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A decision support system to detect morphologic changes of chromatin arrangement in normal-appearing cells.

Identifieur interne : 001E25 ( Main/Exploration ); précédent : 001E24; suivant : 001E26

A decision support system to detect morphologic changes of chromatin arrangement in normal-appearing cells.

Auteurs : Roberto Sacile [Italie] ; Ernesto Montaldo ; Carmelina Ruggiero ; Herbert E. Nieburgs ; Guido Nicol

Source :

IEEE transactions on nanobioscience [ 1536-1241 ] ; 2003.

RBID : pubmed:15382668

English descriptors

KwdEn :
- Algorithms, Chromatin (classification), Chromatin (ultrastructure), Decision Support Techniques, Expert Systems, Humans, Image Interpretation, Computer-Assisted (methods), Lung Neoplasms (classification), Lung Neoplasms (pathology), Neural Networks (Computer), Reproducibility of Results, Sensitivity and Specificity.
MESH :
- chemical , classification : Chromatin.
- chemical , ultrastructure : Chromatin.
- classification : Lung Neoplasms.
- methods : Image Interpretation, Computer-Assisted.
- pathology : Lung Neoplasms.
- Algorithms, Decision Support Techniques, Expert Systems, Humans, Neural Networks (Computer), Reproducibility of Results, Sensitivity and Specificity.

Abstract

Several studies have described malignancy-associated changes (MACs) of chromatin arrangement in the nuclei of apparently normal cells adjacent to and distant from an invasive cancer area. MAC assessment is a hard task, since it requires a deep knowledge of morphologic features of chromatin arrangement. The aim of this work is to verify the reproducibility of the subjective evaluation of the expert on the basis of a decision support system (DSS) that automatically and objectively reproduces MAC diagnosis. A set of 61 patients with suspected clinical diagnosis for lung cancer has been taken into account. The scientist who first described MAC defined each patient as MAC positive or negative on the basis of the MAC diagnosis performed on all cells of the related cytologic sample. A DSS based on an artificial neural network has been set up to learn the relation between 14 morphometric and texture parameters, computed on each nucleus by image processing techniques, with the MAC diagnosis of the expert on each cell. The results show that an objective automatic assessment on MAC by the DSS can effectively support the MAC diagnosis. The method adopted in this approach may be also appropriate for other problems, where an automatic classification of visually inspected patterns of biological micro- and submicrostructure is needed.

PubMed: 15382668

Affiliations:

Italie

Le document en format XML

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<term>Humans</term>
<term>Image Interpretation, Computer-Assisted (methods)</term>
<term>Lung Neoplasms (classification)</term>
<term>Lung Neoplasms (pathology)</term>
<term>Neural Networks (Computer)</term>
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<term>Sensitivity and Specificity</term>
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<front><div type="abstract" xml:lang="en">Several studies have described malignancy-associated changes (MACs) of chromatin arrangement in the nuclei of apparently normal cells adjacent to and distant from an invasive cancer area. MAC assessment is a hard task, since it requires a deep knowledge of morphologic features of chromatin arrangement. The aim of this work is to verify the reproducibility of the subjective evaluation of the expert on the basis of a decision support system (DSS) that automatically and objectively reproduces MAC diagnosis. A set of 61 patients with suspected clinical diagnosis for lung cancer has been taken into account. The scientist who first described MAC defined each patient as MAC positive or negative on the basis of the MAC diagnosis performed on all cells of the related cytologic sample. A DSS based on an artificial neural network has been set up to learn the relation between 14 morphometric and texture parameters, computed on each nucleus by image processing techniques, with the MAC diagnosis of the expert on each cell. The results show that an objective automatic assessment on MAC by the DSS can effectively support the MAC diagnosis. The method adopted in this approach may be also appropriate for other problems, where an automatic classification of visually inspected patterns of biological micro- and submicrostructure is needed.</div>
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<name sortKey="Nieburgs, Herbert E" sort="Nieburgs, Herbert E" uniqKey="Nieburgs H" first="Herbert E" last="Nieburgs">Herbert E. Nieburgs</name>
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<country name="Italie"><noRegion><name sortKey="Sacile, Roberto" sort="Sacile, Roberto" uniqKey="Sacile R" first="Roberto" last="Sacile">Roberto Sacile</name>
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A decision support system to detect morphologic changes of chromatin arrangement in normal-appearing cells.

A decision support system to detect morphologic changes of chromatin arrangement in normal-appearing cells.

Source :

English descriptors

Abstract

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Le document en format XML

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