Megakaryocytic features useful for the diagnosis of myeloproliferative disorders can be obtained by a novel unsupervised software analysis
C. Tripodo1, C. Valenti2, B. Ballarò2, Z. Rudzki3, D. Tegolo2, V. Di Gesù2, A.M. Florena1 and V. Franco1
1Istituto di Anatomia Patologica, 2Dipartimento di Matematica e Applicazioni, Università degli Studi di Palermo, Italy, and 3Katedra Patomorfologii, Wydzial Lekarski, Collegium Medicum Uniwersytetu Jagiello nskiego, Kraków, Poland
Offprint requests to: Claudio Tripodo, Istituto di Anatomia e Istologia Patologica, Università degli Studi di Palermo, via del Vespro 129, 90100 Palermo, Italy. e-mail: tripodo@unipa.it
Summary. An unsupervised method for megakaryocyte detection and analysis is proposed, in order to validate supplementary tools which can be of help in supporting the pathologist in the classification of Philadelphia negative chronic myeloproliferative disorders with thrombocytosis. The experiment was conducted on high power magnification photomicrographs taken from hematoxylin-and-eosin 3 µm thick sections of formalin fixed, paraffin embedded bone marrow biopsies from patients with reactive thrombocytosis or chronic myeloproliferative disorders.
Each megakaryocyte has been isolated in the photos through an image segmentation process, mainly based on mathematical morphology and wavelet analysis. A set of features (e.g. area, perimeter and fractal dimension of the cell and its nucleus, shape complexity via elliptic Fourier transform, and so on) is used to characterize the disorders and discriminate between essential thrombocythemia and idiopathic myelofibrosis. Features related to the general contour of the cell like cytoplasmic area and perimeter are good markers in distinguishing between normal or reactive and pathologic megakaryocytes while nuclear features and global circularity are helpful in the differential diagnosis between ET and prefibrotic IMF. The method proposed should be considered as a fast preprocessing tool for the diagnostic phase and its use can be extended to solve different object recognition problems. Histol Histopathol 21, 813-821 (2006)
Key words: Megakaryocyte morphology, Unsupervised classification, Morphometry, Chronic myeloproliferative disorders
DOI: 10.14670/HH-21.813