CytometryML, an XML format based on DICOM and FCS for analytical cytology data

Area of Science:

• Cytometry
• Bioinformatics
• Medical Imaging

Background:

• The current Flow Cytometry Standard (FCS) facilitates software standardization for flow cytometry data analysis, transmission, and storage.
• Clinical applications of flow cytometry necessitate a standard that aligns with medical regulatory agency requirements.

Purpose of the Study:

• To extend the existing mapping of FCS to the Digital Imaging and Communications in Medicine (DICOM) standard.
• To incorporate list-mode data from flow cytometry, laser scanning cytometry, and microscopic image cytometry into the DICOM standard.
• To develop an open, extensible, and peer-reviewed standard for cytometry data.

Main Methods:

• Mapped FCS list-mode data to the DICOM Waveform Information Object.
• Created Extensible Markup Language (XML) schemas for DICOM analytical cytologic data types.
• Developed a new cytometry markup language, CytometryML, in an open, peer-reviewed environment.

Main Results:

• Demonstrated the feasibility of expressing FCS data, including list-mode, within the DICOM standard.
• Completed a preliminary mapping of list-mode data using XML schemas and documents.
• Showcased DICOM's ability to create indices for rapid cell subset identification within list-mode files.
• Integrated DICOM and XML schemas with other relevant applications like Mathematical Markup Language (MathML).

Conclusions:

• The proposed XML-based DICOM format for analytical cytology meets most specified requirements for regulatory compliance and data handling.
• The current FCS standard should be superseded by the open, XML-based CytometryML standard.
• CytometryML offers enhanced capabilities for data analysis, storage, and regulatory adherence in cytometry.