Advances in emergency networking

Crisis situations require fast regain of control. Wireless ad-hoc networks will enable emergency services to act upon the actual status of the situation by retrieving and exchanging detailed up-to-date information. Deployment of highbandwidth, robust, self-organising ad-hoc networks will therefore enable quicker response to typical hat/where/when questions, than the more vulnerable low-bandwidth communication networks currently in use. This paper addresses a number of results of the projects AAF (Adaptive Ad-hoc Freeband communications) and Easy Wireless that enable high bandwidth robust ad-hoc networking

A series of case studies illustrating the role of flow cytometry in the diagnostic work-up of myelodysplastic syndromes

Current guidelines recommend flow cytometric analysis as part of the diagnostic assessment of patients with cytopenia suspected for myelodysplastic syndrome. Herein we describe the complete work-up of six cases using multimodal integrated diagnostics. Flow cytometry assessments are illustrated by plots from conventional and more recent analysis tools. The cases demonstrate the added value of flow cytometry in case of hypocellular, poor quality, or ambiguous bone marrow cytomorphology. Moreover, they demonstrate how immunophenotyping results support clinical decision-making in inconclusive and clinically ‘difficult’ cases

Immunophenotypic analysis of erythroid dysplasia in myelodysplastic syndromes. A report from the IMDSFlow working group

International audienc

ARTICLE Immunophenotypic analysis of erythroid dysplasia in myelodysplastic syndromes. A report from the IMDSFlow working group © Ferrata Storti Foundation

C urrent recommendations for diagnosing myelodysplastic syndromes endorse flow cytometry as an informative tool. Most flow cytometry protocols focus on the analysis of progenitor cells and the evaluation of the maturing myelomonocytic lineage. However, one of the most frequently observed features of myelodysplastic syndromes is anemia, which may be associated with dyserythropoiesis. Therefore, analysis of changes in flow cytometry features of nucleated erythroid cells may complement current flow cytometry tools. The multicenter study within the IMDSFlow Working Group, reported herein, focused on defining flow cytometry parameters that enable discrimination of dyserythropoiesis associated with myelodysplastic syndromes from non-clonal cytopenias. Data from a learning cohort were compared between myelodysplasia and controls, and results were validated in a separate cohort. The learning cohort comprised 245 myelodysplasia cases, 290 pathological, and 142 normal controls; the validation cohort comprised 129 myelodysplasia cases, 153 pathological, and 49 normal controls. Multivariate logistic regression analysis performed in the learning cohort revealed that analysis of expression of CD36 and CD71 (expressed as coefficient of variation), in combination with CD71 fluorescence intensity and the percentage of CD117 + erythroid progenitors provided the best discrimination between myelodysplastic syndromes and non-clonal cytopenias (specificity 90%; 95% confidence interval: 84-94%). The high specificity of this marker set was confirmed in the validation cohort (92%; 95% confidence interval: 86-97%). This erythroid flow cytometry marker combination may improve the evaluation of cytopenic cases with suspected myelodysplasia, particularly when combined with flow cytometry assessment of the myelomonocytic lineage

Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes

Contains fulltext : 169708.pdf (publisher's version ) (Open Access)Flow cytometric analysis is a recommended tool in the diagnosis of myelodysplastic syndromes. Current flow cytometric approaches evaluate the (im)mature myelo-/monocytic lineage with a median sensitivity and specificity of ~71% and ~93%, respectively. We hypothesized that the addition of erythroid lineage analysis could increase the sensitivity of flow cytometry. Hereto, we validated the analysis of erythroid lineage parameters recommended by the International/European LeukemiaNet Working Group for Flow Cytometry in Myelodysplastic Syndromes, and incorporated this evaluation in currently applied flow cytometric models. One hundred and sixty-seven bone marrow aspirates were analyzed; 106 patients with myelodysplastic syndromes, and 61 cytopenic controls. There was a strong correlation between presence of erythroid aberrancies assessed by flow cytometry and the diagnosis of myelodysplastic syndromes when validating the previously described erythroid evaluation. Furthermore, addition of erythroid aberrancies to two different flow cytometric models led to an increased sensitivity in detecting myelodysplastic syndromes: from 74% to 86% for the addition to the diagnostic score designed by Ogata and colleagues, and from 69% to 80% for the addition to the integrated flow cytometric score for myelodysplastic syndromes, designed by our group. In both models the specificity was unaffected. The high sensitivity and specificity of flow cytometry in the detection of myelodysplastic syndromes illustrates the important value of flow cytometry in a standardized diagnostic approach. The trial is registered at www.trialregister.nl as NTR1825; EudraCT n.: 2008-002195-10

Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes

Flow cytometric analysis is a recommended tool in the diagnosis of myelodysplastic syndromes. Current flow cytometric approaches evaluate the (im)mature myelo-/monocytic lineage with a median sensitivity and specificity of ~71% and ~93%, respectively. We hypothesized that the addition of erythroid lineage analysis could increase the sensitivity of flow cytometry. Hereto, we validated the analysis of erythroid lineage parameters recommended by the International/European LeukemiaNet Working Group for Flow Cytometry in Myelodysplastic Syndromes, and incorporated this evaluation in currently applied flow cytometric models. One hundred and sixty-seven bone marrow aspirates

Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes

Flow cytometric analysis is a recommended tool in the diagnosis of myelodysplastic syndromes. Current flow cytometric approaches evaluate the (im)mature myelo-/monocytic lineage with a median sensitivity and specificity of ~71% and ~93%, respectively. We hypothesized that the addition of erythroid lineage analysis could increase the sensitivity of flow cytometry. Hereto, we validated the analysis of erythroid lineage parameters recommended by the International/European LeukemiaNet Working Group for Flow Cytometry in Myelodysplastic Syndromes, and incorporated this evaluation in currently applied flow cytometric models. One hundred and sixty-seven bone marrow aspirates were analyzed; 106 patients with myelodysplastic syndromes, and 61 cytopenic controls. There was a strong correlation between presence of erythroid aberrancies assessed by flow cytometry and the diagnosis of myelodysplastic syndromes when validating the previously described erythroid evaluation. Furthermore, addition of erythroid aberrancies to two different flow cytometric models led to an increased sensitivity in detecting myelodysplastic syndromes: from 74% to 86% for the addition to the diagnostic score designed by Ogata and colleagues, and from 69% to 80% for the addition to the integrated flow cytometric score for myelodysplastic syndromes, designed by our group. In both models the specificity was unaffected. The high sensitivity and specificity of flow cytometry in the detection of myelodysplastic syndromes illustrates the important value of flow cytometry in a standardized diagnostic approach

Flow cytometric analysis of myelodysplasia: Pre-analytical and technical issues—Recommendations from the European LeukemiaNet

Background: Flow cytometry (FCM) aids the diagnosis and prognostic stratification of patients with suspected or confirmed myelodysplastic syndrome (MDS). Over the past few years, significant progress has been made in the FCM field concerning technical issues (including software and hardware) and pre-analytical procedures. Methods: Recommendations are made based on the data and expert discussions generated from 13 yearly meetings of the European LeukemiaNet international MDS Flow working group. Results: We report here on the experiences and recommendations concerning (1) the optimal methods of sample processing and handling, (2) antibody panels and fluorochromes, and (3) current hardware technologies. Conclusions: These recommendations will support and facilitate the appropriate application of FCM assays in the diagnostic workup of MDS patients. Further standardization and harmonization will be required to integrate FCM in MDS diagnostic evaluations in daily practice

Multiparameter flow cytometry in the evaluation of myelodysplasia: Analytical issues: Recommendations from the European LeukemiaNet/International Myelodysplastic Syndrome Flow Cytometry Working Group

Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow-up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work-up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34+CD19−) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work-up. Looking forward, several machine-learning-based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine-learning-based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS