Meeting Banner
Abstract #0609

Automated MRS quality control across diverse acquisitions and neurological diseases using self-supervised transformers

Jenny Lee1,2, Sana Vaziri1, Nate Tran1, Duan Xu1,2, Yan Li1,2, and Janine Lupo1,2
1Department of Radiology and Biomedical Imaging, UCSF, San Fransisco, CA, United States, 2Graduate program in bioengineering, UCSF/UC Berkeley, San Fransisco, CA, United States

Synopsis

Keywords: Spectroscopy, Multimodal, MRSI, MR Spectroscopy, Self-supervised learning, neurological diseases, model generalizability

Motivation: Preprocessing pipelines for MRSI are time-consuming and typically require trained experts with domain knowledge. With accelerated acquisitions and improved spatial coverage, automated quality control (QC) becomes increasingly important.

Goal(s): To develop a model for automated spectral QC that captures global brain spectra characteristics while being robust across diverse neurological diseases

Approach: We employed a contrastive self-supervised learning framework during pretext training phase. A classification model was stacked on pretrained latent space to predict the quality of voxel-wise MRS data.

Results: The proposed model showed its strength in modeling complex dependencies over spectral sequences and demonstrated robustness across diverse neurological disease and scanner acquisitions

Impact: This approach enables automated quality control for MRS, reducing reliance on manual assessments. It enhances diagnostic accuracy, supports broader clinical adoption, and may reveal complex interdependencies, thus improving our understanding of neurological disease progression and treatment responses

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