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arXiv2011

Low probability Bid-Bax reaction generates heterogeneity in apoptosis resistance of cancer and cancer stem cells

Variability in the tumorigenic potential among cancer cells within a tumor population is an unresolved fundamental issue in cancer biology. It is important to know whether cancer cells with higher tumorigenic potential, such as cancer stem cells, are only a small subpopulation. We attempt to address the question of variability in tumorigenic potential based on the heterogeneity in apoptosis resistance of cancer cells. We use stochastic differential equations and kinetic Monte Carlo simulations to explore the mechanisms that generate cell-to-cell variability in apoptosis resistance of cancer cells. In our model, a simplified scheme of apoptosis signaling reactions is developed focusing on the proapoptotic Bid-Bax reaction and its inhibition by Bcl-2 like antiapoptotic proteins. We show how a combination of low probability Bid-Bax reaction along with overexpressed reactant molecules allows specific killing of cancer cells, especially under targeted therapy such as Bcl-2 inhibition. This low probability Bid-Bax reaction protects normal cells from accidental apoptosis but generates cell-to-cell stochastic variability in apoptotic activation of cells equipped with overexpressed Bid and Bax molecules. We further demonstrate that cellular variations in Bcl-2 / Bax ratio, within a cancer cell population, can affect the intrinsic fluctuations arising from the stochastic Bid-Bax reaction and thereby provides a mechanism for origin of cells with higher tumorigenic potential. We discuss the implications of our results for cancer therapy, such as, optimal strategies to minimize stochastic fluctuations in cancer cell death.

q-bio.MN↗

arXiv2012

Quantifying admissible undersampling for sparsity-exploiting iterative image reconstruction in X-ray CT

Iterative image reconstruction (IIR) with sparsity-exploiting methods, such as total variation (TV) minimization, investigated in compressive sensing (CS) claim potentially large reductions in sampling requirements. Quantifying this claim for computed tomography (CT) is non-trivial, because both full sampling in the discrete-to-discrete imaging model and the reduction in sampling admitted by sparsity-exploiting methods are ill-defined. The present article proposes definitions of full sampling by introducing four sufficient-sampling conditions (SSCs). The SSCs are based on the condition number of the system matrix of a linear imaging model and address invertibility and stability. In the example application of breast CT, the SSCs are used as reference points of full sampling for quantifying the undersampling admitted by reconstruction through TV-minimization. In numerical simulations, factors affecting admissible undersampling are studied. Differences between few-view and few-detector bin reconstruction as well as a relation between object sparsity and admitted undersampling are quantified.

physics.med-ph↗

arXiv2011

Radiobiological investigations at tumor cell lines by exploiting chrono-biological aspects of chronological dose distributions

Using 31P-NMR spectroscopy the chronological behavior of the ATP-metabolism of the tumor spheroids C3H-MA, 9L-Gliome and the mono-layer L1210 has been analyzed via decrease of the β-peak. All three cell lines show characteristic periods, and a homeostatic control cannot be recognized. Essential components of these periods are circadian (i.e. one day), circa-semiseptan (i.e. 3.5 days) and circa-septan (i.e. one week). The determination of the survival fractions provides an optimum exploitation of radiation damages, when the ATP-concentration assumes a maximum value. This optimum is reached, when all three cycles exhibit the ATP maximum, which is only possible by accounting for the circa-septan rhythm. The goal of this study is to elaborate an optimal fractionation scheme with regard to the irradiation of tumors.

physics.med-ph↗

arXiv2012

Statistical characterization of tissue images for detection and classification of cervical precancers

Microscopic images from the biopsy samples of cervical cancer, the current "gold standard" for histopathology analysis, are found to be segregated into differing classes in their correlation properties. Correlation domains clearly indicate increasing cellular clustering in different grades of pre-cancer as compared to their normal counterparts. This trend manifests in the probabilities of pixel value distribution of the corresponding tissue images. Gradual changes in epithelium cell density are reflected well through the physically realizable extinction coefficients. Robust statistical parameters in the form of moments, characterizing these distributions are shown to unambiguously distinguish tissue types. These parameters can effectively improve the diagnosis and classify quantitatively normal and the precancerous tissue sections with a very high degree of sensitivity and specificity.

physics.med-ph↗

arXiv2013

Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI

Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space or/and in time. The performance of parallel imaging strongly depends on the reconstruction algorithm, which can proceed either in the original k-space (GRAPPA, SMASH) or in the image domain (SENSE-like methods). To improve the performance of the widely used SENSE algorithm, 2D- or slice-specific regularization in the wavelet domain has been deeply investigated. In this paper, we extend this approach using 3D-wavelet representations in order to handle all slices together and address reconstruction artifacts which propagate across adjacent slices. The gain induced by such extension (3D-Unconstrained Wavelet Regularized -SENSE: 3D-UWR-SENSE) is validated on anatomical image reconstruction where no temporal acquisition is considered. Another important extension accounts for temporal correlations that exist between successive scans in functional MRI (fMRI). In addition to the case of 2D+t acquisition schemes addressed by some other methods like kt-FOCUSS, our approach allows us to deal with 3D+t acquisition schemes which are widely used in neuroimaging. The resulting 3D-UWR-SENSE and 4D-UWR-SENSE reconstruction schemes are fully unsupervised in the sense that all regularization parameters are estimated in the maximum likelihood sense on a reference scan. The gain induced by such extensions is illustrated on both anatomical and functional image reconstruction, and also measured in terms of statistical sensitivity for the 4D-UWR-SENSE approach during a fast event-related fMRI protocol. Our 4D-UWR-SENSE algorithm outperforms the SENSE reconstruction at the subject and group levels (15 subjects) for different contrasts of interest (eg, motor or computation tasks) and using different parallel acceleration factors (R=2 and R=4) on 2x2x3mm3 EPI images.

stat.AP↗

arXiv2012

Controllability of 3D Low Reynolds Swimmers

In this article, we consider a swimmer (i.e. a self-deformable body) immersed in a fluid, the flow of which is governed by the stationary Stokes equations. This model is relevant for studying the locomotion of microorganisms or micro robots for which the inertia effects can be neglected. Our first main contribution is to prove that any such microswimmer has the ability to track, by performing a sequence of shape changes, any given trajectory in the fluid. We show that, in addition, this can be done by means of arbitrarily small body deformations that can be superimposed to any preassigned sequence of macro shape changes. Our second contribution is to prove that, when no macro deformations are prescribed, tracking is generically possible by means of shape changes obtained as a suitable combination of only four elementary deformations. Eventually, still considering finite dimensional deformations, we state results about the existence of optimal swimming strategies for a wide class of cost functionals.

math.AP↗

arXiv2012

Simultaneous measurement of quality factor and wavelength shift by phase shift microcavity ring down spectroscopy

Optical resonant microcavities with ultra high quality factors are widely used for biosensing. Until now, the primary method of detection has been based upon tracking the resonant wavelength shift as a function of biodetection events. One of the sources of noise in all resonant-wavelength shift measurements is the noise due to intensity fluctuations of the laser source. An alternative approach is to track the change in the quality factor of the optical cavity by using phase shift cavity ring down spectroscopy, a technique which is insensitive to the intensity fluctuations of the laser source. Here, using biotinylated microtoroid resonant cavities, we show simultaneous measurement of the quality factor and the wavelength shift by using phase shift cavity ring down spectroscopy. These measurements were performed for disassociation phase of biotin-streptavidin reaction. We found that the disassociation curves are in good agreement with the previously published results. Hence, we demonstrate not only the application of phase shift cavity ring down spectroscopy to microcavities in the liquid phase but also simultaneous measurement of the quality factor and the wavelength shift for the microcavity biosensors in the application of kinetics measurements.

physics.optics↗

arXiv2012

Synchronous phase-demodulation of high spatial frequency, concentric-rings, Placido fringe patterns

Here a synchronous phase-demodulation method for high spatial frequency (HSF), concentric-rings Placido fringe pattern is proposed. The earliest use of this concentric-rings pattern was to gauge non-spherical irregularities of the human cornea by Portuguese ophthalmologist Antonio Placido in 1880. Most modern corneal topographers use Placido patterns to test human cornea irregularities; a field of application of this paper. Another field of application of HSF conic-carrier fringe patterns is to test wavefronts using what may be called the Placido-Hartmann screen test. These screens would be formed by periodic concentric ring apertures. A Placido-Hartmann test would be sensitive to the radial slope of the wavefront under measurement. Finally as in the Hartmann-Shack test, one may use a radial lenslet array of toroidal-shaped lenses to test the radial slope of a wavefront at the focal plane. The main advantage of estimating the radial slope of a wavefront using a HSF Placido pattern is that a single radial slope image is sufficient to integrate the full wavefront shape.

physics.optics↗

arXiv2012

Techniques of Proton Radiotherapy: Transport Theory

These are notes for the lecture on Transport Theory in a one-week intensive course, "Techniques of Proton Radiotherapy". Topics are: Phase space diagrams: model beam line-effect of a scatterer-effect of a drift-the beam ellipse-phase space diagrams for the model beam line-emittance change in a drift-emittance change in a scatterer-phase space for a more realistic beam line-summary Miscellaneous topics: review of Gaussians-the Gaussian approximation to multiple Coulomb scattering (MCS)-relativistic single particle kinematics-completing the square-scattering power Fermi-Eyges theory: history-the basic theory-the beam ellipse-drawing the ellipse given the moments-ellipse examples-transporting the beam ellipse through a slab-emittance change in a drift-emittance change in a scatterer-differential form of the transport equations-equivalent sources-beam contained in the beam ellipse-summary Beam spreading in matter: theory of Preston and Koehler-generalization to heavy ions-experimental tests (Preston and Koehler, Phillips, Wong et al.)-summary Analytical geometry of the ellipse (appendix): tilted ellipse-transformation to principal frame-summary and explicit procedures-area enclosed by the ellipse

physics.med-ph↗

arXiv2012

From individual to population: Challenges in Medical Visualization

In this paper, we first give a high-level overview of medical visualization development over the past 30 years, focusing on key developments and the trends that they represent. During this discussion, we will refer to a number of key papers that we have also arranged on the medical visualization research timeline. Based on the overview and our observations of the field, we then identify and discuss the medical visualization research challenges that we foresee for the coming decade.

cs.GR↗

arXiv2012

High-power test results of a 3 GHz single-cell cavity

Compact, reliable and little consuming accelerators are required for the treatment of tumours with ions. TERA proposes the "cyclinac", composed of a high-frequency, fast-cycling linac which boosts the energy of the particles previously accelerated in a cyclotron. The dimensions of the linac can be reduced if high gradients are used. TERA initiated a high-gradient test program to understand the operational limit of such structures. The program foresees the design, prototyping and high-power test of several high-gradient structures operating at 3 and 5.7 GHz. The high-power tests of the 3 GHz single-cell cavity were completed in Winter 2012. The maximum BDR threshold measured for Emax of 170 MV/m and RF pulses of 2.5 μs was 3 x 10-6 bpp/m.

physics.acc-ph↗

arXiv2012

Resolution of Identity Crisis of Events in Pile-up

Mutually uncorrelated random discrete events, manifesting a common basic process, are examined often in terms of their occurrence rate as a function of one or more of their distinguishing attributes, such as measurements of photon spectrum as a function of energy. Such rate distributions obtained from the observed attribute values for an ensemble of events will correspond to the "true" distribution only if the event occurrence were {\it mutually exclusive}. However, due to finite resolution in such measurements, the problem of event {\it pile-up} is not only unavoidable, but also increases with event rate. Although extensive simulations to estimate the distortion due to pile-up in the observed rate distribution are available, no restoration procedure has yet been suggested. Here we present an elegant analytical solution to recover the underlying {\it true} distribution. Our method, based on Poisson statistics and Fourier transforms, is shown to perform as desired even when applied to distributions that are significantly distorted by pile-up. Our recipes for correction, as well as for prediction, of pile-up are expected to find ready applications in a wide variety of fields, ranging from high-energy physics to medical clinical diagnostics, and involving, but not limited to, measurements of count-rates and/or spectra of incident radiation using Charge Coupled Devices (CCDs) or other similar devices.

astro-ph.IM↗

arXiv2012

Model of cell response to α-particle radiation

Starting from a general equation for organism (or cell system) growth and attributing additional cell death rate (besides the natural rate) to therapy, we derive an equation for cell response to α radiation. Different from previous models that are based on statistical theory, the present model connects the consequence of radiation with the growth process of a biosystem and each variable or parameter has meaning regarding the cell evolving process. We apply this equation to model the dose response for α-particle radiation. It interprets the results of both high and low linear energy transfer (LET) radiations. When LET is high, the additional death rate is a constant, which implies that the localized cells are damaged immediately and the additional death rate is proportional to the number of cells present. While at low LET, the additional death rate includes a constant term and a linear term of radiation dose, implying that the damage to some cell nuclei has a time accumulating effect. This model indicates that the oxygen-enhancement ratio (OER) decreases while LET increases consistently.

physics.med-ph↗

arXiv2013

Diffusion pore imaging with generalized temporal gradient profiles

In porous material research, one main interest of nuclear magnetic resonance diffusion (NMR) experiments is the determination of the shape of pores. While it has been a longstanding question if this is in principle achievable, it has been shown recently that it is indeed possible to perform NMR-based diffusion pore imaging. In this work we present a generalization of these previous results. We show that the specific temporal gradient profiles that were used so far are not unique as more general temporal diffusion gradient profiles may be used. These temporal gradient profiles may consist of any number of 'short' gradient pulses, which fulfil the short-gradient approximation. Additionally, 'long' gradient pulses of small amplitude may be present, which can be used to fulfil the rephasing condition for the complete profile. Some exceptions exist. For example, classical q-space gradients consisting of two short gradient pulses of opposite sign cannot be used as the phase information is lost due to the temporal antisymmetry of this profile.

physics.med-ph↗

arXiv2013

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an l2-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and l1-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an l1-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this l1 inconsistency while simultaneously exploiting sparsity more optimally than through an l2 prior, we reformulate the reconstruction problem as a constrained formulation between a data term and and a sparsity prior consisting in an explicit bound on the l0 norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed l0 formulation significantly reduces modeling errors compared to the state-of-the-art l2 and l1 regularization approaches.

q-bio.QM↗

arXiv2012

Swallowing a cellular automaton pill: predicting drug release from a matrix tablet

Matrix tablets are drug delivery devices designed to release a drug in a controlled manner over an extended period of time. We develop a cellular automaton (CA) model for the dissolution and release of a water-soluble drug and excipient from a matrix tablet of water-insoluble polymer. Cells of the CA are occupied by drug, excipient, water or polymer and the CA updating rules simulate the dissolution of drug and excipient and the subsequent diffusion of the dissolved substances. In addition we simulate the possible fracture of brittle drug and excipient powders during the tablet compression and the melting of the polymer during a possible thermal curing process. Different stirring mechanisms that facilitate the transport of dissolved drug in the fluid in which the tablet is immersed are modeled in the water cells adjacent to the boundary of the tablet. We find that our simulations can reproduce experimental drug release profiles. Our simulation tool can be used to streamline the formulation and production of sustained release tablets.

physics.med-ph↗

arXiv2013

First-order convex feasibility algorithms for iterative image reconstruction in X-ray CT

Iterative image reconstruction (IIR) algorithms in Computed Tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this article, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for efficient algorithms for their solution -- thereby facilitating the IIR algorithm design process. An accelerated version of the Chambolle-Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization.

physics.med-ph↗

arXiv2012

Monitoring spike train synchrony

Recently, the SPIKE-distance has been proposed as a parameter-free and time-scale independent measure of spike train synchrony. This measure is time-resolved since it relies on instantaneous estimates of spike train dissimilarity. However, its original definition led to spuriously high instantaneous values for event-like firing patterns. Here we present a substantial improvement of this measure which eliminates this shortcoming. The reliability gained allows us to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. Additional new features include selective and triggered temporal averaging as well as the instantaneous comparison of spike train groups. In a second step, a causal SPIKE-distance is defined such that the instantaneous values of dissimilarity rely on past information only so that time-resolved spike train synchrony can be estimated in real-time. We demonstrate that these methods are capable of extracting valuable information from field data by monitoring the synchrony between neuronal spike trains during an epileptic seizure. Finally, the applicability of both the regular and the real-time SPIKE-distance to continuous data is illustrated on model electroencephalographic (EEG) recordings.

physics.data-an↗