Premium
Value of morphometry, texture analysis, densitometry, and histometry in the differential diagnosis and prognosis of malignant mesothelioma
Author(s) -
Weyn Barbara,
Van De Wouwer Gert,
Koprowski Marek,
Van Daele André,
Dhaene Karl,
Scheunders Paul,
Jacob Willem,
Van Marck Eric
Publication year - 1999
Publication title -
the journal of pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.964
H-Index - 184
eISSN - 1096-9896
pISSN - 0022-3417
DOI - 10.1002/(sici)1096-9896(199912)189:4<581::aid-path464>3.0.co;2-p
Subject(s) - mesothelioma , pathology , mesothelium , medicine , immunohistochemistry , adenocarcinoma , densitometry , discriminative model , cancer , artificial intelligence , computer science , peritoneum
Malignant mesothelioma is a tumour with increasing incidence due to widespread use of its causative agent, asbestos, in the past decades. The poor survival necessitates a correct differentiation from other lesions at the same site, such as hyperplastic mesothelium and carcinomas metastatic to pleura or peritoneum. Since genetic and immunohistochemical markers are not absolutely differentiating, the diagnosis is based on the histology complemented with (immuno)histochemistry. However, as the tumour presents itself in numerous heterogeneous histological forms, visual evaluation is extremely difficult. In order to evaluate the prognostic and diagnostic performance of syntactic structure analysis (SSA), chromatin texture analysis, densitometry, and morphometry, an automated KNN‐classification system has been used to compare Feulgen‐stained tissue sections of hyperplastic mesothelium, malignant mesothelioma, and pulmonary adenocarcinoma. In addition, we also studied most discriminative aspects in the differentiation, typing, and prediction of survival. The results indicate that for the diagnosis of malignant mesothelioma, chromatin texture parameters outperform SSA, densitometry, and morphometry (recognition score=96·8 per cent). Most discriminative parameters highlight spatial patterns of the chromatin distribution that are hard to appraise visually and directly show the benefits of a quantitative approach. Typing of the tumour is best described by SSA parameters, relating to the spatial arrangement of the cells in the tissue (recognition score=94·9 per cent). In survival time classifications, chromatin texture yields the highest recognition score (82·9 per cent), although accurate estimations are unreliable due to a large degree of misclassification. Copyright © 1999 John Wiley & Sons, Ltd.