Label-free Identification of Antibody-mediated Rejection in Cardiac Allograft Biopsies Using Infrared Spectroscopic Imaging.

BACKGROUND: Antibody-mediated rejection (AMR) in cardiac allograft recipients remains less well-understood than acute cellular rejection, is associated with worse outcomes, and portends a greater risk of developing chronic allograft vasculopathy. Diffuse immunohistochemical C4d staining of capillary endothelia in formalin-fixed, paraffin-embedded right ventricular endomyocardial biopsies is diagnostic of immunopathologic AMR but serves more as a late-stage marker. Infrared (IR) spectroscopy may be a useful tool in earlier detection of rejection. We performed mid-IR spectroscopy to identify a unique biochemical signature for AMR. METHODS: A total of 30 posttransplant formalin-fixed paraffin-embedded right ventricular tissue biopsies (14 positive for C4d and 16 negative for C4d) and 14 native heart biopsies were sectioned for IR analysis. Infrared images of entire sections were acquired and regions of interest from cardiomyocytes were identified. Extracted spectra were averaged across many pixels within each region of interest. Principal component analysis coupled with linear discriminant analysis and predictive classifiers were applied to the data. RESULTS: Comparison of averaged mid-IR spectra revealed unique features among C4d-positive, C4d-negative, and native heart biopsies. Principal component analysis coupled with linear discriminant analysis and classification models demonstrated that spectral features from the mid-IR fingerprint region of these 3 groups permitted accurate automated classification into each group. CONCLUSIONS: In cardiac allograft biopsies with immunopathologic AMR, IR spectroscopy reveals a biochemical signature unique to AMR compared with that of nonrejecting cardiac allografts and native hearts. Future study will focus on the predictive capabilities of this IR signature.

Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging.

Renal transplants have not seen a significant improvement in their 10-year graft life. Chronic damage accumulation often leads to interstitial fibrosis and tubular atrophy (IF/TA) and thus graft function loss over time. For this reason, IF/TA has been the chief suspect for a potential prognostic marker for long term outcomes. In this study, we have used infrared spectroscopic (IR) imaging to interrogate the biochemistry of regions of fibrosis from renal transplant biopsies to identify a biochemical signature that can predict rapid progression of fibrosis. IR imaging represents an approach that permits label-free biochemical imaging of human tissues towards identifying novel biomarkers for disease diagnosis or prognosis. Two cohorts were identified as progressors (n = 5, > 50% fibrosis increase between time points) and non-progressors (n = 5, < 5% increase between time points). Each patient had an early time point and late time point biopsy. Collagen associated carbohydrate moieties (ν(C-O), 1035 cm-1 and ν(C-O-C),1079 cm-1) spectral ratios demonstrated good separation between the two cohorts (p = 0.001). This was true for late and early time point biopsies suggesting the regions of fibrosis are biochemically altered in cases undergoing progressive fibrosis. Thus, IR imaging can potentially predict rapid progression of fibrosis using histologically normal early time point biopsies.

Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis.

Infrared spectroscopic tissue imaging is a potentially powerful adjunct tool to current histopathology techniques. By coupling the biochemical signature obtained through infrared spectroscopy to the spatial information offered by microscopy, this technique can selectively analyze the chemical composition of different features of unlabeled, unstained tissue sections. In the past, the tissue features that have received the most interest were parenchymal and epithelial cells, chiefly due to their involvement in dysplasia and progression to carcinoma; however, the field has recently turned its focus toward stroma and areas of fibrotic change. These components of tissue present an untapped source of biochemical information that can shed light on many diverse disease processes, and potentially hold useful predictive markers for these same pathologies. Here we review the recent applications of infrared spectroscopic imaging to stromal and fibrotic regions of diseased tissue, and explore the potential of this technique to advance current capabilities for tissue analysis.

Accounting for tissue heterogeneity in infrared spectroscopic imaging for accurate diagnosis of thyroid carcinoma subtypes.

Fourier transform infrared (FT-IR) microscopy was used to image tissue samples from twenty patients diagnosed with thyroid carcinoma. The spectral data were then used to differentiate between follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma using principle component analysis coupled with linear discriminant analysis and a Naïve Bayesian classifier operating on a set of computed spectral metrics. Classification of patients' disease type was accomplished by using average spectra from a wide region containing follicular cells, colloid, and fibrosis; however, classification of disease state at the pixel level was only possible when the extracted spectra were limited to follicular epithelial cells in the samples, excluding the relatively uninformative areas of fibrosis. The results demonstrate the potential of FT-IR microscopy as a tool to assist in the difficult diagnosis of these subtypes of thyroid cancer, and also highlights the importance of selectively and separately analyzing spectral information from different features of a tissue of interest.

Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease.

The importance of stroma as a rich diagnostic region in tissue biopsies is growing as there is an increasing understanding that disease processes in multiple organs can affect the composition of adjacent connective tissue regions. This may be especially true in the liver, since this organ's central metabolic role exposes it to multiple disease processes. We use quantum cascade laser infrared spectroscopic imaging to study changes in the chemical status of hepatocytes and fibrotic regions of liver tissue that result from the progression of liver cirrhosis to hepatocellular carcinoma and the potentially confounding effects of diabetes mellitus.

A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression.

Routine histology, the current gold standard, involves staining for specific biomolecules. However, untapped biochemical information in tissue can be gathered using biochemical imaging. Infrared spectroscopy is an emerging modality that allows label-free chemical imaging to derive biochemical information (such as protein, lipids, DNA, collagen) from tissues. Here we employed this technology in order to better predict the development of diabetic nephropathy. Using human primary kidney biopsies or nephrectomies, we obtained tissue from 4 histologically normal kidneys, 4 histologically normal kidneys from diabetic subjects, and 5 kidneys with evidence of diabetic nephropathy. A biochemical signature of diabetic nephropathy was derived that enabled prediction of nephropathy based on the ratio of only 2 spectral frequencies. Nonetheless, using the entire spectrum of biochemical information, we were able to detect renal disease with near-perfect accuracy. Additionally, study of sequential protocol biopsies from 3 transplanted kidneys showed biochemical changes even prior to clinical manifestation of diabetic nephropathy. Thus, infrared imaging can identify critical biochemical alterations that precede morphologic changes, potentially allowing for earlier intervention.

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.