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.

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone porosity and geometry have been extensively validated in preclinical studies and have recently been shown to detect impaired bone quality in vivo in patients with osteoporosis. However, these techniques rely on laborious image segmentation, which is clinically impractical. Additionally, UTE MRI porosity techniques typically require long scan times or external calibration samples and elaborate physics processing, which limit their translatability. To this end, the UTE MRI-derived Suppression Ratio has been proposed as a simple-to-calculate, reference-free biomarker of porosity which can be acquired in clinically feasible acquisition times. PURPOSE: To explore whether a deep learning method can automate cortical bone segmentation and the corresponding analysis of cortical bone imaging biomarkers, and to investigate the Suppression Ratio as a fast, simple, and reference-free biomarker of cortical bone porosity. METHODS: In this retrospective study, a deep learning 2D U-Net was trained to segment the tibial cortex from 48 individual image sets comprised of 46 slices each, corresponding to 2208 training slices. Network performance was validated through an external test dataset comprised of 28 scans from 3 groups: (1) 10 healthy, young participants, (2) 9 postmenopausal, non-osteoporotic women, and (3) 9 postmenopausal, osteoporotic women. The accuracy of automated porosity and geometry quantifications were assessed with the coefficient of determination and the intraclass correlation coefficient (ICC). Furthermore, automated MRI biomarkers were compared between groups and to dual energy X-ray absorptiometry (DXA)- and peripheral quantitative CT (pQCT)-derived BMD. Additionally, the Suppression Ratio was compared to UTE porosity techniques based on calibration samples. RESULTS: The deep learning model provided accurate labeling (Dice score 0.93, intersection-over-union 0.88) and similar results to manual segmentation in quantifying cortical porosity (R2 ≥ 0.97, ICC ≥ 0.98) and geometry (R2 ≥ 0.82, ICC ≥ 0.75) parameters in vivo. Furthermore, the Suppression Ratio was validated compared to established porosity protocols (R2 ≥ 0.78). Automated parameters detected age- and osteoporosis-related impairments in cortical bone porosity (P ≤ .002) and geometry (P values ranging from <0.001 to 0.08). Finally, automated porosity markers showed strong, inverse Pearson's correlations with BMD measured by pQCT (|R| ≥ 0.88) and DXA (|R| ≥ 0.76) in postmenopausal women, confirming that lower mineral density corresponds to greater porosity. CONCLUSION: This study demonstrated feasibility of a simple, automated, and ionizing-radiation-free protocol for quantifying cortical bone porosity and geometry in vivo from UTE MRI and deep learning.

MRI Quantification of Cortical Bone Porosity, Mineralization, and Morphologic Structure in Postmenopausal Osteoporosis.

Background Preclinical studies have suggested that solid-state MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are useful measures of bone health. Purpose To explore whether MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are affected in postmenopausal osteoporosis (OP) and to examine associations between MRI markers and bone mineral density (BMD) in postmenopausal women. Materials and Methods In this single-center study, postmenopausal women were prospectively recruited from January 2019 to October 2020 into two groups: participants with OP who had not undergone treatment, defined as having any dual-energy x-ray absorptiometry (DXA) T-score of -2.5 or less, and age-matched control participants without OP (hereafter, non-OP). Participants underwent MRI in the midtibia, along with DXA in the hip and spine, and peripheral quantitative CT in the midtibia. Specifically, MRI measures of cortical bone porosity (pore water and total water), osteoid density (bound water [BW]), morphologic structure (cortical bone thickness), and mineralization (phosphorous [P] density [31P] and 31P-to-BW concentration ratio) were quantified at 3.0 T. MRI measures were compared between OP and non-OP groups and correlations with BMD were assessed. Results Fifteen participants with OP (mean age, 63 years ± 5 [SD]) and 19 participants without OP (mean age, 65 years ± 6) were evaluated. The OP group had elevated pore water (11.6 mol/L vs 9.5 mol/L; P = .007) and total water densities (21.2 mol/L vs 19.7 mol/L; P = .03), and had lower cortical bone thickness (4.8 mm vs 5.6 mm; P < .001) and 31P density (6.4 mol/L vs 7.5 mol/L; P = .01) than the non-OP group, respectively, although there was no evidence of a difference in BW or 31P-to-BW concentration ratio. Pore and total water densities were inversely associated with DXA and peripheral quantitative CT BMD (P < .001), whereas cortical bone thickness and 31P density were positively associated with DXA and peripheral quantitative CT BMD (P = .01). BW, 31P density, and 31P-to-BW concentration ratio were positively associated with DXA (P < .05), but not with peripheral quantitative CT. Conclusion Solid-state MRI of cortical bone was able to help detect potential impairments in parameters reflecting porosity, morphologic structure, and mineralization in postmenopausal osteoporosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

Dynamic Contrast-Enhanced MRI in the Abdomen of Mice with High Temporal and Spatial Resolution Using Stack-of-Stars Sampling and KWIC Reconstruction.

Application of quantitative dynamic contrast-enhanced (DCE) MRI in mouse models of abdominal cancer is challenging due to the effects of RF inhomogeneity, image corruption from rapid respiratory motion and the need for high spatial and temporal resolutions. Here we demonstrate a DCE protocol optimized for such applications. The method consists of three acquisitions: (1) actual flip-angle B1 mapping, (2) variable flip-angle T1 mapping and (3) acquisition of the DCE series using a motion-robust radial strategy with k-space weighted image contrast (KWIC) reconstruction. All three acquisitions employ spoiled radial imaging with stack-of-stars sampling (SoS) and golden-angle increments between the views. This scheme is shown to minimize artifacts due to respiratory motion while simultaneously facilitating view-sharing image reconstruction for the dynamic series. The method is demonstrated in a genetically engineered mouse model of pancreatic ductal adenocarcinoma and yielded mean perfusion parameters of Ktrans = 0.23 ± 0.14 min-1 and ve = 0.31 ± 0.17 (n = 22) over a wide range of tumor sizes. The SoS-sampled DCE method is shown to produce artifact-free images with good SNR leading to robust estimation of DCE parameters.

DWI Metrics Differentiating Benign Intraductal Papillary Mucinous Neoplasms from Invasive Pancreatic Cancer: A Study in GEM Models.

KPC (KrasG12D:Trp53R172H:Pdx1-Cre) and CKS (KrasG12D:Smad4L/L:Ptf1a-Cre) mice are genetically engineered mouse (GEM) models that capture features of human pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasms (IPMN), respectively. We compared these autochthonous tumors using quantitative imaging metrics from diffusion-weighted MRI (DW-MRI) and dynamic contrast enhanced (DCE)-MRI in reference to quantitative histological metrics including cell density, fibrosis, and microvasculature density. Our results revealed distinct DW-MRI metrics between the KPC vs. CKS model (mimicking human PDAC vs. IPMN lesion): the apparent diffusion coefficient (ADC) of CKS tumors is significantly higher than that of KPC, with little overlap (mean ± SD 2.24±0.2 vs. 1.66±0.2, p<10−10) despite intratumor and intertumor variability. Kurtosis index (KI) is also distinctively separated in the two models. DW imaging metrics are consistent with growth pattern, cell density, and the cystic nature of the CKS tumors. Coregistration of ex vivo ADC maps with H&E-stained sections allowed for regional comparison and showed a correlation between local cell density and ADC value. In conclusion, studies in GEM models demonstrate the potential utility of diffusion-weighted MRI metrics for distinguishing pancreatic cancer from benign pancreatic cysts such as IPMN.

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.

Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation.

Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep learning-based image reconstruction methods typically apply weight-sharing convolutional neural networks (CNNs) to k-space data without taking into consideration the k-space data's spatial frequency properties, leading to ineffective learning of the image reconstruction models. Moreover, complementary information of spatially adjacent slices is often ignored in existing deep learning methods. To overcome such limitations, we have developed a deep learning algorithm, referred to as adaptive convolutional neural networks for k-space data interpolation (ACNN-k-Space), which adopts a residual Encoder-Decoder network architecture to interpolate the undersampled k-space data by integrating spatially contiguous slices as multi-channel input, along with k-space data from multiple coils if available. The network is enhanced by self-attention layers to adaptively focus on k-space data at different spatial frequencies and channels. We have evaluated our method on two public datasets and compared it with state-of-the-art existing methods. Ablation studies and experimental results demonstrate that our method effectively reconstructs images from undersampled k-space data and achieves significantly better image reconstruction performance than current state-of-the-art techniques. Source code of the method is available at https://gitlab.com/qgpmztmf/acnn-k-space.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer.

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm2/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10-3 mm2/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10-3 mm2/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Bone-Selective MRI as a Nonradiative Alternative to CT for Craniofacial Imaging.

RATIONAL AND OBJECTIVES: Computed tomography (CT) is the clinical gold-standard for high-resolution 3D visualization of cortical bone structures. However, ionizing radiation is of concern, particularly for pediatric patients. This study evaluates the feasibility of producing 3D human skull renderings using a novel bone-selective magnetic resonance imaging technique. MATERIALS AND METHODS: A dual-radiofrequency pulse, dual-echo, 3D ultrashort echo time sequence was applied for scanning of a cadaver skull and five healthy adult subjects. Scans were each completed within 6 minutes. Semiautomatic segmentation of bone voxels was performed using ITK-SNAP software, leading to 3D renderings of the skulls. For comparison, thin-slice head CT scans were performed. Mimics software was used to measure eight anatomic distances from 3D renderings. Lin's Concordance Correlation test was applied to assess agreement between measurements from MR-based and CT-based 3D skull renderings. RESULTS: The 3D rendered MR images depict most craniofacial features (e.g., zygomatic arch), although some voxels were erroneously included or excluded in the renderings. MR-based measurements differed from CT-based measurements by mean percent difference ranging from 2.3%-5.0%. Lin's Concordance Correlation Coefficients for MR-based vs CT-based measurements ranged from 0.998-1.000. CONCLUSION: The proposed dual-radiofrequency dual-echo 3D ultrashort echo time imaging technique produces high-resolution bone-specific images within a clinically feasible imaging time, leading to clear visualization of craniofacial skeletal structures. Concordance coefficients suggest good reliability of the method compared to CT. The method is currently limited by time and manual input necessary for segmentation correction. Further investigation is needed for more accurate 3D renderings and for scanning of pediatric patients.

Impact of gradient imperfections on bone water quantification with UTE MRI.

PURPOSE: The impact of gradient imperfections on UTE images and UTE image-derived bone water quantification was investigated at 3 T field strength. METHODS: The effects of simple gradient time delays and eddy currents on UTE images, as well as the effects of gradient error corrections, were studied with simulation and phantom experiments. The k-space trajectory was mapped with a 2D sequence with phase encoding on both spatial axes by measuring the phase of the signal in small time increments during ramp-up of the read gradient. In vivo 3D UTE images were reconstructed with and without gradient error compensation to determine the bias in bone water quantification. Finally, imaging was performed on 2 equally configured Siemens TIM Trio systems (Siemens Medical Solutions, Erlangen, Germany) to investigate the impact of such gradient imperfections on inter-scanner measurement bias. RESULTS: Compared to values derived from UTE images with full gradient error compensation, total bone water was found to deviate substantially with no (up to 17%) or partial (delay-only) compensation (up to 10.8%). Bound water, obtained with inversion recovery-prepared UTE, was somewhat less susceptible to gradient errors (up to 2.2% for both correction strategies). Inter-scanner comparison indicated a statistically significant bias between measurements from the 2 MR systems for both total and bound water, which either vanished or was substantially reduced following gradient error correction. CONCLUSION: Gradient imperfections impose spatially dependent artifacts on UTE images, which compromise not only bone water quantification accuracy but also inter-scanner measurement agreement if left uncompensated.

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

Ultrashort echo time (UTE) MRI is capable of detecting signals from protons with very short T2 relaxation times, and thus has potential for skull-selective imaging as a radiation-free alternative to computed tomography. However, relatively long scan times make the technique vulnerable to artifacts from involuntary subject motion. Here, we developed a self-navigated, three-dimensional (3D) UTE pulse sequence, which builds on dual-RF, dual-echo UTE imaging, and a retrospective motion correction scheme for motion-resistant skull MRI. Full echo signals in the second readout serve as a self-navigator that yields a time-course of center of mass, allowing for adaptive determination of motion states. Furthermore, golden-means based k-space trajectory was employed to achieve a quasi-uniform distribution of sampling views on a spherical k-space surface for any subset of the entire data collected, thereby allowing reconstruction of low-resolution images pertaining to each motion state for subsequent estimation of rigid-motion parameters. Finally, the extracted trajectory of the head was used to make the whole k-space datasets motion-consistent, leading to motion-corrected, high-resolution images. Additionally, we posit that hardware-related k-space trajectory errors, if uncorrected, result in obscured bone contrast. Thus, a calibration scan was performed once to measure k-space encoding locations, subsequently used during image reconstruction of actual imaging data. In vivo studies were performed to evaluate the effectiveness of the proposed correction schemes in combination with approaches to accelerated bone-selective imaging. Results illustrating effective removal of motion artifacts and clear depiction of skull bone voxels suggest that the proposed method is robust to intermittent head motions during scanning.

Rapid dual-RF, dual-echo, 3D ultrashort echo time craniofacial imaging: A feasibility study.

PURPOSE: To develop a dual-radiofrequency (RF), dual-echo, 3D ultrashort echo-time (UTE) pulse sequence and bone-selective image reconstruction for rapid high-resolution craniofacial MRI. METHODS: The proposed pulse sequence builds on recently introduced dual-RF UTE imaging. While yielding enhanced bone specificity by exploiting high sensitivity of short T2 signals to variable RF pulse widths, the parent technique exacts a 2-fold scan time penalty relative to standard dual-echo UTE. In the proposed method, the parent sequence's dual-RF scheme was incorporated into dual-echo acquisitions while radial view angles are varied every pulse-to-pulse repetition period. The resulting 4 echoes (2 for each RF) were combined by view-sharing to construct 2 sets of k-space data sets, corresponding to short and long TEs, respectively, leading to a 2-fold increase in imaging efficiency. Furthermore, by exploiting the sparsity of bone signals in echo-difference images, acceleration was achieved by solving a bone-sparsity constrained image reconstruction problem. In vivo studies were performed to evaluate the effectiveness of the proposed acceleration approaches in comparison to the parent method. RESULTS: The proposed technique achieves 1.1-mm isotropic skull imaging in 3 minutes without visual loss of image quality, compared to the parent technique (scan time = 12 minutes). Bone-specific images and corresponding 3D renderings of the skull were found to depict the expected craniofacial anatomy over the entire head. CONCLUSION: The proposed method is able to achieve high-resolution volumetric craniofacial images in a clinically practical imaging time, and thus may prove useful as a potential alternative to computed tomography.

In vivo bone 31 P relaxation times and their implications on mineral quantification.

PURPOSE: The intersubject variations in bone phosphorus-31 (31 P) T1 and T 2 * , as well as the implications on in vivo 31 P MRI-based bone mineral quantification, were investigated at 3T field strength. METHODS: A technique that isolates the bone signal from the composite in vivo 31 P spectrum was first evaluated via simulation and experiments ex vivo and subsequently applied to measure the T1 of bone 31 P collectively with a spectroscopic saturation recovery sequence in a group of healthy subjects aged 26 to 76 years. T 2 * was derived from the bone signal linewidth. The density of bone 31 P was derived for all subjects from 31 P zero TE images acquired in the same scan session using the measured relaxation times. Test-retest experiments were also performed to evaluate repeatability of this in vivo MRI-based bone mineral quantification protocol. RESULTS: The T1 obtained in vivo using the proposed spectral separation method combined with saturation recovery sequence is 38.4 ± 1.5 s for the subjects studied. Average 31 P density found was 6.40 ± 0.58 mol/L (corresponding to 1072 ± 98 mg/cm3 mineral density), in good agreement with an earlier study in specimens from donors of similar age range. Neither the relaxation times (P = 0.18 for T1 , P = 0.99 for T 2 * ) nor 31 P density (P = 0.55) were found to correlate with subject age. Average coefficients of variation for the repeat study were 1.5%, 2.6%, and 4.4% for bone 31 P T1 , T 2 * , and density, respectively. CONCLUSION: Neither 31 P T1 nor T 2 * varies significantly in healthy adults across a 50-year age range, therefore obviating the need for subject-specific measurements.

Correction: Feasibility of assessing bone matrix and mineral properties in vivo by combined solid-state 1H and 31P MRI.

[This corrects the article DOI: 10.1371/journal.pone.0173995.].

Accelerated noncontrast-enhanced 4-dimensional intracranial MR angiography using golden-angle stack-of-stars trajectory and compressed sensing with magnitude subtraction.

PURPOSE: To evaluate the feasibility and performance of compressed sensing (CS) with magnitude subtraction regularization in accelerating non-contrast-enhanced dynamic intracranial MR angiography (NCE-dMRA). METHODS: A CS algorithm was introduced in NCE-dMRA by exploiting the sparsity of the magnitude difference of the control and label images. The NCE-dMRA data were acquired using golden-angle stack-of-stars trajectory on six healthy volunteers and one patient with arteriovenous fistula. Images were reconstructed using (i) the proposed magnitude-subtraction CS (MS-CS); (ii) complex-subtraction CS; (iii) independent CS; and (iv) view-sharing with k-space weighted image contrast (KWIC). The dMRA image quality was compared across the four reconstruction strategies. The proposed MS-CS method was further compared with KWIC for temporal fidelity of depicting dynamic flow. RESULTS: The proposed MS-CS method was able to reconstruct NCE-dMRA images with detailed vascular structures and clean background. It provided better subjective image quality than the other two CS strategies (P < 0.05). Compared with KWIC, MS-CS showed similar image quality, but reduced temporal blurring in delineating the fine distal arteries. CONCLUSIONS: The MS-CS method is a promising CS technique for accelerating NCE-dMRA acquisition without compromising image quality and temporal fidelity. Magn Reson Med 79:867-878, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

High-speed whole-brain oximetry by golden-angle radial MRI.

PURPOSE: To determine whole-brain cerebral metabolic rate of oxygen (CMRO2 ), an improved imaging approach, based on radial encoding, termed radial OxFlow (rOxFlow), was developed to simultaneously quantify draining vein venous oxygen saturation (SvO2 ) and total cerebral blood flow (tCBF). METHODS: To evaluate the efficiency and precision of the rOxFlow sequence, 10 subjects were studied during a paradigm of repeated breath-holds with both rOxFlow and Cartesian OxFlow (cOxFlow) sequences. CMRO2 was calculated at baseline from OxFlow-measured data assuming an arterial O2 saturation of 97%, and the SvO2 and tCBF breath-hold responses were quantified. RESULTS: Average neurometabolic-vascular parameters across the 10 subjects for cOxFlow and rOxFlow were, respectively: SvO2 (%) baseline: 64.6 ± 8.0 versus 64.2 ± 6.6; SvO2 peak: 70.5 ± 8.5 versus 72.6 ± 5.4; tCBF (mL/min/100 g) baseline: 39.2 ± 3.8 versus 40.6 ± 8.0; tCBF peak: 53.2 ± 5.1 versus 56.1 ± 11.7; CMRO2 (µmol O2 /min/100 g) baseline: 111.5 ± 26.8 versus 120.1 ± 19.6. The above measures were not significantly different between sequences (P > 0.05). CONCLUSION: There was good agreement between the two methods in terms of the physiological responses measured. Comparing the two, rOxFlow provided higher temporal resolution and greater flexibility for reconstruction while maintaining high SNR. Magn Reson Med 79:217-223, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Noncontrast-enhanced time-resolved 4D dynamic intracranial MR angiography at 7T: A feasibility study.

BACKGROUND: Arterial spin labeling (ASL) based-noncontrast-enhanced 4D MR angiography (NCE 4D MRA) shows potential in characterizing cerebrovascular hemodynamics in cerebrovascular disorders. Ultrahigh-field theoretically benefits ASL signal with increased inherent signal-to-noise ratio (SNR) and prolonged blood T1 , which may provide improved delineation of vasculature in 4D MRA. PURPOSE: To investigate the feasibility of NCE 4D MRA using 3D Cartesian trajectory and stack-of-stars (SOS) golden angle radial trajectory at 7T. STUDY TYPE: A prospective study. SUBJECTS: Six normal volunteers and eight patients with arteriovenous malformation (AVM). FIELD STRENGTH/SEQUENCE: NCE 4D MRA with Cartesian and radial trajectories were performed at 3T and 7T. ASSESSMENT: Subjective image quality of 4D MRA was evaluated using a 4-point scale by two experienced neuroradiologists. The characterization of AVM components with 4D MRA and DSA was also graded using the Spetzler-Martin grading scale. STATISTICAL TESTS: Cohen's kappa coefficient was calculated to evaluate the agreement between two readers within each 4D MRA technique (Cartesian and Radial). A Wilcoxon signed-rank test was performed to compare the subjective image quality scores of 4D MRA between Cartesian and radial trajectories, and between 7T and 3T, respectively. RESULTS: Good-to-excellent image quality was achieved in 4D MRA with both Cartesian (3.83 ± 0.41) and radial (3.42 ± 0.49) acquisitions in healthy volunteers at 7T. However, markedly reduced scan time was needed with radial acquisition. 4D MRA at 7T (3.31 ± 0.59) shows better delineation of AVM lesion features, especially the vein drainage, compared with that of 3T (2.83 ± 0.75), although no statistical significance was achieved (P = 0.180). DATA CONCLUSION: The feasibility of ASL based 4D MRA at 7T with Cartesian and SOS golden angle radial acquisition was demonstrated. The clinical evaluation of 4D MRA in AVMs between 3T and 7T suggested 7T 4D MRA images acquired with radial acquisition demonstrate excellent delineation of AVM features, especially the draining veins. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2017.

Feasibility of assessing bone matrix and mineral properties in vivo by combined solid-state 1H and 31P MRI.

PURPOSE: To develop and evaluate an integrated imaging protocol for bone water and phosphorus quantification in vivo by solid-state 1H and 31P MRI. MATERIALS AND METHODS: All studies were HIPAA-compliant and were performed with institutional review board approval and written informed consent. Proton (1H) ultra-short echo-time (UTE) and phosphorus (31P) zero echo-time (ZTE) sequences were designed and implemented on a 3 T clinical MR scanner to quantify bone water and mineral in vivo. The left tibia of ten healthy subjects (including both genders, 49±15 y/o) was examined with a custom-built 1H/31P dual-frequency extremity RF coil. Total bone water (TW), water bound to the collagen matrix (BW) and bone 31P were quantified from MR images with respect to reference samples of known 1H or 31P concentration, and pore water (PW) was subsequently determined from TW and BW. Porosity index (PI) was calculated as the ratio between UTE images acquired at two echo times. MRI parameters were compared with bone density measures obtained by high-resolution peripheral quantitative CT (HR-pQCT). RESULTS: The total scan time for the bone water and 31P quantification protocol was about 50 minutes. Average TW, BW, PW and 31P concentrations were 13.99±1.26, 10.39±0.80, 3.34±1.41 mol/L and 7.06±1.53 mol/L for the studied cohort, respectively, in good agreement with previous results conducted ex vivo. Average intra-subject coefficients of variation were 3.47%, 2.60% and 7.50% for TW, BW and PW and 5.60% for 31P. Negative correlations were observed between PW and vBMD (p<0.05) as well as between PI and 31P (p<0.05), while bone mineral content (BMC) estimated from 31P MRI and HR-pQCT were strongly positively correlated (p<0.0001). CONCLUSION: This work demonstrates the feasibility of quantifying bone water and mineral phosphorus in human subjects in a single MRI session with a clinically practical imaging protocol.

Effects of flip angle uncertainty and noise on the accuracy of DCE-MRI metrics: comparison between standard concentration-based and signal difference methods.

Dynamic contrast-enhanced MRI is becoming an increasingly important tool to assess tumors and their response to treatment. In the most common method of computing tumor perfusion parameters, the concentration of the injected contrast agent is first computed in both tumor and blood which is subsequently fit to a perfusion model, typically the Tofts two compartment model. However, this strategy can be highly sensitive to errors in the excitation flip angle and noise. More recently, a simpler method of determining perfusion was developed in which the difference signal, obtained by subtracting the measured time course signal by the signal prior to bolus arrival, is utilized in lieu of the concentration values. The goal of this work is to compare the performance of these two strategies with simulation experiments in the presence of flip angle errors and different levels of image signal to noise ratios (SNRs). Results show that with the conventional method, if assumed pre-contrast T1 of blood is used, large errors in perfusion (exceeding 400% and 200% for K(trans) and ve, respectively) can occur in the presence of flip angle deviations typically observed in vivo. However, when baseline T1 values are measured for both tumor and blood, the errors become a function of flip angle difference between the two locations, with nearly no error if the flip angle errors are identical at both locations. The errors are substantially smaller with the signal difference strategy (less than 100% for both K(trans) and ve). The latter method also yields more consistent perfusion values at varying SNR levels. The results suggest that measuring the actual flip angle may be critical for obtaining absolute perfusion values, but in studies in which relative changes in perfusion is of primary interest or if true flip angles are not known, the signal difference strategy may be preferred over the standard concentration-based method.

Registration-based autofocusing technique for automatic correction of motion artifacts in time-series studies of high-resolution bone MRI.

PURPOSE: To develop a registration-based autofocusing (RAF) motion correction technique for high-resolution trabecular bone (TB) imaging and to evaluate its performance on in vivo MR data. MATERIALS AND METHODS: The technique combines serial registration with a previously developed motion correction technique - autofocusing - for automatic correction of subject movement degradation of MR images acquired in longitudinal studies. The method was tested on in vivo images of the distal radius to measure improvements in serial reproducibility of parameters in 12 women (ages 50-75 years), and to compare with the navigator echo-based correction and autofocusing. Furthermore, the technique's ability to optimize the sensitivity to detect simulated bone loss was ascertained. RESULTS: The new technique yielded superior reproducibility of image-derived structural and mechanical parameters. Average coefficient of variation across all parameters improved by 12.5%, 27.0%, 33.5%, and 37.0%, respectively, following correction by navigator echoes, autofocusing, and the RAF technique (without and with correction for rotational motion); average intra-class correlation coefficient increased by 1.2%, 2.2%, 2.8%, and 3.2%, respectively. Furthermore, simulated bone loss (5%) was well recovered independent of the choice of reference image (4.71% or 4.86% with respect to using either the original or the image subjected to bone loss) in the time series. CONCLUSION: The data suggest that our technique simultaneously corrects for intra-scan motion corruption while improving inter-scan registration. Furthermore, the technique is not biased by small changes in bone architecture between time-points.