Scan-rescan Reliability Research Articles

Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting.

Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability and validity of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson's r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we delineated MRF-derived T1 profiles along major white matter fiber tracts and found similar or higher reliability for T1 from MRF compared to diffusion parameters (based on a 10-minute dMRI scan). Lastly, we found that T1 values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.

Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition.

To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method. Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient. The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well. The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.

Improved inter-subject alignment of the lumbosacral cord for group-level in vivo gray and white matter assessments: A scan-rescan MRI study at 3T.

Magnetic resonance imaging (MRI) enables the investigation of pathological changes in gray and white matter at the lumbosacral enlargement (LSE) and conus medullaris (CM). However, conducting group-level analyses of MRI metrics in the lumbosacral spinal cord is challenging due to variability in CM length, lack of established image-based landmarks, and unknown scan-rescan reliability. This study aimed to improve inter-subject alignment of the lumbosacral cord to facilitate group-level analyses of MRI metrics. Additionally, we evaluated the scan-rescan reliability of MRI-based cross-sectional area (CSA) measurements and diffusion tensor imaging (DTI) metrics. Fifteen participants (10 healthy volunteers and 5 patients with spinal cord injury) underwent axial T2*-weighted and diffusion MRI at 3T. We assessed the reliability of spinal cord and gray matter-based landmarks for inter-subject alignment of the lumbosacral cord, the inter-subject variability of MRI metrics before and after adjusting for the CM length, the intra- and inter-rater reliability of CSA measurements, and the scan-rescan reliability of CSA measurements and DTI metrics. The slice with the largest gray matter CSA as an LSE landmark exhibited the highest reliability, both within and across raters. Adjusting for the CM length greatly reduced the inter-subject variability of MRI metrics. The intra-rater, inter-rater, and scan-rescan reliability of MRI metrics were the highest at and around the LSE (scan-rescan coefficient of variation <3% for CSA measurements and <7% for DTI metrics within the white matter) and decreased considerably caudal to it. To facilitate group-level analyses, we recommend using the slice with the largest gray matter CSA as a reliable LSE landmark, along with an adjustment for the CM length. We also stress the significance of the anatomical location within the lumbosacral cord in relation to the reliability of MRI metrics. The scan-rescan reliability values serve as valuable guides for power and sample size calculations in future longitudinal studies.

Characterization of an automated method to segment the human locus coeruleus.

Following the development of magnetic resonance imaging (MRI) methods to assay the integrity of catecholamine nuclei, including the locus coeruleus (LC), there has been an effort to develop automated methods that can accurately segment this small structure in an automated manner to promote its widespread use and overcome limitations of manual segmentation. Here we characterize an automated LC segmentation approach (referred to as the funnel-tip [FT] method) in healthy individuals and individuals with LC degeneration in the context of Alzheimer's disease (AD, confirmed with tau-PET imaging using [18F]MK6240). The first sample included n = 190 individuals across the AD spectrum from cognitively normal to moderate AD. LC signal assayed with FT segmentation showed excellent agreement with manual segmentation (intraclass correlation coefficient [ICC] = 0.91). Compared to other methods, the FT method showed numerically higher correlation to AD status (defined by presence of tau: Cohen's d = 0.64) and AD severity (Braak stage: Pearson R = -.35, cognitive function: R = .25). In a separate sample of n = 12 control participants, the FT method showed excellent scan-rescan reliability (ICC = 0.82). In another sample of n = 30 control participants, we found that the structure of the LC defined by FT segmentation approximated its expected shape as a contiguous line: <5% of LC voxels strayed >1 voxel (0.69 mm) from this line. The FT LC segmentation shows high agreement with manual segmentation and captures LC degeneration in AD. This practical method may facilitate larger research studies of the human LC-norepinephrine system and has potential to support future use of neuromelanin-sensitive MRI as a clinical biomarker.

Tractography Processing with the Sparse Closest Point Transform.

We propose a novel approach for processing diffusion MRI tractography datasets using the sparse closest point transform (SCPT). Tractography enables the 3D geometry of white matter pathways to be reconstructed; however, algorithms for processing them are often highly customized, and thus, do not leverage the existing wealth of machine learning (ML) algorithms. We investigated a vector-space tractography representation that aims to bridge this gap by using the SCPT, which consists of two steps: first, extracting sparse and representative landmarks from a tractography dataset, and second transforming curves relative to these landmarks with a closest point transform. We explore its use in three typical tasks: fiber bundle clustering, simplification, and selection across a population. The clustering algorithm groups fibers from single whole-brain datasets using a non-parametric k-means clustering algorithm, with performance compared with three alternative methods and across four datasets. The simplification algorithm removes redundant curves to improve interactive visualization, with performance gauged relative to random subsampling. The selection algorithm extracts bundles across a population using a one-class Gaussian classifier derived from an atlas prototype, with performance gauged by scan-rescan reliability and sensitivity to normal aging, as compared to manual mask-based selection. Our results demonstrate how the SCPT enables the novel application of existing vector-space ML algorithms to create effective and efficient tools for tractography processing. Our experimental data is available online, and our software implementation is available in the Quantitative Imaging Toolkit.

Reliability of BOLD signals in chronic stroke-induced aphasia.

Investigating the neurobiology of language impairment and treatment in chronic stroke aphasia using fMRI requires an understanding of measurement variability within and between participants. In this multicenter study, we evaluated the scan-rescan reliability of an auditory and visual (written) story comprehension paradigm in stroke participants with aphasia (N=65) and healthy controls (N=22). The multi-modal task was conducted twice (~1week apart) on separate visits upon study enrolment and twice again at completion three months later. A non-language visuomotor task was studied in the aphasia group only, which was conducted once per time point (3months apart). While participants were asked to make responses during the comprehension task, these in-scanner responses were not recorded. Reliability was assessed using intraclass correlation coefficient (ICC) at both group and individual participant levels. The visual story comprehension condition had higher reliability than the auditory condition in both groups, with participants with aphasia exhibiting lower reliability than controls in both conditions (stroke ICC=.43, healthy ICC=.81). Differences in reliability within the group of participants with aphasia were found to be partially explained by overall language impairment as well as greater head motion. In the participants with aphasia, the visuomotor paradigm was found to have greater reliability than the story comprehension task at equivalent interscan intervals (visuomotor=0.50, comprehension=0.34), and its reliability was not associated with language impairment. This work highlights the importance of considering the reliability of fMRI tasks in aphasia research, provides strategies to improve reliability and has potential implications for the field of clinical neuroimaging in general.

A novel algorithm for refining cerebral vascular measurements in infants and adults

BackgroundComprehensive quantification of intracranial vascular characteristics by vascular tracing provides an objective clinical assessment of vascular structure. However, weak signal or low contrast in small distal arteries, artifacts due to volitional motion, and vascular pulsation are challenges for accurate vessel tracing from 3D time-of-flight (3D-TOF) magnetic resonance angiography (MRA) images. New MethodA vascular measurement refinement algorithm is developed and validated for robust quantification of intracranial vasculature from 3D-TOF MRA. After automated vascular tracing, centerline positions, lumen radii and centerline deviations are jointly optimized to restrict traces to within vascular regions in the straightened curved planar reformation (CPR) views. The algorithm is validated on simulated vascular images and on repeat 3D-TOF MRA acquired from infants and adults. ResultsThe refinement algorithm can reliably estimate vascular radius and correct deviated centerlines. For the simulated vascular image with noise level of 1 and deviation of centerline of 3, the mean radius difference is below 15.3 % for scan-rescan reliability. Vascular features from repeated clinical scans show significantly improved measurement agreement, with intra-class correlation coefficient (ICC) improvement from 0.55 to 0.7 for infants and from 0.59 to 0.92 for adults. Comparison with Existing MethodsThe refinement algorithm is novel because it utilizes straightened CPR views that incorporate information from the entire artery. In addition, the optimization corrects centerline positions, lumen radii and centerline deviations simultaneously. ConclusionsIntracranial vasculature quantification using a novel refinement algorithm for vascular tracing improves the reliability of vascular feature measurements in both infants and adults.

Reliability of multimodal MRI brain measures in youth at risk for mental illness.

IntroductionA new generation of large‐scale studies is using neuroimaging to investigate adolescent brain development across health and disease. However, imaging artifacts such as head motion remain a challenge and may be exacerbated in pediatric clinical samples. In this study, we assessed the scan–rescan reliability of multimodal MRI in a sample of youth enriched for risk of mental illness.MethodsWe obtained repeated MRI scans, an average of 2.7 ± 1.4 weeks apart, from 50 youth (mean age 14.7 years, SD = 4.4). Half of the sample (52%) had a diagnosis of an anxiety disorder; 22% had attention‐deficit/hyperactivity disorder (ADHD). We quantified reliability with the test–retest intraclass correlation coefficient (ICC).ResultsGray matter measurements were highly reliable with mean ICCs as follows: cortical volume (ICC = 0.90), cortical surface area (ICC = 0.89), cortical thickness (ICC = 0.82), and local gyrification index (ICC = 0.85). White matter volume reliability was excellent (ICC = 0.98). Diffusion tensor imaging (DTI) components were also highly reliable. Fractional anisotropy was most consistently measured (ICC = 0.88), followed by radial diffusivity (ICC = 0.84), mean diffusivity (ICC = 0.81), and axial diffusivity (ICC = 0.78). We also observed regional variability in reconstruction, with some brain structures less reliably reconstructed than others.ConclusionsOverall, we showed that developmental MRI measures are highly reliable, even in youth at risk for mental illness and those already affected by anxiety and neurodevelopmental disorders. Yet, caution is warranted if patterns of results cluster within regions of lower reliability.

Consensus approach for 3D joint space width of metacarpophalangeal joints of rheumatoid arthritis patients using high-resolution peripheral quantitative computed tomography.

Joint space assessment for rheumatoid arthritis (RA) by ordinal conventional radiographic scales is susceptible to floor and ceiling effects. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides superior resolution, and may detect earlier changes. The goal of this work was to compare existing 3D methods to calculate joint space width (JSW) metrics in human metacarpophalangeal (MCP) joints with HR-pQCT and reach consensus for future studies. Using the consensus method, we established reproducibility with repositioning as well as feasibility for use in second-generation HR-pQCT scanners. Three published JSW methods were compared using datasets from individuals with RA from three research centers. A SPECTRA consensus method was developed to take advantage of strengths of the individual methods. Using the SPECTRA method, reproducibility after repositioning was tested and agreement between scanner generations was also established. When comparing existing JSW methods, excellent agreement was shown for JSW minimum and mean (ICC 0.987-0.996) but not maximum and volume (ICC 0.000-0.897). Differences were identified as variations in volume definitions and algorithmic differences that generated high sensitivity to boundary conditions. The SPECTRA consensus method reduced this sensitivity, demonstrating good scan-rescan reliability (ICC >0.911) except for minimum JSW (ICC 0.656). There was strong agreement between results from first- and second-generation HR-pQCT (ICC >0.833). The SPECTRA consensus method combines unique strengths of three independently-developed algorithms and leverages underlying software updates to provide a mature analysis to measure 3D JSW. This method is robust with respect to repositioning and scanner generations, suggesting its suitability for detecting change.

Accurate and robust segmentation of neuroanatomy in T1‐weighted MRI by combining spatial priors with deep convolutional neural networks

Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for quantitative volume, thickness, and shape measurements, as well as an important intermediate step in many preprocessing pipelines. This work introduces a new highly accurate and versatile method based on 3D convolutional neural networks for the automatic segmentation of neuroanatomy in T1‐weighted MRI. In combination with a deep 3D fully convolutional architecture, efficient linear registration‐derived spatial priors are used to incorporate additional spatial context into the network. An aggressive data augmentation scheme using random elastic deformations is also used to regularize the networks, allowing for excellent performance even in cases where only limited labeled training data are available. Applied to hippocampus segmentation in an elderly population (mean Dice coefficient = 92.1%) and subcortical segmentation in a healthy adult population (mean Dice coefficient = 89.5%), we demonstrate new state‐of‐the‐art accuracies and a high robustness to outliers. Further validation on a multistructure segmentation task in a scan–rescan dataset demonstrates accuracy (mean Dice coefficient = 86.6%) similar to the scan–rescan reliability of expert manual segmentations (mean Dice coefficient = 86.9%), and improved reliability compared to both expert manual segmentations and automated segmentations using FIRST. Furthermore, our method maintains a highly competitive runtime performance (e.g., requiring only 10 s for left/right hippocampal segmentation in 1 × 1 × 1 mm3 MNI stereotaxic space), orders of magnitude faster than conventional multiatlas segmentation methods.

Reliability of cervical muscle volume quantification using magnetic resonance imaging

BackgroundMagnetic resonance imaging (MRI) is used to quantify the size and structure of the architecturally complex cervical spine musculature of individuals with traumatic and idiopathic neck pain. However, to our knowledge, no scan-rescan reliability data is available on neck muscle volumes. ObjectivesThis study investigates the intra- and inter-rater reliability and scan-rescan reliability in cervical muscle volume investigations. DesignClinical Measurement, Reliability study. MethodsMRI scans were performed and repeated (within 1 h) for five asymptomatic individuals. Two raters manually traced levator scapulae, multifidus including semispinalis cervicis, semispinalis capitis, splenius capitis including splenius cervicis, and sternocleidomastoid using Analyze software (v12.0). Reliability was determined using intra-class correlation coefficients, Lin's concordance coefficient and Bland-Altman plots, with interpretation of reliability coefficients using the criteria from Fleiss. ResultsIntra-rater reliability of muscle quantification was excellent (ICCs ranging from 0.78 to 0.96). Inter-rater reliability was excellent for sternocleidomastoid(ICC 0.92, 95% CI 0.80, 0.97) and splenius capitis (ICC 0.77, 0.51, 0.90), and ranged from fair to good for levator scapulae (0.63, 0.18, 0.85), multifidus (0.73, 0.44, 0.88), and semispinalis capitis (0.50, 0.08, 0.77). The scan-rescan reliability was excellent for all muscles (ICCs ranging from 0.94 to 0.98). ConclusionThreats to reliability appear to be more related to manual quantification of muscles on images rather than protocols related to re-positioning a participant in the scanner and repeating the same protocol.The current findings suggest that the proposed methods can be used in establishing normative data for cervical muscle volume and comparing individuals with and without neck pain.

Applying microstructural models to understand the role of white matter in cognitive development

Diffusion MRI (dMRI) holds great promise for illuminating the biological changes that underpin cognitive development. The diffusion of water molecules probes the cellular structure of brain tissue, and biophysical modeling of the diffusion signal can be used to make inferences about specific tissue properties that vary over development or predict cognitive performance. However, applying these models to study development requires that the parameters can be reliably estimated given the constraints of data collection with children. Here we collect repeated scans using a typical multi-shell diffusion MRI protocol in a group of children (ages 7–12) and use two popular modeling techniques to examine individual differences in white matter structure. We first assess scan-rescan reliability of model parameters and show that axon water faction can be reliably estimated from a relatively fast acquisition, without applying spatial smoothing or de-noising. We then investigate developmental changes in the white matter, and individual differences that correlate with reading skill. Specifically, we test the hypothesis that previously reported correlations between reading skill and diffusion anisotropy in the corpus callosum reflect increased axon water fraction in poor readers. Both models support this interpretation, highlighting the utility of these approaches for testing specific hypotheses about cognitive development.

Neck Vessel Cross-Sectional Area Measured with MRI: Scan-Rescan Reproducibility for Longitudinal Evaluations.

The cross-sectional area (CSA) of common carotid arteries-internal carotid arteries (CCA-ICAs), vertebral arteries (VAs), and internal jugular veins (IJVs) is influenced by aging. However, the neck vessel CSA can be affected by other factors as well, including subject positioning, hydration, and respiration, especially in longitudinal studies. This study aimed to assess scan-rescan reproducibility of CCA-ICAs, VAs, and IJVs CSA measurements in order to evaluate their feasibility for longitudinal CSA assessments, and to apply the segmentation method on a longitudinal pilot dataset. Two set of 2-dimensional neck magnetic resonance angiography (MRA) images were acquired on a 3-T scanner from two separate datasets: 9 healthy individuals (HIs) were scanned 5 days apart (scan-rescan dataset) and 12 HIs were acquired 5 years apart (baseline-follow-up dataset). CCA-ICAs, VAs, and IJVs were segmented along the whole vessel length between C3 and C7 intervertebral spaces. Repeated measure analysis of covariance, adjusted for cervical level and sample, and Wilcoxon signed-rank sum test were used to assess the scan-rescan and baseline-follow-up CSA differences. Intraclass correlation coefficient (ICC) was also computed to evaluate scan-rescan reliability. No significant CSA differences were found for the scan-rescan and baseline-follow-up CSA comparisons, using the whole vessel length or single cervical level measurements. ICC analysis showed good degree of scan-rescan reproducibility (considering whole vessel measures: ICC > .9, P-value < .001 for CCA-ICAs, ICC > .6, P-value < .001 for VAs, and ICC > .7, P-value < .001 for IJVs). Scan-rescan reproducibility of CCA-ICAs, VAs, and IJVs CSA measurements is high, making longitudinal studies feasible.

Automated segmentation of cerebral deep gray matter from MRI scans: effect of field strength on sensitivity and reliability

BackgroundThe cerebral subcortical deep gray matter nuclei (DGM) are a common, early, and clinically-relevant site of atrophy in multiple sclerosis (MS). Robust and reliable DGM segmentation could prove useful to evaluate putative neuroprotective MS therapies. The objective of the study was to compare the sensitivity and reliability of DGM volumes obtained from 1.5T vs. 3T MRI.MethodsFourteen patients with MS [age (mean, range) 50.2 (32.0–60.8) years, disease duration 18.4 (8.2–35.5) years, Expanded Disability Status Scale score 3.1 (0–6), median 3.0] and 15 normal controls (NC) underwent brain 3D T1-weighted paired scan-rescans at 1.5T and 3T. DGM (caudate, thalamus, globus pallidus, and putamen) segmentation was obtained by the fully automated FSL-FIRST pipeline. Both raw and normalized volumes were derived.ResultsDGM volumes were generally higher at 3T vs. 1.5T in both groups. For raw volumes, 3T showed slightly better sensitivity (thalamus: p = 0.02; caudate: p = 0.10; putamen: p = 0.02; globus pallidus: p = 0.0004; total DGM: p = 0.01) than 1.5T (thalamus: p = 0.05; caudate: p = 0.09; putamen: p = 0.03; globus pallidus: p = 0.0006; total DGM: p = 0.02) for detecting DGM atrophy in MS vs. NC. For normalized volumes, 3T but not 1.5T detected atrophy in the globus pallidus in the MS group. Across all subjects, scan-rescan reliability was generally very high for both platforms, showing slightly higher reliability for some DGM volumes at 3T. Raw volumes showed higher reliability than normalized volumes. Raw DGM volume showed higher reliability than the individual structures.ConclusionsThese results suggest somewhat higher sensitivity and reliability of DGM volumes obtained from 3T vs. 1.5T MRI. Further studies should assess the role of this 3T pipeline in tracking potential MS neurotherapeutic effects.

Neurological software tool for reliable atrophy measurement (NeuroSTREAM) of the lateral ventricles on clinical-quality T2-FLAIR MRI scans in multiple sclerosis

BackgroundThere is a need for a brain volume measure applicable to the clinical routine scans. Nearly every multiple sclerosis (MS) protocol includes low-resolution 2D T2-FLAIR imaging.ObjectivesTo develop and validate cross-sectional and longitudinal brain atrophy measures on clinical-quality T2-FLAIR images in MS patients.MethodsA real-world dataset from 109 MS patients from 62 MRI scanners was used to develop a lateral ventricular volume (LVV) algorithm with a longitudinal Jacobian-based extension, called NeuroSTREAM. Gold-standard LVV was calculated on high-resolution T1 1 mm, while NeuroSTREAM LVV was obtained on low-resolution T2-FLAIR 3 mm thick images. Scan-rescan reliability was assessed in 5 subjects. The variability of LVV measurement at different field strengths was tested in 76 healthy controls and 125 MS patients who obtained both 1.5T and 3T scans in 72 hours. Clinical validation of algorithm was performed in 176 MS patients who obtained serial yearly MRI 1.5T scans for 10 years.ResultsCorrelation between gold-standard high-resolution T1 LVV and low-resolution T2-FLAIR LVV was r = 0.99, p < 0.001 and the scan-rescan coefficient of variation was 0.84%. Correlation between low-resolution T2-FLAIR LVV on 1.5T and 3T was r = 0.99, p < 0.001 and the scan-rescan coefficient of variation was 2.69% cross-sectionally and 2.08% via Jacobian integration. NeuroSTREAM showed comparable effect size (d = 0.39–0.71) in separating MS patients with and without confirmed disability progression, compared to SIENA and VIENA.ConclusionsBrain atrophy measurement on clinical quality T2-FLAIR scans is feasible, accurate, reliable, and relates to clinical outcomes.

Reliability of analysis of the bone mineral density of the second and fifth metatarsals using dual-energy x-ray absorptiometry (DXA)

BackgroundMetatarsal fractures, especially of the fifth metatarsal, are common injuries of the foot in a young athletic population, but the risk factors for this injury are not well understood. Dual-energy x-ray absorptiometry (DXA) provides reliable measures of regional bone mineral density to predict fracture risk in the hip and lumbar spine. Recently, sub-regional metatarsal reliability was established in fresh cadaveric specimens and associated with ultimate fracture force. The purpose of this study was to assess the reliability of DXA bone mineral density measurements of sub-regions of the second and fifth metatarsals in a young, active population.MethodsThirty two recreationally active individuals participated in the study, and the bone density of the second (2MT) and fifth (5MT) metatarsals of each subject was measured using a Hologic QDR x-ray bone densitometer. Scans were analyzed separately by two raters, and regional bone mineral density, bone mineral content, and area measurements were calculated for the proximal, shaft, and distal regions of the bone. Intra-rater, inter-rater, and scan-rescan reliability were then determined for each region.ResultsProximal and shaft bone mineral density measurements of the second and fifth metatarsal were reliable. ICC’s were variable across regions and metatarsals, with the distal region being the poorest.ConclusionsBone mineral density measurements of the metatarsals may be a better indicator of fracture risk of the metatarsals than whole body measurements. A reliable method for measuring the regional bone mineral densities of the metatarsals was found. However, inter-rater reliability and scan-rescan reliability for the distal regions were poor. Future research should examine the relationship between DXA bone mineral density measurements and fracture risk at the metatarsals.

Longitudinal assessment of marrow fat content using three-point Dixon technique in osteoporotic rabbits.

In this longitudinal pilot study, we aimed to investigate the intra-, interobserver, and scan-rescan reproducibility of marrow fat fraction (FF) measurements using three-point Dixon imaging in osteoporotic rabbits: comparison with histopathology. Twenty female rabbits were randomly assigned to sham-operation and ovariectomy in combination with daily methylprednisolone hemisuccinate groups (n = 10 per group). Marrow FF by three-point Dixon technique and bone density by dual-energy x-ray absorptiometry were assessed at baseline, 6 and 12 weeks after operation. Intra-, inter-reader, and scan-rescan reliability of FF measurements were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman 95% limit of agreement. Histomorphometry was performed to quantify marrow adipocyte parameters. Intra- and inter-reader reproducibility of FF measurements was "substantial" (ICC = 0.984 and 0.978, respectively). Although the ICC for scan-rescan reliability was excellent (ICC = 0.962), increased measurement variability was observed using Bland-Altman plot. Relative to the sham-operated rabbits, the adipocytes mean diameter, density, and percent adipocytes area in the osteoporotic rabbits increased by 23.4%, 68.9%, and 117.0%, respectively. Marrow FF was positively correlated with the quantitative parameters of adipocytes, particularly with percent adipocyte area, but inversely associated with bone density. At the relatively early stage, the percentage of bone loss was similar to that of elevated fatty marrow in the osteoporotic rabbits; at the later stage, the change for the latter outweighed that of the former. Results of three-point Dixon technique demonstrated a very reproducible manner within and between observers and acceptable scan-rescan performance in the assessment of marrow fat in rabbits.

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25–65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

Reliable volumetry of the cervical spinal cord in MS patient follow-up data with cord image analyzer (Cordial).

Spinal cord (SC) atrophy is an important contributor to the development of disability in many neurological disorders including multiple sclerosis (MS). To assess the spinal cord atrophy in clinical trials and clinical practice, largely automated methods are needed due to the sheer amount of data. Moreover, using these methods in longitudinal trials requires them to deliver highly reliable measurements, enabling comparisons of multiple data sets of the same subject over time. We present a method for SC volumetry using 3D MRI data providing volume measurements for SC sections of fixed length and location. The segmentation combines a continuous max flow approach with SC surface reconstruction that locates the SC boundary based on image voxel intensities. Two cutting planes perpendicular to the SC centerline are determined based on predefined distances to an anatomical landmark, and the cervical SC volume (CSCV) is then calculated in-between these boundaries. The development of the method focused on its application in MRI follow-up studies; the method provides a high scan-rescan reliability, which was tested on healthy subject data. Scan-rescan reliability coefficients of variation (COV) were below 1%, intra- and interrater COV were even lower (0.1-0.2%). To show the applicability in longitudinal trials, 3-year follow-up data of 48 patients with a progressive course of MS were assessed. In this cohort, CSCV loss was the only significant predictor of disability progression (p=0.02). We are, therefore, confident that our method provides a reliable tool for SC volumetry in longitudinal clinical trials.

Reproducibility of Brain Morphometry from Short-Term Repeat Clinical MRI Examinations: A Retrospective Study.

PurposeTo assess the inter session reproducibility of automatic segmented MRI-derived measures by FreeSurfer in a group of subjects with normal-appearing MR images.Materials and MethodsAfter retrospectively reviewing a brain MRI database from our institute consisting of 14,758 adults, those subjects who had repeat scans and had no history of neurodegenerative disorders were selected for morphometry analysis using FreeSurfer. A total of 34 subjects were grouped by MRI scanner model. After automatic segmentation using FreeSurfer, label-wise comparison (involving area, thickness, and volume) was performed on all segmented results. An intraclass correlation coefficient was used to estimate the agreement between sessions. Wilcoxon signed rank test was used to assess the population mean rank differences across sessions. Mean-difference analysis was used to evaluate the difference intervals across scanners. Absolute percent difference was used to estimate the reproducibility errors across the MRI models. Kruskal-Wallis test was used to determine the across-scanner effect.ResultsThe agreement in segmentation results for area, volume, and thickness measurements of all segmented anatomical labels was generally higher in Signa Excite and Verio models when compared with Sonata and TrioTim models. There were significant rank differences found across sessions in some labels of different measures. Smaller difference intervals in global volume measurements were noted on images acquired by Signa Excite and Verio models. For some brain regions, significant MRI model effects were observed on certain segmentation results.ConclusionsShort-term scan-rescan reliability of automatic brain MRI morphometry is feasible in the clinical setting. However, since repeatability of software performance is contingent on the reproducibility of the scanner performance, the scanner performance must be calibrated before conducting such studies or before using such software for retrospective reviewing.