Automated Quantification of Total Cerebral Blood Flow from Phase-Contrast MRI and Deep Learning.

Knowledge of input blood to the brain, which is represented as total cerebral blood flow (tCBF), is important in evaluating brain health. Phase-contrast (PC) magnetic resonance imaging (MRI) enables blood velocity mapping, allowing for noninvasive measurements of tCBF. In the procedure, manual selection of brain-feeding arteries is an essential step, but is time-consuming and often subjective. Thus, the purpose of this work was to develop and validate a deep learning (DL)-based technique for automated tCBF quantifications. To enhance the DL segmentation performance on arterial blood vessels, in the preprocessing step magnitude and phase images of PC MRI were multiplied several times. Thereafter, a U-Net was trained on 218 images for three-class segmentation. Network performance was evaluated in terms of the Dice coefficient and the intersection-over-union (IoU) on 40 test images, and additionally, on externally acquired 20 datasets. Finally, tCBF was calculated from the DL-predicted vessel segmentation maps, and its accuracy was statistically assessed with the correlation of determination (R2), the intraclass correlation coefficient (ICC), paired t-tests, and Bland-Altman analysis, in comparison to manually derived values. Overall, the DL segmentation network provided accurate labeling of arterial blood vessels for both internal (Dice=0.92, IoU=0.86) and external (Dice=0.90, IoU=0.82) tests. Furthermore, statistical analyses for tCBF estimates revealed good agreement between automated versus manual quantifications in both internal (R2=0.85, ICC=0.91, p=0.52) and external (R2=0.88, ICC=0.93, p=0.88) test groups. The results suggest feasibility of a simple and automated protocol for quantifying tCBF from neck PC MRI and deep learning.

Validation of a new 3D quantitative BOLD based cerebral oxygen extraction mapping.

Quantitative BOLD (qBOLD) MRI allows evaluation of oxidative metabolism of the brain based purely on an endogenous contrast mechanism. The method quantifies deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Yv), yielding oxygen extraction fraction (OEF), and along with a separate measurement of cerebral blood flow, cerebral metabolic rate of oxygen (CMRO2) maps. Here, we evaluated our recently reported 3D qBOLD method that rectifies a number of deficiencies in prior qBOLD approaches in terms of repeat reproducibility and sensitivity to hypercapnia on the metabolic parameters, and in comparison to dual-gas calibrated BOLD (cBOLD) MRI for determining resting-state oxygen metabolism. Results suggested no significant difference between test-retest qBOLD scans in either DBV and OEF. Exposure to hypercapnia yielded group averages of 38 and 28% for OEF and 151 and 146 µmol/min/100 g for CMRO2 in gray matter at baseline and hypercapnia, respectively. The decrease of OEF during hypercapnia was significant (p ≪ 0.01), whereas CMRO2 did not change significantly (p = 0.25). Finally, baseline OEF (37 vs. 39%) and CMRO2 (153 vs. 145 µmol/min/100 g) in gray matter using qBOLD and dual-gas cBOLD were found to be in good agreement with literature values, and were not significantly different from each other (p > 0.1).

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.

Quantification of whole-organ individual and bilateral renal metabolic rate of oxygen.

PURPOSE: Renal metabolic rate of oxygen (rMRO2 ) is a potentially important biomarker of kidney function. The key parameters for rMRO2 quantification include blood flow rate (BFR) and venous oxygen saturation (SvO2 ) in a draining vessel. Previous approaches to quantify renal metabolism have focused on the single organ. Here, both kidneys are considered as one unit to quantify bilateral rMRO2 . A pulse sequence to facilitate bilateral rMRO2 quantification is introduced. METHODS: To quantify bilateral rMRO2 , measurements of BFR and SvO2 are made along the inferior vena cava (IVC) at suprarenal and infrarenal locations. From the continuity equation, these four parameters can be related to derive an expression for bilateral rMRO2 . The recently reported K-MOTIVE pulse sequence was implemented at four locations: left kidney, right kidney, suprarenal IVC, and infrarenal IVC. A dual-band variant of K-MOTIVE (db-K-MOTIVE) was developed by incorporating simultaneous-multi-slice imaging principles. The sequence simultaneously measures BFR and SvO2 at suprarenal and infrarenal locations in a single pass of 21 s, yielding bilateral rMRO2 . RESULTS: SvO2 and BFR are higher in suprarenal versus infrarenal IVC, and the renal veins are highly oxygenated (SvO2 >90%). Bilateral rMRO2 quantified in 10 healthy subjects (8 M, 30 ± 8 y) was found to be 291 ± 247 and 349 ± 300 (µmolO2 /min)/100 g, derived from K-MOTIVE and db-K-MOTIVE, respectively. In comparison, total rMRO2 from combining left and right was 329 ± 273 (µmolO2 /min)/100 g. CONCLUSION: The present work demonstrates that bilateral rMRO2 quantification is feasible with fair reproducibility and physiological plausibility. The indirect method is a promising approach to compute bilateral rMRO2 when individual rMRO2 quantification is difficult.

Six-minute, in vivo MRI quantification of proximal femur trabecular bone 3D microstructure.

BACKGROUND: Assessment of proximal femur trabecular bone microstructure in vivo by magnetic resonance imaging has recently been validated for acquiring information independent of bone mineral density in osteoporotic patients. However, the requisite signal-to-noise ratio (SNR) and resolution for interrogation of the trabecular microstructure at this anatomical location prolongs the scan duration and renders the imaging protocol clinically infeasible. Parallel imaging and compressed sensing (PICS) techniques can reduce the scan duration of the imaging protocol without substantially compromising image quality. The present work investigates the limits of acceleration for a commonly used PICS technique, ℓ1-ESPIRiT, for the purpose of quantifying measures of trabecular bone microarchitecture. Based on a desired error tolerance, a six-minute, prospectively accelerated variant of the imaging protocol was developed and assessed for intersession reproducibility and agreement with the longer reference scan. PURPOSE: To investigate the limits of acceleration for MRI-based trabecular bone quantification by parallel imaging and compressed sensing reconstruction, and to develop a prototypical imaging protocol for assessing the proximal femur microstructure in a clinically practical scan time. METHODS: Healthy participants (n = 11) were scanned by a 3D balanced steady-state free precession (bSSFP) sequence satisfying the Nyquist criterion with a scan duration of about 18 min. The raw data were retrospectively undersampled and reconstructed to mimic various acceleration factors ranging from 2 to 6. Trabecular volumes-of-interest in four major femoral regions (greater trochanter, intertrochanteric region, femoral neck, and femoral head) were analyzed and six relevant measures of trabecular bone microarchitecture (bone volume fraction, surface-to-curve ratio, erosion index, elastic modulus, trabecular thickness, plates-to-rods ratio) were obtained for images of all accelerations. To assess agreement, median percent error and intraclass correlation coefficients (ICCs) were computed using the fully-sampled data as reference. Based on this analysis, a prospectively 3-fold accelerated sequence with a duration of about 6 min was developed and the analysis was repeated. RESULTS: A prospective acceleration factor of 3 demonstrated comparable performance in reproducibility and absolute agreement to the fully-sampled scan. The median CoV over all image-derived metrics was generally <6 % and ICCs >0.70. Also, measurements from prospectively 3-fold accelerated scans demonstrated in general median percent errors of <7 % and ICCs >0.70. CONCLUSION: The present work proposes a method to make in vivo quantitative assessment of proximal femur trabecular microstructure with a clinically practical scan duration of about 6 min.

Cerebral oxygen metabolism from MRI susceptibility.

This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.

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.

Superior sagittal sinus flow as a proxy for tracking global cerebral blood flow dynamics during wakefulness and sleep.

Sleep, a state of reduced consciousness, affects brain oxygen metabolism and lowers cerebral metabolic rate of oxygen (CMRO2). Previously, we quantified CMRO2 during sleep via Fick's Principle, with a single-band MRI sequence measuring both hemoglobin O2 saturation (SvO2) and superior sagittal sinus (SSS) blood flow, which was upscaled to obtain total cerebral blood flow (tCBF). The procedure involves a brief initial calibration scan to determine the upscaling factor (fc), assumed state-invariant. Here, we used a dual-band sequence to simultaneously provide SvO2 in SSS and tCBF in the neck every 16 seconds, allowing quantification of fc dynamically. Ten healthy subjects were scanned by MRI with simultaneous EEG for 80 minutes, yielding 300 temporal image frames per subject. Four volunteers achieved slow-wave sleep (SWS), as evidenced by increased δ-wave activity (per American Academy of Sleep Medicine criteria). SWS was maintained for 13.5 ± 7.0 minutes, with CMRO2 28.6 ± 5.5% lower than pre-sleep wakefulness. Importantly, there was negligible bias between tCBF obtained by upscaling SSS-blood flow, and tCBF measured directly in the inflowing arteries of the neck (intra-class correlation 0.95 ± 0.04, averaged across all subjects), showing that the single-band approach is a valid substitute for quantifying tCBF, simplifying image data collection and analysis without sacrificing accuracy.

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.

SNR-Enhanced, Rapid Electrical Conductivity Mapping Using Echo-Shifted MRI.

Magnetic resonance electrical impedance tomography (MREIT) permits high-spatial resolution electrical conductivity mapping of biological tissues, and its quantification accuracy hinges on the signal-to-noise ratio (SNR) of the current-induced magnetic flux density (Bz). The purpose of this work was to achieve Bz SNR-enhanced rapid conductivity imaging by developing an echo-shifted steady-state incoherent imaging-based MREIT technique. In the proposed pulse sequence, the free-induction-decay signal is shifted in time over multiple imaging slices, and as a result is exposed to a plurality of injecting current pulses before forming an echo. Thus, the proposed multi-slice echo-shifting strategy allows a high SNR for Bz for a given number of current injections. However, with increasing the time of echo formation, the Bz SNR will also be compromised by T2*-related signal loss. Hence, numerical simulations were performed to evaluate the relationship between the echo-shifting and the Bz SNR, and subsequently to determine the optimal imaging parameters. Experimental studies were conducted to evaluate the effectiveness of the proposed method over conventional spin-echo-based MREIT. Compared with the reference spin-echo MREIT, the proposed echo-shifting-based method improves the efficiency in both data acquisition and current injection while retaining the accuracy of conductivity quantification. The results suggest the feasibility of the proposed MREIT method as a practical means for conductivity mapping.

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 (Yv), 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 deoxyhemoglobin'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 Yv 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 (Yv, 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 Yv and 2.8 ± 0.5 % and 1.8 ± 0.4 % for DBV in cortical gray and white matter, respectively. Given the Yv 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.

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.

Cerebral metabolic rate of oxygen during transition from wakefulness to sleep measured with high temporal resolution OxFlow MRI with concurrent EEG.

During slow-wave sleep, synaptic transmissions are reduced with a concomitant reduction in brain energy consumption. We used 3 Tesla MRI to noninvasively quantify changes in the cerebral metabolic rate of O2 (CMRO2) during wakefulness and sleep, leveraging the 'OxFlow' method, which provides venous O2 saturation (SvO2) along with cerebral blood flow (CBF). Twelve healthy subjects (31.3 ± 5.6 years, eight males) underwent 45-60 min of continuous scanning during wakefulness and sleep, yielding one image set every 3.4 s. Concurrent electroencephalography (EEG) data were available in eight subjects. Mean values of the metabolic parameters measured during wakefulness were stable, with coefficients of variation below 7% (average values: CMRO2 = 118 ± 12 µmol O2/min/100 g, SvO2 = 67.0 ± 3.7% HbO2, CBF = 50.6 ±4.3 ml/min/100 g). During sleep, on average, CMRO2 decreased 21% (range: 14%-32%; average nadir = 98 ± 16 µmol O2/min/100 g), while EEG slow-wave activity, expressed in terms of δ-power, increased commensurately. Following sleep onset, CMRO2 was found to correlate negatively with relative δ-power (r = -0.6 to -0.8, P < 0.005), and positively with heart rate (r = 0.5 to 0.8, P < 0.0005). The data demonstrate that OxFlow MRI can noninvasively measure dynamic changes in cerebral metabolism associated with sleep, which should open new opportunities to study sleep physiology in health and disease.

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.

Alternating unbalanced SSFP for 3D R2' mapping of the human brain.

PURPOSE: Measuring the transverse-relaxation rate R2' provides valuable information in quantitative evaluation of tissue microstructure, for example, in terms of oxygenation levels. Here, we propose an alternating unbalanced SSFP pulse sequence for rapid whole-brain 3D R2' mapping. METHODS: Unlike currently practiced, spin echo-based R2' measurement techniques, the proposed method alternates between SSFP-FID and SSFP-ECHO modes for rapid 3D encoding of transverse relaxation rates expressed as R2 + R2' and R2-R2' . Z-shimming gradients embedded into multi-echo trains of each SSFP module are designed to achieve relative immunity to large-scale magnetic-field variations (ΔB0 ). Appropriate models for the temporal evolution of the two groups of SSFP signals were constructed with ΔB0 -induced modulations accounted for, leading to ΔB0 -corrected estimation of R2 , R2' , and R2∗ (= R2 + R2' ). Additionally, relative magnetic susceptibility (Δχ) maps were obtained by quantitative susceptibility mapping of the phase data. Numerical simulations were performed to optimize scan parameters, followed by in vivo studies at 3 T in 7 healthy subjects. Measured parameters were evaluated in six brain regions, and subjected to interparameter correlation analysis. RESULTS: The resultant maps of R2' and additionally derived R2 , R2∗ , and Δχ all demonstrated the expected contrast across brain territories (eg, deep brain structures versus cortex), with the measured values in good agreement with previous reports. Furthermore, regression analyses yielded strong linear relationships for the transverse relaxation parameters ( R2' , R2 , and R2∗ ) against Δχ. CONCLUSION: Results suggest feasibility of the proposed method as a practical and reliable means for measuring R2' , R2 , R2∗ , and Δχ across the entire brain.

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.

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.

Venous cerebral blood volume mapping in the whole brain using venous-spin-labeled 3D turbo spin echo.

PURPOSE: Venous cerebral blood volume (CBVv ) is a major contributor to BOLD contrast, and therefore is an important parameter for understanding the underlying mechanism. Here, we propose a velocity-selective venous spin labeling (VS-VSL)-prepared 3D turbo spin echo pulse sequence for whole-brain baseline CBVv mapping. METHODS: Unlike previous CBVv measurement techniques that exploit the interrelationship between BOLD signals and CBVv , in the proposed VS-VSL technique both arterial blood and cerebrospinal fluid (CSF) signals were suppressed before the VS pulse train for exclusive labeling of venous blood, while a single-slab 3D turbo spin echo readout was used because of its relative immunity to magnetic field variations. Furthermore, two approximations were made to the VS-VSL signal model for simplified derivation of CBVv . In vivo studies were performed at 3T field strength in 8 healthy subjects. The performance of the proposed VS-VSL method in baseline CBVv estimation was first evaluated in comparison to the existing, hyperoxia-based method. Then, data were also acquired using VS-VSL under hypercapnic and hyperoxic gas breathing challenges for further validation of the technique. RESULTS: The proposed technique yielded physiologically plausible baseline CBVv values, and when compared with the hyperoxia-based method, showed no statistical difference. Furthermore, data acquired using VS-VSL yielded average CBVv of 2.89%/1.78%, 3.71%/2.29%, and 2.88%/1.76% for baseline, hypercapnia, and hyperoxia, respectively, in gray/white matter regions. As expected, hyperoxia had negligible effect (P > .8), whereas hypercapnia demonstrated vasodilation (P << .01). CONCLUSION: Upon further validation of the quantification model, the method is expected to have merit for 3D CBVv measurements across the entire brain.

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.

Calibrated fMRI for dynamic mapping of CMRO2 responses using MR-based measurements of whole-brain venous oxygen saturation.

Functional MRI (fMRI) can identify active foci in response to stimuli through BOLD signal fluctuations, which represent a complex interplay between blood flow and cerebral metabolic rate of oxygen (CMRO2) changes. Calibrated fMRI can disentangle the underlying contributions, allowing quantification of the CMRO2 response. Here, whole-brain venous oxygen saturation (Yv) was computed alongside ASL-measured CBF and BOLD-weighted data to derive the calibration constant, M, using the proposed Yv-based calibration. Data were collected from 10 subjects at 3T with a three-part interleaved sequence comprising background-suppressed 3D-pCASL, 2D BOLD-weighted, and single-slice dual-echo GRE (to measure Yv via susceptometry-based oximetry) acquisitions while subjects breathed normocapnic/normoxic, hyperoxic, and hypercapnic gases, and during a motor task. M was computed via Yv-based calibration from both hypercapnia and hyperoxia stimulus data, and results were compared to conventional hypercapnia or hyperoxia calibration methods. Mean M in gray matter did not significantly differ between calibration methods, ranging from 8.5 ± 2.8% (conventional hyperoxia calibration) to 11.7 ± 4.5% (Yv-based calibration in response to hyperoxia), with hypercapnia-based M values between (p = 0.56). Relative CMRO2 changes from finger tapping were computed from each M map. CMRO2 increased by ∼20% in the motor cortex, and good agreement was observed between the conventional and proposed calibration methods.