Quasi-steady state chemical exchange saturation transfer (QUASS CEST) analysis-correction of the finite relaxation delay and saturation time for robust CEST measurement

• Type of Material: Article
• Authors: Phillip Zhe Sun, Emory University
• Language: English
• Date: 2021-01-23
• Publisher: WILEY
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2021 International Society for Magnetic Resonance in Medicine
• Final Published Version (URL): http://dx.doi.org/10.1002/mrm.28653
• Title of Journal or Parent Work: MAGNETIC RESONANCE IN MEDICINE
• Volume: 85
• Issue: 6
• Start Page: 3281
• End Page: 3289
• Grant/Funding Information: This study was supported in part by a grant from NIH/NIAMS R21AR071529 (to Sun), NIH/NINDS 2R01NS083654 (to Sun), and P51OD011132 (to Yerkes National Primate Research Center, Emory University).
• Keywords: QUASS CEST; QUAsi-Steady State CEST; Science & Technology; Radiology, Nuclear Medicine & Medical Imaging; CEST; chemical exchange saturation transfer; Life Sciences & Biomedicine

Abstract

Purpose: CEST provides a MR contrast mechanism sensitizing to the exchange between dilute labile and bulk water protons. However, the CEST effect depends on the RF saturation duration and relaxation delay, which need to be long to reach its steady state. Our study aims to estimate the QUAsi-Steady State (QUASS) CEST signal from experiments with shorter saturation and relaxation delay times. Methods: The evolution of the CEST signal was modeled as a function of the bulk water longitudinal relaxation rate during the relaxation delay (Td) and spin-lock relaxation rate during the RF saturation (Ts), from which the QUASS CEST effect is solved. Numeric simulations were programmed to compare the apparent CEST and QUASS CEST effects as a function of Ts and Td times. We also performed CEST MRI experiments from a creatine–gel pH phantom under serially varied Ts and Td times. Results: The numeric simulation showed that although the apparent CEST effect depends on Td and Ts, the QUASS CEST solution has little dependence. Phantom results showed that the routine CEST pH contrast could be described by a nonlinear regression model (ie, (Formula presented.)). We had (Formula presented.) = (Formula presented.) (P < 5e−8) and (Formula presented.) (P < 5e−6). For the QUASS CEST analysis, we modeled the pH contrast as (Formula presented.), using a linear regression model. We had (Formula presented.) (P < 5e−9) and (Formula presented.) (P < 0.01), the slope of which is minimal. Conclusions: The QUASS CEST algorithm provides a post-processing solution that facilitates robust CEST measurement.