Neural-network-based solver for vesicle shapes predicted by the Helfrich model.

That a three-dimensional vesicle morphology can be modeled by an artificial neural network is proposed and demonstrated. In the phase-field representation, the Helfrich bending energy of a membrane is equivalently cast into field-based energy, which enables a more direct representation of a deformable, three-dimensional membrane surface. The core of our method is incorporating recent machine-learning techniques to perform the required energy minimization. The versatile ability of the method, to compute axisymmetric and nonsymmetric shapes, is discussed.

Forced extension of a wormlike chain in the Gibbs and Helmholtz ensembles.

A semiflexible polymer can be stretched by either applying a force to it or by fixing the positions of its endpoints. The two approaches generally yield different results and correspond to experiments performed in either the Gibbs or Helmholtz statistical ensembles. Here, we derive the Helmholtz force-extension relationship for the commonly used wormlike-chain model in the strongly stretched regime. By analyzing it in comparison with the Gibbs ensemble result, we show that equivalence between the two relationships is achieved only in the long-chain thermodynamic limit.

Planning system for the optimization of electric field delivery using implanted electrodes for brain tumor control.

BACKGROUND: The use of non-ionizing electric fields from low-intensity voltage sources (< 10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low-intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT). PURPOSE: This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient-specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, postoperative imaging, and treatment stimulation. METHODS: The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows the segmented brain and tumor mesh volumes to be smoothed and simplified by applying selected filters. Electrode trajectories are planned manually on the patient MRI or CT by selecting insertion and tip coordinates for a chosen number of electrodes. The electrode tip positions and stimulation parameters (phase shift and voltage) can then be optimized with the custom semi-automatic IMT optimization algorithm where users can select the prescription electric field, voltage amplitude limit, tissue electrical properties, nearby organs at risk, optimization parameters (electrode tip location, individual contact phase shift and voltage), desired field coverage percent, and field conformity optimization. Tables of optimization results are displayed, and the resulting electric field is visualized as a field-map superimposed on the MR or CT image, with 3D renderings of the brain, tumor, and electrodes. Optimized electrode coordinates are transferred to robotic electrode implantation software to enable planning and subsequent implantation of the electrodes at the desired trajectories. RESULTS: An IMT treatment planning system was developed that incorporates patient-specific MRI or CT, segmentation, volume smoothing, electrode trajectory planning, electrode tip location and stimulation parameter optimization, and results visualization. All previous manual pipeline steps operating on diverse software platforms were coalesced into a single semi-automated 3D Slicer-based user interface. Brain phantom validation of the full system implementation was successful in preoperative planning, robotic electrode implantation, and postoperative treatment planning to adjust stimulation parameters based on actual implant locations. Voltage measurements were obtained in the brain phantom to determine the electrical parameters of the phantom and validate the simulated electric field distribution. CONCLUSIONS: A custom treatment planning and implantation system for IMT has been developed in this study and validated on a phantom brain model, providing an essential step in advancing IMT technology toward future clinical safety and efficacy investigations.

Functional Lung Avoidance for Individualized Radiation Therapy: Results of a Double-Masked, Randomized Controlled Trial.

PURPOSE: To determine whether functional lung avoidance based on 3He magnetic resonance imaging (MRI) improves quality of life (QOL) for patients undergoing concurrent chemoradiotherapy (CCRT) for advanced non-small cell lung cancer. METHODS AND MATERIALS: Patients with stage III non-small cell lung cancer (or oligometastatic disease treated with curative intent) undergoing CCRT with at least a 10 pack-year smoking history were eligible. Patients underwent pretreatment 3He MRI to measure lung ventilation and had 2 radiation therapy (RT) plans created before randomization: a standard plan, which did not make use of the 3He MRI, and an avoidance plan, preferentially sparing well-ventilated lung. All participants were masked to assignment except the physicist responsible for exporting the selected plan. The primary end point was patient-reported QOL measured at 3-months post-RT by the FACT-L lung cancer subscale (LCS); secondary end points included other QOL metrics, toxicity, and survival outcomes. Target accrual was 64. RESULTS: Twenty-seven patients were randomized before the trial was closed due to slower-than-expected accrual, with 11 randomized to the standard arm and 16 to the avoidance arm. Baseline patient characteristics were well-balanced. At 3 months post-RT, the mean ± SD LCS scores were 17.4 ± 2.8 versus 17.3 ± 6.1 for the standard and avoidance arms, respectively (P = .485). A clinically meaningful, prespecified decline of ≥3 points in the LCS score was observed in 50% (4/8) in the standard arm and 33% (4/12) in the avoidance arm (P = .648). Two patients in each arm developed grade ≥2 radiation pneumonitis, with no grade ≥4 toxicities. CONCLUSIONS: Although this trial did not reach full accrual, QOL scores were very similar between arms. Due to the scarcity of 3He MRI, other, more commonly available methods to measure functional lung, such as 4-dimensional computed tomography ventilation mapping, may be considered in the assessment of functional lung avoidance RT, and a larger, multicenter approach would be needed to accrue sufficient patients to test such approaches.

Defect patterns of two-dimensional nematic liquid crystals in confinement.

A two-dimensional or quasi-two-dimensional nematic liquid crystal refers to a surface-confined system. When such a system is further confined by external line boundaries or excluded from internal line boundaries, the nematic directors form a deformed texture that may display defect points or defect lines, for which winding numbers can be clearly defined. Here, a particular attention is paid to the case when the liquid crystal molecules prefer to form a boundary nematic texture in parallel to the wall surface (i.e., following the homogeneous boundary condition). A general theory, based on geometric argument, is presented for the relationship between the sum of all winding numbers in the system (the total winding number) and the type of confinement angles and curved segments. The conclusion is validated by comparing the theoretical defect rule with existing nematic textures observed experimentally and theoretically in recent years.

Glial activation positron emission tomography imaging in radiation treatment of breast cancer brain metastases.

Brain metastases affect more breast cancer patients than ever before due to increased overall patient survival with improved molecularly targeted treatments. Approximately 25-34% of breast cancer patients develop brain metastases in their lifetime. Due to the blood-brain barrier (BBB), the standard treatment for breast cancer brain metastases (BCBM) is surgery, stereotactic radiosurgery (SRS) and/or whole brain radiation therapy (WBRT). At the cost of cognitive side effects, WBRT has proven efficacy in treating brain metastases when used with local therapies such as SRS and surgery. This review investigated the potential use of glial activation positron emission tomography (PET) imaging for radiation treatment of BCBM. In order to put these studies into context, we provided background on current radiation treatment approaches for BCBM, our current understanding of the brain microenvironment, its interaction with the peripheral immune system, and alterations in the brain microenvironment by BCBM and radiation. We summarized preclinical literature on the interactions between glial activation and cognition and clinical studies using translocator protein (TSPO) PET to image glial activation in the context of neurological diseases. TSPO-PET is not employed clinically in assessing and guiding cancer therapies. However, it has gained traction in preclinical studies where glial activation was investigated from primary brain cancer, metastases and radiation treatments. Novel glial activation PET imaging and its applications in preclinical studies using breast cancer models and glial immunohistochemistry are highlighted. Lastly, we discuss the potential clinical application of glial activation imaging to improve the therapeutic ratio of radiation treatments for BCBM.

Second Heart Field-Derived Cells Contribute to Angiotensin II-Mediated Ascending Aortopathies.

BACKGROUND: The ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies. METHODS: Ascending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry-assisted proteomics and molecular features of SHF-derived cells were determined by single-cell transcriptomic analyses. Genetic deletion of either Lrp1 (low-density lipoprotein receptor-related protein 1) or Tgfbr2 (transforming growth factor-ß receptor type 2) in SHF-derived cells was conducted to examine the effect of SHF-derived cells on vascular integrity. RESULTS: Pathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas after AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion before overt pathology occurred evoked downregulation of smooth muscle cell proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single-cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single-cell transcriptomics results identified PAI1 (plasminogen activator inhibitor 1) as the most increased protein in SHF-derived smooth muscle cells and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies. CONCLUSIONS: SHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and transforming growth factor-ß signaling associated with increases of aortic PAI1.

Deletion of AT1a (Angiotensin II Type 1a) Receptor or Inhibition of Angiotensinogen Synthesis Attenuates Thoracic Aortopathies in Fibrillin1C1041G/+ Mice.

Objective: A cardinal feature of Marfan syndrome is thoracic aortic aneurysm. The contribution of the renin-angiotensin system via AT1aR (Ang II [angiotensin II] receptor type 1a) to thoracic aortic aneurysm progression remains controversial because the beneficial effects of angiotensin receptor blockers have been ascribed to off-target effects. This study used genetic and pharmacological modes of attenuating angiotensin receptor and ligand, respectively, to determine their roles on thoracic aortic aneurysm in mice with fibrillin-1 haploinsufficiency (Fbn1C1041G/+). Approach and Results: Thoracic aortic aneurysm in Fbn1C1041G/+ mice was found to be strikingly sexual dimorphic. Males displayed aortic dilation over 12 months while aortic dilation in Fbn1C1041G/+ females did not differ significantly from wild-type mice. To determine the role of AT1aR, Fbn1C1041G/+ mice that were either +/+ or -/- for AT1aR were generated. AT1aR deletion reduced expansion of ascending aorta and aortic root diameter from 1 to 12 months of age in males. Medial thickening and elastin fragmentation were attenuated. An antisense oligonucleotide against angiotensinogen was administered to male Fbn1C1041G/+ mice to determine the effects of Ang II depletion. Antisense oligonucleotide against angiotensinogen administration attenuated dilation of the ascending aorta and aortic root and reduced extracellular remodeling. Aortic transcriptome analyses identified potential targets by which inhibition of the renin-angiotensin system reduced aortic dilation in Fbn1C1041G/+ mice. Conclusions: Deletion of AT1aR or inhibition of Ang II production exerted similar effects in attenuating pathologies in the proximal thoracic aorta of male Fbn1C1041G/+ mice. Inhibition of the renin-angiotensin system attenuated dysregulation of genes within the aorta related to pathology of Fbn1C1041G/+ mice.

Determining the nonequilibrium criticality of a Gardner transition via a hybrid study of molecular simulations and machine learning.

Apparent critical phenomena, typically indicated by growing correlation lengths and dynamical slowing down, are ubiquitous in nonequilibrium systems such as supercooled liquids, amorphous solids, active matter, and spin glasses. It is often challenging to determine if such observations are related to a true second-order phase transition as in the equilibrium case or simply a crossover and even more so to measure the associated critical exponents. Here we show that the simulation results of a hard-sphere glass in three dimensions are consistent with the recent theoretical prediction of a Gardner transition, a continuous nonequilibrium phase transition. Using a hybrid molecular simulation-machine learning approach, we obtain scaling laws for both finite-size and aging effects and determine the critical exponents that traditional methods fail to estimate. Our study provides an approach that is useful to understand the nature of glass transitions and can be generalized to analyze other nonequilibrium phase transitions.

Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy.

PURPOSE: Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. METHODS: Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. RESULTS: The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. CONCLUSIONS: This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.

Rodlike molecules in extreme confinement.

A unique feature of colloid particles and biopolymers is the molecule's intrinsic rigidity characterized by a molecular-level length scale. Under extreme confinement conditions at cellular scales or in nanodevices, these molecules can display orientational ordering accompanied by severe density depletion. Conventional liquid-crystal theories, such as the Oseen-Frank or Landau-de Gennes theories, cannot capture the essential molecular-level properties: the boundary effects, which extend to a distance of the rigidity length scale, and the drastic variations of the inhomogeneous molecular density. Here we show, based on a simple interpretation of the Onsager model, that rodlike molecules in extreme annular confinement produce unusual liquid-crystal defect structures that are independent phases from the patterns usually seen in a weaker confinement environment.

Construction of a Pathway Map on a Complicated Energy Landscape.

How do we search for the entire family tree of possible intermediate states, without unwanted random guesses, starting from a stationary state on the energy landscape all the way down to energy minima? Here we introduce a general numerical method that constructs the pathway map, which guides our understanding of how a physical system moves on the energy landscape. The method identifies the transition state between energy minima and the energy barrier associated with such a state. As an example, we solve the Landau-de Gennes energy incorporating the Dirichlet boundary conditions to model a liquid crystal confined in a square box; we illustrate the basic concepts by examining the multiple stationary solutions and the connected pathway maps of the model.

Technical Note: A fast inverse direct aperture optimization algorithm for volumetric-modulated arc therapy.

PURPOSE: In a recent article, our group proposed a fast direct aperture optimization (DAO) algorithm for fixed-gantry intensity-modulated radiation therapy (IMRT) called fast inverse direct aperture optimization (FIDAO). When tested on fixed-gantry IMRT plans, we observed up to a 200-fold increase in the optimization speed. Compared to IMRT, rotational volumetric-modulated arc therapy (VMAT) is a much larger optimization problem and has many more delivery constraints. The purpose of this work is to extend and evaluate FIDAO for inverse planning of VMAT plans. METHODS: A prototype FIDAO algorithm for VMAT treatment planning was developed in MATLAB using the open-source treatment planning toolkit matRad (v2.2 dev_VMAT build). VMAT treatment plans using one 3600 arc were generated on the AAPM TG-119 phantom, as well as sample clinical liver and prostate cases. The plans were created by first performing fluence map optimization on 28° equispaced beams, followed by aperture sequencing and arc sequencing with a gantry angular sampling rate of 4°. After arc sequencing, a copy of the plan underwent DAO using the prototype FIDAO algorithm, while another copy of the plan underwent DAO using matRad's DAO method, which served as the conventional algorithm. RESULTS: Both algorithms achieved similar plan quality, although the FIDAO plans had considerably fewer hot spots in the unspecified normal tissue. The optimization time (number of iterations) for FIDAO and the conventional DAO algorithm, respectively, were: 65 s (245) vs 602 s (275) in the TG-119 phantom case; 25 s (85) vs 803 s (159) in the liver case; and 99 s (174) vs 754 s (149) in the prostate case. CONCLUSIONS: This study demonstrated promising speed enhancements in using FIDAO for the direct aperture optimization of VMAT plans.

General liquid-crystal theory for anisotropically shaped molecules: Symmetry, orientational order parameters, and system free energy.

A general theory of liquid crystals is presented, starting from the group-theory symmetry analysis of the constituting molecules. A particular attention is paid to the type of elastic free-energies and their relationships with the molecular symmetries. The orientational order-parameter tensors are identified for each molecular symmetry, in a consideration of consistently keeping the leading, characteristic elastic free energies in a model. The order parameters are expressed in terms of symmetric traceless tensors, some of high orders, for all major molecular symmetries, including seven groups of axial symmetries and seven groups of polyhedral symmetries. For spatially inhomogeneous liquid crystals, the couplings of these tensors in the elastic energies are derived by expanding the interaction energies between these molecules. The aim is to provide a general view of the molecular symmetries of individual molecules, orientational order parameters characterizing the orientational distribution functions, and the elastic free energies, all under one single group-theory approach.

Orientationally ordered states of a wormlike chain in spherical confinement.

One of the basic characteristics of a linear dsDNA molecule is its persistence length, typically of order 50 nm. The DNA chain inflicts a large energy penalty if it is bent sharply at that length scale. Viruses of bacteria, known as bacteriophages, typically have a dimension of a few tens of nanometers. Yet, it is known that a bacteriophage actively packages viral DNA inside the capsid and ejects it afterwards. Here, adopting a commonly used polymer model known as the wormlike chain, we answer an idealized question: Placing a linear DNA molecule inside a spherical cavity, what ordered states can we derive from known tools in statistical physics? Solving the model in a rigorous field-theory framework, we report a universal phase diagram for four orientationally ordered and disordered states, in terms of two relevant physical parameters.

Structural Prediction and Inverse Design by a Strongly Correlated Neural Network.

Macromolecules contain molecular units as the coding information for their correlated structures in physical dimensions. The relationship between these two features is governed by the interaction energies of the involved molecular units and their encoded sequences. We present a neural network algorithm that treats molecular units themselves as neural networks, which has the flexibility to allow each unit to respond to its own environment and to influence others in the system. Through a deep neural network and a self-consistent procedure, molecular units in the network establish a strong correlation to produce the desirable features in the physical world. The proposed framework is applied to the HP model. Both the forward problem of predicting folded structures from given sequences and the inverse problem of predicting required sequences for a given structure are examined.

Machine learning topological defects of confined liquid crystals in two dimensions.

Supervised machine learning can be used to classify images with spatially correlated physical features. We demonstrate the concept by using the coordinate files generated from an off-lattice computer simulation of rodlike molecules confined in a square box as an example. Because of the geometric frustrations at high number density, the nematic director field develops an inhomogeneous pattern containing various topological defects as the main physical feature. We describe two machine-learning procedures that can be used to effectively capture the correlation between the defect positions and the nematic directors around them and hence classify the topological defects. First is a feedforward neural network, which requires the aid of presorting the off-lattice simulation data in a coarse-grained fashion. Second is a recurrent neural network, which needs no such sorting and can be directly used for finding spatial correlations. The issues of when to presort a simulation data file and how the network structures affect such a decision are addressed.

Generating the conformational properties of a polymer by the restricted Boltzmann machine.

In polymer theory, computer-generated polymer configurations, by either Monte Carlo simulations or molecular dynamics simulations, help us to establish the fundamental understanding of the conformational properties of polymers. Here, we introduce a different method, exploiting the properties of a machine-learning algorithm, the restricted Boltzmann machine network, to generate independent polymer configurations for self-avoiding walks (SAWs), for studying the conformational properties of polymers. We show that with adequate training data and network size, this method can capture the underlying polymer physics simply from learning the statistics in the training data without explicit information on the physical model itself. We critically examine how the trained Boltzmann machine can generate independent configurations that are not in the original training data set of SAWs.

Aortic Strain Correlates with Elastin Fragmentation in Fibrillin-1 Hypomorphic Mice.

BACKGROUND: High frequency ultrasound has facilitated in vivo measurements of murine ascending aortas, allowing aortic strains to be gleaned from two-dimensional images. Thoracic aortic aneurysms associated with mutations in fibrillin-1 (FBN1) display elastin fragmentation, which may impact aortic strain. In this study, we determined the relationship between elastin fragmentation and aortic circumferential strain in wild type and fibrillin-1 hypomorphic (FBN1 mgR/mgR) mice. METHODS AND RESULTS: Luminal diameters of the ascending aorta from wild type and FBN1 hypomorphic (FBN1 mgR/mgR) mice were measured in systole and diastole. Expansion of the ascending aorta during systole in male and female wild type mice was 0.21±0.02 mm (16.3%) and 0.21±0.01 mm (17.0%) respectively, while expansion in male and female FBN1 mgR/mgR mice was 0.11±0.04 mm (4.9%) and 0.07±0.02 mm (4.5%) respectively. Reduced circumferential strain was observed in FBN1 mgR/mgR mice compared to wild type littermates. Elastin fragmentation was inversely correlated to circumferential strain (R^2 = 0.628 p = 0.004) and significantly correlated with aortic diameter. (R^2 = 0.397, p = 0.038 in systole and R^2 = 0.515, p =0.013 in diastole). CONCLUSIONS: FBN1 mgR/mgR mice had increased aortic diameters, reduced circumferential strain, and increased elastin fragmentation. Elastin fragmentation in FBN1 mgR/mgR and their wild type littermates was correlated with reduced circumferential strain.

Ultrasound Imaging of the Thoracic and Abdominal Aorta in Mice to Determine Aneurysm Dimensions.

Contemporary high-resolution ultrasound instruments have sufficient resolution to facilitate the measurement of mouse aortas. These instruments have been widely used to measure aortic dimensions in mouse models of aortic aneurysms. Aortic aneurysms are defined as permanent dilations of the aorta, which occur most frequently in the ascending and abdominal regions. Sequential measurements of aortic dimensions by ultrasound are the principal approach for assessing the development and progression of aortic aneurysms in vivo. Although many reported studies used ultrasound imaging to measure aortic diameters as a primary endpoint, there are confounding factors, such as probe position and cardiac cycle, that may impact the accuracy of data acquisition, analysis, and interpretation. The purpose of this protocol is to provide a practical guide on the use of ultrasound to measure the aortic diameter in a reliable and reproducible manner. This protocol introduces the preparation of mice and instruments, the acquisition of appropriate ultrasound images, and data analysis.