Image Acquisition Scheme Research Articles

Functional connectomics from a “big data” perspective

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of “big data”, which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field.

Anisotropic phantom to calibrate high-q diffusion MRI methods

A silicon oil-filled glass capillary array is proposed as an anisotropic diffusion MRI phantom. Together with a computational/theoretical pipeline these provide a gold standard for calibrating and validating high-q diffusion MRI experiments. The phantom was used to test high angular resolution diffusion imaging (HARDI) and double pulsed-field gradient (d-PFG) MRI acquisition schemes. MRI-based predictions of microcapillary diameter using both acquisition schemes were compared with results from optical microscopy. This phantom design can be used for quality control and quality assurance purposes and for testing and validating proposed microstructure imaging experiments and the processing pipelines used to analyze them.

A probability-based multi-cycle sorting method for 4D-MRI: A simulation study.

To develop a novel probability-based sorting method capable of generating multiple breathing cycles of 4D-MRI images and to evaluate performance of this new method by comparing with conventional phase-based methods in terms of image quality and tumor motion measurement. Based on previous findings that breathing motion probability density function (PDF) of a single breathing cycle is dramatically different from true stabilized PDF that resulted from many breathing cycles, it is expected that a probability-based sorting method capable of generating multiple breathing cycles of 4D images may capture breathing variation information missing from conventional single-cycle sorting methods. The overall idea is to identify a few main breathing cycles (and their corresponding weightings) that can best represent the main breathing patterns of the patient and then reconstruct a set of 4D images for each of the identified main breathing cycles. This method is implemented in three steps: (1) The breathing signal is decomposed into individual breathing cycles, characterized by amplitude, and period; (2) individual breathing cycles are grouped based on amplitude and period to determine the main breathing cycles. If a group contains more than 10% of all breathing cycles in a breathing signal, it is determined as a main breathing pattern group and is represented by the average of individual breathing cycles in the group; (3) for each main breathing cycle, a set of 4D images is reconstructed using a result-driven sorting method adapted from our previous study. The probability-based sorting method was first tested on 26 patients' breathing signals to evaluate its feasibility of improving target motion PDF. The new method was subsequently tested for a sequential image acquisition scheme on the 4D digital extended cardiac torso (XCAT) phantom. Performance of the probability-based and conventional sorting methods was evaluated in terms of target volume precision and accuracy as measured by the 4D images, and also the accuracy of average intensity projection (AIP) of 4D images. Probability-based sorting showed improved similarity of breathing motion PDF from 4D images to reference PDF compared to single cycle sorting, indicated by the significant increase in Dice similarity coefficient (DSC) (probability-based sorting, DSC = 0.89 ± 0.03, and single cycle sorting, DSC = 0.83 ± 0.05, p-value <0.001). Based on the simulation study on XCAT, the probability-based method outperforms the conventional phase-based methods in qualitative evaluation on motion artifacts and quantitative evaluation on tumor volume precision and accuracy and accuracy of AIP of the 4D images. In this paper the authors demonstrated the feasibility of a novel probability-based multicycle 4D image sorting method. The authors' preliminary results showed that the new method can improve the accuracy of tumor motion PDF and the AIP of 4D images, presenting potential advantages over the conventional phase-based sorting method for radiation therapy motion management.

PANORAMA IMAGE SETS FOR TERRESTRIAL PHOTOGRAMMETRIC SURVEYS

Abstract. High resolution 3D models produced from photographs acquired with consumer-grade cameras are becoming increasingly common in the fields of geosciences. However, the quality of an image-based 3D model depends on the planning of the photogrammetric surveys. This means that the geometric configuration of the multi-view camera network and the control data have to be designed in accordance with the required accuracy, resolution and completeness. From a practical application point of view, a proper planning (of both photos and control data) of the photogrammetric survey especially for terrestrial acquisition, is not always ensured due to limited accessibility of the target object and the presence of occlusions. To solve these problems, we propose a different image acquisition strategy and we test different geo-referencing scenarios to deal with the practical issues of a terrestrial photogrammetric survey. The proposed photogrammetric survey procedure is based on the acquisition of a sequence of images in panorama mode by rotating the camera on a standard tripod. The offset of the pivot point from the projection center prevents the stitching of these images into a panorama. We demonstrate how to still take advantage of this capturing mode. The geo-referencing investigation consists of testing the use of directly observed coordinates of the camera positions, different ground control point (GCP) configurations, and GCPs with different accuracies, i.e. artificial targets vs. natural features. Images of the test field in a low-slope hill were acquired from the ground using an SLR camera. To validate the photogrammetric results a terrestrial laser scanner survey is used as benchmark.

PANORAMA IMAGE SETS FOR TERRESTRIAL PHOTOGRAMMETRIC SURVEYS

High resolution 3D models produced from photographs acquired with consumer-grade cameras are becoming increasingly common in the fields of geosciences. However, the quality of an image-based 3D model depends on the planning of the photogrammetric surveys. This means that the geometric configuration of the multi-view camera network and the control data have to be designed in accordance with the required accuracy, resolution and completeness. From a practical application point of view, a proper planning (of both photos and control data) of the photogrammetric survey especially for terrestrial acquisition, is not always ensured due to limited accessibility of the target object and the presence of occlusions. To solve these problems, we propose a different image acquisition strategy and we test different geo-referencing scenarios to deal with the practical issues of a terrestrial photogrammetric survey. The proposed photogrammetric survey procedure is based on the acquisition of a sequence of images in panorama mode by rotating the camera on a standard tripod. The offset of the pivot point from the projection center prevents the stitching of these images into a panorama. We demonstrate how to still take advantage of this capturing mode. The geo-referencing investigation consists of testing the use of directly observed coordinates of the camera positions, different ground control point (GCP) configurations, and GCPs with different accuracies, i.e. artificial targets vs. natural features. Images of the test field in a low-slope hill were acquired from the ground using an SLR camera. To validate the photogrammetric results a terrestrial laser scanner survey is used as benchmark.

Dual CARS and SHG image acquisition scheme that combines single central fiber and multimode fiber bundle to collect and differentiate backward and forward generated photons.

In coherent anti-Stokes Raman scattering (CARS) and second harmonic generation (SHG) imaging, backward and forward generated photons exhibit different image patterns and thus capture salient intrinsic information of tissues from different perspectives. However, they are often mixed in collection using traditional image acquisition methods and thus are hard to interpret. We developed a multimodal scheme using a single central fiber and multimode fiber bundle to simultaneously collect and differentiate images formed by these two types of photons and evaluated the scheme in an endomicroscopy prototype. The ratio of these photons collected was calculated for the characterization of tissue regions with strong or weak epi-photon generation while different image patterns of these photons at different tissue depths were revealed. This scheme provides a new approach to extract and integrate information captured by backward and forward generated photons in dual CARS/SHG imaging synergistically for biomedical applications.

Data of NODDI diffusion metrics in the brain and computer simulation of hybrid diffusion imaging (HYDI) acquisition scheme.

This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI), “Hybrid diffusion imaging”[1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI) model, “NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain”[2]. HYDI is an extremely versatile diffusion magnetic resonance imaging (dMRI) technique that enables various analyzes methods using a single diffusion dataset. One of the diffusion data analysis methods is the NODDI computation, which models the brain tissue with three compartments: fast isotropic diffusion (e.g., cerebrospinal fluid), anisotropic hindered diffusion (e.g., extracellular space), and anisotropic restricted diffusion (e.g., intracellular space). The NODDI model produces microstructural metrics in the developing brain, aging brain or human brain with neurologic disorders. The first dataset provided here are the means and standard deviations of NODDI metrics in 48 white matter region-of-interest (ROI) averaging across 52 healthy participants. The second dataset provided here is the computer simulation with initial conditions guided by the first dataset as inputs and gold standard for model fitting. The computer simulation data provide a direct comparison of NODDI indices computed from the HYDI acquisition [1] to the NODDI indices computed from the originally proposed acquisition [2]. These data are related to the accompanying research article “Age Effects and Sex Differences in Human Brain White Matter of Young to Middle-Aged Adults: A DTI, NODDI, and q-Space Study” [3].

Rapid brain MRI acquisition techniques at ultra-high fields.

Ultra-high-field MRI provides large increases in signal-to-noise ratio (SNR) as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher-spatial-resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, there is a concurrent increased image-encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI - particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development - such as the move from conventional 2D slice-by-slice imaging to more efficient simultaneous multislice (SMS) or multiband imaging (which can be viewed as "pseudo-3D" encoding) as well as full 3D imaging - have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multichannel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. Copyright © 2016 John Wiley & Sons, Ltd.

Investigation of image guidance strategy for intermittent breath-hold cone beam CT

Objective To develop a practical image acquisition strategy using intermittent breath-hold cone beam computed tomography (CBCT). Methods A breathing phantom was used to simulate the movement of tumor near the diaphragm during free breathing and breath hold and scanned by conventional breath-hold CBCT and type Ⅰ/Ⅱ intermittent breath-hold CBCT. In the conventional breath-hold CBCT, scan paused and free breathing occurred at the break of breath hold and free breathing was not included in the scan. In the intermittent breath-hold CBCT, one scan covered several breath holds separated by free breathing in a ratio of 3 vs1. Image quality and three-dimensional registration accuracy were quantitatively compared between conventional breath-hold CBCT and type Ⅰ/Ⅱ intermittent breath-hold CBCT. Comparison of image quality parameters between conventional breath-hold CBCT and intermittent breath-hold CBCT was made by paired t test. Results Motion artifacts arose in type I and Ⅱ intermittent breath-hold CBCT scans. There were no significant differences in the reconstructed pixel value or uniformity between intermittent breath-hold CBCT and conventional breath-hold CBCT (P>0.05, and P=0.02, 0.53). Compared with conventional breath-hold CBCT images, the signal-to-noise ratios of type I and Ⅱ intermittent breath-hold CBCT images were reduced by 30% and 60%, respectively (P<0.05). The registration error was up to 0.4 cm in the anterior-posterior direction and less than 0.1 cm in other directions. Conclusions The phantom study shows that intermittent breath-hold CBCT does not significantly reduce image quality or registration accuracy compared with conventional breath-hold CBCT. The feasibility of intermittent breath-hold CBCT in clinical application needs to be further validated among a large number of patients. Key words: Breath-hold; Tomography, X-ray computed, cone beam; Respiratory motion

3D Tree Dimensionality Assessment Using Photogrammetry and Small Unmanned Aerial Vehicles.

Detailed, precise, three-dimensional (3D) representations of individual trees are a prerequisite for an accurate assessment of tree competition, growth, and morphological plasticity. Until recently, our ability to measure the dimensionality, spatial arrangement, shape of trees, and shape of tree components with precision has been constrained by technological and logistical limitations and cost. Traditional methods of forest biometrics provide only partial measurements and are labor intensive. Active remote technologies such as LiDAR operated from airborne platforms provide only partial crown reconstructions. The use of terrestrial LiDAR is laborious, has portability limitations and high cost. In this work we capitalized on recent improvements in the capabilities and availability of small unmanned aerial vehicles (UAVs), light and inexpensive cameras, and developed an affordable method for obtaining precise and comprehensive 3D models of trees and small groups of trees. The method employs slow-moving UAVs that acquire images along predefined trajectories near and around targeted trees, and computer vision-based approaches that process the images to obtain detailed tree reconstructions. After we confirmed the potential of the methodology via simulation we evaluated several UAV platforms, strategies for image acquisition, and image processing algorithms. We present an original, step-by-step workflow which utilizes open source programs and original software. We anticipate that future development and applications of our method will improve our understanding of forest self-organization emerging from the competition among trees, and will lead to a refined generation of individual-tree-based forest models.

Asynchronous data acquisition and on-the-fly analysis of dose fractionated cryoEM images by UCSFImage.

Newly developed direct electron detection cameras have a high image output frame rate that enables recording dose fractionated image stacks of frozen hydrated biological samples by electron cryomicroscopy (cryoEM). Such novel image acquisition schemes provide opportunities to analyze cryoEM data in ways that were previously impossible. The file size of a dose fractionated image stack is 20-60 times larger than that of a single image. Thus, efficient data acquisition and on-the-fly analysis of a large number of dose-fractionated image stacks become a serious challenge to any cryoEM data acquisition system. We have developed a computer-assisted system, named UCSFImage4, for semi-automated cryo-EM image acquisition that implements an asynchronous data acquisition scheme. This facilitates efficient acquisition, on-the-fly motion correction, and CTF analysis of dose fractionated image stacks with a total time of ∼60s/exposure. Here we report the technical details and configuration of this system.

T2-weighted four dimensional magnetic resonance imaging with result-driven phase sorting.

T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion. A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2-3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundant images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (NR) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between NR and the following factors: number of slices (NS), number of 4D-MRI respiratory bins (NB), and starting phase at image acquisition (P0). To validate the authors' technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique. 4D data acquisition completeness (Cp) increases as NR increases in an inverse-exponential fashion (Cp = 100 - 99 × exp(-0.18 × NR), when NB = 6, fitted using 29 patients' data). The NR required for 4D-MRI reconstruction (defined as achieving 95% completeness, Cp = 95%, NR = NR,95) is proportional to NB (NR,95 ∼ 2.86 × NB, r = 1.0), but independent of NS and P0. Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior-inferior direction. A novel T2-weighted retrospective phase sorting 4D-MRI technique has been developed and successfully applied on digital phantom and healthy volunteers.

A Relative Imaging CMOS Image Sensor for High Dynamic Range and High Frame-Rate Machine Vision Imaging Applications

This paper proposes an unconventional image acquisition scheme for machine vision applications, based on detecting ratios of illumination (pixel) intensities. Detecting relative ratios enables capturing the scene features and patterns almost independently from the local scene illumination resulting in potentially extremely high dynamic range. Moreover, detecting signal ratios using a fully differential circuit optimally suits the intrinsic nature of very large scale integrated design. A scalable and compact hardware implementation is proposed as a proof-of-concept toward relative image acquisition. The proposed photo-current-ratio-detecting pixels completely bypass the need of conventional photo-current integration which enables high frame-rate operation of up to 24 000 frames/s. The pulse-width-modulated output of the proposed pixel is captured by compact column-parallel readout circuits based on digital counters. The developed 32 x 32 pixel array prototype CMOS image sensor consumes 4 mW of power operating at a nominal 9765 frames/s frame rate, and 6.8 mW of power operating at a maximum 24 000 frames/s. The presented prototype design is fully scalable toward newer CMOS fabrication nodes and higher sensor resolution.

SU-F-303-08: Four-Dimensional MRI Method Based On Internal Respiratory Surrogate Derived by Dimensionality Reduction

Purpose: To investigate the feasibility of constructing 4D MRI using non-navigator, image-based internal respiratory surrogate derived by dimensionality reduction (DR). Methods: DR is a mathematical process that derives a series of scalar indices from the corresponding image frames. We proposed a novel image acquisition scheme (A) designed for the DR- derived internal surrogates (Wachinger, 2012) to better match the temporal pattern of previously established surrogates such as diaphragm position. The idea is to acquire a pair of slices alternatingly so the phase of a slice can be more accurately determined with additional information from the other slice. This scheme was compared with the sequential acquisition scheme (B), the navigator-based approach (C), and a previously proposed method using body area as internal respiratory surrogate (Cai, 2011) (D). Correlation between internal surrogates from all schemes and the diaphragm position was studied using a publicly available 4D MRI dataset (von Siebenthal, 2007). Results: DR did not require any manual preprocessing. It took only a few minutes to process the entire 4D MRI data of 100 respiratory cycles with a common desktop computer. The respiratory surrogate signals were highly correlated with diaphragm positions. Correlation coefficients were 0.996, 0.993, 0.997, and 0.982 and mean absolute phase errors were 1.5%, 2.0%, 1.3%, and 3.3% for A, B, C and D, respectively. With the navigator-based approach C, the sampling rate of the regions of interest was reduced by half. Among those without the need for navigators, the novel acquisition scheme A reflected diaphragm positions better than the sequential scheme B and body area scheme D. Conclusion: The proposed image-based 4D MRI method with a novel acquisition scheme and the DR-derived internal respiratory surrogate compared favorably to the navigator-based approach and has twice the sampling rate. Although tested on sagittal slices, it is potentially applicable to any slice orientation.

SU-E-I-39: Combining Conventional Tomographic Imaging Strategy and Interior Tomography for Low Dose Dual-Energy CT (DECT)

Purpose: Dual-energy CT (DECT) affords quantitative information of tissue density and provides a new dimension for disease diagnosis and treatment planning. The technique, however, increases the imaging dose because of the doubled scans, and thus hinders its widespread clinical applications. The purpose of this work is to develop a novel hybrid DECT image acquisition and reconstruction strategy, in which one of the energies is dealt by interior tomography while the other one is obtained using conventional tomography approach. Methods: In the proposed hybrid imaging strategy, the projection data of one of the energies (e.g., high-energy) were acquired and processed in an interior scanning model, whereas the other energy in the conventional tomographic approach. It known that, if the ROI is piecewise constant or polynomial, the interior ROI can be reconstructed with TV or HOT minimization. Here we extend the TV based interior reconstruction method into dual-energy situation. The ROI images so obtained were overlaid in the context of conventional CT of the companion energy. A material based composition in ROI was used in the proposed reconstruction framework. Results: In the simulation experiment with a diagnostic DECT geometry and energies, we were able to derive the densities of soft-tissues and bonesmore » in the ROI with high fidelity. In the experimental CBCT study, both kV and MV data were collected using the on-board kV and MV imaging system. The MV data were truncated only across the ROI. Using the interior tomography reconstruction above, we were able to obtain the ROI images as that obtained using un-truncated MV data with known tissue densities. Conclusion: The proposed DECT imaging strategy provides an effective way to extract tissue density information in the ROI and in the context of anatomical images of CT imaging, with much reduced imaging dose.« less

In vivo dynamics of retinal microglial activation during neurodegeneration: confocal ophthalmoscopic imaging and cell morphometry in mouse glaucoma.

Microglia, which are CNS-resident neuroimmune cells, transform their morphology and size in response to CNS damage, switching to an activated state with distinct functions and gene expression profiles. The roles of microglial activation in health, injury and disease remain incompletely understood due to their dynamic and complex regulation in response to changes in their microenvironment. Thus, it is critical to non-invasively monitor and analyze changes in microglial activation over time in the intact organism. In vivo studies of microglial activation have been delayed by technical limitations to tracking microglial behavior without altering the CNS environment. This has been particularly challenging during chronic neurodegeneration, where long-term changes must be tracked. The retina, a CNS organ amenable to non-invasive live imaging, offers a powerful system to visualize and characterize the dynamics of microglia activation during chronic disorders. This protocol outlines methods for long-term, in vivo imaging of retinal microglia, using confocal ophthalmoscopy (cSLO) and CX3CR1(GFP/+) reporter mice, to visualize microglia with cellular resolution. Also, we describe methods to quantify monthly changes in cell activation and density in large cell subsets (200-300 cells per retina). We confirm the use of somal area as a useful metric for live tracking of microglial activation in the retina by applying automated threshold-based morphometric analysis of in vivo images. We use these live image acquisition and analyses strategies to monitor the dynamic changes in microglial activation and microgliosis during early stages of retinal neurodegeneration in a mouse model of chronic glaucoma. This approach should be useful to investigate the contributions of microglia to neuronal and axonal decline in chronic CNS disorders that affect the retina and optic nerve.

Free-breathing myocardial T2* mapping using GRE-EPI and automatic non-rigid motion correction.

BackgroundMeasurement of myocardial T2* is becoming widely used in the assessment of patients at risk for cardiac iron overload. The conventional breath-hold, ECG-triggered, segmented, multi-echo gradient echo (MGRE) sequence used for myocardial T2* quantification is very sensitive to respiratory motion and may not be feasible in patients who are unable to breath-hold. We propose a free-breathing myocardial T2* mapping approach that combines a single-shot gradient-echo echo-planar imaging (GRE-EPI) sequence for T2*-weighted image acquisition with automatic non-rigid motion correction (MOCO) of respiratory motion between single-shot images.MethodsECG-triggered T2*-weighted images at different echo times were acquired by a black-blood, single-shot GRE-EPI sequence during free-breathing. A single image at a single TE is acquired in each heartbeat. Automatic non-rigid MOCO was applied to correct for in-plane respiratory motion before pixel-wise T2* mapping. In a total of 117 patients referred for clinical cardiac magnetic resonance exams, the free-breathing MOCO GRE-EPI sequence was compared to the breath-hold segmented MGRE approach. Image quality was scored independently by 2 experienced observers blinded to the particular image acquisition strategy. T2* measurements in the interventricular septum and in the liver were compared for the two methods in all cases with adequate image quality.ResultsT2* maps were acquired in all 117 patients using the breath-hold MGRE and the free-breathing MOCO GRE-EPI approaches, including 8 patients with myocardial iron overload and 25 patients with hepatic iron overload. The mean image quality of the free-breathing MOCO GRE-EPI images was scored significantly higher than that of the breath-hold MGRE images by both reviewers. Out of the 117 studies, 21 breath-hold MGRE studies (17.9 % of all the patients) were scored to be less than adequate or very poor by both reviewers, while only 2 free-breathing MOCO GRE-EPI studies were scored to be less than adequate image quality. In a comparative evaluation of the images with at least adequate quality, the intra-class correlation coefficients for myocardial and liver T2* were 0.868 and 0.986 respectively (p < 0.001), indicating that the T2* measured by breath-hold MGRE and free-breathing MOCO GRE-EPI were in close agreement. The coefficient of variation between the breath-hold and free-breathing approaches for myocardial and liver T2* were 9.88 % and 9.38 % respectively. Bland-Altman plots demonstrated good absolute agreement of T2* in the interventricular septum and the liver from the free-breathing and breath-hold approaches (mean differences -0.03 and 0.16 ms, respectively).ConclusionThe free-breathing approach described for T2* mapping using MOCO GRE-EPI enables accurate myocardial and liver T2* measurements and is insensitive to respiratory motion.

Quantification of iron in the non-human primate brain with diffusion-weighted magnetic resonance imaging

Pathological iron deposits in the brain, especially within basal ganglia, are linked to severe neurodegenerative disorders like Parkinson's disease. As iron induces local changes in magnetic susceptibility, its presence can be visualized with magnetic resonance imaging (MRI). The usual approach, based on iron induced changes in magnetic relaxation (T2/T2′), is often prone, however, to confounding artifacts and lacks specificity. Here, we propose a new method to quantify and map iron deposits using water diffusion MRI. This method is based on the differential sensitivity of two image acquisition schemes to the local magnetic field gradients induced by iron deposits and their cross-term with gradient pulses used for diffusion encoding. Iron concentration could be imaged and estimated with high accuracy in the brain cortex, the thalamus, the substantia nigra and the globus pallidus of macaques, showing iron distributions in agreement with literature. Additionally, iron maps could clearly show a dramatic increase in iron content upon injection of an UltraSmall Particle Iron Oxide (USPIO) contrast agent, notably in the cortex and the thalamus, reflecting regional differences in blood volume. The method will benefit clinical investigations on the effect of iron deposits in the brain or other organs, as iron deposits are increasingly seen as a biomarker for a wide range of diseases, notably, neurodegenerative diseases in the pre-symptomatic stage. It also has the potential for quantifying variations in blood volume induced by brain activation in fMRI studies using USPIOs.

Automated End-to-End Workflow for Precise and Geo-accurate Reconstructions using Fiducial Markers

Abstract. Photogrammetric computer vision systems have been well established in many scientific and commercial fields during the last decades. Recent developments in image-based 3D reconstruction systems in conjunction with the availability of affordable high quality digital consumer grade cameras have resulted in an easy way of creating visually appealing 3D models. However, many of these methods require manual steps in the processing chain and for many photogrammetric applications such as mapping, recurrent topographic surveys or architectural and archaeological 3D documentations, high accuracy in a geo-coordinate system is required which often cannot be guaranteed. Hence, in this paper we present and advocate a fully automated end-to-end workflow for precise and geoaccurate 3D reconstructions using fiducial markers. We integrate an automatic camera calibration and georeferencing method into our image-based reconstruction pipeline based on binary-coded fiducial markers as artificial, individually identifiable landmarks in the scene. Additionally, we facilitate the use of these markers in conjunction with known ground control points (GCP) in the bundle adjustment, and use an online feedback method that allows assessment of the final reconstruction quality in terms of image overlap, ground sampling distance (GSD) and completeness, and thus provides flexibility to adopt the image acquisition strategy already during image recording. An extensive set of experiments is presented which demonstrate the accuracy benefits to obtain a highly accurate and geographically aligned reconstruction with an absolute point position uncertainty of about 1.5 times the ground sampling distance.

A voxel-based morphometry comparison of the 3.0T ADNI-1 and ADNI-2 volumetric MRI protocols.

ObjectivesThe Alzheimer's Disease Neuroimaging Initiative 3.0T MRI image acquisition scheme changed between the original ADNI-1 grant and the two subsequent grants (ADNI-GO and ADNI-2). The aim of the current study was to investigate the compatibility of the 3.0T ADNI-1 and ADNI-2 T1-weighted volumes using voxel-based morphometry (VBM).MethodsT1-weighted images of 30 subjects were acquired using a 3T GE Signa HDx using the ADNI-1 and ADNI-2 T1-weighted volume sequences. Images were pre-processed and analysed using SPM8. Global grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) volumes were compared, as well as voxel-by-voxel differences in GM and WM.ResultsCorrelation coefficients and percentage differences for each tissue type between ADNI-1 and ADNI-2 were as follows: ((GM: intraclass correlation coefficient (ICC) = 0.86, ADNI-1 3.09% < ADNI-2) (WM: ICC = 0.91, ADNI-1 2.92% > ADNI-2) (CSF: ICC = 0.90, ADNI-1 1.94% > ADNI-2)). For ADNI-2, widespread increases in GM were found relative to ADNI-1 (cerebellum and pre-central gyrus), with localised decreases along the midline and temporal lobes. For ADNI-1, widespread increases in WM were found relative to ADNI-2 (cerebellum and pre-central gyrus), together with localised decreases in the temporal gyrus.ConclusionsThe widespread increase in GM and localised decrease in WM in ADNI-2 compared to ADNI-1 images suggests that the image acquisition protocols are not directly comparable using SPM-8. Total volumes of GM, WM and CSF also differed between the protocols in the following order of magnitude: GM > WM > CSF. This has implications for studies aiming to analyse images acquired using the ADNI-1 and ADNI-2 protocols under VBM. © 2014 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.