An Online Flow Cytometry Analysis System
You-Wen Qian MD; Cedars-Sinai Medical Center; Stephen Lee MD; Cedars-Sinai Medical Center; Dinesh Mital PhD; University of Medicine and Dentistry of New Jersey-SHRP;
Content:
Immunophenotyping of cell clusters of designation (CD marker) by flow cytometry plays an important role in making final diagnosis of hematological disorders. Manual data analysis and interpretation is currently performed in majority of flow cytometry laboratories. However, paper analysis is time-consuming and manual data entry to pathology information system is error-prone. The descriptive text data in the flow report is not portable. The aim of the present study is to develop an online flow cytometry system to facilitate flow cytometry analysis and data transfer.
Technology:
A complete Client-Server network application has been built. The technologies employed in this study include: JAVA Development Kit (JDK 1.5.0_10), Apache-Jakarta Tomcat Server Container (version 5.5.20), Extensible Markup Language (XML, version 1.0), and Java Server Pager 2.0 specification.
Design:
The listmode flow cytometry data files are imported to the online flow cytometry system implemented in JAVA Applet where gating, dotplot, histogram and contour plot can be performed. Upon gating, CD marker results are generated in percentage of cell population, based on which positive or negative designation for CD markers is automatically assigned. By analyzing large flow cytometry data profile including both normal condition and hematopoietic neoplasms, we have set the threshold to determine positivity or negativity for commonly tested CD markers.
Results:
A set of 273 flow cytometry listmode data files (in data file standard for flow cytometry version 2.0) are fed into the system. These flow data cover distinctive diagnostic immunphenotyping profile of 28 different hematopoietic neoplasms and normal population as well. The functionalities in this system are comparable to commercial CXP flow cytometry software (Beckman Coulter, CA). All flow results are in discrete data elements which are editable and seamlessly transferable in XML format.
Conclusion:
The website (http://www.flowcytometryonline.com) has been setup for online flow cytometry analysis. The listmode data files located in either Sever side or Client side can be accessed. Stand-alone application is also provided when internet access is limited. The system is expected to facilitate clinical diagnosis of hematologic disease.
