Background

Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations.

Purpose

To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator.

Study type

Prospective feasibility study.

Population/subjects

Three human volunteers.

Field strength/sequence

3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6.

Assessment

Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE).

Statistical tests

Direct comparison of NMSE values.

Results

High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates.

Data conclusion

Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots.

Level of evidence

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

To evaluate the performance of an advanced method for correction of inhomogeneous static magnetic field induced distortion in echo-planar imaging (EPI), applied to diffusion-weighted MRI (DWI) of the breast.An algorithm for distortion correction based on the symmetry of the distortion induced by static field inhomogeneity when the phase encoding polarity is reversed was evaluated in 36 data sets of patients who received an MRI examination that included DWI (b = 0 and 700 s/mm(2) ) and an extra b = 0 s/mm(2) sequence with opposite phase encoding polarity. The decrease of the L2 -square norm after correction between opposed phase encoding b = 0 images was calculated. Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images was calculated before and after correction.The L2 -square norm between different phase encoding polarities for b = 0 images was reduced 94.3% on average after distortion correction. Furthermore, Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images increased significantly after correction for all cases (P < 0.001).Geometric distortion correction in DWI of the breast results in higher similarity of DWI to anatomical non-EPI T2 -weighted images and would potentially allow for a more reliable lesion segmentation mapping among different MRI modalities.

BACKGROUND:High b-value diffusion-weighted imaging has application in the detection of cancerous tissue across multiple body sites. Diffusional kurtosis and bi-exponential modeling are two popular model-based techniques, whose performance in relation to each other has yet to be fully explored. PURPOSE:To determine the relationship between excess kurtosis and signal fractions derived from bi-exponential modeling in the detection of suspicious prostate lesions. MATERIAL AND METHODS:This retrospective study analyzed patients with normal prostate tissue (n = 12) or suspicious lesions (n = 13, one lesion per patient), as determined by a radiologist whose clinical care included a high b-value diffusion series. The observed signal intensity was modeled using a bi-exponential decay, from which the signal fraction of the slow-moving component was derived ( SFs). In addition, the excess kurtosis was calculated using the signal fractions and ADCs of the two exponentials ( KCOMP). As a comparison, the kurtosis was also calculated using the cumulant expansion for the diffusion signal ( KCE). RESULTS:Both K and KCE were found to increase with SFs within the range of SFs commonly found within the prostate. Voxel-wise receiver operating characteristic performance of SFs, KCE, and KCOMP in discriminating between suspicious lesions and normal prostate tissue was 0.86 (95% confidence interval [CI] = 0.85 - 0.87), 0.69 (95% CI = 0.68-0.70), and 0.86 (95% CI = 0.86-0.87), respectively. CONCLUSION:In a two-component diffusion environment, KCOMP is a scaled value of SFs and is thus able to discriminate suspicious lesions with equal precision . KCE provides a computationally inexpensive approximation of kurtosis but does not provide the same discriminatory abilities as SFs and KCOMP.