Meeting Banner
Abstract #5064

Prediction of Prognosis in Acute Ischemic Stroke Based on Multimodal MRI Radiomics and Deep Learning.

Lei Pei1 and Xiaowei Han1
1Department of Radiology, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People’s Hospital, quzhou, China

Synopsis

Keywords: Stroke, Nervous system

Motivation: Acute ischemic stroke(AIS) is associated with high rates of disability and mortality, there are currently no reliable methods for early prediction of poor prognosis in AIS.

Goal(s): Exploring the value of radiomics and deep learning based on multimodal MRI in predicting poor prognosis in Acute ischemic stroke.

Approach: This study combines the Clinic Model, Radiomics Model, and Deep Learning Model to develop the CRD Model (Clinic-Radiomics-Deep Learning). The predictive efficacy of each model for poor prognosis is evaluated using receiver operating characteristic curves.

Results: The CRD model, based on multimodal MRI, demonstrates high diagnostic efficacy and reliability in predicting poor prognosis in AIS

Impact: These findings suggest that CRD model holds considerable potential for aiding clinicians in risk assessment and decision-making for AIS patients.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords