Digistain: a digital staining instrument for histopathology Hemmel Amrania,1 Giuseppe Antonacci,1 Che-Hung Chan,1 Laurence Drummond,1 William R Otto,2 Nicholas A.Wright,2,3 and Chris Phillips1,* 1 Experimental Solid State Group, Physics Dept., Imperial College, London, SW7 2AZ, UK Histopathology Laboratory, Cancer Research UK, London Research Institute,44, Lincolns Inn Fields, London, WC2A 3LY, UK 3 Centre for Digestive Diseases, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, UK *
[email protected] 2
Abstract: We describe a new mid-infrared (mid-IR) imaging method specifically designed to augment the H + E tissue staining protocol. Images are taken with bespoke IR filters at wavelengths that enable chemical maps to be generated, corresponding to the cytoplasmic (amide) and nuclear (phosphodiester) components of unstained oesophageal tissue sections. A suitably calibrated combination of these generates false colour computer images that reproduce not only the tissue morphology, but also accurate and quantitative distributions of the nuclear-to-cytoplasmic ratio throughout the tissue section. This parameter is a well documented marker of malignancy, and because the images can be taken and interpreted by clinically trained personnel in a few seconds, we believe this new “digistain” approach makes spectroscopic mid-IR imaging techniques available for the first time as a practical, specific and sensitive augmentation to standard clinical cancer diagnosis methods. © 2012 Optical Society of America. OCIS codes: (170.3880) Medical and biological imaging; (110.3080) Infrared imaging; (170.0110) Imaging systems; (170.6510) Spectroscopy, tissue diagnostics; (100.4145) Motion, hyperspectral image processing.
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R. Salzer and H. W. Siesler Eds, (2009) ″Infrared and Raman Spectroscopic imaging″ Wiley-VCH, Weinheim ISBN 978–3-527- 31993–0. S. J. Jang, J. M. Gardner, and J. Y. Ro, “Diagnostic approach and prognostic factors of cancers,” Adv. Anat. Pathol. 18(2), 165–172 (2011). L. M. Merlo, L. S. Wang, J. W. Pepper, P. S. Rabinovitch, and C. C. Maley, “Polyploidy, aneuploidy and the evolution of cancer,” Adv. Exp. Med. Biol. 676, 1–13 (2010). L. Hoover and J. J. Berman, “Epithelial repair versus carcinoma in esophageal brush cytology,” Diagn. Cytopathol. 4(3), 217–223 (1988). C. N. Battlehner, P. H. Saldiva, C. R. Carvalho, T. Y. Takagaki, G. S. Montes, R. N. Younes, and V. L. Capelozzi, “Nuclear/cytoplasmic ratio correlates strongly with survival in non-disseminated neuroendocrine carcinoma of the lung,” Histopathology 22(1), 31–34 (1993). D. P. Coco, J. R. Goldblum, J. L. Hornick, G. Y. Lauwers, E. Montgomery, A. Srivastava, H. Wang, and R. D. Odze, “Interobserver variability in the diagnosis of crypt dysplasia in Barrett esophagus,” Am. J. Surg. Pathol. 35(1), 45–54 (2011).
1. Introductory remarks At present the gold standard for diagnosing and monitoring cancer relies on a subjective visual microscopic analysis of excised samples of the patients’ tissue (biopsies) by a trained histopathologist. In general, positive patient outcomes correlate strongly with how early significant tissue abnormalities can be detected, and this in turn largely depends on the degree to which the cytological and architectural changes in the biopsy samples can be graded into an accepted range of normal and malignant classes with expediency and accuracy. As excised, a #159122 - $15.00 USD
(C) 2012 OSA
Received 2 Dec 2011; revised 30 Jan 2012; accepted 4 Feb 2012; published 15 Mar 2012
26 March 2012 / Vol. 20, No. 7 / OPTICS EXPRESS 7290
biopsy sample is essentially colourless, and the current “gold standard” of histopathological analysis employs a tissue staining process to visualise the microscopic tissue structure. Most commonly, in the “H+E” protocol, the two dyes Haemotoxylin and Eosin are used, and they stain the nuclear and cytoplasmic components of the biopsy specimen blue and pink respectively. The technique of Hyper-Spectral imaging (also known as generating a “spectroscopic image”, SI) involves combining a series of images of an object taken at a range of different electromagnetic (EM) wavelengths. In the mid infrared (mid-IR), corresponding to wavelengths between approximately λ~3µm and λ~15µm, the molecules in tissue absorb radiation by a well-understood mechanism involving the creation of vibronic excitations that are localised to specific chemical bonds. Each chemical moiety absorbs with a well characterised strength and wavelength.In contrast to visible and near-IR hyperspectral images (which work with a mix of electronic and vibrational overtone absorption) the mid-IR is absorbed in a linear way, so that a transmission-mode image of a thin tissue section taken at the appropriate mid-IR wavelength can be processed to generate a quantitative 2D distribution map of the corresponding chemical moiety.The technique has been applied to a diverse range of biological and pathological problems, and there is a large literature encompassing quantitative analysis and classification of normal and tumour tissue as well as more diverse applications in drug discovery, forensic science, proteomics and homeland security [1]. Typically a SI is acquired by measuring, often with a Fourier Transform Interferometer linked to an IR microscope, the sample’s mid-IR absorption spectrum. Data is averaged over a point, or sometimes, in the case of systems with multi-channel detectors, a small patch containing a number of points [1] and the SI is built up by mechanically scanning the point/patch across the sample. With this approach, increasing the image’s spatial resolution by a factor q means increasing the number of spectra taken by ~q2, whilst also shrinking the analysed area in a way that decreases the IR signal by ~q−2, so that maintaining the signal-tonoise (SNR) in the image means increasing the scan time by a factor ~q4. The result is that achieving the sort of spatial resolution required for visual histopathology analysis usually requires data acquisition periods that take from tens of minutes to several hours. The resulting data sets are very large and sophisticated statistical data processing methods have been developed that reduce the data to images taken at only a few specific wavelengths. These wavelengths are chosen according to statistical criteria that measure the degree to which absorption data at that wavelength correlates with differences in the pathological state of the tissue [1], that is they are chosen to maximise the ability of the SI technique to be able to discriminate spectrally between different tissue types. The drawback here is that the actual physical mechanism that results in a particular wavelength emerging from the statistical analysis is unknown. This means that, although the reduced data can be used to generate false colour images, even though the information in these images originated from quantitative chemical differences across the sample, there is no way for an expert clinician to interpret the contrast in the image in terms of their own biochemical and medical knowledge; they can work only with the morphology in the picture. Here we adopt a new approach. Rather than collecting large amounts of SI data, then discarding the majority of it in a “hypothesis free” way, we start by devising a stripped-down imaging protocol that tries to mimic the accepted H + E protocol but uses IR spectroscopic methods to replace the wet chemistry. We start from a knowledge of the origins of features in the IR tissue spectra, we restrict our data to only a couple of chemical moieties (analogous to the two dyes used in the H + E protocol), and we develop a technology that aims to augment the accepted H + E process by yielding additional quantitative chemical information about chemical differences between different regions of the biopsy samples. The long term aim is a bench-top instrument which is sufficiently economical, and quick and simple to use, that it can find a place in the clinical environment. Similar to the existing chemical staining protocols, this new “digistaining” method is tightly specified and, compared
#159122 - $15.00 USD
(C) 2012 OSA
Received 2 Dec 2011; revised 30 Jan 2012; accepted 4 Feb 2012; published 15 Mar 2012
26 March 2012 / Vol. 20, No. 7 / OPTICS EXPRESS 7291
to current lab-based SI analysis, somewhat inflexible. However, we see this simplicity as a strength. It is quick and yields results that are potentially more useful and understandable to clinically trained personnel. We believe that it will allow a wide range of comparative IR-based trials to take place, where the clinicians are able to make professional judgements that are, for the first time, based on both the morphological and the spectral information, in a way that is difficult with the often bewilderingly large data sets that are generated by the more technically complex laboratory SI systems. The key components of this imaging system as well as the samples used for the study are as follows:2. Mid-IR imaging system 2.1 Optical setup The illumination source (Fig. 1) is a standard IR Globar (LotOriel Model 6363) IR emitter. Although the low specific brightness of these sources is the principal reason for the long data acquisition times in scanning SI systems, they are better suited for our purposes because our
Aperture BaF2 Condenser Lens F=37.5mm
Electronic Shutter
Magnification = 3.1X
Sample in BaF2 Disc
IR Camera Field of View 2.5mm
Images 10.1mm Recorded
by Labview
75mm
75mm
Globar Source (20mm Extended Source)
~ 220mm
~ 70mm
BaF2 Imaging Lens F=50mm
Focal Plane Array (FPA) Detector Narrow Bandpass Filter
Fig. 1. Schematics of the optical setup. A Barium Fluoride condenser (f = 37.5mm) lens was placed between the Globar element and sample as shown to provide a sample illumination as uniform as possible. The f~50mm imaging lens was placed on a translational stage to allow focussing adjustments (needed to accommodate wavelength dispersion in the imaging lens) alongside the electronically operated shutter and narrow bandpass filters. The IR camera was placed in the image plane of the lens and interfaced with Labview to record data
optics use a much larger fraction of their optical output than does a scanning system. The central Globar segment is a roughly 6mm x 20mm area of sintered silicon carbide, electrically heated to 1050 K. Its black body emissivity is 70% ± 10% over the 1
