Meeting Banner
Abstract #1288

Image quality evaluation of multi-sensitivity diffusion-weighted imaging for rectal cancer with small field of view based on deep learning

Xi Zhang1, Qingqing Xu1, Lili Guo1, Ying Shi1, Amin Dong1, and Dmytro Pylypenko2
1The First Huai 'an Hospital Affiliated to Nanjing Medical University, Huai 'an, China, Huai 'an, China, 2GE Healthcare, MR Research China, Beijing, Beijing, China

Synopsis

Keywords: AI Diffusion Models, DWI/DTI/DKI

Motivation: Diffusion-weighted magnetic resonance imaging (DW-MRI) is essential for rectal cancer imaging.

Goal(s): This study evaluated the image quality, rectal contours, lesion visibility of low-field multiple sensitivity diffusion-weighted imaging enhanced with deep learning reconstruction , assessing their signal-to-noise ratio and contrast-to-noise ratio .

Approach: 60 patients who underwent rectal MR examination at our hospital since January 2024 and were confirmed to have rectal adenocarcinoma by pathology were included.

Results: The SNR , CNR , image quality, rectal contour, and lesion visibility of FOCUS-MUSE images with DL were superior to those without DL (p < 0.01 for SNR, CNR, image quality, rectal contour, p = 0.02 for lesion visibility).

Impact: This study shows that DLR-based FOCUS-MUSE DWI enhances image quality, rectal contour, lesion visibility, SNR, and CNR, suggesting its potential to improve colorectal cancer staging accuracy.

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