Magnetic Resonance in Medicine最新文献

{"title":"Feasibility of magnetic resonance elastography in the healthy rat heart.","authors":"Lisa Smith, Vidar Magne Skulberg, Lili Zhang, Ivar Sjaastad, Emil Knut Stenersen Espe","doi":"10.1002/mrm.30504","DOIUrl":"https://doi.org/10.1002/mrm.30504","url":null,"abstract":"<p><strong>Purpose: </strong>Develop a MR elastography (MRE) protocol to detect in vivo cardiac stiffness in rats.</p><p><strong>Methods: </strong>This study was approved by the National Animal Research Authority. A healthy, adult, male Sprague-Dawley rat underwent cardiac MRE. A specialized direct shaking cardiac MRE setup and MRI protocol were designed. Stiffness was measured at 15 cardiac phases. A single midventricular slice was acquired, and intrasession variability was measured. A direct inversion of the Helmholtz equation was used to calculate the stiffness from MRE images.</p><p><strong>Results: </strong>In the healthy rat, the early systolic stiffness was 2.90 kPa. The stiffness increased to the end systole (3.81 kPa), followed by a reduction during diastole to 2.61 kPa. The intrasession correlation was ρ = 0.88 (p < 0.001).</p><p><strong>Conclusion: </strong>This study demonstrates the feasibility of cardiac MRE in rats. Our results confirm that cardiac stiffness increases from early systole to end systole, followed by a decrease in diastole.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gradient system characterization of a 1.5 T MR-Linac with application to 4D UTE imaging for adaptive MR-guided radiotherapy of lung cancer","authors":"Rosie Goodburn,&nbsp;Tom Bruijnen,&nbsp;Bastien Lecoeur,&nbsp;Prashant Nair,&nbsp;Merina Ahmed,&nbsp;Helen Barnes,&nbsp;Uwe Oelfke,&nbsp;Andreas Wetscherek","doi":"10.1002/mrm.30505","DOIUrl":"10.1002/mrm.30505","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To measure the gradient system transfer function (GSTF) of an MR-Linac (Elekta Unity, Stockholm, Sweden) using an accessible phantom-based method and to apply trajectory corrections for UTE image reconstruction in the context of MR-guided radiotherapy of lung cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The first-order GSTF of a 1.5 T, split gradient Elekta Unity MR-Linac was measured using a thin-slice technique to characterize gradient system imperfections for each physical gradient axis (X, Y, Z). Repeatability measurements of the GSTF were performed 48 h apart. The GSTF was applied to trajectory correction in multi-echo UTE image reconstruction (TEs = 0.176, 1.85, 3.52 ms) to allow for UTE-Dixon inputs in the generation of synthetic CT. Images were acquired in an anthropomorphic phantom and in two free-breathing lung cancer patients. For patient scans, respiratory-correlated 4D-MR images were reconstructed using self-navigation and an iterative compressed-sensing algorithm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The GSTF magnitude was similar across the X/Y/Z axes up to ˜6 kHz. The GSTF phase was similar between the X/Y/Z components up to ˜3 kHz. Repeatability measurements demonstrated minimal variations corresponding to a system delay difference of 0.06 μs. Corrected UTE trajectory spokes are shifted approximately 1 m⁻¹ compared to the nominal <i>k</i>-space location. Corrected phantom and patient UTE images exhibited improved signal uniformity and contrast and reduced halo and signal loss artifacts. Trajectory correction for the later TE images did not improve overall image quality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The proposed GSTF measurement method using standard MR-Linac hardware enables successful trajectory correction in UTE imaging reconstruction, with applications to lung synthetic CT generation for MR-guided radiotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":"94 1","pages":"28-40"},"PeriodicalIF":3.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mrm.30505","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Referenceless 4D flow MRI using radial balanced SSFP at 0.6 T.","authors":"Charles McGrath, Pietro Dirix, Vincent Vousten, Jouke Smink, Ece Ercan, Peter Börnert, Sebastian Kozerke","doi":"10.1002/mrm.30503","DOIUrl":"https://doi.org/10.1002/mrm.30503","url":null,"abstract":"<p><strong>Purpose: </strong>To implement four-dimensional-flow MRI using phase-contrast balanced steady-state free precession (bSSFP) at 0.6 T using a free-running three-dimensional (3D) radial trajectory and referenceless background phase correction.</p><p><strong>Methods: </strong>A free-running, wobbling Archimedean spiral approach including bipolar velocity-encoding gradients (3D PC-bSSFP) was implemented on a 0.6T prototype scanner. Bipolar rewinder gradients were added to ensure first-moment nulling per repetition time. Velocity encoding was performed using a three-point encoding scheme (i.e., omitting a reference measurement). Advanced computer simulations were carried out to validate the approach. Image reconstruction was performed using a locally low-rank approach. Results for anatomical visualization and flow quantification were reconstructed separately with different regularization factors. Background phase correction was achieved using phase estimation on time-averaged reconstructions. In vivo data were acquired in 6 healthy subjects during free breathing. Additional two-dimensional (2D) phase-contrast spoiled gradient-echo (2D PC-GRE) breath-hold data were obtained for reference to compare flow values in the ascending aorta, descending aorta, and pulmonary trunk.</p><p><strong>Results: </strong>Velocity data acquired with 3D PC-bSSFP compared well with 2D PC-GRE (root mean square error = 3.96 cm/s), with minor underestimation of velocities (-0.52 cm/s). Cardiac phase-dependent signal-to-noise ratios normalized for differences in scan time and resolution between 3D PC-bSSFP and 2D PC-GRE demonstrate relatively steady values for 3D PC-bSSFP when compared to 2D PC-bSSFP with some reduction during phases of high flow.</p><p><strong>Conclusion: </strong>Free-running, referenceless, four-dimensional-flow MRI using radial 3D PC-bSSFP is feasible on a lower-field 0.6T system, producing adequate flow quantification while yielding simultaneously reasonable cine images for concurrent flow and functional assessment of the heart and great vessels.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous 3D quantitative magnetization transfer imaging and susceptibility mapping.","authors":"Albert Jang, Kwok-Shing Chan, Azma Mareyam, Jason Stockmann, Susie Yi Huang, Nian Wang, Hyungseok Jang, Hong-Hsi Lee, Fang Liu","doi":"10.1002/mrm.30493","DOIUrl":"https://doi.org/10.1002/mrm.30493","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;Introduce a unified acquisition and modeling strategy to simultaneously quantify magnetization transfer (MT), tissue susceptibility ( &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;χ&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$$ chi $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ) and &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;T&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt; &lt;mo&gt;*&lt;/mo&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_2^{ast } $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; .&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Theory and methods: &lt;/strong&gt;Magnetization transfer is induced through the application of off-resonance irradiation between excitation and acquisition of an RF-spoiled gradient-echo scheme, where free pool spin-lattice relaxation ( &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;T&lt;/mi&gt; &lt;mn&gt;1&lt;/mn&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1^{mathrm{F}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ), macromolecular proton fraction ( &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$$ f $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ) and magnetization exchange rate ( &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;k&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {k}_{mathrm{F}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; ) were calculated by modeling the magnitude of the MR signal using a binary spin-bath MT model with &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;B&lt;/mi&gt; &lt;mn&gt;1&lt;/mn&gt; &lt;mo&gt;+&lt;/mo&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {B}_1^{+} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; inhomogeneity correction via Bloch-Siegert shift. Simultaneously, a multi-echo acquisition is incorporated into this framework to measure the time evolution of both signal magnitude and phase, which was further modeled for estimating &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;T&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt; &lt;mo&gt;*&lt;/mo&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_2^{ast } $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; and tissue susceptibility. In this work, we demonstrate the feasibility of this new acquisition and modeling strategy in vivo on the brain tissue.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In vivo brain experiments were conducted on five healthy subjects to validate our method. Utilizing an analytically derived signal model, we simultaneously obtained 3D &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;T&lt;/mi&gt; &lt;mn&gt;1&lt;/mn&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1^{mathrm{F}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; , &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$$ f $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; , &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;k&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {k}_{mathrm{F}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; , &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;χ&lt;/mi&gt;&lt;/mrow&gt; &lt;annotation&gt;$$ chi $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; and &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt;&lt;msubsup&gt;&lt;mi&gt;T&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt; &lt;mo&gt;*&lt;/mo&gt;&lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_2^{ast } $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; maps of the whole brain. Our results from the brain regional analysis show good agreement with those previously reported in the literature, which used separate MT and QSM methods.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;A unified acquisition and modeling strategy based ","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetization transfer explains most of the T1 variability in the MRI literature","authors":"Jakob Assländer,&nbsp;Sebastian Flassbeck","doi":"10.1002/mrm.30451","DOIUrl":"10.1002/mrm.30451","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To identify the predominant source of the &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; variability described in the literature, which ranges from 0.6–1.1 s for brain white matter at 3 T.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;25 &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;-mapping methods from the literature were simulated with a mono-exponential and various magnetization-transfer (MT) models, each followed by mono-exponential fitting. A single set of model parameters was assumed for the simulation of all methods, and these parameters were estimated by fitting the simulation-based to the corresponding literature &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; values of white matter at 3 T. We acquired in vivo data with a quantitative magnetization transfer and three &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;-mapping techniques. The former was used to synthesize MR images that correspond to the three &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 ","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":"94 1","pages":"293-301"},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetization transfer imaging using non-balanced SSFP at ultra-low field.","authors":"Sharada Balaji, Neale Wiley, Adam Dvorak, Francesco Padormo, Rui P A G Teixiera, Megan E Poorman, Alex MacKay, Tobias Wood, Adam R Cassidy, Anthony Traboulsee, David K B Li, Irene Vavasour, Steven C R Williams, Sean C L Deoni, Emil Ljungberg, Shannon H Kolind","doi":"10.1002/mrm.30494","DOIUrl":"https://doi.org/10.1002/mrm.30494","url":null,"abstract":"<p><strong>Purpose: </strong>Ultra-low field MRI scanners have the potential to improve health care delivery, both through improved access in areas where there are few MRI scanners and allowing more frequent monitoring of disease progression and treatment response. This may be particularly true in white matter disorders, including leukodystrophies and multiple sclerosis, in which frequent myelin-sensitive imaging, such as magnetization transfer (MT) imaging, might improve clinical care and patient outcomes.</p><p><strong>Methods: </strong>We implemented an on-resonance approach to MT imaging on a commercial point-of-care 64 mT scanner using a non-balanced steady-state free precession sequence. Phantom and in vivo experiments were used to evaluate and optimize the sequence sensitivity and reproducibility, and to demonstrate in vivo performance and inter-site reproducibility.</p><p><strong>Results: </strong>From phantom experiments, T₁ and T₂ effects were determined to have a negligible effect on the differential MT weighting. MT ratio (MTR) values in white matter were 23.1 ± 1.0% from 10 healthy volunteers, with an average reproducibility coefficient of variation of 1.04%. Normal-appearing white matter MTR values in a multiple sclerosis participant (21.5 ± 6.2%) were lower, but with a similar spread of values, compared to an age-matched healthy volunteer (23.3 ± 6.2%).</p><p><strong>Conclusion: </strong>An on-resonance MT imaging approach was developed at 64 mT that can be performed in as little as 4 min. A semi-quantitative myelin-sensitive imaging biomarker at this field strength is available for assessing both myelination and demyelination.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulated radiation levels and patterns of MRI without a Faraday shielded room.","authors":"Ehsan Kazemivalipour, Bastien Guerin, Lawrence L Wald","doi":"10.1002/mrm.30499","DOIUrl":"https://doi.org/10.1002/mrm.30499","url":null,"abstract":"<p><strong>Purpose: </strong>We characterize electromagnetic (EM) radiation patterns and levels in conventional MRI systems as a function of field strength and load symmetry, providing a framework for mitigation strategies allowing operation without a shielded room.</p><p><strong>Methods: </strong>We simulated the far-field radiation pattern and fields at a 10 m radius (|E|_10m and |B|_10m) for a solenoidal superconducting MRI with a body birdcage coil operated between 0.25T and 6.5T. Five load configurations probed the impact of load-symmetry, ranging from a sphere to a body load (least-symmetric). We also assessed simple layered EM absorbers at the bore-ends.</p><p><strong>Results: </strong>All configurations exceeded regulatory limits for realistic transmit levels. At 1.5T, a 300 V_rms RF-pulse is 2700-fold the |E|_10m limit. Field strength and load symmetry strongly modulate radiation patterns and levels. The radiated power increased by more than four orders of magnitude from 0.25T to 6.5T. Spherical load radiation transitioned from a peak gain at the bore-ends (0.25-0.5T) to a donut-shaped pattern, suggesting current loops around the bore (1 T-1.5T), back to bore-axis-directed gain, suggesting propagating waves along the bore (2T-6.5T). Transition patterns were seen between these regimes; uniform radiation at 0.75T and a combined donut/bore-directed pattern at 1.75T. Load asymmetry increased both strength and pattern asymmetry, with the body load having the highest and least symmetric radiation with the legs facilitating wave propagation at high-fields. A simple optimized layered absorber at scanner's service-end reduced 3T peak radiation by 11 dB.</p><p><strong>Conclusion: </strong>Radiation from unshielded scanners far exceeds regulatory limits, particularly at high-field. Mitigation strategies must address load-symmetry, field strength, and wave effects.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerated EPR imaging using deep learning denoising","authors":"Irene Canavesi,&nbsp;Navin Viswakarma,&nbsp;Boris Epel,&nbsp;Alan McMillan,&nbsp;Mrignayani Kotecha","doi":"10.1002/mrm.30473","DOIUrl":"10.1002/mrm.30473","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Trityl OXO71-based pulse electron paramagnetic resonance imaging (EPRI) is an excellent technique to obtain partial pressure of oxygen (pO₂) maps in tissues. In this study, we used deep learning techniques to denoise 3D EPR amplitude and pO₂ maps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>All experiments were performed using a 25 mT EPR imager, JIVA-25®. The MONAI implementation of four neural networks (autoencoder, Attention UNet, UNETR, and UNet) was tested, and the best model (UNet) was then enhanced with joint bilateral filters (JBF). The training dataset was comprised of 227 3D images (56 in vivo and 171 in vitro), 159 images for training, 45 for validation, and 23 for testing. UNet with 1, 2, and 3 JBF layers was tested to improve image SNR, focusing on multiscale structural similarity index measure and edge sensitivity preservation. The trained algorithm was tested using acquisitions with 15, 30, and 150 averages in vitro with a sealed deoxygenated OXO71 phantom and in vivo with fibrosarcoma tumors grown in a hind leg of C3H mice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We demonstrate that UNet with 2 JBF layers (UNet+JBF2) provides the best outcome. We demonstrate that using the UNet+JBF2 model, the SNR of 15-shot amplitude maps provides higher SNR compared to 150-shot pre-filter maps, both in phantoms and in tumors, therefore, allowing 10-fold accelerated imaging. We demonstrate that the trained algorithm improves SNR in pO₂ maps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We demonstrate the application of deep learning techniques to EPRI denoising. Higher SNR will bring the EPRI technique one step closer to clinics.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":"94 1","pages":"436-446"},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic glucose enhanced imaging using direct water saturation","authors":"Linda Knutsson,&nbsp;Nirbhay N. Yadav,&nbsp;Sajad Mohammed Ali,&nbsp;David Olayinka Kamson,&nbsp;Eleni Demetriou,&nbsp;Anina Seidemo,&nbsp;Lindsay Blair,&nbsp;Doris D. Lin,&nbsp;John Laterra,&nbsp;Peter C. M. van Zijl","doi":"10.1002/mrm.30447","DOIUrl":"10.1002/mrm.30447","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based linewidth <i>(LW)</i> broadening of the direct water saturation (DS) curve of the water saturation spectrum (Z-spectrum) during and after glucose infusion (DS-DGE MRI).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To estimate the glucose-infusion-induced <i>LW</i> changes <i>(</i>Δ<i>LW)</i>, Bloch-McConnell simulations were performed for normoglycemia and hyperglycemia in blood, gray matter (GM), white matter (WM), CSF, and malignant tumor tissue. Whole-brain DS-DGE imaging was implemented at 3 T using dynamic Z-spectral acquisitions (1.2 s per offset frequency, 38 s per spectrum) and assessed on four brain tumor patients using infusion of 35 g of D-glucose. To assess Δ<i>LW</i>, a deep learning-based Lorentzian fitting approach was used on voxel-based DS spectra acquired before, during, and post-infusion. Area-under-the-curve <i>(AUC)</i> images, obtained from the dynamic Δ<i>LW</i> time curves, were compared qualitatively to perfusion-weighted imaging parametric maps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In simulations, Δ<i>LW</i> was 1.3%, 0.30%, 0.29/0.34%, 7.5%, and 13% in arterial blood, venous blood, GM/WM, malignant tumor tissue, and CSF, respectively. In vivo, Δ<i>LW</i> was approximately 1% in GM/WM, 5% to 20% for different tumor types, and 40% in CSF. The resulting DS-DGE <i>AUC</i> maps clearly outlined lesion areas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>DS-DGE MRI is highly promising for assessing D-glucose uptake. Initial results in brain tumor patients show high-quality <i>AUC</i> maps of glucose-induced line broadening and DGE-based lesion enhancement similar and/or complementary to perfusion-weighted imaging.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":"94 1","pages":"15-27"},"PeriodicalIF":3.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mrm.30447","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative multislice and jointly optimized rapid CEST for in vivo whole-brain imaging.","authors":"Ouri Cohen, Robert J Young, Ricardo Otazo","doi":"10.1002/mrm.30488","DOIUrl":"https://doi.org/10.1002/mrm.30488","url":null,"abstract":"<p><strong>Purpose: </strong>To develop a quantitative multislice chemical exchange saturation transfer (CEST) schedule optimization and pulse sequence that reduces the loss of sensitivity inherent to multislice sequences.</p><p><strong>Methods: </strong>A deep learning framework was developed for simultaneous optimization of scan parameters and slice order. The optimized sequence was tested in numerical simulations against a random schedule and an optimized single-slice schedule. The scan efficiency of each schedule was quantified. Three healthy subjects were scanned with the proposed sequence. Regions of interest in white matter (WM) and gray matter (GM) were defined. The sequence was compared with the single-slice sequence in vivo and differences quantified using Bland-Altman plots. Test-retest reproducibility was assessed, and the Lin's concordance correlation coefficient (CCC) was calculated for WM and GM. Intersubject variability was also measured with the CCC. Feasibility of whole-brain clinical imaging was tested using a multislab acquisition in 1 subject.</p><p><strong>Results: </strong>The optimized multislice sequence yielded a lower mean error than the random schedule for all tissue parameters and a lower error than the optimized single-slice schedule for four of six parameters. The optimized multislice sequence provided the highest scan efficiency. In vivo tissue-parameter values obtained with the proposed sequence agreed well with those of the optimized single-slice sequence and prior studies. The average WM/GM CCC was 0.8151/0.7779 for the test-retest scans and 0.7792/0.7191 for the intersubject variability experiment.</p><p><strong>Conclusion: </strong>A multislice schedule optimization framework and pulse sequence were demonstrated for quantitative CEST. The proposed approach enables accurate and reproducible whole-brain quantitative CEST imaging in clinically relevant scan times.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}