Self-Navigated Three-Dimensional Ultrashort Echo Time Technique for Motion-Corrected Skull MRI

Three-Dimensional Variable Slab-Selective Projection Acquisition Imaging

Three-dimensional (3D) projection acquisition (PA) imaging has recently gained attention because of its advantages, such as achievability of very short echo time, less sensitivity to motion, and undersampled acquisition of projections without sacrificing spatial resolution. However, larger subjects require a stronger Nyquist criterion and are more likely to be affected by outer-volume signals outside the field of view (FOV), which significantly degrades the image quality. Here, we proposed a variable slab-selective projection acquisition (VSS-PA) method to mitigate the Nyquist criterion and effectively suppress aliasing streak artifacts in 3D PA imaging. The proposed method involves maintaining the vertical orientation of the slab-selective gradient for frequency-selective spin excitation and the readout gradient for data acquisition. As VSS-PA can selectively excite spins only in the width of the desired FOV in the projection direction during data acquisition, the effective size of the scanned object that determines the Nyquist criterion can be reduced. Additionally, unwanted signals originating from outside the FOV (e.g., aliasing streak artifacts) can be effectively avoided. The mitigation of the Nyquist criterion owing to VSS-PA was theoretically described and confirmed through numerical simulations and phantom and human lung experiments. These experiments further showed that the aliasing streak artifacts were nearly suppressed.

Three contrasts in 3 min: Rapid, high-resolution, and bone-selective UTE MRI for craniofacial imaging with automated deep-learning skull segmentation

PURPOSE

Ultrashort echo time (UTE) MRI can be a radiation-free alternative to CT for craniofacial imaging of pediatric patients. However, unlike CT, bone-specific MR imaging is limited by long scan times, relatively low spatial resolution, and a time-consuming bone segmentation workflow.

METHODS

A rapid, high-resolution UTE technique for brain and skull imaging in conjunction with an automatic segmentation pipeline was developed. A dual-RF, dual-echo UTE sequence was optimized for rapid scan time (3 min) and smaller voxel size (0.65 mm3). A weighted least-squares conjugate gradient method for computing the bone-selective image improves bone specificity while retaining bone sensitivity. Additionally, a deep-learning U-Net model was trained to automatically segment the skull from the bone-selective images. Ten healthy adult volunteers (six male, age 31.5 ± 10 years) and three pediatric patients (two male, ages 12 to 15 years) were scanned at 3 T. Clinical CT for the three patients were obtained for validation. Similarities in 3D skull reconstructions relative to clinical standard CT were evaluated based on the Dice similarity coefficient and Hausdorff distance. Craniometric measurements were used to assess geometric accuracy of the 3D skull renderings.

RESULTS

The weighted least-squares method produces images with enhanced bone specificity, suppression of soft tissue, and separation from air at the sinuses when validated against CT in pediatric patients. Dice similarity coefficient overlap was 0.86 ± 0.05, and the 95th percentile Hausdorff distance was 1.77 ± 0.49 mm between the full-skull binary masks of the optimized UTE and CT in the testing dataset.

CONCLUSION

An optimized MRI acquisition, reconstruction, and segmentation workflow for craniofacial imaging was developed.

Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis

PURPOSE

To develop a generalized rigid body motion correction method in 3D radial brain MRI to deal with continuous motion pattern through projection moment analysis.

METHODS

An assumption was made that the multichannel coil moves with the head, which was achieved by using a flexible head coil. A two-step motion correction scheme was proposed to directly extract the motion parameters from the acquired k-space data using the analysis of center-of-mass with high noise robustness, which were used for retrospective motion correction. A recursive least-squares model was introduced to recursively estimate the motion parameters for every single spoke, which used the smoothness of motion and resulted in high temporal resolution and low computational cost. Five volunteers were scanned at 3 T using a 3D radial multidimensional golden-means trajectory with instructed motion patterns. The performance was tested through both simulation and in vivo experiments. Quantitative image quality metrics were calculated for comparison.

RESULTS

The proposed method showed good accuracy and precision in both translation and rotation estimation. A better result was achieved using the proposed two-step correction compared to traditional one-step correction without significantly increasing computation time. Retrospective correction showed substantial improvements in image quality among all scans, even for stationary scans.

CONCLUSIONS

The proposed method provides an easy, robust, and time-efficient tool for motion correction in brain MRI, which may benefit clinical diagnosis of uncooperative patients as well as scientific MRI researches.

Cranial bone imaging using ultrashort echo-time bone-selective MRI as an alternative to gradient-echo based "black-bone" techniques

OBJECTIVES

CT is the clinical standard for surgical planning of craniofacial abnormalities in pediatric patients. This study evaluated three MRI cranial bone imaging techniques for their strengths and limitations as a radiation-free alternative to CT.

METHODS

Ten healthy adults were scanned at 3 T with three MRI sequences: dual-radiofrequency and dual-echo ultrashort echo time sequence (DURANDE), zero echo time (ZTE), and gradient-echo (GRE). DURANDE bright-bone images were generated by exploiting bone signal intensity dependence on RF pulse duration and echo time, while ZTE bright-bone images were obtained via logarithmic inversion. Three skull segmentations were derived, and the overlap of the binary masks was quantified using dice similarity coefficient. Craniometric distances were measured, and their agreement was quantified.

RESULTS

There was good overlap of the three masks and excellent agreement among craniometric distances. DURANDE and ZTE showed superior air-bone contrast (i.e., sinuses) and soft-tissue suppression compared to GRE.

DISCUSSIONS

ZTE has low levels of acoustic noise, however, ZTE images had lower contrast near facial bones (e.g., zygomatic) and require effective bias-field correction to separate bone from air and soft-tissue. DURANDE utilizes a dual-echo subtraction post-processing approach to yield bone-specific images, but the sequence is not currently manufacturer-supported and requires scanner-specific gradient-delay corrections.

The signs of computer tomography combined with artificial intelligence can indicate the correlation between status of consciousness and primary brainstem hemorrhage of patients

Background

For patients of primary brainstem hemorrhage (PBH), it is crucial to find a method that can quickly and accurately predict the correlation between status of consciousness and PBH.

Objective

To analyze the value of computer tomography (CT) signs in combination with artificial intelligence (AI) technique in predicting the correlation between status of consciousness and PBH.

Methods

A total of 120 patients with PBH were enrolled from August 2011 to March 2021 according to the criteria. Patients were divided into three groups [consciousness, minimally conscious state (MCS) and coma] based on the status of consciousness. Then, first, Mann–Whitney U test and Spearman rank correlation test were used on the factors: gender, age, stages of intracerebral hemorrhage, CT signs with AI or radiology physicians, hemorrhage involving the midbrain or ventricular system. We collected hemorrhage volumes and mean CT values with AI. Second, those significant factors were screened out by the Mann–Whitney U test and those highly or moderately correlated by Spearman’s rank correlation test, and a further ordinal multinomial logistic regression analysis was performed to find independent predictors of the status of consciousness. At last, receiver operating characteristic (ROC) curves were drawn to calculate the hemorrhage volume for predictively assessing the status of consciousness.

Results

Preliminary meaningful variables include hemorrhage involving the midbrain or ventricular system, hemorrhage volume, grade of hematoma shape and density, and CT value from Mann–Whitney U test and Spearman rank correlation test. It is further shown by ordinal multinomial logistic regression analysis that hemorrhage volume and hemorrhage involving the ventricular system are two major predictors of the status of consciousness. It showed from ROC that the hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL correspond to consciousness, MCS or coma, respectively. If the hemorrhage volume is the same, hemorrhage involving the ventricular system should be correlated with more severe disorders of consciousness (DOC).

Conclusion

CT signs combined with AI can predict the correlation between status of consciousness and PBH. Hemorrhage volume and hemorrhage involving the ventricular system are two independent factors, with hemorrhage volume in particular reaching quantitative predictions.

Motion corrected silent ZTE neuroimaging

Purpose

To develop self‐navigated motion correction for 3D silent zero echo time (ZTE) based neuroimaging and characterize its performance for different types of head motion.

Methods

The proposed method termed MERLIN (Motion Estimation & Retrospective correction Leveraging Interleaved Navigators) achieves self‐navigation by using interleaved 3D phyllotaxis k‐space sampling. Low resolution navigator images are reconstructed continuously throughout the ZTE acquisition using a sliding window and co‐registered in image space relative to a fixed reference position. Rigid body motion corrections are then applied retrospectively to the k‐space trajectory and raw data and reconstructed into a final, high‐resolution ZTE image.

Results

MERLIN demonstrated successful and consistent motion correction for magnetization prepared ZTE images for a range of different instructed motion paradigms. The acoustic noise response of the self‐navigated phyllotaxis trajectory was found to be only slightly above ambient noise levels (<4 dBA).

Conclusion

Silent ZTE imaging combined with MERLIN addresses two major challenges intrinsic to MRI (i.e., subject motion and acoustic noise) in a synergistic and integrated manner without increase in scan time and thereby forms a versatile and powerful framework for clinical and research MR neuroimaging applications.

Automatic Segmentation of Bone Selective MR Images for Visualization and Craniometry of the Cranial Vault

RATIONALE AND OBJECTIVES

Solid-state MRI has been shown to provide a radiation-free alternative imaging strategy to CT. However, manual image segmentation to produce bone-selective MR-based 3D renderings is time and labor intensive, thereby acting as a bottleneck in clinical practice. The objective of this study was to evaluate an automatic multi-atlas segmentation pipeline for use on cranial vault images entirely circumventing prior manual intervention, and to assess concordance of craniometric measurements between pipeline produced MRI and CT-based 3D skull renderings.

MATERIALS AND METHODS

Dual-RF, dual-echo, 3D UTE pulse sequence MR data were obtained at 3T on 30 healthy subjects along with low-dose CT images between December 2018 to January 2020 for this prospective study. The four-point MRI datasets (two RF pulse widths and two echo times) were combined to produce bone-specific images. CT images were thresholded and manually corrected to segment the cranial vault. CT images were then rigidly registered to MRI using mutual information. The corresponding cranial vault segmentations were then transformed to MRI. The "ground truth" segmentations served as reference for the MR images. Subsequently, an automated multi-atlas pipeline was used to segment the bone-selective images. To compare manually and automatically segmented MR images, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) were computed, and craniometric measurements between CT and automated-pipeline MRI-based segmentations were examined via Lin's concordance coefficient (LCC).

RESULTS

Automated segmentation reduced the need for an expert to obtain segmentation. Average DSC was 90.86 ± 1.94%, and average 95th percentile HD was 1.65 ± 0.44 mm between ground truth and automated segmentations. MR-based measurements differed from CT-based measurements by 0.73-1.2 mm on key craniometric measurements. LCC for distances between CT and MR-based landmarks were vertex-basion: 0.906, left-right frontozygomatic suture: 0.780, and glabella-opisthocranium: 0.956 for the three measurements.

CONCLUSION

Good agreement between CT and automated MR-based 3D cranial vault renderings has been achieved, thereby eliminating the laborious manual segmentation process. Target applications comprise craniofacial surgery as well as imaging of traumatic injuries and masses involving both bone and soft tissue.

Whole-brain 3D mapping of oxygen metabolism using constrained quantitative BOLD

Quantitative BOLD (qBOLD) MRI permits noninvasive evaluation of hemodynamic and metabolic states of the brain by quantifying parametric maps of deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Y_v), and along with a measurement of cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO₂). The method, thus should have potential to provide important information on many neurological disorders as well as normal cerebral physiology. One major challenge in qBOLD is to separate de-oxyhemoglobin’s contribution to R₂′ from other sources modulating the voxel signal, for instance, R₂, R₂′ from non-heme iron (R′_2,nh), and macroscopic magnetic field variations. Further, even with successful separation of the several confounders, it is still challenging to extract DBV and Y_v from the heme-originated R₂′ because of limited sensitivity of the qBOLD model. These issues, which have not been fully addressed in currently practiced qBOLD methods, have so far precluded 3D whole-brain implementation of qBOLD. Thus, the purpose of this work was to develop a new 3D MRI oximetry technique that enables robust qBOLD parameter mapping across the entire brain. To achieve this goal, we employed a rapid, R₂′-sensitive, steady-state 3D pulse sequence (termed ‘AUSFIDE’) for data acquisition, and implemented a prior-constrained qBOLD processing pipeline that exploits a plurality of preliminary parameters obtained via AUSFIDE, along with additionally measured cerebral venous blood volume. Numerical simulations and in vivo studies at 3 T were performed to evaluate the performance of the proposed, constrained qBOLD mapping in comparison to the parent qBOLD method. Measured parameters (Y_v, DBV, R′_2,nh, nonblood magnetic susceptibility) in ten healthy subjects demonstrate the expected contrast across brain territories, while yielding group-averages of 64.0 ± 2.3 % and 62.2 ± 3.1 % for Y_v and 2.8 ± 0.5 % and 1.8 ± 0.4 % for DBV in cortical gray and white matter, respectively. Given the Y_v measurements, additionally quantified CBF in seven of the ten study subjects enabled whole-brain 3D CMRO₂ mapping, yielding group averages of 134.2 ± 21.1 and 79.4 ± 12.6 µmol/100 g/min for cortical gray and white matter, in good agreement with literature values. The results suggest feasibility of the proposed method as a practical and reliable means for measuring neurometabolic parameters over an extended brain coverage.

MRI-derived porosity index is associated with whole-bone stiffness and mineral density in human cadaveric femora

Ultrashort echo time (UTE) magnetic resonance imaging (MRI) measures proton signals in cortical bone from two distinct water pools, bound water, or water that is tightly bound to bone matrix, and pore water, or water that is freely moving in the pore spaces in bone. By isolating the signal contribution from the pore water pool, UTE biomarkers can directly quantify cortical bone porosity in vivo. The Porosity Index (PI) is one non-invasive, clinically viable UTE-derived technique that has shown strong associations in the tibia with μCT porosity and other UTE measures of bone water. However, the efficacy of the PI biomarker has never been examined in the proximal femur, which is the site of the most catastrophic osteoporotic fractures. Additionally, the loads experienced during a sideways fall are complex and the femoral neck is difficult to image with UTE, so the usefulness of the PI in the femur was unknown. Therefore, the aim of this study was to examine the relationships between the PI measure in the proximal cortical shaft of human cadaveric femora specimens compared to (1) QCT-derived bone mineral density (BMD) and (2) whole bone stiffness obtained from mechanical testing mimicking a sideways fall. Fifteen fresh, frozen whole cadaveric femora specimens (age 72.1 ± 15.0 years old, 10 male, 5 female) were scanned on a clinical 3-T MRI using a dual-echo UTE sequence. Specimens were then scanned on a clinical CT scanner to measure volumetric BMD (vBMD) and then non-destructively mechanically tested in a sideways fall configuration. The PI in the cortical shaft demonstrated strong correlations with bone stiffness (r = -0.82, P = 0.0014), CT-derived vBMD (r = -0.64, P = 0.0149), and with average cortical thickness (r = -0.60, P = 0.0180). Furthermore, a hierarchical regression showed that PI was a strong predictor of bone stiffness which was independent of the other parameters. The findings from this study validate the MRI-derived porosity index as a useful measure of whole-bone mechanical integrity and stiffness.

Trajectory correction based on the gradient impulse response function improves high-resolution UTE imaging of the musculoskeletal system

PURPOSE

UTE sequences typically acquire data during the ramping up of the gradient fields, which makes UTE imaging prone to eddy current and system delay effects. The purpose of this work was to use a simple gradient impulse response function (GIRF) measurement to estimate the real readout gradient waveform and to demonstrate that precise knowledge of the gradient waveform is important in the context of high-resolution UTE musculoskeletal imaging.

METHODS

The GIRF was measured using the standard hardware of a 3 Tesla scanner and applied on 3D radial UTE data (TE: 0.14 ms). Experiments were performed on a phantom, in vivo on a healthy knee, and in vivo on patients with spine fractures. UTE images were reconstructed twice, first using the GIRF-corrected gradient waveforms and second using nominal-corrected waveforms, correcting for the low-pass filter characteristic of the gradient chain.

RESULTS

Images reconstructed with the nominal-corrected gradient waveforms exhibited blurring and showed edge artifacts. The blurring and the edge artifacts were reduced when the GIRF-corrected gradient waveforms were used, as shown in single-UTE phantom scans and in vivo dual-UTE gradient-echo scans in the knee. Further, the importance of the GIRF-based correction was indicated in UTE images of the lumbar spine, where thin bone structures disappeared when the nominal correction was employed.

CONCLUSION

The presented GIRF-based trajectory correction method using standard scanner hardware can improve the quality of high-resolution UTE musculoskeletal imaging.