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Project: ProstataCA2
Published year: 20122
Classifying prostate cancer malignancy by quantitative histomorphometry.
ProstataCA

Abstract (Expand)

PURPOSE: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is … difficult to standardize and often leads to discussion due to interrater and intrarater disagreement. Thus, we investigated whether digital image based automated quantitative histomorphometry could be used to achieve a more standardized, reproducible classification outcome. MATERIALS AND METHODS: In a proof of principle study we developed a method to evaluate digitized histological images of single prostate cancer regions in hematoxylin and eosin stained sections. Preprocessed color images were subjected to color deconvolution, followed by the binarization of obtained hematoxylin related image channels. Highlighted neoplastic epithelial gland related objects were morphometrically assessed by a classifier based on 2 calculated quantitative and objective geometric measures, that is inverse solidity and inverse compactness. The procedure was then applied to the prostate cancer probes of 125 patients. Each probe was independently classified for Gleason grade 3, 4 or 5 by an experienced pathologist blinded to image analysis outcome. RESULTS: Together inverse compactness and inverse solidity were adequate discriminatory features for a powerful classifier that distinguished Gleason grade 3 from grade 4/5 histology. The classifier was robust on sensitivity analysis. CONCLUSIONS: Results suggest that quantitative and interpretable measures can be obtained from image based analysis, permitting algorithmic differentiation of prostate Gleason grades. The method must be validated in a large independent series of specimens.

Authors: M. Loeffler, L. Greulich, P. Scheibe, P. Kahl, Z. Shaikhibrahim, U. D. Braumann, J. P. Kuska, N. Wernert

Date Published: 20th Mar 2012

Publication Type: Not specified

Human Diseases: prostate cancer

Suitability of infrared microspectroscopic imaging for histopathology of the uterine cervix.
ProstataCA

Abstract (Expand)

AIMS: Infrared microspectroscopy (IR-MSP) has been proposed for automated histological tissue differentiation of unstained specimens based on chemical analysis of cell and extracellular constituents. … This study aimed to determine the accuracy of IR-MSP-based histopathology of cervical carcinoma sections with complex tissue architecture under practically relevant testing conditions. METHODS AND RESULTS: In total, 46 regions of interest, covering an area of almost 50 mm(2) on sections derived from paraffin-embedded tissue of radical hysterectomy specimens, were analysed by IR-MSP (nominal resolution ~4.2 mum). More than 2.8 million pixel spectra that were processed using fuzzy c-means clustering followed by hierarchical cluster analysis permitted image segmentation regarding different biochemical properties. Linear image registration was applied to compare these segmentation results with manual labelling on haematoxylin and eosin-stained references (resolution ~0.7 mum). For recognition of nine tissue types, sensitivities were 42-91% and specificities were 79-100%, mostly being affected by peritumoral inflammatory responses. Algorithmic variation of the outline of dysplasia and carcinoma revealed a spatial preference of false values in tissue transition areas. CONCLUSIONS: This imaging technique has potential as a new method for tissue characterization; however, the recognition accuracy does not justify a pathologist-independent tissue analysis, and the application is only possible in combination with concomitant conventional histopathology.

Authors: J. Einenkel, U. D. Braumann, W. Steller, H. Binder, L. C. Horn

Date Published: 1st Mar 2012

Publication Type: Not specified

Human Diseases: cervical cancer

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