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Free Breathing Phase-Resolved Lung Imaging Using a 3D UTE Cones Sequence with Randomized Encoding1UC San Diego, San Diego, CA, United States, 2GE Healthcare, San Diego, CA, United States, 3VA Health system, San Diego, CA, United States
Synopsis
MR imaging of lung is challenging due to its short T2* and low proton density. In this study, we proposed a free breathing phase-resolved lung imaging technique using a 3D UTE sequence with an efficient Cones trajectory. Five different respiration phases were resolved using a self-navigator technique, and the corresponding lung images were reconstructed with a combined parallel imaging and compressed sensing algorithm. Small pulmonary vessels were well-displayed in these images.
Introduction
Computed tomography (CT), the golden standard modality for lung imaging, offers excellent spatial and temporal resolution. However, due to the ionizing radiation exposure associated with CT, this imaging modality is not recommended for pediatric patients or for patients requiring longitudinal follow-up imaging (1). Magnetic resonance imaging (MRI), meanwhile, shows excellent soft tissue contrast and avoids ionizing radiation exposure, but is challenging for lung imaging due to its short T2* and low proton density (2). Clinical MRI sequences, such as gradient recalled echo (GRE) sequences with echo times (TEs) longer than 1 ms, suffer significant signal loss in lung imaging. Ultrashort echo time sequences with TEs less than 100 µs have been used successfully in short T2/T2* imaging (3) and demonstrated great potential for application in lung imaging. Phase-resolved UTE lung imaging with self-navigation techniques have been developed by several groups, with most research having focused on UTE imaging with a radial trajectory (4-7). In this study, we propose a free breathing phase-resolved lung imaging using a highly efficient Cones trajectory (8-9). This UTE sequence employs a short rectangular pulse for signal excitation, followed by 3D spiral trajectories sampled on the Cones which allow volumetric lung imaging in a time-efficient way.Methods and Materials
The 3D UTE Cones sequence can be found in Figure 1. A short rectangular pulse with a duration of 20 μs is used for signal excitation of each spoke. This is followed by a ramp-sampling with a minimal nominal TE of 32 µs. The gradient encoding forms a spiral k-space trajectory with 3D conical view ordering (8-9). For the lung imaging (see Figure 2), a bit-reversed algorithm was used to randomize the gradient encoding ordering in Cones (5). The image in the first row in Figure 2 illustrates the 3D k-space including all the Cones spokes. The second row of Figure 2 shows the k-space trajectories in different phase groups. The randomly ordered data sampling ensures each group of spokes is uniformly distributed in k-space.The sequence was implemented on a 3T GE MR750 scanner. A 32-channel abdomen coil was used for signal reception (body coil was used for signal excitation). Four male volunteers (aged 28- to 47-years-old) were recruited in this study. During the scan, each volunteer was asked to breathe normally. The 3D UTE Cones sequence employed the following parameters: coronal plane, TR/TE = 4/0.032 ms, field of view (FOV) = 36×36×18 cm3, acquisition matrix = 240×240×120, flip angle (FA) = 4º, and scan time = 6 min.
The respiration was estimated from the phase of the center of k-space (e.g., the first point, also called the DC term). A low pass filter was applied to the raw phase and the cut-off frequency was ranged from 0.1 to 0.5 Hz (7). The filtered respiration curve was then segmented into five phases and the lung images in each phase were reconstructed using a combined parallel imaging and compressed sensing algorithm (10).
Results and Discussion
Figure 3 shows the estimated respiration using the phase of DC acquired from a 37-year-old healthy male volunteer. Panel A shows the raw phase of DC (i.e., the blue curve) received from a coil close to the liver. The red curve in panel A is the corresponding low pass-filtered phase representing the respiration. The respiration was segmented into five phases as shown with green lines in panel B. Phases 1 and 5 correspond to the end of inspiration and expiration, respectively.Figure 4 shows the representative sagittal images of the five different respiratory motion phases from the same volunteer. The green and blue lines denote the location of the diaphragms at end-expiration and end-inspiration, respectively. All the phase-resolved images displayed the small lung vessels very well. The images at the end expiration show the best quality with a sharp vessel boundary.
Figure 5 shows the maximum intensity projection (MIP) lung images reconstructed from the end-expiration phase. The small pulmonary vessels are well-displayed in these images.
Conclusion
The 3D UTE Cones sequence with a randomized ordering scheme can provide self-navigated and phase-resolved high-resolution lung imaging, which may be potentially useful in clinical practice.Acknowledgements
The authors acknowledge grant support from NIH (R01AR062581, R01AR068987, R01AR075825, and R21AR075851), VA Clinical Science and Rehabilitation Research and Development Services (Merit Awards I01CX001388 and I01RX002604), and GE Healthcare.References
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