open access

Vol 47, No 4 (2009)
Original paper
Submitted: 2011-12-19
Published online: 2010-05-01
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New automated image analysis method for the assessment of Ki-67 labeling index in meningiomas.

Bartłomiej Grala, Tomasz Markiewicz, Wojciech Kozłowski, Stanisław Osowski, Janina Słodkowska, Wielisław Papierz
DOI: 10.2478/v10042-008-0098-0
·
Folia Histochem Cytobiol 2009;47(4):587-592.

open access

Vol 47, No 4 (2009)
ORIGINAL PAPERS
Submitted: 2011-12-19
Published online: 2010-05-01

Abstract

Many studies have emphasised the importance of Ki-67 labeling index (LI) as the proliferation marker in meningiomas. Several authors confirmed, that Ki-67 LI has prognostic significance and correlates with likelihood of tumour recurrences. These observations were widely accepted by pathologists, but up till now no standard method for Ki-67 LI assessment was developed and introduced for the diagnostic pathology. In this paper we present a new computerised system for automated Ki-67 LI estimation in meningiomas as an aid for histological grading of meningiomas and potential standard method of Ki-67 LI assessment. We also discuss the concordance of Ki-67 LI results obtained by presented computerized system and expert pathologist, as well as possible pitfalls and mistakes in automated counting of immunopositive or negative cells. For the quantitative evaluation of digital images of meningiomas the designed software uses an algorithm based on mathematical description of cell morphology. This solution acts together with the Support Vector Machine (SVM) used in the classification mode for the recognition of immunoreactivity of cells. The applied sequential thresholding simulated well the human process of cell recognition. The same digital images of randomly selected tumour areas were parallelly analysed by computer and blindly by two expert pathologists. Ki-67 labeling indices were estimated and the results compared. The mean relative discrepancy between the levels of Ki-67 LI by our system and by the human expert did not exceed 14% in all investigated cases. These preliminary results suggest that the designed software could be an useful tool supporting the diagnostic digital pathology. However, more extended studies are needed for approval of this suggestion.

Abstract

Many studies have emphasised the importance of Ki-67 labeling index (LI) as the proliferation marker in meningiomas. Several authors confirmed, that Ki-67 LI has prognostic significance and correlates with likelihood of tumour recurrences. These observations were widely accepted by pathologists, but up till now no standard method for Ki-67 LI assessment was developed and introduced for the diagnostic pathology. In this paper we present a new computerised system for automated Ki-67 LI estimation in meningiomas as an aid for histological grading of meningiomas and potential standard method of Ki-67 LI assessment. We also discuss the concordance of Ki-67 LI results obtained by presented computerized system and expert pathologist, as well as possible pitfalls and mistakes in automated counting of immunopositive or negative cells. For the quantitative evaluation of digital images of meningiomas the designed software uses an algorithm based on mathematical description of cell morphology. This solution acts together with the Support Vector Machine (SVM) used in the classification mode for the recognition of immunoreactivity of cells. The applied sequential thresholding simulated well the human process of cell recognition. The same digital images of randomly selected tumour areas were parallelly analysed by computer and blindly by two expert pathologists. Ki-67 labeling indices were estimated and the results compared. The mean relative discrepancy between the levels of Ki-67 LI by our system and by the human expert did not exceed 14% in all investigated cases. These preliminary results suggest that the designed software could be an useful tool supporting the diagnostic digital pathology. However, more extended studies are needed for approval of this suggestion.
Get Citation
About this article
Title

New automated image analysis method for the assessment of Ki-67 labeling index in meningiomas.

Journal

Folia Histochemica et Cytobiologica

Issue

Vol 47, No 4 (2009)

Article type

Original paper

Pages

587-592

Published online

2010-05-01

Page views

2463

Article views/downloads

2115

DOI

10.2478/v10042-008-0098-0

Bibliographic record

Folia Histochem Cytobiol 2009;47(4):587-592.

Authors

Bartłomiej Grala
Tomasz Markiewicz
Wojciech Kozłowski
Stanisław Osowski
Janina Słodkowska
Wielisław Papierz

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