Magnetic Resonance Materials in Physics, Biology and Medicine最新文献

In-cell nuclear magnetic resonance (NMR) spectroscopy has emerged as a leading technique in structural biology, providing atomic-level insights into the structures, dynamics, and interactions of biomolecules within their native cellular environments. By bridging the gap between conventional in vitro studies and the complexity of living systems, in-cell NMR enables direct observation of biomolecular behavior under near-physiological conditions. This review highlights recent methodological advances that have expanded the scope and feasibility of in-cell NMR. Innovations in isotopic labeling, including selective incorporation strategies, have enhanced spectral resolution and sensitivity. Optimized delivery approaches, such as microinjection and electroporation, facilitate efficient introduction of labeled biomolecules into diverse cell types. The use of cryogenically cooled probes and high-field magnets further improves signal detection, enabling the study of low-abundance targets. We discuss key applications, including protein folding, conformational dynamics, biomolecular interaction networks, and nucleic acid structural rearrangements. In addition, in-cell NMR has proven invaluable for drug discovery, providing mechanistic insights into intracellular drug-target interactions. Despite these advances, challenges remain, including spectral overlap from endogenous components, low intracellular concentrations, and maintaining cell viability during extended experiments. Future developments integrating cryo-electron microscopy (cryo-EM), mass spectrometry (MS), hyperpolarization techniques, and advanced labeling strategies promise to enhance sensitivity, resolution, and applicability, solidifying in-cell NMR as an indispensable tool for probing biomolecular function in living cells.

Objective: Denoising low-field MR images is often essential to obtain image quality that is adequate for clinical diagnosis while keeping scan time patient-friendly. The recently introduced zero-shot self-supervised approach shows great promise, requiring no prior data collection for training, which is particularly challenging at low-field. Here, this scan-specific denoising approach is adapted to low-field MR data and optimized to accelerate the training process.

Material and method: We extended the zero-shot noise-as-clean method by modifying the training process to achieve faster training times. The proposed method was compared to BM4D and the recent zero-shot noise2noise methods. Denoising performance was first evaluated quantitatively on high-field data where high SNR images are available, then assessed qualitatively on prospective low-field data (0.1 T). Ultimately, we studied the denoising performance with respect to training on portions of the original data matrix as a potential strategy for further training acceleration.

Results: The proposed method achieved high denoising performance across different SNR levels within a few seconds on a GPU for typical low-field data dimensions. Additionally, training on portion of the data showed potential for further training acceleration.

Discussion: In the context of low-field MRI, this denoising method shows great potential, as it could be integrated into acquisition workflows relatively seamlessly to improve image quality. Code: https://github.com/reinaayde7/zs-nac.git.

Objectives: To develop a method for imaging near titanium implants at 0.55 T, which enables the use of a low readout bandwidth for higher SNR while reducing in-plane geometric distortions.

Materials and methods: A pair of turbo spin echo (TSE) data with opposite frequency-encoding directions is acquired. For each frequency direction, a gradient nonlinearity (GNL)-corrected image is reconstructed with a model-based iterative reconstruction incorporating GNL. A susceptibility-induced displacement map along the readout direction is estimated from two GNL-corrected images. A single final image is reconstructed with the model-based reconstruction incorporating both GNL and metal-induced displacement fields using both k-space acquisitions. The proposed method is compared against TSE with view angle tilting (VAT) and slice encoding for metal artifact correction (SEMAC).

Results: The proposed reconstruction method maintains spatial resolution compared to current correction techniques. Unlike image-domain correction, VAT, and SEMAC, it does not introduce spatial blurring at equivalent bandwidths. It is feasible to reduce distortion due to off-resonance at a low readout bandwidth, resulting in higher apparent SNR (1.4-1.6-fold) without blurring under current imaging settings. In phantoms, and in patients with total hip arthroplasty and spinal fusion, the proposed method provides clearer delineation of tissues compared to conventional methods.

Discussion: The proposed GNL and off-resonance distortion correction method for imaging near metal at 0.55 T enables the use of low readout bandwidth, providing SNR improvements without the blurring typically associated with low-bandwidth VAT.

Objective: Accurate prediction of the response to nano-photothermal therapy (NPTT) requires rapid feedback from the tumor. This study utilizes proton magnetic resonance spectroscopy (¹H-MRS) to non-invasively assess metabolic changes in glioma treated with NPTT using gold-coated iron oxide nanoparticles, providing insight into early therapeutic efficacy.

Materials and methods: The study was conducted on nude mice bearing U87-MG human glioma xenografts, which were assigned to distinct treatment cohorts: Au@Fe₂O₃ core-shell nanoparticles alone, laser irradiation alone, and the combined nano-photothermal therapy. The efficacy was determined by assessing post-treatment alterations in tumor volume and corresponding changes in choline and lipid metabolite signals detected via ¹H-MRS.

Results: Analysis of metabolite ratios, normalized to the water peak, demonstrated a significant post-NPTT therapeutic response. A marked decrease was observed in both the choline/creatine ratio (from 0.48 ± 0.17 to 0.24 ± 0.07) and the choline/lipid ratio (from 0.47 ± 0.23 to 0.13 ± 0.06). Notably, these metabolic alterations were evident within 24 h of the procedure. In contrast, significant reductions in tumor volume were not detectable until day 9 post-treatment.

Conclusion: ¹H-MRS analysis of metabolite ratios serves as a sensitive, early biomarker of the biological response to NPTT. The capacity for in vivo assessment of therapeutic efficacy within 24 h post-procedure provides a significant advantage. This rapid feedback can critically inform clinical decision-making and guide the strategic planning of subsequent cancer treatments.

Object: Repeatability and reproducibility are imperative for new Magnetic Resonance Imaging (MRI) methods, such as the quantitative technique MR Fingerprinting (MRF), to be clinically adopted for regular patient usage.

Materials and methods: We tested the repeatability and reproducibility of a new free-breathing (FB) quadratic RF phase Magnetic Resonance Fingerprinting (qRF-MRF) with Pilot Tone (PT) navigator in the abdominal cavity with a focus on liver by performing repeat scan-rescan collection comparisons for 8 healthy volunteers on 2 different Siemens Vida 3T scanners at the same site running different software versions.

Results: Using Bland-Altman analysis, our results for T1, T2, and T2* establish the repeatability and reproducibility, via the limits of agreement and bias estimations, of the FB qRF-MRF sequence and compare to its breath-held qRF-MRF and clinical standard counterparts across scanners and scan conditions.  DISCUSSION: Based on the bias and limits of agreement of breath-hold and FB qRF-MRF patients can receive reliable and comparable imaging at different sessions for prognosis and treatment planning.

Objective: This work aimed to demonstrate the feasibility of quantifying heart function during bicycling exercise with dynamic real-time cine MRI at 3 Tesla, and to assess its measurement precision.

Materials and methods: Twelve volunteers performed steady-state bicycling exercise, while real-time cine MR images were collected using a 72-channel receiver coil array and a parallel imaging acceleration factor of 5. Biventricular end-diastolic and end-systolic (ESV) volumes and function during exercise were compared with resting-state real-time cine MRI and conventional cardiac-gated cine MRI under breath holding, and validated against 2D phase-contrast MRI-based estimates of aortic blood flow. Precision was evaluated as the inter-session measurement repeatability.

Results: Left (LV) and right ventricular (RV) stroke volumes (SV) increased progressively with exercise intensity, which was mediated by a decrease in ESV. Likewise, LV SV estimated with 2D phase-contrast MRI increased from 90 ± 17 mL at rest to 114 ± 29 mL during vigorous-intensity exercise. Repeatability coefficients were 52% and 41% for LV SV at moderate- and vigorous-intensity exercise, while RV SV repeatability coefficients were 58% and 42%, respectively.

Discussion: We established an exercise MRI stress testing protocol for quantifying biventricular volumes and function during moderate- and vigorous-intensity steady-state bicycling exercise.

Objectives: Quantification of muscles and adipose depots is essential for characterising pathological changes in neuromuscular, musculoskeletal, and metabolic diseases. This study presents a deep learning framework for automated comprehensive analysis of muscle and adipose tissue in the lower extremities.

Material and methods: Axial two-point dixon magnetic resonance imaging data from thigh and calf were retrospectively collected from 25 participants (mean age: 40.5 ± 5.86 years; 64% male) from the Asian Indian Prediabetes Study. A 3D Attention-Res-V-Net pipeline was trained on expert-labelled ground truth data. A cascade of Attention-Res-V-Net models was trained to first quantify the entire muscle region and subcutaneous adipose tissue (SAT) in thigh and calf. Then, thigh and calf-specific networks quantified 13 thigh and 9 calf muscles, respectively. Intermuscular (InterMAT) and intramuscular (IntraMAT) adipose tissues were quantified by intensity thresholding fat-only image volumes within muscle-specific segmentation masks. Resulting fat voxels were multiplied by the voxel resolution to obtain adipose tissue volumes, which were evaluated as relative errors against the ground truth volumes.

Results: Whole muscle segmentation achieved mean DSCs of 92 (thigh) and 87% (calf); SAT reached 95%. Muscle-specific DSCs ranged from 76 to 90% (thigh) and 68 to 90% (calf). InterMAT errors were ~ 21% (thigh) and ~ 19% (calf), while IntraMAT errors ranged from 17.4 to 58.8%. In addition, the high-quality, expert-annotated dataset generated in this study will be publicly released to facilitate future research.

Discussion: The framework advances muscle-fat composition analysis in the lower limbs by enabling granular quantification of individual muscles, SAT, InterMAT, and muscle-specific IntraMAT.

Background: Evaluating prostate MRI resolution is challenging due to motion artifacts caused by body movement or intestinal gas, which can degrade image quality. One simple approach to resolution assessment is the ladder method, but reports of its application to clinical images remain limited. This study aimed to compare the ladder method with visual evaluation to assess its utility.

Methods: T2-weighted images of the prostate in healthy volunteers and a ladder phantom at various resolutions with altered pixel sizes (0.5, 0.7, 0.9 and 1.1 mm) were acquired. Three radiologists conducted visual evaluations of the prostate images. Correlation coefficients between the visual evaluation scores and the ladder index (LI) obtained from the ladder method were compared.

Results: Average visual evaluation scores were 7.7, 5.9, 3.8, and 2.1, while the spatial frequencies corresponding to LI = 0.5 (50%LI) were 0.86, 0.81, 0.54, and 0.42 cycles/mm for each pixel size ranging from 0.5 to 1.1 mm, demonstrating higher values at smaller pixel sizes. The correlation coefficients exceeded 0.7 at most spatial frequencies, indicating a strong correlation. Inter-reader agreement was high (Kendall's W = 0.87), indicating consistent evaluation among radiologists.

Conclusions: Spatial resolution for prostate MRI could be evaluated objectively using the ladder method.

Objective: Accurate quantitative tissue characterization in organs with considerable fat content, like the liver, requires thorough understanding of fat's influence on the MR signal. To continue the investigations into the use of quantitative susceptibility mapping (QSM) in abdominal regions, we present a dedicated phantom that replicates liver-like conditions in terms of effective transverse relaxation rates (R₂*) and proton density fat fractions.

Materials and methods: The spherical agar phantom consists of nine smaller spheres (diameter: 3 cm) doped with a paramagnetic substance (iron nanoparticles or manganese chloride) and fat (peanut oil), embedded in a large agar sphere (diameter: 14 cm), ensuring no barriers exist between the enclosed spheres and their surrounding medium. Concentrations were selected to represent both healthy and pathologic conditions. 3T MRI measurements for relaxometry, fat-water imaging, and QSM were conducted with the head coil and for ¹H-spectroscopy with the knee coil at three time points, including a scan-rescan assessment and a follow-up measurement 14 months later.

Results: The phantoms' relaxation and magnetic properties are in similar range as reported for liver tissue. Substantial alterations in local field and susceptilibty maps were observed in regions with elevated fat and iron content, where fat correction of the local field via chemical shift-encoded reconstruction effectively reduced streaking artifacts in susceptibility maps and substantially increased susceptibility values. Linear regression analysis revealed a consistent linear relationship between R₂* and magnetic susceptibility, as well as iron concentration and magnetic susceptibility. The relaxation, fat, and susceptibility measurements remained stable across scan-rescan assessment and long-term follow-up.

Discussion: We developed a versatile phantom to study fat-iron interactions in abdominal imaging, facilitating the optimization and comparison of susceptibility processing methods in future research.

Objective: To review the latest developments in self-supervised deep learning (DL) techniques for magnetic resonance imaging (MRI) reconstruction, emphasizing their potential to overcome the limitations of supervised methods dependent on fully sampled k-space data.

Background: While DL has significantly advanced MRI, supervised approaches require large amounts of fully sampled k-space data for training-a major limitation given the impracticality and expense of acquiring such data clinically. Self-supervised learning has emerged as a promising alternative, enabling model training using only undersampled k-space data, thereby enhancing feasibility and driving research interest.

Methods: We conducted a comprehensive literature review to synthesize recent progress in self-supervised DL for MRI reconstruction. The analysis focused on methods and architectures designed to improve image quality, reduce scanning time, and address data scarcity challenges, drawing from peer-reviewed publications and technical innovations in the field.

Conclusions: Self-supervised DL holds transformative potential for MRI reconstruction, offering solutions to data limitations while maintaining image quality and accelerating scans. Key challenges include robustness across diverse anatomies, standardization of validation, and clinical integration. Future research should prioritize hybrid methodologies, domain-specific adaptations, and rigorous clinical validation. This review consolidates advancements and unresolved issues, providing a foundation for next-generation medical imaging technologies.