Paper # 087 Versión en Español Versión en Español

Automatic Determination of Intraglomerular Hypercellularity by Computerised Image Analysis.

Marco Masseroli, Francisco O'Valle, Raimundo G. del Moral.
Departament of Pathology, School of Medicine and University Hospital, University of Granada, 18012 Granada, Spain

Address: Dpto. de Anatomía Patológica, Facultad de Medicina,
Avda. de Madrid 11 - 18012 Granada, Spain

[Introduction] [Materials & Methods] [Results] [Pictures] [Discussion] [Bibliography]

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BACKGROUND: Glomerular hypercellularity, more than 50 ± 10 cells per glomerulus in an equatorial section, is a criteria used in algorithms of glomerular morphological interpretation. Many glomerulopaties present mesangial hypercellularity (IgA glomerulonephropathy, lupus nephritis, postinfectious glomerulonephritis, diabetes glomerulosclerosis, minimal changes nephropathic syndrome, focal segmental glomerulosclerosis, membranoproliferative glomerulonephritis type II and III). In this study an image analysis application for automatic quantification of intraglomerular hypercellularity is presented.

MATERIAL AND METHODS: Renal tissue was embedded in paraffin and cells nuclei stained with Mayer's progressive hematoxylin. Images of the histological sections were captured using a BCD-700 CCD Vidamax video camera coupled to a BH-2 Olympus microscope (X200 magnification) and digitized in 256 grey level resolution (black and white). The image processing program used for the analysis was realised in MS-DOS environment (PC Pentium-S 100 MHz) with Visilog 3.6 (Noesis) software for development of image analysis applications.

RESULTS: The main modules of the image analysis application for automatic quantification of glomerular proliferative cell lesions consist of: double image thresholding, to extract the essential information about each cell nucleus; mathematical morphological filtering, to separate and individually identify connected or partial superposed cell nuclei; interactive glomerular area identification, and automatic glomerular cell nuclei counting.

CONCLUSIONS: The presented application allows the accurate counting of glomerular cellularity in a minimum time (real time of image set-up and interpretation with the described computer configuration is about 105 sec/image).

Marco Masseroli is a postdoctoral fellow of the Pathology Departament of the School of Medicine of the University of Granada, where he develops image analysis applications in histopathological videomicroscopy.

Granada, besides being world wide known for the Alhambra monument, is the most important university town of the Andalucía region. Located in the south of Spain enjoys the vicinity both of "Costa del Sol" and "Sierra Nevada".

M. Masseroli, Ph.D.

Key Words: Glomerular cellularity, Cell nuclei counting, Image processing, Automatic quantification.

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Marco Masseroli, Ph.D.
Copyright © 1997, Departamento de Anatomía Patológica, Facultad de Medicina y Hospital Universitario, Universidad de Granada, 18012 Granada, España. Reservados todos los derechos.