Magnetic resonance imaging最新文献

{"title":"Combined model based on multimodal imaging and clinical pathology: A new pathway to assess hypoxia status and HIF-1α expression in breast cancer","authors":"Zhiyuan He ,&nbsp;Yiwen Wang ,&nbsp;Yunxi Li ,&nbsp;Laimin Zhu ,&nbsp;Yueqin Chen ,&nbsp;Ning Mao ,&nbsp;Wenwen Zhao ,&nbsp;Xiuzheng Yue ,&nbsp;Yufei Xue ,&nbsp;Shuzhen Wang ,&nbsp;Weiwei Wang ,&nbsp;Zhanguo Sun","doi":"10.1016/j.mri.2025.110537","DOIUrl":"10.1016/j.mri.2025.110537","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop and validate a combined model integrating multimodal magnetic resonance imaging (MRI) and clinical-pathological parameters to assess hypoxia status and hypoxia-inducible factor-1α (HIF-1α) expression in mass-like breast cancer.</div></div><div><h3>Methods</h3><div>This retrospective cohort study included 197 patients with mass-like breast cancer from two medical centers, who were divided into a training set (<em>n</em> = 104), an internal validation set (<em>n</em> = 45), and an external validation set (<em>n</em> = 48). Clinical-pathological and multimodal MRI parameters were analyzed using histopathology as the reference. The combined model was developed through logistic and least absolute shrinkage and selection operator (LASSO) regression analysis to identify features, and visualized using nomograms.</div></div><div><h3>Results</h3><div>Axillary lymph node (ALN) metastasis, time-intensity curve (TIC) type, mean diffusivity (MD), volumetric transfer constant (K^trans), and rate constant (Kep) were selected to construct the combined model. The diagnostic performance of the combined model [area under the curve (AUC) = 0.967, 95 % CI: 0.913–0.992] (training), was significantly better than that of other individual models (<em>P</em> &lt; 0.001). This performance was replicated in internal (AUC= 0.907) and external (AUC = 0.928) validation sets. The nomogram of the combined model showed excellent calibration (Hosmer-Lemeshow <em>P</em> = 0.653) and the highest net benefit across threshold probabilities in the decision curve analysis (DCA). Tumors with high HIF-1α expression exhibited higher ALN metastasis, histological grade, unclear margins, Type 3 TIC, and elevated K^trans, Kep, and MK, but reduced MD values.</div></div><div><h3>Conclusions</h3><div>The combined model (ALN + TIC + MD + K^trans + Kep) shows potential as a reliable tool for predicting HIF-1α expression levels in mass-like breast cancer.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110537"},"PeriodicalIF":2.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145232921","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":"Optimizing MPRAGE for enhanced blood suppression and intraplaque hemorrhage detection in carotid artery imaging","authors":"Seong-Eun Kim ,&nbsp;John A. Roberts ,&nbsp;J. Rock Hadley ,&nbsp;J. Scott McNally ,&nbsp;Gerald S. Treiman ,&nbsp;Yibin Xie ,&nbsp;Debiao Li ,&nbsp;Kim-Lien Nguyen ,&nbsp;Dimitrios Mitsouras ,&nbsp;Jonas Schollenberger ,&nbsp;David Saloner ,&nbsp;Arunbalaji Pugazhendhi ,&nbsp;Kevin J. Johnson ,&nbsp;Maria Altbach ,&nbsp;Herman Morris ,&nbsp;Kevin DeMarco ,&nbsp;Vibhas Deshpande ,&nbsp;Pedro Itriago-Leon ,&nbsp;Dennis L. Parker","doi":"10.1016/j.mri.2025.110531","DOIUrl":"10.1016/j.mri.2025.110531","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aims to optimize the Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE) technique to improve the accuracy of intraplaque hemorrhage (IPH) detection in carotid diseases and enhance reliability for clinical use, addressing the challenge of inconsistent blood suppression observed in commonly used clinical protocols.</div></div><div><h3>Methods</h3><div>Bloch equation simulations were used to evaluate the effects of inversion time and flip angle on blood suppression and tissue contrast. The optimized parameters were implemented on a clinical 3 T scanner and tested in four subjects. Quantitative measures included blood–muscle contrast and contrast-to-noise ratios (CNR) for lumen–wall and lumen–IPH. Imaging was performed in 21 patients with carotid artery disease, two MPRAGE acquisitions were performed per patient: (1) at the magnet isocenter with the standard IR pulse, and (2) at a 50-mm shifted position toward the heart with the wideband IR pulse. Qualitative image quality was evaluated independently by two neuroradiologists using a predefined 4-point scale (1 = poor, 4 = excellent) for blood suppression, vessel wall clarity, motion artifacts, and IPH visualization, in addition to quantitative SNR and CNR measurements.</div></div><div><h3>Results</h3><div>The optimized MPRAGE sequence demonstrated significantly improved blood suppression, with blood–muscle contrast increasing from 0.42 ± 0.08 to 0.61 ± 0.07 (<em>p</em> = 0.002). Lumen–wall CNR increased from 15.2 ± 3.4 to 22.8 ± 4.1 (<em>p</em> = 0.01), and lumen–IPH CNR increased from 18.7 ± 5.2 to 26.3 ± 6.0 (<em>p</em> = 0.004). These improvements enhanced vessel wall delineation and IPH conspicuity.</div></div><div><h3>Conclusion</h3><div>Optimization of MPRAGE parameters enhances blood suppression and contrast, providing improved visualization of the carotid vessel wall and more reliable detection of IPH. This approach may increase the diagnostic accuracy of carotid plaque imaging.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110531"},"PeriodicalIF":2.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145213152","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":"PHASE: Personalized Head-based Automatic Simulation for Electromagnetic properties in 7T MRI","authors":"Zhengyi Lu ,&nbsp;Hao Liang ,&nbsp;Ming Lu ,&nbsp;Dann Martin ,&nbsp;Benjamin M. Hardy ,&nbsp;Benoit M. Dawant ,&nbsp;Xiao Wang ,&nbsp;Xinqiang Yan ,&nbsp;Yuankai Huo","doi":"10.1016/j.mri.2025.110532","DOIUrl":"10.1016/j.mri.2025.110532","url":null,"abstract":"<div><div>Accurate and individualized human head models are becoming increasingly important for electromagnetic (EM) simulations. These simulations depend on precise anatomical representations to realistically model electric and magnetic field distributions, particularly when evaluating Specific Absorption Rate (SAR) within safety guidelines. State of the art simulations use the Virtual Population due to limited public resources and the impracticality of manually annotating patient data at scale. This paper introduces Personalized Head-based Automatic Simulation for EM properties (PHASE), an automated open-source toolbox that generates high-resolution, patient-specific head models for EM simulations using paired T1-weighted (T1w) magnetic resonance imaging (MRI) and computed tomography (CT) scans with 14 tissue labels. To evaluate the performance of PHASE models, we conduct semi-automated segmentation and EM simulations on 15 real human patients, serving as the gold standard reference. The PHASE model achieved comparable global SAR and localized SAR averaged over 10 grams of tissue (SAR-10g), demonstrating its potential as a promising tool for generating large-scale human model datasets in the future. The code and models of PHASE toolbox have been made publicly available: <span><span>https://github.com/hrlblab/PHASE</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110532"},"PeriodicalIF":2.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145182084","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":"Coherent flow effects on IVIM-based perfusion measurements: A phantom study in 3 T","authors":"Kamil Lipiński ,&nbsp;Grzegorz Domański ,&nbsp;Piotr Bogorodzki","doi":"10.1016/j.mri.2025.110533","DOIUrl":"10.1016/j.mri.2025.110533","url":null,"abstract":"<div><div>Quantitative, non-invasive measurement of perfusion remains a challenge in MRI. The Intravoxel Incoherent Motion (IVIM) technique, based on Diffusion-Weighted Imaging (DWI), offers a method to estimate perfusion at the sub-voxel level by modeling blood flow as a pseudo-diffusive process within a microvascular network. Key IVIM-derived parameters include the perfusion fraction (f) and the pseudo-diffusion coefficient (D*). While under specific structural assumptions, IVIM can be used to estimate Cerebral Blood Flow (CBF), direct conversions from IVIM metrics to CBF are rarely validated. This study investigates the accuracy of the IVIM-based perfusion measures, exploring coherent flow influence on signal from voxel. To assess the relation between flow (ground truth CBF), IVIM parameters, and calculated CBF, a phantom, composed of agarose gel and tubes mimicking arterioles with regulated flow velocity, was constructed. Thus, a signal fraction from the “fast” compartment, described by D* in the IVIM model, is represented by flow in tubes occupying a fixed fraction of the imaged voxel, simulating desired Cerebral Blood Volume (CBV) and CBF values. The phantom was scanned using IVIM-optimized DWI protocol, and data were processed for the IVIM measures. Besides IVIM, we also propose a model based on extended Bloch-Torrey equations with coherent flow term. Results demonstrate that IVIM can yield reasonable estimates of CBF and CBV within physiologically relevant flow ranges (0.5–2 mm/s) observed in the brain vasculature. However, a consistent overestimation of flow (up to 200 %) was obscerved at higher velocities, especially in arterial or vein-like flow conditions.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110533"},"PeriodicalIF":2.0,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145149806","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":"Imaging cardiac fat by cardiovascular magnetic resonance – A state-of-the art review","authors":"Franca Morselli ,&nbsp;Iain Pierce ,&nbsp;Matthew Webber ,&nbsp;Debbie Falconer ,&nbsp;Alun D. Hughes ,&nbsp;Michele Orini ,&nbsp;Pier D. Lambiase ,&nbsp;James C. Moon ,&nbsp;Gabriella Captur","doi":"10.1016/j.mri.2025.110529","DOIUrl":"10.1016/j.mri.2025.110529","url":null,"abstract":"<div><div>Myocardial fat infiltration may represent a substrate for ventricular arrhythmias, and its presence has been associated with increased risk for sudden cardiac death in both ischaemic and non-ischaemic cardiomyopathies. Epicardial and pericardial adiposity has also been linked with adverse cardiovascular outcomes. Fat-water separation (FWS) is an advanced magnetic resonance imaging technique enabling for visualisation and quantification of lipid content within the myocardium, and it can also identify fat-containing neoplasms, discriminate epicardial and pericardial fat, and characterise pericardial disease. Methods for FWS have improved significantly over the years, with resulting optimisation of cardiac and extracardiac fat imaging, and resolution of artifacts that may arise from the presence of fat. This review covers the physics underlying FWS imaging technique, its evolution, the practical aspects of sequence acquisition, clinical applications, and future directions.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110529"},"PeriodicalIF":2.0,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145131200","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":"Cardiac-induced brain tissue motion in Chiari Malformation type 1 subjects and its relationship to symptomatology, morphometrics, and surgical outcomes","authors":"Mahsa Karamzadeh ,&nbsp;Mohamad Motaz Al Samman ,&nbsp;Christopher Maclellan ,&nbsp;Rafeeque A. Bhadelia ,&nbsp;John Oshinski ,&nbsp;Rouzbeh Amini ,&nbsp;Seyed Amir Ebrahimzadeh ,&nbsp;Francis Loth","doi":"10.1016/j.mri.2025.110530","DOIUrl":"10.1016/j.mri.2025.110530","url":null,"abstract":"<div><h3>Purpose</h3><div>To determine whether cardiac-induced brain-tissue displacement in Chiari Malformation type 1 (CMI) relates to patient symptoms, morphometrics, and surgical outcomes.</div></div><div><h3>Methods</h3><div>We performed cardiac-gated phase-contrast MRI in 45 adults with CMI, converting velocity measurements to voxel-wise displacement in the cerebellum, pons, medulla, and cervical cord. We examined if displacement was correlated with each symptoms of subjects, and two anatomic measurements: tonsillar position (TP) and the ratio of neural-tissue area at foramen magnum to the area of foramen magnum. In seven patients who underwent posterior fossa decompression (PFD), we compared pre- versus post-operative displacement in seven paired scans and related changes to the Chicago Chiari Outcome Scale (CCOS).</div></div><div><h3>Results</h3><div>No significant correlations were found between displacement and symptom reports. TP correlated moderately with displacement (<em>r</em> = 0.47–0.61, <em>p</em> &lt; 0.002), and ratio of neural-tissue area showed modest links to cerebellar motion (<em>r</em> = 0.34–0.36, <em>p</em> &lt; 0.02). After PFD, mean and peak cerebellar displacement decreased by 45 % and 60 %, respectively (<em>p</em> &lt; 0.05), but neither pre-operative motion nor its reduction predicted CCOS scores.</div></div><div><h3>Conclusion</h3><div>While displacement increases with anatomical crowding and normalizes after surgery, it does not predict clinical symptoms or surgical outcomes. Future work should combine multiple biomechanical markers and detailed symptom scales in an effort to develop a multidimensional biomarker for guiding treatment and assessing recovery in CMI.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110530"},"PeriodicalIF":2.0,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118542","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":"DF-TransUNet: A novel TransUNet model of pixel level classification for cardiac MR image segmentation","authors":"Yunhui Zheng,&nbsp;Zhiyong Wu,&nbsp;Fengna Ji,&nbsp;Lei Du,&nbsp;Zhenyu Yang","doi":"10.1016/j.mri.2025.110502","DOIUrl":"10.1016/j.mri.2025.110502","url":null,"abstract":"<div><div>A crucial step in the intelligent healthcare system is the automatic analysis of medical images by machines and processing them accordingly, particularly in disease diagnosis, as it provides accurate anatomical structure information for subsequent treatment. This process provides precise anatomical data vital for the subsequent treatments. There is a problem of uneven intensity distribution and fuzzy boundaries etc. in medical images, which creates a great problem in the segmentation task. To cope with this problem, an improved TransUNet structure is introduced in this paper. This method is based on the TransUNet framework, and adds a pixel level classification module on the basis of TransUNet segmentation. This module can further classify the boundary parts of the mask to be segmented at the pixel level to achieve more accurate segmentation results. The method in this paper effectively reduces the classification errors associated with pixels near the boundaries of various masks within the MR image. In particular, The pixel classification module aims to learn the category of pixels near the mask boundary, and then enhance the original segmentation results through pixel level adjustments. To validate the effectiveness of this model, a series of experiments were conducted using the 2017 MICCAI Automated Cardiac Diagnostic Challenge (ACDC) dataset. The results show that with an average Dice coefficient of 90.55% and a Hausdorff distance of up to 2.23 mm, the proposed approach achieves a commendable segmentation performance. Code and models are available at <span><span>https://github.com/laodeyip/DF-TransUNet</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110502"},"PeriodicalIF":2.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102708","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":"Histogram analysis of quantitative susceptibility mapping and diffusion kurtosis imaging for the grading prediction of 2021 WHO adult-type diffuse gliomas","authors":"Pengxin Shen ,&nbsp;Yangyang Li ,&nbsp;Wenji Xu ,&nbsp;Zhiyi Zhang ,&nbsp;Xiaochun Wang ,&nbsp;Guoqiang Yang ,&nbsp;Jiangfeng Du ,&nbsp;Hui Zhang ,&nbsp;Yan Tan","doi":"10.1016/j.mri.2025.110528","DOIUrl":"10.1016/j.mri.2025.110528","url":null,"abstract":"<div><h3>Objectives</h3><div>To evaluate the role of quantitative susceptibility mapping (QSM) and diffusion kurtosis imaging (DKI) histogram features in improving the 2021 World Health Organization Classification of Central Nervous System Tumors (WHO CNS 5) grading accuracy for adult-type diffuse gliomas when combined with conventional imaging sequences.</div></div><div><h3>Methods</h3><div>A total of 62 patients were retrospectively collected. Histogram features of QSM, DKI, CE-T1WI, T2FLAIR were extracted from tumor parenchyma. Independent <em>t</em>-tests and Mann-Whitney <em>U</em> tests were used to compare differences between grade 2/3 and grade 4 gliomas. The evaluation of the model included receiver operating characteristic (ROC) curves, 5-fold cross-validation, nomogram construction, and calibration curve analysis. Prognostic differences between two groups were assessed using Kaplan-Meier survival analysis.</div></div><div><h3>Results</h3><div>The functional imaging model (AUC = 0.892) was constructed using QSM mean absolute deviation (MAD) and relative mean kurtosis 90th percentile (rMK P90), while the conventional imaging model (AUC = 0.776) was built using CE-T1WI robust mean absolute deviation (RMAD) and T2FLAIR maximum. The imaging combined model, incorporating CE-T1WI RMAD, QSM MAD, and rMK P90, achieved an AUC of 0.936. Among the clinical factors, age showed a statistically significant difference between the two groups, with an AUC of 0.769. The integrated model combining the imaging model and age achieved the highest AUC of 0.949. The 5-fold internal cross validation showed that the average AUC was 0.944. Survival analysis revealed a significant difference between grade 2/3 and grade 4 gliomas.</div></div><div><h3>Conclusion</h3><div>Histogram features of QSM and DKI can complement conventional sequences, enhancing the diagnostic performance for adult-type diffuse gliomas grading.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110528"},"PeriodicalIF":2.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145086431","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":"Correction of orientation dependence in magnetization transfer measures in the context of tractometry: Challenges, pitfalls and solutions","authors":"Philippe Karan ,&nbsp;Manon Edde ,&nbsp;Guillaume Gilbert ,&nbsp;Muhamed Barakovic ,&nbsp;Stefano Magon ,&nbsp;Maxime Descoteaux","doi":"10.1016/j.mri.2025.110522","DOIUrl":"10.1016/j.mri.2025.110522","url":null,"abstract":"<div><div>In this work we investigate the feasibility of a correction method for removing the orientation dependence of magnetization transfer (MT) measures in the context of tractometry. Following previous work on the track-based characterization of such orientation dependence using diffusion MRI, a correction method was developed. It uses polynomial fits to extrapolate the single-fiber characterizations and allows the MT measures across all white matter tracks to be shifted towards a chosen reference value, effectively removing the bias of fiber orientation with respect to the main magnetic field. Three different references were tested on a dataset of one hundred acquisitions and the performance was accessed by evaluating the removal of the orientation dependence and the reduction of variance between acquisitions, while also exploring the effects on tractometry results. Throughout these experiments, various challenges and pitfalls of an empirical correction method were laid out, like the absence of ground truth or the lack of knowledge about the complex behavior of the phenomenon in crossing-fiber voxels. Nonetheless, a solution was presented, paving the way towards a fully validated correction method for MT measures.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110522"},"PeriodicalIF":2.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065287","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":"Reply to “Unveiling cartilage nanostructures via anisotropic relaxometry of water protons: feasibility or fallacy?”","authors":"Theodore Aptekarev ,&nbsp;Gregory Furman ,&nbsp;Vladimir Sokolovsky ,&nbsp;Yang Xia","doi":"10.1016/j.mri.2025.110523","DOIUrl":"10.1016/j.mri.2025.110523","url":null,"abstract":"<div><div>This Reply addresses the issues raised in the Letter, entitled “Unveiling Cartilage Nanostructures via Anisotropic Relaxometry of Water Protons: Feasibility or Fallacy?” by Y. Pang, K. Momot, and V. Mlynárik (<em>Magnetic Resonance Imaging,</em> 123, 2025, 110508). The authors of the previous letter claimed that our model and theoretical results presented in our paper “Depth-dependent characterization of cartilage nanostructures using MRI signal decays” (<em>Magnetic Resonance Imaging</em>, 120, 2025, 110395) are incorrect. Here, we demonstrate that our model is based on theoretical and experimental data obtained using various methods, and that our results are consistent with previously published findings. Our developed approach allows analyzing the tissue structure: estimating the volumes of ellipsoidal water-filled nanocavities, their angular distributions, and the variations of these characteristics with depth. The principal difference of the new method from the early published studies is that these characteristics were obtained using a single NMR/MRI signal (echo decay) without a sample rotation.</div><div>We believe our results contribute to a better understanding of the complex issues related to MRI signal and tissue nanostructures.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"124 ","pages":"Article 110523"},"PeriodicalIF":2.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145040677","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}