrays and samples for spectroscopic imaging.

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Correspondence to Ira W Levin.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

H&E stained images and their corresponding classified images from two arrays demonstrating the validity of the approach for large populations. (PDF 740 kb)

Supplementary Fig. 2

Patient-matched benign and malignant samples visualized using conventional staining and spectroscopic segmentation. (PDF 245 kb)

Supplementary Table 1

Spectral biomarkers employed for spectroscopic histology. (PDF 10 kb)

Supplementary Table 2

Spectral biomarkers employed for distinguishing diseased from benign epithelial tissue. (PDF 12 kb)

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Fernandez, D., Bhargava, R., Hewitt, S. et al. Infrared spectroscopic imaging for histopathologic recognition. Nat Biotechnol 23, 469–474 (2005). https://doi.org/10.1038/nbt1080

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