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. 2017 Feb;36(2):549-559.
doi: 10.1109/TMI.2016.2622238. Epub 2016 Oct 27.

Body Diffusion Weighted Imaging Using Non-CPMG Fast Spin Echo

Body Diffusion Weighted Imaging Using Non-CPMG Fast Spin Echo

Eric K Gibbons et al. IEEE Trans Med Imaging. 2017 Feb.

Abstract

SS-FSE is a fast technique that does not suffer from off-resonance distortions to the degree that EPI does. Unlike EPI, SS-FSE is ill-suited to diffusion weighted imaging (DWI) due to the Carr-Purcell-Meiboom-Geill (CPMG) condition. Non-CPMG phase cycling does accommodate SS-FSE and DWI but places constraints on reconstruction, which are resolved here through parallel imaging. Additionally, improved echo stability can be achieved by using short duration and highly selective DIVERSE radiofrequency pulses. Here, signal-to-noise ratio (SNR) comparisons between EPI and nCPMG SS-FSE acquisitions and reconstruction techniques give similar values. Diffusion imaging with nCPMG SS-FSE gives similar SNR to an EPI acquisition, though apparent diffusion coefficient values are higher than seen with EPI. In vivo images have good image quality with little distortion. This method has the ability to capture distortion-free DWI images near areas of significant off-resonance as well as preserve adequate SNR. Parallel imaging and DIVERSE refocusing RF pulses allow shorter ETL compared to previous implementations and thus reduces phase encode direction blur and SAR accumulation.

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Figures

Fig. 1
Fig. 1
Aliasing artifacts after reconstruction. These artifacts arise from the quadrature component alternating in sign in each readout line due to the nCPMG phase cycling (Eq. (8)). A trivial reconstruction of conjugating the quadrature component is non-achievable due to the unknown receiver phases.
Fig. 2
Fig. 2
Data separation reconstruction flow. The even and odd echoes are separated in order to create two distinct reconstruction problems. SENSE reconstruction is facilitated by coil maps generated from ESPIRiT calibration on fully-sampled FSE data (not shown in this figure).
Fig. 3
Fig. 3
Sequence design considerations: a) Various RF refocusing pulses considered for this sequence. b–d) The corresponding spin echo profiles for each RF refocusing pulse at b) 0Hz, c) 100Hz, and d) 200Hz off-resonance. In each plot, the flip angle threshold (|sin(120°/2)|2) to maintain a stable echo train is shown. e) First portion of the proposed sequence: a spin echo diffusion pulse with diffusion lobes played out simultaneously to achieve maximum b-value while lowering TE. The FSE readout consists of DV-SLR pulses with both ω (frequency modulation) and θ (phase modulation) channels being used to improve the fidelity of phase modulation accuracy provided by the MR system. Each refocusing pulse in the FSE train has a phase ϕ to achieve signal stability despite loss of the CPMG condition. Note: The DV-SLR pulse achieves the level of selectivity of the conventional NV-SLR pulse, but also maintains the short duration of the m-sinc pulse.
Fig. 4
Fig. 4
Extended phase graph (EPG) simulation showing the signal behavior with a T1/T2 values of 1000 ms/200 ms. In each plot the phase of the tipdown 90° pulse was varied from 0° to 90° mimicking the random phase accrual from diffusion weighting. a) traditional CPMG phase cycling. b) nCPMG phase cycling.
Fig. 5
Fig. 5
Comparisons between EPI, the previously used nCPMG DEASM, and the proposed split echo SENSE acquisition and reconstruction. The EPI images yield the sharpest images but suffer from the greatest geometric distortion. Both nCPMG images give an image without geometric distortions. It is seen that the split echo SENSE method yields a sharper image in the phase encode direction.
Fig. 6
Fig. 6
Phantom image comparisons between m-sinc, NV-SLR, and DV-SLR refocusing images using the split echo SENSE reconstruction. It is seen that the DV-SLR images suffer the least from the intermediate aliasing artifacts seen in the m-sinc image (shown by the red arrows) while maintaining the similar edge sharpness in the phase encode direction seen in the m-sinc case.
Fig. 7
Fig. 7
Reconstruction examples with a grid phantom. When viewing the individual odd and even echoes images prior to averaging (b and c), there is very little difference between the two. In the cases where a standard Fourier reconstruction is used (d–f) with nCPMG SS-FSE acquisition, the quadrature component signal is aliased as expected. However, in the cases where a nCPMG SS-FSE acquisition is used with the proposed parallel imaging reconstruction (g–i), the aliasing is resolved.
Fig. 8
Fig. 8
Pixel-wise SNR maps comparing various acquistion and reconstruction schemes using an oil body phantom as well as coil geometry g-factor maps. a: standard CPMG FSE acquisition and Fourier reconstruction. b: coil geometry g-factor maps. c: standard CPMG FSE acquisition but reconstructed with the proposed ESPIRiT/SENSE approach. d: nCPMG FSE acquisition and proposed ESPIRiT/SENSE approach.
Fig. 9
Fig. 9
SNR and ADC maps using a doped agar ball phantom as well as an ex vivo (pork shoulder) phantom. The primary aim of the doped agar ball phantom images are to demonstrate SNC and ADC comparisons using a homogenous phantom. The ex vivo phantom images demonstrate the effects of single- versus multi-slice nCPMG SS-FSE acquisitions (namely, the impact on magnetization transfer and slice cross-talk) compared to a multi-slice EPI protocol. Note: an ROI for statistical purposes is drawn over one doped agar ball phantom image as well as one ex vivo phantom image using a red box. The same ROI was used on all respective images for determining mean, standard deviation, and statistical significance (see Table 1).
Fig. 10
Fig. 10
Axial slices ncPMG SS-FSE with EPI with b = 700s/mm2 diffusion weighted images. (Patient A) Two year old patient after neuroblastoma resection. (Patient B) Five week old patient with biliary dilation and a lesion in the liver (yellow arrow). (Patient C) Twenty one year old patient with cirrhosis of the liver, with the lesion identifiable in each image (green arrow). Areas of off resonance distortion in the EPI images are marked with a red arrow.

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References

    1. Harry VN, Deans H, Ramage E, Parkin DE, Gilbert FJ. Magnetic resonance imaging in gynecological oncology. International Journal of Gynecological Cancer. 2009;19(2):186–193. - PubMed
    1. Shinagare AB, Ip IK, Raja AS, Sahni VA, Banks P, Khorasani R. Use of CT and MRI in emergency department patients with acute pancreatitis. Abdominal Imaging. 2015;40(2):272–277. - PubMed
    1. Le Bihan D, Breton E, et al. Imagerie de diffusion in-vivo par resonance magnetique nucleaire. Comptes-Rendus de l’Académie des Sciences. 1985;93(5):27–34.
    1. Eastwood JD, Lev MH, Wintermark M, Fitzek C, Barboriak DP, Delong DM, Lee TY, Azhari T, Herzau M, Chilukuri VR, et al. Correlation of early dynamic CT perfusion imaging with whole-brain MR diffusion and perfusion imaging in acute hemispheric stroke. American Journal of Neuroradiology. 2003;24(9):1869–1875. - PMC - PubMed
    1. Attariwala R, Picker W. Whole body MRI: Improved lesion detection and characterization with diffusion weighted techniques. Journal of Magnetic Resonance Imaging. 2013;38(2):253–268. - PMC - PubMed

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