Magnetic Resonance in Medicine最新文献

Purpose: To propose a gradient-echo multiple overlapping-echo detachment (GRE-MOLED) method for rapid abdominal T₂* mapping, and to systematically validate its efficacy in non-invasive monitoring of dynamic hepatic glycometabolism.

Methods: The GRE-MOLED sequence was optimized to achieve ultrafast abdominal T₂* mapping under free-breathing without respiratory gating, the scan time per slice was only 60 ms. A deep neural network architecture was developed and trained on synthetic data generated through Bloch equation simulations to achieve direct end-to-end reconstruction of T₂* maps from GRE-MOLED images. The proposed method was evaluated through numerical abdomen experiments, water phantom experiments, test-retest experiments in healthy volunteers, and dynamic glycometabolic experiments.

Results: Quantitative analyses revealed excellent agreement between the results of our method and reference method. Numerical abdomen experiment achieved mean structural similarity index (SSIM) of 0.9818 and voxel-wise R² = 0.9163. Water phantom experiments demonstrated high linear correlation (R² = 0.9992) with a Bland-Altman bias of 0.2686 ms (95% limits of agreement: -1.1048 to 1.6420 ms). Test-retest analysis showed intra-subject coefficient of variation (CV) below 7% across multiple organs. Dynamic glycometabolism mapping successfully captured postprandial hepatic T₂* fluctuations with temporal resolution outperforming conventional breath-holding methods.

Conclusion: The GRE-MOLED method enables robust abdominal T₂* mapping under free-breathing, demonstrating obvious potential for non-invasive assessment of hepatic glycometabolic dynamics. Validation across numerical simulations, water phantom and in vivo experiments confirm technical reliability and high reproducibility.

Purpose: To push the speed and resolution limit of in vivo quantitative imaging and enable estimation of quantitative tissue parameters of subtle brain structures that were previously difficult to assess.

Methods: This study implemented an efficient quantitative imaging approach, 3D-SPI MRF, on the NexGen 7T scanner equipped with a high-performance head-only gradient and 96-channel receiver array. To address challenges associated with performing rapid mesoscale MRF on this system, acquisition and reconstruction mitigation methods were developed and incorporated into the MRF framework, including: (i) flip-angle-aware dictionary fitting to account for both B₁ ⁺ inhomogeneity and voxel-specific RF frequency response, (ii) gradient imperfection corrections via Skope measurements that incorporates a new per-TR trajectory rewinder compensation, (iii) incorporation of rapid B₁ ⁺ and B₀ mappings into the MRF sequence, and (iv) high-temporal motion navigation.

Results: Whole-brain T₁ and T₂ maps were obtained at 560-μm isotropic resolution within 4 min, where ablation studies demonstrated the necessity of the various mitigation methods implemented in removing bias and artifacts. For comparison, MRF data were acquired using current state-of-the-art method but limited to typical whole-body gradient specifications to demonstrate that the proposed developments resulted in ∼3× shorter scan time while producing more accurate parameter maps. Data were also acquired at ∼3.8× smaller voxel size, 360-μm isotropic, using the developed technique, to achieve mesoscale multi-parameter quantitative mapping in vivo.

Conclusion: Tailored 3D MRF acquisition and reconstruction were developed to enable fast and accurate T₁ and T₂ mapping across the whole-brain at mesoscale resolution on the NexGen 7T scanner.

Purpose: To develop a robust and efficient multidimensional MRI (MD-MRI) data processing framework for accurately estimating joint frequency-dependent diffusion-relaxation distributions, while overcoming computational limitations and noise instability inherent to Monte Carlo (MC) inversion.

Methods: We introduced an Informed Dictionary-guided Monte Carlo (ID-MC) strategy that incorporates data-driven dictionary matching into the inversion process, followed by targeted local mutation refinement to enhance flexibility and reduce overfitting. This hybrid approach aims to improve the stability, accuracy, and reproducibility of MD-MRI parameter estimation. We evaluated ID-MC through in silico simulations across a range of signal-to-noise ratios and in vivo test-retest experiments in the human brain. Reproducibility was assessed using intraclass correlation coefficients (ICC) and within-subject variability, allowing rigorous comparison with MC.

Results: In simulations, the ID-MC approach consistently achieved lower fitting errors and higher estimation accuracy across a wide range of noise levels, demonstrating its ability to balance local flexibility and global biological plausibility. Compared to MC inversion, ID-MC also reduced computation time by approximately 69%, highlighting its potential for time-efficient large-scale applications. In in vivo test-retest analyses, ID-MC substantially improved reproducibility, doubling the number of MD-MRI parameters with ICC greater than 0.75 relative to MC. Notably, diffusion frequency-dependent parameters, previously poorly reproducible with MC, showed up to 146% higher ICC with ID-MC.

Conclusion: By integrating data-driven dictionary matching with targeted mutation refinement, ID-MC improves the robustness, reproducibility, and computational efficiency of MD-MRI inversion, supporting studies that require highly sensitive detection of subtle brain microstructural changes.

Purpose: This work aims to develop a robust Nyquist ghost correction method for multishot echo-planar imaging (EPI). The method helps correct challenging Nyquist ghosts, particularly on scanners with high-performance gradients or ultra-high fields.

Methods: A method for multishot EPI ghost correction, called multishot dual-polarity GRAPPA (msDPG), is developed by extending the DPG concept to multishot readouts. msDPG employs tailored DPG kernels to address high-order phase differences between two EPI readout polarities, which cannot be fully addressed using linear phase correction (LPC) or non-linear phase correction (nLPC). Advanced regularizers can be readily employed with the proposed msDPG for physiologic inter-shot phase variation correction during reconstruction. Additionally, a calibration refinement method is proposed to improve the quality of the DPG calibration data and enhance reconstruction performance.

Results: Phantom and in vivo experiments on scanners with high-performance gradients and ultra-high fields demonstrated that msDPG achieved superior ghost correction performance than LPC and nLPC, reducing the ghost-to-signal ratio (GSR) by over 50%. Compared to conventional DPG, msDPG provided images with lower noise amplification, particularly for acquisitions with large in-plane acceleration. Consequently, high-fidelity, submillimeter diffusion images were obtained using msDPG with regularized reconstruction.

Conclusion: The proposed msDPG provides a robust Nyquist ghost correction method for multishot EPI, enabling submillimeter imaging with improved fidelity.

Purpose: Supine breast MRI has the potential to improve patient comfort compared to prone breast MRI, in addition to providing images in the same position as subsequent treatment protocols. Novel flexible coil arrays have enabled high SNR and parallel imaging in supine breast imaging, but the combined effect of coil and patient positioning on SNR has yet to be investigated. The aim of this study is to use a tissue-independent metric to account for tissue deformation to compare SNR between prone and supine positions, using appropriate coils for each.

Methods: Relative SNR (rSNR) metric is proposed as the ratio of SNR between a breast coil and a body coil. This metric is demonstrated to be tissue-independent, allowing for easier SNR comparisons in cases of tissue deformation. We scanned 10 female subjects and compared the rSNR in segmented regions consisting of breast tissue, chest wall, and axilla between prone and supine breast imaging.

Results: The rSNR was significantly higher in the breast tissue and chest wall in the supine position for all cases. The axilla rSNR was significantly higher in supine for four cases, with another four significantly higher in prone, and two showing no statistical difference. Using a distance-from-coil analysis, we found that the tissue is closer to the coil in supine, and that the supine coil provided higher SNR at distances closer than 4cm.

Conclusion: Our results show that using a surface array coil in the supine position can provide higher SNR than a standard setup in most subjects for most relevant regions of breast MRI.

Purpose: Segmentation of cranial nerves (CNs) bundles using magnetic resonance imaging (MRI) provides a valuable quantitative approach for analyzing the morphology and orientation of individual CNs. Currently, the CN regions can be segmented directly using deep learning-based methods. However, existing methods overlook the unique characteristics of CNs, particularly their environmental features and representation in multimodal images that may lead to suboptimal segmentation outcomes.

Methods: We proposed a dynamic-guided diffusion probability model for CNs segmentation, which enhances segmentation performance by integrating the intrinsic characteristics of CNs. A dynamic-guided mechanism approach called the SE-A-NL module was proposed. The module is capable of addressing both the varying characterization abilities of multimodal images and the long-range connections of CNs within images.

Results: Quantitative and qualitative experiments demonstrate that the proposed method surpasses current state-of-the-art approaches, delivering accurate and effective segmentation of five pairs of cranial nerves. Notably, the method outperforms existing techniques in 16 out of the 20 evaluated metrics.

Conclusion: The overall network model effectively integrates multimodal information and anatomical priors by combining multi-channel attention and non-local attention mechanisms, thereby improving CNs segmentation performance. Thorough comparative and ablation studies highlight the superior performance of the proposed method.

Purpose: Chemical shift encoding (Dixon) can simultaneously remove multiple fat peaks in multi-shot EPI diffusion-weighted imaging (ms-EPI DWI) at 3 T with low sensitivity to B₀ inhomogeneity. However, this method is not applicable at 5 T, since increased fat off-resonance frequencies cause slice position mismatches between different fat peaks. In this work, we propose a two-step strategy combining slice-selection gradient modulation (SSGM) and Dixon to enhance fat suppression for ms-EPI DWI at 5 T.

Methods: In the first step, SSGM adjusts the amplitudes of excitation and refocusing slice-selection gradients according to the off-resonance frequencies of methyl/methylene fat peaks, so that these fat slices are excited but not refocused. In the second step, the olefinic fat peak is chemical shift encoded and separated from the diffusion-weighted water images through a joint water/fat separation algorithm with structured low-rank regularization. The two-step strategy was evaluated in the leg, head-and-neck, and prostate.

Results: In vivo experiments demonstrated that the Dixon-only methods cannot simultaneously suppress all fat peaks at 5 T, while this problem was addressed by combining SSGM and Dixon. SSGM showed superior suppression for methyl/methylene fat compared to SPAIR. The following Dixon further removed olefinic fat untouched by SPAIR. Qualitative analysis showed improved overall image quality for all anatomies. Prostate experiments showed that the proposed method is also applicable in reduced FOV acquisitions, high-resolution (1.6-mm isotropic) and high b value imaging (2800 s/mm²).

Conclusion: The proposed two-step strategy improved fat suppression in ms-EPI DWI at 5 T, which can potentially enhance whole-body disease screening and diagnosis.

Purpose: Investigating time-division multiplexing for parallel transmission in ultra high-field imaging, striving for homogeneous whole brain excitation with a limited number of RF channels.

Methods: A fast RF switch was built to alternately route 8 transmit channels to each row of a double-row 16-element transmit coil array at a 9.4 T human MRI system. Methods for SAR monitoring and pulse design for this temporal degree of freedom were developed and investigated in electromagnetic simulations and in vivo measurements, employing parallel transmission kT points pulses aiming for homogeneous whole-brain excitation. The achievable trade-off between local SAR and excitation homogeneity was compared for multiplexed and simultaneous transmission.

Results: Using time-division multiplexing, similar excitation fidelity as with 16 transmit channels can be achieved with only 8 channels. For instance, multiplexing reduces the flip angle inhomogeneity by 2.22-fold compared to exciting only a single row of the array, and by 1.85-fold compared to statically splitting and routing 8 channels to 16 transmit coil elements. As a trade-off, compared to simultaneous excitation, multiplexing requires either increased pulse duration or amplitudes, the latter causing increased SAR. However, with appropriate SAR-aware pulse design, the multiplexing-induced local SAR increase can be controlled. This allows for viable pulse design solutions for the considered low-flip-angle imaging scenarios.

Conclusion: Time-division multiplexing allows driving a larger number of transmit elements with a smaller number of RF channels, resulting in improved parallel transmission performance. This opens up new possibilities for using advanced multi-row transmit coil arrays in sites with only 8 RF channels available.

Our goal was to understand the barriers and challenges to clinical translation of quantitative MR (qMR) as perceived by stakeholders in the UK. We conducted an electronic survey on seven key areas related to clinical translation of qMR, developed at the BIC-ISMRM workshop: “Steps on the path to clinical translation”. Based on the seven areas identified: (i) clinical workflow, (ii) changes in clinical practice, (iii) improving validation, (iv) standardization of data acquisition and analysis, (v) sharing of data and code, (vi) improving quality management, and (vii) end-user engagement, a 40-question survey was developed. Members of BIC-ISMRM, MR-PHYSICS, BSNR and institutional mailing lists were invited to respond to the online survey over a 5-week period between September and October 2022. The responses were analysed via descriptive statistics of multiple-choice questions, Likert scores and a thematic analysis of free text questions. A total of 69 responses were received from predominantly research imaging scientists (69%) in numerous centres across the UK. Three main themes were identified: (1) Consensus; the need to develop in terminology, decision making and validation; (2) Context Dependency; an appreciation of the uniqueness of each clinical situation, and (3) Product Profile; a clear description of the imaging biomarker and its intended use. Effective translation of qMR imaging and spectroscopic biomarkers to achieve their full clinical potential must address the differing needs and expectations of a wide range of stakeholders.