Image analysis detects lineage-specific morphologic markers in leukemic blast cells.
This report outlines the morphologic classification of acute myeloid (AML: French-American-British FAB classification: M1) and lymphoid (ALL) leukemia by automatic image analysis and the correlation to immunologic and cytochemical classification. The investigation was carried out on Romanowsky-Giemsa stained bone marrow (n = 15) and blood smears (n = 10) from 25 patients with primary acute leukemia. The cases had been classified as of myeloid or lymphoid origin by three hematologic centers using immunochemistry or cytochemistry, but the specimens were submitted to the authors' laboratory without the diagnosis. The nuclear and cytoplasmic pattern of the blast cells were analyzed by a high resolution image analysis system and the measured and calculated cell features were sorted by means of a classifier program (CART). The image analysis classification was then compared with the immunophenotypical and cytochemical classification. Blood blast cells showed nuclear features that were significantly correlated to a myeloid or lymphoid immunophenotype. In contrast, bone marrow blast cells displayed overlapping and therefore nondiscriminating nuclear features. However, by generating a learning data set using the immunophenotypes the classifier program found specific cytoplasmic features that eventually permitted a differentiation into myeloid or lymphoid subtypes. In summary, the authors suggest that high resolution image analysis of leukemic blast cells detect nuclear and cytoplasmic features that are associated with the immunophenotype and therefore with the lineage determination of the cell. With this new objective and reproducible approach of morphologic cell analysis, it might not only be possible to classify blast cells with minimal cellular differentiation, but furthermore to discover prognostic features because the remarkable difference in classification quality between blood and bone marrow blast cells reported in this study, might be of biologic relevance and requires further investigation.
Baumann
I
I
Institute of Pathology, University of Würzburg, Germany.
Nenninger
R
R
Harms
H
H
Zwierzina
H
H
Wilms
K
K
Feller
A C
AC
Ter Meulen
V
V
Müller-Hermelink
H K
HK
D000293:Adolescent; D000328:Adult; D000368:Aged; D001853:Bone Marrow / Q000473:pathology; D002467:Cell Nucleus / Q000648:ultrastructure; D002648:Child; D003593:Cytoplasm / Q000648:ultrastructure; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016130:Immunophenotyping; D015470:Leukemia, Myeloid, Acute / Q000097:blood / Q000145:classification* / Q000473:pathology; D008875:Middle Aged; D009195:Peroxidase / Q000378:metabolism; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000097:blood / Q000145:classification* / Q000473:pathology
D009195:Peroxidase