A 3D IR radial FLASH technique and a model-based iterative algorithm for the reconstruction of undersampled data are demonstrated for efficient high-resolution T1 mapping of the prostate. The method is insensitive to B1 inhomogeneity and provides full coverage of the prostate volume within the time constrains of a clinical examination.
Currently, the clinical prostate MR exam is dominated by T2-weighted imaging as T1 contrast in the prostate is limited in non-contrast exams. However, for dynamic contrast enhanced (DCE) MRI, a good pre-contrast T1 map is essential to convert the MR signal intensities of the dynamic phases into contrast agent concentration. Due to clinical time constraints, a low resolution (~1.5mm in-plane, 4mm through-plane) variable flip angle (VFA) method is used for T1 mapping, with T1 maps obtained from data acquired with only 2-3 flip angles (FA). The T1 mapping accuracy of the VFA method is known to be sensitive to B1 inhomogeneity [1,2,3], which in turn affects accuracy of the DCE pharmacokinetic analysis [4].
Here we present a 3D Inversion-recovery (IR) radial FLASH technique (3D IR-radFLASH) for imaging the prostate. IR-radFLASH is based on the Look-Locker approach, which uses constant FAs and has a higher tolerance to B1 inhomogeneity. The technique takes advantage of radial undersampling and uses a model-based reconstruction to obtain accurate T1 maps with high spatial and temporal resolution covering the prostate volume within a clinically acceptable time.The 3D IR-radFLASH pulse sequence was implemented on a Siemens 3T Skyra scanner. Figure 1 shows a diagram of the sequence. It starts with an 180˚ slab-selective adiabatic inversion RF pulse, followed by data collection using a train of constant FA RF pulses and a radial trajectory with sequential view ordering in a k-z partition-first acquisition order. During the recovery period of each IR pulse, we acquire data for 25 TI groups. On each group we acquire one view/partition with the same angular orientation for all views; between groups the angular orientation of views is incremented sequentially. To complete the acquisition of all views in the group we re-invert the spins after a time delay (TD) to allow for recovery. The number of inversion periods, or measurements, M=13 yielded 13 views/partition. Since the number of views/partition is highly undersmapled we use the model-based algorithm from [6] for reconstruction of TI images from which the T1 maps are derived. Since each view within a group is associated with a different TI, the group is approximated to the average of the acquired TIs. The reconstruction algorithm was implemented on 8 Nvidia Tesla P100 GPUs using C++ with OpenCL.
3D IR-radFLASH data for a phantom and in vivo studies were acquired using the parameters listed in Table 1. A slab-selective inversion pulse with a TD of 3s was used to allow for spin recovery and avoid slab cross-talk.
For comparison, 3D VFA T1 mapping data were acquired with a Cartesian spoiled gradient-echo pulse sequence with FA={2˚,5˚,9˚}, TE=1.66ms, TR=4.57ms, FOV=23cm, receiver bandwidth=400Hz/Pixel, spatial resolution=1.60×1.44×4.36mm. A low resolution B1 map was acquired for FA correction. Total scan time was 49s.
Table 2 shows T1 estimates for a NIST phantom. T1 values obtained with the 3D IR-radFLASH method are compared to reference values obtained using an IR spin-echo method. As the table shows, T1 estimates from the 3D IR-radFLASH matches the spin echo reference.
Figure 2 shows in vivo pelvic T1 maps for 4 out of 40 slices acquired with (a) the 3D IR-radFLASH and (b) the 3D VFA methods. In both cases the prostate’s center zone (CZ) and peripheral zone (PZ) can be identified. Table 3 shows the T1 values from these two zones for both methods. The VFA method overestimates T1, while the 3D IR-radFLASH method yields T1s consistent with those reported in the literature using a variable TR (VTR) method [4]. In [4] the authors showed that the VTR method provides stable and accurate T1 values compared to the VFA method. The drawback of the VTR method is the long scan time (~10 minutes) needed for data acquisition.
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