Philip G Batchelor

King's College London, London, ENG, United Kingdom

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Publications (43)75.77 Total impact

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    ABSTRACT: In vivo imaging of cardiac 3D fibre architecture is still a practical and methodological challenge. However it potentially provides important clinical insights, for example leading to a better understanding of the pathophysiology and the follow up of ventricular remodelling after therapy. Recently, the acquisition of 2D multi-slice Diffusion Tensor Images (DTI) of the in vivo human heart has become feasible, yielding a limited number of slices with relatively poor signal-to-noise ratios. In this article, we present a method to analyse the fibre architecture of the left ventricle (LV) using shape-based transformation into a normalised Prolate Spheroidal coordinate frame. Secondly, a dense approximation scheme of the complete 3D cardiac fibre architecture of the LV from a limited number of DTI slices is proposed and validated using ex vivo data. Those two methods are applied in vivo to a group of healthy volunteers, on which 2D DTI slices of the LV were acquired using a free-breathing motion compensated protocol. Results demonstrate the advantages of using curvilinear coordinates both for the anaylsis and the interpolation of cardiac DTI information. Resulting in vivo fibre architecture was found to agree with data from previous studies on ex vivo hearts.
    Medical image analysis 03/2013; · 3.09 Impact Factor
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    ABSTRACT: Compressed sensing (CS) has been demonstrated to accelerate MRI acquisitions by reconstructing sparse images of good quality from highly undersampled data. Motion during MR scans can cause inconsistencies in k-space data, resulting in strong motion artifacts in the reconstructed images. For CS to be useful in these applications, motion correction techniques need to be combined with the undersampled reconstruction. Recently, joint motion correction and CS approaches have been proposed to partially correct for effects of motion. However, the main limitation of these approaches is that they can only correct for affine deformations. In this work, we propose a novel motion corrected CS framework for free-breathing dynamic cardiac MRI that incorporates a general motion correction formulation directly into the CS reconstruction. This framework can correct for arbitrary affine or nonrigid motion in the CS reconstructed cardiac images, while simultaneously benefiting from highly accelerated MR acquisition. The application of this approach is demonstrated both in simulations and in vivo data for 2D respiratory self-gated free-breathing cardiac CINE MRI, using a golden angle radial acquisition. Results show that this approach allows for the reconstruction of respiratory motion corrected cardiac CINE images with similar quality to breath-held acquisitions. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 08/2012; · 3.27 Impact Factor
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    ABSTRACT: Compressed sensing has been of great interest to speed up the acquisition of MR images. The k-t group sparse (k-t GS) method has recently been introduced for dynamic MR images to exploit not just the sparsity, as in compressed sensing, but also the spatial group structure in the sparse representation. k-t GS achieves higher acceleration factors compared to the conventional compressed sensing method. However, it assumes a spatial structure in the sparse representation and it requires a time consuming hard-thresholding reconstruction scheme. In this work, we propose to modify k-t GS by incorporating prior information about the sorted intensity of the signal in the sparse representation, for a more general and robust group assignment. This approach is referred to as group sparse reconstruction using intensity-based clustering. The feasibility of the proposed method is demonstrated for static 3D hyperpolarized lung images and applications with both dynamic and intensity changes, such as 2D cine and perfusion cardiac MRI, with retrospective undersampling. For all reported acceleration factors the proposed method outperforms the original compressed sensing method. Improved reconstruction over k-t GS method is demonstrated when k-t GS assumptions are not satisfied. The proposed method was also applied to cardiac cine images with a prospective sevenfold acceleration, outperforming the standard compressed sensing reconstruction. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 05/2012; · 3.27 Impact Factor
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    ABSTRACT: The aim of this article is to describe a novel hardware perfusion phantom that simulates myocardial first-pass perfusion allowing comparisons between different MR techniques and validation of the results against a true gold standard. MR perfusion images were acquired at different myocardial perfusion rates and variable doses of gadolinium and cardiac output. The system proved to be sensitive to controlled variations of myocardial perfusion rate, contrast agent dose, and cardiac output. It produced distinct signal intensity curves for perfusion rates ranging from 1 to 10 mL/mL/min. Quantification of myocardial blood flow by signal deconvolution techniques provided accurate measurements of perfusion. The phantom also proved to be very reproducible between different sessions and different operators. This novel hardware perfusion phantom system allows reliable, reproducible, and efficient simulation of myocardial first-pass MR perfusion. Direct comparison between the results of image-based quantification and reference values of flow and myocardial perfusion will allow development and validation of accurate quantification methods. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 04/2012; · 3.27 Impact Factor
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    ABSTRACT: The purpose of this study is to enable high spatial resolution voxel-wise quantitative analysis of myocardial perfusion in dynamic contrast-enhanced cardiovascular MR, in particular by finding the most favorable quantification algorithm in this context. Four deconvolution algorithms-Fermi function modeling, deconvolution using B-spline basis, deconvolution using exponential basis, and autoregressive moving average modeling -were tested to calculate voxel-wise perfusion estimates. The algorithms were developed on synthetic data and validated against a true gold-standard using a hardware perfusion phantom. The accuracy of each method was assessed for different levels of spatial averaging and perfusion rate. Finally, voxel-wise analysis was used to generate high resolution perfusion maps on real data acquired from five patients with suspected coronary artery disease and two healthy volunteers. On both synthetic and perfusion phantom data, the B-spline method had the highest error in estimation of myocardial blood flow. The autoregressive moving average modeling and exponential methods gave accurate estimates of myocardial blood flow. The Fermi model was the most robust method to noise. Both simulations and maps in the patients and hardware phantom showed that voxel-wise quantification of myocardium perfusion is feasible and can be used to detect abnormal regions. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 02/2012; · 3.27 Impact Factor
  • Proceedings of the International Society for Magnetic Resonance in Medicine 05/2011;
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    ABSTRACT: Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved.
    Physics in Medicine and Biology 03/2011; 56(7):N99-114. · 2.70 Impact Factor
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    ABSTRACT: Long acquisition times are still a limitation for many applications of magnetic resonance imaging (MRI), specially in 3-D and dynamic imaging. Several undersampling reconstruction techniques have been proposed to overcome this problem. These techniques are based on acquiring less samples than specified by the Nyquist criterion and estimating the nonacquired data by using some sort of prior information. Most of these reconstruction methods use prior information based on estimations of the pixel intensities of the images and therefore they are prone to introduce spatial or temporal blurring. Instead of using the pixel intensities, we propose to use information that allows us to sort the pixels of an image from darkest to brightest. The set of order relations which sort the pixels of an image has been called intensity order. The intensity order of an image can be estimated from low-resolution images, adjacent slices in volumetric acquisitions, temporal correlation in dynamic sequences or from prior reconstructions. Our technique for reconstruction using intensity order (TRIO) consists of looking for an image that satisfies the intensity order and minimizes the discrepancy between the acquired and reconstructed data. Results show that TRIO can effectively reconstruct 2-D-cine cardiac MR images (under-sampling factor of 4), estimating correctly the temporal evolution of the objects. Furthermore, TRIO is used as a second stage reconstruction after reconstructing with other techniques, keyhole, sliding window and k-t BLAST, to estimate the order information. In all cases the images are improved by TRIO.
    IEEE transactions on medical imaging. 03/2011; 30(8):1566-76.
  • M Usman, C Prieto, T Schaeffter, P G Batchelor
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    ABSTRACT: Compressed sensing (CS) is a data-reduction technique that has been applied to speed up the acquisition in MRI. However, the use of this technique in dynamic MR applications has been limited in terms of the maximum achievable reduction factor. In general, noise-like artefacts and bad temporal fidelity are visible in standard CS MRI reconstructions when high reduction factors are used. To increase the maximum achievable reduction factor, additional or prior information can be incorporated in the CS reconstruction. Here, a novel CS reconstruction method is proposed that exploits the structure within the sparse representation of a signal by enforcing the support components to be in the form of groups. These groups act like a constraint in the reconstruction. The information about the support region can be easily obtained from training data in dynamic MRI acquisitions. The proposed approach was tested in two-dimensional cardiac cine MRI with both downsampled and undersampled data. Results show that higher acceleration factors (up to 9-fold), with improved spatial and temporal quality, can be obtained with the proposed approach in comparison to the standard CS reconstructions.
    Magnetic Resonance in Medicine 03/2011; 66(4):1163-76. · 3.27 Impact Factor
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    Journal of Cardiovascular Magnetic Resonance 01/2011; · 4.44 Impact Factor
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    Journal of Cardiovascular Magnetic Resonance 01/2011; 13:1-2. · 4.44 Impact Factor
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    ABSTRACT: This paper describes an acquisition and reconstruction strategy for cardiac cine MRI that does not require the use of electrocardiogram or breath holding. The method has similarities with self-gated techniques as information about cardiac and respiratory motion is derived from the imaging sequence itself; here, by acquiring the center k-space line at the beginning of each segment of a balanced steady-state free precession sequence. However, the reconstruction step is fundamentally different: a generalized reconstruction by inversion of coupled systems is used instead of conventional gating. By correcting for nonrigid cardiac and respiratory motion, generalized reconstruction by inversion of coupled systems (GRICS) uses all acquired data, whereas gating rejects data acquired in certain motion states. The method relies on the processing and analysis of the k-space central line data: local information from a 32-channel cardiac coil is used in order to automatically extract eigenmodes of both cardiac and respiratory motion. In the GRICS framework, these eigenmodes are used as driving signals of a motion model. The motion model is defined piecewise, so that each cardiac phase is reconstructed independently. Results from six healthy volunteers, with various slice orientations, show improved image quality compared to combined respiratory and cardiac gating.
    Magnetic Resonance in Medicine 05/2010; 63(5):1247-57. · 3.27 Impact Factor
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    ABSTRACT: The anterior commissure is a critical interhemispheric pathway in animals, yet its connections in humans are not clearly understood. Its distribution has shown to vary greatly between species, and it is thought that in humans it may convey axons from a larger territory than previously thought. The aim was to use an anatomical mapping tool to look at the anterior commissure fibres and to compare the distribution findings with published anatomical understanding. Two different diffusion-weighted imaging data sets were acquired from eight healthy subjects using a 3 Tesla MR scanner with 32 gradient directions. Diffusion tensor imaging tractography was performed, and the anterior commissure fibres were selected using three-dimensional regions of interest. Distribution of the fibres was observed by means of registration with T2-weighted images. The fibre field similarity maps were produced for five of the eight subjects by comparing each subject's fibres to the combined map of the five data sets. Fibres were shown to lead into the temporal lobe and towards the orbitofrontal cortex in the majority of subjects. Fibres were also distributed to the parietal or occipital lobes in all five subjects in whom the anterior commissure was large enough for interhemispheric fibres to be tracked through. The fibre field similarity maps highlighted areas where the local distances of fibre tracts were displayed for each subject compared to the combined bundle map. The anterior commissure may play a more important role in interhemispheric communication than currently presumed by conveying axons from a wider territory, and the fibre field similarity maps give a novel approach to quantifying and visualising characteristics of fibre tracts.
    MAGMA Magnetic Resonance Materials in Physics Biology and Medicine 03/2010; 23(5-6):399-408. · 1.86 Impact Factor
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    ABSTRACT: Cardiac perfusion modelling using ARMA systems is studied. ARMA is a generalization of a recently proposed exponential approximation technique, which was shown to exhibit better performance than the widely used truncated singular value decomposition method. Experiments demonstrate that ARMA achieves results as accurate as the those obtained using the exponential approximation, but it its at the same time less sensitive to additive noise and model order selection.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010 · 4.63 Impact Factor
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    ABSTRACT: In vivo imaging of the cardiac 3D fibre architecture is still a challenge, but it would have many clinical applications, for instance to better understand pathologies and to follow up remodelling after therapy. Recently, cardiac MRI enabled the acquisition of Diffusion Tensor images (DTI) of 2D slices. We propose a method for the complete 3D reconstruction of cardiac fibre architecture in the left ventricular myocardium from sparse in vivo DTI slices. This is achieved in two steps. First we map non-linearly the left ventricular geometry to a truncated ellipsoid. Second, we express coordinates and tensor components in Prolate Spheroidal System, where an anisotropic Gaussian kernel regression interpolation is performed. The framework is initially applied to a statistical cardiac DTI atlas in order to estimate the optimal anisotropic bandwidths. Then, it is applied to in vivo beating heart DTI data sparsely acquired on a healthy subject. Resulting in vivo tensor field shows good correlation with literature, especially the elevation (helix) angle transmural variation. To our knowledge, this is the first reconstruction of in vivo human 3D cardiac fibre structure. Such approach opens up possibilities in terms of analysis of the fibre architecture in patients.
    Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2010; 13(Pt 1):418-25.
  • Book of Abstracts, International Society in Magnetic Resonance in Medicine (ISMRM'10); 01/2010
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    ABSTRACT: Whole-heart isotropic nonangulated cardiac magnetic resonance (CMR) is becoming an important protocol in simplifying MRI, since it reduces the need of cumbersome planning of angulations. However the acquisition times of whole-heart MRI are prohibitive due to the large fields of view (FOVs) and the high spatial resolution required for depicting small structures and vessels. To address this problem, we propose a three-dimensional (3D) acquisition scheme that combines Cartesian sampling in the readout direction with an undersampled radial scheme in the phase-encoding plane. Different undersampling patterns were investigated in combination with an iterative sensitivity encoding (SENSE) reconstruction and a 32-channel cardiac coil. Noise amplification maps were calculated to compare the performance of the different patterns using iterative SENSE reconstruction. The radial phase-encoding (RPE) scheme was implemented on a clinical MR scanner and tested on phantoms and healthy volunteers. The proposed method exhibits better image quality even for high acceleration factors (up to 12) in comparison to Cartesian acquisitions.
    Magnetic Resonance in Medicine 09/2009; 62(5):1331-7. · 3.27 Impact Factor
  • Book of Abstracts, European Society of Magnetic Resonance in Medicine (ESMRMB) 26th Annual Scientific Meeting; 01/2009
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    ABSTRACT: Delayed contrast-enhanced magnetic resonance imaging (DCE-MRI) provides prognostic information by delineating regions of myocardial scar. The mechanism of this delayed enhancement in myocardial infarctions (MIs) is hypothesized to result from altered kinetics and changes in the volumes of distribution in the myocardium. Pharmacokinetic models with two and three compartments were fitted to the concentration-time curves of dynamic contrast-enhanced MRI data obtained from five patients with known MI. Furthermore, the parameter stability was investigated in simulations for the two different models. The transfer constants and volumes of distribution showed a good correlation with imaging findings on early and delayed contrast-enhanced MRI. The two compartment model showed higher parameter stability. The three compartment model allows a more in-depth quantification of myocardial scarring. These models have the potential to improve the diagnosis of myocardial pathologies involving scar, with differing kinetics and volumes of distribution such as infarction or cardiomyopathy.
    Magnetic Resonance in Medicine 12/2008; 60(6):1524-30. · 3.27 Impact Factor
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    ABSTRACT: We propose a new framework to propagate the labels in a heart atlas to the cardiac MRI images for ventricle segmentations based on image registrations. The method employs the anatomical information from the atlas as priors to constrain the initialisation between the atlas and the MRI images using region based registrations. After the initialisation which minimises the possibility of local misalignments, a fluid registration is applied to fine-tune the labelling in the atlas to the detail in the MRI images. The heart shape from the atlas does not have to be representative of that of the segmented MRI images in terms of morphological variations of the heart in this framework. In the experiments, a cadaver heart atlas and a normal heart atlas were used to register to in-vivo data for ventricle segmentation propagations. The results have shown that the segmentations based on the proposed method are visually acceptable, accurate (surface distance against manual segmentations is 1.0 ± 1.0 mm in healthy volunteer data, and 1.6 ± 1.8 mm in patient data), and reproducible (0.7 ± 1.0 mm) for in-vivo cardiac MRI images. The experiments also show that the new initialisation method can correct the local misalignments and help to avoid producing unrealistic deformations in the nonrigid registrations with 21% quantitative improvement of the segmentation accuracy.
    Proc SPIE 04/2008;

Publication Stats

820 Citations
75.77 Total Impact Points

Institutions

  • 2001–2013
    • King's College London
      • Division of Imaging Sciences and Biomedical Engineering
      London, ENG, United Kingdom
  • 2012
    • Guy's and St Thomas' NHS Foundation Trust
      • Department of Imaging Sciences and Biomedical Engineering
      Londinium, England, United Kingdom
  • 2005–2007
    • University College London
      • • Centre for Medical Image Computing
      • • Department of Medical Physics and Bioengineering
      Londinium, England, United Kingdom
  • 2002–2003
    • The King's College
      Charlotte, North Carolina, United States