Volumetric thermometry in moving tissues using stack-of-radial MRI and an image-navigated multi-baseline proton resonance frequency shift method.

Abstract

Purpose: To develop and evaluate a volumetric proton resonance frequency shift (PRF)-based thermometry method for monitoring thermal ablation in moving tissues.

Methods: A golden-angle-ordered 3D stack-of-radial MRI sequence was combined with an image-navigated multi-baseline (iNAV-MB) PRF method to reconstruct motion-compensated 3D temperature maps with high spatiotemporal resolution and volumetric coverage. Two radial MRI reconstruction techniques, k-space weighted image contrast filter (KWIC) and golden-angle radial sparse parallel (GRASP) MRI, were implemented and compared within a sliding window reconstruction framework. Ex vivo motion phantom experiments were performed with high-intensity focused ultrasound ablation to evaluate motion tracking and temperature accuracy using input motion waveforms and temperature probe readings as references. In vivo non-heating swine experiments were conducted to assess temperature mapping stability in 3D liver regions of interest.

Results: The proposed iNAV-MB thermometry framework achieved volumetric coverage of 24 axial slices (3-mm thickness), in-plane resolution of 1.6 × 1.6 to 1.8 × 1.8 mm², and effective temporal resolution of 0.98 s/volume. In ex vivo high-intensity focused ultrasound experiments, motion tracking achieved correlation coefficients of 0.951 and 0.973, and temporal mean absolute errors were 1.80°C and 1.44°C using KWIC and GRASP, respectively. In vivo experiments demonstrated improvements in voxel-wise temperature temporal SD from a median of 8.03 to 3.85°C (KWIC) and from a median of 7.23 to 2.37°C (GRASP), compared to single-baseline PRF.

Conclusion: The proposed stack-of-radial iNAV-MB volumetric PRF thermometry framework can reliably track respiratory motion and map ablation-associated temperature change. This framework has the potential to improve MRI-guided thermal ablation in moving tissues.