A multi-imaging modality study of bone density, bone structure and the muscle - bone unit in end-stage renal disease.

End stage renal disease (ESRD) is associated with sarcopenia and skeletal fragility. The objectives of this cross-sectional study were to (1) characterize body composition, bone mineral density (BMD) and bone structure in hemodialysis patients compared with controls, (2) assess whether DXA areal BMD (aBMD) correlates with peripheral quantitative CT (pQCT) measures of volumetric BMD (vBMD), cortical dimensions and MRI measures of trabecular microarchitecture, and (3) determine the magnitude of bone deficits in ESRD after adjustment for muscle mass. Thirty ESRD participants, ages 25 to 64 years, were compared with 403 controls for DXA and pQCT outcomes and 104 controls for MRI outcomes; results were expressed as race- and sex- specific Z-scores relative to age. DXA appendicular lean mass index (ALMI kg/m2) and total hip, femoral neck, ultradistal and 1/3rd radius aBMD were significantly lower in ESRD, vs. controls (all p < 0.01). pQCT trabecular vBMD (p < 0.01), cortical vBMD (p < 0.001) and cortical thickness (due to a greater endosteal circumference, p < 0.02) and MRI measures of trabecular number, trabecular thickness, and whole bone stiffness were lower (all p < 0.01) in ESRD, vs. controls. ALMI was positively associated with total hip, femoral neck, ultradistal radius and 1/3rd radius aBMD and with tibia cortical thickness (R = 0.46 to 0.64). Adjustment for ALMI significantly attenuated bone deficits at these sites: e.g. mean femoral neck aBMD was 0.79 SD lower in ESRD, compared with controls and this was attenuated to 0.33 with adjustment for ALMI. In multivariate models within the dialysis participants, pQCT trabecular vBMD and cortical area Z-scores were significant and independently (all p < 0.02) associated with DXA femoral neck, total hip, and ultradistal radius aBMD Z-scores. Cortical vBMD (p = 0.01) and cortical area (p < 0.001) Z-scores were significantly and independently associated with 1/3rd radius areal aBMD Z-scores (R2 = 0.62). These data demonstrate that DXA aBMD captures deficits in trabecular and cortical vBMD and cortical area. The strong associations with ALMI, as an index of skeletal muscle, highlight the importance of considering the role of sarcopenia in skeletal fragility in patients with ESRD.

High-Density, Long-Lasting, and Multi-region Electrophysiological Recordings Using Polymer Electrode Arrays.

The brain is a massive neuronal network, organized into anatomically distributed sub-circuits, with functionally relevant activity occurring at timescales ranging from milliseconds to years. Current methods to monitor neural activity, however, lack the necessary conjunction of anatomical spatial coverage, temporal resolution, and long-term stability to measure this distributed activity. Here we introduce a large-scale, multi-site, extracellular recording platform that integrates polymer electrodes with a modular stacking headstage design supporting up to 1,024 recording channels in freely behaving rats. This system can support months-long recordings from hundreds of well-isolated units across multiple brain regions. Moreover, these recordings are stable enough to track large numbers of single units for over a week. This platform enables large-scale electrophysiological interrogation of the fast dynamics and long-timescale evolution of anatomically distributed circuits, and thereby provides a new tool for understanding brain activity.

A Fully Automated Approach to Spike Sorting.

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible.

Selective in vivo bone imaging with long-T2 suppressed PETRA MRI.

PURPOSE: To design and evaluate an optimized PETRA (point-wise encoding time reduction with radial acquisition) sequence with long-T2 suppression at 3 Tesla. METHODS: An adiabatic inversion recovery-based scheme was used to null the long-T2 signal. To minimize scan time, the signal was sampled multiple times after each inversion with variable excitation flip angles designed to yield constant short-T2 signal amplitude. The excitation pulses were phase-modulated, allowing for increased flip angle and higher signal-to-noise ratio (SNR). A fast, noniterative image reconstruction algorithm was designed to minimize image artifacts due to nonuniform excitation profile. RESULTS: Phase-modulated pulse excitation, along with the noniterative reconstruction algorithm, allows the use of larger radiofrequency pulse flip angles, resulting in effective suppression of long-T2 protons and improved image SNR without causing image artifacts. Midtibia images representative of collagen-bound water yielded SNR of 15 at 1-mm isotropic resolution in 6.5 minutes with a standard extremity coil. Further, the technology is shown to be suited for generating multi-angle projection images of bone akin to X-ray images displaying subtle anatomic detail. CONCLUSION: Optimized long-T2 suppressed PETRA allows imaging of bone matrix water unencumbered by long-T2 soft tissue and pore water protons, opening up new possibilities for anatomic bone imaging at isotropic resolution and quantification in clinically practical scan times. Magn Reson Med 77:989-997, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Validation of neural spike sorting algorithms without ground-truth information.

BACKGROUND: The throughput of electrophysiological recording is growing rapidly, allowing thousands of simultaneous channels, and there is a growing variety of spike sorting algorithms designed to extract neural firing events from such data. This creates an urgent need for standardized, automatic evaluation of the quality of neural units output by such algorithms. NEW METHOD: We introduce a suite of validation metrics that assess the credibility of a given automatic spike sorting algorithm applied to a given dataset. By rerunning the spike sorter two or more times, the metrics measure stability under various perturbations consistent with variations in the data itself, making no assumptions about the internal workings of the algorithm, and minimal assumptions about the noise. RESULTS: We illustrate the new metrics on standard sorting algorithms applied to both in vivo and ex vivo recordings, including a time series with overlapping spikes. We compare the metrics to existing quality measures, and to ground-truth accuracy in simulated time series. We provide a software implementation. COMPARISON WITH EXISTING METHODS: Metrics have until now relied on ground-truth, simulated data, internal algorithm variables (e.g. cluster separation), or refractory violations. By contrast, by standardizing the interface, our metrics assess the reliability of any automatic algorithm without reference to internal variables (e.g. feature space) or physiological criteria. CONCLUSIONS: Stability is a prerequisite for reproducibility of results. Such metrics could reduce the significant human labor currently spent on validation, and should form an essential part of large-scale automated spike sorting and systematic benchmarking of algorithms.

Pulse sequence programming in a dynamic visual environment: SequenceTree.

PURPOSE: To describe SequenceTree, an open source, integrated software environment for implementing MRI pulse sequences and, ideally, exporting them to actual MRI scanners. The software is a user-friendly alternative to vendor-supplied pulse sequence design and editing tools and is suited for programmers and nonprogrammers alike. METHODS: The integrated user interface was programmed using the Qt4/C++ toolkit. As parameters and code are modified, the pulse sequence diagram is automatically updated within the user interface. Several aspects of pulse programming are handled automatically, allowing users to focus on higher-level aspects of sequence design. Sequences can be simulated using a built-in Bloch equation solver and then exported for use on a Siemens MRI scanner. Ideally, other types of scanners will be supported in the future. RESULTS: SequenceTree has been used for 8 years in our laboratory and elsewhere and has contributed to more than 50 peer-reviewed publications in areas such as cardiovascular imaging, solid state and nonproton NMR, MR elastography, and high-resolution structural imaging. CONCLUSION: SequenceTree is an innovative, open source, visual pulse sequence environment for MRI combining simplicity with flexibility and is ideal both for advanced users and users with limited programming experience.

Method for rapid MRI quantification of global cerebral metabolic rate of oxygen.

A recently reported quantitative magnetic resonance imaging (MRI) method denoted OxFlow has been shown to be able to quantify whole-brain cerebral metabolic rate of oxygen (CMRO2) by simultaneously measuring oxygen saturation (SvO2) in the superior sagittal sinus and cerebral blood flow (CBF) in the arteries feeding the brain in 30 seconds, which is adequate for measurement at baseline but not necessarily in response to neuronal activation. Here, we present an accelerated version of the method (referred to as F-OxFlow) that quantifies CMRO2 in 8 seconds scan time under full retention of the parent method's capabilities and compared it with its predecessor at baseline in 10 healthy subjects. Results indicate excellent agreement between both sequences, with mean bias of 2.2% (P=0.18, two-tailed t-test), 3.4% (P=0.08, two-tailed t-test), and 2.0% (P=0.56, two-tailed t-test) for SvO2, CBF, and CMRO2, respectively. F-OxFlow's potential to monitor dynamic changes in SvO2, CBF, and CMRO2 is illustrated in a paradigm of volitional apnea applied to five of the study subjects. The sequence captured an average increase in SvO2, CBF, and CMRO2 of 10.1±2.5%, 43.2±9.2%, and 7.1±2.2%, respectively, in good agreement with literature values. The method may therefore be suited for monitoring alterations in CBF and SvO2 in response to neurovascular stimuli.

Effects of age and smoking on endothelial function assessed by quantitative cardiovascular magnetic resonance in the peripheral and central vasculature.

BACKGROUND: Both age and smoking promote endothelial dysfunction and impair vascular reactivity. Here, we tested this hypothesis by quantifying new cardiovascular magnetic resonance (CMR)-based biomarkers in smokers and nonsmokers. METHODS: Study population: young non-smokers (YNS: N = 45, mean age = 30.2 ± 0.7 years), young smokers (YS: N = 39 mean age 32.1 ± 0.7 years), older non-smokers (ONS: N = 45, mean age = 57.8 ± 0.6 years), and older smokers (OS: N = 40, mean age = 56.3 ± 0.6 years), all without overt cardiovascular disease. Vascular reactivity was evaluated following cuff-induced hyperemia via time-resolved blood flow velocity and oxygenation (SvO2) in the femoral artery and vein, respectively. SvO2 dynamics yielded washout time (time to minimum SvO2), resaturation rate (upslope) and maximum change from baseline (overshoot). Arterial parameters included pulse ratio (PR), hyperemic index (HI) and duration of hyperemia (TFF). Pulse-wave velocity (PWV) was assessed in aortic arch, thoracoabdominal aorta and iliofemoral arteries. Ultrasound-based carotid intimal-medial thickness (IMT) and brachial flow-mediated dilation were measured for comparison. RESULTS: Age and smoking status were independent for all parameters. Smokers had reduced upslope (-28.4%, P < 0.001), increased washout time (+15.3%, P < 0.01), and reduced HI (-19.5%, P < 0.01). Among non-smokers, older subjects had lower upslope (-22.7%, P < 0.01) and overshoot (-29.4%, P < 0.01), elevated baseline pulse ratio (+14.9%, P < 0.01), central and peripheral PWV (all P < 0.05). Relative to YNS, YS had lower upslope (-23.6%, P < 0.01) and longer washout time (13.5%, P < 0.05). Relative to ONS, OS had lower upslope (-33.0%, P < 0.01). IMT was greater in ONS than in YNS (+45.6%, P < 0.001), and also in YS compared to YNS (+14.7%, P < 0.05). CONCLUSIONS: Results suggest CMR biomarkers of endothelial function to be sensitive to age and smoking independent of each other.

Rapid T2- and susceptometry-based CMRO2 quantification with interleaved TRUST (iTRUST).

Susceptometry-based oximetry (SBO) and T2-relaxation-under-spin-tagging (TRUST) are two promising methods for quantifying the cerebral metabolic rate of oxygen (CMRO2), a critical parameter of brain function. We present a combined method, interleaved TRUST (iTRUST), which achieves rapid, simultaneous quantification of both susceptometry- and T2-based CMRO2 via insertion of a flow-encoded, dual-echo gradient-recalled echo (OxFlow) module within the T1 recovery portion of the TRUST sequence. In addition to allowing direct comparison between SBO- and TRUST-derived venous oxygen saturation (Yv) values, iTRUST substantially improves TRUST temporal resolution for CMRO2 quantification and obviates the need for a separate blood flow measurement following TRUST acquisition. iTRUST was compared directly to TRUST and OxFlow alone in three resting subjects at baseline, exhibiting close agreement with the separate techniques and comparable precision. These baseline data as well as simulation results support the use of two instead of the traditional four T2 preparation times for T2 fitting, allowing simultaneous quantification of susceptometry- and T2-based Yv (and CMRO2) with three- and six-second temporal resolution, respectively. In 10 young healthy subjects, iTRUST was applied during a 5% CO2 gas mixture-breathing paradigm. T2-based Yv values were lower at baseline relative to susceptometry (62.3 ± 3.1 vs. 66.7 ± 5.1 %HbO2, P<0.05), but increased more in response to hypercapnia. As a result, T2-based CMRO2 decreased from 140.4 ± 9.7 to 120.0 ± 9.5 µMol/100g/min, a significant -14.6 ± 3.6% response (P < 0.0001), whereas susceptometry-based CMRO2 changed insignificantly from 123.4 ± 18.7 to 127.9 ± 25.7, a 3.3 ± 9.7% response (P = 0.31). These differing results are in accord with previous studies applying the parent OxFlow or TRUST sequences individually, thus supporting the reliability of iTRUST but also strongly suggesting that a systematic bias exists between the susceptometry- and T2-based Yv quantification techniques.

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.

Comparison of MRI methods for measuring whole-brain venous oxygen saturation.

PURPOSE: In this work, we compare susceptometry-based oximetry (SBO) and two T2 -based methods for estimating resting baseline SvO2 in the superior sagittal sinus (SSS). METHODS: SBO is a field-mapping technique whereas in T2 -based methods the intravascular blood signal is isolated either with velocity-encoded projections [projection-based T2 (PT2 )] or a tag-control scheme [T2 -relaxation under spin tagging (TRUST)] after T2 -preparation. The measurements were performed on twelve healthy subjects (mean age = 33 ± 6 years) at 3 Tesla field strength. The reliability, precision, and reproducibility were examined for the three techniques. RESULTS: The mean (± standard deviation) SvO2 quantified by SBO, PT2 , and TRUST were found to be 65.9 ± 3.3, 65.6 ± 3.5, and 63.2 ± 4.1%. The standard deviation (SD) for 10 consecutive measurements in the quantified SvO2 was less than 2.7%, 4.7%, and 5.0% for SBO, PT2 , and TRUST across all subjects. In testing reproducibility across different days, the resulting SDs were 2.6, 3.5, and 2.0% for SBO, PT2 , and TRUST. CONCLUSION: The results indicate that all three SvO2 quantification techniques to be reliable with good agreement between PT2 and SBO while TRUST yielded slightly lower values compared with the other two techniques.

Correction of excitation profile in Zero Echo Time (ZTE) imaging using quadratic phase-modulated RF pulse excitation and iterative reconstruction.

Zero-echo Time (ZTE) imaging is a promising technique for magnetic resonance imaging (MRI) of short-T2 tissue nuclei in tissues. A problem inherent to the method currently hindering its translation to the clinic is the presence of a spatial encoding gradient during excitation, which causes the hard pulse to become spatially selective, resulting in blurring and shadow artifacts in the image. While shortening radio-frequency (RF) pulse duration alleviates this problem the resulting elevated RF peak power and specific absorption rate (SAR) in practice impede such a solution. In this work, an approach is described to correct the artifacts by applying quadratic phase-modulated RF excitation and iteratively solving an inverse problem formulated from the signal model of ZTE imaging. A simple pulse sequence is also developed to measure the excitation profile of the RF pulse. Results from simulations, phantom and in vivo studies, demonstrate the effectiveness of the method in correcting image artifacts caused by inhomogeneous excitation. The proposed method may contribute toward establishing ZTE MRI as a routine 3D pulse sequence for imaging protons and other nuclei with quasi solid-state behavior on clinical scanners.

The shear modulus of the nucleus pulposus measured using magnetic resonance elastography: a potential biomarker for intervertebral disc degeneration.

PURPOSE: This study aims to: (1) measure the shear modulus of nucleus pulposus (NP) in intact human vertebra-disc-vertebra segments using a magnetic resonance elastography setup for a 7T whole-body scanner, (2) quantify the effect of disc degeneration on the NP shear modulus measured using magnetic resonance elastography, and (3) compare the NP shear modulus to other magnetic resonance-based biomarkers of dis degeneration. METHODS: Thirty intact human disc segments were classified as normal, mild, or severely degenerated. The NP shear modulus was measured using a custom-made setup that included a novel inverse method less sensitive to noisy displacements. T2 relaxation time was measured at 7T. The accuracy of these parameters to classify different degrees of degeneration was evaluated using receiver operating characteristic curves. RESULTS: The magnetic resonance elastography measure of shear modulus in the NP was able to differentiate between normal, mild degeneration, and severe degeneration. The T2 relaxation time was able to differentiate between normal and mild degeneration, but it could not distinguish between mild and severe degeneration. CONCLUSIONS: This study shows that the NP shear modulus measured using magnetic resonance elastography is sensitive to disc degeneration and has the potential of being used as a clinical tool to quantify the mechanical integrity of the intervertebral disc.

Task-correlated facial and head movements in classifier-based real-time FMRI.

BACKGROUND: Real-time fMRI is especially vulnerable to task-correlated movement artifacts because statistical methods normally available in conventional analyses to remove such signals cannot be used in the context of real-time fMRI. Multi-voxel classifier-based methods, although advantageous in many respects, are particularly sensitive. Here we systematically studied various movements of the head and face to determine to what extent these can "masquerade" as signal in multi-voxel classifiers. METHODS: Ten subjects were instructed to move systematically (twelve instructed movements) throughout fMRI exams and data from a previously published real-time study was also analyzed to determine the extent to which non-neural signals contributed to the high reported accuracy in classifier output. RESULTS: Of potential concern, whole-brain classifiers based solely on movements exhibited false positives in all cases (P < .05). Artifacts were also observed in the spatial activation maps for two of the twelve movement tasks. In the retrospective analysis, it was determined that the relatively high reported classification accuracies were (fortunately) mostly explainable by neural activity, but that in some cases performance was likely dominated by movements. CONCLUSION: Movement tasks of many types (including movements of the eyes, face, and body) can lead to false positives in classifier-based real-time fMRI paradigms.

Assessment of trabecular bone yield and post-yield behavior from high-resolution MRI-based nonlinear finite element analysis at the distal radius of premenopausal and postmenopausal women susceptible to osteoporosis.

RATIONALE AND OBJECTIVES: To assess the performance of a nonlinear microfinite element model on predicting trabecular bone yield and post-yield behavior based on high-resolution in vivo magnetic resonance images via the serial reproducibility. MATERIALS AND METHODS: The nonlinear model captures material nonlinearity by iteratively adjusting tissue-level modulus based on tissue-level effective strain. It enables simulations of trabecular bone yield and post-yield behavior from micro magnetic resonance images at in vivo resolution by solving a series of nonlinear systems via an iterative algorithm on a desktop computer. Measures of mechanical competence (yield strain/strength, ultimate strain/strength, modulus of resilience, and toughness) were estimated at the distal radius of premenopausal and postmenopausal women (N = 20, age range 50-75) in whom osteoporotic fractures typically occur. Each subject underwent three scans (20.2 ± 14.5 days). Serial reproducibility was evaluated via coefficient of variation (CV) and intraclass correlation coefficient (ICC). RESULTS: Nonlinear simulations were completed in an average of 14 minutes per three-dimensional image data set involving analysis of 61 strain levels. The predicted yield strain/strength, ultimate strain/strength, modulus of resilience, and toughness had a mean value of 0.78%, 3.09 MPa, 1.35%, 3.48 MPa, 14.30 kPa, and 32.66 kPa, respectively, covering a substantial range by a factor of up to 4. Intraclass correlation coefficient ranged from 0.986 to 0.994 (average 0.991); CV ranged from 1.01% to 5.62% (average 3.6%), with yield strain and toughness having the lowest and highest CV values, respectively. CONCLUSIONS: The data suggest that the yield and post-yield parameters have adequate reproducibility to evaluate treatment effects in interventional studies within short follow-up periods.

Potential of in vivo MRI-based nonlinear finite-element analysis for the assessment of trabecular bone post-yield properties.

PURPOSE: Bone strength is the key factor impacting fracture risk. Assessment of bone strength from high-resolution (HR) images have largely relied on linear micro-finite element analysis (µFEA) even though failure always occurs beyond the yield point, which is outside the linear regime. Nonlinear µFEA may therefore be more informative in predicting failure behavior. However, existing nonlinear models applied to trabecular bone (TB) have largely been confined to micro-computed tomography (µCT) and, more recently, HR peripheral quantitative computed tomography (HR-pQCT) images, and typically have ignored evaluation of the post-yield behavior. The primary purpose of this work was threefold: (1) to provide an improved algorithm and program to assess TB yield as well as post-yield properties; (2) to explore the potential benefits of nonlinear µFEA beyond its linear counterpart; and (3) to assess the feasibility and practicality of performing nonlinear analysis on desktop computers on the basis of micro-magnetic resonance (µMR) images obtained in vivo in patients. METHODS: A method for nonlinear µFE modeling of TB yield as well as post-yield behavior has been designed where material nonlinearity is captured by adjusting the tissue modulus iteratively according to the tissue-level effective strain obtained from linear analysis using a computationally optimized algorithm. The software allows for images at in vivo µMRI resolution as input with retention of grayscale information. Associations between axial stiffness estimated from linear analysis and yield as well as post-yield parameters from nonlinear analysis were investigated from in vivo µMR images of the distal tibia (N = 20; ages: 58-84) and radius (N = 20; ages: 50-75). RESULTS: All simulations were completed in 1 h or less for 61 strain levels using a desktop computer (dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM). Although yield stress and ultimate stress correlated strongly (R(2) > 0.95, p < 0.001) with axial stiffness, toughness correlated moderately at the distal tibia (R(2) = 0.81, p < 0.001) and only weakly at the distal radius (R(2) = 0.34, p = 0.007). Further, toughness was found to vary by up to 16% for bone of very similar axial stiffness (<2%). CONCLUSIONS: The work demonstrates the practicality of nonlinear µFE simulations at in vivo µMRI resolution, as well as its potential for providing additional information beyond that obtainable from linear analysis. The data suggest that a direct assessment of toughness may provide information not captured by stiffness.

Computationally-optimized bone mechanical modeling from high-resolution structural images.

Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (µFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time), which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for µFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM). To illustrate the system's potential for large-scale µFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging.

Micro-MR imaging-based computational biomechanics demonstrates reduction in cortical and trabecular bone strength after renal transplantation.

PURPOSE: To examine the ability of three-dimensional micro-magnetic resonance (MR) imaging-based computational biomechanics to detect mechanical alterations in trabecular bone and cortical bone in the distal tibia of incident renal transplant recipients 6 months after renal transplantation and compare them with bone mineral density (BMD) outcomes. MATERIALS AND METHODS: The study was approved by the institutional review board and complied with HIPAA guidelines. Written informed consent was obtained from all subjects. Micro-MR imaging of distal tibial metaphysis was performed within 2 weeks after renal transplantation (baseline) and 6 months later in 49 participants (24 female; median age, 44 years; range, 19-61 years) with a clinical 1.5-T whole-body imager using a modified three-dimensional fast large-angle spin-echo pulse sequence. Micro-finite-element models for cortical bone, trabecular bone, and whole-bone section were generated from each image by delineating the endosteal and periosteal boundaries. Mechanical parameters (stiffness and failure load) were estimated with simulated uniaxial compression tests on the micro-finite-element models. Structural parameters (trabecular bone volume fraction [BV/TV, bone volume to total volume ratio], trabecular thickness [TbTh], and cortical thickness [CtTh]) were computed from micro-MR images. Total hip and spine areal BMD were determined with dual-energy x-ray absorptiometry (DXA). Parameters obtained at the follow-up were compared with the baseline values by using parametric or nonparametric tests depending on the normality of data. RESULTS: All mechanical parameters were significantly lower at 6 months compared with baseline. Decreases in cortical bone, trabecular bone, and whole-bone stiffness were 3.7% (P = .03), 4.9% (P = .03), and 4.3% (P = .003), respectively. Decreases in cortical bone, trabecular bone, and whole-bone failure strength were 7.6% (P = .0003), 6.0% (P = .004), and 5.6% (P = .0004), respectively. Conventional structural measures, BV/TV, TbTh, and CtTh, did not change significantly. Spine BMD decreased by 2.9% (P < .0001), while hip BMD did not change significantly at DXA. CONCLUSION: MR imaging-based micro-finite-element analysis suggests that stiffness and failure strength of the distal tibia decrease over a 6-month interval after renal transplantation.

Comparison of optimized soft-tissue suppression schemes for ultrashort echo time MRI.

Ultrashort echo time (UTE) imaging with soft-tissue suppression reveals short-T(2) components (typically hundreds of microseconds to milliseconds) ordinarily not captured or obscured by long-T(2) tissue signals on the order of tens of milliseconds or longer. Therefore, the technique enables visualization and quantification of short-T(2) proton signals such as those in highly collagenated connective tissues. This work compares the performance of the three most commonly used long-T(2) suppression UTE sequences, i.e., echo subtraction (dual-echo UTE), saturation via dual-band saturation pulses (dual-band UTE), and inversion by adiabatic inversion pulses (IR-UTE) at 3 T, via Bloch simulations and experimentally in vivo in the lower extremities of test subjects. For unbiased performance comparison, the acquisition parameters are optimized individually for each sequence to maximize short-T(2) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) between short- and long-T(2) components. Results show excellent short-T(2) contrast which is achieved with these optimized sequences. A combination of dual-band UTE with dual-echo UTE provides good short-T(2) SNR and CNR with less sensitivity to B(1) homogeneity. IR-UTE has the lowest short-T(2) SNR efficiency but provides highly uniform short-T(2) contrast and is well suited for imaging short-T(2) species with relatively short T(1) such as bone water.

Predicting trabecular bone elastic properties from measures of bone volume fraction and fabric on the basis of micromagnetic resonance images.

The relationship between fabric (a measure of structural anisotropy) and elastic properties of trabecular bone was examined by invoking morphology and homogenization theory on the basis of micromagnetic resonance images from the distal tibia in specimens (N = 30) and human subjects (N = 16) acquired at a 160 × 160 × 160 µm(3) voxel size. The fabric tensor was mapped in 7.5 × 7.5 × 7.5 mm(3) cubic subvolumes by a three-dimensional mean-intercept-length method. Elastic constants (three Young's and three shear moduli) were derived from linear microfinite element simulations of three-dimensional grayscale bone volume fraction-mapped images. In the specimen data, moduli fit power laws of bone volume fraction (bone volume/total volume) for all three test directions and subvolumes (R(2) = 0.92-0.98) with exponents ranging from 1.3 to 1.8. Weaker linear relationships were found for the in vivo data because of a narrower range in bone volume/total volume. When pooling the data for all test directions and subvolumes, bone volume/total volume predicted elastic moduli less well in the specimens (mean R(2) = 0.74) and not at all in vivo. A model of bone volume/total volume and fabric was highly predictive of microfinite element-derived Young's moduli: mean R(2) s of 0.98 and 0.82 (in vivo). The results show that fabric, an important predictor of bone mechanical properties, can be assessed in the limited resolution and signal-to-noise ratio regime of micromagnetic resonance images.