Synopsis

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

Overestimation of perfusion volume fraction has been reported in conventional IVIM imaging. In a model known as extended T2-IVIM, compartmentalized relaxation times are incorporated to improve quantification of perfusion volume fraction, which requires acquisition of additional images at different TEs. A main challenge is that the scan time is lengthened, decreasing the efficiency while increasing vulnerability to motion. We herein introduce a novel sequence for time-efficient, relaxation-incorporated (TERI) IVIM imaging to address the aforementioned issues. TERI IVIM imaging uses multiple EPI readouts at different TEs in a single shot. The proposed technique has been demonstrated in the human brain.

Introduction

The intra-voxel incoherent motion (IVIM) diffusion model, originally proposed by Le Bihan et al. ¹, has attracted renewed attention. In this model, the diffusion-weighted MR signal at a given echo time (TE) is attenuated by pseudo-diffusion (or perfusion) and true-diffusion: $$$ S\left ( b,TE \right )/S_{0}= exp\left ( -TE/T2 \right )\times \left [ fexp\left ( -bD^{^{\ast }} \right )+\left ( 1-f \right )exp\left ( -bD \right ) \right ]$$$. In this two-compartmental model, f is the perfusion volume fraction, D* and D are the pseudo- and true-diffusion coefficients, respectively, and T2 is the transverse relaxation time which is typically assumed to be the same in both compartments. However, blood associated with the perfusion compartment is known to have a longer T2 than tissues, leading to an overestimated perfusion volume fraction f ^2–5. In a model known as extended T2-IVIM ³, the compartmentalized relaxation times can be accounted for by acquiring additional images in multiple scans, each with a distinctive TE. This approach, however, leads to a substantial increase in the total scan times and hence vulnerability to motion. We herein report a time-efficient technique that acquires diffusion-weighted signals at multiple TEs following a single excitation. We call this technique time-efficient, relaxation-incorporated (TERI) IVIM imaging. The signals from TERI-IVIM are analyzed using an extended T2-IVIM model to simultaneously characterize perfusion, diffusion, relaxation, and volume fraction.

Methods

Pulse sequence design: The sequence for TERI-IVIM imaging was based on a spin-echo diffusion-weighted EPI sequence in which multiple (e.g., 3) EPI readout echo-trains were placed after a Stejskal-Tanner diffusion preparation module (Figure 1). Each EPI readout echo-train corresponded to a distinct effective TE, where the effective TE is defined as the TE when the k-space center is sampled. The first echo-train coincided with the nominal TE (TE₀). Following the first readout echo-train, a180° RF refocusing pulse was applied to refocus the signal for the second echo-train acquisition. This process was repeated until the last echo-train was acquired. To reduce the length of each echo-train without compromising the spatial resolution, thereby enabling acquisition of multiple echo-trains, GRAPPA was employed with a two-fold acceleration.
Experiments: The TERI-IVIM imaging sequence was implemented on a GE MR750 3T scanner. Using this sequence, axial brain images were acquired with a 32‐channel head coil on healthy subjects. The acquisition parameters were: FOV=192×192 mm², imaging matrix=64×64, number of slices=6, slice thickness=5 mm, slice spacing=1 mm, TR=4000 ms, TEs=50.5/80.0/109.5 ms, number of echo-trains=3, echo-train length for each train=32, b=0/20/50/100/150/200/500 s/mm², NEX=6/6/6/6/8/10/16, and the scan time=11 min and 40 s.
Data analysis: Diffusion-weighted images with different b-values acquired at different TEs were separately reconstructed. The voxel-level signal in these images can be described by ³:$$S\left ( b,TE \right )/S_{0}=fexp\left ( -TE/T2_{p} \right )exp\left ( -bD^{^{\ast }} \right )+\left ( 1-f \right )exp\left ( -TE/T2_{d} \right )exp\left ( -bD \right )$$where S₀ is the signal intensity with b-value = 0 s/mm² and TE = 0 ms, and T2_p and T2_d are the T2 values of the perfusion and true-diffusion compartments, respectively. In comparison with the conventional IVIM model, the model above can simultaneously determine compartmentalized perfusion, diffusion, and T2 relaxation parameters. The model was used to fit to all 21 images (7 b-values × 3 TEs) voxel-by-voxel using a non-linear least-squares fitting algorithm in MATLAB 2021a (MathWorks, Inc.). Fitting was repeated 100 times with randomized initial parameters to avoid local minima. For comparison, a conventional IVIM model was also fitted to the diffusion-weighted images acquired at TE_0. Regions of interest (ROIs) were drawn only in the white matter to minimize the partial-volume effects from cerebrospinal fluid (Figure 2). After obtaining the voxel-wise parameter maps, the mean value of perfusion volume fraction within the ROIs was compared between TERI-IVIM and conventional IVIM imaging.

Results

TERI-IVIM imaging enabled a three-fold acceleration without compromising the spatial resolution when compared with conventional separate scans with different TEs. Using the TERI-IVIM sequence, two-dimensional diffusion-weighted brain images (Figure 2) from a representative healthy subject with seven b-values and three TEs were obtained within 12 minutes. TERI-IVIM imaging provided information not only on perfusion (D*) and diffusion (D), but also on compartmentalized T2 values, thereby removing the T2/TE bias in perfusion fraction quantification. Figure 3 shows that the model fits the measured data well with respect to both b-value and TE [RSE (relative squared error) < 0.01]. The resultant parameter maps are shown in Figures 4. Quantitative measurement of perfusion volume fraction in the white matter revealed an approximately 30.4% reduction in TERI-IVIM imaging (f = 0.064) compared with conventional IVIM imaging (f = 0.092). The perfusion volume fraction maps of a representative slice obtained with the two techniques are shown in Figure 5, together with their difference map.

Discussion and Conclusion

We have demonstrated a novel technique, TERI-IVIM imaging, that can be used to acquire multiple diffusion-weighted images at different TEs in a single shot. The three-fold improvement in time efficiency has enabled quantification of perfusion, diffusion, relaxation, and volume fraction in the human brain in less than 12 minutes. Our observation that TERI-IVIM produced a lower perfusion volume fraction than conventional IVIM imaging demonstrates the ability to reduce overestimation. The TERI-IVIM sequence is expected to stimulate ongoing research to expand and refine the IVIM model for diffusion imaging studies.

Acknowledgements

This work was supported in part by the National Institutes of Health (5R01EB026716-01 and 1S10RR028898-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We thank Drs. Muge Karaman, Alessandro Scotti, and Kezhou Wang for helpful discussions.