Synopsis

Keywords: Quantitative Imaging, Kidney

The overlapping-echo detachment (OLED) imaging can capture a T₂ map within about 150 ms. However, when the region of interest (ROI) is smaller than the object, it is inefficient to acquire the whole object because many unnecessary phase-encoding steps should be acquired. The zonal oblique multislice (ZOOM) is a method to reduce the field of view (FOV) by using two pulses to excite two slabs that have a specific angle between them. This study combined ZOOM with OLED to capture the T₂ map with reduced FOV. The ZOOM-OLED can reduce geometric distortion and improve image resolution.

Introduction

The overlapping-echo detachment (OLED) imaging is a fast quantitative magnetic resonance imaging (MRI) method which can quantify multiple MR parameres within a single shot. As the EPI readout is used in data acquisition, OLED is sensitive to the B₀ inhomogeneity, and the image resolution is limited. For the EPI-based sequence, reducing the field of view (FOV) in the phase-encoding direction can reduce the image distortion when the region of interest (ROI) is much smaller than the object. Zonal oblique multislice (ZOOM) is a technique that can reduce the FOV by rotating the excitation slab by a specific angle. Here, we combined OLED and ZOOM to obtain the T₂ map with high image resolution and less geometric distortion. The ZOOM-OLED can obtain the T₂ map in a single shot, which allows us to capture the real-time T₂ values of the kidney without breath-hold.

Methods

Pulse sequence design: The OLED sequence can be easily combined with the ZOOM technique. The ZOOM-OLED sequence is shown in Figure 1c. Two excitation RF pulses are applied to generate two magnetization pathways (Figure 1b) that can be considered replicas of the k-space signal with different T₂ weightings. The excitation and refocusing slabs have a specific angle (Figure 1a). Before the two excitation pulses, regional saturation (RS) pulses are used to suppress the signals outside the ROI.
Training samples generation: The open-source MRI simulation software (MRiLab) was used to generate the training samples. Details about training samples generation can be found in literature [1].
Reconstruction: The flowchart of T₂ map reconstruction is shown in Figure 2. U-Net was used to reconstruct the T₂ map from the acquired OLED image. At the training stage, we took the simulated OLED image as input, and the corresponding T₂ map was taken as the label. At the testing stage, the acquired DICOM data were fed into the pre-trained U-Net to obtain the T₂ map. Experiments: This study was approved by the IRB at Zhongshan Hospital of Xiamen University. One volunteer (male, age = 27) was recruited and imaged on a 3.0 T MR scanner (Ingenia CX, Philips Healthcare). The experiments were performed with the ZOOM-OLED sequence (TE/TR, 41 ms/2000 ms; FOV, 250 × 120 mm²; matrix, 125 × 60). The flip angle of the excitation pulses was α = 55°.

Results

The OLED image acquired with the original OLED technique was compared with that acquired with ZOOM-OLED (Figure 3), and the volunteer was scanned under free breathing. It shows that the stripe is finer in ZOOM-OLED image, resuting higher spatial resolution of the T₂ map. The ZOOM-OLED scans were also performed multiple times with TR = 2000 ms. During the scan, the volunteer was asked to keep his breath. The reconstructed real-time T₂ maps are shown in Figure 4. We can see that due to its ultrafast characteristic, ZOOM-OLED provides T2 maps without motion artifacts. The regions of interest (ROI) are located almost at the same place in different T₂ maps. The boxplot of the T₂ value for the ROI shown in Figure 4 (TR = 1) is given in Figure 5. The T₂ variation could probably be attributed to the dynamic physiological process of the blood flow and the volunteer’s tiny movement.

Conclusion

In this work, we proposed a fast quantitative MRI method, ZOOM-OLED, to obtain less-distortion and high-spatial-resolution T₂ maps.

Acknowledgements

This work was supported by the National Natural Science Foundation of China under grant number 11775184.

References

[1] Ma LC, Wu J, et al. Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging. Neuroimage, 2022, 263:119645.