With recent advances in ultrashort time echo (UTE) imaging, it has become feasible to perform quantitative measurements of short T2* decay to draw clinically meaningful information (i.e. meniscus¹ and tendon²). However, the acquisition of multiple UTE and gradient echo images at different TEs with sufficient spatial resolution is very time consuming (e.g., 20-80 minutes per scan). In this study we propose a novel multi-echo UTE imaging scheme based on hybrid encoding, which allows simultaneous measurement of short and long T2* components with highly efficient sampling.In the proposed method, we use a ramped hybrid encoding (RHE)³ scheme where gradients are applied before the RF pulse and ramped up to the maximum gradient amplitude immediately after RF excitation to optimize per-excitation encoding time as the pulse sequence diagram (PSD) shows in Figure 1-a. The missing data in central k-space (during RF coil deadtime) is measured by Cartesian single point imaging (SPI), and the outer k-space is acquired by radial frequency encoding as shown in Figure 1-b. The diameter of SPI sampled region (N_SPI) is required to be larger than $$γ/πFOV_D ∫_o^{TE}G_{max}(t)dt$$ to avoid aliasing (fold-over) artifact at the desired time echo (TE), where FOV_D denotes a desired FOV, and G_max is maximum phase encoding gradient amplitude. Conversely, the density of SPI encoding (determined by NSPI) determines the availability of multiple TEs; where a larger N_SPI enables a wider range of TEs available without aliasing, and vice versa. In the proposed method, the SPI region is intentionally oversampled to allow a wide selection of TEs at which images can be reconstructed without aliasing, so that T2* decay can be resolved using those images. The DTE is equivalent to the data sampling rate (2µs in the utillized MR system), and is vastly lower than conventional multi-echo imaging. In addition, a gradient echo (GRE) imaging scheme is applied to acquire images at later TEs, which allows estimation of longer T2* components. Figure 2-a shows the PSD for UTE acquisitions followed by a gradient echo train. Note that a extremely large number of TEs are available owing to the oversampled SPI in both UTE and GRE acquisitions as indicated as green color in Figure 2-b, which is beneficial in parameter estimation for multi exponential decay. To evaluate the proposed method, knee imaging was performed in 3.0T MRI scanner (GE MR750) using a 8 channel T/R knee coil. Spherical SPI encoding was performed with NSPI=49x49x81 with # of SPI encoding = 96,417, which yields asymmetric FOV (larger in S-I direction), and the number of frequency encoding was 45,000. Scan parameters were as following: 24µs hard pulse with flip angle=6 degree, G_max=30mT/m, G_RF=0%, TR=5.96ms, scan time=14min 3sec, readout BW=500kHz, image resolution=1x1x1mm, and FOV=200mm. In practice, approximately 750 images can be reconstructed without aliasing artifact; however, only 83 images were reconstructed over 70µs~4080µs: utilizing 37 UTE images between 70µs and 220µs, and 46 images at later echoes. After reconstruction pixel-wise T2* was estimated by fitting the resulting magnitude image to a bi-exponential signal decay model. Figure 3 shows reconstructed images at UTE and later echoes with matching FOV, without any aliasing artifacts. Figure 4 shows estimated short T2* and long T2* in (a) medial meniscus and (b) femoris tendon. The short T2* estimate in the medial meniscus was 118.2±125.9µs, and the long T2* was 8.49±3.97ms. In femoris tendon, short T2* estimate was 548.4±233.9µs, while long T2* estimate was 7.24±4.59ms. Short T2* fraction was 32.7±21.3% and 64.5±22.5% in meniscus and tendon, respectively.In this study, we proposed a new acquisition to simultaneously estimate short and long T2* components. The use of oversampled SPI with hybrid encoding permitted acquisitions with highly efficient multi-TE sampling. In future work, the abundance of temporal data will allow signal fitting with more complex models such as multi exponential decay model including correction of fat and water signal components. Addtionally, while scan time is reduced compared to conventional methods, the additional scan time required by SPI encoding can be reduced by employing acceleration techniques such as parallel imaging or model-based 4D compressed sensing⁴.