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

Objective: To quantify the T₁ relaxation times at 7T for key abdominal organs and tissues, including the liver, kidney, spleen, and skeletal paraspinal muscles.

Materials and methods: T₁ mapping was performed on a 7T whole-body scanner with a parallel transmission (pTx) system in five healthy volunteers. Static pTx (B₁⁺ shimming) was applied to maximize B₁⁺ magnitude in the target region. For each T₁ map, data were collected using eight snapshot gradient-echo inversion recovery sequences during breath holding. Voxel-wise T₁ values were calculated based on DICOM data using exponential model fitting.

Results: Mean abdomen T₁ values and corresponding coefficients of variation across the group were: 1829 ± 60 ms, 3.3% for the kidney cortex; 2619 ± 83 ms, 3.2% for the kidney medulla; 1378 ± 48 ms, 3.5% for the liver; 1954 ± 28 ms, 1.4% for the skeletal paraspinal muscle; 1770 ± 36 ms, 2.0% for the spleen.

Conclusion: In this study, we quantified the T₁ relaxation times at 7T for key abdominal organs and tissues, including the liver, kidney, spleen, and skeletal paraspinal muscle. To achieve this, pTx was applied to mitigate B₁⁺ dropouts in the target regions. The B₁⁺ insensitive snapshot gradient-echo inversion recovery method was utilized to acquire accurate and reproducible T₁ maps.

Objective: This review aims to summarize the research progress of magnetic resonance imaging (MRI)-based deep learning ( DL) in meningiomas, analyze its advantages, limitations, and key issues in clinical translation, provide technical references for relevant medical researchers and clinicians, thereby promoting the faster and more standardized application of DL in clinical diagnosis and treatment, and ultimately benefiting patients.

Background: The early detection and accurate grading and classification of meningiomas are crucial for formulating personalized treatment plans. DL has achieved breakthrough progress in the field of meningioma imaging analysis. By adopting objective and quantitative analysis methods, it effectively overcomes the limitation of traditional diagnostic methods that rely on subjective human visual judgment, opening up broad prospects for the precise diagnosis and treatment of meningiomas.

Methods: The literature search and selection process for this review was conducted as follows: Search period: 1 January 2019 to 31 October 2024; Databases searched: PubMed, Web of Science, and Embase; Search string: (("meningioma" OR "meningiomas") AND ("magnetic resonance imaging" OR "MRI") AND ("deep learning" OR "convolutional neural network" OR "CNN" OR "transformer" OR "neural network" OR "neural networks")).

Conclusions: The application of DL in meningioma research marks that medical imaging diagnosis has entered a new intelligent stage. By providing doctors with more objective and accurate diagnostic basis, it facilitates the formulation of personalized treatment plans, thereby improving patients' treatment outcomes and quality of life. The continuous breakthroughs of DL in the field of meningiomas indicate that the future of medical imaging diagnosis will be more intelligent and precise.

Objective: To investigate the physiological factors affecting the timing of late arterial phase imaging in gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid-enhanced MRI (EOB-MRI), with a focus on contrast transit times.

Methods: This retrospective study included 122 patients who underwent EOB-MRI between April and September 2024. Contrast transit times from the right atrium to the left ventricle (RA-LV time) and to the celiac artery (RA-CeA time) were measured using real-time bolus-tracking images. Using vascular enhancement patterns, the late arterial phase timing was visually assessed and categorized as Early, Appropriate, or Delayed. Differences among the imaging timing groups were analyzed using analysis of variance (ANOVA) and post hoc Welch's t tests with Holm correction, with a significance threshold of p < 0.05.

Results: Mean RA-LV times (mean ± SD, range) were 7.0 ± 1.1 s (5.0-9.0 s), 5.2 ± 0.9 s (4.0-8.0 s), and 4.7 ± 0.6 s (4.0-6.0 s) for the Early, Appropriate, and Delayed groups, respectively; significant differences were observed between Early vs. Appropriate (p < 0.001) and Appropriate vs. Delayed (p = 0.02). Correspondingly, RA-CeA times were 12.4 ± 2.0 s (10.0-15.0 s), 8.9 ± 1.8 s (5.0-14.0 s), and 7.7 ± 1.1 s (6.0-10.0 s), respectively, with significant differences between Early vs. Appropriate (p < 0.001) and Appropriate vs. Delayed (p = 0.001). Additionally, significant differences in sex and height were observed between the Early and Appropriate groups (p < 0.01). No other variables showed significant differences.

Conclusion: Contrast transit times significantly affect the appropriateness of late arterial phase imaging in EOB-MRI. Incorporating individualized transit time assessment alongside conventional bolus tracking may improve the consistency of late arterial phase acquisition and enhance the performance for diagnosing hepatic tumors.

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.