Single projection driven real-time multi-contrast (SPIDERM) MR imaging using pre-learned spatial subspace and linear transformation

Abstract

Objective. To develop and test the feasibility of a novel Single ProjectIon DrivEn Real-time Multi-contrast (SPIDERM) MR imaging technique that can generate real-time 3D images on-the-fly with flexible contrast weightings and a low latency. Approach. In SPIDERM, a “prep” scan is first performed, with sparse k-space sampling periodically interleaved with the central k-space line (navigator data), to learn a subject-specific model, incorporating a spatial subspace and a linear transformation between navigator data and subspace coordinates. A “live” scan is then performed by repeatedly acquiring the central k-space line only to dynamically determine subspace coordinates. With the “prep”-learned subspace and “live” coordinates, real-time 3D images are generated on-the-fly with computationally efficient matrix multiplication. When implemented based on a multi-contrast pulse sequence, SPIDERM further allows for data-driven image contrast regeneration to convert real-time contrast-varying images into contrast-frozen images at user’s discretion while maintaining motion states. Both digital phantom and in-vivo experiments were performed to evaluate the technical feasibility of SPIDERM. Main results. The elapsed time from the input of the central k-space line to the generation of real-time contrast-frozen 3D images was approximately 45 ms, permitting a latency of 55 ms or less. Motion displacement measured from SPIDERM and reference images showed excellent correlation (R^2≥0.983). Geometric variation from the ground truth in the digital phantom was acceptable as demonstrated by pancreas contour analysis (Dice≥0.84, mean surface distance≤0.95 mm). Quantitative image quality metrics showed good consistency between reference images and contrast-varying SPIDREM images in in-vivo studies (mean NMRSE=0.141, PSNR=30.12, SSIM=0.88). Significance. SPIDERM is capable of generating real-time multi-contrast 3D images with a low latency. An imaging framework based on SPIDERM has the potential to serve as a standalone package for MR guided radiation therapy by offering adaptive simulation through a “prep” scan and real-time image guidance through a “live” scan.

Accelerating 4D image reconstruction for magnetic resonance-guided radiotherapy

“…We explored the benefits of inter-slice parallelism for the XD-GRASP algorithm. The presented approach could be applied to other MRI reconstruction algorithms, where at least one sampling dimension is Cartesian, such as the stack-of-stars [28] or the stack-of-spirals [47] patterns and could be extended to time-resolved 4D-MRI [10] based on XD-GRASP such as MRSIGMA [22] or SPIDERM [48] . In particular regarding time-resolved 4D-MRI, the use of randomized projection-encoding [49] could be beneficial, but wouldn’t allow for straight-forward inter-slice parallelism.…”

Live‐view 4D GRASP MRI: A framework for robust real‐time respiratory motion tracking with a sub‐second imaging latency

“…The live-view stage can only acquire 2D navigators, and real-time 3D images can be efficiently generated with simple 2D pattern matching using acquired navigators. Although the idea of two-stage imaging was previously explored in MRSIGMA 29 and SPIDERM, 30 there are a number of limitations in these two approaches. A major limitation of MRSIGMA, among several others, is the generation of a motion database based on respiratory-resolved 4D imaging, which requires an explicit step for motion extraction and relies on stable and uniform breathing.…”

“…Another technique that adopted the idea of two-stage imaging is single projection driven real-time MR imaging (SPIDERM). 30 Instead of generating a respiratory-resolved motion database, SPIDERM aims to reconstruct a spatial basis that serves as a motion database to generate real-time 3D images. External head-to-foot 1D projections are periodically acquired throughout the two stages as navigators.…”

Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system

“…Another study attempted to estimate real-time 3D motion with high spatiotemporal resolution and relatively low latency (less than 500 ms) using multi-resolution neural networks (Terpstra et al 2021). In addition, a real-time multi-contrast 4D MRI approach based on multi-tasking and a single projection was proposed to achieve a latency of 55 ms for MR-guided radiotherapy (Han et al 2022). However, these techniques were only implemented on digital phantom or healthy subjects and have not been demonstrated in clinical patients treated on 1.5T MR-Linac systems.…”