Improved Resting-State Functional MRI Using Multi-Echo Echo-Planar Imaging on a Compact 3T MRI Scanner with High-Performance Gradients.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

A geometric view of signal sensitivity metrics in multi-echo fMRI.

In multi-echo fMRI (ME-fMRI), two metrics have been widely used to measure the performance of various acquisition and analysis approaches. These are temporal SNR (tSNR) and differential contrast-to-noise ratio (dCNR). A key step in ME-fMRI is the weighted combination of the data from multiple echoes, and prior work has examined the dependence of tSNR and dCNR on the choice of weights. However, most studies have focused on only one of these two metrics, and the relationship between the two metrics has not been examined. In this work, we present a geometric view that offers greater insight into the relation between the two metrics and their weight dependence. We identify three major regimes: (1) a tSNR robust regime in which tSNR is robust to the weight selection with most weight variants achieving close to optimal performance, whereas dCNR shows a pronounced dependence on the weights with most variants achieving suboptimal performance; (2) a dCNR robust regime in which dCNR is robust to the weight selection with most weight variants achieving close to optimal performance, while tSNR exhibits a strong dependence on the weights with most variants achieving significantly lower than optimal performance; and (3) a within-type robust regime in which both tSNR and dCNR achieve nearly optimal performance when the form of the weights are variants of their respective optimal weights and exhibit a moderate decrease in performance for other weight variants. Insight into the behavior observed in the different regimes is gained by considering spherical representations of the weight dependence of the components used to form each metric. For multi-echo acquisitions, dCNR is shown to be more directly related than tSNR to measures of CNR and signal-to-noise ratio (SNR) for task-based and resting-state fMRI scans, respectively.

Fully Integrated Quantitative Multiparametric Analysis of Non-Small Cell Lung Cancer at 3-T PET/MRI: Toward One-Stop-Shop Tumor Biological Characterization at the Supervoxel Level.

INTRODUCTION: The aim of this study was to study the feasibility of a fully integrated multiparametric imaging framework to characterize non-small cell lung cancer (NSCLC) at 3-T PET/MRI. PATIENTS AND METHODS: An 18F-FDG PET/MRI multiparametric imaging framework was developed and prospectively applied to 11 biopsy-proven NSCLC patients. For each tumor, 12 parametric maps were generated, including PET full kinetic modeling, apparent diffusion coefficient, T1/T2 relaxation times, and DCE full kinetic modeling. Gaussian mixture model-based clustering was applied at the whole data set level to define supervoxels of similar multidimensional PET/MRI behaviors. Taking the multidimensional voxel behaviors as input and the supervoxel class as output, machine learning procedure was finally trained and validated voxelwise to reveal the dominant PET/MRI characteristics of these supervoxels at the whole data set and individual tumor levels. RESULTS: The Gaussian mixture model-based clustering clustering applied at the whole data set level (17,316 voxels) found 3 main multidimensional behaviors underpinned by the 12 PET/MRI quantitative parameters. Four dominant PET/MRI parameters of clinical relevance (PET: k2, k3 and DCE: ve, vp) predicted the overall supervoxel behavior with 97% of accuracy (SD, 0.7; 10-fold cross-validation). At the individual tumor level, these dimensionality-reduced supervoxel maps showed mean discrepancy of 16.7% compared with the original ones. CONCLUSIONS: One-stop-shop PET/MRI multiparametric quantitative analysis of NSCLC is clinically feasible. Both PET and MRI parameters are useful to characterize the behavior of tumors at the supervoxel level. In the era of precision medicine, the full capabilities of PET/MRI would give further insight of the characterization of NSCLC behavior, opening new avenues toward image-based personalized medicine in this field.

Improving the Breath-Holding CVR Measurement Using the Multiband Multi-Echo EPI Sequence.

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is commonly used to measure cerebrovascular reactivity (CVR), which can convey insightful information about neurovascular health. Breath-holding (BH) has been shown to be a practical vasodilatory stimulus for measuring CVR in clinical settings. The conventional BOLD fMRI approach has some limitations, however, such as susceptibility-induced signal dropout at air tissue interfaces and low BOLD sensitivity especially in areas of low T 2 * . These drawbacks can potentially be mitigated with multi-echo sequences, which acquire several images at different echo times in one shot. When combined with multiband techniques, high temporal resolution images can be acquired. This study compared an advanced multiband multi-echo (MBME) echo planar imaging (EPI) sequence with an existing multiband single-echo (MB) sequence to evaluate the repeatability and sensitivity of BH activation and CVR mapping. Images were acquired from 28 healthy volunteers, of which 18 returned for repeat imaging. Both MBME and MB data were pre-processed using both standard and advanced denoising techniques. The MBME data was further processed by combining echoes using a T 2 * -weighted approach and denoising using multi-echo independent component analysis. BH activation was calculated using a general linear model and the respiration response function. CVR was computed as the percent change related to the activation. To account for differences in CVR related to TE, relative CVR (rCVR) was computed and normalized to the mean gray matter CVR. Test-retest metrics were assessed with the Dice coefficient, rCVR difference, within subject coefficient of variation, and the intraclass correlation coefficient. Our findings demonstrate that rCVR for MBME scans were significantly higher than for MB scans across most of the gray matter. In areas of high susceptibility-induced signal dropout, however, MBME rCVR was significantly less than MB rCVR due to artifactually high rCVR for MB scans in these regions. MBME rCVR showed improved test-retest metrics compared with MB. Overall, the MBME sequence displayed superior BOLD sensitivity, improved specificity in areas of signal dropout on MBME scans, enhanced reliability, and reduced variability across subjects compared with MB acquisitions. Our results suggest that the MBME EPI sequence is a promising tool for imaging CVR.

Improved resting state functional connectivity sensitivity and reproducibility using a multiband multi-echo acquisition.

Recent advances in functional MRI techniques include multiband (MB) imaging and multi-echo (ME) imaging. In MB imaging multiple slices are acquired simultaneously leading to significant increases in temporal and spatial resolution. Multi-echo imaging enables multiple echoes to be acquired in one shot, where the ME images can be used to denoise the BOLD time series and increase BOLD sensitivity. In this study, resting state fMRI (rs-fMRI) data were collected using a combined MBME sequence and compared to an MB single echo sequence. In total, 29 subjects were imaged, and 18 of them returned within two weeks for repeat imaging. Participants underwent one MBME scan with three echoes and one MB scan with one echo. Both datasets were processed using standard denoising and advanced denoising. Advanced denoising included multi-echo independent component analysis (ME-ICA) for the MBME data and ICA-AROMA for the MB data. Resting state functional connectivity (RSFC) was evaluated using both selective seed-based and whole grey matter (GM) region-of-interest (ROI) based approaches. The reproducibility of connectivity metrics was also analyzed in the repeat subjects. In addition, functional connectivity density (FCD), a data-driven approach that counts the number of significant connections, both within a local cluster and globally, with each voxel was analyzed. Regardless of the standard or advanced denoising technique, all seed-based RSFC was significantly higher for MBME compared to MB. Much more GM ROI combinations showed significantly higher RSFC for MBME vs. MB. Reproducibility, evaluated using the dice coefficient was significantly higher for MBME relative to MB data. Finally, FCD was also higher for MBME vs. MB data. This study showed higher RSFC for MBME vs. MB data using selected seed-based, whole GM ROI-based, and data-driven approaches. Reproducibility found also higher for MBME data. Taken together, these results indicate that MBME is a promising technique for rs-fMRI.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas.

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T1 -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR2 *(t) and ΔR2 (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR2 *- and ΔR2 -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR2 *- and ΔR2 -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Detecting Task Functional MRI Activation Using the Multiband Multiecho (MBME) Echo-Planar Imaging (EPI) Sequence.

BACKGROUND: Blood oxygen level-dependent (BOLD) functional MRI (fMRI) has been widely applied to detect brain activations. Recent advances in multiband (MB) and multiecho (ME) techniques have greatly improved fMRI methods. MB imaging improves temporal and/or spatial resolution, while ME imaging has been shown to improve BOLD sensitivity. This study aimed to evaluate the novel MBME echo planar imaging (EPI) sequence utilizing MB and ME simultaneously to determine if the MBME outperform the MB single echo (MBSE) sequence for task fMRI. PURPOSE: To compare the performance of MBME with MBSE in a task fMRI study. STUDY TYPE: Prospective. POPULATION: A total of 29 healthy volunteers aged 20-46 years (9 male, 20 female). FIELD STRENGTH/SEQUENCE: MBSE and MBME gradient-echo EPI sequences were applied at 3T. Additional T1 -weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) was collected. ASSESSMENT: A checkerboard visual task was presented during the functional MBSE and MBME scans. The MBME or MBSE signal was evaluated using the temporal signal-to-noise ratio (tSNR). Task activation was evaluated using the z-score, volume, sensitivity, and specificity. Test-retest metrics of task activation were examined with the Dice coefficient (DC) and intraclass correlation coefficient (ICC) on subjects with repeated scans. STATISTICAL TESTS: A linear mixed-effects model was used to compared MBME and MBSE activation at the voxel base. The paired t-test was used to compare tSNR, activation z-score, and volume, along with sensitivity, specificity, and DC between MBSE and MBME. RESULTS: While similar task activation was detected in the visual cortex, MBME showed higher activation volume and higher sensitivity compared with MBSE (P < 0.05). ICC was higher for MBME than MBSE, while there was a trend of differences in DC (P = 0.08). DATA CONCLUSION: MBME resulted in higher task fMRI activation volume and sensitivity without losing specificity. Reliability was also higher for MBME scans compared with MBSE. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

AZTEK: Adaptive zero TE k-space trajectories.

PURPOSE: Because of short signal lifetimes and respiratory motion, 3D lung MRI is still challenging today. Zero-TE (ZTE) pulse sequences offer promising solutions as they overcome the issue of short T2∗ . Nevertheless, as they rely on continuous readout gradients, the trajectories they follow in k-space are not adapted to retrospective gating and inferred motion correction. THEORY AND METHODS: We propose AZTEK (adaptive ZTE k-space trajectories), a set of 3D radial trajectories featuring three tuning parameters, to adapt the acquisition to any moving organ while keeping seamless transitions between consecutive spokes. Standard ZTE and AZTEK trajectories were compared for static and moving phantom acquisitions as well as for human thoracic imaging performed on 3 volunteers (1 healthy and 2 patients with lung cancer). RESULTS: For the static phantom, we observe comparable image qualities with standard and AZTEK trajectories. For the moving phantom, spatially coherent undersampling artifacts observed on gated images with the standard trajectory are alleviated with AZTEK. The same improvement in image quality is obtained in human, so details are more delineated in the lung with the use of the adaptive trajectory. CONCLUSION: The AZTEK technique opens the possibility for 3D dynamic ZTE lung imaging with retrospective gating. It enables us to uniformly sample the k-space for any arbitrary respiratory motion gate, while preserving static image quality, improving dynamic image quality and guaranteeing continuous readout gradient transitions between spokes, which makes it appropriate to ZTE.

Publisher Correction: 3D Magnetic Resonance Spirometry.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

18F-FDG PET and DCE kinetic modeling and their correlations in primary NSCLC: first voxel-wise correlative analysis of human simultaneous [18F]FDG PET-MRI data.

OBJECTIVES: To decipher the correlations between PET and DCE kinetic parameters in non-small-cell lung cancer (NSCLC), by using voxel-wise analysis of dynamic simultaneous [18F]FDG PET-MRI. MATERIAL AND METHODS: Fourteen treatment-naïve patients with biopsy-proven NSCLC prospectively underwent a 1-h dynamic [18F]FDG thoracic PET-MRI scan including DCE. The PET and DCE data were normalized to their corresponding T1-weighted MR morphological space, and tumors were masked semi-automatically. Voxel-wise parametric maps of PET and DCE kinetic parameters were computed by fitting the dynamic PET and DCE tumor data to the Sokoloff and Extended Tofts models respectively, by using in-house developed procedures. Curve-fitting errors were assessed by computing the relative root mean square error (rRMSE) of the estimated PET and DCE signals at the voxel level. For each tumor, Spearman correlation coefficients (rs) between all the pairs of PET and DCE kinetic parameters were estimated on a voxel-wise basis, along with their respective bootstrapped 95% confidence intervals (n = 1000 iterations). RESULTS: Curve-fitting metrics provided fit errors under 20% for almost 90% of the PET voxels (median rRMSE = 10.3, interquartile ranges IQR = 8.1; 14.3), whereas 73.3% of the DCE voxels showed fit errors under 45% (median rRMSE = 31.8%, IQR = 22.4; 46.6). The PET-PET, DCE-DCE, and PET-DCE voxel-wise correlations varied according to individual tumor behaviors. Beyond this wide variability, the PET-PET and DCE-DCE correlations were mainly high (absolute rs values > 0.7), whereas the PET-DCE correlations were mainly low to moderate (absolute rs values < 0.7). Half the tumors showed a hypometabolism with low perfused/vascularized profile, a hallmark of hypoxia, and tumor aggressiveness. CONCLUSION: A dynamic "one-stop shop" procedure applied to NSCLC is technically feasible in clinical practice. PET and DCE kinetic parameters assessed simultaneously are not highly correlated in NSCLC, and these correlations showed a wide variability among tumors and patients. These results tend to suggest that PET and DCE kinetic parameters might provide complementary information. In the future, this might make PET-MRI a unique tool to characterize the individual tumor biological behavior in NSCLC.

3D Magnetic Resonance Spirometry.

Spirometry is today the gold standard technique for assessing pulmonary ventilatory function in humans. From the shape of a flow-volume loop measured while the patient is performing forced respiratory cycles, the Forced Vital Capacity (FVC) and the Forced Expiratory Volume in one second (FEV1) can be inferred, and the pulmonologist is able to detect and characterize common respiratory afflictions. This technique is non-invasive, simple, widely available, robust, repeatable and reproducible. Yet, its outcomes rely on the patient's cooperation and provide only global information over the lung. With 3D Magnetic Resonance (MR) Spirometry, local ventilation can be assessed by MRI anywhere in the lung while the patient is freely breathing. The larger dimensionality of 3D MR Spirometry advantageously allows the extraction of original metrics that characterize the anisotropic and hysteretic regional mechanical behavior of the lung. Here, we demonstrated the potential of this technique on a healthy human volunteer breathing along different respiratory patterns during the MR acquisition. These new results are discussed with lung physiology and recent pulmonary CT data. As respiratory mechanics inherently support lung ventilation, 3D MR Spirometry may open a new way to non-invasively explore lung function while providing improved diagnosis of localized pulmonary diseases.

Diffusion-weighted Imaging Voxelwise-matched Analyses of Lung Cancer at 3.0-T PET/MRI: Reverse Phase Encoding Approach for Echo-planar Imaging Distortion Correction.

Background PET/MRI has drawn increasing interest in thoracic oncology due to the simultaneous acquisition of PET and MRI data. Geometric distortions related to diffusion-weighted imaging (DWI) limit the evaluation of voxelwise multimodal analyses. Purpose To assess the effectiveness of reverse phase encoding in correcting DWI geometric distortion for multimodal PET/MRI voxelwise lung tumor analyses. Materials and Methods In this prospective study, reverse phase encoding method was implemented with 3.0-T PET/MRI to correct geometric distortions related to DWI. The method was validated in dedicated phantom and then applied to 12 consecutive patients (mean age, 66 years ± 13 [standard deviation]; 10 men) suspected of having lung cancer who underwent fluorodeoxyglucose PET/MRI between October 2018 and April 2019. The effects on DWI-related image matching and apparent diffusion coefficient (ADC) regional map computation were assessed. Consequences on multimodal PET/MRI voxelwise lung tumor analyses were evaluated. Spearman correlation coefficients (rs) between the standardized uptake value (SUV) and ADC data corrected for distortion were computed from optimal realigned DWI PET data, along with bootstrap confidence intervals. Results Phantom results showed that in highly distorted areas, correcting the distortion significantly reduced the mean error against the ground truth (-25% ± 10.6 to -18.4% ± 12.6; P < .001) and the number of voxels with more than 20% error (from 85.3% to 31.4%). In the 12 patients, the coregistration of multimodal PET/MRI tumor data was improved by using the reverse phase encoding method (0.4%-44%). In all tumors, voxelwise correlations (rs) between ADC and SUV revealed null or weak monotonic relationships (mean rs of 0.016 ± 0.24 with none above 0.5). Conclusion Reverse phase encoding is a simple-to-implement method for improved diffusion-weighted multimodal PET/MRI voxelwise-matched analyses in lung cancer. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Colletti in this issue.

ZTE MR-based attenuation correction in brain FDG-PET/MR: performance in patients with cognitive impairment.

OBJECTIVE: One of the main challenges of integrated PET/MR is to achieve an accurate PET attenuation correction (AC), especially in brain acquisition. Here, we evaluated an AC method based on zero echo time (ZTE) MRI, comparing it with the single-atlas AC method and CT-based AC, set as reference. METHODS: Fifty patients (70 ± 11 years old, 28 men) underwent FDG-PET/MR examination (SIGNA PET/MR 3.0 T, GE Healthcare) as part of the investigation of suspected dementia. They all had brain computed tomography (CT), 2-point LAVA-flex MRI (for atlas-based AC), and ZTE-MRI. Two AC methods were compared with CT-based AC (CTAC): one based on a single atlas, one based on ZTE segmentation. Impact on brain metabolism was evaluated using voxel and volumes of interest-based analyses. The impact of AC was also evaluated through comparisons between two subgroups of patients extracted from the whole population: 15 patients with mild cognitive impairment and normal metabolic pattern, and 22 others with metabolic pattern suggestive of Alzheimer disease, using SPM12 software. RESULTS: ZTE-AC yielded a lower bias (3.6 ± 3.2%) than the atlas method (4.5 ± 6.1%) and lowest interindividual (4.6% versus 6.8%) and inter-regional (1.4% versus 2.6%) variabilities. Atlas-AC resulted in metabolism overestimation in cortical regions near the vertex and cerebellum underestimation. ZTE-AC yielded a moderate metabolic underestimation mainly in the occipital cortex and cerebellum. Voxel-wise comparison between the two subgroups of patients showed that significant difference clusters had a slightly smaller size but similar locations with PET images corrected with ZTE-AC compared with those corrected with CT, whereas atlas-AC images showed a notable reduction of significant voxels. CONCLUSION: ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia. KEY POINTS: • The ZTE-based AC improved the accuracy of the metabolism quantification in PET compared with the atlas-AC method. • The overall uptake bias was 21% lower when using ZTE-based AC compared with the atlas-AC method. • ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia.

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units ([Formula: see text]) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous µ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into [Formula: see text] was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of [Formula: see text] corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Multi-echo EPI of human fear conditioning reveals improved BOLD detection in ventromedial prefrontal cortex.

Standard T2* weighted functional magnetic resonance imaging (fMRI) performed with echo-planar imaging (EPI) suffers from signal loss in the ventromedial prefrontal cortex (vmPFC) due to macroscopic field inhomogeneity. However, this region is of special interest to affective neuroscience and psychiatry. The Multi-echo EPI (MEPI) approach has several advantages over EPI but its performance against EPI in the vmPFC has not yet been examined in a study with sufficient statistical power using a task specifically eliciting activity in this region. We used a fear conditioning task with MEPI to compare the performance of MEPI and EPI in vmPFC and control regions in 32 healthy young subjects. We analyzed activity associated with short (12ms), standard (29ms) and long (46ms) echo times, and a voxel-wise combination of these three echo times. Behavioral data revealed successful differentiation of the conditioned versus safety stimulus; activity in the vmPFC was shown by the contrast "safety stimulus > conditioned stimulus" as in previous research and proved significantly stronger with the combined MEPI than standard single-echo EPI. Then, we aimed to demonstrate that the additional cluster extent (ventral extension) detected in the vmPFC with MEPI reflects activation in a relevant cluster (i.e., not just non-neuronal noise). To do this, we used resting state data from the same subjects to show that the time-course of this region was both connected to bilateral amygdala and the default mode network. Overall, we demonstrate that MEPI (by means of the weighted sum combination approach) outperforms standard EPI in vmPFC; MEPI performs always at least as good as the best echo time for a given brain region but provides all necessary echo times for an optimal BOLD sensitivity for the whole brain. This is relevant for affective neuroscience and psychiatry given the critical role of the vmPFC in emotion regulation.

Real valued diffusion-weighted imaging using decorrelated phase filtering.

PURPOSE: Because of the intrinsic low signal-to-noise ratio in diffusion-weighted imaging (DWI), magnitude processing often causes an overestimation of the signal's amplitude. This results in low-estimation accuracy of diffusion models and reduced contrast because of a superposition of the image signal and the noise floor. We adopt a new phase correction (PC) technique that yields real valued diffusion data while maintaining a Gaussian noise distribution. METHODS: We conduct simulations of the noise propagation in the echo-planar imaging reconstruction chain to determine the spatial noise correlation in the image. Using the correlation pattern, optimized filter kernels are derived to estimate the true phase of the signal in each voxel. Furthermore, we adopt an outlier detection technique to replace the real value by the magnitude in case of substantial signal loss resulting from incorrect PC. RESULTS: The benefits of our method are demonstrated on Monte Carlo simulations, DWI data acquired from healthy volunteer experiments, estimated parameters of the diffusion kurtosis imaging model, and the model-free diffusion spectrum imaging technique. The improved PC approach significantly reduces the noise bias and only slightly increases the sensitivity to local phase variations. CONCLUSION: PC can enhance the usefulness of higher b-values, allowing deeper insights into tissue microstructure. Magn Reson Med 77:559-570, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes.

PURPOSE: Diffusional kurtosis imaging (DKI) is an approach to characterizing the non-Gaussian fraction of water diffusion in biological tissue. However, DKI is highly susceptible to the low signal-to-noise ratio of diffusion-weighted images, causing low precision and a significant bias due to Rician noise distribution. Here, we evaluate precision and bias using weighted linear least squares fitting of different acquisition schemes including several multishell schemes, a diffusion spectrum imaging (DSI) scheme, as well as a compressed sensing reconstruction of undersampled DSI scheme. METHODS: Monte Carlo simulations were performed to study the three-dimensional distribution of the apparent kurtosis coefficient (AKC). Experimental data were acquired from one healthy volunteer with multiple repetitions, using the same acquisition schemes as for the simulations. RESULTS: The angular distribution of the bias and precision were very inhomogeneous. While axial kurtosis was significantly overestimated, radial kurtosis was underestimated. The precision of radial kurtosis was up to 10-fold lower than axial kurtosis. CONCLUSION: The noise bias behavior of DKI is highly complex and can cause overestimation as well as underestimation of the AKC even within one voxel. The acquisition scheme with three shells, suggested by Poot et al, provided overall the best performance. Magn Reson Med 76:1684-1696, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Free-breathing imaging of the heart using 2D cine-GRICS (generalized reconstruction by inversion of coupled systems) with assessment of ventricular volumes and function.

PURPOSE: To assess cardiac function by means of a novel free-breathing cardiac magnetic resonance imaging (MRI) strategy. MATERIALS AND METHODS: A stack of ungated 2D steady-state free precession (SSFP) slices was acquired during free breathing and reconstructed as cardiac cine imaging based on the generalized reconstruction by inversion of coupled systems (GRICS). A motion-compensated sliding window approach allows reconstructing cine movies with most motion artifacts cancelled. The proposed reconstruction uses prior knowledge from respiratory belts and electrocardiogram recordings and features a piecewise linear model that relates the electrocardiogram signal to cardiac displacements. The free-breathing protocol was validated in six subjects against a standard breath-held protocol. RESULTS: Image sharpness, as assessed by the image gradient entropy, was comparable to that of breath-held images and significantly better than in uncorrected images. Volumetric parameters of cardiac function in the left ventricle (LV) and right ventricle (RV) were similar, including end-systolic volumes, end-diastolic volumes and mass, stroke volumes, and ejection fractions (with differences of 3% ± 2.4 in the LV and 2.9% ± 4.4 in the RV). The duration of the free-breathing protocol was nearly the same as the breath-held protocol. CONCLUSION: Free-breathing cine-GRICS enables accurate assessment of volumetric parameters of cardiac function with efficient correction of motion.

Adaptive black blood fast spin echo for end-systolic rest cardiac imaging.

Black Blood Fast Spin Echo imaging of the heart is usually performed during mid-diastolic rest. This is a direct consequence of the long inversion time required to suppress the blood signal, which is constrained by the T(1) of the blood, and of the heart rate. To overcome these constraints, and to acquire black blood images in the end-systolic rest period, a new approach is introduced aiming at adaptively predicting the best time to prepare and acquire MR signals. It is based on a RR interval prediction algorithm and on a cardiac cycle model. The proposed method was applied to 14 healthy volunteers and is compared to a simple alternative method using a fixed delay and to the standard black blood imaging method for imaging in the mid-diastolic rest period. Results show that the proposed method offers an increased robustness in terms of trigger delay error and image quality compared to the tested simple alternative. Also, it has been shown by qualitative analysis done by an experienced observer that the right ventricle, especially the thin right ventricle free wall, is better depicted with our method than with the standard mid-diastolic rest acquisition.