Automated high-throughput assessment of prostate biopsy tissue using infrared spectroscopic chemical imaging

Paul Bassan; Ashwin Sachdeva; Jonathan H. Shanks; Mick D. Brown; Noel W. Clarke; Peter Gardner

doi:10.1117/12.2043290

20 March 2014 Automated high-throughput assessment of prostate biopsy tissue using infrared spectroscopic chemical imaging

Paul Bassan, Ashwin Sachdeva, Jonathan H. Shanks, Mick D. Brown, Noel W. Clarke, Peter Gardner

Author Affiliations +

Proceedings Volume 9041, Medical Imaging 2014: Digital Pathology; 90410D (2014) https://doi.org/10.1117/12.2043290
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Fourier transform infrared (FT-IR) chemical imaging has been demonstrated as a promising technique to complement histopathological assessment of biomedical tissue samples. Current histopathology practice involves preparing thin tissue sections and staining them using hematoxylin and eosin (H&E) after which a histopathologist manually assess the tissue architecture under a visible microscope. Studies have shown that there is disagreement between operators viewing the same tissue suggesting that a complementary technique for verification could improve the robustness of the evaluation, and improve patient care. FT-IR chemical imaging allows the spatial distribution of chemistry to be rapidly imaged at a high (diffraction-limited) spatial resolution where each pixel represents an area of 5.5 × 5.5 μm² and contains a full infrared spectrum providing a chemical fingerprint which studies have shown contains the diagnostic potential to discriminate between different cell-types, and even the benign or malignant state of prostatic epithelial cells. We report a label-free (i.e. no chemical de-waxing, or staining) method of imaging large pieces of prostate tissue (typically 1 cm × 2 cm) in tens of minutes (at a rate of 0.704 × 0.704 mm² every 14.5 s) yielding images containing millions of spectra. Due to refractive index matching between sample and surrounding paraffin, minimal signal processing is required to recover spectra with their natural profile as opposed to harsh baseline correction methods, paving the way for future quantitative analysis of biochemical signatures. The quality of the spectral information is demonstrated by building and testing an automated cell-type classifier based upon spectral features.

Citation Download Citation

Paul Bassan, Ashwin Sachdeva, Jonathan H. Shanks, Mick D. Brown, Noel W. Clarke, and Peter Gardner "Automated high-throughput assessment of prostate biopsy tissue using infrared spectroscopic chemical imaging", Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 90410D (20 March 2014); https://doi.org/10.1117/12.2043290

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available