Enhanced detection of paramagnetic fluorine‐19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing
Abstract
Fluorine‐19 (19F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal‐to‐noise ratio (SNR) makes three‐dimensional spin‐density–weighted 19F imaging challenging. Recent advances in tracer paramagnetic metallo‐perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19F T1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19F T2‐reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity‐promoting algorithm. Our CS‐ZTE scheme acquires k‐space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off‐the‐shelf sparse solvers to solve a joint total variation and ‐norm regularized least square problem. To evaluate CS‐ZTE, we performed simulations and acquired 19F MRI data at 11.7 T in phantoms and mice receiving MPFC‐labeled dendritic cells. For MPFC‐labeled cells in vivo, we show SNR gains of ~6.3 × with 8‐fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T1. Importantly, 19F image intensity analyses yield accurate estimates of absolute quantification of 19F spins. Overall, the CS‐ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19F spin quantification, and minimal image artifacts.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 29, 2022
- Source ID
- 10.1002/nbm.4725
Entities
People
- Eric T. Ahrens
- Jiawen Chen
- Piya Pal
Organizations
- Department of Energy and Climate Change
- National Institutes of Health
- Office of Naval Research Global
- University of California, San Diego