Abstract #0243

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning

Yueyao Chen¹, Zhongxian Pan¹, Qiuyi Chen¹, Haiwei Lin², Bingsheng Huang², Wensheng Huang³, Fanqi Meng¹, Zhangnan Zhong², Wenxi Liu², Zhujing Li¹, and Haodong Qin⁴

¹Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China, ²Medical AI Lab,School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China, ³Department of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China, ⁴MR Research Collaboration, Siemens Healthineers, Guangzhou, China

Synopsis

Keywords: Diagnosis/Prediction, Diabetes

Motivation: Intra-pancreatic fat deposition (IPFD) is linked to the onset and progression of type 2 diabetes mellitus (T2DM).

Goal(s): Develop an accurate and automated method to measure IPFD on multi-echo Dixon MRI.

Approach: 518 patients who underwent upper abdomen MRI were included.A deep learning radiomics (DLR) model and two radiologist models were constructed.

Results: The mean Dice similarity coefficient for pancreas segmentation was 0.959.The DLR model achieved the AUCs of 0.862 (training cohort) and 0.786 (external test cohort),both outperforming the radiologist models.The ICCs between radiologists’ pancreatic proton density fat fraction (PDFF) measurements were 0.797 and 0.708 in the two cohorts,suggesting good and moderate reproducibility,respectively.

Impact: The DLR model demonstrated superior performance over radiologists, providing a more efficient, accurate and stable method for monitoring IPFD.

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.