Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.

ABSTRACT:

Purpose

The interest in applying and modeling dynamic MRS has recently grown. 2D modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to 1D modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches.

Methods

Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multi-transient LCM with 1D-LCM of the average. 2,500 datasets per condition with different noise representations of a 64-transient MRS experiment at 6 s

SUBMITTER: Zollner HJ 

PROVIDER: S-EPMC10802456 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature