Magnetic resonance imaging最新文献

{"title":"Insertable, dual-density dielectric barrier for acoustic pressure level reduction in a high-performance human head-only MRI system","authors":"S.-K. Lee,&nbsp;Matthew R. Tarasek,&nbsp;Keith Park,&nbsp;Desmond T.-B. Yeo,&nbsp;Thomas K.-F. Foo","doi":"10.1016/j.mri.2024.110224","DOIUrl":"10.1016/j.mri.2024.110224","url":null,"abstract":"<div><p>We report use of a dual-density dielectric barrier surrounding a detachable high-pass radiofrequency (RF) birdcage coil to achieve an order-of-magnitude reduction of acoustic noise in a high-performance head gradient system. The barrier consisted of a 4.5 mm-thick mass-loaded vinyl and a 6 mm-thick polyurethane foam. It was inserted into the radial gap between the birdcage coil and the RF shield in a prototype head-only gradient system at 3 T. More than 9 dB_A reduction of sound pressure level was achieved on the average with representative, high acoustic-noise imaging sequences. Increased acoustic damping was apparent from acoustic impulse response functions. High dielectric constant of the mass-loaded vinyl effectively added distributed capacitance to the birdcage coil, lowering the resonance frequency, but not seriously degrading the RF transmission performance. The barrier occupied the radial space normally used for air cooling of the RF coil and the RF shield. The resulting omission of air cooling was found to be acceptable with efficient gradient thermal management and use of a high-resistivity RF shield for eddy current reduction. The proposed method can improve patient experience while preserving image quality in a high-power head-only gradient system.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"114 ","pages":"Article 110224"},"PeriodicalIF":2.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142133171","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":"Inter-visit and inter-reader reproducibility of multi-parametric diffusion-weighted MR imaging in longitudinally imaged patients with metabolic dysfunction-associated fatty liver disease and healthy volunteers.","authors":"Anton Volniansky ,&nbsp;Thierry L. Lefebvre ,&nbsp;Merve Kulbay ,&nbsp;Boyan Fan ,&nbsp;Emre Aslan ,&nbsp;Kim-Nhien Vu ,&nbsp;Emmanuel Montagnon ,&nbsp;Bich Ngoc Nguyen ,&nbsp;Giada Sebastiani ,&nbsp;Jeanne-Marie Giard ,&nbsp;Marie-Pierre Sylvestre ,&nbsp;Guillaume Gilbert ,&nbsp;Guy Cloutier ,&nbsp;An Tang","doi":"10.1016/j.mri.2024.110223","DOIUrl":"10.1016/j.mri.2024.110223","url":null,"abstract":"<div><h3>Background</h3><p>Despite the widespread use of diffusion-weighted imaging (DWI) in metabolic dysfunction-associated fatty liver disease (MAFLD), MRI acquisition and quantification techniques vary in the literature suggesting the need for established and reproducible protocols. The goal of this study was to assess inter-visit and inter-reader reproducibility of DWI- and IVIM-derived parameters in patients with MAFLD and healthy volunteers using extensive sampling of the “fast” compartment, non-rigid registration, and exclusion voxels with poor fit quality.</p></div><div><h3>Methods</h3><p>From June 2019 to April 2023, 31 subjects (20 patients with biopsy-proven MAFLD and 11 healthy volunteers) were included in this IRB-approved study. Subjects underwent MRI examinations twice within 40 days. 3.0 T DWI was acquired using a respiratory-triggered spin-echo diffusion-weighted echo-planar imaging sequence (<em>b</em>-values of 0, 10, 20, 30, 40, 50, 100, 200, 400, 800 s/mm²). DWI series were co-registered prior to voxel-wise non-linear regression of the IVIM model and voxels with poor fit quality were excluded (normalized root mean squared error ≥ 0.05). IVIM parameters (perfusion fraction, <em>f</em>; diffusion coefficient, <em>D</em>; and pseudo-diffusion coefficient, <em>D*</em>), and apparent diffusion coefficients (ADC) were computed from manual segmentation of the right liver lobe performed by two analysts on two MRI examinations.</p></div><div><h3>Results</h3><p>All results are reported for <em>f</em>, <em>D</em>, <em>D*</em>, and ADC respectively. For inter-reader agreement on the first visit, ICC were of 0.985, 0.994, 0.986, and 0.993 respectively. For intra-reader agreement of analyst 1 assessed on both imaging examinations, ICC between visits were of 0.805, 0.759, 0.511, and 0.850 respectively. For inter-reader agreement on the first visit, mean bias and 95 % limits of agreement were (0.00 ± 0.03), (−0.01 ± 0.03) × 10⁻³ mm²/s, (0.70 ± 10.40) × 10⁻³ mm²/s, and (−0.02 ± 0.04) × 10⁻³ mm²/s respectively. For intra-reader agreement of analyst 1, mean bias and 95 % limits of agreement were (0.01 ± 0.09) × 10⁻³ mm²/s, (−0.01 ± 0.21) × 10⁻³ mm²/s, (−13.37 ± 56.19) × 10⁻³ mm²/s, and (−0.01 ± 0.16) × 10⁻³ mm²/s respectively. Except for parameter <em>D*</em> that was associated with between-subjects parameter variability (<em>P</em> <strong>=</strong> 0.009), there was no significant variability between subjects, examinations, or readers.</p></div><div><h3>Conclusion</h3><p>With our approach, IVIM parameters <em>f</em>, <em>D</em>, <em>D*</em>, and ADC provided excellent inter-reader agreement and good to very good inter-visit or intra-reader agreement, thus showing the reproducibility of IVIM-DWI of the liver in MAFLD patients and volunteers.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110223"},"PeriodicalIF":2.1,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24002042/pdfft?md5=5bca27d4e324c10083f3213e93b09487&pid=1-s2.0-S0730725X24002042-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142056001","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 registration of T1-weighted breast MRI: A registration algorithm (FLIRE) and clinical application","authors":"Michelle W. Tong ,&nbsp;Hon J. Yu ,&nbsp;Maren M. Sjaastad Andreassen ,&nbsp;Stephane Loubrie ,&nbsp;Ana E. Rodríguez-Soto ,&nbsp;Tyler M. Seibert ,&nbsp;Rebecca Rakow-Penner ,&nbsp;Anders M. Dale","doi":"10.1016/j.mri.2024.110222","DOIUrl":"10.1016/j.mri.2024.110222","url":null,"abstract":"<div><h3>Purpose</h3><p>MRI is commonly used to aid breast cancer diagnosis and treatment evaluation. For patients with breast cancer, neoadjuvant chemotherapy aims to reduce the tumor size and extent of surgery necessary. The current clinical standard to measure breast tumor response on MRI uses the longest tumor diameter. Radiologists also account for other tissue properties including tumor contrast or pharmacokinetics in their assessment. Accurate longitudinal image registration of breast tissue is critical to properly compare response to treatment at different timepoints.</p></div><div><h3>Methods</h3><p>In this study, a deformable Fast Longitudinal Image Registration (FLIRE) algorithm was optimized for breast tissue. FLIRE was then compared to the publicly available software packages with high accuracy (DRAMMS) and fast runtime (Elastix). Patients included in the study received longitudinal T₁_-weighted MRI without fat saturation at two to six timepoints as part of asymptomatic screening (<em>n</em> = 27) or throughout neoadjuvant chemotherapy treatment (<em>n</em> = 32). T₁_-weighted images were registered to the first timepoint with each algorithm.</p></div><div><h3>Results</h3><p>Alignment and runtime performance were compared using two-way repeated measure ANOVAs (<em>P</em> &lt; 0.05). Across all patients, Pearson's correlation coefficient across the entire image volume was slightly higher with statistical significance and had less variance for FLIRE (0.98 ± 0.01 stdev) compared to DRAMMS (0.97 ± 0.03 stdev) and Elastix (0.95 ± 0.03 stdev). Additionally, FLIRE runtime (10.0 mins) was 9.0 times faster than DRAMMS (89.6 mins) and 1.5 times faster than Elastix (14.5 mins) on a Linux workstation.</p></div><div><h3>Conclusion</h3><p>FLIRE demonstrates promise for time-sensitive clinical applications due to its accuracy, robustness across patients and timepoints, and speed.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110222"},"PeriodicalIF":2.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24002030/pdfft?md5=3a8823f570ed73e6dfad0e0fd6b7ec98&pid=1-s2.0-S0730725X24002030-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142056000","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":"Dynamic contrast enhanced MRI of the head and neck region using a VIBE sequence with Cartesian undersampling and compressed sensing","authors":"F. Kubicka ,&nbsp;L. Nitschke ,&nbsp;T. Penzkofer ,&nbsp;Q. Tan ,&nbsp;M.D. Nickel ,&nbsp;K.M. Wakonig ,&nbsp;U.L. Fahlenkamp ,&nbsp;M. Lerchbaumer ,&nbsp;F. Michallek ,&nbsp;S. Dommerich ,&nbsp;B. Hamm ,&nbsp;M. Wagner ,&nbsp;T. Walter-Rittel","doi":"10.1016/j.mri.2024.110220","DOIUrl":"10.1016/j.mri.2024.110220","url":null,"abstract":"<div><h3>Objectives</h3><p>Compressed sensing allows for image reconstruction from sparsely sampled k-space data, which is particularly useful in dynamic contrast enhanced MRI (DCE-MRI). The aim of the study was to assess the diagnostic value of a volume-interpolated 3D T1-weighted spoiled gradient-echo sequence with variable density Cartesian undersampling and compressed sensing (CS) for head and neck MRI.</p></div><div><h3>Methods</h3><p>Seventy-one patients with clinical indications for head and neck MRI were included in this study. DCE-MRI was performed at 3 Tesla magnet using CS-VIBE (variable density undersampling, temporal resolution 3.4 s, slice thickness 1 mm). Image quality was compared to standard Cartesian VIBE. Three experienced readers independently evaluated image quality and lesion conspicuity on a 5-point Likert scale and determined the DCE-derived time intensity curve (TIC) types.</p></div><div><h3>Results</h3><p>CS-VIBE demonstrated higher image quality scores compared to standard VIBE with respect to overall image quality (4.3 ± 0.6 vs. 4.2 ± 0.7, <em>p</em> = 0.682), vessel contour (4.6 ± 0.4 vs. 4.4 ± 0.6, <em>p</em> &lt; 0.001), muscle contour (4.4 ± 0.5 vs. 4.5 ± 0.6, <em>p</em> = 0.302), lesion conspicuity (4.5 ± 0.7 vs. 4.3 ± 0.9, <em>p</em> = 0.024) and showed improved fat saturation (4.8 ± 0.3 vs. 3.8 ± 0.4, <em>p</em> &lt; 0.001) and movement artifacts were significantly reduced (4.6 ± 0.6 vs. 3.7 ± 0.7, <em>p</em> &lt; 0.001). Standard VIBE outperformed CS-VIBE in the delineation of pharyngeal mucosa (4.2 ± 0.5 vs. 4.6 ± 0.6, p &lt; 0.001). Lesion size in cases where a focal lesion was identified was similar for all readers for CS-VIBE and standard VIBE (<em>p</em> = 0.101). TIC curve assessment showed good interobserver agreement (<em>k</em>=0.717).</p></div><div><h3>Conclusion</h3><p>CS-VIBE with variable density Cartesian undersampling allows for DCE-MRI of the head and neck region with diagnostic, high image quality and high temporal resolution.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110220"},"PeriodicalIF":2.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24002017/pdfft?md5=9c1700c3f67502cbd678a68c550c21dd&pid=1-s2.0-S0730725X24002017-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142036264","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":"Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices","authors":"Emma Friesen ,&nbsp;Madison Chisholm ,&nbsp;Bibek Dhakal ,&nbsp;Morgan Mercredi ,&nbsp;Mark D. Does ,&nbsp;John C. Gore ,&nbsp;Melanie Martin","doi":"10.1016/j.mri.2024.110221","DOIUrl":"10.1016/j.mri.2024.110221","url":null,"abstract":"<div><p>Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter <span><math><mover><mi>AxD</mi><mo>¯</mo></mover></math></span>, packing fraction <span><math><msub><mi>f</mi><mi>in</mi></msub></math></span>, intra-cellular and <span><math><msub><mi>D</mi><mi>in</mi></msub></math></span> and extra-cellular <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span> diffusion coefficients, as well as the frequency dependence of <span><math><msub><mi>D</mi><mi>ex</mi></msub></math></span>, <span><math><msub><mi>β</mi><mi>ex</mi></msub></math></span> for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110221"},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24002029/pdfft?md5=d10d02e6d2c3f79e3d27a0ae71b624be&pid=1-s2.0-S0730725X24002029-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142036265","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":"An unrolled neural network for accelerated dynamic MRI based on second-order half-quadratic splitting model","authors":"Jiabing Sun,&nbsp;Changliang Wang,&nbsp;Lei Guo,&nbsp;Yongxiang Fang,&nbsp;Jiawen Huang,&nbsp;Bensheng Qiu","doi":"10.1016/j.mri.2024.110218","DOIUrl":"10.1016/j.mri.2024.110218","url":null,"abstract":"<div><p>The reconstruction of dynamic magnetic resonance images from incomplete k-space data has sparked significant research interest due to its potential to reduce scan time. However, traditional iterative optimization algorithms fail to faithfully reconstruct images at higher acceleration factors and incur long reconstruction time. Furthermore, end-to-end deep learning-based reconstruction algorithms suffer from large model parameters and lack robustness in the reconstruction results. Recently, unrolled deep learning models, have shown immense potential in algorithm stability and applicability flexibility. In this paper, we propose an unrolled deep learning network based on a second-order Half-Quadratic Splitting(HQS) algorithm, where the forward propagation process of this framework strictly follows the computational flow of the HQS algorithm. In particular, we propose a degradation-sense module by associating random sampling patterns with intermediate variables to guide the iterative process. We introduce the Information Fusion Transformer(IFT) to extract both local and non-local prior information from image sequences, thereby removing aliasing artifacts resulting from random undersampling. Finally, we impose low-rank constraints within the HQS algorithm to further enhance the reconstruction results. The experiments demonstrate that each component module of our proposed model contributes to the improvement of the reconstruction task. Our proposed method achieves comparably satisfying performance to the state-of-the-art methods and it exhibits excellent generalization capabilities across different sampling masks. At the low acceleration factor, there is a 0.7% enhancement in the PSNR. Furthermore, when the acceleration factor reached 8 and 12, the PSNR achieves an improvement of 3.4% and 5.8% respectively.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110218"},"PeriodicalIF":2.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788595","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":"Comparison of R2* and FerriScan liver iron concentration (LIC) quantification in the clinical classification of Iron overload states","authors":"Marshall S. Sussman ,&nbsp;Stephan A.R. Kannengiesser ,&nbsp;Shopnil Prasla ,&nbsp;Richard Ward ,&nbsp;Kartik S. Jhaveri","doi":"10.1016/j.mri.2024.110216","DOIUrl":"10.1016/j.mri.2024.110216","url":null,"abstract":"<div><h3>Purpose</h3><p>This study assessed the clinical classification performance of an R2*-based MRI technique for LIC quantification relative to FerriScan, with intra-patient FerriScan LIC uncertainty taken into account. The variabilities of R2* and FerriScan LIC were also assessed.</p></div><div><h3>Materials and methods</h3><p>This was an ethics approved retrospective study, performed on patients undergoing chelation treatment for iron overload. 126 patients (69 women, 57 men), with an age of 42 +/− 16 years (range 19–86 years) were included. FerriScan and R2* MRI at 1.5 T were performed as part of a routine liver iron assessment protocol. For R2* MRI, a commercially available pulse sequence and reconstruction implementation was used, together with a previously derived calibration curve to convert R2* to LIC. Clinical classifications arising from R2*-derived LIC estimates were compared to those based on FerriScan. The accuracy and precision of the R2* technique was calculated. The variabilities of FerriScan- and R2*-derived estimates of LIC were compared with a Wilcoxon Signed Rank test. Significance was set at the 95% confidence level.</p></div><div><h3>Results</h3><p>The precision of R2* ranged from 0.59 to 0.92, with an overall accuracy of 72%. When intra-patient FerriScan LIC uncertainty was considered, precision and accuracy increased to &gt;94% and 97% respectively. The R2*-LIC variability (=17%) was significantly lower than the FerriScan-LIC variability (34%) at the 95% confidence level (<em>p</em> &lt; 10⁻³).</p></div><div><h3>Conclusion</h3><p>MRI R2*-based LIC estimates provided a similar clinical classification as FerriScan. The intra-patient uncertainty of R2*-based LIC estimates was significantly lower than FerriScan.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110216"},"PeriodicalIF":2.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788596","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":"Spectro-ViT: A vision transformer model for GABA-edited MEGA-PRESS reconstruction using spectrograms","authors":"Gabriel Dias ,&nbsp;Rodrigo Pommot Berto ,&nbsp;Mateus Oliveira ,&nbsp;Lucas Ueda ,&nbsp;Sergio Dertkigil ,&nbsp;Paula D.P. Costa ,&nbsp;Amirmohammad Shamaei ,&nbsp;Hanna Bugler ,&nbsp;Roberto Souza ,&nbsp;Ashley Harris ,&nbsp;Leticia Rittner","doi":"10.1016/j.mri.2024.110219","DOIUrl":"10.1016/j.mri.2024.110219","url":null,"abstract":"<div><p>This study investigated the use of a Vision Transformer (ViT) for reconstructing GABA-edited Magnetic Resonance Spectroscopy (MRS) data from a reduced number of transients. Transients refer to the samples collected during an MRS acquisition by repeating the experiment to generate a signal of sufficient quality. Specifically, 80 transients were used instead of the typical 320 transients, aiming to reduce scan time. The 80 transients were pre-processed and converted into a spectrogram image representation using the Short-Time Fourier Transform (STFT). A pre-trained ViT, named Spectro-ViT, was fine-tuned and then tested using <em>in-vivo</em> GABA-edited MEGA-PRESS data. Its performance was compared against other pipelines in the literature using quantitative quality metrics and estimated metabolite concentration values, with the typical 320-transient scans serving as the reference for comparison. The Spectro-ViT model exhibited the best overall quality metrics among all other pipelines against which it was compared. The metabolite concentrations from Spectro-ViT's reconstructions for GABA+ achieved the best average R² value of 0.67 and the best average Mean Absolute Percentage Error (MAPE) value of 9.68%, with no significant statistical differences found compared to the 320-transient reference. The code to reproduce this research is available at <span><span>https://github.com/MICLab-Unicamp/Spectro-ViT</span><svg><path></path></svg></span></p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110219"},"PeriodicalIF":2.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0730725X24001942/pdfft?md5=8ffa729ed54b95fb16984886f1916963&pid=1-s2.0-S0730725X24001942-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788597","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":"Test-retest repeatability of myocardial radiomic features from quantitative cardiac magnetic resonance T1 and T2 mapping","authors":"Daniela Marfisi ,&nbsp;Marco Giannelli ,&nbsp;Chiara Marzi ,&nbsp;Jacopo Del Meglio ,&nbsp;Andrea Barucci ,&nbsp;Luigi Masturzo ,&nbsp;Claudio Vignali ,&nbsp;Mario Mascalchi ,&nbsp;Antonio Traino ,&nbsp;Giancarlo Casolo ,&nbsp;Stefano Diciotti ,&nbsp;Carlo Tessa","doi":"10.1016/j.mri.2024.110217","DOIUrl":"10.1016/j.mri.2024.110217","url":null,"abstract":"<div><p>Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance.</p><p>The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps.</p><p>A representative group of 24 subjects (mean age 54 ± 18 years) referred for clinical cardiac MR imaging were enrolled in the study. For each subject, T1 and T2 mapping through MOLLI and T2-prepared TrueFISP acquisition sequences, respectively, were performed at 1.5 T. Then, 98 radiomic features of different classes (shape, first-order, second-order) were extracted from a region of interest encompassing the whole left ventricle myocardium in a short axis slice. The repeatability was assessed performing different and complementary analyses: intraclass correlation coefficient (ICC) and limits of agreement (LOA) (i.e., the interval within which 95% of the percentage differences between two repeated measures are expected to lie).</p><p>Radiomic features were characterized by a relatively wide range of repeatability degree in terms of both ICC and LOA. Overall, 44.9% and 38.8% of radiomic features showed ICC values &gt; 0.75 for T1 and T2 maps, respectively, while 25.5% and 23.4% of radiomic features showed LOA between ±10%. A subset of radiomic features for T1 (Mean, Median, 10Percentile, 90Percentile, RootMeanSquared, Imc2, RunLengthNonUniformityNormalized, RunPercentage and ShortRunEmphasis) and T2 (MaximumDiameter, RunLengthNonUniformityNormalized, RunPercentage, ShortRunEmphasis) maps presented both ICC &gt; 0.75 and LOA between ±5%.</p><p>Overall, radiomic features extracted from T1 maps showed better repeatability performance than those extracted from T2 maps, with shape features characterized by better repeatability than first-order and textural features. Moreover, only a limited subset of 9 and 4 radiomic features for T1 and T2 maps, respectively, showed high repeatability degree in terms of both ICC and LOA. These results confirm the importance of assessing test-retest repeatability degree in radiomic feature estimation and might be useful for a more effective/reliable use of myocardial T1 and T2 mapping radiomics in clinical or research studies.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110217"},"PeriodicalIF":2.1,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788598","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":"Correlation between matrix metalloproteinase-2, matrix metalloproteinase-9, and tissue inhibitor of metalloproteinases-1 and white matter hyperintensities in patients with cerebral small vessel disease based on cranial magnetic resonance 3D imaging","authors":"Bei-Lin Luo ,&nbsp;Shun-Po He ,&nbsp;Yi-Fen Zhang ,&nbsp;Qing-Wei Yang ,&nbsp;Jing-Cong Zhuang ,&nbsp;Ren-Jing Zhu ,&nbsp;Ya-Qin Zheng ,&nbsp;Hua-Mei Su","doi":"10.1016/j.mri.2024.110213","DOIUrl":"10.1016/j.mri.2024.110213","url":null,"abstract":"<div><h3>Objective</h3><p>The objective of this study was to investigate the correlation between serum levels of matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9), and tissue inhibitor of metalloproteinases-1 (TIMP-1) levels and their ratios with the severity of white matter hyperintensities (WMHs) in patients with cerebral small vessel disease (CSVD).</p></div><div><h3>Methods</h3><p>This cross-sectional study was done on a prospective cohort of patients with CSVD. Qualitative and quantitative analyses of WMHs were performed using Fazekas grading and lesion prediction algorithm (LPA) methods. Biomarkers MMP-2, MMP-9, and TIMP-1 were measured to explore their correlation with the severity of WMHs.</p></div><div><h3>Results</h3><p>The sample consisted of 144 patients with CSVD. There were 63 male and 81 female patients, with an average age of 67.604 ± 8.727 years. Among these, 58.33% presented with white matter hyperintensities at Fazekas grading level 1, with an average total template volume of WMHs of 4.305 mL. MMP-2 (<em>P</em> = 0.025), MMP-9 (<em>P</em> = 0.008), TIMP-1 (<em>P</em> = 0.026), and age (<em>P</em> = 0.007) were identified as independent correlates of WMHs based on Fazekas grading. Independent correlates of the total template volume of WMHs included MMP-2 (<em>P</em> = 0.023), TIMP-1 (<em>P</em> = 0.046), age (<em>P</em> = 0.047), systolic blood pressure (<em>P</em> = 0.047), and homocysteine (Hcy) (<em>P</em> = 0.014). In addition, age (<em>P</em> = 0.003; <em>P</em> &lt; 0.001), interleukin-6 (IL-6) (<em>P</em> &lt; 0.001; <em>P</em> = 0.044), Hcy (<em>P</em> &lt; 0.001; <em>P</em> &lt; 0.001), glycated hemoglobin (HbA1c) (<em>P</em> = 0.016; <em>P</em> = 0.043), and chronic kidney disease (<em>P</em> &lt; 0.001; <em>P</em> &lt; 0.001) were associated with both WMHs Fazekas grading and the total template volume of WMHs.</p></div><div><h3>Conclusion</h3><p>Serum levels of MMP-9, MMP-2, and TIMP-1 were independently associated with the Fazekas grading, while serum TIMP-1 and MMP-2 levels were independently related to the total template volume of WMHs. The association of TIMP-1 and MMP-2 with the severity of CSVD-related WMHs suggests their potential role as disease-related biomarkers. However, further research is required to uncover the specific mechanisms underlying these interactions.</p></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"113 ","pages":"Article 110213"},"PeriodicalIF":2.1,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759607","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}