NMR in Biomedicine最新文献

{"title":"Domain-Conditioned and Temporal-Guided Diffusion Modeling for Accelerated Dynamic MRI Reconstruction.","authors":"Liping Zhang, Iris Yuwen Zhou, Sydney B Montesi, Li Feng, Fang Liu","doi":"10.1002/nbm.70256","DOIUrl":"10.1002/nbm.70256","url":null,"abstract":"<p><p>This study introduces a domain-conditioned and temporally guided diffusion framework for accelerated dynamic MRI reconstruction, in which the reverse diffusion process is explicitly guided to model spatiotemporal structure in time-resolved data. The framework integrates temporal information from time-resolved dimensions, allowing for the concurrent capture of intraframe spatial features and interframe temporal dynamics in diffusion modeling. Meanwhile, it employs additional spatiotemporal and self-consistent frequency-temporal priors to guide the diffusion process, ensuring precise temporal alignment and enhancing fine image detail recovery. To facilitate a smooth diffusion process, the nonlinear conjugate gradient algorithm is utilized during the reverse diffusion steps. The proposed model was tested on two types of MRI data: Cartesian-acquired multicoil cardiac MRI and golden-angle-radial-acquired multicoil free-breathing lung MRI, across various undersampling rates. It achieved high-quality reconstructions, demonstrating improved temporal alignment and structural recovery compared with other competitive reconstruction methods, both qualitatively and quantitatively. This diffusion framework exhibited robust performance in handling both Cartesian and non-Cartesian acquisitions, effectively reconstructing dynamic datasets in cardiac and lung MRI under different imaging conditions.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70256"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147504577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Role of Vascular Factors and Tissue Properties in Pulsatile Brain Deformation.","authors":"Marius Burman Ingeberg, Elijah Van Houten, Andrej Shoykhet, Jaco J M Zwanenburg","doi":"10.1002/nbm.70282","DOIUrl":"10.1002/nbm.70282","url":null,"abstract":"<p><p>Strain tensor imaging (STI) provides precise measurements of brain tissue deformation caused by cerebral arterial pulsations (CAPs). This CAP-related brain tissue deformation is expressed in rotation-invariant strain metrics, such as volumetric strain and octahedral shear strain, which hold promise as quantitative markers of the (mechanical) properties of both the intracerebral vasculature and the intervascular tissue components. However, the extent to which these strain metrics can be specifically linked to the underlying anatomical, vascular, and tissue properties remains largely unknown. This study aims to explore the relationship between STI metrics and independent markers of pulse pressure (arterial transit time, ATT), vascular function (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT), and tissue properties (shear stiffness). Volumetric and octahedral shear strain were computed from previously obtained 7T displacement data (approximately 2-mm isotropic resolution) of eight healthy subjects (27 ± 7 years). Shear stiffness maps were generated from the same displacement data set using poroviscoelastic intrinsic MR elastography. Regional values of CBV, CBF, MTT, and ATT were obtained from standard-space atlases. Linear mixed-effects models were used to investigate potential regional relationships between specific strain metrics and the corresponding tissue, pulse pressure, or vascular markers. Volumetric strain showed significant positive correlations with CBV (globally and in cortical gray and white matters) and significant negative correlations with ATT (globally and in cortical gray and white matters), but not with shear stiffness. Octahedral shear strain showed a significant negative correlation with shear stiffness (globally and in subcortical gray and white matters) and also with ATT (globally and in cortical gray matter). Volumetric strain reflects mainly vascular properties (pulse pressure and blood volume), whereas octahedral shear strain is more sensitive to tissue properties. These findings provide a foundation for future studies that investigate the physiological characteristics reflected by these strain metrics and their intricate interplay.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 5","pages":"e70282"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13036297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Sensitivity of Literature <ns0:math> <ns0:semantics> <ns0:mrow> <ns0:msub><ns0:mrow><ns0:mi>T</ns0:mi></ns0:mrow> <ns0:mrow><ns0:mn>1</ns0:mn></ns0:mrow> </ns0:msub> </ns0:mrow> <ns0:annotation>$$ {T}_1 $$</ns0:annotation></ns0:semantics> </ns0:math> Mapping Methods to the Underlying Magnetization Transfer Parameters.","authors":"Jakob Assländer","doi":"10.1002/nbm.70246","DOIUrl":"10.1002/nbm.70246","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Magnetization transfer (MT) has been identified as the principal source of &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; variability in the MRI literature. This study assesses the sensitivity of established &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; mapping techniques to variations in the underlying MT parameters. For each &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; -mapping method, the observed &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; was simulated as a function of the underlying MT parameters &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;p&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;MT&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {p}_i^{mathrm{MT}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; , corresponding to different brain regions of interest (ROIs) at 3T. As measures of sensitivity, the derivatives &lt;math&gt; &lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;∂&lt;/mi&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;observed&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;mo&gt;/&lt;/mo&gt; &lt;mi&gt;∂&lt;/mi&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;p&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;MT&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ partial {T}_1^{mathrm{observed}}/partial {p}_i^{mathrm{MT}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; were computed and analyzed with a linear mixed-effects model as a function of &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;p&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;MT&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {p}_i^{mathrm{MT}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; , ROI, pulse sequence type (e.g., inversion-recovery and variable-flip angle), and the individual sequences. The analyzed &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1 $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; -mapping sequences have a considerable sensitivity to changes in the semisolid spin pool size &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;m&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;s&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;mspace&gt;&lt;/mspace&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;f&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {m}_0^{mathrm{s}},kern0.3em {T}_1^{mathrm{f}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; of the free, &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msubsup&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;s&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msubsup&gt; &lt;/mrow&gt; &lt;annotation&gt;$$ {T}_1^{mathrm{s}} $$&lt;/annotation&gt;&lt;/semantics&gt; &lt;/math&gt; of the semisolid spin pool, and the (inverse) exchange rate &lt;math&gt; &lt;semantics&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt; &lt;mrow&gt;&lt;mtext&gt;x&lt;/mtext&gt;&lt;/","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70246"},"PeriodicalIF":2.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13037397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147372996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection Accuracy of Ischemia and Neuroinflammation in Traumatic Brain Injury in Rats Using Amide Proton Transfer-Weighted MRI.","authors":"Yunfan Zou, Yinfeng Dong, Jieru Wan, Jianhua Lu, Shanshan Jiang, Raymond C Koehler, Jinyuan Zhou","doi":"10.1002/nbm.70229","DOIUrl":"10.1002/nbm.70229","url":null,"abstract":"<p><p>Ischemia and neuroinflammation are two key secondary injury events following traumatic brain injuries (TBIs), but they are difficult to assess in vivo. Early detection of these secondary injuries post-TBI allows for precise severity assessment and enables timely, targeted interventions to reduce adverse outcomes. This study aimed to quantify the diagnostic accuracy of amide proton transfer-weighted (APTw) imaging to detect these two post-TBI endophenotypes. Controlled cortical impact (CCI) at depths of 1 mm (mild), 3 mm (moderate), and 5 mm (severe) was induced in 55 adult rats (28 males, 27 females), followed by 4.7 T MRI scanning (at 1 h, 1, 3, 7, 14, and 28 days). T₂, T₁, apparent diffusion coefficient, cerebral blood flow, APTw, and magnetization transfer ratio values in the perilesional cortex were analyzed. The area under the receiver operating curve (AUC) was calculated to assess the ability of these MRI signals to identify ischemia and neuroinflammation. At 1 h post-injury, perilesional cortical APTw signals decreased due to ischemia. APTw hypointensities used to identify ischemia had medium to large effect sizes of -0.620, -0.931, and -0.516 for mild, moderate, and severe TBI, respectively. At 3 days post-injury, perilesional cortical APTw signals increased due to neuroinflammation. APTw hyperintensities used to identify neuroinflammation had effect sizes of 0.247, 2.099, and 2.830 for mild, moderate, and severe TBI, respectively, superior to all other MRI parameters (APTw AUC = 0.950). APTw imaging shows promise for the detection of ischemia and neuroinflammation at an early stage post-CCI.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 2","pages":"e70229"},"PeriodicalIF":2.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13129811/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145985268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly Accelerated T_1ρ Imaging in 3 min: Comparison Between Compressed Sensing and Deep Learning Reconstruction.","authors":"Jeehun Kim, Hongyu Li, Ruiying Liu, Zhiyuan Zhang, Mingrui Yang, Carl S Winalski, Naveen Subhas, Leslie Ying, Xiaojuan Li","doi":"10.1002/nbm.70226","DOIUrl":"10.1002/nbm.70226","url":null,"abstract":"<p><p>The purpose of this study was to compare between compressed sensing (CS) and deep learning (DL) accelerated T_1ρ mapping in knee cartilage, a quantitative imaging technique that provides valuable information for disease diagnosis but requires long scan time. Both retrospectively and prospectively undersampled reconstruction were evaluated in nine volunteers including three with diagnosed pathology. For data collection, DESS images were collected for segmentation of six cartilage compartments. T_1ρ-weighted 3D MAPSS sequence was used to create T_1ρ maps. A 3T MRI scanner was used and GRAPPA 2 accelerated data were collected to provide 8-echo reference T_1ρ maps and was retrospectively undersampled for reconstruction with two sampling schemes: 4 TSLs with each echo image undersampled by 4 (UF4_4echo), and 8 TSLs with each echo image undersampled by 8 (UF8_8echo). Separate prospectively undersampled datasets were also collected for reconstruction. Volunteers were scanned and rescanned with repositioning for repeatability comparison. Reference, retrospectively undersampled reconstruction, and prospectively undersampled reconstruction were compared by voxel-wise median normalized absolute differences (MNADs), concordance correlation coefficient (CCC), and coefficient of variation (CV) using cartilage compartment-wise mean value. As a result, for retrospective undersampling, CS showed CCC 0.992, MNAD 10.0%, and CV 1.3% for UF4_4echo, and CCC 0.988, MNAD 9.9%, and CV 1.4% for UF8_8echo. DL showed CCC 0.971, MNAD 9.8%, and CV 1.7% for UF4_4echo, and CCC 0.968, MNAD 10.6%, and CV 1.7% for UF8_8echo. For prospective undersampling, CS showed CCC 0.853 and CV 3.3% for UF4_4echo, and CCC 0.754 and CV 3.9% for UF8_8echo. DL showed CCC 0.939 and CV 2.4% for UF4_4echo and CCC 0.845 and CV 2.8% for UF8_8echo. The maps had 2.57%, 3.80%, 2.79%, 2.29%, and 2.85% scan-rescan CV, respectively, for reference, CS UF4_4echo, CS UF8_8echo, DL UF4_4echo, and DL UF8_8echo reconstructions. As a conclusion, DL provided better results compared to CS in prospectively undersampled reconstruction.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 2","pages":"e70226"},"PeriodicalIF":2.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12831483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal MRI Characterization of T₁ and T₂ Relaxation Times in an Amyloid Mouse Model of Alzheimer's Disease at 11.7 T.","authors":"Soven Kumar, Xiuli Yang, Yuguo Li, Adnan Bibic, Zhiliang Wei","doi":"10.1002/nbm.70187","DOIUrl":"10.1002/nbm.70187","url":null,"abstract":"<p><p>Longitudinal (T₁) and transverse (T₂) relaxation times measured by MRI are promising markers for assessing biological processes and disease pathology. In this study, we characterized the T₁ and T₂ relaxation times in the Tg2576 mouse model of Alzheimer's disease (N = 10) across ten time points, ranging from 3 to 14 months of age, using an 11.7 T MRI scanner. Genotype-dependent changes over time were observed in the thalamus, hypothalamus, and piriform cortex, suggesting that the rates of change in relaxation times within these regions may serve as potential markers for distinguishing Tg2576 mice from their wildtype (WT) counterparts. In addition, significant genotype differences were detected in the isocortex and hippocampus. These observations likely reflect the interplay between changes in tissue water content and the accumulation of amyloid plaques. To provide a reference for future MRI studies, we also calculated the average relaxation times over time points for WT mice. The mean T₁ values were 2036.3 ± 26.8 ms (isocortex), 2046.5 ± 28.7 ms (hippocampus), 1861.7 ± 22.2 ms (thalamus), 1897.8 ± 57.0 ms (hypothalamus), and 2099.7 ± 30.5 ms (piriform cortex). Corresponding T₂ values were 38.3 ± 0.5 ms (isocortex), 39.0 ± 0.2 ms (hippocampus), 35.4 ± 0.3 ms (thalamus), 36.9 ± 0.4 ms (hypothalamus), and 40.3 ± 0.3 ms (piriform cortex).</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 1","pages":"e70187"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12634190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145564642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of Dynamic Deuterium Metabolic Imaging (DMI) for the Measurement of Cerebral Metabolic Rates of Glucose in Rat.","authors":"Claudius S Mathy, Monique A Thomas, Graeme F Mason, Robin A de Graaf, Henk M De Feyter","doi":"10.1002/nbm.70194","DOIUrl":"10.1002/nbm.70194","url":null,"abstract":"<p><p>Deuterium metabolic imaging (DMI) is an innovative technique in which ²H magnetic resonance spectroscopic imaging (MRSI) is utilized to determine the metabolic activity of administered ²H-labeled substrates. As such it can be viewed as the ²H counterpart to more traditional ¹³C labeling methods that can be considered the gold standard for metabolic mapping in vivo. To ensure reliable findings from dynamic ²H MRSI experiments about absolute metabolic flux rates after administration of a ²H-labeled substrate it is essential to take into account ²H-specific aspects, namely ²H label losses and kinetic isotopy effects (KIEs). Here, a modified version of a ¹³C-based metabolic model for glucose metabolism in rat brain was developed to address these ²H-related effects, tested for ²H MRSI data acquired during infusion of [6,6'-²H₂]-glucose, and validated by comparison with indirect ¹H-[¹³C] MRSI data acquired during infusion of [1-¹³C]-glucose. The flux rates for glucose consumption (CMR_gl = 0.57 ± 0.08 μmol/min/g) and the TCA cycle (V_tca = 1.24 ± 0.14 μmol/min/g) derived from the ²H MRSI data and using the updated metabolic model were in excellent agreement with the estimates based on ¹³C data (CMR_gl = 0.59 ± 0.14 μmol/min/g and V_tca = 1.24 ± 0.32 μmol/min/g). The successful validation of dynamic ²H MRSI for absolute flux rate determination forms the basis for future quantitative study of metabolic disorders in vivo.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 1","pages":"e70194"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12695439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145724870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiparametric Saturation Transfer MR Fingerprinting Using Rosette-Accelerated Readout.","authors":"Sultan Z Mahmud, Hye-Young Heo","doi":"10.1002/nbm.70210","DOIUrl":"10.1002/nbm.70210","url":null,"abstract":"<p><p>Quantitative MR-derived tissue parameters are typically measured one by one, which is time-consuming for clinical practice. MR fingerprinting (MRF) allows the efficient and simultaneous measurement of multiple tissue properties. The purpose of this study was to develop a novel, multiparametric MRF framework for the simultaneous measurement of quantitative bulk water, semisolid magnetization transfer (MT), myelin water fraction (MWF), and B₀ inhomogeneity (ΔB₀) and susceptibility-weighted imaging (SWI) and chemical exchange saturation transfer (CEST) imaging contrast. A motion-robust, rosette-accelerated MRF sequence was developed by integrating RF saturation and T₂-preparation modules. Optimized MRF acquisition parameters, including RF saturation strength, saturation duration, frequency offset, relaxation delay, T₂-prep TE, and readout TE, were varied during image acquisition. Quantitative tissue parameters were estimated from unique MRF signal evolutions in human brain scans of healthy volunteers at 3T and evaluated against the reference parameters calculated using conventional standalone sequences. Quantitative bulk water, MTC, myelin water parameters, SWI, ΔB₀, and semiqualitative CEST estimated from a single scan using the multiparametric rosette-MRF technique were in very good agreement with reference parameters. Overall, the semisolid macromolecular pool size ratio (relative to bulk water) and MWF were higher in the white matter (WM) compared to the gray matter (GM). Susceptibility-dependent tissue contrast was visible in the SWI. An accurate ΔB₀ map was derived from the rosette images themselves. Furthermore, multimolecular (MTC, APT, rNOE, and CEST at 3 ppm) images were synthesized by solving forward Bloch equations with the tissue parameter estimated from the MRF reconstruction. In conclusion, a rosette-accelerated, multiparametric MRF technique, combined with synthetic MRI analysis, has the potential to offer valuable insights into disease pathology and serve as an efficient tool for the evaluation of various MRI biomarkers in clinical settings within a short time frame.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 1","pages":"e70210"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12718447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145715266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gradient Scheme Optimization for PRESS-Localized Edited MRS Using Weighted Pathway Suppression.","authors":"Gizeaddis L Simegn, Zahra Shams, Saipavitra Murali-Manohar, Dunja Simicic, Abdelrahman Gad, Yulu Song, Vivek Yedavalli, Christopher W Davies-Jenkins, Aaron T Gudmundson, Helge J Zöllner, Georg Oeltzschner, Richard A E Edden","doi":"10.1002/nbm.70182","DOIUrl":"10.1002/nbm.70182","url":null,"abstract":"<p><p>This study aimed to design and implement an optimized gradient scheme for PRESS-localized edited magnetic resonance spectroscopy (MRS) to enhance suppression of out-of-voxel (OOV) artifacts. These artifacts, which originate from insufficient crushing of unwanted coherence transfer pathways (CTPs), are particularly challenging in editing schemes for metabolites like gamma-aminobutyric acid and glutathione. To address this, a volume-based likelihood model was developed to guide gradient scheme optimization, prioritizing suppression of CTPs based on likelihood. The volume-based likelihood model for CTP weighting was integrated into a Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient optimization. Using a genetic algorithm with a weighted dual-penalty cost function, gradient schemes were optimized to maximize pathway-specific suppression. Hardware and sequence constraints, maximum gradient amplitudes and delay durations respectively, informed the optimization. Validation of the optimized scheme was performed with simulations by calculating the k-space crushing efficiency analytically with k-space trajectory and in vivo using an edited MRS sequence in three brain regions (posterior cingulate cortex PCC, thalamus, and medial prefrontal cortex [mPFC]), with particular focus on OOV artifact reduction and spectral quality improvements. A three-way Analysis of Variance was used to assess the significance level of OOV artifact reduction. The optimized gradient scheme demonstrated improved k-space crushing efficiency (by an average of 197%). OOV artifacts were reduced in all brain regions, particularly in highly OOV-susceptible regions (thalamus and mPFC). Improvements were most notable around 4.3 ppm with significant OOV artifact amplitude reductions (p < 0.001). By using a volume-based likelihood model for CTP prioritization, the optimized DOTCOPS scheme ensures robust and region-agnostic performance in reducing OOV artifacts.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 1","pages":"e70182"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12631011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145557520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Parameter Magnetic Resonance Spectroscopy in Cervix.","authors":"Gavin Hamilton, Nicole A Gamboa, Alex N Schlein, Sheida Ebrahimi, Summer J Batasin, Hon Yu, Stephan Jordan, Breanna Hill, Catherine Moran, Ana E Rodriguez Soto, Rebecca Rakow-Penner","doi":"10.1002/nbm.70211","DOIUrl":"10.1002/nbm.70211","url":null,"abstract":"<p><p>The aim of this study is to examine cervix-adapted versions of steady-state multi-parameter MRS (SMP MRS) and flip-angle-corrected multi-parameter MRS (CMP MRS), comparing estimated cervix T1_w and T2_w for the two sequences. CMP MRS and SMP MRS were adapted from liver versions of the sequences, adding long TR acquisitions to better estimate cervix T1_w. CMP MRS differs from SMP MRS by correcting for inaccurate B1 calibration. Both CMP MRS and SMP MRS were acquired at 3 T in 13 adult female subjects (10 healthy, 3 with cancer). Values of T1_w and T2_w were estimated from both sequences, and the relationship between the values was examined. While there was no significant difference in T1_w given by the two sequences (CMP T1_w = 1568 ms, SMP T1_w = 1571 ms, p = 0.95; SMP T1_w = 0.657 CMP T1_w + 541 ms, r = 0.36), there was a single case where SMP MRS underestimated T1_w by over 400 ms. A significant difference was observed in T2_w (CMP T2_w = 39.9 ms, SMP T2_w = 45.6 ms, p = 0.001; SMP T2_w = 0.812 CMP T2_w + 13.3 ms, r = 0.87). Cervix adapted CMP MRS and SMP MRS both successfully estimated values of T1_w and T2_w, though the single case where SMP MRS gave a non-physical T1_w suggests CMP MRS may be better suited for cervix T1_w estimation.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 1","pages":"e70211"},"PeriodicalIF":2.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145743552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}