Meeting Banner
Abstract #3607

Utility of whole tumor texture analysis based on MRI and ADC values in differentiating uterine sarcomas from cellular uterine leiomyomas

Zhong Yang1 and Cao Wei2
1Department of Radiology, Graduate school of Bengbu Medical College, Bengbu, China, 2Department of Radiology, The First Affiliated Hospital of USTC, Hefei, China

Synopsis

Keywords: Diagnosis/Prediction, Machine Learning/Artificial Intelligence

Motivation: The treatment methods and prognosis of cellular uterine leiomyomas (CULs) and uterine sarcomas (USs) are different. The ADC values has certain differential diagnostic value, but there is some overlap between them. Texture analysis (TA) may have some potential and complementary role in differential diagnosis.

Goal(s): To explore the capability of TA based on MRI and ADC values in the differential diagnosis of USs from CULs.

Approach: Combining the ADC values and texture parameters to set up diagnostic model and evaluate the diagnosis value and clinical usefulness of the model.

Results: Texture analysis combined with DWI could be helpful to distinguish USs and CULs.

Impact: Texture analysis combined with DWI give a better method to identify uterine sarcomas and cellular uterine leiomyomas, providing a more reliable basis for the choice of clinical treatment.

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