NMR in Biomedicine最新文献

{"title":"Detection of Muscle Fiber Orientation During Human Tongue Development: Analysis Using Diffusion Tensor Imaging.","authors":"Saho Suto, Toru Kanahashi, Sena Fujii, Hirohiko Imai, Hiroki Otani, Shigehito Yamada, Tetsuya Takakuwa","doi":"10.1002/nbm.70257","DOIUrl":"10.1002/nbm.70257","url":null,"abstract":"<p><p>The tongue consists of intrinsic and extrinsic muscles that enable complex movements. Previous studies, based on gross and histological observations, were limited in their ability to fully distinguish between them, which may have resulted in inaccurate differentiation timelines for intrinsic and extrinsic muscles. This study analyzed tongue muscle fiber orientation during embryonic development using diffusion tensor imaging (DTI). Human embryonic and fetal specimens (n = 29) were used in this study. A 7-Tesla magnetic resonance imaging (MRI) system was used to acquire T1-weighted images and DTI data. Fiber tractography was used to track muscle orientation. Tongue muscles that differentiate into myotubules were first recognized at Carnegie stage (CS) 19, with many muscles becoming identifiable by CS23. Most extrinsic and intrinsic muscles could be clearly distinguished based on differences in their fractional anisotropy values and fiber orientations. Precise discrimination and quantification were only successful for a limited number of muscles. Serial histological sections identified the vertical, transverse, hyoglossus, and genioglossus muscles at CS19. This study indicates that intrinsic and extrinsic muscles differentiate along a similar timeline during the first differentiation of myotubules at CS19. Moreover, this study highlights the capabilities and limitations of DTI for evaluating the embryonic development of tongue muscles. Additionally, DTI can detect immature muscle tissues, suggesting potential applications for other regions at similar stages of embryonic development.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70257"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147365830","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":"Analyzing Nicotine Action Against Amyloid Toxicity by NMR-Pharmacometabolomics: An Exploratory Study.","authors":"Enza Napolitano, Carmen Marino, Manuela Grimaldi, Michela Buonocore, Angelo Santoro, Anna Maria D'Ursi","doi":"10.1002/nbm.70255","DOIUrl":"10.1002/nbm.70255","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is the primary neurodegenerative disease spread worldwide. One of the main histopathological hallmarks of AD is the deposition of amyloid plaques in the brain. Despite some epidemiological studies demonstrating that cigarette smoke is a factor in predisposing people to AD, nicotine, the principal alkaloid of Nicotiana Tobacco, has been widely studied for its ability to improve cognitive performance, both in animal models and in human studies. Several hypotheses have been proposed to explain the mechanism of action underlying the beneficial effect of nicotine in AD; however, this is still questioned. To gain new insights into the molecular mechanism underlying nicotine's neuroprotective action in AD, we performed NMR metabolomics on SH-SY5Y neuroblastoma cells treated with Aβ(1-42) in the presence of nicotine. Our data show that the neuroprotective action of nicotine resides in its ability to restore the systemic unbalanced metabolism associated with AD. In particular, nicotine reverses most Aβ(1-42)-induced metabolic impairments, including those related to amino acid metabolism, especially neurotransmission, as well as alterations in energy and membrane phospholipid metabolism.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70255"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12965194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147365794","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":2.8,"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":"Optimized Quantitative Susceptibility Mapping at 7T MRI for Assessing Iron Deposition in Alzheimer's Disease.","authors":"Felisha Ma, Pinar Senay Özbay, Berkin Bilgic, Trey Hedden, Bradley Delman, Priti Balchandani, Akbar Alipour","doi":"10.1002/nbm.70268","DOIUrl":"10.1002/nbm.70268","url":null,"abstract":"<p><p>Elevated brain iron levels are common in Alzheimer's disease (AD). Quantitative susceptibility mapping (QSM) is an advanced MRI technique for assessing iron accumulation. The optimized QSM at 7 Tesla (7T) MRI may further improve the sensitivity to detect subtle susceptibility changes in AD. We optimized a QSM processing pipeline for 7T MRI by systematically comparing multiple reconstruction algorithms. Evaluation criteria included image quality, artifact suppression, and anatomical clarity. The finalized pipeline was applied to individuals with AD and healthy controls (HCs). The results revealed significantly elevated magnetic susceptibility values in the globus pallidus and dentate nucleus of the AD group compared to HCs. These findings were confirmed through both visual inspection and quantitative analysis of high-resolution QSM maps. This study provides a systematic evaluation and optimization of QSM processing pipelines at 7T MRI, offering improved sensitivity and reliability for detecting ad-related susceptibility alterations. Our results highlight the importance of optimizing QSM pipelines at 7T for accurate susceptibility quantification. AD patients exhibited higher susceptibility than controls in the globus pallidus (98.7-102.9 ppb) and dentate nucleus (51.1-52.8 ppb), consistent across all QSM pipelines. We identified an optimal pipeline suitable for future applications in patients with AD and other neurological conditions.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70268"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13392853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147481250","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":"Effect of the Temporal Sampling Strategy for the Assessment of Cerebral Perfusion in Multidelay Arterial Spin Labeling.","authors":"Ryoji Mikayama, Osamu Togao, Makoto Obara, Tatsuhiro Wada, Chiaki Tokunaga, Koji Yamashita, Kazufumi Kikuchi, Toyoyuki Kato, Kousei Ishigami, Hidetake Yabuuchi","doi":"10.1002/nbm.70271","DOIUrl":"10.1002/nbm.70271","url":null,"abstract":"<p><p>Multidelay arterial spin labeling (ASL) MRI requires balancing temporal resolution with scan duration. The goal of the current study is to evaluate the influence of the temporal sampling strategy, implemented through temporal downsampling, on the quantitative accuracy of cerebral perfusion parameters obtained using multidelay ASL. In this prospective single-center study, 12 healthy volunteers (mean age, 37 ± 9 years; seven men and five women) underwent multidelay pseudo-continuous ASL on a 3-T MRI system. Data were acquired using a variable time repetition scheme with 61 time points at a 75-ms sampling interval. Cerebral blood flow (CBF) and arterial transit time (ATT) maps were calculated using seven temporally downsampled datasets with sampling intervals of 75 (gold standard), 150, 300, 450, 600, 750, and 900 ms. The normalized root mean square error (RMSE) between each sampling interval and the gold standard (75 ms) was calculated for both CBF and ATT. Additionally, subgroup analyses were performed for regions with ATT shorter or longer than the median, as determined from the 75-ms interval dataset. The normalized RMSE of the CBF and ATT increased with more aggressive temporal downsampling. Across all sampling schemes, the normalized RMSE of CBF was significantly lower in regions with shorter ATT than in those with longer ATT (p < 0.05). Temporal sampling configuration influences the quantitative reliability of CBF and ATT estimation. CBF bias is particularly pronounced in regions with prolonged ATT.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70271"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147474538","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":"A Unified Deep Learning Framework for Liver MR Elastography Postprocessing: Proof-of-Concept Study.","authors":"Vitaliy Atamaniuk, Andrii Pozaruk, Michał Madera, Mikołaj Wcisło, Bogdan Obrzut, Marian Cholewa, Jacek Kluska, Marzanna Obrzut","doi":"10.1002/nbm.70258","DOIUrl":"10.1002/nbm.70258","url":null,"abstract":"<p><p>Magnetic resonance elastography (MRE) enables non-invasive quantification of liver stiffness and plays a pivotal role in the assessment of hepatic fibrosis. However, clinical implementation remains limited by the need for manual delineation of regions of interest (ROIs), which is time-consuming, requires expert input, and is prone to interobserver variability. This study assesses the feasibility of a single deep learning (DL) pipeline to fully automate this process-from acquired MRE data to liver-stiffness quantification-within a controlled proof-of-concept setting. To investigate this, we developed and validated a convolutional neural network-based framework capable of reconstructing stiffness maps and generating liver segmentation masks directly from magnitude and phase images. The models were trained using MRE data from 83 adult volunteers (56 women, 27 men; median age 21 years), primarily representing healthy individuals or those with early-stage disease. This homogeneous cohort was deliberately selected to facilitate proof-of-concept development and reduce confounding sources of biological variability during model optimization. Across several neural network architectures (U-Net, ResNet, and CycleGAN hybrids), the pipeline produced liver-stiffness estimates with less than 11% deviation from the reference values in all cases, and less than 3% in the best performing configurations. Agreement between automated and manual measurements was comparable to interreader agreement, with intraclass correlation coefficients-ICC(A,1), calculated using a two-way random effects model for absolute agreement-of 0.86 (95% CI: 0.71-0.95) and 0.89 (95% CI: 0.74-0.97), respectively. Total inference time per examination was 23.7 ± 4.4 s. These findings demonstrate the technical feasibility of a fully automated, AI-driven postprocessing pipeline for liver MRE within a controlled proof-of-concept setting using data from healthy volunteers. Although the approach shows promise for reducing analysis time and operator dependence, further validation in diverse clinical populations is required before broader generalization. This work represents an initial step toward more accessible, scalable, and standardized liver-stiffness assessment in research and, potentially, future clinical applications.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70258"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147378135","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":"Structural Fiber Tract Alterations in Relation to Surgery in Children With a Posterior Fossa Tumor.","authors":"Pien E J Jellema, Jannie P Wijnen, Karina J Kersbergen, Martijn Froeling, Maarten H Lequin, Wouter P Nieuwenhuis, Alberto De Luca, Eelco W Hoving","doi":"10.1002/nbm.70250","DOIUrl":"10.1002/nbm.70250","url":null,"abstract":"<p><p>Cerebellar mutism syndrome (CMS) is a potential complication of pediatric posterior fossa tumor (pPFT) resection and may be related to disruption of the dentato-rubro-thalamic tract (DRTT). Intraoperative tractography allows assessment of changes to the DRTT during surgery. We evaluated macro- and microstructural changes of the DRTT by comparing pre- and intraoperative diffusion MRI (dMRI) tractography in patients with pPFT. Pre- and intraoperative T1-weighted and dMRI data were acquired to reconstruct the DRTT, while the arcuate fasciculus (AF) was reconstructed as a control tract. To evaluate macrostructural intraoperative alterations, tract volume and diameter were calculated. Microstructural changes were assessed using fractional anisotropy (FA) and mean diffusivity (MD), both globally and along the tract. Speech disturbances, as a characteristic symptom of CMS, were scored preoperatively and at hospital discharge, based on retrospective neurological reports. In 30 patients (aged > 21 months) with sufficient data quality, intraoperative reductions in tract volumes and diameters were observed (p < 0.05) in the decussating DRTT (d-DRTT) (-45.4% to -10%) and AF (-9.9% to -5.1%), while the non-decussating DRTT (nd-DRTT) remained stable. Right d-DRTT volume loss correlated with ventricular enlargement (r = -0.476, p = 0.022). Whole-tract analyses revealed increased FA in the AF and increased MD in the nd-DRTT and AF. Along-tract analyses demonstrated high variance of the MD in the DRTT cerebellar segments. Patients with postoperative speech disturbances showed higher variance of FA and MD along the DRTT, particularly in the left cerebellar segment. pPFT surgery affected the variation of the DRTT microstructure near the resection cavity, whereas the AF remained relatively stable. Although we did not find significant differences in patients with postoperative speech disturbances, we observed a much higher variability in MD in this group, suggesting a potential effect of DRTT disruption in these symptoms.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70250"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12923661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146258618","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 3D-DCE MRI Assessment of Placental Perfusion Under Reduced Uterine Perfusion Pressure in Pregnant Rats.","authors":"Fatimah M Al Darwish, Caren M van Kammen, Fieke Terstappen, Lindy K Alles, Raymond M Schiffelers, A Titia Lely, Gustav J Strijkers, Bram F Coolen","doi":"10.1002/nbm.70251","DOIUrl":"10.1002/nbm.70251","url":null,"abstract":"<p><p>Placental insufficiency is a major cause of preeclampsia and fetal growth restriction. The reduced uterine perfusion pressure (RUPP) rat model reproduces cardinal features of these disorders, but longitudinal changes in placental perfusion after RUPP are poorly documented. This study aimed to assess the acute and late effects of RUPP on placental perfusion between gestational day (GD) 14 and GD18 using 3D dynamic contrast-enhanced magnetic resonance imaging (3D-DCE MRI). Pregnant Sprague Dawley rats (n = 31) were randomized to RUPP or normal pregnant (NP) groups on GD14. 3D-DCE MRI scans were performed on GD14, GD15, and GD16 or GD18. Perfusion parameters, including time to peak (TTP), maximum enhancement (ME), wash-out percentage (WO%), initial area under the curve (iAUC), and total area under the curve (AUC), were derived from fitted signal-time curves. In addition, exploratory voxel-wise histogram analysis was performed to assess intralitter variability. At GD14, RUPP placentas showed delayed TTP (p < 0.0001), reduced ME (p = 0.03), reduced WO% (p < 0.0001), and elevated iAUC (p = 0.02). Differences persisted for TTP (p = 0.02) and WO% (p = 0.01) at GD15 but resolved by GD16-GD18. Voxel-wise analysis revealed intralitter heterogeneity, with 20% of analyzed RUPP placentas deviating from the NP template. These findings indicate that RUPP induces an acute but transient impairment of placental perfusion, with recovery by late gestation. GD14-GD15 emerge as a critical window for detecting acute perfusion impairment and evaluating interventions targeting acute injury.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70251"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12926275/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147271561","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":"Enhanced Glioma Genotype Prediction Using CEST MRI With Full Z-Spectrum Input, Pixel-Level Learning, and Majority Voting.","authors":"Zhekai Chen, Jue Lu, Xinli Zhang, Jing Wang, Lin Chen","doi":"10.1002/nbm.70269","DOIUrl":"10.1002/nbm.70269","url":null,"abstract":"<p><p>Accurate glioma genotype prediction, such as the isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, is critical for personalized treatment planning and prognosis. Chemical exchange saturation transfer (CEST) MRI enables noninvasive assessment of tumor metabolism and the microenvironment, offering promising potential for genotype prediction. However, existing CEST-based diagnostic methods are limited by information loss from simplified quantification and by instability arising from ROI-dependent analysis. To address these limitations, a deep learning framework was developed that integrates the full Z-spectrum input, pixel-level training, and a majority voting mechanism to improve prediction accuracy and robustness. In a cohort of 84 patients, a feedforward neural network (FNN) was trained to process the entire Z-spectrum and generate pixel-wise predictions, which were subsequently aggregated into patient-level outcomes through majority voting. T-distributed stochastic neighbor embedding (t-SNE) was applied to evaluate the effectiveness of the full Z-spectrum input. Model generalizability and robustness were assessed using fivefold cross-validation, and stability was quantified via the coefficient of variation (CoV). Prediction performance was evaluated in terms of accuracy, sensitivity, specificity, and the area under the curve (AUC). The proposed method demonstrated improved interclass separability with the full Z-spectrum input (t-SNE score: 64.50), outperforming APTw (55.60) and Lorentzian fitting (56.97). Stable prediction performance was achieved for both IDH (accuracy: 0.86 ± 0.04 and AUC: 0.91 ± 0.03) and MGMT (accuracy: 0.82 ± 0.02 and AUC: 0.91 ± 0.04) genotypes. The approach also showed strong robustness to ROI selection, with a CoV of 0.69%, compared to 7.44% for APTw-mean and 3.67% for Lorentzian fitting (LF-mean). These findings support the effectiveness of combining the full Z-spectrum input, pixel-level learning, and majority voting to improve the reliability of noninvasive glioma genotype prediction using CEST MRI.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70269"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147474461","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":"Dynamics of Glutamate and Glutamine Assessed Using MRS in Response to a Short Heat Pain Stimulation.","authors":"Alexey Yakovlev, Elena Voronkova, Maxim Ublinskiy, Ilia Mel'nikov, Olga Bozhko, Sergey Varfolomeev, Tolibdzhon Akhadov","doi":"10.1002/nbm.70273","DOIUrl":"10.1002/nbm.70273","url":null,"abstract":"<p><p>It is assumed that the mechanism of changes in neurotransmitter levels measured by MRS in the short period of response to stimulation differs from the long one. According to compartmental shift hypothesis, the rapid increase in the MRS-measured level of neurotransmitters after event-related stimulus is due to their release from vesicles, and the subsequent decrease is due to their refilling. To test this hypothesis, we studied the concentration of the sum of glutamate and glutamine (Glx) in response to a short painful thermal stimulus. fMRI data and PRESS magnetic resonance spectra [echo time/repetition time = 35 ms/2000 ms] of an activated area in the left insular cortex of 26 subjects were acquired using a 3-T MR scanner. Stimulation was performed by presenting painful heat stimulus for 3 s, repeated with an interval of 7-9 s. The time course of Glx, N-acetylaspartate (NAA), and creatine (Cr) concentrations and the width and height of resonance lines were obtained with a nominal time resolution of 2 s. Changes in the linewidth and height of N-acetylaspartate and Cr signals were used to determine the BOLD effect. Seven subjects were excluded from analyses due to bad spectral quality or high Glx change in the dynamics. Because of nonreliable stimulation, analysis of response to stimulation was conducted in the two groups (less and more activated). In response to the activation, the Glx as the Glx/Cr ratio maximal increases were 4.2% ± 1.4% and 5.2% ± 1.4% (p < 0.05), respectively in 2 s after the establishing the stimulus temperature. Time courses of Cr and NAA signal width and height showed statistically significant decrease of Cr at 4 s after stimulus onset (-2.6% ± 0.8%, p = 0.03). The sensitivity of MRS to the BOLD effect was lower than that of the fMRI method. In the short response period, a short-term increase in the Glx level is observed. This result is in line with the compartmental shift hypothesis for short-term neurotransmitter dynamics, but further work is necessary to directly confirm this interpretation. Reliable detection of rapid increases in neurotransmitter levels following a short stimulus requires robust neural activation and minimal motion-related artifacts.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":"39 4","pages":"e70273"},"PeriodicalIF":2.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147463617","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}