{"title":"Signal-to-noise trade-offs between magnet diameter and shield-to-coil distance for cylindrical Halbach-based portable MRI systems for neuroimaging.","authors":"Javad Parsa, Andrew Webb","doi":"10.1007/s10334-024-01210-6","DOIUrl":"10.1007/s10334-024-01210-6","url":null,"abstract":"<p><strong>Objective: </strong>To investigate the trade-off between magnet bore diameter and the distance between the conductive Faraday shield and RF head coil for low-field point-of-care neuroimaging systems.</p><p><strong>Methods: </strong>Electromagnetic simulations were performed for three different Faraday shield geometries and two commonly used RF coil designs (spiral and solenoid) to assess the effects of a close-fitting shield on the RF coil's transmit and receive efficiencies. Experimental measurements were performed to confirm the accuracy of the simulations. Parallel simulations were performed to assess the static magnet ( <math><msub><mi>B</mi> <mn>0</mn></msub> </math> ) field as a function of the magnet bore diameter. The obtainable SNR was then calculated as a function of these two related variables.</p><p><strong>Results: </strong>Simulations of the RF coil characteristics and <math><msubsup><mi>B</mi> <mrow><mn>1</mn></mrow> <mo>+</mo></msubsup> </math> transmit efficiencies agreed well with corresponding experimentally determined parameters. Overall, the RF coil transmit efficiency was, as expected, higher when the gap between the shield and coil increased. The calculated intrinsic SNR showed that maximum SNR would be obtained for a cylindrical shield of diameter 310 mm with an inner diameter of the magnet of 320 mm (assuming 10 mm for the gradient coils).</p><p><strong>Conclusion: </strong>This work presents an overview of the trade-offs in transmit efficiencies for RF coils used for POC MRI neuroimaging as a function of coil-to-shield distance and inner diameter of the Halbach magnet. Results show that there is a relatively shallow optimum between a magnet diameter of 290 and 330 mm, with values falling more than 10% if either smaller or larger magnets are used.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"97-105"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469072","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}
Mehdi Panahi, Maliheh Habibi, Mahboube Sadat Hosseini
{"title":"Enhancing MRI radiomics feature reproducibility and classification performance in Parkinson's disease: a harmonization approach to gray-level discretization variability.","authors":"Mehdi Panahi, Maliheh Habibi, Mahboube Sadat Hosseini","doi":"10.1007/s10334-024-01215-1","DOIUrl":"10.1007/s10334-024-01215-1","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to assess the reproducibility of MRI-derived radiomic features across multiple gray-level discretization levels for classifying Parkinson's disease (PD) subtypes, and to evaluate the impact of ComBat harmonization on feature stability and machine learning performance.</p><p><strong>Methods: </strong>T1-weighted MRI scans from 140 PD patients (70 tremor-dominant, 70 postural instability gait difficulty) and 70 healthy controls were obtained from the Parkinson's progression markers initiative (PPMI) database. Radiomic features were extracted from 16 brain regions using 6 discretization levels (8, 16, 32, 64, 128, and 256 bins). ComBat harmonization was applied using a combined batch variable incorporating both scanner models and discretization levels. Intraclass correlation coefficients (ICC) and Kruskal-Wallis tests assessed feature reproducibility before and after harmonization. Support vector machine classifiers were used for PD subtype classification.</p><p><strong>Results: </strong>ComBat harmonization significantly improved feature reproducibility across all feature groups. The percentage of features showing excellent robustness (ICC ≥ 0.90) increased substantially after harmonization. The proportion of features significantly affected by discretization levels was reduced following harmonization. Classification accuracy improved dramatically, from a range of 0.42-0.49 before harmonization to 0.86-0.96 after harmonization across most discretization levels. AUC values similarly increased from 0.60-0.67 to 0.93-0.99 after harmonization.</p><p><strong>Conclusions: </strong>ComBat harmonization significantly enhanced the reproducibility of radiomic features across discretization levels and improved PD subtype classification performance. This study highlights the importance of harmonization in radiomics research for PD and suggests potential clinical applications in personalized treatment planning.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"23-35"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142739731","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":"Accelerating multi-coil MR image reconstruction using weak supervision.","authors":"Arda Atalık, Sumit Chopra, Daniel K Sodickson","doi":"10.1007/s10334-024-01206-2","DOIUrl":"10.1007/s10334-024-01206-2","url":null,"abstract":"<p><p>Deep-learning-based MR image reconstruction in settings where large fully sampled dataset collection is infeasible requires methods that effectively use both under-sampled and fully sampled datasets. This paper evaluates a weakly supervised, multi-coil, physics-guided approach to MR image reconstruction, leveraging both dataset types, to improve both the quality and robustness of reconstruction. A physics-guided end-to-end variational network (VarNet) is pretrained in a self-supervised manner using a 4 <math><mo>×</mo></math> under-sampled dataset following the self-supervised learning via data undersampling (SSDU) methodology. The pre-trained weights are transferred to another VarNet, which is fine-tuned using a smaller, fully sampled dataset by optimizing multi-scale structural similarity (MS-SSIM) loss in image space. The proposed methodology is compared with fully self-supervised and fully supervised training. Reconstruction quality improvements in SSIM, PSNR, and NRMSE when abundant training data is available (the high-data regime), and enhanced robustness when training data is scarce (the low-data regime) are demonstrated using weak supervision for knee and brain MR image reconstructions at 8 <math><mo>×</mo></math> and 10 <math><mo>×</mo></math> acceleration, respectively. Multi-coil physics-guided MR image reconstruction using both under-sampled and fully sampled datasets is achievable with transfer learning and fine-tuning. This methodology can provide improved reconstruction quality in the high-data regime and improved robustness in the low-data regime at high acceleration rates.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"37-51"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142391636","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}
Luis Carlos Sanmiguel-Serpa, Pieter de Visschere, Pim Pullens
{"title":"Concentric-object and equiangular-object methods to perform standardized regional analysis in renal mpMRI.","authors":"Luis Carlos Sanmiguel-Serpa, Pieter de Visschere, Pim Pullens","doi":"10.1007/s10334-024-01208-0","DOIUrl":"10.1007/s10334-024-01208-0","url":null,"abstract":"<p><strong>Objective: </strong>Renal multiparametric magnetic resonance imaging (mpMRI) sequences, including T<sub>1</sub>-T<sub>2</sub> mapping, Blood oxygenation level-dependent (BOLD), Renal blood flow (RBF), and Apparent Diffusion Coefficient (ADC) from diffusion-weighted imaging (DWI), provide insights into kidney function. However, consensus on selecting regions of interest (ROIs) is lacking. This study aims to describe and compare the Concentric Objects (CO) and Equiangular Objects (EO) methods for standardized ROI selection and assess their efficacy in capturing regional variations in renal MRI parameters.</p><p><strong>Materials and methods: </strong>Twelve healthy volunteers underwent mpMRI renal scans. ROIs were selected manually and by applying the CO and EO algorithms to each mpMRI sequence. The methods were tested across various subregion configurations. Regional differences in renal MRI parameters were evaluated.</p><p><strong>Results: </strong>CO and EO methods demonstrated statistically significant differences in mpMRI parameters across renal regions. ASL-RBF, BOLD-MRI, and T<sub>2</sub>-map results indicated substantial variations from the lower to upper kidney areas.</p><p><strong>Discussion: </strong>This study implemented CO and EO algorithms in renal mpMRI, showing their potential for evaluating cortico-medullary and cranio-caudal profiles. The findings validate the CO method for BOLD and ADC measurements and presented ASL-RBF and T<sub>1</sub>-T<sub>2</sub> map profiles. The EO method's utility needs further validation with renal patients.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"67-83"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469069","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}
Muhammad Shafique, Sizhuo Liu, Philip Schniter, Rizwan Ahmad
{"title":"MRI recovery with self-calibrated denoisers without fully-sampled data.","authors":"Muhammad Shafique, Sizhuo Liu, Philip Schniter, Rizwan Ahmad","doi":"10.1007/s10334-024-01207-1","DOIUrl":"10.1007/s10334-024-01207-1","url":null,"abstract":"<p><strong>Objective: </strong>Acquiring fully sampled training data is challenging for many MRI applications. We present a self-supervised image reconstruction method, termed ReSiDe, capable of recovering images solely from undersampled data.</p><p><strong>Materials and methods: </strong>ReSiDe is inspired by plug-and-play (PnP) methods, but unlike traditional PnP approaches that utilize pre-trained denoisers, ReSiDe iteratively trains the denoiser on the image or images that are being reconstructed. We introduce two variations of our method: ReSiDe-S and ReSiDe-M. ReSiDe-S is scan-specific and works with a single set of undersampled measurements, while ReSiDe-M operates on multiple sets of undersampled measurements and provides faster inference. Studies I, II, and III compare ReSiDe-S and ReSiDe-M against other self-supervised or unsupervised methods using data from T1- and T2-weighted brain MRI, MRXCAT digital perfusion phantom, and first-pass cardiac perfusion, respectively.</p><p><strong>Results: </strong>ReSiDe-S and ReSiDe-M outperform other methods in terms of peak signal-to-noise ratio and structural similarity index measure for Studies I and II, and in terms of expert scoring for Study III.</p><p><strong>Discussion: </strong>We present a self-supervised image reconstruction method and validate it in both static and dynamic MRI applications. These developments can benefit MRI applications where the availability of fully sampled training data is limited.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"53-66"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469071","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":"Design of multi-row parallel-transmit coil arrays for enhanced SAR efficiency with deep brain electrodes at 3T: an electromagnetic simulation study.","authors":"Nejat Karadeniz, Joseph V Hajnal, Özlem Ipek","doi":"10.1007/s10334-024-01212-4","DOIUrl":"10.1007/s10334-024-01212-4","url":null,"abstract":"<p><strong>Objective: </strong>Tissue heating near the implanted deep brain stimulation (DBS) during magnetic resonance imaging (MRI) poses a significant safety constraint. This study aimed to evaluate the performance of parallel transmit (pTx) head transmit radiofrequency (RF) coils in DBS patients, with a focus on excitation fidelity under specific absorption rate (SAR) control for brain imaging at 3T MRI.</p><p><strong>Materials and methods: </strong>We employed electromagnetic simulations to assess different coil configurations, including multi-row pTx coils of 16-24 channels arranged in 1, 2, and 3 rows, and compared these to a circularly polarised and pTx birdcage coil using a realistic human model without and with DBS leads and electrodes.</p><p><strong>Results: </strong>Two- and three-row pTx coils with overlapping loop elements exhibited similar performance, which was superior in excitation homogeneity and local SAR compared to the single-row coil and the birdcage coil both without and with DBS.</p><p><strong>Discussion: </strong>These findings suggest that multi-row coils can enhance the safety and efficacy of MRI in patients with DBS devices, so potentially improving imaging performance in this expanding patient population. There was a minimal difference in performance between the 2 and 3-row coils, favouring the simpler, lower channel count design for practical implementation.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"107-120"},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790791/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142623018","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}
Wan-Ting Zhao, Karl-Heinz Herrmann, Weiwei Wei, Martin Krämer, Uta Dahmen, Jürgen R Reichenbach
{"title":"A quality assurance protocol for reliable and reproducible multi-TI arterial spin labeling perfusion imaging in rat livers.","authors":"Wan-Ting Zhao, Karl-Heinz Herrmann, Weiwei Wei, Martin Krämer, Uta Dahmen, Jürgen R Reichenbach","doi":"10.1007/s10334-024-01223-1","DOIUrl":"https://doi.org/10.1007/s10334-024-01223-1","url":null,"abstract":"<p><strong>Objective: </strong>To establish an arterial spin labeling (ASL) protocol for rat livers that improves data reliability and reproducibility for perfusion quantification.</p><p><strong>Methods: </strong>This study used respiratory-gated, single-slice, FAIR-based ASL imaging with multiple inversion times (TI) in rat livers. Quality assurance measures included: (1) introduction of mechanical ventilation to ensure consistent respiratory cycles by controlling the respiratory rate (45 bpm), tidal volume (10 ml/kg), and inspiration: expiration ratio (I:E ratio, 1:2), (2) optimization of the trigger window for consistent trigger points, and (3) use of fit residual map and coefficient of variance as metrics to assess data quality. We compared image quality, perfusion maps, and fit residual maps between mechanically ventilated and non-ventilated animals, as well as repeated ASL measurements (session = 4 per animal) in two mechanically ventilated animals.</p><p><strong>Results: </strong>Perfusion measurements over multiple sessions in mechanically ventilated rats exhibited low perfusion data variability and high reproducibility both within and between liver lobes. Image quality and perfusion maps were significantly improved in mechanically ventilated animals compared to non-ventilated animals.</p><p><strong>Discussion: </strong>The implementation of mechanical ventilation and optimized quality assurance protocols enhanced the reliability and reproducibility of FAIR-based multi-TI-ASL imaging in rat livers. Our findings demonstrate these measures as a robust approach for achieving consistent liver perfusion quantification in preclinical settings.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142927458","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}
Habeeb Yusuff, Pierre-Emmanuel Zorn, Céline Giraudeau, Benoît Wach, Philippe Choquet, Simon Chatelin, Jean-Philippe Dillenseger
{"title":"Development of a cost-effective 3D-printed MRI phantom for enhanced teaching of system performance and image quality concepts.","authors":"Habeeb Yusuff, Pierre-Emmanuel Zorn, Céline Giraudeau, Benoît Wach, Philippe Choquet, Simon Chatelin, Jean-Philippe Dillenseger","doi":"10.1007/s10334-024-01217-z","DOIUrl":"https://doi.org/10.1007/s10334-024-01217-z","url":null,"abstract":"<p><strong>Purposes: </strong>This research highlights the need for affordable phantoms for MRI education. Current options are either expensive or limited. A phantom, easy to manufacture and distribute, is proposed to demonstrate various pedagogical concepts, aiding students in understanding MRI image quality concepts.</p><p><strong>Methods: </strong>We designed a cylindrical MRI phantom that comprises sections that can be filled with chosen liquids and gels. The dimensions were chosen to fit most consumer-grade 3D printers, facilitating widespread dissemination. It includes five modular sections for evaluating spatial resolution, geometrical accuracy, slice thickness accuracy, homogeneity, and contrast.</p><p><strong>Results: </strong>The modular cylindrical MRI phantom was successfully fabricated. Each section of the phantom was tested to ensure it met the specified pedagogical needs. The spatial resolution section provided clear images for evaluating fine details. The geometrical accuracy section allowed for precise measurement of distortions. The slice thickness accuracy section confirmed the consistency of slice thickness across different MRI sequences. The homogeneity section demonstrated uniform signal distribution, and the contrast section effectively displayed varying contrast levels.</p><p><strong>Conclusions: </strong>This modular MRI phantom offers a cost-effective tool for educational purposes in MRI. Its design enables educators to demonstrate multiple pedagogical scenarios with a single object. The phantom's compatibility with consumer-grade 3D printers and its modularity makes it accessible and adaptable to various educational settings. Future work could explore further customization and enhancement of the phantom to cover additional educational needs. This tool represents a significant step toward improving MRI education and training by providing a practical, hands-on learning experience.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142813653","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}
Lei Li, Qingyuan He, Shufeng Wei, Huixian Wang, Zheng Wang, Zhao Wei, Hongyan He, Ce Xiang, Wenhui Yang
{"title":"Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources.","authors":"Lei Li, Qingyuan He, Shufeng Wei, Huixian Wang, Zheng Wang, Zhao Wei, Hongyan He, Ce Xiang, Wenhui Yang","doi":"10.1007/s10334-024-01184-5","DOIUrl":"10.1007/s10334-024-01184-5","url":null,"abstract":"<p><strong>Objective: </strong>To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, unshielded imaging using minimal hardware resources.</p><p><strong>Methods: </strong>Firstly, we analyze the correlation of EMI signals between the sensing coil and the MRI coil to preliminarily verify the feasibility of active EMI shielding using a single sensing coil. Then, a powerful deep learning EMI elimination model is proposed, which can accurately predict the EMI components in the MRI coil signals using EMI signals from at least one sensing coil. Further, deep learning models with different task objectives (super-resolution and denoising) are strategically stacked for multi-level post-processing to enable fast and high-quality low-field MRI. Finally, extensive phantom and brain experiments were conducted on a home-built 0.2 T mobile brain scanner for the evaluation of the proposed strategy.</p><p><strong>Results: </strong>20 healthy volunteers were recruited to participate in the experiment. The results show that the proposed strategy enables the 0.2 T scanner to generate images with sufficient anatomical information and diagnostic value under unshielded conditions using a single sensing coil. In particular, the EMI elimination outperforms the state-of-the-art deep learning methods and numerical computation methods. In addition, 2 × super-resolution (DDSRNet) and denoising (SwinIR) techniques enable further improvements in imaging speed and quality.</p><p><strong>Discussion: </strong>The proposed strategy enables low-field mobile MRI scanners to achieve fast, high-quality imaging under unshielded conditions using minimal hardware resources, which has great significance for the widespread deployment of low-field mobile MRI scanners.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"1091-1104"},"PeriodicalIF":2.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141534759","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}
Soo Hyun Shin, Dina Moazamian, Qingbo Tang, Saeed Jerban, Yajun Ma, Jiang Du, Eric Y Chang
{"title":"Towards assessing and improving the reliability of ultrashort echo time quantitative magnetization transfer (UTE-qMT) MRI of cortical bone: In silico and ex vivo study.","authors":"Soo Hyun Shin, Dina Moazamian, Qingbo Tang, Saeed Jerban, Yajun Ma, Jiang Du, Eric Y Chang","doi":"10.1007/s10334-024-01190-7","DOIUrl":"10.1007/s10334-024-01190-7","url":null,"abstract":"<p><strong>Objective: </strong>To assess and improve the reliability of the ultrashort echo time quantitative magnetization transfer (UTE-qMT) modeling of the cortical bone.</p><p><strong>Materials and methods: </strong>Simulation-based digital phantoms were created that mimic the UTE-qMT properties of cortical bones. A wide range of SNR from 25 to 200 was simulated by adding different levels of noise to the synthesized MT-weighted images to assess the effect of SNR on UTE-qMT fitting results. Tensor-based denoising algorithm was applied to improve the fitting results. These results from digital phantom studies were validated via ex vivo rat leg bone scans.</p><p><strong>Results: </strong>The selection of initial points for nonlinear fitting and the number of data points tested for qMT analysis have minimal effect on the fitting result. Magnetization exchange rate measurements are highly dependent on the SNR of raw images, which can be substantially improved with an appropriate denoising algorithm that gives similar fitting results from the raw images with an 8-fold higher SNR.</p><p><strong>Discussion: </strong>The digital phantom approach enables the assessment of the reliability of bone UTE-qMT fitting by providing the known ground truth. These findings can be utilized for optimizing the data acquisition and analysis pipeline for UTE-qMT imaging of cortical bones.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"983-992"},"PeriodicalIF":2.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11582156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141913158","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}