Rigid motion correction for magnetic resonance fingerprinting with sliding-window reconstruction and image registration

Nonuniform sliding-window reconstruction for accelerated dual contrast agent quantification with MR fingerprinting

OBJECTIVE

MR fingerprinting (MRF) can enable preclinical studies of cell tracking by quantifying multiple contrast agents simultaneously, but faster scan times are required for in vivo applications. Sliding window (SW)-MRF is one option for accelerating MRF, but standard implementations are not sufficient to preserve the accuracy of T2*, which is critical for tracking iron-labelled cells in vivo.

PURPOSE

To develop a SW approach to MRF which preserves the T2* accuracy required for accelerated concentration mapping of iron-labelled cells on single-channel preclinical systems.

METHODS

A nonuniform SW was applied to the MRF sequence and dictionary. Segments of the sequence most sensitive to T2* were subject to a shorter window length, preserving the T2* sensitivity. Phantoms containing iron-labelled CD8+ T cells and gadolinium were used to compare 24× undersampled uniform and nonuniform SW-MRF parameter maps. Dual concentration maps were generated for both uniform and nonuniform MRF and compared.

RESULTS

Lin's concordance correlation coefficient, compared to gold standard parameter values, was much greater for nonuniform SW-MRF than for uniform SW-MRF. A Wilcoxon signed-rank test showed no significant difference between nonuniform SW-MRF and gold standards. Nonuniform SW-MRF outperformed the uniform SW-MRF concentration maps for all parameters, providing a balance between T2* sensitivity of short window lengths, and SNR of longer window lengths.

CONCLUSIONS

Nonuniform SW-MRF improves the accuracy of matching compared to uniform SW-MRF, allowing higher accelerated concentration mapping for preclinical systems.

Improving motion robustness of 3D MR fingerprinting with a fat navigator

PURPOSE

To develop a 3D MR fingerprinting (MRF) method in combination with fat navigators to improve its motion robustness for neuroimaging.

METHODS

A rapid fat navigator was developed using the stack-of-spirals acquisition and non-Cartesian spiral GRAPPA. The fat navigator module was implemented in the 3D MRF sequence with high scan efficiency. The developed method was first validated in phantoms and five healthy subjects with intentional head motion. The method was further applied to infants with neonatal opioid withdrawal symptoms. The 3D MRF scans with fat navigators acquired with and without acceleration along the partition-encoding direction were both examined in the study.

RESULTS

Both phantom and in vivo results demonstrated that the added fat navigator modules did not influence the quantification accuracy in MRF. In combination with non-Cartesian spiral GRAPPA, a rapid fat navigator sampling with whole-brain coverage was achieved in ˜0.5 s at 3T, reducing its sensitivity to potential motion. Based on the motion waveforms extracted from fat navigators, the motion robustness of the 3D MRF was largely improved. With the proposed method, the motion-corrupted MRF datasets yielded T1 and T2 maps with significantly reduced artifacts and high correlations with measurements from the reference motion-free MRF scans.

CONCLUSION

We developed a 3D MRF method coupled with rapid fat navigators to improve its motion robustness for quantitative neuroimaging. Our results demonstrate that (1) accurate tissue quantification was preserved with the fat navigator modules and (2) the motion robustness for quantitative tissue mapping was largely improved with the developed method.

Prospective motion correction and automatic segmentation of penetrating arteries in phase contrast MRI at 7 T

PURPOSE

To develop a prospective motion correction (MC) method for phase contrast (PC) MRI of penetrating arteries (PAs) in centrum semiovale at 7 T and to evaluate its performance using automatic PA segmentation.

METHODS

Head motion was monitored and corrected during the scan based on fat navigator images. Two convolutional neural networks (CNN) were developed to automatically segment PAs and exclude surface vessels. Real-life scans with MC and without MC (NoMC) were performed to evaluate the MC performance. Motion score was calculated from the ranges of translational and rotational motion parameters. MC versus NoMC pairs with similar motion scores during MC and NoMC scans were compared. Data corrupted by motion were reacquired to further improve PA visualization.

RESULTS

PA counts (N_PA ) and PC and magnitude contrasts (MgC) relative to neighboring tissue were significantly correlated with motion score and were higher in MC than NoMC images at motion scores above 0.5-0.8 mm. Data reacquisition further increased PC but had no significant effect on N_PA and MgC. CNNs had higher sensitivity and Dice similarity coefficient for detecting PAs than a threshold-based method.

CONCLUSIONS

Prospective MC can improve the count and contrast of segmented PAs in the presence of severe motion. CNN-based PA segmentation has improved performance in delineating PAs than the threshold-based method.

Motion corrected silent ZTE neuroimaging

Purpose

To develop self‐navigated motion correction for 3D silent zero echo time (ZTE) based neuroimaging and characterize its performance for different types of head motion.

Methods

The proposed method termed MERLIN (Motion Estimation & Retrospective correction Leveraging Interleaved Navigators) achieves self‐navigation by using interleaved 3D phyllotaxis k‐space sampling. Low resolution navigator images are reconstructed continuously throughout the ZTE acquisition using a sliding window and co‐registered in image space relative to a fixed reference position. Rigid body motion corrections are then applied retrospectively to the k‐space trajectory and raw data and reconstructed into a final, high‐resolution ZTE image.

Results

MERLIN demonstrated successful and consistent motion correction for magnetization prepared ZTE images for a range of different instructed motion paradigms. The acoustic noise response of the self‐navigated phyllotaxis trajectory was found to be only slightly above ambient noise levels (<4 dBA).

Conclusion

Silent ZTE imaging combined with MERLIN addresses two major challenges intrinsic to MRI (i.e., subject motion and acoustic noise) in a synergistic and integrated manner without increase in scan time and thereby forms a versatile and powerful framework for clinical and research MR neuroimaging applications.

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain

PURPOSE

To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates.

METHODS

Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world.

RESULTS

The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction.

CONCLUSIONS

Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer

Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.

Quantitative T1 and T2 mapping by magnetic resonance fingerprinting (MRF) of the placenta before and after maternal hyperoxia

INTRODUCTION

MR relaxometry has been used to assess placental exchange function, but methods to date are not sufficiently fast to be robust to placental motion. Magnetic resonance fingerprinting (MRF) permits rapid, voxel-wise, intrinsically co-registered T₁ and T₂ mapping. After characterizing measurement error, we scanned pregnant women during air and oxygen breathing to demonstrate MRF's ability to detect placental oxygenation changes.

METHODS

The accuracy of FISP-based, sliding-window reconstructed MRF was tested on phantoms. MRF scans in 9-s breath holds were acquired at 3T in 31 pregnant women during air and oxygen breathing. A mixed effects model was used to test for changes in placenta relaxation times between physiological states, to assess the dependency on gestational age (GA), and the impact of placental motion.

RESULTS

MRF estimates of known phantom relaxation times resulted in mean absolute errors for T₁ of 92 ms (4.8%), but T₂ was less accurate at 16 ms (13.6%). During normoxia, placental T₁ = 1825 ± 141 ms (avg ± standard deviation) and T₂ = 60 ± 16 ms (gestational age range 24.3-36.7, median 32.6 weeks). In the statistical model, placental T₂ rose and T₁ remained contant after hyperoxia, and no GA dependency was observed for T₁ or T₂.

DISCUSSION

Well-characterized, motion-robust MRF was used to acquire T₁ and T₂ maps of the placenta. Changes with hyperoxia are consistent with a net increase in oxygen saturation. Toward the goal of whole-placenta quantitative oxygenation imaging over time, we aim to implement 3D MRF with integrated motion correction to improve T₂ accuracy.

Free-breathing abdominal T1 mapping using an optimized MR fingerprinting sequence

In this work, we propose a free-breathing magnetic resonance fingerprinting (MRF) method that can be used to obtain B₁⁺ -robust quantitative T₁ maps of the abdomen in a clinically acceptable time. A three-dimensional MRF sequence with a radial stack-of-stars trajectory was implemented, and its k-space acquisition ordering was adjusted to improve motion-robustness in the context of MRF. The flip angle pattern was optimized using the Cramér-Rao Lower Bound, and the encoding efficiency of sequences with 300, 600, 900 and 1800 flip angles was evaluated. To validate the sequence, a movable multicompartment phantom was developed. Reference multiparametric maps were acquired under stationary conditions using a previously validated MRF method. Periodic motion of the phantom was used to investigate the motion-robustness of the proposed sequence. The best performing sequence length (600 flip angles) was used to image the abdomen during a free-breathing volunteer scan. When using a series of 600 or more flip angles, the estimated T₁ values in the stationary phantom showed good agreement with the reference scan. Phantom experiments revealed that motion-related artifacts can appear in the quantitative maps and confirmed that a motion-robust k-space ordering is essential. The in vivo scan demonstrated that the proposed sequence can produce clean parameter maps while the subject breathes freely. Using this sequence, it is possible to generate B₁⁺ -robust quantitative maps of T₁ and B₁⁺ next to M₀ -weighted images under free-breathing conditions at a clinically usable resolution within 5 min.

Free-Breathing Abdominal Magnetic Resonance Fingerprinting Using a Pilot Tone Navigator

BACKGROUND

Quantitative T1 and T2 mapping in the abdomen provides valuable information in tissue characterization but is technically challenging due to respiratory motions. The proposed technique integrates magnetic resonance fingerprinting (MRF) and pilot tone (PT) navigator with retrospective gating to provide simultaneous quantification of multiple tissue properties in a single acquisition without breath-holding or patient set-up.

PURPOSE

To develop a free-breathing abdominal MRF technique for quantitative mapping in the abdomen.

STUDY TYPE

Prospective.

POPULATION

Twelve healthy volunteers.

FIELD STRENGTH/SEQUENCE

A 3 T, two-dimensional (2D) and three-dimensional (3D) spiral MRF sequence with fast imaging with steady-state free precession (FISP) readout.

ASSESSMENT

The PT navigator was compared to standard respiratory belt performance. The T1 and T2 values acquired using 2D and 3D MRF with and without PT were obtained in a phantom and compared to reference values. Digital phantom simulation was performed to evaluate PT MRF reconstruction with varying breathing patterns. In the in vivo studies, T1 and T2 values derived from PT 2D MRF were compared to 2D breath-hold MRF. T1 and T2 values derived from PT 3D MRF were compared to published values.

STATISTICAL TESTS

Principal component analysis (PCA), linear regression, relative error, Pearson correlation, paired Student's t-test, Bland-Altman Analysis.

RESULTS

The phantom study showed PT MRF T1 values had a mean difference of 0.2% ± 0.1%, and T2 values had a mean difference of 0.1% ± 0.4% when compared to no-PT MRF values. The digital phantom experiment suggested the T1 and T2 maps at both end-exhalation and end-inhalation states resemble the corresponding ground-truth maps.

DATA CONCLUSION

The phantom study showed good agreement between MRF T1 and T2 values and with reference values. In vivo studies demonstrated that 2D and 3D quantitative imaging in the abdomen could be achieved with integration of PT navigation with MRF reconstruction using retrospective gating of respiratory motion. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Cardiac cine magnetic resonance fingerprinting for combined ejection fraction, T1 and T2 quantification

This study introduces a technique called cine magnetic resonance fingerprinting (cine-MRF) for simultaneous T₁ , T₂ and ejection fraction (EF) quantification. Data acquired with a free-running MRF sequence are retrospectively sorted into different cardiac phases using an external electrocardiogram (ECG) signal. A low-rank reconstruction with a finite difference sparsity constraint along the cardiac motion dimension yields images resolved by cardiac phase. To improve SNR and precision in the parameter maps, these images are nonrigidly registered to the same phase and matched to a dictionary to generate T₁ and T₂ maps. Cine images for computing left ventricular volumes and EF are also derived from the same data. Cine-MRF was tested in simulations using a numerical relaxation phantom. Phantom and in vivo scans of 19 subjects were performed at 3 T during a 10.9 seconds breath-hold with an in-plane resolution of 1.6 x 1.6 mm² and 24 cardiac phases. Left ventricular EF values obtained with cine-MRF agreed with the conventional cine images (mean bias -1.0%). Average myocardial T₁ times in diastole/systole were 1398/1391 ms with cine-MRF, 1394/1378 ms with ECG-triggered cardiac MRF (cMRF) and 1234/1212 ms with MOLLI; and T₂ values were 30.7/30.3 ms with cine-MRF, 32.6/32.9 ms with ECG-triggered cMRF and 37.6/41.0 ms with T₂ -prepared FLASH. Cine-MRF and ECG-triggered cMRF relaxation times were in good agreement. Cine-MRF T₁ values were significantly longer than MOLLI, and cine-MRF T₂ values were significantly shorter than T₂ -prepared FLASH. In summary, cine-MRF can potentially streamline cardiac MRI exams by combining left ventricle functional assessment and T₁ -T₂ mapping into one time-efficient acquisition.

Retrospective rigid motion correction of three-dimensional magnetic resonance fingerprinting of the human brain

PURPOSE

To obtain three-dimensional (3D), quantitative and motion-robust imaging with magnetic resonance fingerprinting (MRF).

METHODS

Our acquisition is based on a 3D spiral projection k-space scheme. We compared different orderings of trajectory interleaves in terms of rigid motion-correction robustness. In all tested orderings, we considered the whole dataset as a sum of 56 segments of 7-s duration, acquired sequentially with the same flip angle schedule. We performed a separate image reconstruction for each segment, producing whole-brain navigators that were aligned to the first segment using normalized correlation. The estimated rigid motion was used to correct the k-space data, and the aligned data were matched with the dictionary to obtain motion-corrected maps.

RESULTS

A significant improvement on the motion-affected maps after motion correction is evident with the suppression of motion artifacts. Correlation with the motionless baseline improved by 20% on average for both T₁ and T₂ estimations after motion correction. In addition, the average motion-induced quantification bias of 70 ms for T₁ and 18 ms for T₂ values was reduced to 12 ms and 6 ms, respectively, improving the reliability of quantitative estimations.

CONCLUSION

We established a method that allows correcting 3D rigid motion on a 7-s timescale during the reconstruction of MRF data using self-navigators, improving the image quality and the quantification robustness.

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Magnetic resonance fingerprinting (MRF) is a powerful quantitative MRI technique capable of acquiring multiple property maps simultaneously in a short timeframe. The MRF framework has been adapted to a wide variety of clinical applications, but faces challenges in technical development, and to date has only demonstrated repeatability and reproducibility in small studies. In this review, we discuss the current implementations of MRF and their use in a clinical setting. Based on this analysis, we highlight areas of need that must be addressed before MRF can be fully adopted into the clinic and make recommendations to the MRF community on standardization and validation strategies of MRF techniques. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:675-692.

Sparsity and locally low rank regularization for MR fingerprinting

PURPOSE

Develop a sparse and locally low rank (LLR) regularized reconstruction to accelerate MR fingerprinting (MRF).

METHODS

Recent works have introduced low rank reconstructions to MRF, based on temporal compression operators learned from the MRF dictionary. In other MR applications, LLR regularization has been introduced to exploit temporal redundancy in local regions of the image. Here, we propose to include spatial sparsity and LLR regularization terms in the MRF reconstruction. This approach, so called SLLR-MRF, further reduces aliasing in the time-point images and enables higher acceleration factors. The proposed approach was evaluated in simulations, T1 /T2 phantom acquisition, and in vivo brain acquisitions in 5 healthy subjects with different undersampling factors. Acceleration was also used in vivo to enable acquisitions with higher in-plane spatial resolution in comparable scan time.

RESULTS

Simulations, phantom, and in vivo results show that low rank MRF reconstructions with high acceleration factors (<875 time-point images, 1 radial spoke per time-point) have residual aliasing artifacts that propagate into the parametric maps. The artifacts are reduced with the proposed SLLR-MRF resulting in considerable improvements in precision, without changes in accuracy. In vivo results show improved parametric maps for the proposed SLLR-MRF, potentially enabling MRF acquisitions with 1 radial spoke per time-point in approximately 2.6 s (~600 time-point images) for 2 × 2 mm and 9.6 s (1750 time-point images) for 1 × 1 mm in-plane resolution.

CONCLUSION

The proposed SLLR-MRF reconstruction further improves parametric map quality compared with low rank MRF, enabling shorter scan times and/or increased spatial resolution.