A Platform for Collection and Analysis of Image Data on Stroke

Area of Science:

• Neuroimaging
• Radiomics
• Stroke Diagnostics

Background:

• Identifying imaging biomarkers (IBs) for stroke is crucial in neurodiagnostics.
• Current methods require extensive DICOM images and clinical data, posing a data acquisition challenge.

Purpose of the Study:

• To design and implement a platform for systematic collection of clinical data and medical images.
• To facilitate the creation of formalized radiology reports, contouring of regions of interest (ROIs), and radiomics data extraction.
• To enable the identification of IBs for predicting stroke outcomes and complications.

Main Methods:

• Development of a platform for systematic data collection across various imaging modalities.
• Integration of tools for formalized radiology reporting, ROI contouring, and DICOM image tagging.
• Extraction of radiomics features from processed medical images.

Main Results:

• A comprehensive dataset of clinical data and medical images has been amassed.
• The platform streamlines the process of data preparation for radiomics analysis.
• Enables the identification of potential imaging biomarkers for stroke.

Conclusions:

• The developed platform supports the systematic collection and analysis of multimodal imaging data for stroke research.
• This approach facilitates the discovery of novel imaging biomarkers.
• The ultimate goal is to develop predictive algorithms for improved stroke diagnostics.