Fourier transform infrared spectromicroscopy and hierarchical cluster analysis of human meningiomas

Abstract

Abstract. Limitations of conventional light microscopy in pathological diagnosis of brain tumors include subjective bias in interpretation and discordance of nomenclature. A study using mid-infrared (IR) spectromicroscopy was undertaken to determine whether meningiomas, a group of brain tumors prone to recurrence, could be identified by the unique spectral 'fingerprints' of their chemical composition. Paired, thin (5-μm) cryosections of snap-frozen human meningioma tumor samples removed at elective surgery were mounted on glass (hematoxylin and eosin-stained tissue section) and infrared (unstained tissue section) reflectance slides, respectively. Concordance of the tumor-bearing areas identified in the stained section by a pathologist with the unstained IR tissue section was ensured using a novel digital grid and tumor-mapping system developed in our laboratory. Compared with the normal control, tumor samples from four meningioma patients revealed a marked decrease in bands associated with unsaturated fatty acids, particularly in the bands at 3010, 2920, 2850, and 1735 cm -1 . Spectral datasets were subjected to hierarchical cluster analyses (HCA) using Ward's algorithm for comparison and grouping of similar data groups, and were converted into color-coded digital maps for matching spectra with their respective clusters. False color images of 5 and 6 clusters obtained by HCA identified dominant clusters corresponding to tumor tissue. Corroboration of these findings in a larger number of meningiomas may allow for more precise identification of these and other types of brain tumors.

FTIR Imaging of Tissues: Techniques and Methods of Analysis

“…It should be noted that various multivariate approaches have been employed for sensitive and selective classification of the grade and origin of brain tumours, i.e. uhCA [120,122], K-means [118,121,123], SImCA (Soft Independent modeling of Class Analogy) [119,123], PCA [123,125], LdA [116][117][118]124] and their combinations. In this section, we introduce the reader to the results of FtIR imaging of the brain tissue in neurodegenerative disorders such as Alzheimer's and Parkinson diseases, multiple sclerosis and others, for which the etiology or clinical diagnosis have not been clearly revealed, and are still the subject of intensive investigations.…”

Identification of Skin Electrical Injury Using Infrared Imaging: A Possible Complementary Tool for Histological Examination

“…Second derivative transformation is a common method of resolving overlapping bands, where the negative peaks are directly aligned to the center peak of non-derivative spectrum. In this study, this pre-processing method was used to identify several peaks from C = O stretching of various protein structures, which were included within the Amide I region[18–20]. Fig 2C illustrates superimposition of second derivative spectra between control and electrical mark groups.…”

Chemical Analysis in the Corpus Callosum Following Traumatic Axonal Injury using Fourier Transform Infrared Microspectroscopy: A Pilot Study

“…As conformation‐related protein absorption bands usually exist in obscure peak shoulders in the amide I band, secondary derivative spectra and curve‐fitting analysis, respectively, were used to identify and quantify them. After conversion of the original spectra into the secondary derivative spectra within the region of the amide I band, four protein conformation‐related peaks were determined in both the injured and control group: β‐sheet structure was fixed at around 1625 cm −1 , α‐helix structure was fixed at around 1654 cm −1 ; β‐turn structure was fixed at around 1680 cm −1 , and antiparallel β‐sheet structure was fixed at around 1694 cm −1 (Fig. a ).…”