We would like to acknowledge the Department of Pathology at the University of Illinois at Chicago for financial support. Histology and visible imaging services were provided by the Research Resources Center - Research Histology and Tissue Imaging Core at the University of Illinois at Chicago established with the support of the Vice Chancellor of Research, in particular we would like to thank Ryan Deaton and Andy Hall for their expertise. We would also like to thank Agilent Technologies, in particular Frank Weston for support and loaning of additional IR lens.

1. Setting up an FT-IR Microscope and Acquiring Tissue Images
<ol>
	<li>Section a formalin-fixed paraffin-embedded tissue block at 4 &#956;m thickness on to an IR compatible slide using a microtome. Alternately, section a liquid nitrogen frozen tissue at 4 &#956;m thickness onto an IR compatible slide using a cryostat. 
	NOTE: Typically, a serial section will also be acquired on a glass slide and stained with a special (such as Haematoxylin and Eosin (H&#38;E)) or immunohistochemical stain. In addition, cultured cell lines can be grown on IR compatible slides. IR compatible slides can be IR reflective slides for reflection mode imaging (e.g., MirrIR slide, gold) or IR transparent slides for transmission mode imaging (e.g., BaF2, CaF2).</li>
	<li>Purge the FT-IR microscope and spectrometer using either dry air or dry nitrogen gas to remove atmospheric water from the system. Wait at least 45 min before imaging to ensure a thorough purge.</li>
	<li>Cool both the FPA detector (to 79 K) and the internal MCT detector in the FT-IR microscope using liquid nitrogen. Cool the detectors approximately every 6 hr. 
	CAUTION! Liquid nitrogen is a cryogenic fluid and can cause cold burns, frostbite and in enclosed spaces asphyxiation.</li>
	<li>Mount the sample slide on the microscope stage for FT-IR imaging.</li>
	<li>Ensure the visible light is &#8220;ON&#8221; and then either using the binoculars or the sample capture program (which provides a real-time visible image of the tissue), focus on the sample.</li>
	<li>Open the bundle software package such as resolutions pro and click &#8216;Collect&#8217;, then click &#8216;Diagnostics&#8217; and then select &#8216;Align Spectrometer&#8217;. Ensure that the beam path to the spectrometer internal detector is not obstructed.</li>
	<li>Click on &#8216;Imaging Setup&#8217;.</li>
	<li>In the &#8216;Electronics&#8217; tab, select the appropriate &#8216;Speed&#8217;, &#8216;Under Sampling Ratio (UDR)&#8217; and &#8216;Filters&#8217; settings depending on the system. 
	NOTE: In this example, the setting is Speed = 2.5 KHz, UDR = 4 and Filters = None.</li>
	<li>In the &#8216;Optics&#8217; tab ensure that &#8216;Mid-IR source&#8217;, &#8216;Open aperture&#8217; and &#8216;100% beam attenuator&#8217; are selected.</li>
	<li>To calibrate the system, in the &#8216;Optics&#8217; tab, select &#8216;Detector&#8217; as &#8216;Ground&#8217;, &#8216;Microscope Detector&#8217; as &#8216;Left&#8217;, and then select either &#8216;Transmittance&#8217; or &#8216;Reflectance&#8217; under &#8216;Optics mode&#8217; depending on the type of slide being used.</li>
	<li>Click Setup, which will open up the &#8216;Lancer Control&#8217; window. 
	NOTE: For reflection mode follow instructions in 1.12 and 1.13 and for transmission mode follow instructions in 1.14 to 1.16. Continue from 1.17 for both reflection and transmission.</li>
	<li>For reflection mode, in &#8216;Lancer Control&#8217; click on &#8216;Raw&#8217;. Using the stage control joystick and watching the live view of the FT-IR interferogram image (top right image), move to a clean area on the slide.</li>
	<li>Adjust the integration time to approximately 8,000 counts. Next, move the stage to find a piece of tissue with structure, preferably the edge of a tissue, and perfect the focus of the image. Change &#8216;Warmth&#8217; and &#8216;Contrast&#8217; options to help form an image to improve focusing, this will have no effect on the IR data. Continue from 1.18.</li>
	<li>For transmission mode, in &#8216;Lancer Control&#8217; click on &#8216;Raw&#8217;. Using the stage control joystick and watching the live view of the FT-IR interferogram image (top right image), move to a clean area of the slide.</li>
	<li>Adjust the integration time to approximately 8,000 counts.</li>
	<li>Adjust the bottom focusing/condenser objective to increase the number of counts to its maximum. Watch the shape of the bottom right image in Lancer Control to ensure that it is Gaussian in appearance and relatively uniform. Adjust the integration time again to approximately 8,000 counts. 
	NOTE: If any of the pixels in the FT-IR interferogram image turn white, reduce the integration time.</li>
	<li>Move the stage to find a piece of tissue with structure, preferably the edge of a tissue and perfect the focus of the image. Optionally, change the warmth and contrast options to help form an image to improve focusing, but will have no effect on the IR data.</li>
	<li>Using the stage control joystick, move to a clean area of the slide. Press the &#8216;Calibrate&#8217; button. Ensure the &#8216;Out Of Range (OOR)&#8217; value is less than 50 and the difference between the &#8216;High Flux&#8217; and &#8216;Low Flux&#8217; counts is at least 4,000 counts.</li>
	<li>Select &#8216;OK&#8217; twice. In the optics tabs select; &#8216;Detector&#8217; = &#8216;MCT&#8217;, &#8216;Microscope Detector&#8217; = &#8216;Right&#8217; and then click &#8216;Setup&#8217;. At this point there will be a FT-IR interferogram on the screen. Click on &#8216;Find Centerburst&#8217;. Click &#8216;Okay&#8217;.</li>
	<li>In the &#8216;Optics&#8217; tab, reselect &#8216;Detector&#8217; = &#8216;Ground&#8217;, &#8216;Microscope Detector&#8217; = &#8216;Left&#8217; and select &#8216;Setup&#8217;.</li>
	<li>In Lancer Control &#8212; ensure the image is still on a clean area and click &#8216;Calibrate&#8217; again. Click &#8216;Okay&#8217;.</li>
	<li>Next, collect a background FT-IR image to correct for absorbance from the atmosphere, system and slide. Go to the &#8216;Electronics&#8217; tab and select an appropriate spectral resolution, typically of 4 cm-1 or 8 cm-1 for tissue.</li>
	<li>Go to the &#8216;Background&#8217; tab and type 128 in &#8216;Scans to co-add&#8217;. Select the &#8216;New File&#8230;&#8217; button and place the background file in appropriate folder. Check the &#8216;Imaging&#8217; tab to ensure mosaicing is 1 by 1. Click &#8216;Background&#8217;, wait for the scan to finish and confirm where to save the file. Click a region on the background FT-IR image and check the spectrum.</li>
	<li>To take a large mosaic image of the sample, select the &#8216;Imaging&#8217; tab and insert the number of X and Y frames for the mosaic size you wish to acquire.</li>
	<li>Click &#8216;Setup&#8217; and in Lancer Control use the live IR view to find the area of interest. If taking a mosaic, center the live feed in the middle of the area of interest. Click &#8216;Okay&#8217;. Go to the &#8216;Electronics&#8217; tab and type the number of scans to co-add (typically a value between 2 and 16 scans for tissue). Click &#8216;Scan&#8217;.</li>
	<li>Check the collected FT-IR image on the screen to ensure it looks focused. Click on the image to bring up an IR spectrum from that location and check that it looks to have an acceptable signal to noise. Acquire a visible image of the sample.</li>
	<li>Save the image and export it to the required format, such as ENVI-IDL.</li>
</ol>
2. Adapting an FT-IR Microscope for High-definition Capabilities
NOTE: Most FT-IR systems are equipped with an objective approximately 15X magnification and 0.5 numerical aperture (NA). To image in high-definition mode, an IR compatible 36X or 74X objective can be used to give diffraction limited imaging capabilities.
<ol>
	<li>Remove the system&#8217;s 15X objective by unscrewing counter clockwise.</li>
	<li>Screw in either the 36X or 74X objective in its place. Align the objective prior to use. Use lens extension tubes to bring the objective close enough to the sample.</li>
	<li>Place tissue under the new objective and focus using visible light using either the binoculars or Sample Capture program. 
	NOTE: High-definition imaging must be done in transmission mode. The very close working distance of these objectives (1-2 mm) and very shallow depth of focus requires focusing slowly and carefully, taking time to lower the objective without touching the sample.</li>
	<li>Follow instructions from 1.6 to 1.11. 
	NOTE: Due to being significantly more difficult to focus and much less light reaching the detector, the following protocol is adjusted based on 1.14.</li>
	<li>In transmission mode, click on &#8216;Raw&#8217;. Using the stage control joystick and watching the live view of the FT-IR interferogram image (top right image), move to the tissue and focus (ideally on an edge). 
	NOTE: This may be difficult, therefore adjust the &#8216;Warmth&#8217; and &#8216;Contrast&#8217; options to help form an image to improve focusing (these options have no affect on the IR data).</li>
	<li>Once focused, using the stage control joystick and the live IR view move to a clean area of the slide. Adjust the integration time to approximately 8,000 counts. Adjust the bottom focusing objective to increase the number of counts to its maximum. Adjust the integration time again to approximately 8,000 counts.</li>
	<li>Move the stage to find a piece of tissue with structure, preferably the edge of a tissue, and perfect the focus of the image.</li>
	<li>If mosaicking an image at high resolution, adjust the stage to allow correct movement required across distances for accurate mosaicing. To change the stage distance settings, go to &#8216;Setup stage&#8217; in Lancer Control and adjust the horizontal and vertical alignment settings to allow for correct mosaicking.</li>
	<li>Using the stage control joystick move to a clean area of the slide. Press the &#8216;Calibrate&#8217; button. Ensure the Out Of Range (OOR) value is less than 50 for both 36X and 74X objectives. Ensure the difference between the High Flux and Low Flux values is at least 1,000 counts for the 74X objective and 2,000 counts for the 36X objective.</li>
	<li>Continue from 1.19 to 1.27. The number of scans in 1.23 and 1.25 will need to be adjusted due to reduced signal to approximately 256 scans for the background image and 16 to 128 scans for the tissue image.</li>
</ol>
3. Visualizing and Classifying IR Spectral Datasets
NOTE: In this section, we will discuss how to visualize and extract data from spectral images using geospatial image processing and analyzing software such as ENVI+IDL, however the process is very similar for any alternate software such as MATLAB, free software such as CytoSpec, or the instrument developer&#8217;s own software. There are a few different spectral processing techniques that may be performed on the IR data.
<ol>
	<li>Open geospatial image processing and analyzing software and load the IR data file.</li>
	<li>Apply a baseline correction algorithm to the IR data by selecting &#8220;Spectral tools&#8221; and scroll down and click &#8220;Absorbance spectra&#8221;. Observe a pop-up menu and select &#8220;Baseline correction&#8221; 
	NOTE: Baseline correction will remove a baseline offset slope from the data due to scattering</li>
	<li>Perform Spectral normalization, by ratioing the data to a certain spectral peak (typically Amide I (1,650 cm-1) or Amide II (1,550 cm-1)) or area under a defined region of the spectra. Do this by selecting &#8220;Normal spectra&#8221; under the &#8220;Absorbance Spectra&#8221; menu options. 
	NOTE: Spectral normalization is performed so that any differences in spectra are real biochemical differences and not due to thickness or density differences between samples.</li>
	<li>Use a noise reduction algorithm to remove noise from the spectra if necessary28. 
	NOTE: There are multiple approaches available by which baseline correction, spectral normalization and noise reduction can be achieved, with most software having automated algorithms built in. In addition, there are an emerging number of approaches that will correct for spectral aberrations, which have been discussed in detail29-42; however, the community does not yet agree on which of these are needed.</li>
	<li>Observe a list of all the IR frequencies collected within the image (typically of a spectral range from 900 to 4,000 cm-1). Click on the frequencies that correspond to specific biomolecules to observe an image of the tissue at the selected frequency.
	<ol>
		<li>For example, click on 1,650 cm-1 band to observe the distribution of proteins in the sample. Alternatively click on 1,080 cm-1 band to observe the distribution of nucleic acids in the sample. Use wavenumber 1,650 cm-1.</li>
	</ol>
	</li>
	<li>Create additional images by computing spectral peak height ratios, peak area ratios etc. that will allow for visualization of different biomolecular components. Click on &#8216;Spectral Tools&#8217; and then select either &#8216;Peak Height Ratios&#8217; or &#8216;Calculate Image Area&#8217; to create images.</li>
	<li>Scan the corresponding adjacent tissue section which is stained using a separate whole slide imager system that captures brightfield images. Alongside the IR image, bring up the digital image of the stained tissue with a visible image program.</li>
	<li>Right click on the image at a region of interest and select &#8216;Z profile&#8217;. This will give the spectral information at the selected pixel.</li>
	<li>Look at the IR spectra of multiple pixels from multiple classes, such as comparing cell types, disease states. Mark specific pixels on the image using the &#8216;Regions Of Interest&#8217; (ROI) tool. To perform this, right click on the image and select &#8216;ROI tool&#8217;. Create the classes that are to be labeled, for example normal, dysplasia, and cancer classes. Then select, &#8216;ROI type&#8217; &#8212; &#8216;Point&#8217;. Then select the class to select pixels for and draw on the appropriate pixels on the IR image. Derive the average spectra for each of the classes using the &#8216;Average ROI&#8217; tool.</li>
	<li>Compare derived spectra by plotting in graphing software.</li>
</ol>

The authors have nothing to disclose.

FT-IR is an emerging modality for label-free biochemical imaging of tissue sections, with the potential to have an important role in improving the current standard of diagnosis in pathology. The current gold standard for pathology requires tissues to be biopsied, fixed in formalin, embedded in paraffin, sectioned multiple times, and stained with multiple stains. A highly trained pathologist has to subjectively visually assess the tissue structure and cellular morphology to determine a diagnosis. Here we show how to collect high-resolution IR images from the same type of sections and discuss some of the computational approaches to examine chemical differences between cell types and disease states.
The critical steps within this protocol are to ensure that the tissues are very carefully focused and that the system is well calibrated to ensure very high quality spectroscopic data. The care when setting up the system is particularly critical when working with high magnification objectives. To aid in troubleshooting, the following list covers some of the potential difficulties encountered;
Problem: Low IR intensity when imaging in reflection. Solution: Check IR slide orientation as the reflective coating may be on the wrong side of the slide.
Problem: Low signal/Red warning sign in Lancer Control. Solution: Cool detectors with LN2. Liquid nitrogen is required for the FPA detectors to function and requires periodically being topped up.
Problem: Velocity error/movement errors. Solution: Reset spectrometer and reduce vibrations. Vibrations will cause the moving mirror in the interferometer to be disturbed.
Problem: Water vapor spikes in data. Solution: Increase purge on system and protect sample from air.
Problem: Invalid centerburst. Solution: Find centerburst again.
Problem: Low flux difference in transmission, even though focused. Solution: Adjust bottom condenser. This will occur as the IR light is not being focused to a point on the sample.
In this paper, we have focused on how to acquire high definition IR images of tissues in either transmission or transflectance mode. The nature of FT-IR imaging, is that there are multiple modifications that can be made to the data acquisition, such as, type of substrate, fixation technique, sample thickness, spectral resolution, interferometer mirror speed etc. The effect of these parameters has been discussed in extensive detail recently 4,5,17,51.
There are a number of modifications that can be made to the imaging system including imaging in ATR mode10,24,26 and using nanoscale thermal approaches52,53 to allow for high resolution IR imaging. The main limitation with high resolution IR imaging is that the tissues must be carefully prepared and thin enough for IR to pass through (typically 4 &#956;m thickness). In addition, transmission and reflectance FT-IR imaging requires the samples to be dry due to the absorbance of IR by water. However, FT-IR imaging has significant advantages over other techniques, in that it can very rapidly image large areas of tissue while deriving rich and detailed biochemical information. Other similar techniques that derive biochemical information in a label-free fashion include Raman spectroscopy, however the time of data acquisition is much slower to acquire images. New Raman imaging approaches are emerging including Stimulated Raman scattering (SRS) and Coherent Antistokes Raman scattering (CARS); however, they have access limited spectral range or single frequency imaging.
The advances in speed of data acquisition, spatial resolution, and availability of computational approaches have been of tremendous value in making FT-IR imaging a more feasible approach for translation as a new imaging tool in pathology. The recent advances in spatial resolution have been particularly important for tissue pathology due to key cell types not being resolvable using conventional FT-IR imaging systems. The recent paper by Reddy et al. showed how to model an ideal system to obtain the optimal spatial resolution of an FT-IR imaging system5. The kidney tissue example presented in this paper demonstrates the importance of higher spatial resolutions in order to extract biochemical information from glomerular structures (Figure&#160;3 and Figure&#160;5). In the future, new advances in Quantum Cascade Lasers as very bright IR light sources54-57, 3D spectral imaging58, and breakthroughs in the field of nanoscale IR technologies52,53,59,60 hold exciting new avenues of research that may have huge implications in the future of tissue imaging.
We have presented examples of applications in liver and kidney disease where there is a need for additional biochemical information that can be of diagnostic value. The Spectral Pathology Lab in the Department of Pathology at the University of Illinois at Chicago is focused on the translation of IR imaging technologies towards improving disease diagnosis and improved prediction of patient outcome. FT-IR imaging may overcome some of the current limitations in pathology practice where quantitative and objective information is required. In particular, future work is focused on identifying areas in current pathology practice where current techniques fail to provide adequate diagnostic sensitivity or provide limited information. A clear need exists in improving the current practice of pathology and towards giving more information to the pathologist about a patient&#8217;s disease status, which may be achievable using high-definition FT-IR imaging.

IR spectroscopy has been an analytical tool available in some form since the 1930s; however, it is only been within the last decade that the area of tissue imaging with FT-IR has exploded. The advances in FT-IR for tissue imaging have been driven in a large part by three key developments: 1) increased speed of data acquisition due to the availability of large Focal Plane Array (FPA) detectors which typically have thousands of IR sensitive detectors1,2, 2) development of advanced processing algorithms and computational power to handle large hyperspectral data sets3, and 3) modeling of FT-IR imaging systems to maximize spatial resolution4,5. There have been numerous high quality and very extensive articles reviewing the field of FT-IR spectroscopy recently6-16, in addition to a Nature Protocols paper that details the steps to obtain point spectra or maps from tissues17. In this paper, we will focus on the protocol to obtain images of tissues using a 128 x 128 FPA detector in a modified FT-IR system with high-definition capabilities.
FT-IR imaging has long been suggested to be a potentially desirable tool for cell and tissue imaging due to the ability to obtain images in which every pixel has a wealth of biochemical information. FT-IR imaging is based on the principle that different biomolecules in a sample will quantitatively absorb different regions of the mid-infrared; this allows for the derivation of a &#8216;biochemical fingerprint&#8217;. This fingerprint had been shown in many studies to alter between different cell types and disease states. Unlike in conventional pathology practice where stains and immunohistochemical markers need to be used to visualize and identify cell types and tissue structures that are used to guide diagnosis and treatment options, the images from FT-IR are formed based on the inherent biochemistry of the tissue. The current technique of staining tissue for diagnosis is time-consuming, destructive, laborious, and requires subjective expertise of the pathologist, whereas FT-IR offers the potential to make this process rapid, non-destructive, highly automated, and more objective. In addition, FT-IR provides a novel route to obtaining additional biochemical information that may not be readily accessible using conventional staining techniques.
One of the most exciting advances in recent years has been the availability of high resolution imaging approaches that can now allow for the visualization and characterization of cell types and tissue structures that are critical for comprehensive disease diagnosis. One of these techniques is Attenuated Total Reflectance (ATR) FT-IR which incorporates a solid immersion lens (SIL) of a high refractive index which allows for high resolution imaging18, with many very exciting studies showing its applications19-25. In addition, it was recently demonstrated that the increased spatial resolution associated with ATR imaging can allow for the visualization and classification of endothelial and myoepithelial cells in breast tissue which form a key component of breast cancer diagnosis26. While ATR imaging is very useful, this technique requires the SIL to make contact with the tissue to form FT-IR images; therefore, its use is somewhat limited for tissue pathology where large regions of tissues must be quickly imaged.
A second approach was demonstrated by coupling a high magnification objective to an existing FT-IR system that uses a synchrotron as a bright source of IR, it is possible to fully illuminate an FPA and image with an effective pixel size of 0.54 x 0.54 &#956;m. This allowed for us to visualize key structures in breast and prostate tissues that were not resolvable using conventional FT-IR systems4. While these dramatic increases in IR image spatial resolution were exciting, its use remained limited due to requiring a synchrotron. Subsequently, an optimal system was designed that could also allow for high-definition imaging capabilities with a 1.1 x 1.1 &#956;m pixel size without the requirement of a synchrotron source but rather using a traditional globar IR source5. In this article, we show how to modify an existing commercial FT-IR imaging system to allow for diffraction limited IR imaging of tissues with an acceptable signal to noise ratio using multiple IR objectives (15X, 36X, and 74X). The effective pixel size with the three objectives is 5.5 x 5.5 &#956;m (15X), 2.2 x 2.2 &#956;m (36X) and 1.1 x 1.1 &#956;m (74X). We then give some examples of the importance of the gains in spatial resolution for disease detection in liver and kidney biopsies27.

<table border="0" cellpadding="0" cellspacing="0" width="1102">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Cary 600 Series FT-IR system</td>
			<td style="width:308px;">Agilent</td>
			<td style="width:192px;">Multiple configurations&#160;</td>
			<td style="width:267px;">Alternate FT-IR imaging systems exist</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Adjustable ReflX Objective 74X/0.65NA IR</td>
			<td style="width:308px;">Edmund Optics</td>
			<td style="width:192px;">66-592</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Adjustable ReflX Objective 36X/0.5NA IR</td>
			<td style="width:308px;">Edmund Optics</td>
			<td style="width:192px;">66-586</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">MirrIR slide</td>
			<td style="width:308px;">Kevley Technologies</td>
			<td style="width:192px;">CFR</td>
			<td>For FT-IR reflection-mode measurements</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Barium Fluoride slides</td>
			<td style="width:308px;">International Crystal Laboratories</td>
			<td style="width:192px;">Multiple sizes</td>
			<td>For FT-IR transmission-mode measurements</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Calcium Fluoride slides</td>
			<td style="width:308px;">International Crystal Laboratories</td>
			<td style="width:192px;">Multiple sizes</td>
			<td>For FT-IR transmission-mode measurements</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Dry Nitrogen/Dry Air gas</td>
			<td style="width:308px;">Multiple gas suppliers</td>
			<td style="width:192px;">Multiple sizes</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Hexane</td>
			<td style="width:308px;">Sigma Aldrich</td>
			<td style="width:192px;">Multiple sizes</td>
			<td>For deparafinizing tissue</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">Liquid Nitrogen</td>
			<td style="width:308px;">Multiple cryogenic liquid suppliers</td>
			<td style="width:192px;">Multiple sizes</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:336px;">ENVI-IDL software</td>
			<td style="width:308px;">Exelis-Vis</td>
			<td style="width:192px;"></td>
			<td>Other software packages available</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:336px;">Whole slide Imager</td>
			<td style="width:308px;">Scanscope (Aperio) or Nanozoomer (Hamamatsu)</td>
			<td style="width:192px;"></td>
			<td>To image stained slides</td>
		</tr>
	</tbody>
</table>

high-definition fourier transform infrared (ft-ir) spectroscopic imaging of human tissue sections towards improving pathology

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.

FT-IR imaging allows for the derivation of IR images of tissue that can give different contrasts depending on the IR frequency of interest. In addition, in an IR image, every pixel comprises of the entire IR spectrum, with different peaks corresponding to different biomolecules which can give information about the biochemical properties of cell types or disease states (Figure 1). Here, we have shown how to compare spectral signatures between classes, however more advanced automated classification is possible using additional algorithms3,43-50, such as Bayesian classification, Random Forests, Artificial Neural Networks, and Hierarchal Cluster Analysis can be performed on the data. Supervised classification approaches will allow for the construction of a classifier that can be trained to allow for automated recognition of cell types or disease states. Unsupervised classification approaches can be used to look for naturally occurring differences in tissue or cells due to biochemical variance.
FT-IR instrumentation has evolved over the past few decades, from measuring in a single point/mapping mode using IR opaque apertures to imaging mode using Cassegrain objectives, using either an illuminating objective coupled with a collecting objective in transmission-mode or a single objective that both illuminates and collects in reflection-mode (Figure 2). It was recently demonstrated that the collecting objective in transmission mode could be switched out for a higher magnification and numerical aperture objective to allow for diffraction limited IR imaging, that leads to substantial increases in the spatial resolution of collected IR images4,5. The advances in spatial resolution for tissue imaging have been of critical importance as we can now identify cell types and tissue structures, for example the functional units of the kidney, the glomeruli, using adapted in-house FT-IR systems (Figure 3).
High-definition FT-IR imaging allows for detailed images of tissues to be examined to identify abnormal regions and to identify biochemical differences between different cell types. In a liver tissue core, it is possible to visualize hepatocytes and regions of infiltrating fibrosis that divides two distinct areas of dysplasia and non-dysplastic cirrhosis (Figure 4). We are working to exploit this towards making automated diagnostic tools for use in difficult cases of liver disease.
Importantly, the increased spatial resolution can now allow us to isolate specific structural features that may be chemically modified by disease before histological changes are apparent. For example, we are focused on identifying biochemical changes in kidney glomerular structures such as the Bowman&#8217;s capsule, mesangium, glomerular basement membrane and tubular basement membrane, before changes identified by the pathologist can be observed (Figure 5). In particular, we are interested in identifying changes associated with the progression of diabetic nephropathy and chronic rejection in transplant patients, where current techniques fail to identify changes in an early enough fashion for successful intervention.
<img alt="Figure 1" src="/files/ftp_upload/52332/52332fig1.jpg" /> 
Figure 1. FT-IR images and spectrum from a liver core. Image of (A) H&#38;E stained core from liver biopsy and images of IR absorbance of serial section of the same core at (B) 3,286 cm-1 and (C) 2,603 cm-1, which highlighted different structural features. (D) Typical IR spectrum of tissue, with important peaks labeled. Scale bar = 100 &#956;m. <a href="https://www.jove.com/files/ftp_upload/52332/52332fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/52332/52332fig2.jpg" /> 
Figure 2. Optics schematic detailing FT-IR microscope operation modes.&#160;(A) In transmission mode, the sample is illuminated through the bottom objective, and the light passing through the sample is collected by the top objective. (B) In reflection mode, the top objective serves both to illuminate the sample and to collect the reflected light. The bottom objective is not used. <a href="https://www.jove.com/files/ftp_upload/52332/52332fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/52332/52332fig3.jpg" /> 
Figure 3. Comparison of different microscope objectives on FT-IR images of a kidney glomerulus at 2,925 cm-1. (A) 15X collecting objective with NA = 0.5 (5.5 x 5.5 &#181;m pixel size). (B) 36X collecting objective with NA = 0.5 (2.2 x 2.2 &#181;m pixel size). (C) 74X collecting objective with NA = 0.65 (1.1 x 1.1 &#181;m pixel size). Scale bar = 50 &#956;m. <a href="https://www.jove.com/files/ftp_upload/52332/52332fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/52332/52332fig4.jpg" /> 
Figure 4. Spectral differences between fibrosis and hepatocytes in a liver core. (A) H&#38;E stained core from liver biopsy. (B) Image of a serial section core scanned in FT-IR (36X objective setup). (C) Representative spectra of hepatocytes and fibrosis, taken from regions of tissue indicated by arrows in (A) and (B). Scale bar = 100 &#956;m. <a href="https://www.jove.com/files/ftp_upload/52332/52332fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/52332/52332fig5.jpg" /> 
Figure 5. Differentiation of kidney tissue biopsy features through the use of high-definition FT-IR imaging. (A) Periodic acid-Schiff stained section with the features to be extracted labeled. (B) High-definition FT-IR image of the CH2 asymmetric stretching region (36X objective setup) of a serial section of the same tissue. (C) Features labeled in (A) extracted using the FT-IR image in (B) to be able to chemically differentiate the four features of the tissue. Scale bar = 50 &#956;m. <a href="https://www.jove.com/files/ftp_upload/52332/52332fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology at JoVE.com

High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Fourier Transform Infrared (FT-IR) spectroscopic imaging is a fast and label-free approach to obtain biochemical data sets of cells and tissues. Here, we demonstrate how to obtain high-definition FT-IR images of tissue sections towards improving disease diagnosis.

High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated ...

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33.0K Views.  University of Illinois at Chicago. Fourier Transform Infrared (FT-IR) spectroscopic imaging is a fast and label-free approach to obtain biochemical data sets of cells and tissues. Here, we demonstrate how to obtain high-definition FT-IR images of tissue sections towards improving disease diagnosis. 

Video: High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS)

High-definition transcranial direct current stimulation (HD-tDCS) has recently been developed as a noninvasive brain stimulation approach that increases the accuracy of current delivery to the brain by using arrays of smaller "high-definition" electrodes, instead of the larger pad-electrodes of conventional tDCS. Targeting is achieved by energizing electrodes placed in predetermined configurations. One of these is the 4x1-ring configuration. In this approach, a center ring electrode (anode or cathode) overlying the target cortical region is surrounded by four return electrodes, which help circumscribe the area of stimulation. Delivery of 4x1-ring HD-tDCS is capable of inducing significant neurophysiological and clinical effects in both healthy subjects and patients. Furthermore, its tolerability is supported by studies using intensities as high as 2.0 milliamperes for up to twenty minutes.
Even though 4x1 HD-tDCS is simple to perform, correct electrode positioning is important in order to accurately stimulate target cortical regions and exert its neuromodulatory effects. The use of electrodes and hardware that have specifically been tested for HD-tDCS is critical for safety and tolerability. Given that most published studies on 4x1 HD-tDCS have targeted the primary motor cortex (M1), particularly for pain-related outcomes, the purpose of this article is to systematically describe its use for M1 stimulation, as well as the considerations to be taken for safe and effective stimulation. However, the methods outlined here can be adapted for other HD-tDCS configurations and cortical targets.

Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation HD-tDCS

High-definition transcranial direct current stimulation (HD-tDCS), with its 4x1-ring montage, is a noninvasive brain stimulation technique that combines both the neuromodulatory effects of conventional tDCS with increased focality. This article provides a systematic demonstration of the use of 4x1 HD-tDCS, and the considerations needed for safe and effective stimulation.

High-definition transcranial direct current stimulation (HD-tDCS) has recently been developed as a noninvasive brain stimulation approach that increases ...

Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery

Inaccuracies in intraoperative tumor localization and evaluation of surgical margin status result in suboptimal outcome of breast-conserving surgery (BCS). Optical imaging, in particular near-infrared fluorescence (NIRF) imaging, might reduce the frequency of positive surgical margins following BCS by providing the surgeon with a tool for pre- and intraoperative tumor localization in real-time. In the current study, the potential of NIRF-guided BCS is evaluated using tissue-simulating breast phantoms for reasons of standardization and training purposes.
Breast phantoms with optical characteristics comparable to those of normal breast tissue were used to simulate breast conserving surgery. Tumor-simulating inclusions containing the fluorescent dye indocyanine green (ICG) were incorporated in the phantoms at predefined locations and imaged for pre- and intraoperative tumor localization, real-time NIRF-guided tumor resection, NIRF-guided evaluation on the extent of surgery, and postoperative assessment of surgical margins. A customized NIRF camera was used as a clinical prototype for imaging purposes.
Breast phantoms containing tumor-simulating inclusions offer a simple, inexpensive, and versatile tool to simulate and evaluate intraoperative tumor imaging. The gelatinous phantoms have elastic properties similar to human tissue and can be cut using conventional surgical instruments. Moreover, the phantoms contain hemoglobin and intralipid for mimicking absorption and scattering of photons, respectively, creating uniform optical properties similar to human breast tissue. The main drawback of NIRF imaging is the limited penetration depth of photons when propagating through tissue, which hinders (noninvasive) imaging of deep-seated tumors with epi-illumination strategies.

Near-infrared fluorescence (NIRF) imaging may improve therapeutic outcome of breast cancer surgery by enabling intraoperative tumor localization and evaluation of surgical margin status. Using tissue-simulating breast phantoms containing fluorescent tumor-simulating inclusions, potential clinical applications of NIRF imaging in breast cancer patients can be assessed for standardization and training purposes.

Inaccuracies in intraoperative tumor localization and evaluation of surgical margin status result in suboptimal outcome of breast-conserving surgery ...

Cerenkov Luminescence Imaging of Interscapular Brown Adipose Tissue

Brown adipose tissue (BAT), widely known as a &#8220;good fat&#8221; plays pivotal roles for thermogenesis in mammals. This special tissue is closely related to metabolism and energy expenditure, and its dysfunction is one important contributor for obesity and diabetes. Contrary to previous belief, recent PET/CT imaging studies indicated the BAT depots are still present in human adults. PET imaging clearly shows that BAT has considerably high uptake of 18F-FDG under certain conditions. In this video report, we demonstrate that Cerenkov luminescence imaging (CLI) with 18F-FDG can be used to optically image BAT in small animals. BAT activation is observed after intraperitoneal injection of norepinephrine (NE) and cold treatment, and depression of BAT is induced by long anesthesia. Using multiple-filter Cerenkov luminescence imaging, spectral unmixing and 3D imaging reconstruction are demonstrated. Our results suggest that CLI with 18F-FDG is a practical technique for imaging BAT in small animals, and this technique can be used as a cheap, fast, and alternative imaging tool for BAT research.

In this video report, we show the application of Cerenkov Luminescence Imaging (CLI) for interscapular brown adipose tissue in mice under activated and depressed conditions.

Brown adipose tissue (BAT), widely known as a &#8220;good fat&#8221; plays pivotal roles for thermogenesis in mammals. This special tissue is closely ...

Working with Human Tissues for Translational Cancer Research

Medical research for human benefit is greatly impeded by the necessity for human tissues and subjects. However, upon obtaining consent for human specimens, precious samples must be handled with the greatest care in order to ensure integrity of organs, tissues, and cells to the highest degree. Unfortunately, tissue processing by definition requires extraction of tissues from the host, a change which can cause great cellular stress and have major repercussions on subsequent analyses. These stresses could result in the specimen being no longer representative of the site from which it was retrieved. Therefore, a strict protocol must be adhered to while processing these specimens to ensure representativeness. The desired assay(s) must also be taken into consideration in order to ensure that an optimal technique is used for sample processing. Outlined here is a protocol for tissue retrieval, processing and various analyses which may be performed on processed tissue in order to maximize downstream production from limited tissue samples.

Translational cancer research is dependent on extraction of human tissues. Much work has gone into optimizing extraction methods for ex vivo analysis. Here, we describe tissue processing methods allowing for maximal data output from limited samples.

Medical research for human benefit is greatly impeded by the necessity for human tissues and subjects. However, upon obtaining consent for human ...

Combined Near-infrared Fluorescent Imaging and Micro-computed Tomography for Directly Visualizing Cerebral Thromboemboli

Direct thrombus imaging visualizes the root cause of thromboembolic infarction. Being able to image thrombus directly allows far better investigation of stroke than relying on indirect measurements, and will be a potent and robust vascular research tool. We use an optical imaging approach that labels thrombi with a molecular imaging thrombus marker&#160;&#8212; a Cy5.5 near-infrared fluorescent (NIRF) probe that is covalently linked to the fibrin strands of the thrombus by the fibrin-crosslinking enzymatic action of activated coagulation factor XIIIa during the process of clot maturation. A micro-computed tomography (microCT)-based approach uses thrombus-seeking gold nanoparticles (AuNPs) functionalized to target the major component of the clot: fibrin. This paper describes a detailed protocol for the combined in vivo microCT and ex vivo NIRF imaging of thromboemboli in a mouse model of embolic stroke. We show that in vivo microCT and fibrin-targeted glycol-chitosan AuNPs (fib-GC-AuNPs) can be used for visualizing both in situ thrombi and cerebral embolic thrombi. We also describe the use of in vivo microCT-based direct thrombus imaging to serially monitor the therapeutic effects of tissue plasminogen activator-mediated thrombolysis. After the last imaging session, we demonstrate by ex vivo NIRF imaging the extent and the distribution of residual thromboemboli in the brain. Finally, we describe quantitative image analyses of microCT and NIRF imaging data. The combined technique of direct thrombus imaging allows two independent methods of thrombus visualization to be compared: the area of thrombus-related fluorescent signal on ex vivo NIRF imaging vs. the volume of hyperdense microCT thrombi in vivo.

This protocol describes the application of combined near-infrared fluorescent (NIRF) imaging and micro-computed tomography (microCT) for visualizing cerebral thromboemboli. This technique allows the quantification of thrombus burden and evolution. The NIRF imaging technique visualizes fluorescently labeled thrombus in excised brain, while the microCT technique visualizes thrombus inside living animals using gold-nanoparticles.

Direct thrombus imaging visualizes the root cause of thromboembolic infarction. Being able to image thrombus directly allows far better investigation of ...

3D Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue

The developmental goal of 3D ultrasound imaging (3DUS) is to engineer a modality to perform 3D morphological ultrasound analysis of human muscles. 3DUS images are constructed from calibrated freehand 2D B-mode ultrasound images, which are positioned into a voxel array. Ultrasound (US) imaging allows quantification of muscle size, fascicle length, and angle of pennation. These morphological variables are important determinants of muscle force and length range of force exertion. The presented protocol describes an approach to determine volume and fascicle length of m.&#160;vastus lateralis and m.&#160;gastrocnemius medialis. 3DUS facilitates standardization using 3D anatomical references. This approach provides a fast and cost-effective approach for quantifying 3D morphology in skeletal muscles. In healthcare and sports, information on the morphometry of muscles is very valuable in diagnostics and/or follow-up evaluations after treatment or training.

3D ultrasound imaging (3DUS) allows fast and cost-effective morphometry of musculoskeletal tissues. We present a protocol to measure muscle volume and fascicle length using 3DUS.

The developmental goal of 3D ultrasound imaging (3DUS) is to engineer a modality to perform 3D morphological ultrasound analysis of human muscles. 3DUS ...

Skeletal Muscle Neurovascular Coupling, Oxidative Capacity, and Microvascular Function with 'One Stop Shop' Near-infrared Spectroscopy

Exercise represents a major hemodynamic stress that demands a highly coordinated neurovascular response in order to match oxygen delivery to metabolic demand. Reactive hyperemia (in response to a brief period of tissue ischemia) is an independent predictor of cardiovascular events and provides important insight into vascular health and vasodilatory capacity. Skeletal muscle oxidative capacity is equally important in health and disease, as it determines the energy supply for myocellular processes. Here, we describe a simple, non-invasive approach using near-infrared spectroscopy to assess each of these major clinical endpoints (reactive hyperemia, neurovascular coupling, and muscle oxidative capacity) during a single clinic or laboratory visit. Unlike Doppler ultrasound, magnetic resonance images/spectroscopy, or invasive catheter-based flow measurements or muscle biopsies, our approach is less operator-dependent, low-cost, and completely non-invasive. Representative data from our lab taken together with summary data from previously published literature illustrate the utility of each of these end-points. Once this technique is mastered, application to clinical populations will provide important mechanistic insight into exercise intolerance and cardiovascular dysfunction.

Skeletal Muscle Neurovascular Coupling, Oxidative Capacity, and Microvascular Function with &#039;One Stop Shop&#039; Near-infrared Spectroscopy

Here, we describe a simple, non-invasive approach using near-infrared spectroscopy to assess reactive hyperemia, neurovascular coupling and skeletal muscle oxidative capacity in a single clinic or laboratory visit.

Exercise represents a major hemodynamic stress that demands a highly coordinated neurovascular response in order to match oxygen delivery to metabolic ...

Characterization of Immune Cells in Human Adipose Tissue by Using Flow Cytometry

Infiltration of immune cells in the subcutaneous and visceral adipose tissue (AT) deposits leads to a low-grade inflammation contributing to the development of obesity-associated complications such as type 2 diabetes. To quantitatively and qualitatively investigate the immune cell subsets in human AT deposits, we have developed a flow cytometry approach. The stromal vascular fraction (SVF), containing the immune cells, is isolated from subcutaneous and visceral AT biopsies by collagenase digestion. Adipocytes are removed after centrifugation. The SVF cells are stained for multiple membrane-bound markers selected to differentiate between immune cell subsets and analyzed using flow cytometry. As a result of this approach, pro- and anti-inflammatory macrophage subsets, dendritic cells (DCs), B-cells, CD4+ and CD8+ T-cells, and NK cells can be detected and quantified. This method gives detailed information about immune cells in AT and the amount of each specific subset. Since there are numerous fluorescent antibodies available, our flow cytometry approach can be adjusted to measure various other cellular and intracellular markers of interest.

This article describes a method to analyze immune cell content of adipose tissue by isolation of immune cells from adipose tissue and subsequent analysis using flow cytometry.

Infiltration of immune cells in the subcutaneous and visceral adipose tissue (AT) deposits leads to a low-grade inflammation contributing to the ...

Nanoscopic Imaging of Human Tissue Sections via Physical and Isotropic Expansion

In modern pathology, optical microscopy plays an important role in disease diagnosis by revealing microscopic structures of clinical specimens. However, the fundamental physical diffraction limit prevents interrogation of nanoscale anatomy and subtle pathological changes when using conventional optical imaging approaches. Here, we describe a simple and inexpensive protocol, called expansion pathology (ExPath), for nanoscale optical imaging of common types of clinical primary tissue specimens, including both fixed-frozen or formalin-fixed paraffin embedded (FFPE) tissue sections. This method circumvents the optical diffraction limit by chemically transforming the tissue samples into tissue-hydrogel hybrid and physically expanding them isotropically across multiple scales in pure water. Due to expansion, previously unresolvable molecules are separated and thus can be observed using a conventional optical microscope.

Nanoscale imaging of clinical tissue samples can improve understanding of disease pathogenesis. Expansion pathology (ExPath) is a version of expansion microscopy (ExM), modified for compatibility with standard clinical tissue samples, to explore the nanoscale configuration of biomolecules using conventional diffraction limited microscopes.

In modern pathology, optical microscopy plays an important role in disease diagnosis by revealing microscopic structures of clinical specimens. However, ...

DIPLOMA Approach for Standardized Pathology Assessment of Distal Pancreatectomy Specimens

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant cancers. A minority (20%) of PDACs are found in the pancreatic body and tail. Accurate pathology assessment of the pancreatic specimen is essential for providing prognostic information and it may guide further treatment strategies. The recent 8th edition of the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) staging system for pancreatic tumors has incorporated significant changes to tumor (pT) stage, which is predominantly based on tumor size. This change emphasizes the importance of careful block selection. Owing to the greater prevalence of tumors in the head of the pancreas, efforts are made to standardize the assessment of pancreatoduodenectomy specimens. However, consensus regarding the macroscopic assessment of distal (i.e., left) pancreatectomy specimens is lacking. The DIPLOMA approach includes the standardized measurement of pancreas and other resected organs, inking of relevant surgical margins and anatomical surfaces without removing covering layers of fat, measurement of tumor size (for T-stage), together with assessment of splenic vessel involvement (and other organs if present). All relevant margins are assessed, and relevant blocks are selected to confirm these parameters microscopically. The current protocol describes a standardized approach to the macroscopic assessment of distal pancreatectomy specimens. This approach was developed during several meetings with pathologists and surgeons during the preparation phase for an international multicenter trial (DIPLOMA, ISRCTN44897265), which focuses on radicality of distal pancreatectomy for pancreatic ductal adenocarcinoma. This standardized approach can be instrumental in the design of studies and will uniform reporting on the outcomes of distal pancreatectomy. The described technique is used in the DIPLOMA trial for pancreatic ductal adenocarcinoma but may also be useful for other indications.

The current study highlights a standardized approach to the macroscopic assessment of distal pancreatectomy specimens for pancreatic ductal adenocarcinoma, with special emphasis on the measurement of pancreatic dimensions and those of other organs, inking of margins, measurement of tumor size and proximity to margins, lymph node sampling and block selection.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant cancers. A minority (20%) of PDACs are found in the pancreatic body and tail. ...