Nonrigid motion modeling of the liver from 3-D undersampled self-gated golden-radial phase encoded MRI

Tailored and universal parallel transmit broadband pulses for homogeneous 3D excitation of the human heart at 7T

PURPOSE

To research and evaluate the performance of broadband tailored kT-point pulses (TP) and universal pulses (UP) for homogeneous excitation of the human heart at 7T.

METHODS

Relative 3DB 1 + $$ {\mathrm{B}}_1^{+} $$ -maps of the thorax were acquired from 29 healthy volunteers. TP and UP were designed using the small-tip-angle approximation for a different composition of up to seven resonance frequencies. TP were computed for each of the 29B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps, and UPs were calculated using 22B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps and tested in seven testcases. The performance of the pulses was analyzed using the coefficient of variation (CV) in the 3D heart volumes. The 3D gradient-echo (GRE) scans were acquired for the seven testcases to qualitatively validate theB 1 + $$ {\mathrm{B}}_1^{+} $$ -predictions.

RESULTS

Single- and double-frequency optimized pulses achieved homogeneity in flip angle (FA) for the frequencies they were optimized for, while the broadband pulses achieved uniformity in FA across a 1300 Hz frequency range.

CONCLUSION

Broadband TP and UP can be used for homogeneous excitation of the heart volume across a 1300 Hz frequency range, including the water and the main six fat peaks, or with longer pulse durations and higher FAs for a smaller transmit bandwidth. Moreover, despite large inter-volunteer variations, broadband UP can be used for calibration-free 3D heart FA homogenization in time-critical situations.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Respiration induced B 1 + changes and their impact on universal and tailored 3D kT-point parallel transmission pulses for 7T cardiac imaging

PURPOSE

Human heart imaging at ultra-high fields is highly challenging because of respiratory motion-induced artefacts and spatially heterogeneous B 1 + profiles. This work demonstrates that respiration resolved 3D B 1 + -maps can be used with a dedicated tailored and universal parallel transmission (pTx) pulse design to compensate respiration related B 1 + changes in subjects performing shallow and deep breathing (SB/DB).

METHODS

Three-dimensional (3D) B 1 + -maps of the thorax were acquired in 31 subjects under SB and in 15 subjects under SB and DB. Different universal and tailored non-selective pTx pulses were designed from non-respiration resolved (NRR) and respiration resolved (RR) reconstructions of the SB/DB B 1 + -maps. The performance of all pulses was tested with RR-SB/DB B 1 + -maps. Respiration-robust tailored and universal pulses were applied in vivo in 5 subjects at 7T in 3D gradient-echo free-breathing scans.

RESULTS

All optimized pTx pulses performed well for SB. For DB, however, only the universal and the tailored respiration-robust pulses achieved homogeneous flip angles (FAs) in all subjects and across all respiration states, whereas the tailored respiration-specific pulses resulted in a higher FA variation. The respiration-robust universal pulse resulted in an average coefficient of variation in the FA maps of 12.6% compared to 8.2% achieved by tailored respiration-robust pulses. In vivo measurements at 7T demonstrate the benefits of using respiration-robust pulses for DB.

CONCLUSION

Universal and tailored respiration-robust pTx pulses based on RR B 1 + -maps are highly preferred to achieve 3D heart FA homogenization at 7T when subjects perform DB, whereas universal and tailored pulses based on NRR B 1 + -maps are sufficient when subjects perform SB.

Motion-compensated fat-water imaging for 3D cardiac MRI at ultra-high fields

PURPOSE

Respiratory motion-compensated (MC) 3D cardiac fat-water imaging at 7T.

METHODS

Free-breathing bipolar 3D triple-echo gradient-recalled-echo (GRE) data with radial phase-encoding (RPE) trajectory were acquired in 11 healthy volunteers (7M\4F, 21-35 years, mean: 30 years) with a wide range of body mass index (BMI; 19.9-34.0 kg/m² ) and volunteer tailored B 1 + shimming. The bipolar-corrected triple-echo GRE-RPE data were binned into different respiratory phases (self-navigation) and were used for the estimation of non-rigid motion vector fields (MF) and respiratory resolved (RR) maps of the main magnetic field deviations (ΔB₀ ). RR ΔB₀ maps and MC ΔB₀ maps were compared to a reference respiratory phase to assess respiration-induced changes. Subsequently, cardiac binned fat-water images were obtained using a model-based, respiratory motion-corrected image reconstruction.

RESULTS

The 3D cardiac fat-water imaging at 7T was successfully demonstrated. Local respiration-induced frequency shifts in MC ΔB₀ maps are small compared to the chemical shifts used in the multi-peak model. Compared to the reference exhale ΔB₀ map these changes are in the order of 10 Hz on average. Cardiac binned MC fat-water reconstruction reduced respiration induced blurring in the fat-water images, and flow artifacts are reduced in the end-diastolic fat-water separated images.

CONCLUSION

This work demonstrates the feasibility of 3D fat-water imaging at UHF for the entire human heart despite spatial and temporal B 1 + and B₀ variations, as well as respiratory and cardiac motion.

Calibration-free pTx of the human heart at 7T via 3D universal pulses

PURPOSE

MRI at ultra-high fields in the human body is highly challenging and requires lengthy calibration times to compensate for spatially heterogeneous B 1 + profiles. This study investigates the feasibility of using pre-computed universal pulses for calibration-free homogeneous 3D flip angle distribution in the human heart at 7T.

METHODS

Twenty-two channel-wise 3D B 1 + data sets were acquired under free-breathing in 19 subjects to generate a library for an offline universal pulse (UP) design (group 1: 12 males [M] and 7 females [F], 21-66 years, 19.8-28.3 kg/m² ). Three of these subjects (2M/1F, 21-33 years, 20.8-23.6 kg/m² ) were re-scanned on different days. A 4kT-points UP optimized for the 22 channel-wise 3D B 1 + data sets in group 1 (UP22-4kT) is proposed and applied at 7T in 9 new and unseen subjects (group 2: 4M/5F, 25-56 years, 19.5-35.3 kg/m² ). Multiple tailored and universal static and dynamic parallel-transmit (pTx) pulses were designed and evaluated for different permutations of the B 1 + data sets in group 1 and 2.

RESULTS

The proposed UP22-4kT provides low B 1 + variation in all subjects, seen and unseen, without severe signal drops. Experimental data at 7T acquired with UP22-4kT shows comparable image quality as data acquired with tailored-4kT pulses and demonstrates successful calibration-free pTx of the human heart.

CONCLUSION

UP22-4kT allows for calibration-free homogeneous flip angle distributions across the human heart at 7T. Large inter-subject variations because of sex, age, and body mass index are well tolerated. The proposed universal pulse removes the need for lengthy (10-15 min) calibration scans and therefore has the potential to bring body imaging at 7T closer to the clinical application.

Three-dimensional static and dynamic parallel transmission of the human heart at 7 T

Three-dimensional (3D) human heart imaging at ultra-high fields is highly challenging due to respiratory and cardiac motion-induced artifacts as well as spatially heterogeneous B1+ profiles. In this study, we investigate the feasibility of applying 3D flip angle (FA) homogenization targeting the whole heart via static phase-only and dynamic kT-point in vivo parallel transmission at 7 T. 3D B1+ maps of the thorax were acquired under free breathing in eight subjects to compute parallel transmission pulses that improve excitation homogeneity in the human heart. To analyze the number of kT-points required, excitation homogeneity and radiofrequency (RF) power were compared using different regions of interest in six subjects with different body mass index (BMI) values of 20-34 kg/m² for a wide range of regularization parameters. One subset of the optimized subject-specific pulses was applied in vivo on a 7 T scanner for six subjects in Cartesian 3D breath-hold scans as well as in two subjects in a radial phase-encoded 3D free-breathing scan. Across all subjects, 3-4 kT-points achieved a good tradeoff between RF power and nominal FA homogeneity. For subjects with a BMI in the normal range, the 4 kT-point pulses reliably improved the coefficient of variation by less than 10% compared with less than 25% achieved by static phase-only parallel transmission. in vivo measurements on a 7 T scanner validated the B1+ estimations and the pulse design, despite neglecting ΔB₀ in the optimizations and Bloch simulations. This study demonstrates in vivo that kT-point pTx pulses are highly suitable for mitigating nominal FA heterogeneities across the entire 3D heart volume at 7 T. Furthermore, 3-4 kT-points demonstrate a practical tradeoff between nominal FA heterogeneity mitigation and RF power.

3D Free-breathing multichannel absolute B 1 + Mapping in the human body at 7T

PURPOSE

To introduce and investigate a method for free-breathing three-dimensional (3D) B 1 + mapping of the human body at ultrahigh field (UHF), which can be used to generate homogenous flip angle (FA) distributions in the human body at UHF.

METHODS

A 3D relative B 1 + mapping sequence with a radial phase-encoding (RPE) k-space trajectory was developed and applied in 11 healthy subjects at 7T. An RPE-based actual flip angle mapping method was applied with a dedicated B 1 + shim setting to calibrate the relative B 1 + maps yielding absolute B 1 + maps of the individual transmit channels. The method was evaluated in a motion phantom and by multidimensional in vivo measurements. Additionally, 3D gradient echo scans with and without static phase-only B 1 + shims were used to qualitatively validate B 1 + shim predictions.

RESULTS

The phantom validation revealed good agreement for B 1 + maps between dynamic measurement and static reference acquisition. The proposed 3D method was successfully validated in vivo by comparing magnitude and phase distributions with a 2D Cartesian reference. 3D B 1 + maps free from visible motion artifacts were successfully acquired for 11 subjects with body mass indexes ranging from 19 kg/m² to 34 kg/m² . 3D respiration-resolved absolute B 1 + maps indicated FA differences between inhalation and exhalation up to 15% for one channel and up to 24% for combined channels for shallow breathing.

CONCLUSION

The proposed method provides respiration-resolved absolute 3D B 1 + maps of the human body at UHF, which enables the investigation and development of 3D B 1 + shimming and parallel transmission methods to further enhance body imaging at UHF.

Evaluation of MRI-derived surrogate signals to model respiratory motion

An MR-Linac can provide motion information of tumour and organs-at-risk before, during, and after beam delivery. However, MR imaging cannot provide real-time high-quality volumetric images which capture breath-to-breath variability of respiratory motion. Surrogate-driven motion models relate the motion of the internal anatomy to surrogate signals, thus can estimate the 3D internal motion from these signals. Internal surrogate signals based on patient anatomy can be extracted from 2D cine-MR images, which can be acquired on an MR-Linac during treatment, to build and drive motion models. In this paper we investigate different MRI-derived surrogate signals, including signals generated by applying principal component analysis to the image intensities, or control point displacements derived from deformable registration of the 2D cine-MR images. We assessed the suitability of the signals to build models that can estimate the motion of the internal anatomy, including sliding motion and breath-to-breath variability. We quantitatively evaluated the models by estimating the 2D motion in sagittal and coronal slices of 8 lung cancer patients, and comparing them to motion measurements obtained from image registration. For sagittal slices, using the first and second principal components on the control point displacements as surrogate signals resulted in the highest model accuracy, with a mean error over patients around 0.80 mm which was lower than the in-plane resolution. For coronal slices, all investigated signals except the skin signal produced mean errors over patients around 1 mm. These results demonstrate that surrogate signals derived from 2D cine-MR images, including those generated by applying principal component analysis to the image intensities or control point displacements, can accurately model the motion of the internal anatomy within a single sagittal or coronal slice. This implies the signals should also be suitable for modelling the 3D respiratory motion of the internal anatomy.

Non-rigid image registration of 4D-MRI data for improved delineation of moving tumors

Background

To increase the image quality of end-expiratory and end-inspiratory phases of retrospective respiratory self-gated 4D MRI data sets using non-rigid image registration for improved target delineation of moving tumors.

Methods

End-expiratory and end-inspiratory phases of volunteer and patient 4D MRI data sets are used as targets for non-rigid image registration of all other phases using two different registration schemes: In the first, all phases are registered directly (dir-Reg) while next neighbors are successively registered until the target is reached in the second (nn-Reg). Resulting data sets are quantitatively compared using diaphragm and tumor sharpness and the coefficient of variation of regions of interest in the lung, liver, and heart. Qualitative assessment of the patient data regarding noise level, tumor delineation, and overall image quality was performed by blinded reading based on a 4 point Likert scale.

Results

The median coefficient of variation was lower for both registration schemes compared to the target. Median dir-Reg coefficient of variation of all ROIs was 5.6% lower for expiration and 7.0% lower for inspiration compared with nn-Reg. Statistical significant differences between the two schemes were found in all comparisons. Median sharpness in inspiration is lower compared to expiration sharpness in all cases. Registered data sets were rated better compared to the targets in all categories. Over all categories, mean expiration scores were 2.92 ± 0.18 for the target, 3.19 ± 0.22 for nn-Reg and 3.56 ± 0.14 for dir-Reg and mean inspiration scores 2.25 ± 0.12 for the target, 2.72 ± 215 0.04 for nn-Reg and 3.78 ± 0.04 for dir-Reg.

Conclusions

In this work, end-expiratory and inspiratory phases of a 4D MRI data sets are used as targets for non-rigid image registration of all other phases. It is qualitatively and quantitatively shown that image quality of the targets can be significantly enhanced leading to improved target delineation of moving tumors.

Breathing deformation model - application to multi-resolution abdominal MRI

Dynamic MRI is a technique of acquiring a series of images continuously to follow the physiological changes over time. However, such fast imaging results in low resolution images. In this work, abdominal deformation model computed from dynamic low resolution images have been applied to high resolution image, acquired previously, to generate dynamic high resolution MRI. Dynamic low resolution images were simulated into different breathing phases (inhale and exhale). Then, the image registration between breathing time points was performed using the B-spline SyN deformable model and using cross-correlation as a similarity metric. The deformation model between different breathing phases were estimated from highly undersampled data. This deformation model was then applied to the high resolution images to obtain high resolution images of different breathing phases. The results indicated that the deformation model could be computed from relatively very low resolution images.

Image registration in dynamic renal MRI-current status and prospects

Magnetic resonance imaging (MRI) modalities have achieved an increasingly important role in the clinical work-up of chronic kidney diseases (CKD). This comprises among others assessment of hemodynamic parameters by arterial spin labeling (ASL) or dynamic contrast-enhanced (DCE-) MRI. Especially in the latter, images or volumes of the kidney are acquired over time for up to several minutes. Therefore, they are hampered by motion, e.g., by pulsation, peristaltic, or breathing motion. This motion can hinder subsequent image analysis to estimate hemodynamic parameters like renal blood flow or glomerular filtration rate (GFR). To overcome motion artifacts in time-resolved renal MRI, a wide range of strategies have been proposed. Renal image registration approaches could be grouped into (1) image acquisition techniques, (2) post-processing methods, or (3) a combination of image acquisition and post-processing approaches. Despite decades of progress, the translation in clinical practice is still missing. The aim of the present article is to discuss the existing literature on renal image registration techniques and show today’s limitations of the proposed techniques that hinder clinical translation. This paper includes transformation, criterion function, and search types as traditional components and emerging registration technologies based on deep learning. The current trend points towards faster registrations and more accurate results. However, a standardized evaluation of image registration in renal MRI is still missing.

A novel amplitude binning strategy to handle irregular breathing during 4DMRI acquisition: improved imaging for radiotherapy purposes

Background

For radiotherapy of abdominal cancer, four-dimensional magnetic resonance imaging (4DMRI) is desirable for tumor definition and the assessment of tumor and organ motion. However, irregular breathing gives rise to image artifacts. We developed a outlier rejection strategy resulting in a 4DMRI with reduced image artifacts in the presence of irregular breathing.

Methods

We obtained 2D T2-weighted single-shot turbo spin echo images, with an interleaved 1D navigator acquisition to obtain the respiratory signal during free breathing imaging in 2 patients and 12 healthy volunteers. Prior to binning, upper and lower inclusion thresholds were chosen such that 95% of the acquired images were included, while minimizing the distance between the thresholds (inclusion range (IR)). We compared our strategy (Min95) with three commonly applied strategies: phase binning with all images included (Phase), amplitude binning with all images included (MaxIE), and amplitude binning with the thresholds set as the mean end-inhale and mean end-exhale diaphragm positions (MeanIE). We compared 4DMRI quality based on:

Data included (DI); percentage of images remaining after outlier rejection.

Reconstruction completeness (RC); percentage of bin-slice combinations containing at least one image after binning.

Intra-bin variation (IBV); interquartile range of the diaphragm position within the bin-slice combination, averaged over three central slices and ten respiratory bins.

IR.

Image smoothness (S); quantified by fitting a parabola to the diaphragm profile in a sagittal plane of the reconstructed 4DMRI.

A two-sided Wilcoxon’s signed-rank test was used to test for significance in differences between the Min95 strategy and the Phase, MaxIE, and MeanIE strategies.

Results

Based on the fourteen subjects, the Min95 binning strategy outperformed the other strategies with a mean RC of 95.5%, mean IBV of 1.6 mm, mean IR of 15.1 mm and a mean S of 0.90. The Phase strategy showed a poor mean IBV of 6.2 mm and the MaxIE strategy showed a poor mean RC of 85.6%, resulting in image artifacts (mean S of 0.76). The MeanIE strategy demonstrated a mean DI of 85.6%.

Conclusions

Our Min95 reconstruction strategy resulted in a 4DMRI with less artifacts and more precise diaphragm position reconstruction compared to the other strategies.

Trial registration

Volunteers: protocol W15_373#16.007; patients: protocol NL47713.018.14

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1279-z) contains supplementary material, which is available to authorized users.

A post-processing method based on interphase motion correction and averaging to improve image quality of 4D magnetic resonance imaging: a clinical feasibility study

METHODS:

Nine patients (seven pancreas, one liver, and one lung) were recruited. 4D-MRI was performed using two prototype k-space sorted techniques, stack-of-stars (SOS) and koosh-ball (KB) acquisitions. Post-processing using MoCoAve was implemented for both methods. Image quality score, apparent SNR (aSNR), sharpness, motion trajectory and standard deviation (σ_GTV) of the gross tumor volumes were compared between original and MoCoAve image sets.

RESULTS:

All subjects successfully underwent 4D-MRI scans and MoCoAve was performed on all data sets. Significantly higher image quality scores (2.64 ± 0.39 vs 1.18 ± 0.34, p = 0.001) and aSNR (37.6 ± 15.3 vs 18.1 ± 5.7, p = 0.001) was observed in the MoCoAve images when compared to the original images. High correlation in tumor motion trajectories in the superoinferior direction (SI: 0.91 ± 0.08) and weaker in the anteroposterior (AP: 0.51 ± 0.44) and mediolateral (ML: 0.37 ± 0.23) directions, similar image sharpness (0.367 ± 0.068 vs 0.369 ± 0.072, p = 0.805), and minimal average absolute difference (0.47 ± 0.34  mm) of the motion trajectory profiles was found between the two image sets. The σ_GTV in pancreas patients was significantly (p = 0.039) lower in MoCoAve images (1.48 ± 1.35  cm3) than in the original images (2.17 ± 1.31  cm3).

CONCLUSION:

MoCoAve using interphase motion correction and averaging has shown promise as a post-processing method for improving k-space sorted (SOS and KB) 4D-MRI image quality in thoracic and abdominal cancer patients.

ADVANCES IN KNOWLEDGE:

The proposed method is an image based post-processing method that could be applied to many k-space sorted 4D-MRI methods for improved image quality and signal-to-noise ratio while preserving image sharpness and respiratory motion fidelity. It is a useful technique for the radiotherapy planning community who are interested in using 4D-MRI but aren't satisfied with their current MR image quality.

A clustering approach to 4D MRI retrospective sorting for the investigation of different surrogates

PURPOSE

In retrospective 4-Dimensional Magnetic Resonance Imaging (4D MRI) sorting, respiratory surrogate selection affects the image quality of reconstructed volumes. We propose a method for retrospective 4D MRI sorting based on clustering, which allowed us to compare the performance of single or multiple internal surrogates vs. a conventional external signal.

METHODS

A k-medoids clustering algorithm was exploited for sorting 2D MRI into 4D MRI, relying on (A) multiple or (B) single automatically tracked internal landmarks or (C) respiratory belt signal. 4D MRI reconstructions for seven liver cancer patients were compared to those of the state-of-the-art mutual information (MI) approach. Sorting artifacts were measured by the root mean square error (RMSE) between the diaphragm profile and a fitted second order curve. Diaphragm and tumor motions were evaluated.

RESULTS

The median RMSEs ranged 0.97-1.66 mm, 1.24-1.89 mm, 1.43-2.27 mm, 1.74-3.72 mm for the MI, (A), (B) and (C) methods, respectively. Significant differences (Friedman, α = 5%) were found between (C) and all other methods, and between (B) and MI approaches. The discrepancies between (A) and MI approaches ranged 1.1-6.2 mm and 0.7-5.3 mm respectively in diaphragm and tumor motions. Methods (A) and (B) showed similar ranges of motion.

CONCLUSION

With multiple internal points, our method yielded the description of a higher range of motion and similar image quality with respect to the MI approach. The single point method led to more artifacts, suggesting the superior suitability of multiple internal surrogates for retrospective 4D MRI sorting. Considering internal rather than external information favored superior performance.

MRI-guidance for motion management in external beam radiotherapy: current status and future challenges

High precision conformal radiotherapy requires sophisticated imaging techniques to aid in target localisation for planning and treatment, particularly when organ motion due to respiration is involved. X-ray based imaging is a well-established standard for radiotherapy treatments. Over the last few years, the ability of magnetic resonance imaging (MRI) to provide radiation-free images with high-resolution and superb soft tissue contrast has highlighted the potential of this imaging modality for radiotherapy treatment planning and motion management. In addition, these advantageous properties motivated several recent developments towards combined MRI radiation therapy treatment units, enabling in-room MRI-guidance and treatment adaptation. The aim of this review is to provide an overview of the state-of-the-art in MRI-based image guidance for organ motion management in external beam radiotherapy. Methodological aspects of MRI for organ motion management are reviewed and their application in treatment planning, in-room guidance and adaptive radiotherapy described. Finally, a roadmap for an optimal use of MRI-guidance is highlighted and future challenges are discussed.

Respiratory motion estimation of the liver with abdominal motion as a surrogate

Background: Respiratory‐induced motion (RIM) causes uncertainties in localizing hepatic lesions, which could lead to inaccurate targeting during interventions. One approach to mitigate the problem is respiratory motion estimation (RME), in which the liver motion is estimated by measuring external signals called surrogates.

Methods: A learning‐based approach has been developed and validated to estimate the RIM of hepatic lesions. External markers placed on the human's abdomen were chosen as surrogates. Accordingly, appropriate motion models (multivariate, Ridge and Lasso regression models) were designed to correlate the liver motion with the abdominal motion, and trained to estimate the superior–inferior (SI) motion of the liver. Three subjects volunteered for 6 sessions of such that liver images acquired by magnetic resonance imaging (MRI) were recorded alongside camera‐tracked external markers.

Results and conclusions: The proposed machine learning approach was validated in MRI on human subjects and the results show that the approach could estimate the respiratory‐induced SI motion of the liver with a mean absolute error (MAE) accuracy below 2 mm.

Ultrasound-driven 4D MRI

We present an ultrasound-driven 4D magnetic resonance imaging (US-4DMRI) method for respiratory motion imaging in the thorax and abdomen. The proposed US-4DMRI comes along with a high temporal resolution, and allows for organ motion imaging beyond a single respiratory cycle. With the availability of the US surrogate both inside and outside the MR bore, 4D MR images can be reconstructed for 4D treatment planning and online respiratory motion prediction during radiotherapy. US-4DMRI relies on simultaneously acquired 2D liver US images and abdominal 2D MR multi-slice scans under free respiration. MR volumes are retrospectively composed by grouping the MR slices corresponding to the most similar US images. We present two different US similarity metrics: an intensity-based approach, and a similarity measure relying on predefined fiducials which are being tracked over time. The proposed method is demonstrated on MR liver scans of eight volunteers acquired over a duration of 5.5 min each at a temporal resolution of 2.6 Hz with synchronous US imaging at 14 Hz-17 Hz. Visual inspection of the reconstructed MR volumes revealed satisfactory results in terms of continuity in organ boundaries and blood vessels. In quantitative leave-one-out experiments, both US similarity metrics reach the performance level of state-of-the-art navigator-based approaches.

CAPTURE: Consistently Acquired Projections for Tuned and Robust Estimation: A Self-Navigated Respiratory Motion Correction Approach

OBJECTIVES

In this study, we present a fully automated and robust self-navigated approach to obtain 4-dimensional (4-D) motion-resolved images during free breathing.

MATERIALS AND METHODS

The proposed method, Consistently Acquired Projections for Tuned and Robust Estimation (CAPTURE), is a variant of the stack-of-stars gradient-echo sequence. A 1-D navigator was consistently acquired at a fixed azimuthal angle for all stacks of spokes to reduce nonphysiological signal contamination due to system imperfections. The resulting projections were then "tuned" using complex phase rotation to adapt to scan-to-scan variations, followed by the detection of the respiratory curve. Four-dimensional motion-corrected and uncorrected images were then reconstructed via respiratory and temporal binning, respectively.This Health Insurance Portability and Accountability Act-compliant study was performed with Institutional Review Board approval. A phantom experiment was performed using a custom-made deformable motion phantom with an adjustable frequency and amplitude. For in vivo experiments, 10 healthy participants and 12 liver tumor patients provided informed consent and were imaged with the CAPTURE sequence.Two radiologists, blinded to which images were motion-corrected and which were not, independently reviewed the images and scored the image quality using a 5-point Likert scale.

RESULTS

In the respiratory motion phantom experiment, CAPTURE reversed the effects of motion blurring and restored edge sharpness from 36% to 78% of that observed in the images from the static scan.Despite large intra- and intersubject variability in respiration patterns, CAPTURE successfully detected the respiratory motion signal in all participants and significantly improved the image quality according to the subjective radiological assessments of 2 raters (P < 0.05 for both raters) with a 1 to 2-point improvement in the median Likert scores across the whole set of participants. Small lesions (<1 cm in size) which might otherwise be missed on uncorrected images because of motion blurring were more clearly depicted on the CAPTURE images.

CONCLUSIONS

CAPTURE provides a robust and fully automated solution for obtaining 4-D motion-resolved images in a free-breathing setting. With its unique tuning feature, CAPTURE can adapt to large intersubject and interscan variations. CAPTURE also enables better lesion delineation because of improved image sharpness, thereby increasing the visibility of small lesions.

Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study

OBJECTIVE

Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural network (CNN) to obtain motion-free abdominal images throughout the respiratory cycle.

METHODS

Abdominal data were acquired from 10 volunteers using a 1.5 T MRI system. The respiratory signal was extracted from the central-space spokes, and the acquired data were reordered in three bins according to the corresponding breathing signal. Retrospective image reconstruction of the three near-motion free respiratory phases was performed using non-Cartesian iterative SENSE reconstruction. Then, we trained a CNN to analyse the spatial transform among the different bins. This network could generate the displacement vector field and be applied to perform registration on unseen image pairs. To demonstrate the feasibility of this registration method, we compared the performance of three different registration approaches for accurate image fusion of three bins: non-motion corrected (NMC), local affine registration method (LREG) and CNN.

RESULTS

Visualization of coronal images indicated that LREG had caused broken blood vessels, while the vessels of the CNN were sharper and more consecutive. As shown in the sagittal view, compared to NMC and CNN, distorted and blurred liver contours were caused by LREG. At the same time, zoom-in axial images presented that the vessels were delineated more clearly by CNN than LREG. The statistical results of the signal-to-noise ratio, visual score, vessel sharpness and registration time over all volunteers were compared among the NMC, LREG and CNN approaches. The SNR indicated that the CNN acquired the best image quality (207.42 ± 96.73), which was better than NMC (116.67 ± 44.70) and LREG (187.93 ± 96.68). The image visual score agreed with SNR, marking CNN (3.85 ± 0.12) as the best, followed by LREG (3.43 ± 0.13) and NMC (2.55 ± 0.09). A vessel sharpness assessment yielded similar values between the CNN (0.81 ± 0.03) and LREG (0.80 ± 0.04), differentiating them from the NMC (0.78 ± 0.06). When compared with the LREG-based reconstruction, the CNN-based reconstruction reduces the registration time from 1 h to 1 min.

CONCLUSION

Our preliminary results demonstrate the feasibility of the CNN-based approach, and this scheme outperforms the NMC- and LREG-based methods. Advances in knowledge: This method reduces the registration time from ~1 h to ~1 min, which has promising prospects for clinical use. To the best of our knowledge, this study shows the first convolutional neural network-based registration method to be applied in abdominal images.

Concurrent Respiratory Motion Correction of Abdominal PET and Dynamic Contrast-Enhanced-MRI Using a Compressed Sensing Approach

We present an approach for concurrent reconstruction of respiratory motion-compensated abdominal dynamic contrast-enhanced (DCE)-MRI and PET data in an integrated PET/MR scanner. The MR and PET reconstructions share the same motion vector fields derived from radial MR data; the approach is robust to changes in respiratory pattern and does not increase the total acquisition time. Methods: PET and DCE-MRI data of 12 oncologic patients were simultaneously acquired for 6 min on an integrated PET/MR system after administration of ¹⁸F-FDG and gadoterate meglumine. Golden-angle radial MR data were continuously acquired simultaneously with PET data and sorted into multiple motion phases on the basis of a respiratory signal derived directly from the radial MR data. The resulting multidimensional dataset was reconstructed using a compressed sensing approach that exploits sparsity among respiratory phases. Motion vector fields obtained using the full 6-min (MC_6-min) and only the last 1 min (MC_1-min) of data were incorporated into the PET reconstruction to obtain motion-corrected PET images and in an MR iterative reconstruction algorithm to produce a series of motion-corrected DCE-MR images (moco_GRASP). The motion-correction methods (MC_6-min and MC_1-min) were evaluated by qualitative analysis of the MR images and quantitative analysis of SUV_max and SUV_mean, contrast, signal-to-noise ratio (SNR), and lesion volume in the PET images. Results: Motion-corrected MC_6-min PET images demonstrated 30%, 23%, 34%, and 18% increases in average SUV_max, SUV_mean, contrast, and SNR and an average 40% reduction in lesion volume with respect to the non-motion-corrected PET images. The changes in these figures of merit were smaller but still substantial for the MC_1-min protocol: 19%, 10%, 15%, and 9% increases in average SUV_max, SUV_mean, contrast, and SNR; and a 28% reduction in lesion volume. Moco_GRASP images were deemed of acceptable or better diagnostic image quality with respect to conventional breath-hold Cartesian volumetric interpolated breath-hold examination acquisitions. Conclusion: We presented a method that allows the simultaneous acquisition of respiratory motion-corrected diagnostic quality DCE-MRI and quantitatively accurate PET data in an integrated PET/MR scanner with negligible prolongation in acquisition time compared with routine PET/DCE-MRI protocols.

Technical note: Accelerated nonrigid motion-compensated isotropic 3D coronary MR angiography

PURPOSE

To develop an accelerated and nonrigid motion-compensated technique for efficient isotropic 3D whole-heart coronary magnetic resonance angiography (CMRA) with Cartesian acquisition.

METHODS

Highly efficient whole-heart 3D CMRA was achieved by combining image reconstruction from undersampled data using compressed sensing (CS) with a nonrigid motion compensation framework. Undersampled acquisition was performed using a variable-density Cartesian trajectory with radial order (VD-CAPR). Motion correction was performed in two steps: beat-to-beat 2D translational correction with motion estimated from interleaved image navigators, and bin-to-bin 3D nonrigid correction with motion estimated from respiratory-resolved images reconstructed from undersampled 3D CMRA data using CS. Nonrigid motion fields were incorporated into an undersampled motion-compensated reconstruction, which combines CS with the general matrix description formalism. The proposed approach was tested on 10 healthy subjects and compared against a conventional twofold accelerated 5-mm navigator-gated and tracked acquisition.

RESULTS

The proposed method achieves isotropic 1.2-mm Cartesian whole-heart CMRA in 5 min ± 1 min (~8× acceleration). The proposed approach provides good-quality images of the left and right coronary arteries, comparable to those of a twofold accelerated navigator-gated and tracked acquisition, but scan time was up to about four times faster. For both coronaries, no significant differences (P > 0.05) in vessel sharpness and length were found between the proposed method and reference scan.

CONCLUSION

The feasibility of a highly efficient motion-compensated reconstruction framework for accelerated 3D CMRA has been demonstrated in healthy subjects. Further investigation is required to assess the clinical value of the method.

Autocalibrating motion-corrected wave-encoding for highly accelerated free-breathing abdominal MRI

PURPOSE

To develop a motion-robust wave-encoding technique for highly accelerated free-breathing abdominal MRI.

METHODS

A comprehensive 3D wave-encoding-based method was developed to enable fast free-breathing abdominal imaging: (a) auto-calibration for wave-encoding was designed to avoid extra scan for coil sensitivity measurement; (b) intrinsic butterfly navigators were used to track respiratory motion; (c) variable-density sampling was included to enable compressed sensing; (d) golden-angle radial-Cartesian hybrid view-ordering was incorporated to improve motion robustness; and (e) localized rigid motion correction was combined with parallel imaging compressed sensing reconstruction to reconstruct the highly accelerated wave-encoded datasets. The proposed method was tested on six subjects and image quality was compared with standard accelerated Cartesian acquisition both with and without respiratory triggering. Inverse gradient entropy and normalized gradient squared metrics were calculated, testing whether image quality was improved using paired t-tests.

RESULTS

For respiratory-triggered scans, wave-encoding significantly reduced residual aliasing and blurring compared with standard Cartesian acquisition (metrics suggesting P < 0.05). For non-respiratory-triggered scans, the proposed method yielded significantly better motion correction compared with standard motion-corrected Cartesian acquisition (metrics suggesting P < 0.01).

CONCLUSION

The proposed methods can reduce motion artifacts and improve overall image quality of highly accelerated free-breathing abdominal MRI. Magn Reson Med 78:1757-1766, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Improved vessel-tissue contrast and image quality in 3D radial sampling-based 4D-MRI

Purpose

In radiation treatment planning for thoracic and abdominal tumors, 4D‐MRI has shown promise in respiratory motion characterization with improved soft‐tissue contrast compared to clinical standard, 4D computed tomography (4D‐CT). This study aimed to further improve vessel–tissue contrast and overall image quality in 3D radial sampling‐based 4D‐MRI using a slab‐selective (SS) excitation approach.

Methods

The technique was implemented in a 3D radial sampling with self‐gating‐based k‐space sorting sequence. The SS excitation approach was compared to a non‐selective (NS) approach in six cancer patients and two healthy volunteers at 3T. Improvements in vessel–tissue contrast ratio (CR) and vessel signal‐to‐noise ratio (SNR) were analyzed in five of the eight subjects. Image quality was visually assessed in all subjects on a 4‐point scale (0: poor; 3: excellent). Tumor (patients) and pancreas (healthy) motion trajectories were compared between the two imaging approaches.

Results

Compared with NS‐4D‐MRI, SS‐4D‐MRI significantly improved the overall vessel–tissue CR (2.60 ± 3.97 vs. 1.03 ± 1.44, P < 0.05), SNR (63.33 ± 38.45 vs. 35.74 ± 28.59, P < 0.05), and image quality score (2.6 ± 0.5 vs. 1.4 ± 0.5, P = 0.02). Motion trajectories from the two approaches exhibited strong correlation in the superior–inferior (0.96 ± 0.06), but weaker in the anterior–posterior (0.78 ± 0.24) and medial–lateral directions (0.46 ± 0.44).

Conclusions

The proposed 4D‐MRI with slab‐selectively excited 3D radial sampling allows for improved blood SNR, vessel–tissue CR, and image quality.

Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices

In this work, we introduce a novel motion-robust spatially constrained parameter estimation (MOSCOPE) technique for kidney diffusion-weighted MRI. The proposed motion compensation technique does not require a navigator, trigger, or breath-hold but only uses the intrinsic features of the acquired data to track and compensate for motion to reconstruct precise models of the renal diffusion signal. We have developed a technique for physiological motion tracking based on robust state estimation and sequential registration of diffusion sensitized slices acquired within 200ms. This allows a sampling rate of 5Hz for state estimation in motion tracking that is sufficiently faster than both respiratory and cardiac motion rates in children and adults, which range between 0.8 to 0.2Hz, and 2.5 to 1Hz, respectively. We then apply the estimated motion parameters to data from each slice and use motion-compensated data for 1) robust intra-voxel incoherent motion (IVIM) model estimation in the kidney using a spatially constrained model fitting approach, and 2) robust weighted least squares estimation of the diffusion tensor model. Experimental results, including precision of IVIM model parameters using bootstrap-sampling and in-vivo whole kidney tractography, showed significant improvement in precision and accuracy of these models using the proposed method compared to models based on the original data and volumetric registration.

Detection and Compensation of Periodic Motion in Magnetic Particle Imaging

The temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in x -space approaches. To improve the signal-to-noise ratio, blockwise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this paper, a framework for averaging motion-corrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heartbeat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are, in general, not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For high-frequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom, it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heartbeat.

High-Resolution Self-Gated Dynamic Abdominal MRI Using Manifold Alignment

We present a novel retrospective self-gating method based on manifold alignment (MA), which enables reconstruction of free breathing, high spatial, and temporal resolution abdominal magnetic resonance imaging sequences. Based on a radial golden-angle acquisition trajectory, our method enables a multidimensional self-gating signal to be extracted from the k -space data for more accurate motion representation. The k -space radial profiles are evenly divided into a number of overlapping groups based on their radial angles. MA is then used to simultaneously learn and align the low dimensional manifolds of all groups, and embed them into a common manifold. In the manifold, k -space profiles that represent similar respiratory positions are close to each other. Image reconstruction is performed by combining radial profiles with evenly distributed angles that are close in the manifold. Our method was evaluated on both 2-D and 3-D synthetic and in vivo data sets. On the synthetic data sets, our method achieved high correlation with the ground truth in terms of image intensity and virtual navigator values. Using the in vivo data, compared with a state-of-the-art approach based on the center of k -space gating, our method was able to make use of much richer profile data for self-gating, resulting in statistically significantly better quantitative measurements in terms of organ sharpness and image gradient entropy.

Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data

PURPOSE

Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed.

METHODS

The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUV_mean, SUV_max, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio.

RESULTS

For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUV_mean, SUV_max, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively.

CONCLUSIONS

Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.

Cardiac and Respiratory Motion Correction for Simultaneous Cardiac PET/MR

Cardiac PET is a versatile imaging technique providing important diagnostic information about ischemic heart diseases. Respiratory and cardiac motion of the heart can strongly impair image quality and therefore diagnostic accuracy of cardiac PET scans. The aim of this study was to investigate a new cardiac PET/MR approach providing respiratory and cardiac motion-compensated MR and PET images in less than 5 min. Methods: Free-breathing 3-dimensional MR data were acquired and retrospectively binned into multiple respiratory and cardiac motion states. Three-dimensional cardiac and respiratory motion fields were obtained with a nonrigid registration algorithm and used in motion-compensated MR and PET reconstructions to improve image quality. The improvement in image quality and diagnostic accuracy of the technique was assessed in simultaneous ¹⁸F-FDG PET/MR scans of a canine model of myocardial infarct and was demonstrated in a human subject. Results: MR motion fields were successfully used to compensate for in vivo cardiac motion, leading to improvements in full width at half maximum of the canine myocardium of 13% ± 5%, similar to cardiac gating but with a 90% ± 57% higher contrast-to-noise ratio between myocardium and blood. Motion correction led to an improvement in MR image quality in all subjects, with an increase in sharpness of the canine coronary arteries of 85% ± 72%. A functional assessment showed good agreement with standard MR cine scans with a difference in ejection fraction of -2% ± 3%. MR-based respiratory and cardiac motion information was used to improve the PET image quality of a human in vivo scan. Conclusion: The MR technique presented here provides both diagnostic and motion information that can be used to improve MR and PET image quality. Reliable respiratory and cardiac motion correction could make cardiac PET results more reproducible.

Highly efficient nonrigid motion-corrected 3D whole-heart coronary vessel wall imaging

Purpose

To develop a respiratory motion correction framework to accelerate free‐breathing three‐dimensional (3D) whole‐heart coronary lumen and coronary vessel wall MRI.

Methods

We developed a 3D flow‐independent approach for vessel wall imaging based on the subtraction of data with and without T2‐preparation prepulses acquired interleaved with image navigators. The proposed method corrects both datasets to the same respiratory position using beat‐to‐beat translation and bin‐to‐bin nonrigid corrections, producing coregistered, motion‐corrected coronary lumen and coronary vessel wall images. The proposed method was studied in 10 healthy subjects and was compared with beat‐to‐beat translational correction (TC) and no motion correction for the left and right coronary arteries. Additionally, the coronary lumen images were compared with a 6‐mm diaphragmatic navigator gated and tracked scan.

Results

No significant differences (P > 0.01) were found between the proposed method and the gated and tracked scan for coronary lumen, despite an average improvement in scan efficiency to 96% from 59%. Significant differences (P < 0.01) were found in right coronary artery vessel wall thickness, right coronary artery vessel wall sharpness, and vessel wall visual score between the proposed method and TC.

Conclusion

The feasibility of a highly efficient motion correction framework for simultaneous whole‐heart coronary lumen and vessel wall has been demonstrated. Magn Reson Med 77:1894–1908, 2017. © 2016 International Society for Magnetic Resonance in Medicine

4D MR imaging using robust internal respiratory signal

The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.

Accelerated motion corrected three-dimensional abdominal MRI using total variation regularized SENSE reconstruction

PURPOSE

Develop a nonrigid motion corrected reconstruction for highly accelerated free-breathing three-dimensional (3D) abdominal images without external sensors or additional scans.

METHODS

The proposed method accelerates the acquisition by undersampling and performs motion correction directly in the reconstruction using a general matrix description of the acquisition. Data are acquired using a self-gated 3D golden radial phase encoding trajectory, enabling a two stage reconstruction to estimate and then correct motion of the same data. In the first stage total variation regularized iterative SENSE is used to reconstruct highly undersampled respiratory resolved images. A nonrigid registration of these images is performed to estimate the complex motion in the abdomen. In the second stage, the estimated motion fields are incorporated in a general matrix reconstruction, which uses total variation regularization and incorporates k-space data from multiple respiratory positions. The proposed approach was tested on nine healthy volunteers and compared against a standard gated reconstruction using measures of liver sharpness, gradient entropy, visual assessment of image sharpness and overall image quality by two experts.

RESULTS

The proposed method achieves similar quality to the gated reconstruction with nonsignificant differences for liver sharpness (1.18 and 1.00, respectively), gradient entropy (1.00 and 1.00), visual score of image sharpness (2.22 and 2.44), and visual rank of image quality (3.33 and 3.39). An average reduction of the acquisition time from 102 s to 39 s could be achieved with the proposed method.

CONCLUSION

In vivo results demonstrate the feasibility of the proposed method showing similar image quality to the standard gated reconstruction while using data corresponding to a significantly reduced acquisition time. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

4D respiratory motion-compensated image reconstruction of free-breathing radial MR data with very high undersampling

PURPOSE

To develop four-dimensional (4D) respiratory time-resolved MRI based on free-breathing acquisition of radial MR data with very high undersampling.

METHODS

We propose the 4D joint motion-compensated high-dimensional total variation (4D joint MoCo-HDTV) algorithm, which alternates between motion-compensated image reconstruction and artifact-robust motion estimation at multiple resolution levels. The algorithm is applied to radial MR data of the thorax and upper abdomen of 12 free-breathing subjects with acquisition times between 37 and 41 s and undersampling factors of 16.8. Resulting images are compared with compressed sensing-based 4D motion-adaptive spatio-temporal regularization (MASTeR) and 4D high-dimensional total variation (HDTV) reconstructions.

RESULTS

For all subjects, 4D joint MoCo-HDTV achieves higher similarity in terms of normalized mutual information and cross-correlation than 4D MASTeR and 4D HDTV when compared with reference 4D gated gridding reconstructions with 8.4 ± 1.1 times longer acquisition times. In a qualitative assessment of artifact level and image sharpness by two radiologists, 4D joint MoCo-HDTV reveals higher scores (P < 0.05) than 4D HDTV and 4D MASTeR at the same undersampling factor and the reference 4D gated gridding reconstructions, respectively.

CONCLUSIONS

4D joint MoCo-HDTV enables time-resolved image reconstruction of free-breathing radial MR data with undersampling factors of 16.8 while achieving low-streak artifact levels and high image sharpness. Magn Reson Med 77:1170-1183, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Four-dimensional MRI using three-dimensional radial sampling with respiratory self-gating to characterize temporal phase-resolved respiratory motion in the abdomen

PURPOSE

To develop a four-dimensional MRI (4D-MRI) technique to characterize the average respiratory tumor motion for abdominal radiotherapy planning.

METHODS

A continuous spoiled gradient echo sequence was implemented with 3D radial trajectory and 1D self-gating for respiratory motion detection. Data were retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase was reconstructed by means of a self-calibrating CG-SENSE program. Motion phantom, healthy volunteer and patient studies were performed to validate the respiratory motion detected by the proposed method against that from a 2D real-time protocol.

RESULTS

The proposed method successfully visualized the respiratory motion in phantom and human subjects. The 4D-MRI and real-time 2D-MRI yielded comparable superior-inferior (SI) motion amplitudes (intraclass correlation = 0.935) with up-to one pixel mean absolute differences in SI displacements over 10 phases and high cross-correlation between phase-resolved displacements (phantom: 0.985; human: 0.937-0.985). Comparable anterior-posterior and left-right displacements of the tumor or gold fiducial between 4D and real-time 2D-MRI were also observed in the two patients, and the hysteresis effect was shown in their 3D trajectories.

CONCLUSION

We demonstrated the feasibility of the proposed 4D-MRI technique to characterize abdominal respiratory motion, which may provide valuable information for radiotherapy planning.

Highly efficient respiratory motion compensated free-breathing coronary MRA using golden-step Cartesian acquisition

PURPOSE

To develop an efficient 3D affine respiratory motion compensation framework for Cartesian whole-heart coronary magnetic resonance angiography (MRA).

MATERIALS AND METHODS

The proposed method achieves 100% scan efficiency by estimating the affine respiratory motion from the data itself and correcting the acquired data in the reconstruction process. For this, a golden-step Cartesian sampling with spiral profile ordering was performed to enable reconstruction of respiratory resolved images at any breathing position and with different respiratory window size. Affine motion parameters were estimated from image-based registration of 3D undersampled respiratory resolved images reconstructed with iterative SENSE and motion correction was performed directly in the reconstruction using a multiple-coils generalized matrix formulation method. This approach was tested on healthy volunteers and compared against a conventional diaphragmatic navigator-gated acquisition using quantitative and qualitative image quality assessment.

RESULTS

The proposed approach achieved 47 ± 12% and 59 ± 6% vessel sharpness for the right (RCA) and left (LAD) coronary arteries, respectively. Also, good quality visual scores of 2.4 ± 0.74 and 2.44 ± 0.86 were observed for the RCA and LAD (scores from 0, no to 4, excellent coronary vessel delineation). A not statically significant difference (P = 0.05) was found between the proposed method and an 8-mm navigator-gated and tracked scan, although scan efficiency increased from 61 ± 10% to 100%.

CONCLUSION

We demonstrate the feasibility of a new 3D affine respiratory motion correction technique for Cartesian whole-heart CMRA that achieves 100% scan efficiency and therefore a predictable acquisition time. This approach yields image quality comparable to that of an 8-mm navigator-gated acquisition with lower scan efficiency. Further evaluation of this technique in patients is now warranted to determine its clinical use.

Iterative k-t principal component analysis with nonrigid motion correction for dynamic three-dimensional cardiac perfusion imaging

PURPOSE

In this study, an iterative k-t principal component analysis (PCA) algorithm with nonrigid frame-to-frame motion correction is proposed for dynamic contrast-enhanced three-dimensional perfusion imaging.

METHODS

An iterative k-t PCA algorithm was implemented with regularization using training data corrected for frame-to-frame motion in the x-pc domain. Motion information was extracted using shape-constrained nonrigid image registration of the composite of training and k-t undersampled data. The approach was tested for 10-fold k-t undersampling using computer simulations and in vivo data sets corrupted by respiratory motion artifacts owing to free-breathing or interrupted breath-holds. Results were compared to breath-held reference data.

RESULTS

Motion-corrected k-t PCA image reconstruction resolved residual aliasing. Signal intensity curves extracted from the myocardium were close to those obtained from the breath-held reference. Upslopes were found to be more homogeneous in space when using the k-t PCA approach with motion correction.

CONCLUSIONS

Iterative k-t PCA with nonrigid motion correction permits correction of respiratory motion artifacts in three-dimensional first-pass myocardial perfusion imaging.