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arXiv2018

BPE and computer-extracted parenchymal enhancement for breast cancer risk, response monitoring, and prognosis

Functional behavior of breast cancer - representing underlying biology - can be analyzed using MRI. The most widely used breast MR imaging protocol is dynamic contrast-enhanced T1-weighted imaging. The cancer enhances on dynamic contrast-enhanced MR imaging because the contrast agent leaks from the leaky vessels into the interstitial space. The contrast agent subsequently leaks back into the vascular space, creating a washout effect. The normal parenchymal tissue of the breast can also enhance after contrast injection. This enhancement generally increases over time. Typically, a radiologist assesses this background parenchymal enhancement (BPE) using the Breast Imaging Reporting and Data System (BI-RADS). According to the BI-RADS, BPE refers to the volume of enhancement and the intensity of enhancement and is divided in four incremental categories: minimal, mild, moderate, and marked. Researchers have developed semi-automatic and automatic methods to extract properties of BPE from MR images. For clarity, in this syllabus the BI-RADS definition will be referred to as BPE, whereas the computer-extracted properties will not. Both BPE and computer-extracted parenchymal enhancement properties have been linked to screening and diagnosis, hormone status and age, risk of development of breast cancer, response monitoring, and prognosis.

physics.med-ph↗
arXiv2018

Validation of a track repeating algorithm for intensity modulated Carbon therapy with GEANT4

The Fast Dose Calculator (FDC), a track repeating algorithm Monte Carlo method was initially developed for proton therapy. The validation for proton therapy has been demonstrated in a previous work. This method can be expanded to ion applications. Our purpose of this paper is to validate the FDC for carbon therapy. We compare the 3D dose distributions and dose-volume-histograms (DVH) for carbon calculated by FDC with a full Monte Carlo method, GEANT 4. 19 patients in total will be discussed, including 3 patients of prostate, 5 of brain, 3 of head and neck, 4 of lung and 4 of spine. We use gamma-index technique to analyse dose distributions and we do dosimetric analysis for DVH, a more direct and informative quantity for planning system assessment. The FDC calculations of both quantities agree with GEANT4. The gamma-index passing rates of all patients discussed in this paper are above 90% with the criterion 1%/1 mm, above 98% with the criterion 2%/2 mm and over 99.9% with the criterion 3%/3 mm. The Root Mean Square (RMS) of percent difference of dosimetric indices D02, D05, D50, D95 and D98 are 0.75%, 0.70%, 0.79%, 0.83% and 0.76%. And all the difference are allowed for clinical use.

physics.med-ph↗
arXiv2018

Computational Study of Pulmonary Flow Patterns after Repair of Transposition of Great Arteries

Patients that undergo the arterial switch operation (ASO) to repair transposition of great arteries (TGA) can develop abnormal pulmonary trunk morphology with significant long-term complications. In this study, cardiovascular magnetic resonance was combined with computational fluid dynamics to investigate the impact of the post-operative layout on the pulmonary flow patterns. Three ASO patients were analyzed and compared to a normal control. Results showed the presence of anomalous shear layer instabilities, vortical and helical structures, and turbulent-like states in all patients, particularly as a consequence of the unnatural curvature of the pulmonary bifurcation. Streamlined, mostly laminar flow was instead found in the healthy subject. These findings shed light on the correlation between the post-ASO anatomy and the presence of altered flow features, and may be useful to improve surgical planning as well as the long-term care of TGA patients.

physics.med-ph↗
arXiv2018

Ultrafast Magnetic Resonance Imaging

We propose a radical advance in Magnetic Resonance Imaging. MRI remains slow because it requires successive applications of magnetic field gradients to encode for spatial location. Parallel MRI accelerates imaging by permitting undersampling of k-space using multiple detectors, each with a unique spatial sensitivity to the radio field emitted by the object. This is called spatial sensitivity encoding. A fourfold undersampling means a fourfold acceleration, however a five-fold undersampling cannot be reconstructed. This is because too much reliance is placed on spatial sensitivity encoding, and spatial sensitivity encoding is less efficient than gradient encoding when the detectors are large. On the contrary, we hypothesized that when very large numbers of very small detectors are deployed, it would render spatial sensitivity encoding efficient, and would allow complete elimination of gradient reversals and therefore extremely rapid MR imaging. Since each detector receives all of the signal from all of the object all of the time, signal is expected to be high, and each detector is predicted to receive signal of the same order of magnitude as one large detector in conventional MRI. Moreover, the elimination of gradients removes the major source of electrical noise. Unexpectedly, therefore, we anticipate that signal-to-noise (SNR) will be high. By means of a detailed simulation, in which the exact Hertzian radio field is simulated for each of 32x32x32 voxels interacting with each of 1024 detector loops, we demonstrate that 3-dimensional MR images can indeed be acquired very quickly. Nevertheless, we also simulated imaging in the presence of unforeseen sources of noise, and found that image reconstruction is resistant to noise, even with unrealistically low SNR values. In summary, high quality volumetric MRI is likely to be achievable in milliseconds.

physics.med-ph↗
arXiv2018

A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts

Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the endocardium of the right ventricle, the interventricular septum and the outflow tracts. We also carried out electrophysiological simulations involving these structures and with different fiber configurations. In particular, we built a modelling pipeline for creating patient-specific volumetric meshes of biventricular geometries, including the outflow tracts, and subsequently simulate the electrical wavefront propagation in outflow tract ventricular arrhythmias with different origins for the ectopic focus. The resulting simulations with the proposed rule-based method showed a very good agreement with clinical parameters such as the 10 ms isochrone ratio in a cohort of nine patients suffering from this type of arrhythmia. The developed modelling pipeline confirms its potential for an in silico identification of the site of origin in outflow tract ventricular arrhythmias before clinical intervention.

physics.med-ph↗
arXiv2018

Comparison of Sinogram-based Iterative Reconstruction with Compressed Sensing Techniques in X-ray CT

Performing X-ray computed tomography (CT) examinations with less radiation has recently received increasing interest: in medical imaging this means less (potentially harmful) radiation for the patient; in non-destructive testing of materials/objects such as testing jet engines, the redution of the number of projection angles (which for large objects is in general high) leads to a substantial decreasing of the experiment time. In the experiment, less radiation is usually achieved by either (1) reducing the radiation dose used at each projection angle or (2) using sparse view X-ray CT, which means significantly less projection angles are used during the examination. In this work, we study the performance of the recently proposed sinogram-based iterative reconstruction algorithm in sparse view X-ray CT and show that it provides, in some cases, reconstruction accuracy better than that obtained by some of the Total Variation regularization techniques. The provided accuracy is obtained with computation times comparable to other techniques. An important feature of the sinogram-based iterative reconstruction algorithm is that it has no parameters to be set.

physics.med-ph↗
arXiv2018

Higher order spectral analysis of ECG signals

Higher Order Spectral (HOS) analysis is often applied effectively to analyze many bio-medical signals to detect nonlinear and non-Gaussian processes. One of the most basic HOS methods is the bispectral estimation, which extracts the degree of quadratic phase coupling between individual frequency components of a nonlinear signal. Most of the studies in this direction as applied to ECG signals are on the conventional, long duration (up to 24 hours) Heart Rate Variability (HRV) data. We report results of our studies on short duration ECG data of 60 seconds using power spectral and bispectral parameters. We analyze 60 healthy cases and 60 cases of patients diagnosed with four different heart diseases, Bundle Branch Block, Cardiomyopathy, Dysrhythmia and Myocardial Infarction. From the power spectra of these data sets we observe that the pulse frequency around 1 Hz has maximum power for all normal ECG data while in all disease cases, the power in the pulse frequency is suppressed and gets distributed among higher frequencies. The bicoherence indices computed show that the pulse frequency has strong quadratic phase coupling with a large number of higher frequencies in healthy cases indicating nonlinearity in the underlying dynamical processes. The loss or decrease of the phase coupling with pulse frequency is a clear indicator of abnormal conditions. In specific cases, bicoherence studies coupled with spectral filter, suggest ECG for Myocardial Infarction has noisy components while in Dysrhythmia, power is mostly at high frequencies with strong quadratic coupling indicating much more irregularity and complexity than normal ECG signals. In addition to serving as indicators suggestive of abnormal conditions of the heart, the detailed analysis presented can lead to a wholistic understanding of normal heart dynamics and its variations during onset of diseases.

physics.med-ph↗
arXiv2018

Fast, Precise Myelin Water Quantification using DESS MRI and Kernel Learning

Purpose: To investigate the feasibility of myelin water content quantification using fast dual-echo steady-state (DESS) scans and machine learning with kernels. Methods: We optimized combinations of steady-state (SS) scans for precisely estimating the fast-relaxing signal fraction ff of a two-compartment signal model, subject to a scan time constraint. We estimated ff from the optimized DESS acquisition using a recently developed method for rapid parameter estimation via regression with kernels (PERK). We compared DESS PERK ff estimates to conventional myelin water fraction (MWF) estimates from a longer multi-echo spin-echo (MESE) acquisition in simulation, in vivo, and ex vivo studies. Results: Simulations demonstrate that DESS PERK ff estimators and MESE MWF estimators achieve comparable error levels. In vivo and ex vivo experiments demonstrate that MESE MWF and DESS PERK ff estimates are quantitatively comparable measures of WM myelin water content. To our knowledge, these experiments are the first to demonstrate myelin water images from a SS acquisition that are quantitatively similar to conventional MESE MWF images. Conclusion: Combinations of fast DESS scans can be designed to enable precise ff estimation. PERK is well-suited for ff estimation. DESS PERK ff and MESE MWF estimates are quantitatively similar measures of WM myelin water content.

physics.med-ph↗
arXiv2018

Prediction of Coronary Heart Disease Using Routine Blood Tests

Background --The objective of this study was to examine the association of routine blood test results with coronary heart disease (CHD) risk, to incorporate them into coronary prediction models and to compare the discrimination properties of this approach with other prediction functions. Methods and Results --This work was designed as a retrospective, single-center study of a hospital-based cohort. The 5060 CHD patients (2365 men and 2695 women) were 1 to 97 years old at baseline with 8 years (2009-2017) of medical records, 5051 health check-ups and 5075 cases of other diseases. We developed a two-layer Gradient Boosting Decision Tree(GBDT) model based on routine blood data to predict the risk of coronary heart disease, which could identify 86% of people with coronary heart disease. We built a dataset with 15,000 routine blood tests results. Using this dataset, we trained the two-layer GBDT model to classify healthy status, coronary heart disease and other diseases. As a result of the classification after machine learning, we found that the sensitivity of detecting the health data was approximately 93% for all data, and the sensitivity of detecting CHD was 93% for disease data that included coronary heart disease. On this basis, we further visualized the correlation between routine blood results and related data items, and there was an obvious pattern in health and coronary heart disease in all data presentations, which can be used for clinical reference. Finally, we briefly analyzed the results above from the perspective of pathophysiology. Conclusions --Routine blood data provides more information about CHD than what we already know through the correlation between test results and related data items. A simple coronary disease prediction model was developed using a GBDT algorithm, which will allow physicians to predict CHD risk in patients without overt CHD.

physics.med-ph↗
arXiv2018

Design of Intra-body Nano-communication Network for Future Nano-medicine

Intra-body communication is a method that utilizes the human body as a broadcast biological medium for electromagnetic signals to inter-connect wireless body sensors. Study of the collaboration between electromagnetic waves and human cells has gained importance in recent years leading towards developing and establishing new novel concept which is the idea of nano-communications using nano-networks to form in-vivo communication that are aimed to offer wireless communication between interior nano-sensors. The emergent of this advanced unprecedented prospective approach of deploying the in vivo communication concept in the health sector is considered as a key potential technology that enhances healthcare delivery and enables the progress of future applications and services.

eess.SP↗
arXiv2018

Pulsed Schlieren Imaging of Ultrasonic Haptics and Levitation using Phased Arrays

Ultrasonic acoustic fields have recently been used to generate haptic effects on the human skin as well as to levitate small sub-wavelength size particles. Schlieren imaging and background-oriented schlieren techniques can be used for acoustic wave pattern and beam shape visualization. These techniques exploit variations in the refractive index of a propagation medium by applying refractive optics or cross-correlation algorithms of photographs of illuminated background patterns. Here both background-oriented and traditional schlieren systems are used to visualize the regions of the acoustic power involved in creating dynamic haptic sensations and dynamic levitation traps. We demonstrate for the first time the application of back-ground-oriented schlieren for imaging ultrasonic fields in air. We detail our imaging apparatus and present improved algorithms used to visualize these phenomena that we have produced using multiple phased arrays. Moreover, to improve imaging, we leverage an electronically controlled, high-output LED which is pulsed in synchrony with the ultrasonic carrier frequency.

physics.med-ph↗
arXiv2018

Survival prediction using ensemble tumor segmentation and transfer learning

Segmenting tumors and their subregions is a challenging task as demonstrated by the annual BraTS challenge. Moreover, predicting the survival of the patient using mainly imaging features, while being a desirable outcome to evaluate the treatment of the patient, it is also a difficult task. In this paper, we present a cascaded pipeline to segment the tumor and its subregions and then we use these results and other clinical features together with image features coming from a pretrained VGG-16 network to predict the survival of the patient. Preliminary results with the training and validation dataset show a promising start in terms of segmentation, while the prediction values could be improved with further testing on the feature extraction part of the network.

q-bio.QM↗
arXiv2018

Dynamic vortical flow profile quantitatively characterizes mitral valvular-left ventricular hemodynamic coupling: In vivo analysis by dynamic 3D enstrophy mapping from 4D Flow MRI

Vortical blood flow in the human left ventricular (LV) inflow initiates from the mitral valve (MV) and evolves within the LV during diastolic E-filling. Hence, vortical flow links MV and LV hemodynamics. This study sought to elucidate and quantitatively characterize the in vivo 3D dynamics of LV vortical flow over E-filling and relation to MV-LV hemodynamic coupling using 4D Flow MRI flow field. 34 healthy volunteers and 5 example patients underwent 4D Flow MRI. Vortical blood flow evolution was mapped in the LV over E-wave using enstrophy density. A new dimensionless profile PMV-LV was derived as a function of both MV vortex formation time (VFT) and LV volumetric enstrophy density. Results reveal that 3D vortical flow evolution in the healthy LV follows a bi-phasic behavior with a vortical growth phase followed by a vortical decay phase. In healthy LVs studied, the PMV-LV profile showed that the vortical growth and decay phases are characterized by a vortical growth time T_growth= 1.23+/-0.25, growth rate α=0.80+/-0.17, decay time T_decay= 0.96+/-0.39 and decay rate \b{eta}=-1.02+/-0.49. Distinctly altered parameters were found in the pilot patients studied. The derived PMV-LV profile quantitatively characterizes MV-LV hemodynamic coupling by vortical flow dynamics. Results herein unravel new insights into cardiac physiology and could enable a novel standardized methodology to study MV-LV hemodynamic coupling and association to cardiac function in health and disease.

physics.med-ph↗
arXiv2018

Quantification of Trabeculae Inside the Heart from MRI Using Fractal Analysis

Left ventricular non-compaction (LVNC) is a rare cardiomyopathy (CMP) that should be considered as a possible diagnosis because of its potential complications which are heart failure, ventricular arrhythmias, and embolic events. For analysis cardiac functionality, extracting information from the Left ventricular (LV) is already a broad field of Medical Imaging. Different algorithms and strategies ranging that is semiautomated or automated has already been developed to get useful information from such a critical structure of heart. Trabeculae in the heart undergoes difference changes like solid from spongy. Due to failure of this process left ventricle non-compaction occurred. In this project, we will demonstrate the fractal dimension (FD) and manual segmentation of the Magnetic Resonance Imaging (MRI) of the heart that quantify amount of trabeculae inside the heart. The greater the value of fractal dimension inside the heart indicates the greater complex pattern of the trabeculae in the heart.

q-bio.QM↗
arXiv2018

Observation of magnetic structural universality using transverse NMR relaxation

Transverse NMR relaxation from spins diffusing through a random magnetic medium is sensitive to its structure on a mesoscopic scale. In particular, this results in the time-dependent relaxation rate. We show analytically and numerically that this rate approaches the long-time limit in a power-law fashion, with the exponent reflecting the disorder class of mesoscopic magnetic structure. The spectral line shape acquires a corresponding non-analytic power law singularity at zero frequency. We experimentally detect a change in the dynamical exponent as a result of the transition into a maximally random jammed state characterized by hyperuniform correlations.

cond-mat.soft↗
arXiv2018

Discussing the discrepancy between analytical calculations and the observed biological effectiveness in proton boron capture therapy (pbct)

A work recently published experimentally demonstrates an increase in the radiobiological efficacy of clinical proton beams when a tumour is treated in the presence of a concentration of 11B. The paper, for the first time, demonstrates the potential role of the p+11B to 3α (for brevity, p-B) reaction in the biological enhancement of proton therapy effectiveness. The work reports robust experimental data in terms of clonogenic cell survival and chromosomal aberrations and unambiguously shows the presence of an enhancement when cells were exposed to a clinical proton beam subject to treatment with sodium boroncaptate (BSH). Moreover, the greater occurrence of complex-type chromosomal exchanges points to the effect as due radiation of a LET (Linear Energy Transfer) greater than that of protons alone, possibly the alpha particles generated by the reaction. At the same time, we emphasized that analytical calculations, performed on the basis of the well-known total production cross section data, are not able to explain the effect in a macroscopic way, i.e. solely in terms of a trivial increase in the total dose released in the cells by the alpha-particles. In this paper, thanks to simulations and analytical calculations, we will discuss the theoretically expected alpha particle yield and the corresponding LET and RBE (Relative Biological Effectiveness) increase related to the 11B presence. We conclude that a mere calculation based on the classical concepts of integral Dose, and average LET and RBE cannot be used to justify the observed radiobiological phenomena. We, therefore, suggest that micro- and nano-dosimetric aspects must be taken into account.

physics.med-ph↗
arXiv2018

Joint bi-modal image reconstruction of DOT and XCT with an extended Mumford-Shah functional

Feature similarity measures are indispensable for joint image reconstruction in multi-modality medical imaging, which enable joint multi-modal image reconstruction (JmmIR) by communication of feature information from one modality to another, and vice versa. In this work, we establish an image similarity measure in terms of image edges from Tversky's theory of feature similarity in psychology. For joint bi-modal image reconstruction (JbmIR), it is found that this image similarity measure is an extended Mumford-Shah functional with a-priori edge information proposed previously from the perspective of regularization approach. This image similarity measure consists of Hausdorff measures of the common and different parts of image edges from both modalities. By construction, it posits that two images are more similar if they have more common edges and fewer unique/distinctive features, and will not force the nonexistent structures to be reconstructed when applied to JbmIR. With the Gamma-approximation of the JbmIR functional, an alternating minimization method is proposed for the JbmIR of diffuse optical tomography and x-ray computed tomography. The performance of the proposed method is evaluated by three numerical phantoms. It is found that the proposed method improves the reconstructed image quality by more than 10% compared to single modality image reconstruction (SmIR) in terms of the structural similarity index measure (SSIM)

eess.IV↗