Synopsis

Three-line navigator correction of Nyquist ghosts in spin-echo echo-planar imaging (SE-EPI) diffusion weighted imaging (DWI) often fails in body imaging. Several alternative strategies have been proposed including referenceless methods, which do not require any type of reference information but instead minimize a cost function based on the data itself. The purpose of this work is to assess ghost correction of undersampled (R=3) breast DWI using several referenceless methods, including minimization of SVD in k-space, image entropy, a ghost/object ratio of the image, and a combination. All four referenceless strategies outperform the standard navigator correction, providing higher quality images and unbiased ADC maps.

Introduction

Methods

Acquisition

Single-shot 2D SE-EPI DWI was acquired under IRB-approved protocols from 41 female subjects, including healthy volunteers and patients undergoing MRI for screening or treatment monitoring (Table 1). DWI was performed on a Siemens Prisma^fit 3T system with a Sentinelle 16-channel breast coil, using a protocol derived from the ACRIN 6698 clinical trial⁵: TR=8 s, TE=51/74 ms (monopolar/bipolar diffusion, N=12/29), GRAPPA acceleration R=3, acquisition time ≤ 5 min. Three-scan traces were acquired (2-3 averages) with b-values between b=0-800 s/mm². Three-line navigators were acquired with each acquisition.

Reconstruction and ghost correction

First-order ghost correction requires estimation of a linear shift and phase correction to alternating lines of k-space of the form $$$S_{corrected}(k_x,k_{y,odd}) = S_{ghost}(k_x-\kappa,k_{y,odd}) * e^{-i \phi}$$$. Method A represents the standard correction, in which the phase difference between alternating echoes of the 3-line navigator is filtered, weighted, and fit to estimate κ and ϕ.

The referenceless methods minimize a cost function $$$f_{cost}(\kappa, \phi)$$$ using a simplex minimization in Matlab (fminsearch). In method B (“Entropy”) the cost function is the image entropy^2,3; in method C (“SVD”) f_cost is the summation over the tail of singular values after rearranging k-space into GRAPPA-like kernels⁴; in method D (“Ghost/Object”) f_cost is the summation of the ratio between the image and its FOV/2-shifted replica⁶. The final method (E, “Median”) combines the referenceless methods as $$$\kappa_{median} = \text{median}(\kappa_B, \kappa_C, \kappa_D)$$$ and $$$\phi_{median} = \text{median}(\phi_B, \phi_C, \phi_D)$$$. For all referenceless methods, the GRAPPA autocalibration (ACS) data were used to estimate initial correction parameters for the undersampled data. The solutions were dynamically refined by minimizing f_cost on single-channel data after unaliasing with ghost-corrected ACS lines. ADC maps were generated using a pixel-by-pixel log-linear fit over the b-values.

Analysis

The severity of ghost artifacts was assessed by measuring the signal intensity in the background of the images determined by semi-automatic thresholding and dilation of T₁-weighted anatomical images (3D GRE). The background to noise ratio (BNR) was defined as the mean background signal compared to a case-specific noise measurement in the corner of the image. To compare method performance, the per-volume BNR measurements were fit to a linear mixed model including the effects of method, b-value, and subject BMI. All five methods were compared in a pairwise manner, adjusting for multiple comparisons using Tukey-Kramer’s method.

Results

All referenceless methods yielded reduced ghosts compared to the standard approach. Whole volume BNRs are plotted in Figure 1a on a per-slice and b-value basis. Similarly, individual BNR values were compared between the referenceless methods and standard navigator in Figure 1b. The distributions of per-volume BNRs are shown for each b-value in Figure 2.

According to the linear mixed model, the method (p<0.0001), b-value (p<0.0001), and BMI (p=0.0256) significantly affect the BNR; however, the interaction between b-value and method is not significant. The pairwise comparisons between each method are reported in Table 2. All four referenceless methods yielded lower BNR values (p<0.0001) than method A. There was no statistically significant difference between the referenceless methods (B,C,D,E), although the median method (E) yielded the lowest ghost level at all b-values.

Figure 3 shows images of a single b=0 s/mm² average and ADC maps from a single slice of two cases that represent successful and failed corrections by the linear navigator.

Discussion

Conclusions

Acknowledgements

NIH P41 EB015894

NIH R21 CA201834

References

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