Histopathological Image Analysis: A Review <s> C. Spectroscopic Imaging Modalities for Histopathology <s> Summary and Conclusions Infrared absorption curves in the region 1–15 µ for typical normal tissues, neoplastic tissues, and important constituents of tissues have been determined. These data have been analyzed to ascertain the relationship between the absorption bands and sample composition. The following conclusions have been drawn: ::: 1.The infrared absorption pattern of ribo- and desoxyribonucleic acids consisting of the 8.1, 9.35, and 10.3 µ bands is due mainly to the pentose and phosphoric acid components. 2.RNA and DNA are present in many tissues in sufficient concentrations to cause appreciable absorption in the region 8–11 µ. 3.The absorption pattern of mouse liver and tumor nuclei, and of many tissues both neoplastic and normal, strongly resembles that for DNA and RNA in the region 8–11 µ. 4.Absorption intensities at approximately 8.1, 9.3, and 10.3 µ can be correlated with the concentrations of nucleic acids in tissues. 5.Highly cellular neoplastic and normal tissues rich in nucleic acids produce strong and characteristic absorption in the 8–11-µ region, while muscular tissue generally displays less pronounced absorption bands. Mouse brain appears to be an exception, but further study may account for the discrepancy. 6.The absorption pattern for tissues in the 8–11-µ region is subject to many sources of interference. Carbohydrates, such as gluclose, and many phosphoric compounds have intense bands in this region. Fats and proteins such as occur in whole blood, blood serum, and erythrocytes absorb in this region, but the absorptions are not very pronounced. <s> BIB001 </s> Histopathological Image Analysis: A Review <s> C. Spectroscopic Imaging Modalities for Histopathology <s> Accurate diagnosis is essential for optimum management and treatment of patients with brain tumours. Proton magnetic resonance spectroscopy (1H MRS) provides information non-invasively on tumour biochemistry and has been shown to provide important additional information to that obtained by conventional radiology. We review the current status of 1H MRS in classifying brain tumour type and grade, for monitoring response to therapy and progression to higher grade, and as a molecular imaging technique for determining tumour extent for treatment planning. Copyright © 2003 John Wiley & Sons, Ltd. <s> BIB002 </s> Histopathological Image Analysis: A Review <s> C. Spectroscopic Imaging Modalities for Histopathology <s> 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. <s> BIB003 </s> Histopathological Image Analysis: A Review <s> C. Spectroscopic Imaging Modalities for Histopathology <s> RATIONALE AND OBJECTIVES ::: Quality Assessment of Diagnostic Accuracy Studies (QUADAS) is a new tool to measure the methodological quality of diagnostic accuracy studies in systematic reviews. We used data from a systematic review of magnetic resonance spectroscopy (MRS) in the characterization of suspected brain tumors to provide a preliminary evaluation of the inter-rater reliability of QUADAS. ::: ::: ::: MATERIALS AND METHODS ::: A structured literature search identified 19 diagnostic accuracy studies. These publications were distributed randomly to primary and secondary reviewers for dual independent assessment. Reviewers recorded methodological quality by using QUADAS on a custom-designed spreadsheet. We calculated correlation, percentage of agreement, and kappa statistic to assess inter-rater reliability. ::: ::: ::: RESULTS ::: Most studies in our review were judged to have used an accurate reference standard. Conversely, the MRS literature frequently failed to specify the length of time between index and reference tests or that the clinicians were unaware of the index test findings when reporting the reference standard. There was good correlation (rho = 0.78) between reviewers in assessment of the overall number of quality criteria met. However, mean agreement for individual QUADAS questions was only fair (kappa = 0.22) and ranged from no agreement beyond chance (kappa < 0) to moderate agreement (kappa = 0.58). ::: ::: ::: CONCLUSION ::: Inter-rater reliability in our study was relatively low. Nevertheless, we believe that QUADAS potentially is a useful tool for highlighting the strengths and weaknesses of existing diagnostic accuracy studies. Low reliability suggests that different reviewers will reach different conclusions if QUADAS is used to exclude "low-quality" articles from meta-analyses. We discuss methods for improving the validity and reliability of QUADAS. <s> BIB004
In recent years, several spectral data acquisition methods have been employed to aid the diagnosis process with additional information about the biochemical makeup of cells and other tissue constituents. Generally, computerized histopathology image analysis takes as its input a three-channel (red, green, and blue or RGB) color image captured by digital imaging equipment (normally a CCD camera) and attempts to emulate the manual analysis and/or provide additional quantitative information to aid in the diagnosis. While analysis of ordinary color images has been shown to be useful, one of the major drawbacks is that only three color channels of the light spectrum are used, potentially limiting the amount of information required for characterizing different kinds of tissue constituents. On the other hand, recently proposed immuno-histochemistry (IHC) methods are not sufficiently well developed for their use in quantitative pathology BIB003 . Spectral methods offer a relatively inexpensive way of providing a deeper insight into tissue composition. Most of these methods can be categorized into three broad classes: point spectroscopy, spectral imaging, and spectroscopic imaging. Point spectroscopy is a well-established area of study whereby, in the context of histopathology, the chemical composition of a tissue sample is ascertained with the help of the spectrum emitted or absorbed at a specific point on the biopsy. Point spectroscopy methods can employ both visible light and beyond. Spectral imaging, also known as multispectral or hyperspectral imaging, measures intensity of light from the entire optical field after exciting the sample with visible light of varying wavelengths. Spectroscopic imaging combines the strengths of both of the above two methods, building spatial imaging of the human tissue in a multitude of wavelength regimes. 1) Point Spectroscopy: Vibrational spectroscopy is the most widely researched point spectroscopy method for characterization of normal and diseased tissue. It measures molecular vibrations, induced by incident light, corresponding to the chemical makeup at the molecular level in two different ways: absorption of electromagnetic radiation or frequency shifts between incident and scattered light-the so-called Raman scattering effect. In case of infrared (IR) absorption spectroscopy, the sample is irradiated with a mid-IR beam and the transmitted light is examined for absorption of energy. The absorption spectrum, a plot of absorption versus different wavelengths, can reveal the biochemical makeup of the molecules. IR spectroscopy has been used to analyze tissue constituents at a molecular level for almost 60 years  ,  . Indeed, IR spectra was investigated for characterization of normal and neoplastic tissue as far back as 1952 by Woernley BIB001 , who also showed that the absorption at certain frequencies can be correlated with the concentrations of nucleic acids in tissues. Recent advances in machine learning and pattern recognition algorithms and the development of the IR spectroscopic imaging modality have renewed interest in this technique for studying the biochemical makeup of healthy and diseased tissue. In Raman spectroscopy, the sample is illuminated with a monochromatic visible or near-IR (NIR) light from a laser source and frequency shifts in the scattered light are measured. The Raman spectrum is a plot of intensity of the scattered photon versus shifts in its frequency, often measured in terms of wave numbers in cm . NIR-Raman spectroscopy is often used as an alternative to IR spectroscopy since NIR light has higher energy than mid-IR light and can penetrate much farther into the sample. Fourier-transform (FT) spectroscopy, known as FT-IR when IR light is used, allows a faster acquisition of the IR spectra by using an interferometer followed by the Fourier transform (FT). FT-IR spectroscopy is the most commonly used form of IR spectroscopy. 2) Spectral Imaging: Spectral imaging is carried out by building an image cube with slices corresponding to images of the same scene obtained by incident light at differing wavelengths. This technique is referred to as multispectral (MS) or hyperspectral (HS) imaging depending on the number of spectral bands, individual slices of the image cube in the spectral direction (generally with for MS and for HS). 3) Spectroscopic Imaging: Spectroscopic imaging is similar to spectral imaging in that a volumetric cube is obtained with a spectrum per pixel in the optical field. The main difference is that spectroscopic imaging builds the image cube by dividing the image scene into a uniform Cartesian grid, raster scanning the scene according to the grid, and collecting point spectra for each of the grid points. Fernandez et al. BIB003 have proposed an IR spectroscopic imaging method based on a Michelson interferometer and all-reflecting microscope equipped with a 16-element linear array detector with a narrow aperture size of 6.25 6.25 m. A massive 1641-dimensional point spectrum was obtained for each pixel spanning a spectral range of 4000-720 cm at an effective spectral resolution of 2 cm and at a spatial resolution of 6.25 m. Tissue sections were also stained with H&E and imaged with a digital light microscope for manual histopathology analysis. While most of the above methods are generally invasive for internal body organs, magnetic resonance spectroscopy (MRS) is a completely noninvasive way of probing the biochemical makeup of tissue. By this virtue, it is a particularly attractive prospect for the imaging of brain tumors, along with magnetic resonance (MR) imaging which has become a mainstay in the diagnosis of suspicious brain lesions BIB004 . The main principle behind MRS imaging is the chemical shift process, the process whereby different metabolites in the tissue respond at different resonating frequencies, with the chemical shift often measured in parts per million (ppm). One particular advantage of MRS is that it can be tuned to specific nuclei in the tissue; with hydrogen ( , also known as proton) being the most commonly studied one. Studies have shown clear differences between MRS spectra of brain tumors and normal brain BIB002 .