A Methodological Approach to the Characterization of Brain Gliomas, by Means of Semi-Automatic Morphometric Analysis

Abstract

The aims of this paper were to present a reliable morphometric procedure for glioma analysis for preliminary prognosis and to develop a semi-automatic procedure that is easy to use. The data presented are important to the extent that they verify the reliability of the results by showing that they are consistent with the findings from more complicated automatic analytical tools. The objects for analysis were digital images of haematoxylineosin stained glioma samples. The overall analysis consisted of digital image analysis and the determination of morphometric parameters. Interestingly, an increase in the mean values of aspect ratio with increasing malignancy grade was found. Moreover, the morphometric parameters in relation to the histological origin of gliomas were examined and it was found that, the cellular nuclei of glioblastoma multiforme reveal the biggest mean values of aspect ratio compared with other gliomas.

The combination of artificial neural networks and synchrotron radiation-based infrared micro-spectroscopy for a study on the protein composition of human glial tumors

“…Hence, our study suggests that it is probable that modifications in protein secondary structure, which were shown to be correlated with a malignancy grade, could be a useful marker of tumors' clinical aggressiveness. It could directly reflect increased cellularity and mitotic activity of glial-derived neoplastic cells, all of which were suggested in our previous morphometric studies on brain gliomas [55] . In turn, by using the LDA to discriminate different types of gliomas, we were capable to show whether protein-related information could be a useful marker to distinguish glial tumors with respect to either their histological type or origin.…”

“…It could directly reflect the increased cellularity and mitotic activity of glial-derived neoplastic cells, all of which were suggested in our previous morphometric studies on brain gliomas. 55 In turn, by using the LDA to distinguish between different types of gliomas, we were able to show whether protein-related information could be a useful marker to distinguish between glial tumors with respect to either their histological type or origin. In fact, among all the classifications used, the most conspicuous differences are noted when gliomas are divided according to either their histological origin (OLIGO, ASTROsee Fig.…”

Identification of Histological Correlates of Overall Survival in Lower Grade Gliomas Using a Bag-of-words Paradigm: A Preliminary Analysis Based on Hematoxylin & Eosin Stained Slides from the Lower Grade Glioma Cohort of The Cancer Genome Atlas

“…[14] Therefore, morphological features that capture this information have been explored in the classification of this disease. [1516] The availability of public domain Hematoxylin & Eosin (H and E) slide data from efforts such as the TCGA permits the use of such data for the inference of data-derived phenotypic characteristics that might serve to complement the molecular markers for the diagnosis and prognosis of disease. Indeed, an integrated phenotypic-genotypic classification systems are now being implemented to increase the prognostic value of the classifications.…”