Magnetic Resonance in Medicine最新文献

{"title":"3D joint T₁/T₁ _ρ/T₂ mapping and water-fat imaging for contrast-agent free myocardial tissue characterization at 1.5T.","authors":"Michael G Crabb, Karl P Kunze, Simon J Littlewood, Donovan Tripp, Anastasia Fotaki, Claudia Prieto, René M Botnar","doi":"10.1002/mrm.30397","DOIUrl":"https://doi.org/10.1002/mrm.30397","url":null,"abstract":"<p><strong>Purpose: </strong>To develop a novel, free-breathing, 3D joint <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> <annotation>$$ {T}_1 $$</annotation></semantics> </math> / <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>ρ</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1rho } $$</annotation></semantics> </math> / <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>2</mn></mrow> </msub> </mrow> <annotation>$$ {T}_2 $$</annotation></semantics> </math> mapping sequence with Dixon encoding to provide co-registered 3D <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> <annotation>$$ {T}_1 $$</annotation></semantics> </math> , <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>ρ</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1rho } $$</annotation></semantics> </math> , and <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>2</mn></mrow> </msub> </mrow> <annotation>$$ {T}_2 $$</annotation></semantics> </math> maps and water-fat volumes with isotropic spatial resolution in a single <math> <semantics><mrow><mo>≈</mo> <mn>7</mn></mrow> <annotation>$$ approx 7 $$</annotation></semantics> </math> min scan for comprehensive contrast-agent-free myocardial tissue characterization and simultaneous evaluation of the whole-heart anatomy.</p><p><strong>Methods: </strong>An interleaving sequence over 5 heartbeats is proposed to provide <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> <annotation>$$ {T}_1 $$</annotation></semantics> </math> , <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>ρ</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1rho } $$</annotation></semantics> </math> , and <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>2</mn></mrow> </msub> </mrow> <annotation>$$ {T}_2 $$</annotation></semantics> </math> encoding, with 3D data acquired with Dixon gradient-echo readout and 2D image navigators to enable <math> <semantics><mrow><mn>100</mn> <mo>%</mo></mrow> <annotation>$$ 100% $$</annotation></semantics> </math> respiratory scan efficiency. Images were reconstructed with a non-rigid motion-corrected, low-rank patch-based reconstruction, and maps were generated through dictionary matching. The proposed sequence was compared against conventional 2D techniques in phantoms, 10 healthy subjects, and 1 patient.</p><p><strong>Results: </strong>The proposed 3D <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn></mrow> </msub> </mrow> <annotation>$$ {T}_1 $$</annotation></semantics> </math> , <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>ρ</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1rho } $$</annotation></semantics> </math> , and <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>2</mn></mrow> </msub> </mrow> <annota","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468476","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":"An evaluation of the coax monopole antenna as a transmit array element for head imaging at 14 T.","authors":"Lyanne M I Budé, Koen Vat, Ingmar J Voogt, Irena Zivkovic, Alexander J E Raaijmakers","doi":"10.1002/mrm.30464","DOIUrl":"https://doi.org/10.1002/mrm.30464","url":null,"abstract":"<p><strong>Purpose: </strong>In comparison to dipole antennas, the coax monopole antenna (CMA) diminishes the possibility of cable-coil coupling. This greatly facilitates cable routing in spatially restricted environments, such as head coil arrays. With the outlook of a 14T MRI system being installed at the Donders Center in Nijmegen, the Netherlands, this study aims to optimize the CMA for an eight-channel head array at 14 T and compare its performance with an array of fractionated dipole antennas.</p><p><strong>Methods: </strong>Both antenna designs were optimized for head imaging at 14 T using single-channel finite-difference time-domain (FDTD) simulations at 596 MHz. Eight-channel simulations were then used on a human model to evaluate <math> <semantics> <mrow><msubsup><mi>B</mi> <mn>1</mn> <mo>+</mo></msubsup> </mrow> <annotation>$$ {mathrm{B}}_1^{+} $$</annotation></semantics> </math> and specific absorption rate (SAR) distributions. For both antenna types, prototype arrays were built by placing eight elements on a 26-cm-diameter cylindrical holder. These prototype arrays were used for S₁₁ and S₁₂ evaluation.</p><p><strong>Results: </strong>The optimal dimensions of the CMA were a length of 20 cm and a gap position of 4 cm. The fractionated dipole was optimal for a length of 25 cm. Evaluation of 100 000 random shims revealed that the CMA performs with lower SAR efficiency, although the SAR efficiencies are similar in CP mode. Measured S₁₁ and S₁₂ levels were both lower for the CMA.</p><p><strong>Conclusion: </strong>The coax monopole would be an excellent candidate for head coil arrays at 14T MRI. Although the CMA is expected to perform with lower SAR efficiency than the fractionated dipole, its single-ended design will facilitate elements placement and cable-routing, especially in a spatially restricted environment.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441371","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":"Machine learning-based multi-pool Voigt fitting of CEST, rNOE, and MTC in Z-spectra.","authors":"Sajad Mohammed Ali, Peter C M van Zijl, Jannik Prasuhn, Ronnie Wirestam, Linda Knutsson, Nirbhay N Yadav","doi":"10.1002/mrm.30460","DOIUrl":"https://doi.org/10.1002/mrm.30460","url":null,"abstract":"<p><strong>Purpose: </strong>Four-pool Voigt (FPV) machine learning (ML)-based fitting for Z-spectra was developed to reduce fitting times for clinical feasibility in terms of on-scanner analysis and to promote larger cohort studies. The approach was compared to four-pool Lorentzian (FPL)-ML-based modeling to empirically verify the advantage of Voigt models for Z-spectra.</p><p><strong>Methods: </strong>Voigt and Lorentzian models were fitted to human 3 T Z-spectral data using least squares (LS) to generate training data for the corresponding ML versions. Gradient boosting decision trees were trained, resulting in one Voigt and one Lorentzian ML model. Modeling accuracy was tested, and the fitting times of the ML models and LS versions were evaluated. The goodness of fits of Voigt and Lorentzian ML models were compared.</p><p><strong>Results: </strong>The training time for each ML model (Voigt and Lorentzian) was less than 1 min, and the modeling accuracy compared to the corresponding LS versions was excellent, as indicated by a nonsignificant difference between the parameters obtained by LS and corresponding ML versions. The average fitting time was 20 μs/spectrum for both ML models compared to 0.27 and 0.82 s/spectrum for LS with FPL and FPV, respectively. The goodness of fits of FPV-ML and FPL-ML differed significantly (p < 0.005), with FPV-ML showing an improvement for all tested data.</p><p><strong>Conclusion: </strong>Gradient boosting decision trees fitting of multi-pool Z-spectra significantly reduces fitting times compared to traditional LS approaches, allowing fast data processing while upholding fitting quality. Along with the short training times, this makes the method suitable for clinical settings and for large cohort research applications. The FPV-ML approach provides a significant improvement of goodness of fit compared to FPL-ML.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441392","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":"Whole liver phase-based R2 mapping in liver iron overload within a breath-hold.","authors":"Daiki Tamada, Ruvini Navaratna, Jayse Merle Weaver, Diego Hernando, Scott B Reeder","doi":"10.1002/mrm.30461","DOIUrl":"https://doi.org/10.1002/mrm.30461","url":null,"abstract":"<p><strong>Purpose: </strong>Diagnosis and treatment monitoring of iron overload increasingly relies on non-invasive MRI-based measurement of liver iron concentration (LIC). Liver R₂ mapping is known to correlate well with LIC. However, traditional spin-echo based R₂ mapping methods have drawbacks such as long acquisition times and limited volumetric coverage. In this work, we present an optimized phase-based R₂ mapping method to quantify whole-liver R₂ in iron overload patients within a single breathhold.</p><p><strong>Theory and methods: </strong>A recently developed phase-based R₂ mapping method is optimized in this study to improve estimation of high R₂ values using reduced TR, spatial averaging, and R₁ correction. Using Bloch equation simulations, the proposed optimization method was evaluated. Furthermore, the impact of fat on R₂ bias was investigated through simulations. The feasibility of the optimized phase-based R₂ method was assessed in healthy volunteers and patients with iron overload and compared to reference STEAM-MRS R₂ measurements.</p><p><strong>Results: </strong>Simulations demonstrate that a shorter TR extends the dynamic range of R₂ estimation to higher values and that averaging of signal phase before R₂ estimation is necessary when R₂ is high. Phantom experiments also demonstrate reduced phase-based R₂ bias using R₁ correction. Good agreement (1.5 T: r² = 0.76, 3.0 T: r² = 0.70) between the modified phase-based R₂ method and reference STEAM R₂ was found in healthy volunteers and iron overload patients over a wide range of LIC values.</p><p><strong>Conclusion: </strong>This study demonstrates the feasibility of the proposed phase-based R₂ method to accurately measure whole-liver R₂ mapping in severe iron overloaded patients during a single breathhold.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440471","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":"A data-driven approach for improved quantification of in vivo metabolic conversion rates of hyperpolarized [1-¹³C]pyruvate.","authors":"Yaewon Kim, Tanner M Nickles, Philip M Lee, Robert A Bok, Jeremy W Gordon, Peder E Z Larson, Daniel B Vigneron, Cornelius von Morze, Michael A Ohliger","doi":"10.1002/mrm.30445","DOIUrl":"https://doi.org/10.1002/mrm.30445","url":null,"abstract":"<p><strong>Purpose: </strong>Accurate quantification of metabolism in hyperpolarized (HP) ¹³C MRI is essential for clinical applications. However, kinetic model parameters are often confounded by uncertainties in radiofrequency flip angles and other model parameters.</p><p><strong>Methods: </strong>A data-driven kinetic fitting approach for HP ¹³C-pyruvate MRI was proposed that compensates for uncertainties in the B₁ ⁺ field. We hypothesized that introducing a scaling factor to the flip angle to minimize fit residuals would allow more accurate determination of the pyruvate-to-lactate conversion rate (k_PL). Numerical simulations were performed under different conditions (flip angle, k_PL, and T₁ relaxation), with further testing using HP ¹³C-pyruvate MRI of rat liver and kidneys.</p><p><strong>Results: </strong>Simulations showed that the proposed method reduced k_PL error from 60% to 1% when the prescribed and actual flip angles differed by 60%. The method also showed robustness to T₁ uncertainties, achieving median k_PL errors within ±3% even when the assumed T₁ was incorrect by up to a factor of 2. In rat studies, better-quality fitting for lactate signals (a 1.4-fold decrease in root mean square error [RMSE] for lactate fit) and tighter k_PL distributions (an average of 3.1-fold decrease in k_PL standard deviation) were achieved using the proposed method compared with when no correction was applied.</p><p><strong>Conclusion: </strong>The proposed data-driven kinetic fitting approach provided a method to accurately quantify HP ¹³C-pyruvate metabolism in the presence of B₁ ⁺ inhomogeneity. This model may also be used to correct for other error sources, such as T₁ relaxation and flow, and may prove to be clinically valuable in improving tumor staging or assessing treatment response.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441339","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":"Whole-brain BOLD responses to graded hypoxic challenges at 7 T, 9.4 T, and 15.2 T: Implications for ultrahigh-field functional MRI and BOLD-dynamic susceptibility contrast MRI.","authors":"Thuy Thi Le, Sang Han Choi, Geun Ho Im, Chanhee Lee, Dongkyu Lee, Jacob Schulman, HyungJoon Cho, Kamil Uludağ, Seong-Gi Kim","doi":"10.1002/mrm.30459","DOIUrl":"https://doi.org/10.1002/mrm.30459","url":null,"abstract":"<p><strong>Purpose: </strong>Blood oxygen-level dependent (BOLD) functional MRI signals depend on changes in deoxyhemoglobin content, which is associated with baseline cerebral blood volume (CBV) and blood oxygen saturation change. To accurately interpret activation-induced BOLD responses and quantify perfusion values by BOLD dynamic susceptibility contrast (BOLD-DSC) with transient hypoxia, it is critical to assess Δ <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {mathrm{R}}_2^{ast } $$</annotation></semantics> </math> values in tissue and blood across varying levels of hypoxia and magnetic field strengths (B₀).</p><p><strong>Methods: </strong>Whole-brain BOLD responses were examined using 5-s graded hypoxic challenges with 10%, 5%, and 0% O₂ at ultrahigh field strengths of 7 T, 9.4 T, and 15.2 T. Both tissue and blood responses were analyzed for BOLD-DSC quantification.</p><p><strong>Results: </strong>Substantial heterogeneity in hypoxia-induced Δ <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {mathrm{R}}_2^{ast } $$</annotation></semantics> </math> was observed among regions under different hypoxic doses and B₀. Nonlinear Δ <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {mathrm{R}}_2^{ast } $$</annotation></semantics> </math> responses with increasing field strength were observed, depending on hypoxic levels: 10% O₂ condition exhibited pronounced supralinear trends, whereas 0% and 5% O₂ conditions showed nearly linear dependencies. Blood arterial and venous <math> <semantics> <mrow> <msubsup><mrow><mo>∆</mo> <mi>R</mi></mrow> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ Delta {mathrm{R}}_2^{ast } $$</annotation></semantics> </math> responses showed a similar dependence as tissue. However, at 15.2 T, the venous signal saturated under 5% and 0% O₂ conditions. Quantitative CBV values obtained from BOLD-DSC data showed dependency on susceptibility effects, and higher B₀ and hypoxic severity resulted in slightly higher CBV, indicating that caution is needed when comparing quantitative CBV values derived from different experimental protocols. Normalizing regional CBV values to those of white matter effectively reduced the impact of varying susceptibility contrasts.</p><p><strong>Conclusions: </strong>Our investigations provide biophysical insights into the BOLD contrast mechanism at ultrahigh fields, and address quantification issues in susceptibility-based CBV measurements.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440874","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":"Interpretation of inhomogeneous magnetization transfer in myelin water using a four-pool model with dipolar reservoirs.","authors":"Michelle H Lam, Masha Novoselova, Andrew Yung, Valentin H Prevost, Alan P Manning, Jie Liu, Wolfram Tetzlaff, Piotr Kozlowski","doi":"10.1002/mrm.30465","DOIUrl":"https://doi.org/10.1002/mrm.30465","url":null,"abstract":"<p><strong>Purpose: </strong>To confirm ihMT's specificity to myelin, an ihMT presaturation module was combined with a Poon-Henkelman multi-echo spin-echo readout to separate the ihMT signal in myelin water from intra-/extra-cellular water. This study explored the relationship between two quantitative myelin imaging techniques and measured the ihMT signal of myelin water.</p><p><strong>Methods: </strong>Six rats were injured; three were sacrificed three weeks post-injury, and three were sacrificed eight weeks post-injury, and three healthy control rats were also sacrificed. The nine formalin-fixed rat spinal cords were imaged using a Poon-Henkelman multi-echo spin-echo readout with an ihMT prepulse at different strengths of <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1D} $$</annotation></semantics> </math> filtering at 7T.</p><p><strong>Results: </strong>The proposed model was able to characterize the ihMT decay signal in myelin water and intra-/extra-cellular water pool. From this proposed four-pool model with dipolar order reservoirs, we see a drop in the <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> <mo>(</mo> <mtext>myelin</mtext> <mo>)</mo></mrow> <annotation>$$ {T}_{1D}left(mathrm{myelin}right) $$</annotation></semantics> </math> fit parameter in the fasciculus gracilis white matter region of the three-week post-injury cord. <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> <mo>(</mo> <mtext>myelin</mtext> <mo>)</mo></mrow> <annotation>$$ {T}_{1D}left(mathrm{myelin}right) $$</annotation></semantics> </math> and <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> </mrow> <annotation>$$ {T}_{1D} $$</annotation></semantics> </math> (non-myelin) were estimated to be approx. 8 and 1.5 ms, respectively.</p><p><strong>Conclusion: </strong>The drop in <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> <mo>(</mo> <mtext>myelin</mtext> <mo>)</mo></mrow> <annotation>$$ {T}_{1D}left(mathrm{myelin}right) $$</annotation></semantics> </math> in the three-week post-injury cords suggests that <math> <semantics> <mrow> <msub><mrow><mi>T</mi></mrow> <mrow><mn>1</mn> <mi>D</mi></mrow> </msub> <mo>(</mo> <mtext>myelin</mtext> <mo>)</mo></mrow> <annotation>$$ {T}_{1D}left(mathrm{myelin}right) $$</annotation></semantics> </math> could potentially distinguish between functional myelin and myelin debris; however, more studies are needed to confirm this.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441391","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":"Amide mapping in the human brain using downfield MRSI at 3 T and 7 T.","authors":"İpek Özdemir, Semra Etyemez, Peter B Barker","doi":"10.1002/mrm.30458","DOIUrl":"https://doi.org/10.1002/mrm.30458","url":null,"abstract":"<p><strong>Purpose: </strong>To quantitatively compare signal-to-noise ratios (SNRs), linewidth values, and Cramér-Rao lower bounds (CRLBs) for amide resonances in the human brain measured at 3T and 7T using downfield MR spectroscopic imaging (DF-MRSI).</p><p><strong>Methods: </strong>Seven normal volunteers (25-52 years, 5 female) were imaged using Philips 3T Elition and 7T Achieva scanners. Both systems have 32-channel receive head coils and 16-channel local shim arrays (MRShim GmbH) in addition to high-order spherical harmonic shims. Three-dimensional DF-MRSI data were collected using a previously developed pulse sequence with spectral-spatial excitation and frequency-selective refocusing pulses. Matched imaging protocols on both field strengths were applied to achieve a nominal voxel size of 7 × 7 × 15 mm in a scan time of 10.6 min. Spectral analysis was performed using the \"LCModel\" software package. SNR and CRLB values (%) were compared between 3T and 7T data using univariate general linear models.</p><p><strong>Results: </strong>Significantly increased amide SNR and decreased CRLB values (p < 0.05) were found at 7T. Averaged over all brain regions, SNR was 2.9 ± 1.1 at 3T and 5.4 ± 1.5 at 7T, and CRLBs were 11.4 ± 3.9 and 4.9 ± 1.5 respectively. 7T MRI and amide images did show some regional signal dropoff due to transmit B₁ inhomogeneity, however.</p><p><strong>Conclusion: </strong>Three-dimensional DF-MRSI at 7T showed 86% increased SNR and 57% decreased CRLB values compared with 3T, confirming the expected improvements at higher field. Improvements are probably due to multiple factors, including higher magnetization at 7T, the shorter minimum echo time available, among others.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441342","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":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Focused ultrasound-induced blood-brain barrier opening: A comparative analysis of permeability quantification based on <ns0:math> <ns0:mrow> <ns0:msup><ns0:mrow><ns0:mi>K</ns0:mi></ns0:mrow> <ns0:mrow><ns0:mtext>trans</ns0:mtext></ns0:mrow> </ns0:msup> </ns0:mrow> </ns0:math> and PS.","authors":"Denisa Hývlová, Radovan Jiřík, Jiří Vitouš, Ondřej Macíček, Lucie Krátká, Eva Dražanová, Zenon Starčuk","doi":"10.1002/mrm.30446","DOIUrl":"https://doi.org/10.1002/mrm.30446","url":null,"abstract":"<p><strong>Purpose: </strong>Focused ultrasound-induced blood-brain barrier (BBB) opening is a promising method for neurotherapeutic delivery. The standard for quantifying induced BBB permeability is the <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> parameter, which reflects both permeability and plasma flow. The influence of plasma flow can be eliminated by estimating the PS parameter. However, this parameter has been largely unexplored in this application. This study aims to compare permeability estimates based on <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> and PS in focused ultrasound-induced BBB opening experiments.</p><p><strong>Methods: </strong>We used the extended Tofts model (ETM) and the two-compartment exchange model (2CXM) to estimate <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> and PS parameters, respectively. Permeability estimates were compared using simulated concentration curves, simulated DCE-MRI data, and real datasets. We explored the influence of spatially-regularized model fitting on the results.</p><p><strong>Results: </strong>For opened BBB, <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> was minimally influenced by plasma flow under the tested conditions. However, fitting the ETM often introduced outliers in <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> estimates in regions with closed BBB. The 2CXM outperformed the ETM at high signal-to-noise ratios, but its higher complexity led to lower precision at low signal-to-noise ratios. Both these issues were successfully compensated by spatially-regularized model fitting.</p><p><strong>Conclusion: </strong>Both <math> <semantics> <mrow> <msup><mrow><mi>K</mi></mrow> <mrow><mtext>trans</mtext></mrow> </msup> </mrow> <annotation>$$ {K}^{mathrm{trans}} $$</annotation></semantics> </math> and PS seem to be eligible options for the quantification of BBB opening, and the correct choice depends on the specifics of the acquired DCE-MRI data. Additionally, spatial regularization has demonstrated its importance in enhancing the accuracy and reproducibility of results for both models.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441320","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":"Basis function compression for field probe monitoring.","authors":"Paul I Dubovan, Gabriel Varela-Mattatall, Eric S Michael, Franciszek Hennel, Ravi S Menon, Klaas P Pruessmann, Adam B Kerr, Corey A Baron","doi":"10.1002/mrm.30471","DOIUrl":"https://doi.org/10.1002/mrm.30471","url":null,"abstract":"<p><strong>Purpose: </strong>Field monitoring using field probes allows for accurate measurement of magnetic field perturbations, such as from eddy currents, during MRI scanning. However, errors may result when the spatial variation of the fields is not well-described by the conventionally used spherical harmonics model that has the maximum order constrained by the number of probes. The objective of this work was to develop and validate a field monitoring approach that compresses higher order spherical harmonics into a smaller set of new basis functions that can be characterized using fewer probes.</p><p><strong>Methods: </strong>Field monitoring of acquisitions was repeated with probes in different locations. High-order field dynamics were computed from this \"calibration\" data assembled from provided scans, from which compression matrices could be devised using principal component analysis. Compression matrices were then used to fit field dynamics using \"compressed\" basis functions with data from 16 probes, which were then used in image reconstruction. Performance was evaluated by assessing the accuracy of computed field dynamics as well as in vivo image quality. Technique generalizability was also assessed by using various acquisition and diffusion encoding strategies in the calibration.</p><p><strong>Results: </strong>Qualitative and quantitative improvements in accuracy were observed when using the proposed fitting method compared to the conventional approach. However, compression effectiveness was influenced by the probe quantity and arrangement, and the specific acquisition data included in the calibration.</p><p><strong>Conclusion: </strong>The ability to tailor basis functions to more compactly describe the spatial variation of field perturbations enables improved characterization of fields with rapid spatial variations.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441374","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}