Magnetic Resonance Materials in Physics, Biology and Medicine最新文献

Objective: Despite widespread uses in MRI research, the relative accuracies of different motion artifact simulation approaches in reproducing artifacts and artifact-induced changes (AIC) of morphometric parameters in structural MRI remain largely unknown. We aim to evaluate the performances of four simulation approaches in reproducing artifacts and AIC of brain morphometric parameters.

Methods: Within-session repeated T₁-weighted scans were acquired on ten volunteers with their heads remaining still or undergoing intentional motion monitored by fat navigators. Four simulation approaches were adopted, which differed in terms of whether channel-combined magnitude image or complex multi-channel k-space data were utilized, and whether motion effects were introduced by modifying k-space data value (MDV) or modifying k-space coordinates and data phase (MCP). By means of simulation, the dependence of morphometric parameter changes on motion pattern and severity was studied.

Results: Multi-channel k-space database simulation achieved higher artifact similarity and AIC consistency with measured motion scan images than magnitude image-based simulation. MDV- and MCP-based simulations achieved comparable results. From k-space database simulation employing MDV, the motion-induced biases in morphometric parameters were found to vary linearly with motion severity with motion pattern-dependent slopes.

Conclusions: Simulations based on multi-channel complex k-space data outperformed those based on channel-combined magnitude images in reproducing artifacts and AICs. Head motion caused imaging artifacts and systematic biases in morphometric parameters which can be equally reproduced by simulations using two different motion effect introduction strategies.

Objective: Intraoperative fiber tractography can help neurosurgeons in localizing eloquent tracts potentially displaced by tumors. In pediatric posterior fossa tumor (pPFT) patients, disturbances to the eloquent dentato-rubro-thalamic tract (DRTT) might contribute to cerebellar mutism syndrome. This study investigates the effect of fiber tractography parameters on DRTT reconstruction in pre- and intraoperative settings.

Methods: T1-weighted and diffusion MRI data were acquired from ten pPFT patients and two healthy volunteers. The patients were scanned pre- and intraoperatively. The DRTT was reconstructed using multiple fiber orientation distribution (FOD) and angle thresholds. An expert panel evaluated tract reconstructions to identify optimal parameters in our dataset. The corticospinal tract (CST) served as a control. Relative tract volumes of the DRTT and the CST were calculated.

Results: Diffusion MRI data were sufficient for reliable DRTT reconstruction in healthy volunteers. In most pPFT patients, an FOD of 0.01 and a 60° angle threshold were evaluated as optimal for DRTT reconstruction in our dataset. Preoperative DRTT reconstructions showed more reconstructed streamlines and larger relative volumes, particularly in non-decussating tracts. CST reconstructions remained consistent across both timepoints.

Discussion: DRTT reconstruction is feasible in pPFT patients before and during surgery. However, inter-subject variability suggests that some patients may require adjusted thresholds for optimal results.

Objective: To investigate the use of spiral readouts for sub-millimeter BOLD fMRI at 9.4T and to verify simulations of the BOLD point spread function (PSF) with functional experiments.

Materials and methods: Spiral readouts were evaluated through simulations and functional experiments to test their performance in sub-millimeter BOLD fMRI. Both spiral-out and spiral-in readout strategies were considered, with attention to echo time (TE) relative to T₂*.

Results: We confirmed that a TE shorter than T₂* can be employed for spiral-out readouts without compromising BOLD sensitivity. The use of shorter TE provided a reduced repetition time (TR), improved temporal signal-to-noise ratio (tSNR), and minimized off-resonance effects.

Discussion: Spiral-in readouts were found to be mainly useful for lower-resolution applications at ultra-high field (UHF). In contrast, segmented spiral-out readouts demonstrated strong potential for mesoscopic BOLD fMRI at ultra-high fields (> 7T).

Objective: First-pass myocardial perfusion involves several types of dynamics, including cardiac motion, respiratory motion, bulk motion and contrast agent inflow. To accurately quantify the initial inflow of the contrast agent, high spatiotemporal resolution MR imaging must be obtained. To achieve this, we present a novel approach, named CMR-MOTUS, for the reconstruction of time-resolved free-running first-pass myocardial perfusion by jointly estimating high-quality motion fields and contrast-varying images.

Materials and methods: We propose CMR-MOTUS, which extends the MR-MOTUS framework by integrating a contrast-varying reference image with a low-rank plus sparse decomposition to capture additional dynamics such as blood flow and contrast agent inflow. This joint reconstruction framework alternates between solving for time-dependent image contrast changes and motion fields, eliminating the need for a pre-acquisition motion-static reference image. The method was tested on simulations and in-vivo datasets.

Results: In simulations, CMR-MOTUS showed improved image similarity and motion field accuracy compared to state-of-the-art methods. In in-vivo tests, the methods effectively captured cardiac and respiratory motion dynamics, resulting in cine images with sharper features than state-of-the-art.

Discussion: CMR-MOTUS presents significant advantages by modelling motion and contrast dynamics in the reconstruction of first-pass myocardial perfusion. The framework enables a data-efficient free-running workflow since the entire acquisition is correlated with high-quality motion fields. This approach has the potential to enhance the diagnostic value of cardiac MRI but needs further clinical validations.

Objective: This study aimed to describe important criteria for phantom design, while designing an open-source phantom that uses accessible materials and fabrication processes, and that can be easily reproduced and modified by others in the MRI research community.

Materials and methods: We enumerate considerations related to designing a phantom based on literature and previous experience. We design and use an open-source phantom on a low-field MRI system. The phantom was 3D printed and assembled, and the imaged samples were made from commonly available materials. T1-weighted and T2-weighted axial and coronal images were acquired at 64 mT, and signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and geometric distortion along one dimension were assessed for each image.

Results: Two iterations of the phantom design were made to improve the construction materials and overall form factor for imaging. T1-weighted and T2-weighted images showed contrast between samples and background. T2-weighted images had an 8-10× increase in SNR and CNR compared to T1-weighted images. Geometric distortion measurements were within one-pixel spacing for all scans.

Discussion: An open-source phantom was created to assess MRI scans at low-field. Future users may modify the phantom to suit their needs. User-designed inserts can be added, allowing for validation of many MRI-related measurements.

Objective: Low-field magnetic resonance imaging is currently developing into a valuable diagnostic tool due to its simplicity of magnet array designs. Particularly, this allows the development of scanners as part of educational workshops, thus ensuring knowledge transfer and empowering local scientists to design tailored solutions for specific local problems. To obtain the maximum performance, the magnet needs to be shimmed requiring an automated system measuring the spatial magnetic field distribution.

Methods: A self-designed measuring probe based on commercial integrated Hall sensor chips is used and optimized by calibrating it in an easy-to-build calibration system. For positioning of the sensor, a low-cost five-degree-of-freedom robot arm is used and improved by camera-based motion tracking for precise localization of the sensor.

Results: The system is able to map the field of a $45\text{mT}$ -Halbach desktop MR magnet, as well as a self-designed x-gradient (used inside the magnet) with an efficiency of $2\text{mT}/\text{m}/\text{A}$ . The built-up Hall sensor demonstrates a level of precision that is competitive with commercial sensors. The entire positioning system can be freely scaled to accommodate larger designs by adjusting the kinematics.

Conclusion: The presented system is demonstrated to be comparable to already established measurement systems, while the costs, setup times, and mapping duration are greatly reduced.

Object: Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are well-known and powerful imaging techniques for MRI. Although DTI evaluation has evolved continually in recent years, there are still struggles regarding quantitative measurements that can benefit brain areas that are consistently difficult to measure via diffusion-based methods, e.g., gray matter (GM). The present study proposes a new image processing technique based on diffusion distribution evaluation of López-Ruiz, Mancini and Calbet (LMC) complexity called diffusion complexity (DC).

Materials and methods: The OASIS-3 and TractoInferno open-science databases for healthy individuals were used, and all the codes are provided as open-source materials.

Results: The DC map showed relevant signal characterization in brain tissues and structures, achieving contrast-to-noise ratio (CNR) gains of approximately 39% and 93%, respectively, compared to those of the FA and ADC maps.

Discussion: In the special case of GM tissue, the DC map obtains its maximum signal level, showing the possibility of studying cortical and subcortical structures challenging for classical DTI quantitative formalism. The ability to apply the DC technique, which requires the same imaging acquisition for DTI and its potential to provide complementary information to study the brain's GM structures, can be a rich source of information for further neuroscience research and clinical practice.