Spyglass: a framework for reproducible and shareable neuroscience research.

Scientific progress depends on reliable and reproducible results. Progress can also be accelerated when data are shared and re-analyzed to address new questions. Current approaches to storing and analyzing neural data typically involve bespoke formats and software that make replication, as well as the subsequent reuse of data, difficult if not impossible. To address these challenges, we created Spyglass, an open-source software framework that enables reproducible analyses and sharing of data and both intermediate and final results within and across labs. Spyglass uses the Neurodata Without Borders (NWB) standard and includes pipelines for several core analyses in neuroscience, including spectral filtering, spike sorting, pose tracking, and neural decoding. It can be easily extended to apply both existing and newly developed pipelines to datasets from multiple sources. We demonstrate these features in the context of a cross-laboratory replication by applying advanced state space decoding algorithms to publicly available data. New users can try out Spyglass on a Jupyter Hub hosted by HHMI and 2i2c: https://spyglass.hhmi.2i2c.cloud/.

SpikeInterface, a unified framework for spike sorting.

Much development has been directed toward improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.

SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters.

Spike sorting is a crucial step in electrophysiological studies of neuronal activity. While many spike sorting packages are available, there is little consensus about which are most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of ground-truth electrophysiological recordings, displaying results interactively on a continuously-updating website. With contributions from eleven laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include paired intracellular/extracellular recordings and state-of-the-art simulated recordings. Ten of the most popular spike sorting codes are wrapped in a Python package and evaluated on a compute cluster using an automated pipeline. SpikeForest documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions.

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.

Adverse Fat Depots and Marrow Adiposity Are Associated With Skeletal Deficits and Insulin Resistance in Long-Term Survivors of Pediatric Hematopoietic Stem Cell Transplantation.

Allogeneic hematopoietic stem-cell transplantation (alloHSCT) survivors treated with total body irradiation (TBI) exhibit bone deficits and excess adiposity, potentially related to altered mesenchymal stem cell differentiation into osteoblasts or adipocytes. We examined associations among fat distribution, bone microarchitecture, and insulin resistance in alloHSCT survivors after TBI. This was a cross-sectional observational study of 25 alloHSCT survivors (aged 12 to 25 years) a median of 9.7 (4.3 to 19.3) years after alloHSCT compared to 25 age-, race-, and sex-matched healthy controls. Vertebral MR spectroscopic imaging and tibia micro-MRI were used to quantify marrow adipose tissue (MAT) and trabecular microarchitecture. Additional measures included DXA whole-body fat mass (WB-FM), leg lean mass (Leg-LM), trunk visceral adipose tissue (VAT), and CT calf muscle density. Insulin resistance in alloHSCT survivors was estimated by HOMA-IR. AlloHSCT survivors had lower Leg-LM (p < 0.001) and greater VAT (p < 0.01), MAT (p < 0.001), and fat infiltration of muscle (p = 0.04) independent of WB-FM, versus matched controls; BMI did not differ. Survivors had lower bone volume fraction and abnormal microarchitecture including greater erosion and more rod-like structure versus controls (all p = 0.04); 14 had vertebral deformities and two had compression fractures. Greater WB-FM, VAT, MAT, and muscle fat infiltration were associated with abnormal trabecular microarchitecture (p < 0.04 for all). AlloHSCT HOMA-IR was elevated, associated with younger age at transplantation (p < 0.01), and positively correlated with WB-FM and VAT (both p < 0.01). In conclusion, the markedly increased marrow adiposity, abnormal bone microarchitecture, and abnormal fat distribution highlight the risks of long-term treatment-related morbidity and mortality in alloHSCT recipients after TBI. Trabecular deterioration was associated with marrow and visceral adiposity. Furthermore, long-term survivors demonstrated sarcopenic obesity, insulin resistance, and vertebral deformities. Future studies are needed to identify strategies to prevent and treat metabolic and skeletal complications in this growing population of childhood alloHSCT survivors.

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.

Time-resolved MRI oximetry for quantifying CMRO(2) and vascular reactivity.

This brief review of magnetic resonance susceptometry summarizes the methods conceived in the authors' laboratory during the past several years. This article shows how venous oxygen saturation is quantified in large draining veins by field mapping and how this information, in concert with simultaneous measurement of cerebral blood flow, yields cerebral metabolic rate of oxygen, the brain's rate of oxygen consumption. The accuracy of this model-based approach in which the blood vessel is approximated as a long, straight cylinder, for which an analytical solution for the induced field exists, is discussed. It is shown that the approach is remarkably robust, allowing for time-resolved quantification of whole-brain metabolism at rest and in response to stimuli, thereby providing detailed information on cerebral physiology in health and disease not previously amenable by noninvasive methods.

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.

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.

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.