Abstract Accurately predicting fracture risk in the clinic is challenging because the determinants are multi-factorial. A common approach to fracture risk assessment is to combine X-ray-based imaging ...methods such as dual-energy X-ray absorptiometry (DXA) with an online Fracture Risk Assessment Tool (FRAX) that includes additional risk factors such as age, family history, and prior fracture incidents. This approach still does not adequately diagnose many individuals at risk, especially those with certain diseases like type 2 diabetes. As such, this study investigated bound water and pore water concentrations ( Cbw and Cpw ) from ultra-short echo time (UTE) magnetic resonance imaging (MRI) as new predictors of fracture risk. Ex vivo cadaveric arms were imaged with UTE MRI as well as with DXA and high-resolution micro-computed tomography (μCT), and imaging measures were compared to both whole-bone structural and material properties as determined by three-point bending tests of the distal-third radius. While DXA-derived areal bone mineral density (aBMD) and μCT-derived volumetric BMD correlated well with structural strength, they moderately correlated with the estimate material strength with gender being a significant covariate for aBMD. MRI-derived measures of Cbw and Cpw had a similar predictive ability of material strength as aBMD but did so independently of gender. In addition, Cbw was the only imaging parameter to significantly correlate with toughness, the energy dissipated during fracture. Notably, the strength of the correlations with the material properties of bone tended to be higher when a larger endosteal region was used to determine Cbw and Cpw . These results indicate that MRI measures of Cbw and Cpw have the ability to probe bone material properties independent of bone structure or subject gender. In particular, toughness is a property of fracture resistance that is not explained by X-ray based methods. Thus, these MRI-derived measures of Cbw and Cpw in cortical bone have the potential to be useful in clinical populations for evaluating fracture risk, especially involving diseases that affect material properties of the bone beyond its strength.
Purpose
To introduce a combined machine learning (ML)‐ and physics‐based image reconstruction framework that enables navigator‐free, highly accelerated multishot echo planar imaging (msEPI) and ...demonstrate its application in high‐resolution structural and diffusion imaging.
Methods
Single‐shot EPI is an efficient encoding technique, but does not lend itself well to high‐resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high‐quality msEPI has been elusive because of phase mismatch arising from shot‐to‐shot variations which preclude the combination of the multiple‐shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations attributed to shot‐to‐shot changes. These variations are then included in a joint virtual coil sensitivity encoding (JVC‐SENSE) reconstruction to utilize data from all shots and improve upon the ML solution.
Results
Our combined ML + physics approach enabled Rinplane × multiband (MB) = 8‐ × 2‐fold acceleration using 2 EPI shots for multiecho imaging, so that whole‐brain T2 and T2* parameter maps could be derived from an 8.3‐second acquisition at 1 × 1 × 3‐mm3 resolution. This has also allowed high‐resolution diffusion imaging with high geometrical fidelity using 5 shots at Rinplane × MB = 9‐ × 2‐fold acceleration. To make these possible, we extended the state‐of‐the‐art MUSSELS reconstruction technique to simultaneous multislice encoding and used it as an input to our ML network.
Conclusion
Combination of ML and JVC‐SENSE enabled navigator‐free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end‐to‐end ML approaches.
Whole-brain high-resolution quantitative imaging is extremely encoding intensive, and its rapid and robust acquisition remains a challenge. Here we present a 3D MR fingerprinting (MRF) acquisition ...with a hybrid sliding-window (SW) and GRAPPA reconstruction strategy to obtain high-resolution T1, T2 and proton density (PD) maps with whole brain coverage in a clinically feasible timeframe.
3D MRF data were acquired using a highly under-sampled stack-of-spirals trajectory with a steady-state precession (FISP) sequence. For data reconstruction, kx-ky under-sampling was mitigated using SW combination along the temporal axis. Non-uniform fast Fourier transform (NUFFT) was then applied to create Cartesian k-space data that are fully-sampled in the in-plane direction, and Cartesian GRAPPA was performed to resolve kz under-sampling to create an alias-free SW dataset. T1, T2 and PD maps were then obtained using dictionary matching.
Phantom study demonstrated that the proposed 3D-MRF acquisition/reconstruction method is able to produce quantitative maps that are consistent with conventional quantification techniques. Retrospectively under-sampled in vivo acquisition revealed that SW + GRAPPA substantially improves quantification accuracy over the current state-of-the-art accelerated 3D MRF. Prospectively under-sampled in vivo study showed that whole brain T1, T2 and PD maps with 1 mm3 resolution could be obtained in 7.5 min.
3D MRF stack-of-spirals acquisition with hybrid SW + GRAPPA reconstruction may provide a feasible approach for rapid, high-resolution quantitative whole-brain imaging.
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•Combination of sliding-window and GRAPPA allows highly accelerated 3D MRF.•High-resolution (1 mm3) whole-brain multi-parameter maps obtained in 7.5-min.•Compared to 2D, 3D MRF enables higher SNR for accurate, isotropic resolution maps.
Purpose
To develop a method for fast distortion‐ and blurring‐free imaging.
Theory: EPI with point‐spread‐function (PSF) mapping can achieve distortion‐ and blurring‐free imaging at a cost of long ...acquisition time. In this study, an acquisition/reconstruction technique, termed “tilted‐CAIPI,” is proposed to achieve >20× acceleration for PSF‐EPI. The proposed method systematically optimized the k‐space sampling trajectory with B0‐inhomogeneity‐informed reconstruction, to exploit the inherent signal correlation in PSF‐EPI and take full advantage of coil sensitivity. Susceptibility‐induced phase accumulation is regarded as an additional encoding that is estimated by calibration data and integrated into reconstruction. Self‐navigated phase correction was developed to correct shot‐to‐shot phase variation in diffusion imaging.
Methods
Tilted‐CAIPI was implemented at 3T, with incorporation of partial Fourier and simultaneous multislice to achieve further accelerations. T2‐weighted, T2*‐weighted, and diffusion‐weighted imaging experiments were conducted to evaluate the proposed method.
Results
The ability of tilted‐CAIPI to provide highly accelerated imaging without distortion and blurring was demonstrated through in vivo brain experiments, where only 8 shots per simultaneous slice group were required to provide high‐quality, high‐SNR imaging at 0.8–1 mm resolution.
Conclusion
Tilted‐CAIPI achieved fast distortion‐ and blurring‐free imaging with high SNR. Whole‐brain T2‐weighted, T2*‐weighted, and diffusion imaging can be obtained in just 15–60 s.
Purpose
To implement the time‐resolved relaxometry PEPTIDE technique into a diffusion acquisition to provide self‐navigated, distortion‐ and blurring‐free diffusion imaging that is robust to motion, ...while simultaneously providing T2 and T2∗ mapping.
Theory and Methods
The PEPTIDE readout was implemented into a spin‐echo diffusion acquisition, enabling reconstruction of a time‐series of T2‐ and T2∗‐weighted images, free from conventional echo planar imaging (EPI) distortion and blurring, for each diffusion‐encoding. Robustness of PEPTIDE to motion and shot‐to‐shot phase variation was examined through a deliberate motion‐corrupted diffusion experiment. Two diffusion‐relaxometry in vivo brain protocols were also examined: (1)1 × 1 × 3 mm3 across 32 diffusion directions in 20 min, (2)1.5 × 1.5 × 3.0 mm3 across 6 diffusion‐weighted images in 3.4 min. T2, T2∗, and diffusion parameter maps were calculated from these data. As initial exploration of the rich diffusion‐relaxometry data content for use in multi‐compartment modeling, PEPTIDE data were acquired of a gadolinium‐doped asparagus phantom. These datasets contained two compartments with different relaxation parameters and different diffusion orientation properties, and T2 relaxation variations across these diffusion directions were explored.
Results
Diffusion‐PEPTIDE showed the capability to provide high quality diffusion images and T2 and T2∗ maps from both protocols. The reconstructions were distortion‐free, avoided potential resolution losses exceeding 100% in equivalent EPI acquisitions, and showed tolerance to nearly 30° of rotational motion. Expected variation in T2 values as a function of diffusion direction was observed in the two‐compartment asparagus phantom (P < .01), demonstrating potential to explore diffusion‐PEPTIDE data for multi‐compartment modeling.
Conclusions
Diffusion‐PEPTIDE provides highly robust diffusion and relaxometry data and offers potential for future applications in diffusion‐relaxometry multi‐compartment modeling.
Abstract Fragility fractures are a growing problem worldwide, and current methods for diagnosing osteoporosis do not always identify individuals who require treatment to prevent a fracture and may ...misidentify those not a risk. Traditionally, fracture risk is assessed using dual-energy X-ray absorptiometry, which provides measurements of areal bone mineral density (BMD) at sites prone to fracture. Recent advances in imaging show promise in adding new information that could improve the prediction of fracture risk in the clinic. As reviewed herein, advances in quantitative computed tomography (QCT) predict hip and vertebral body strength; high resolution HR-peripheral QCT (HR-pQCT) and micro-magnetic resonance imaging (μMRI) assess the micro-architecture of trabecular bone; quantitative ultrasound (QUS) measures the modulus or tissue stiffness of cortical bone; and quantitative ultra-short echo time MRI methods quantify the concentrations of bound water and pore water in cortical bone, which reflect a variety of mechanical properties of bone. Each of these technologies provides unique characteristics of bone and may improve fracture risk diagnoses and reduce prevalence of fractures by helping to guide treatment decisions.
Purpose
To develop an efficient MR technique for ultra‐high resolution diffusion MRI (dMRI) in the presence of motion.
Methods
gSlider is an SNR‐efficient high‐resolution dMRI acquisition technique. ...However, subject motion is inevitable during a prolonged scan for high spatial resolution, leading to potential image artifacts and blurring. In this study, an integrated technique termed Motion Corrected gSlider (MC‐gSlider) is proposed to obtain high‐quality, high‐resolution dMRI in the presence of large in‐plane and through‐plane motion. A motion‐aware reconstruction with spatially adaptive regularization is developed to optimize the conditioning of the image reconstruction under difficult through‐plane motion cases. In addition, an approach for intra‐volume motion estimation and correction is proposed to achieve motion correction at high temporal resolution.
Results
Theoretical SNR and resolution analysis validated the efficiency of MC‐gSlider with regularization, and aided in selection of reconstruction parameters. Simulations and in vivo experiments further demonstrated the ability of MC‐gSlider to mitigate motion artifacts and recover detailed brain structures for dMRI at 860 μm isotropic resolution in the presence of motion with various ranges.
Conclusion
MC‐gSlider provides motion‐robust, high‐resolution dMRI with a temporal motion correction sensitivity of 2 s, allowing for the recovery of fine detailed brain structures in the presence of large subject movements.
To translate and evaluate an in vivo magnetic resonance (MR) imaging protocol for quantitative mapping of collagen-bound and pore water concentrations in cortical bone that involves ...relaxation-selective ultrashort echo time (UTE) methods.
All HIPAA-compliant studies were performed with institutional review board approval and written informed consent. UTE imaging sequences were implemented on a clinical 3.0-T MR imaging unit and were used for in vivo imaging of bound and pore water in cortical bone. Images of the lower leg and wrist were acquired in five volunteers each (lower leg: two men and three women aged 24, 24, 49, 30, and 26 years; wrist: two men and three women aged 31, 23, 25, 24, and 26 years) to generate bound and pore water concentration maps of the tibia and radius. Each volunteer was imaged three times, and the standard error of the measurements at the region-of-interest (ROI) level was computed as the standard deviation across studies, pooled across volunteers and ROIs.
Quantitative bound and pore water maps in the tibia and radius, acquired in 8-14 minutes, had per-voxel signal-to-noise ratios of 18 (bound water) and 14 (pore water) and inter-study standard errors of approximately 2 mol (1)H per liter of bone at the ROI level.
The results of this study demonstrate the feasibility of quantitatively mapping bound and pore water in vivo in human cortical bone with practical human MR imaging constraints.
Purpose
We combine SNR‐efficient acquisition and model‐based reconstruction strategies with newly available hardware instrumentation to achieve distortion‐free in vivo diffusion MRI of the brain at ...submillimeter‐isotropic resolution with high fidelity and sensitivity on a clinical 3T scanner.
Methods
We propose blip‐up/down acquisition (BUDA) for multishot EPI using interleaved blip‐up/blip‐down phase encoding and incorporate B0 forward‐modeling into structured low‐rank reconstruction to enable distortion‐free and navigator‐free diffusion MRI. We further combine BUDA‐EPI with an SNR‐efficient simultaneous multislab acquisition (generalized slice‐dithered enhanced resolution “gSlider”), to achieve high‐isotropic‐resolution diffusion MRI. To validate gSlider BUDA‐EPI, whole‐brain diffusion data at 860‐μm and 780‐μm data sets were acquired. Finally, to improve the conditioning and minimize noise penalty in BUDA reconstruction at very high resolutions where B0 inhomogeneity can have a detrimental effect, the level of B0 inhomogeneity was reduced by incorporating slab‐by‐slab dynamic shimming with a 32‐channel AC/DC coil into the acquisition. Whole‐brain 600‐μm diffusion data were then acquired with this combined approach of gSlider BUDA‐EPI with dynamic shimming.
Results
The results of 860‐μm and 780‐μm datasets show high geometry fidelity with gSlider BUDA‐EPI. With dynamic shimming, the BUDA reconstruction’s noise penalty was further alleviated. This enables whole‐brain 600‐μm isotropic resolution diffusion imaging with high image quality.
Conclusions
The gSlider BUDA‐EPI method enables high‐quality, distortion‐free diffusion imaging across the whole brain at submillimeter resolution, where the use of multicoil dynamic B0 shimming further improves reconstruction performance, which can be particularly useful at very high resolutions.
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