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The WHO scheme for prothrombin time (PT) standardization has been limited in application, because of its difficulties in implementation, particularly the need for mandatory manual PT testing and for local provision of thromboplastin international reference preparations (IRP).The value of a new simpler procedure to derive international normalized ratio (INR), the PT/INR Line, based on only five European Concerted Action on Anticoagulation (ECAA) calibrant plasmas certified by experienced centres has been assessed in two independent exercises using a range of commercial thromboplastins and coagulometers. INRs were compared with manual certified values with thromboplastin IRP from expert centres and in the second study also with INRs from local ISI calibrations.In the first study with the PT/INR Line, 8.7% deviation from certified INRs was reduced to 1.1% with human reagents, and from 7.0% to 2.6% with rabbit reagents. In the second study, deviation was reduced from 11.2% to 0.4% with human reagents by both local ISI calibration and the PT/INR Line. With rabbit reagents, 10.4% deviation was reduced to 1.1% with both procedures; 4.9% deviation was reduced to 0.5% with bovine/combined reagents with local ISI calibrations and to 2.9% with the PT/INR Line. Mean INR dispersion was reduced with all thromboplastins and automated systems using the PT/INR Line.The procedure using the PT/INR Line provides reliable INR derivation without the need for WHO ISI calibration across the range of locally used commercial thromboplastins and automated PT systems included in two independent international studies.? 2010 International Society on Thrombosis and Haemostasis.

INTRODUCTION / BACKGROUND: In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. AIMS: The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. METHODS: Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labelling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a micro- scope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). RESULTS: Currently, a total of 60 patients (CLL and healthy) were in- cluded in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (RandomForest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.