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arXiv2019

Keratoconus Recognition Using A Parameter Set Determined from IOP-Matched Scenario

PURPOSE: Among the current practices for keratoconus recognition using biomechanical parameters from Corvis ST, matching intra-ocular pressure (IOP) is often required to eliminate the biasing influence; as a result, the combined biomechanical parameters determined from IOP-unmatched scenario possibly bring in confounding influence. This paper was therefore designed to introduce a novel compatible parameter set (CPS) determined from IOP-matched scenario, hopefully could show its compatibility and superiority for recognizing keratoconus in both IOP-matched and not scenarios. METHODS: A total of 335 eyes were included. Among them, 70 eyes were used to determined CPS by forward logistics regression, 62 eyes were used to validate CPS in IOP-matched scenario, and resting 203 eyes were used to validate CPS in IOP-unmatched scenario. To analyze its superiority, CPS was also compared with other two reported Biomechanical Indexes (aCBI and DCR) in both scenarios. Receiver operating characteristic curves (ROC), accuracy, FI, sensitivity and specificity were used to access and compare the performance of these three parameter sets in both scenarios. RESULTS: The resulting CPS was comprised of only 3 biomechanical parameters: DA Ratio Max 1mm (DRM1), the first applanation time (AT1) and an energy loading parameter (Eload). In the IOP-matched validation, the area under ROC (AUC) reached 95.73%, with an accuracy of 95.2%, sensitivity of 93.5% and specificity of 96.8% (leave one out cross-validation). All these indicators reached 96.54%, 95.1%, 95.6% and 94.6% respectively, in the IOP-unmatched validation (leave one out cross-validation). Surprisingly, CPS performed better than other two parameter sets on a whole. CONCLUSIONS: The parameter set determined from IOP-matched scenario indeed exhibit its superiority for differentiation of keratoconus and normal corneas, regardless of IOP-matched or not.

physics.med-ph↗

arXiv2019

SMS MUSSELS: A Navigator-free Reconstruction for Simultaneous MultiSlice Accelerated MultiShot Diffusion Weighted Imaging

Purpose: To introduce a novel reconstruction method for simultaneous multi-slice (SMS) accelerated multi shot diffusion weighted imaging (ms-DWI). Methods: SMS acceleration using blipped CAIPI schemes have been proposed to speed up the acquisition of ms-DWIs. The reconstruction of the above data requires (i) phase compensation to combine data from different shots and (ii) slice unfolding to separate the data of different slices. The traditional approach is to first estimate the phase maps corresponding to each shot from a navigator or from the slice-aliased individual shot data. The phase maps are subsequently fed to a iterative reconstruction scheme to recover the slice unfolded DWIs. We propose a novel reconstruction method to jointly recover the slice-unfolded k-space data of the multiple shots. The proposed reconstruction is enabled by the low-rank property inherent in the k-space samples of a ms-DW acquisition. Specifically, we recover the missing samples of the multi-shot acquisition by enforcing a low-rank penalty on the block-Hankel matrix formed by the k-space data of each shot for each slice. The joint recovery of the slice-unfolded k-space data is then performed using a SENSE-based slice-unfolding subject to the low-rank constraint. The proposed joint recovery scheme is tested on simulated and in-vivo data and compared to similar un-navigated methods at slice acceleration factors of 2 and 3. Results: Our experiments show effective slice unaliasing and successful recovery of DWIs with minimal phase artifacts using the proposed method. The performance is comparable to existing methods at low acceleration factors and better than existing methods as the acceleration factor increase. Conclusion: For the slice acceleration factors considered in this study, the proposed method can successfully recover DWIs from SMS-accelerated ms-DWI acquisitions.

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arXiv2019

Quantitative electron spectroscopy of $^{125}$I over an extended energy range

Auger electrons emitted after nuclear decay have potential application in targeted cancer therapy. For this purpose it is important to know the Auger electron yield per nuclear decay. In this work we measure the ratio of the number of conversion electrons (emitted as part of the nuclear decay process) and the number of Auger electrons (emitted as part of the atomic relaxation process after the nuclear decay) for the case of $^{125}$I. Results are compared with Monte-Carlo type simulations of the relaxation cascade using the BrIccEmis code. With the appropriate choice of parameters this program describes the observed spectra quite well over the whole energy range.

physics.med-ph↗

arXiv2019

Dynamic fluence map sequencing using piecewise linear leaf position functions

Within the setting of intensity modulated radiation therapy (IMRT) and the fully continuous version of IMRT called volumetric modulated radiation therapy (VMAT), we consider the problem of matching a given fluence map as well as possible in limited time by the use of a linear accelerator (linac) with a multi-leaf collimator (MLC). We introduce two modeling strategies to manage the nonconvexity and the associated local minima of this problem. The first is the use of linear splines to model the MLC leaf positions as functions of time. The second is a progressively controllable smooth model (instead of a step function) of how the leaves block the fluence radiation. We propose a two part solution: an outer loop that optimizes the dose rate pattern over time, and an inner loop that given a dose rate pattern optimizes the leaf trajectories.

physics.med-ph↗

arXiv2019

Build-A-FLAIR: Synthetic T2-FLAIR Contrast Generation through Physics Informed Deep Learning

Purpose: Magnetic resonance imaging (MRI) exams include multiple series with varying contrast and redundant information. For instance, T2-FLAIR contrast is based upon tissue T2 decay and the presence of water, also present in T2- and diffusion-weighted contrasts. T2-FLAIR contrast can be hypothetically modeled through deep learning models trained with diffusion- and T2-weighted acquisitions. Methods: Diffusion-, T2-, T2-FLAIR-, and T1-weighted brain images were acquired in 15 individuals. A convolutional neural network was developed to generate a T2-FLAIR image from other contrasts. Two datasets were withheld from training for validation. Results: Inputs with physical relationships to T2-FLAIR contrast most significantly impacted performance. The best model yielded results similar to acquired T2-FLAIR images, with a structural similarity index of 0.909, and reproduced pathology excluded from training. Synthetic images qualitatively exhibited lower noise and increased smoothness compared to acquired images. Conclusion: This suggests that with optimal inputs, deep learning based contrast generation performs well with creating synthetic T2-FLAIR images. Feature engineering on neural network inputs, based upon the physical basis of contrast, impacts the generation of synthetic contrast images. A larger, prospective clinical study is needed.

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arXiv2019

Decoupling of Two Closely Located Dipoles by a Single Passive Scatterer for Ultra-High Field MRI

We report decoupling of two closely located resonant dipole antennas dedicated for ultra-high field magnetic resonance imaging (MRI). We show that a scatterer slightly raised over the plane of antennas grants a sufficient decoupling even for antennas separated by very small gap (below 1/30 of the wavelength). We compare the operation of two decoupling scatterers. One of them is a shortcut resonant dipole and another is a split-loop resonator (SLR). Previously, we have shown that the SLR offers a wider operational band than the dipole and the same level of decoupling. However, it was so for an array in free space. The presence of the body phantom drastically changes the decoupling conditions. Moreover, the requirement to minimize the parasitic scattering from the decoupling element into the body makes the decoupling dipole much more advantageous compared to the SLR.

physics.med-ph↗

arXiv2019

Drug delivery from microcapsules: how can we estimate the release time?

Predicting the release performance of a drug delivery device is an important challenge in pharmaceutics and biomedical science. In this paper, we consider a multi-layer diffusion model of drug release from a composite spherical microcapsule into an external surrounding medium. Based on this model, we present two approaches that provide useful indicators of the release time, i.e. the time required for the drug-filled capsule to be depleted. Both approaches make use of temporal moments of the drug concentration versus time curve at the centre of the capsule, which provide useful insight into the timescale of the process and can be computed exactly without explicit calculation of the full transient solution of the multi-layer diffusion model. The first approach, which uses the zeroth and first temporal moments only, provides simple algebraic expressions involving the various parameters in the model (e.g. layer diffusivities, mass transfer coefficients, partition coefficients) to characterize the release time while the second approach yields an asymptotic estimate of the release time that depends on consecutive higher moments. Through several test cases, we show that both approaches provide a computationally-cheap and useful measure to compare \textit{a priori} the release time of different composite microcapsule configurations.

physics.med-ph↗

arXiv2019

Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock

Objective: Predict individual septic children's personalized physiologic responses to vasoactive titrations by training a Recurrent Neural Network (RNN) using EMR data. Materials and Methods: This study retrospectively analyzed EMR of patients admitted to a pediatric ICU from 2009 to 2017. Data included charted time series vitals, labs, drugs, and interventions of children with septic shock treated with dopamine, epinephrine, or norepinephrine. A RNN was trained to predict responses in heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial pressure (MAP) to 8,640 titrations during 652 septic episodes and evaluated on a holdout set of 3,883 titrations during 254 episodes. A linear regression model using titration data as its sole input was also developed and compared to the RNN model. Evaluation methods included the correlation coefficient between actual physiologic responses and RNN predictions, mean absolute error (MAE), and area under the receiver operating characteristic curve (AUC). Results: The actual physiologic responses displayed significant variability and were more accurately predicted by the RNN model than by titration alone (r=0.20 vs r=0.05, p<0.01). The RNN showed MAE and AUC improvements over the linear model. The RNN's MAEs associated with dopamine and epinephrine were 1-3% lower than the linear regression model MAE for HR, SBP, DBP, and MAP. Across all vitals vasoactives, the RNN achieved 1-19% AUC improvement over the linear model. Conclusion: This initial attempt in pediatric critical care to predict individual physiologic responses to vasoactive dose changes in children with septic shock demonstrated an RNN model showed some improvement over a linear model. While not yet clinically applicable, further development may assist clinical administration of vasoactive medications in children with septic shock.

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arXiv2019

Model reduction methodology for computational simulations of endovascular repair

Endovascular aneurysm repair (EVAR) is a current alternative treatment for thoracic and abdominal aortic aneurysms, but is still sometimes compromised by possible complications such as device migration or endoleaks. In order to assist clinicians in preventing these complications, finite element analysis (FEA) is a promising tool. However, the strong material and geometrical nonlinearities added to the complex multiple contacts result in costly finite-element models. To reduce this computational cost, we establish here an alternative and systematic methodology to simplify the computational simulations of stent-grafts (SG) based on FEA. The model reduction methodology relies on equivalent shell models with appropriate geometrical and mechanical parameters. It simplifies significantly the contact interactions but still shows very good agreement with a complete reference finite-element model. Finally, the computational time for EVAR simulations is reduced of a factor 6 to 10. An application is shown for the deployment of a SG during thoracic endovascular repair, showing that the developed methodology is both effective and accurate to determine the final position of the deployed SG inside the aneurysm.

physics.med-ph↗

arXiv2019

Detection of perfusion ROI as a quality control in perfusion analysis

In perfusion analysis automated approaches for image processing is preferable due to reduce time-consuming tasks for radiologists. Assessment of perfusion results quality is important step in development of algorithms for automated processing. One of them is an assessment of perfusion maps quality based on detection of perfusion ROI.

physics.med-ph↗

arXiv2019

3-D Motion Correction for Volumetric Super-Resolution Ultrasound (SR-US) Imaging

Motion during image acquisition can cause image degradation in all medical imaging modalities. This is particularly relevant in 2-D ultrasound imaging, since out-of-plane motion can only be compensated for movements smaller than elevational beamwidth of the transducer. Localization based super-resolution imaging creates even a more challenging motion correction task due to the requirement of a high number of acquisitions to form a single super-resolved frame. In this study, an extension of two-stage motion correction method is proposed for 3-D motion correction. Motion estimation was performed on high volumetric rate ultrasound acquisitions with a handheld probe. The capability of the proposed method was demonstrated with a 3-D microvascular flow simulation to compensate for handheld probe motion. Results showed that two-stage motion correction method reduced the average localization error from 136 to 18 micrometres.

physics.med-ph↗

arXiv2019

Simultaneous Acoustic Trapping and Imaging of Microbubbles at Clinically Relevant Flow Rates

Mechanisms for non-invasive target drug delivery using microbubbles and ultrasound have attracted growing interest. Microbubbles can be loaded with a therapeutic payload and tracked via ultrasound imaging to selectively release their payload at ultrasound-targeted locations. In this study, an ultrasonic trapping method is proposed for simultaneously imaging and controlling the location of microbubbles in flow by using acoustic radiation force. Targeted drug delivery methods are expected to benefit from the use of the ultrasonic trap, since trapping will increase the MB concentration at a desired location in human body. The ultrasonic trap was generated by using an ultrasound research system UARP II and a linear array transducer. The trap was designed asymmetrically to produces a weaker radiation force at the inlet of the trap to further facilitate microbubble entrance. A pulse sequence was generated that can switch between a long duration trapping waveform and short duration imaging waveform. High frame rate plane wave imaging was chosen for monitoring trapped microbubbles at 1 kHz. The working principle of the ultrasonic trap was explained and demonstrated in an ultrasound phantom by injecting SonoVue microbubbles flowing at 80 mL/min flow rate in a 3.5 mm diameter vessel.

physics.med-ph↗

arXiv2019

Coupling of Wideband Impulses Generated by Granular Chains into Liquids

An ultrasonic transducer technology to generate wideband impulses using a one-dimensional chain of spheres was previously presented. The Hertzian contact between the spheres causes the nonlinearity of the system to increase, which transforms high amplitude narrowband sinusoidal input into a train of wideband impulses. Generation of short duration ultrasonic pulses is desirable both in diagnostic and therapeutic ultrasound. Nevertheless, the biggest challenge in terms of adaptation to biomedical ultrasound is the coupling of the ultrasonic energy into biological tissue. An analytical model was created to address the coupling issue. Effect of the matching layer was modelled as a flexible thin plate clamped from the edges. Model was verified against hydrophone measurements. Different coupling materials, such as glass, aluminium, acrylic, silicon rubber, and vitreous carbon, was analysed with this model. Results showed that soft matching layers such as acrylic and rubber inhibit the generation of higher order harmonics. Between the hard matching materials, vitreous carbon achieved the best results due to its acoustic impedance.

physics.med-ph↗

arXiv2019

Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis

Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between radiographs with minimal and clinical post-processing, and to compare the differences in bone characteristics between controls and subjects with knee osteoarthritis or medial tibial bone marrow lesions (BMLs). Tibial bone density and texture was evaluated from radiographs with both minimal and clinical post-processing in 109 subjects with and without osteoarthritis. Bone texture was evaluated using fractal signature analysis. Significant correlations (p<0.001) were found in all regions (between 0.94 and 0.97) for calibrated bone density between radiographs with minimal and clinical post-processing. Correlations varied between 0.51 and 0.97 (p<0.001) for FD_Ver texture variable and between -0.10 and 0.97 for FD_Hor. Bone density and texture were different (p<0.05) between controls and subjects with osteoarthritis or BMLs mainly in medial tibial regions. When classifying healthy and osteoarthritic subjects using a machine learning-based elastic net model with bone characteristics, area under the receiver operating characteristics (ROCAUC) curve was 0.77. For classifying controls and subjects with BMLs, ROCAUC was 0.85. In conclusion, differences in bone density and texture can be assessed from knee radiographs when using minimal post-processing.

physics.med-ph↗

arXiv2019

3-D Super-Resolution Ultrasound (SR-US) Imaging using a 2-D Sparse Array with High Volumetric Imaging Rate

Super-resolution ultrasound imaging has been so far achieved in 3-D by mechanically scanning a volume with a linear probe, by co-aligning multiple linear probes, by using multiplexed 3-D clinical ultrasound systems, or by using 3-D ultrasound research systems. In this study, a 2-D sparse array was designed with 512 elements according to a density-tapered 2-D spiral layout and optimized to reduce the sidelobes of the transmitted beam profile. High frame rate volumetric imaging with compounded plane waves was performed using two synchronized ULA-OP 256 systems. Localization-based 3-D super-resolution images of two touching sub-wavelength tubes were generated from a 120 second acquisition.

physics.med-ph↗

arXiv2019

Predictive Numerical Simulations of Double Branch Stent-Graft Deployment in an Aortic Arch Aneurysm

Total endovascular repair of the aortic arch represents a promising option for patients ineligible to open surgery. Custom-made design of stent-grafts (SG), such as the Terumo Aortic RelayBranch device (DB), requires complex preoperative measures. Accurate SG deployment is required to avoid intraoperative or postoperative complications, which is extremely challenging in the aortic arch. In that context, our aim is to develop a computational tool able to predict SG deployment in such highly complex situations. A patient-specific case is performed with complete deployment of the DB and its bridging stents in an aneurysmal aortic arch. Deviations of our simulation predictions from actual stent positions are estimated based on post-operative scan and a sensitivity analysis is performed to assess the effects of material parameters. Results show a very good agreement between simulations and post-operative scan, with especially a torsion effect, which is successfully reproduced by our simulation. Relative diameter, transverse and longitudinal deviations are of 3.2$\pm$4.0%, 2.6$\pm$2.9mm and 5.2$\pm$3.5mm respectively. Our numerical simulations show their ability to successfully predict the DB deployment in complex anatomy. The results emphasize the potential of computational simulations to assist practitioners in planning and performing complex and secure interventions.

physics.med-ph↗

arXiv2019

Evaluation of Peak Wall Stress in an Ascending Thoracic Aortic Aneurysm Using FSI Simulations: Effects of Aortic Stiffness and Peripheral Resistance

Purpose. It has been reported clinically that rupture or dissections in thoracic aortic aneurysms (TAA) often occur due to hypertension which may be modelled with sudden increase of peripheral resistance, inducing acute changes of blood volumes in the aorta. There is clinical evidence that more compliant aneurysms are less prone to rupture as they can sustain such changes of volume. The aim of the current paper is to verify this paradigm by evaluating computationally the role played by the variation of peripheral resistance and the impact of aortic stiffness onto peak wall stress in ascending TAA. Methods. Fluid-Structure Interaction (FSI) analyses were performed using patient-specific geometries and boundary conditions derived from 4D MRI datasets acquired on a patient. Blood was assumed incompressible and was treated as a non-Newtonian fluid using the Carreau model while the wall mechanical properties were obtained from the bulge inflation tests carried out in vitro after surgical repair. The Navier Stokes equations were solved in ANSYS Fluent. The Arbitrary Lagrangian Eulerian formulation was used to account for the wall deformations. At the interface between the solid domain and the fluid domain, the fluid pressure was transferred to the wall and the displacement of the wall was transferred to the fluid. The two systems were connected by the System Coupling component which controls the solver execution of fluid and solid simulations in ANSYS. Fluid and solid domains were solved sequentially starting from the fluid simulations. Results. Distributions of blood flow, wall shear stress and wall stress were evaluated in the ascending thoracic aorta using the FSI analyses. We always observed a significant flow eccentricity in the simulations, in very good agreement with velocity profiles measured using 4D MRI. The results also showed significant increase of peak wall stress due to the increase of peripheral resistance and aortic stiffness. In the worst case scenario, the largest peripheral resistance (10 10 kg.s.m-4) and stiffness (10 MPa) resulted in a maximal principal stress equal to 702 kPa, whereas it was only 77 kPa in normal conditions. Conclusions. This is the first time that the risk of rupture of an aTAA is quantified in case of the combined effects of hypertension and aortic stiffness increase. Our findings suggest that a stiffer TAA may have the most altered distribution of wall stress and an acute change of peripheral vascular resistance could significantly increase the risk of rupture for a stiffer aneurysm.

physics.med-ph↗

arXiv2019

An improved physics model for multi-material identification in photon counting CT

Photon-counting computed tomography (PCCT) with energy discrimination capabilities hold great potentials to improve the limitations of the conventional CT, including better signal-to-noise ratio (SNR), improved contrast-to-noise ratio (CNR), lower radiation dose, and most importantly, simultaneous multiple material identification. One potential way of material identification is via calculation of effective atomic number and effective electron density from PCCT image data. However, the current methods for calculating effective atomic number and effective electron density from PCCT image data are mostly based on semi-empirical models and accordingly are not sufficiently accurate. Here, we present a physics-based model to calculate the effective atomic number and effective electron density of various matters, including single element substances, molecular compounds, and multi-material mixtures as well. The model was validated over several materials under various combinations of energy bins. A PCCT system was simulated to generate the PCCT image data, and the proposed model was applied to the PCCT image data. Our model yielded a relative standard deviations for effective atomic numbers and effective electron densities at less than 1%. Our results further showed that five different materials can be simultaneously identified and well separated in a effective atomic number - effective electron density map. The model could serve as a basis for simultaneous material identification from PCCT.

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