Magnetic resonance imaging最新文献

{"title":"Diagnostic accuracy of segmental strain analysis by cardiac magnetic resonance feature tracking for chronic myocardial ischemic scar assessment","authors":"Mohammed Mousa ,&nbsp;Islam Mahmoud ,&nbsp;Tarek Elkammash ,&nbsp;Azza Gad ,&nbsp;Radwa Noureldin","doi":"10.1016/j.mri.2025.110408","DOIUrl":"10.1016/j.mri.2025.110408","url":null,"abstract":"<div><h3>Rationale and objective</h3><div>This study investigates the potential of segmental strain parameters derived from cine magnetic resonance imaging (MRI) using feature tracking (FT) to detect chronic ischemic scars in patients with ischemic heart disease, offering an alternative to late gadolinium enhancement (LGE) MRI, which has limitations such as long scan times and contraindications to gadolinium.</div></div><div><h3>Patients and methods</h3><div>A total of 47 patients with chronic coronary syndrome and 20 healthy controls were enrolled, with CMR examinations performed on a 1.5 Tesla MRI system. Strain parameters were analyzed from 1072 myocardial segments. Myocardial segments were categorized into four groups: healthy controls, remote myocardium (no late gadolinium enhancement), scarred-viable (&lt;50 % scar transmurality), and nonviable (&gt;50 % scar transmurality).</div></div><div><h3>Results</h3><div>Results showed significant differences in segmental peak circumferential strain (SPCS), peak radial strain (SPRS), and peak longitudinal strain (SPLS) between scarred viable and nonviable segments compared to remote and control segments, with all <em>p</em>-values &lt;0.001. Specifically, SPCS had a superior ability to distinguish scarred myocardium from remote tissue, showing an area under the curve (AUC) of 0.77, with a sensitivity of 71.5 % and specificity of 70 %. For differentiating nonviable from viable myocardium, SPCS achieved an AUC of 0.80, with a sensitivity of 82.02 % and specificity of 70.21 %.</div></div><div><h3>Conclusion</h3><div>CMR-FT strain analysis is promising complementary tool, particularly in situations where contrast administration is contraindicated or when a rapid, non-contrast assessment of myocardial viability and potential scar burden is desired.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110408"},"PeriodicalIF":2.1,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931961","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":"Accelerated ultrashort echo time quantitative magnetization transfer (UTE-qMT) imaging of macromolecular fraction (MMF) in cortical bone based on a self-attention convolutional neural network","authors":"Kevin Du ,&nbsp;Harry Tang ,&nbsp;Jiyo Athertya ,&nbsp;Yidan Wang ,&nbsp;Megan Hu ,&nbsp;Avery Wang ,&nbsp;Saeed Jerban ,&nbsp;Soo Hyun Shin ,&nbsp;Yajun Ma ,&nbsp;Christine B. Chung ,&nbsp;Eric Y. Chang","doi":"10.1016/j.mri.2025.110405","DOIUrl":"10.1016/j.mri.2025.110405","url":null,"abstract":"<div><h3>Purpose</h3><div>To combine ultrashort echo time quantitative magnetization transfer (UTE-qMT) imaging with a self-attention convolutional <em>neural network</em> (<em>SAT-Net</em>) for accelerated mapping of macromolecular fraction (MMF) in cortical bone.</div></div><div><h3>Materials and methods</h3><div>This institutional review board-approved study involved 31 young female subjects (young control, &lt;45 years) and 50 postmenopausal subjects (6 normal (old control), 14 with osteopenia (osteopenia group), and 30 with osteoporosis (OP group)). After written informed consent was obtained from each subject, 15 UTE-qMT images of the tibial midshaft were acquired with three saturation powers (500°, 1000°, and 1500°) and five frequency offsets (2, 5, 10, 20, and 50 kHz) for each power to estimate the baseline MMF using a two-pool model. The densely connected <em>SAT-Net</em> model was used to predict bone MMF maps based on seven evenly distributed UTE-qMT images, which were well separated in terms of MT powers and frequency offsets (namely 5 and 20 kHz for 500° and 1500°, and 2, 10, 50 kHz for 1000°). Errors relative to the baseline MMF were calculated. Linear regression was used to assess the performance of the SAT-Net model. The mean MMF values for different groups were calculated.</div></div><div><h3>Results</h3><div>Conventional two-pool modeling of seven evenly distributed UTE-qMT input images shows a significant relative error of ∼34 %. In comparison, the SAT-Net model accurately predicted MMF values for the tibial midshafts of 81 human subjects with a high correlation (R² = 0.97, <em>P</em> &lt; 0.0001) between the baseline and predicted values. The SAT-Net model accelerated UTE-qMT data acquisition by 2.1-fold, with relative errors in MMF mapping less than 2.4 %. The average MMF values were 46.10 ± 13.25 % for the young control group, 40.03 ± 2.56 % for the old control group, 31.22 ± 13.18 % for the osteopenia group, and 22.53 ± 8.12 % for the OP group.</div></div><div><h3>Conclusion</h3><div>While it is difficult to accelerate MMF mapping in bone using conventional two-pool modeling, the SAT-Net model allows accurate MMF mapping with a substantial reduction in the number of UTE-qMT input images. UTE-qMT with SAT-Net makes clinical evaluation of bone matrix possible.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110405"},"PeriodicalIF":2.1,"publicationDate":"2025-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918307","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":"Neuroimaging biomarkers of neuroprotection: Impact of voluntary versus enforced exercise in Alzheimer's disease models","authors":"Alexandra Badea ,&nbsp;Ali Mahzarnia ,&nbsp;Divya Reddy ,&nbsp;Zijian Dong ,&nbsp;Robert J. Anderson ,&nbsp;Hae Sol Moon ,&nbsp;Jacques A. Stout ,&nbsp;Janai Williams ,&nbsp;Lydiane Hirschler ,&nbsp;Emmanuel L. Barbier ,&nbsp;Christina L. Williams","doi":"10.1016/j.mri.2025.110406","DOIUrl":"10.1016/j.mri.2025.110406","url":null,"abstract":"<div><div>Exercise is a promising strategy for preventing or delaying Alzheimer's disease (AD), yet its mechanisms remain unclear. We investigated how exercise influences brain structure, function, and behavior in a familial AD model. Mice underwent voluntary, voluntary plus enforced exercise, or remained sedentary. Neuroimaging included in vivo manganese-enhanced MRI (MEMRI). perfusion, and ex vivo diffusion MRI to assess morphometry, activity, cerebral blood flow (CBF), microstructural integrity and connectivity.</div><div>Both exercise regimens induced structural and functional brain adaptations while reducing anhedonia. Voluntary exercise increased cortical and limbic volumes, particularly in the hippocampus, cingulate, and entorhinal cortex, supporting cognitive and emotional regulation. Adding enforced exercise influenced subcortical and sensory regions, including visual, motor and associative areas, supporting sensory-motor integration. MEMRI revealed increased activity in sensorimotor, limbic, and associative cortices, with voluntary exercise enhancing limbic and associative regions, and enforced exercise strengthening sensorimotor and subcortical circuits.</div><div>White matter integrity improved in memory-associate pathways such as the corpus callosum, cingulum, and hippocampal commissure. Synaptic remodeling was observed in the cingulate cortex, anterior thalamic nuclei, and amygdala. Voluntary exercise enhanced CBF in the motor cortex and hippocampus, while enforced exercise limited these increases.</div><div>Connectivity analyses revealed exercise-responsive networks spanning the cingulate cortex, entorhinal cortex, anterior thalamic nuclei, and basolateral amygdala, and associated tracts. Graph analyses linked running distance with increased thalamic, brainstem, and cerebellar connectivity, associating exercise intensity with plasticity.</div><div>These findings highlight the ability of chronic exercise to modulate neuroimaging biomarkers through distinct but complementary pathways, reinforcing its potential as a neuroprotective intervention for AD.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110406"},"PeriodicalIF":2.1,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927846","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":"Self-supervised learning for MRI reconstruction through mapping resampled k-space data to resampled k-space data","authors":"Jinhong Huang ,&nbsp;Xinzhen Li ,&nbsp;Genjiao Zhou ,&nbsp;Wenyu Hu","doi":"10.1016/j.mri.2025.110404","DOIUrl":"10.1016/j.mri.2025.110404","url":null,"abstract":"<div><div>In recent years, significant advancements have been achieved in applying deep learning (DL) to magnetic resonance imaging (MRI) reconstruction, which traditionally relies on fully sampled data. However, real-world clinical scenarios often demonstrate that the fully sampled data can be challenging or impossible to obtain due to physiological constraints, such as organ motion, and physical constraints, such as signal decay. In this paper, we introduce a self-supervised DL approach, termed randomly self-supervised learning via data undersampling (abbreviated as RSSDU), which is proficient in efficiently and accurately reconstructing images from undersampled MRI data without requiring fully sampled datasets as references. The proposed method involves resampling the acquired k-space data twice to generate two subsets using the same undersampling pattern as the original acquisitions, albeit with different acceleration factors. Subsequently, a network is trained to learn to map from one of the sets to the other in a supervised manner. Extensive experiments demonstrate that the RSSDU method outperforms several well-known self-supervised methods, including SSDU and K-band, regarding peak signal-to-noise ratio and structural similarity index measurement.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110404"},"PeriodicalIF":2.1,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906090","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":"Predicting sentinel lymph node metastatic burden with intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in clinical early-stage breast cancer patients","authors":"Mingli Jin ,&nbsp;Fang Xiao ,&nbsp;Qi Zhao ,&nbsp;Ying Jiang ,&nbsp;Zhihua Pan ,&nbsp;Zhicai Duan ,&nbsp;Juxi Jiang ,&nbsp;Miaoqi Zhang ,&nbsp;Jian Shu","doi":"10.1016/j.mri.2025.110397","DOIUrl":"10.1016/j.mri.2025.110397","url":null,"abstract":"<div><h3>Purpose</h3><div>The goal of this study was to investigate the value of IVIM-MRI and DCE-MRI in predicting SLN metastatic burden in clinical practice for early-stage breast cancer patients.</div></div><div><h3>Methods</h3><div>The clinicopathologic and MRI data from 132 early-stage breast cancer patients were retrospectively reviewed and analyzed using logistic regression to identify risk factors for a high SLN metastatic burden. The diagnostic performance of those factors was then assessed via receiver operating characteristic (ROC) curve analysis.</div></div><div><h3>Results</h3><div>Lymphovascular invasion (OR, 0.220; 95 % CI, 0.076–0.642; <em>p = 0.006</em>), K^trans (OR, 0.971; 95 % CI, 0.944–0.998; <em>p = 0.034</em>) and D (OR, 1.010; 95 % CI, 1.003–1.017; <em>p = 0.004</em>) were independently associated with high metastatic burden. The area under the curve (AUC) for combined MRI &amp; pathologic features (0.893; 95 % CI, 0.830–0.956; <em>p &lt; 0.001</em>) and combined MRI (0.870; 95 % CI, 0.802–0.937; <em>p &lt; 0.001</em>) was significantly higher than for each single MRI parameter alone (<em>p = 0.002, 0.004)</em>, while the difference in AUCs between the combined MRI &amp; pathologic features and combined MRI was not significant ((<em>p = 0.154</em>).</div></div><div><h3>Conclusion</h3><div>IVIM-MRI and DCE-MRI can be used to predict SLN metastatic burden in early-stage breast cancer patients in clinical practice.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110397"},"PeriodicalIF":2.1,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900169","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":"Evaluation of blood supply using dynamic contrast-enhanced magnetic resonance imaging and its application in spinal tumor surgery.","authors":"Hongyang Guo, Xueyan Li, Xiaodong Gao, Ying Wang, Yuanjie Fan, Jiawei Miao, Chen Cheng, Yongqiang Jiao","doi":"10.1016/j.mri.2025.110400","DOIUrl":"https://doi.org/10.1016/j.mri.2025.110400","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to assess the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in evaluating blood supply for spinal tumors and its predictive value for intraoperative blood loss and transfusion requirements during spinal tumor surgery.</p><p><strong>Methods: </strong>We retrospectively analyzed clinical data from 20 patients with single vertebral tumors who underwent surgery at the Affiliated Hospital of Hebei University of Technology between December 2018 and December 2020. Patients were categorized based on DCE-MRI into two groups: those with tumors indicating rich blood supply (15 patients, with 12 undergoing preoperative embolization) and those with non-rich blood supply tumors (5 patients, without embolization). The primary outcomes measured were blood loss, operation time, and blood transfusion.</p><p><strong>Results: </strong>The blood flow (BF) ratio from DCE-MRI showed a significant positive correlation with DSA scores (r = 0.569, P < 0.05), indicating the reliability of DCE-MRI in evaluating tumor vascularity. In the group with rich blood supply tumors, the median DSA score was 3.25 (range 3-4), and the BF ratio ranged from 1.84 to 5.14, with a median value greater than 1.8. The BF ratio also correlated significantly with intraoperative bleeding (r = 0.537, P < 0.001) and blood transfusion requirements (r = 0.579, P < 0.001). The correlation with operation time was less pronounced (r = 0.259, P < 0.001).</p><p><strong>Conclusion: </strong>The DCE-MRI BF ratio is significantly correlated with intraoperative blood loss and transfusion requirements, providing valuable preoperative guidance for spinal tumor surgery. Its non-invasive predictive capabilities offer a clear advantage over traditional angiography, facilitating more informed surgical planning and patient care.</p>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":" ","pages":"110400"},"PeriodicalIF":2.1,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143990499","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":"Age-related change of glymphatic function in normative children assessed using diffusion tensor imaging-analysis along the perivascular space","authors":"Alex Mun-Ching Wong ,&nbsp;Tiing-Yee Siow ,&nbsp;Yi-Ting Cheng ,&nbsp;Eddy Chien-Yuan Lin ,&nbsp;Shin-Nan Lin ,&nbsp;Kuang-Lin Lin ,&nbsp;Cheng-Hong Toh","doi":"10.1016/j.mri.2025.110398","DOIUrl":"10.1016/j.mri.2025.110398","url":null,"abstract":"<div><h3>Background</h3><div>The glymphatic system, crucial for brain waste removal and homeostasis, has an underexplored developmental trajectory in children. This study describes changes in glymphatic function during childhood via diffusion tensor imaging-analysis along the perivascular space (DTI-ALPS).</div></div><div><h3>Methods</h3><div>We retrospectively studied DTI MR images of 72 pediatric participants (mean age = 92.37 months; 0–19.8 years; 50 % females), all showing normal MRI findings from 2019 to 2022. Imaging utilized 3 T scanners with a DTI sequence of 21 diffusion-encoded gradients, focusing on the ALPS index to assess glymphatic function. Clinical outcomes were determined using the Pediatric Cerebral Performance Category Scale and medical records within two weeks post-MRI. Regions-of-interest on diffusion maps were selected manually, guided by fractional anisotropy maps, for automatic ALPS computation. Pearson correlation and multiple linear regression analyzed the relationship between ALPS indices, age, and clinical scores, with a paired <em>t</em>-test comparing bilateral ALPS indices. Significance was set at <em>P</em> &lt; 0.05.</div></div><div><h3>Results</h3><div>Significant positive correlations between age and both left (<em>R</em> = 0.510, <em>P</em> &lt; 0.001) and right (<em>R</em> = 0.688, P &lt; 0.001) DTI-ALPS indices were observed, indicating developmental changes in glymphatic function. Age alone significantly predicted the DTI-ALPS indices (left ALPS: adjusted R² = 0.235; right ALPS: adjusted R² = 0.460), underscoring its developmental trajectory. The study found no significant differences between left and right DTI-ALPS indices, suggesting symmetrical glymphatic function during childhood.</div></div><div><h3>Conclusion</h3><div>This study reveals developmental changes in the glymphatic system across childhood, demonstrating an age-related increase in glymphatic function and bilateral symmetry.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"120 ","pages":"Article 110398"},"PeriodicalIF":2.1,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887320","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":"Linear rotationally invariant kurtosis measures from double diffusion encoding MRI","authors":"Hunter G. Moss ,&nbsp;Thorsten Feiweier ,&nbsp;Andreana Benitez ,&nbsp;Jens H. Jensen","doi":"10.1016/j.mri.2025.110399","DOIUrl":"10.1016/j.mri.2025.110399","url":null,"abstract":"<div><h3>Purpose</h3><div>To characterize the complete set of linear rotationally invariant kurtosis measures provided by double diffusion encoding (DDE) MRI, show their utility in distinguishing different types of multiple Gaussian compartment (MGC) models, and demonstrate simplified acquisition and analysis schemes for their estimation.</div></div><div><h3>Theory and methods</h3><div>The lowest order novel information obtainable with DDE MRI can be encapsulated in a six-dimensional kurtosis tensor. The most basic DDE MRI kurtosis measures are rotational invariants that are linear in this tensor while depending on no other physical quantities. We identify four such invariants and show that any others must be linear combinations of these. The invariants are applied to classify MGC models according to whether they include microscopic anisotropy or intercompartmental water exchange. In addition, they are used to investigate the effect of exchange on estimates of the microscopic fractional anisotropy (μFA). Simplified acquisition and analysis schemes for the invariants are proposed and demonstrated with human brain data obtained at 3 T.</div></div><div><h3>Results</h3><div>For the considered brain regions, the kurtosis invariants are found to be largely consistent with MGC models having microscopic anisotropy. They also indicate that water exchange in gray matter may affect estimates of μFA.</div></div><div><h3>Conclusion</h3><div>The kurtosis measures can classify MGC models according to whether they have microscopic anisotropy or water exchange, and they can be estimated with simple acquisition and analysis schemes. Measurements of the invariants in brain support the validity of MGC models with microscopic anisotropy and the importance of water exchange for modeling diffusion in gray matter.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"120 ","pages":"Article 110399"},"PeriodicalIF":2.1,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891357","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":"End-to-End Deep Learning-Based Motion Correction and Reconstruction for Accelerated Whole-Heart Joint T1/T2 Mapping","authors":"Lina Felsner ,&nbsp;Carlos Velasco ,&nbsp;Andrew Phair ,&nbsp;Thomas J. Fletcher ,&nbsp;Haikun Qi ,&nbsp;René M. Botnar ,&nbsp;Claudia Prieto","doi":"10.1016/j.mri.2025.110396","DOIUrl":"10.1016/j.mri.2025.110396","url":null,"abstract":"<div><h3>Purpose</h3><div>To accelerate 3D whole-heart joint T₁/T₂ mapping for myocardial tissue characterization using an end-to-end deep learning algorithm for joint motion estimation and model-based motion-corrected reconstruction of multi-contrast undersampled data.</div></div><div><h3>Methods</h3><div>A free-breathing high-resolution motion-compensated 3D joint T₁/T₂ water/fat sequence is employed. The sequence consists of the acquisition of four interleaved volumes with 2-echo encoding, resulting in eight volumes with different contrasts. An end-to-end non-rigid motion-corrected reconstruction network is used to estimate high quality motion-corrected reconstructions from the eight multi-contrast undersampled data for subsequent joint T₁/T₂ mapping. Reconstruction with the proposed approach was compared against state-of-the-art motion-corrected HD-PROST reconstruction.</div></div><div><h3>Results</h3><div>The proposed approach yields images with good visual agreement compared to the reference reconstructions. The comparison of the quantitative values in the T₁ and T₂ maps showed the absence of systematic errors, and a small bias of <span><math><mo>−</mo><mn>6.35</mn></math></span> ms and <span><math><mo>−</mo><mn>1.8</mn></math></span> ms, respectively. The proposed reconstruction time was <span><math><mn>24</mn></math></span> seconds in comparison to <span><math><mn>2.5</mn></math></span> hours with motion-corrected HD-PROST, resulting in a reconstruction speed-up of over <span><math><mn>370</mn></math></span> times.</div></div><div><h3>Conclusion</h3><div>In conclusion, this study presents a promising method for efficient whole-heart myocardial tissue characterization. Specifically, the research highlights the potential of the multi-contrast end-to-end deep learning algorithm for joint motion estimation and model-based motion-corrected reconstruction of multi-contrast undersampled data. The findings underscore its ability to compute T₁ and T₂ values with good agreement when compared to the reference motion-corrected HD-PROST method, while substantially reducing reconstruction time.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"121 ","pages":"Article 110396"},"PeriodicalIF":2.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921700","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":"Depth-dependent characterization of cartilage nanostructures using MRI signal decays","authors":"Theodore Aptekarev ,&nbsp;Gregory Furman ,&nbsp;Vladimir Sokolovsky ,&nbsp;Farid Badar ,&nbsp;Yang Xia","doi":"10.1016/j.mri.2025.110395","DOIUrl":"10.1016/j.mri.2025.110395","url":null,"abstract":"<div><h3>Objective</h3><div>The multi-exponential nature of echo decay in nuclear magnetic resonance exam of cartilage complicates the determination of relaxation times. In this study, a novel method has been developed and applied to analyze the cartilage nanostructure using multi-exponential signals. This approach eliminates the need for relaxation time determination, avoids sample rotation, and removes the requirement for multiple experiments. A key feature of this method is its ability to provide detailed insights into the nanostructures of the sample.</div></div><div><h3>Methods</h3><div>Quantitative <em>T</em>₂ imaging method was used to examine the signal delays in mature and healthy canine articular cartilage, at a transverse resolution of 35.1 μm. A modeling method was used to analyze the multi-exponential echo decay for each resolved tissue depth along the full thickness of articular cartilage.</div></div><div><h3>Results</h3><div>The developed approach provides detailed information on the nanostructure in the tissue, which varies with cartilage depth. The information contains the volumes of the water-filled nanocavities created by the fibril structure and their orientation. This information reveals that the superficial and transitional anatomic zones of cartilage contain two distinct types of nanocavities, while the radial zone contains only one type.</div></div><div><h3>Discussion</h3><div>The proposed voxel-based method of echo decay analysis enables the estimation of nanocavities, their angular distribution, and spatial variations of the nanocavity characteristics throughout the sample. This newly developed approach demonstrated that detailed structural tissue information can be obtained as a depth function, representing a significant advancement in understanding cartilage nanostructures and holds potential for future medical applications.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"120 ","pages":"Article 110395"},"PeriodicalIF":2.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858988","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}