In clinical practice, the diagnosis and classification of acute myeloid leukaemia (AML) and myelodysplastic syndrome (MDS) start from the manual examination of stained smears of bone marrow (BM) and peripheral blood (PB) by using an optical microscope. This step is subjective and scarcely reproducible. Therefore, the development of subjective and potentially automatable methods for the recognition of typical AML/MDS cells is necessary. Here we have used Raman spectroscopy for distinguishing myeloblasts, promyelocytes, abnormal promyelocytes and erhytroblasts, which have to be counted for a correct diagnosis and morphological classification of AML and MDS. BM samples from patients affected by four different AML subtypes, mostly characterized by the presence of the four subpopulations selected for this study, were analyzed. First, each cell was scanned by acquiring 4096 spectra, thus obtaining Raman images which demonstrate an accurate description of morphological features characteristic of each subpopulation. Raman imaging coupled with hierarchical cluster analysis permitted the automatic discrimination and localization of the nucleus, the cytoplasm, myeloperoxidase containing granules and haemoglobin. Second, the averaged Raman fingerprint of each cell was analysed by multivariate analysis (principal component analysis and linear discriminant analysis) in order to study the typical vibrational features of each subpopulation and also for the automatic recognition of cells. The leave-one-out cross validation of a Raman-based classification model demonstrated the correct classification of myeloblasts, promyelocytes (normal/abnormal) and erhytroblasts with an accuracy of 100%. Normal and abnormal promyelocytes were distinguished with 95% accuracy. The overall classification accuracy considering the four subpopulations was 98%. This proof-of-concept study shows that Raman micro-spectroscopy could be a valid approach for developing label-free, objective and automatic methods for the morphological classification and counting of cells from AML/MDS patients, in substitution of the manual examination of BM and PB stained smears.

Immune-mediated refractoriness to platelet transfusion is a major problem in patients undergoing HSCT. In a cohort of 50 pediatric patients affected by beta thalassemia coming from Middle East countries, we experienced a high incidence of refractoriness because of anti-HLA antibodies during post-HSCT aplasia. In a risk factors analysis, factors predicting a negative transfusion outcome were presence of spleen and the number of anti-HLA antibodies. We adopted a policy to select platelet donors by avoiding HLA antigens against which the patient had specific antibodies. Transfusion of dedicated units resulted in 26% refractoriness compared to 74% to random units (p < 0.0001). When dedicated transfusions were used, the presence of spleen did not influence transfusion outcome. Analyzing transfusion outcome depending on the degree of HLA match and ABO compatibility, 76% successful transfusions were obtained with HLA-matched- ABO compatible followed by 67% in HLA-1mismatch- ABO compatible or HLA-matched- ABO incompatible and by 46% in HLA-1mismatch- ABO incompatible. In conclusion, we provide evidence that the selection of platelet donors according to patient characteristics, anti-HLA antibodies and ABO matching, is successful in reducing platelet refractoriness in heavily alloimmunized thalassemia patients undergoing transplantation.

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