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arXiv2014

Parallel MRI Reconstruction by Convex Optimization

In parallel magnetic resonance imaging (pMRI), to find a joint solution for the image and coil sensitivity functions is a nonlinear and nonconvex problem. A class of algorithms reconstruct sensitivity encoded images of the coils first followed by the magnitude only image reconstruction, e.g. GRAPPA. It is shown in this paper that, if only the magnitude image is reconstructed, there exists a convex solution space for the magnitude image and sensitivity encoded images. This solution space enables formulation of a regularized convex optimization problem and leads to a globally optimal and unique solution for the magnitude image reconstruction. Its applications to in-vivo MRI data sets result in superior reconstruction performance compared with other algorithms.

physics.med-ph↗

arXiv2014

Delivery of Liquid Metal to the Target Vessels as Vascular Embolic Agent to Starve Diseased Tissues or Tumors to Death

Tumor growth relies heavily on the continuous blood and nutrients supply. Theoretically, it is an ideal therapeutic way of killing tumor by only vascular embolization. However, most of the existing vascular embolic agents are still rather insufficient to fulfill the real clinical need due to the reasons like: incomplete filling of target vasculature, being easily washed away by blood or body solution, or just producing toxicity to tissues. Here from an alternative way, the body temperature liquid metal, a kind of soft and highly compliant material, was proposed for the first time as blood vessel embolization agent for tumor physical therapy. With its unique capability of easy phase transition between liquid and solid state and sub-cooling behavior, such material can be fluently injected into the tiny vessels including ending capillaries and fully block them. The in vitro cytotoxicity experiments were performed which showed that treating localized diseased tissues through liquid metal embolic agent is acceptable. Endowed with a high density, the liquid metal-filled vessels are highly visible under the CT scan, which offers the potential of diagnosis-treatment integration. To further demonstrate the new conceptual liquid metal vascular embolization therapy, several experiments on in vivo vasculatures of rabbit ears and mouse tails were performed to provide evidences of destroying the targeted tissues. To interpret the liquid metal starvation therapy effects, a theoretical model was established to simulate the tumor growth with zero, partial or complete filling of the metal agent inside the vessels. All the results support that, given appropriate administration, the liquid metal embolization is able to destruct the target regions and might starve the tumors to death through a relatively easy way. This study lays the foundation of a promising tumor starvation therapy in the coming time.

physics.med-ph↗

arXiv2014

Ventricular torsional relation to ventricular fiber arrangement

Left ventricular torsion from helically oriented myofibers is a key parameter of cardiac performance. Physicians observing heart motion on echocardiograms, during cardiac catheterization, or in the operating room, are impressed by the twisting or rotary motion of the left ventricle during systole. Conceptually, the heart has been treated as a pressure chamber. The rotary or torsional deformation has been poorly understood by basic scientists and has lacked clinical relevance. The aim of this paper attempts to discuss about this question: Is ventricular twisting related to ventricular fiber arrangement? That is dependent to an assumed model of the left ventricular structure.

physics.med-ph↗

arXiv2014

Applications of Lorentz force in medical acoustics: Lorentz force hydrophone, Lorentz Force Electrical Impedance Tomography, Imaging of shear waves induced by Lorentz force

The ability of the Lorentz force to link a mechanical displacement to an electrical current presents a strong interest for medical acoustics, and three applications were studied in this thesis. In the first part of this work, a hydrophone was developed for mapping the particle velocity of an acoustic field. This hydrophone was constructed using a thin copper wire and an external magnetic field. A model was elaborated to determine the relationship between the acoustic pressure and the measured electrical current, which is induced by Lorentz force when the wire vibrates in the acoustic field of an ultrasound transducer. The built prototype was characterized and its spatial resolution, frequency response, sensitivity, robustness and directivity response were investigated. An imaging method called Lorentz Force Electrical Impedance Tomography was also studied. In this method, a biological tissue is vibrated by ultrasound in a magnetic field, which induces an electrical current by Lorentz force. The electrical impedance of the tissue can be deduced from the measurement of the current. This technique was applied for imaging a gelatin phantom, a beef muscle sample, and a thermal lesion in a chicken breast sample. This showed the method may be useful for providing additional contrast to conventional ultrasound imaging. Finally, this thesis demonstrated that shear waves can be generated in soft tissues using Lorentz force. This work was performed by applying an electrical current with two electrodes in a soft solid placed in a magnetic field. Shear waves were observed in gelatin phantom and liver sample. The speed of the shear waves were used to compute elasticity and their source to map the electrical conductivity of the samples.

physics.med-ph↗

arXiv2014

Simulation of Cone Beam CT System Based on Monte Carlo Method

Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established based on Monte Carlo program and validated against the measurement. The BEAMnrc program was adopted to the KV x-ray tube. Both IOURCE-13 and ISOURCE-24 were chosen to simulate the path of beam particles. The measured Percentage Depth Dose (PDD) and lateral dose profiles under 1cm water were compared with the dose calculated by DOSXYZnrc program. The calculated PDD was better than 1% within the depth of 10cm. More than 85% points of calculated lateral dose profiles was within 2%. The correct CBCT system model helps to improve CBCT image quality for dose verification in ART and assess the CBCT image concomitant dose risk.

physics.med-ph↗

arXiv2014

Full-wave nonlinear ultrasound simulation on distributed clusters with applications in high-intensity focused ultrasound

Model-based treatment planning and exposimetry for high-intensity focused ultrasound (HIFU) requires the numerical simulation of nonlinear ultrasound propagation through heterogeneous and absorbing media. This is a computationally demanding problem due to the large distances travelled by the ultrasound waves relative to the wavelength of the highest frequency harmonic. Here, the k-space pseudospectral method is used to solve a set of coupled partial differential equations equivalent to a generalised Westervelt equation. The model is implemented in C++ and parallelised using the message passing interface (MPI) for solving large-scale problems on distributed clusters. The domain is partitioned using a 1D slab decomposition, and global communication is performed using a sparse communication pattern. Operations in the spatial frequency domain are performed in transposed space to reduce the communication burden imposed by the 3D fast Fourier transform. The performance of the model is evaluated using grid sizes up to 4096 x 2048 x 2048 grid points distributed over a cluster using up to 1024 compute cores. Given the global nature of the gradient calculation, the model shows good strong scaling behaviour, with a speed-up of 1.7x whenever the number of cores is doubled. This means large-scale simulations can be distributed across high numbers of cores on a cluster to minimise execution times with a relatively small computational overhead. The efficacy of the model is demonstrated by simulating the ultrasound beam pattern for a HIFU sonication of the kidney.

physics.med-ph↗

arXiv2014

Metal artifact reduction based on the combined prior image

Metallic implants introduce severe artifacts in CT images, which degrades the image quality. It is an effective method to reduce metal artifacts by replacing the metal affected projection with the forward projection of a prior image. How to find a good prior image is the key of this class methods, and numerous algorithms have been proposed to address this issue recently. In this work, by using image mutual correlation, pixels in the original reconstructed image or linear interpolation corrected image, which are less affected by artifacts, are selected to build a combined image. Thereafter, a better prior image is generated from the combined image by using tissue classification. The results of three patients' CT images show that the proposed method can reduce metal artifacts remarkably.

physics.med-ph↗

arXiv2014

Unsupervised Spike Sorting Based on Discriminative Subspace Learning

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

cs.CV↗

arXiv2014

A new variable for SRS plan quality evaluation based on normal tissue sparing: The Effect of Prescription Isodose Levels

Objectives: A new dosimetric variable, dose dropping speed (DDS), was proposed and used to evaluate normal tissue sparing among stereotactic radiosurgery (SRS) plans with different prescription isodose lines. Methods: Forty plans were generated for 8 intracranial SRS cases, prescribing to isodose levels (IDLs) ranging from 50% to 90% in 10% increments. Whilst maintaining similar coverage and conformity, plans at different IDLs were evaluated in terms of normal tissue sparing using the proposed DDS. The DDS was defined as the greater decay coefficient in a double exponential decay fit of the dose drop-off outside the PTV, which models the steep portion of the drop-off. Provided that the prescription dose covers the whole PTV, a greater DDS indicates better normal tissue sparing. Results: Among all plans, the DDS was found the lowest for the prescription at 90% IDL and the highest for the prescription at 60% or 70%. Beam profile slope change in penumbra and its field size dependence were explored and given as the physical basis of the findings. Conclusions: A variable was proposed for SRS plan quality evaluation. Using this measure, prescriptions at 60% and 70% IDLs were found to provide best normal tissue sparing. Advances in knowledge: A new variable was proposed based on which normal tissue sparing was quantitatively evaluated, comparing different prescription IDLs in SRS.

physics.med-ph↗

arXiv2016

A New Proton CT Scanner

The design, construction, and preliminary testing of a second generation proton CT scanner is presented. All current treatment planning systems at proton therapy centers use X-ray CT as the primary imaging modality for treatment planning to calculate doses to tumor and healthy tissues. One of the limitations of X-ray CT is in the conversion of X-ray attenuation coefficients to relative (proton) stopping powers, or RSP. This results in more proton range uncertainty, larger target volumes and therefore, more dose to healthy tissues. To help improve this, we present a novel scanner capable of high dose rates, up to 2~MHz, and large area coverage, 20~x~24~cm$^2$, for imaging an adult head phantom and reconstructing more accurate RSP values.

physics.ins-det↗

arXiv2014

Neutron Therapy in the 21st Century

The question of whether or not neutron therapy works has been answered. It is a qualified yes, as is the case with all of radiation therapy. But, neutron therapy has not kept pace with the rest of radiation therapy in terms of beam delivery techniques. Modern photon and proton based external beam radiotherapy routinely implements image-guidance, beam intensity-modulation and 3-dimensional treatment planning. The current iteration of fast neutron radiotherapy does not. Addressing these deficiencies, however, is not a matter of technology or understanding, but resources. The future of neutron therapy lies in better understanding the interaction processes of radiation with living tissue. A combination of radiobiology and computer simulations is required in order to optimize the use of neutron therapy. The questions that need to be answered are: Can we connect the macroscopic with the microscopic? What is the optimum energy? What is the optimum energy spectrum? Can we map the sensitivity of the various tissues of the human body and use that knowledge to our advantage? And once we gain a better understanding of the above radiobiological issues will we be able to capitalize on this understanding by precisely and accurately delivering fast neutrons in a manner comparable to what is now possible with photons and protons? This presentation will review the accomplishments to date. It will then lay out the questions that need to be answered for neutron therapy to truly be a 21st Century therapy.

physics.med-ph↗

arXiv2014

Nuclear halo of a 177 MeV proton beam in water: theory, measurement and parameterization

The dose distribution of a monoenergetic pencil beam in water consists of an electromagnetic "core", a "halo" from charged nuclear secondaries, and a much larger "aura" from neutral secondaries. These regions overlap, but each has distinct spatial characteristics. We have measured the core/halo using a 177MeV test beam offset in a water tank. The beam monitor was a fluence calibrated plane parallel ionization chamber (IC) and the field chamber, a dose calibrated Exradin T1, so the dose measurements are absolute (MeV/g/p). We performed depth-dose scans at ten displacements from the beam axis ranging from 0 to 10cm. The dose spans five orders of magnitude, and the transition from halo to aura is clearly visible. We have performed model-dependent (MD) and model-independent (MI) fits to the data. The MD fit separates the dose into core, elastic/inelastic nuclear, nonelastic nuclear and aura terms, and achieves a global rms measurement/fit ratio of 15%. The MI fit uses cubic splines and the same ratio is 9%. We review the literature, in particular the use of Pedroni's parametrization of the core/halo. Several papers improve on his Gaussian transverse distribution of the halo, but all retain his T(w), the radial integral of the depth-dose multiplying both the core and halo terms and motivating measurements with large "Bragg peak chambers" (BPCs). We argue that this use of T(w), which by its definition includes energy deposition by nuclear secondaries, is incorrect. T(w) should be replaced in the core term, and in at least part of the halo, by a purely electromagnetic mass stopping power. BPC measurements are unnecessary, and irrelevant to parameterizing the pencil beam.

physics.med-ph↗

arXiv2014

Traveling Wave MRI at 21.1 T: Propagation below Cut-off for Ultrahigh Field Vertical Bore System

At high magnetic field strengths (> 4 T), the propagation wave vector of the excitation field B1 can no longer be ignored as the wavelength becomes commensurate or smaller than the imaging field of view (FOV), particularly for high dielectric media. The emergence of this propagation wave vector renders the excitation field variant in both time and space. In this paper, the propagation of RF excitation waves in a high field vertical NMR system is demonstrated for the first time with an appropriate screened dielectric waveguide excited by a simple loop coil to enable below cutoff propagation for imaging in the far field. Uniquely, aqueous samples provide the high permittivity required to modify the cut-off requirements of this transmission system. Theory and simulations corroborate the observed propagating modes field patterns. The ease of construction and implementation of this setup permits use in a variety of high field systems. At a minimum, this design provides a larger FOV that is limited primarily by the three-dimensional linearity of the gradient coil. More critically, it also opens up the use of multimode excitation for selective nulling or maximum excitation of the FOV along the direction of wave propagation.

physics.med-ph↗

arXiv2014

The Effects of Long Pulse Durations and Radiation Damping in Selective Inversion Recovery Experiments

Long pulse durations necessary in selective inversion recovery (SIR) experiments along with radiation damping (RD) introduce difficulties in quantitative nuclear magnetic resonance measurements, such as those that allow for the determination of a sample's characteristics, including the rates that govern magnetization transfer. Because of these influences, the assumption of perfect inversion is invalid. In this work, we present data that demonstrates that long pulse durations as well as RD cause difficulties in SIR experiments performed on simple one-spin systems, indicating that they will be problematic for multiple-spin systems as well. These results emphasize the importance of understanding the evolution of magnetization for all time points throughout an experiment used in quantitative NMR measurements. Furthermore, experimental parameters must be chosen carefully and understood completely.

physics.med-ph↗

arXiv2014

Using Topological Data Analysis for diagnosis pulmonary embolism

Pulmonary Embolism (PE) is a common and potentially lethal condition. Most patients die within the first few hours from the event. Despite diagnostic advances, delays and underdiagnosis in PE are common.To increase the diagnostic performance in PE, current diagnostic work-up of patients with suspected acute pulmonary embolism usually starts with the assessment of clinical pretest probability using plasma d-Dimer measurement and clinical prediction rules. The most validated and widely used clinical decision rules are the Wells and Geneva Revised scores. We aimed to develop a new clinical prediction rule (CPR) for PE based on topological data analysis and artificial neural network. Filter or wrapper methods for features reduction cannot be applied to our dataset: the application of these algorithms can only be performed on datasets without missing data. Instead, we applied Topological data analysis (TDA) to overcome the hurdle of processing datasets with null values missing data. A topological network was developed using the Iris software (Ayasdi, Inc., Palo Alto). The PE patient topology identified two ares in the pathological group and hence two distinct clusters of PE patient populations. Additionally, the topological netowrk detected several sub-groups among healthy patients that likely are affected with non-PE diseases. TDA was further utilized to identify key features which are best associated as diagnostic factors for PE and used this information to define the input space for a back-propagation artificial neural network (BP-ANN). It is shown that the area under curve (AUC) of BP-ANN is greater than the AUCs of the scores (Wells and revised Geneva) used among physicians. The results demonstrate topological data analysis and the BP-ANN, when used in combination, can produce better predictive models than Wells or revised Geneva scores system for the analyzed cohort

physics.med-ph↗

arXiv2014

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity

We derive a two-layer multiplex Kuramoto model from weakly coupled Wilson-Cowan oscillators on a cortical network with inhibitory synaptic time delays. Depending on the coupling strength and a phase shift parameter, related to cerebral blood flow and GABA concentration, respectively, we numerically identify three macroscopic phases: unsynchronized, synchronized, and chaotic dynamics. These correspond to physiological background-, epileptic seizure-, and resting-state cortical activity, respectively. We also observe frequency suppression at the transition from resting-state to seizure activity.

q-bio.NC↗

arXiv2014

Simultaneous submicrometric 3D imaging of the micro-vascular network and the neuronal system in a mouse spinal cord

Defaults in vascular (VN) and neuronal networks of spinal cord are responsible for serious neurodegenerative pathologies. Because of inadequate investigation tools, the lacking knowledge of the complete fine structure of VN and neuronal systems is a crucial problem. Conventional 2D imaging yields incomplete spatial coverage leading to possible data misinterpretation, whereas standard 3D computed tomography imaging achieves insufficient resolution and contrast. We show that X-ray high-resolution phase-contrast tomography allows the simultaneous visualization of three-dimensional VN and neuronal systems of mouse spinal cord at scales spanning from millimeters to hundreds of nanometers, with neither contrast agent nor a destructive sample-preparation. We image both the 3D distribution of micro-capillary network and the micrometric nerve fibers, axon-bundles and neuron soma. Our approach is a crucial tool for pre-clinical investigation of neurodegenerative pathologies and spinal-cord-injuries. In particular, it should be an optimal tool to resolve the entangled relationship between VN and neuronal system.

physics.med-ph↗

arXiv2014

Neural Hypernetwork Approach for Pulmonary Embolism diagnosis

This work introduces an integrative approach based on Q-analysis with machine learning. The new approach, called Neural Hypernetwork, has been applied to a case study of pulmonary embolism diagnosis. The objective of the application of neural hyper-network to pulmonary embolism (PE) is to improve diagnose for reducing the number of CT-angiography needed. Hypernetworks, based on topological simplicial complex, generalize the concept of two-relation to many-body relation. Furthermore, Hypernetworks provide a significant generalization of network theory, enabling the integration of relational structure, logic and analytic dynamics. Another important results is that Q-analysis stays close to the data, while other approaches manipulate data, projecting them into metric spaces or applying some filtering functions to highlight the intrinsic relations. A pulmonary embolism (PE) is a blockage of the main artery of the lung or one of its branches, frequently fatal. Our study uses data on 28 diagnostic features of 1,427 people considered to be at risk of PE. The resulting neural hypernetwork correctly recognized 94% of those developing a PE. This is better than previous results that have been obtained with other methods (statistical selection of features, partial least squares regression, topological data analysis in a metric space).

physics.med-ph↗