Whole-body Model Research Articles

Structure-exploiting Newton-type method for optimal control of switched systems

ABSTRACT This study proposes an efficient Newton-type method for the optimal control of switched systems under a given mode sequence. A mesh-refinement-based approach is utilised to discretise continuous-time optimal control problems (OCPs) and formulate a nonlinear program (NLP), which guarantees the local convergence of a Newton-type method. A dedicated structure-exploiting algorithm (Riccati recursion) is proposed to perform a Newton-type method for the NLP efficiently because its sparsity structure is different from a standard OCP. The proposed method computes each Newton step with linear time-complexity for the total number of discretization grids as the standard Riccati recursion algorithm. Additionally, the computation is always successful if the solution is sufficiently close to a local minimum. Conversely, general quadratic programming (QP) solvers cannot accomplish this because the Hessian matrix is inherently indefinite. Moreover, a modification on the reduced Hessian matrix is proposed using the nature of the Riccati recursion algorithm as the dynamic programming for a QP subproblem to enhance the convergence. A numerical comparison is conducted with off-the-shelf NLP solvers, which demonstrates that the proposed method is up to two orders of magnitude faster. Whole-body optimal control of quadrupedal gaits is also demonstrated and shows that the proposed method can achieve the whole-body model predictive control (MPC) of robotic systems with rigid contacts.

1302-P: Predicting Insulin Time-Course Profiles for Early Prediabetes Interception Using a Mechanistic Mathematical Model

Early detection of prediabetes using blood glucose remains difficult as individuals often present with slight elevations or even normoglycaemia. However, their insulin profiles usually show marked elevations, suggesting that insulin is a more sensitive biomarker for prediabetes. We developed a mechanistic whole-body model that can predict an individual’s insulin time-course and insulin sensitivity from a given glucose time-course. The model describes the absorption, distribution, metabolism and excretion of glucose and the relevant hormones, while various homeostatic processes such as insulin secretion were dynamically represented by sub-models. Matched glucose and insulin data were obtained from 7 oral glucose tolerance test studies. Model predictions of insulin time-course using glucose data as inputs were compared with observed data for validation (Fig 1). Both population and individual simulation results indicated robust prediction of insulin profiles and demonstrate that it is possible to utilize glucose data (easy to obtain) to predict insulin data (difficult to obtain) for prediabetes screening. Disclosure K.Hor cheng: None. J.C.Y.Chan: None.

Physiologically based pharmacokinetic modeling of levetiracetam to predict the exposure in hepatic and renal impairment and elderly populations.

Levetiracetam (LEV) is an anti-epileptic drug approved for use in various populations. The pharmacokinetic (PK) behavior of LEV may be altered in the elderly and patients with renal and hepatic impairment. Thus, dosage adjustment is required. This study was conducted to investigate how the physiologically-based PK (PBPK) model describes the PKs of LEV in adult and elderly populations, as well as to predict the PKs of LEV in patients with renal and hepatic impairment in both populations. The whole-body PBPK models were developed using the reported physicochemical properties of LEV and clinical data. The models were validated using data from clinical studies with different dose ranges and different routes and intervals of administration. The fit performance of the models was assessed by comparing predicted and observed blood concentration data and PK parameters. It is recommended that the doses be reduced to ~70%, 60%, and 45% of the adult dose for the mild, moderate, and severe renal impairment populations and ~95%, 80%, and 57% of the adult dose for the Child Pugh-A (CP-A), Child Pugh-B (CP-B), and Child Pugh-C (CP-C) hepatic impairment populations, respectively. No dose adjustment is required for the healthy elderly population, but dose reduction is required for the elderly with organ dysfunction accordingly, on a scale similar to that of adults. A PBPK model of LEV was successfully developed to optimize dosing regimens for special populations.

Effect of Whole Body Parameters on Knee Joint Biomechanics: Implications for ACL Injury Prevention During Single-Leg Landings

Background: Previous studies have examined the effect of whole body (WB) parameters on anterior cruciate ligament (ACL) strain and loads, as well as knee joint kinetics and kinematics. However, articular cartilage damage occurs in relation to ACL failure, and the effect of WB parameters on ACL strain and articular cartilage biomechanics during dynamic tasks is unclear. Purposes: (1) To investigate the effect of WB parameters on ACL strain, as well as articular cartilage stress and contact force, during a single-leg cross drop (SLCD) and single-leg drop (SLD). (2) To identify WB parameters predictive of high ACL strain during these tasks. Study Design: Descriptive laboratory study. Methods: Three-dimensional motion analysis data from 14 physically active men and women were recorded during an SLCD and SLD. OpenSim was used to obtain their kinematics, kinetics, and muscle forces for the WB model. Using these data in kinetically driven finite element simulations of the knee joint produced outputs of ACL strains and articular cartilage stresses and contact forces. Spearman correlation coefficients were used to assess relationships between WB parameters and ACL strain and cartilage biomechanics. Moreover, receiver operating characteristic curve analyses and multivariate binary logistic regressions were used to find the WB parameters that could discriminate high from low ACL strain trials. Results: Correlations showed that more lumbar rotation away from the stance limb at peak ACL strain had the strongest overall association (ρ = 0.877) with peak ACL strain. Higher knee anterior shear force (ρ = 0.895) and lower gluteus maximus muscle force (ρ = 0.89) at peak ACL strain demonstrated the strongest associations with peak articular cartilage stress or contact force in ≥1 of the analyzed tasks. The regression model that used muscle forces to predict high ACL strain trials during the dominant limb SLD yielded the highest accuracy (93.5%), sensitivity (0.881), and specificity (0.952) among all regression models. Conclusion: WB parameters that were most consistently associated with and predictive of high ACL strain and poor articular cartilage biomechanics during the SLCD and SLD tasks included greater knee abduction angle at initial contact and higher anterior shear force at peak ACL strain, as well as lower gracilis, gluteus maximus, and medial gastrocnemius muscle forces. Clinical relevance: Knowledge of which landing postures create a high risk for ACL or cartilage injury may help reduce injuries in athletes by avoiding those postures and practicing the tasks with reduced high-risk motions, as well as by strengthening the muscles that protect the knee during single-leg landings.

Physiologically-based pharmacokinetic pharmacodynamic parent-metabolite model of edoxaban to predict drug-drug-disease interactions: M4 contribution.

This study aimed to develop a physiologically-based pharmacokinetic pharmacodynamic (PBPK/PD) parent-metabolite model of edoxaban, an oral anticoagulant with a narrow therapeutic index, and to predict pharmacokinetic (PK)/PD profiles and potential drug-drug-disease interactions (DDDIs) in patients with renal impairment. A whole-body PBPK model with a linear additive PD model of edoxaban and its active metabolite M4 was developed and validated in SimCYP for healthy adults with or without interacting drugs. The model was extrapolated to situations including renal impairment and drug-drug interactions (DDIs). Observed PK and PD data in adults were compared with predicted data. The effect of several model parameters on the PK/PD response of edoxaban and M4 was investigated in sensitivity analysis. The PBPK/PD model successfully predicted PK profiles of edoxaban and M4 as well as anticoagulation PD responses with or without the influence of interacting drugs. For patients with renal impairment, the PBPK model successfully predicted the fold change in each impairment group. Inhibitory DDI and renal impairment had a synergistic effect on the increased exposure of edoxaban and M4, and their downstream anticoagulation PD effect. Sensitivity analysis and DDDI simulation show that renal clearance, intestinal P-glycoprotein activity, and hepatic OATP1B1 activity are the major factors affecting edoxaban-M4 PK profiles and PD responses. Anticoagulation effect induced by M4 cannot be ignored when OATP1B1 is inhibited or downregulated. Our study provides a reasonable approach to adjust the dose of edoxaban in several complicated scenarios especially when M4 cannot be ignored due to decreased OATP1B1 activity.

Physiologically-based pharmacokinetic modelling to predict intragastric rifabutin concentrations in the treatment of Helicobacter pylori infection.

Sustained intragastric antibiotic exposure is important for Helicobacter pylori eradication, yet little is known about gastric pharmacology of commonly used H. pylori regimens. For rifabutin, differing intragastric concentrations based on dosing regimen may account for differences in reported eradication rates. To compare intragastric rifabutin concentrations between low-dose rifabutin (50 mg three time daily; as in RHB-105) and generically dosed rifabutin 150 mg once daily, 150 mg twice daily, and 300 mg once daily using a validated Physiologically-based pharmacokinetic (PBPK) model. We obtained plasma pharmacokinetic data from the RHB-105 clinical development programs and used it to develop and validate a whole-body PBPK model using PK-SIM software. We modified the existing rifabutin model to include the impact of omeprazole on gastric pH and emptying time. Modelled intragastric rifabutin exposure was expressed as the time that each regimen maintained its concentration ≥MIC90 . Rifabutin 50 mg three times daily achieved significantly longer times with intragastric concentration above MIC90 (22.3 ± 1.1 h) than 150 mg once daily (8.3 ± 1.7 h), 150 mg twice daily (16.3 ± 2.3 h), or 300 mg once daily (8.5 ± 1.9 h) while providing the lowest mean maximal plasma concentration and mean area under the plasma concentration-time curve of all regimens studied. PBPK modelling showed rifabutin 50 mg three times daily had higher intragastric exposure times than 150 mg once daily or twice daily, or 300 mg once daily. This low-dose rifabutin regimen provides the highest potential for H. pylori eradication while minimising systemic rifabutin exposure.

Gait optimization and energy-based stability for biped locomotion using large-scale programming

AbstractThis paper presents a gait optimization method to generate the locomotion pattern for biped and discuss its stability. The main contribution of this paper is a newly proposed energy-based stability criterion, which permits the dynamic stable walking and could be straight-forwardly generalized to different locomotion scenarios and biped robots. The gait optimization problem is formulated subject to the constraints of the whole-body dynamics and kinematics. The constraints are established based on the modelling of bipedal hybrid dynamical systems. Following the whole-body modelling, the system energy is acquired and then applied to create the stability criterion. The optimization objective is also established on the system energy. The gait optimization is solved by being converted to a large-scale programming problem, where the transcription accuracy is improved via the spectral method. To further reduce the dimensionality of the large-scale problem, the whole-body dynamics is re-constructed. The generalization of the optimized gait is improved by the design of feedback control. The optimization examples demonstrate that the stability criterion naturally leads to a cyclic biped locomotion, though the periodicity was not previously imposed. Two simulation cases, level ground walking and slope walking, verify the generalization of the stability criterion and feedback control. The stability analyses are carried out by investigating the motions of centre of gravity and centre of pressure. It is revealed that if the tracked speed is above 0.3 m/s or the biped accelerates/climbs the slope, the stability criterion accomplishes the dynamic stable walking, where zero moment point criterion is not strictly complied.

Predicting Hydroxychloroquine Clearance in Healthy and Diseased Populations Using a Physiologically Based Pharmacokinetic Approach.

Hydroxychloroquine (HCQ), a congener of chloroquine, is widely used in prophylaxis and the treatment of malaria, and also as a cure for rheumatoid arthritis, systemic lupus erythematosus, and various other diseases. Physiologically based pharmacokinetic modeling (PBPK) has attracted great interest in the past few years in predicting drug pharmacokinetics (PK). This study focuses on predicting the PK of HCQ in the healthy population and extrapolating it to the diseased populations, i.e., liver cirrhosis and chronic kidney disease (CKD), utilizing a systematically built whole-body PBPK model. The time vs. concentration profiles and drug-related parameters were obtained from the literature after a laborious search and in turn were integrated into PK-Sim software for designing healthy intravenous, oral, and diseased models. The model's evaluation was performed using observed-to-predicted ratios (Robs/Rpre) and visual predictive checks within a 2-fold error range. The healthy model was then extrapolated to liver cirrhosis and CKD populations after incorporating various disease-specific pathophysiological changes. Box-whisker plots showed an increase in AUC0-t in liver cirrhosis, whereas a decrease in AUC0-t was seen in the CKD population. These model predictions may assist clinicians in adjusting the administered HCQ doses in patients with different degrees of hepatic and renal impairment.

Physicochemical characterization and phase II metabolic profiling of echinochrome A, a bioactive constituent from sea urchin, and its physiologically based pharmacokinetic modeling in rats and humans

Echinochrome A, a natural naphthoquinone pigment found in sea urchins, is increasingly being investigated for its nutritional and therapeutic value associated with antioxidant, anticancer, antiviral, antidiabetic, and cardioprotective activities. Although several studies have demonstrated the biological effects and therapeutic potential of echinochrome A, little is known regarding its biopharmaceutical behaviors. Here, we aimed to investigate the physicochemical properties and metabolic profiles of echinochrome A and establish a physiologically-based pharmacokinetic (PBPK) model as a useful tool to support its clinical applications. We found that the lipophilicity, color variability, ultraviolet/visible spectrometry, and stability of echinochrome A were markedly affected by pH conditions. Moreover, metabolic and pharmacokinetic profiling studies demonstrated that echinochrome A is eliminated primarily by hepatic metabolism and that four possible metabolites, i.e., two glucuronidated and two methylated conjugates, are formed in rat and human liver preparations. A whole-body PBPK model incorporating the newly identified hepatic phase II metabolic process was constructed and optimized with respect to chemical-specific parameters. Furthermore, model simulations suggested that echinochrome A could exhibit linear disposition profiles without systemic and local tissue accumulation in clinical settings. Our proposed PBPK model of echinochrome A could be a valuable tool for predicting drug interactions in previously unexplored scenarios and for optimizing dosage regimens and drug formulations.

Comparison of cardiac image-derived input functions for quantitative whole body [18F]FDG imaging with arterial blood sampling.

Introduction: Dynamic positron emission tomography (PET) and the application of kinetic models can provide important quantitative information based on its temporal information. This however requires arterial blood sampling, which can be challenging to acquire. Nowadays, state-of-the-art PET/CT systems offer fully automated, whole-body (WB) kinetic modelling protocols using image-derived input functions (IDIF) to replace arterial blood sampling. Here, we compared the validity of an automatic WB kinetic model protocol to the reference standard arterial input function (AIF) for both clinical and research settings. Methods: Sixteen healthy participants underwent dynamic WB [18F]FDG scans using a continuous bed motion PET/CT system with simultaneous arterial blood sampling. Multiple processing pipelines that included automatic and manually generated IDIFs derived from the aorta and left ventricle, with and without motion correction were compared to the AIF. Subsequently generated quantitative images of glucose metabolism were compared to evaluate performance of the different input functions. Results: We observed moderate to high correlations between IDIFs and the AIF regarding area under the curve (r = 0.49-0.89) as well as for the cerebral metabolic rate of glucose (CMRGlu) (r = 0.68-0.95). Manual placing of IDIFs and motion correction further improved their similarity to the AIF. Discussion: In general, the automatic vendor protocol is a feasible approach for the quantification of CMRGlu for both, clinical and research settings where expertise or time is not available. However, we advise on a rigorous inspection of the placement of the volume of interest, the resulting IDIF, and the quantitative values to ensure valid interpretations. In protocols requiring longer scan times or where cohorts are prone to involuntary movement, manual IDIF definition with additional motion correction is recommended, as this has greater accuracy and reliability.

Mapping out the gut microbiota-dependent trimethylamine N-oxide super pathway for systems biology applications

The metabolic axis linking the gut microbiome and heart is increasingly being researched in the context of cardiovascular health. The gut microbiota-derived trimethylamine/trimethylamine N-oxide (TMA/TMAO) pathway is responsible along this axis for the bioconversion of dietary precursors into TMA/TMAO and has been implicated in the progression of heart failure and dysbiosis through a positive-feedback interaction. Systems biology approaches in the context of researching this interaction offer an additional dimension for deepening the understanding of metabolism along the gut-heart axis. For instance, genome-scale metabolic models allow to study the functional role of pathways of interest in the context of an entire cellular or even whole-body metabolic network. In this mini review, we provide an overview of the latest findings on the TMA/TMAO super pathway and summarize the current state of knowledge in a curated pathway map on the community platform WikiPathways. The pathway map can serve both as a starting point for continual curation by the community as well as a resource for systems biology modeling studies. This has many applications, including addressing remaining gaps in our understanding of the gut-heart axis. We discuss how the curated pathway can inform a further curation and implementation of the pathway in existing whole-body metabolic models, which will allow researchers to computationally simulate this pathway to further understand its role in cardiovascular metabolism.

Titanium Dioxide Nanoparticles Modulate Systemic Immune Response and Increase Levels of Reduced Glutathione in Mice after Seven-Week Inhalation

Titanium dioxide nanoparticles (TiO2 NPs) are used in a wide range of applications. Although inhalation of NPs is one of the most important toxicologically relevant routes, experimental studies on potential harmful effects of TiO2 NPs using a whole-body inhalation chamber model are rare. In this study, the profile of lymphocyte markers, functional immunoassays, and antioxidant defense markers were analyzed to evaluate the potential adverse effects of seven-week inhalation exposure to two different concentrations of TiO2 NPs (0.00167 and 0.1308 mg TiO2/m3) in mice. A dose-dependent effect of TiO2 NPs on innate immunity was evident in the form of stimulated phagocytic activity of monocytes in low-dose mice and suppressed secretory function of monocytes (IL-18) in high-dose animals. The effect of TiO2 NPs on adaptive immunity, manifested in the spleen by a decrease in the percentage of T-cells, a reduction in T-helper cells, and a dose-dependent decrease in lymphocyte cytokine production, may indicate immunosuppression in exposed mice. The dose-dependent increase in GSH concentration and GSH/GSSG ratio in whole blood demonstrated stimulated antioxidant defense against oxidative stress induced by TiO2 NP exposure.

Comparison of the dynamics of exoskeletal-assisted and unassisted locomotion in an FDA-approved lower extremity device: Controlled experiments and development of a subject-specific virtual simulator.

Robotic exoskeletons have considerable, but largely untapped, potential to restore mobility in individuals with neurological disorders, and other conditions that result in partial or complete immobilization. The growing demand for these devices necessitates the development of technology to characterize the human-robot system during exoskeletal-assisted locomotion (EAL) and accelerate robot design refinements. The goal of this study was to combine controlled experiments with computational modeling to build a virtual simulator of EAL. The first objective was to acquire a minimum empirical dataset comprising human-robot kinematics, ground reaction forces, and electromyography during exoskeletal-assisted and unassisted locomotion from an able-bodied participant. The second objective was to quantify the dynamics of the human-robot system using a subject-specific virtual simulator reproducing EAL compared to the dynamics of normal gait. We trained an able-bodied participant to ambulate independently in a Food and Drug Administration-approved exoskeleton, the ReWalk P6.0 (ReWalk Robotics, Yoknaem, Israel). We analyzed the motion of the participant during exoskeletal-assisted and unassisted walking, sit-to-stand, and stand-to-sit maneuvers, with simultaneous measurements of (i) three-dimensional marker trajectories, (ii) ground reaction forces, (iii) electromyography, and (iv) exoskeleton encoder data. We created a virtual simulator in OpenSim, comprising a whole-body musculoskeletal model and a full-scale exoskeleton model, to determine the joint kinematics and moments during exoskeletal-assisted and unassisted maneuvers. Mean peak knee flexion angles of the human subject during exoskeletal-assisted walking were 50.1° ± 0.6° (left) and 52.6° ± 0.7° (right), compared to 68.6° ± 0.3° (left) and 70.7° ± 1.1° (right) during unassisted walking. Mean peak knee extension moments during exoskeletal-assisted walking were 0.10 ± 0.10 Nm/kg (left) and 0.22 ± 0.11 Nm/kg (right), compared to 0.64 ± 0.07 Nm/kg (left) and 0.73 ± 0.10 Nm/kg (right) during unassisted walking. This work provides a foundation for parametric studies to characterize the effects of human and robot design variables, and predictive modeling to optimize human-robot interaction during EAL.

Model predictive control of legged and humanoid robots: models and algorithms

ABSTRACT Model predictive control (MPC) of legged and humanoid robotic systems has been an active research topic in the past decade. While MPC for robotic systems has a long history, its paradigm such as problem formulations and algorithms has changed along with the recent drastic progress in robot hardware, computational processors, and algorithms. This survey paper reviews recent progress on MPC for legged and humanoid robotics from the following three points of view. First, we review a variety of dynamical models of robotic systems used in the MPC formulation. Second, we give an overview of MPC algorithms, particularly focusing on suitable ones for robotic problems. Finally, we introduce methods and applications of MPC for practical robotic problems from MPC based on reduced-order models to recent progress on MPC based on whole-body models.

Physiologically based pharmacokinetic modeling to predict OAT3-mediated drug-drug interactions of meropenem in varying stages of chronic kidney disease

ObjectiveThis study aimed to predict OAT3-mediated meropenem DDIs in varying stages of CKD using physiologically based pharmacokinetic (PBPK) models. MethodsMeropenem DDI model was performed with OAT3 perpetrators probenecid (strong inhibitor), piperacillin (moderate inhibitor) and acyclovir (weak inhibitor). Firstly, whole-body PBPK models were developed for meropenem and piperacillin in healthy adults with PK-Sim®. Then the models were translated to patients with varying stages of CKD by accounting for changes in eGFR, kidney volume, kidney blood flow, hematocrit, gastric emptying time, small intestinal transit time, OAT transport function and non-renal clearance. Subsequently, meropenem DDI model was verified by comparing the model simulation results of the interaction between meropenem and probenecid with the observational data from clinical studies. Finally, pharmacokinetics of meropenem under co-administration of piperacillin and acyclovir were predicted through simulations with the virtual population in varying stages of CKD. ResultsThe developed PBPK models of meropenem and piperacillin adequately described the pharmacokinetic characteristics in healthy adults and in adults with varying stages of CKD. The predicted AUC ratio of meropenem co-administered with probenecid to meropenem given alone was within 1.5-fold of the observed clinical data. The predicted steady-state AUC values of meropenem in healthy adults co-administered with probenecid, piperacillin or acyclovir were 1.593-fold (95% CI, 1.436-1.6244), 1.031-fold (95% CI, 1.017-1.045) and 1.005-fold (95% CI, 1.004-1.005), respectively, as compared to the AUC of meropenem given alone. And all predicted probenecid-meropenem, piperacillin-meropenem and acyclovir-meropenem DDI AUC ratios were decreased in renal impairment. Our presented meropenem DDI model demonstrated that patients with CKD may be less vulnerable to OAT3-mediated DDIs compared with healthy adults. However, further clinical DDI studies are required to verify our prediction results. ConclusionPBPK analysis provided a quantitative basis for guiding the clinical application of meropenem combined with OAT3 inhibitor in varying stages of CKD.

Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models.

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.

Motion control framework for unmanned wheel-legged hybrid vehicle considering uncertain disturbances based robust model predictive control

The paper proposes a motion control framework for the unmanned wheel-legged hybrid vehicle to track the motion trajectory considering uncertain disturbances. The whole-body dynamic model is built with the contact force of each rolling wheel, which serves as the foundation to obtain trajectory tracking. The angular momentum and linear momentum are optimized by the robust model predictive control algorithm considering the soft constraint of the relaxation variable. The contact force between wheel and ground is solved by the quadratic programming algorithm to efficiently obtain the flexion/extension joint and wheel motion planning. Then, the explicit algorithm to calculate the torque commands of the flexion/extension joint considering the feed-forward torque and feedback torque to improve the control accuracy. Simulation results validate that the control framework based on the robust model predictive control algorithm can solve the uncertain disturbances in process of the vehicle running on the rough road.

A high-resolution pediatric female whole-body numerical model with comparison to a male model

Objective. Numerical models are central in designing and testing novel medical devices and in studying how different anatomical changes may affect physiology. Despite the numerous adult models available, there are only a few whole-body pediatric numerical models with significant limitations. In addition, there is a limited representation of both male and female biological sexes in the available pediatric models despite the fact that sex significantly affects body development, especially in a highly dynamic population. As a result, we developed Athena, a realistic female whole-body pediatric numerical model with high-resolution and anatomical detail. Approach. We segmented different body tissues through Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images of a healthy 3.5 year-old female child using 3D Slicer. We validated the high anatomical accuracy segmentation through two experienced sub-specialty-certified neuro-radiologists and the inter and intra-operator variability of the segmentation results comparing sex differences in organ metrics with physiologic values. Finally, we compared Athena with Martin, a similar male model, showing differences in anatomy, organ metrics, and MRI dosimetric exposure. Main results. We segmented 267 tissue compartments, which included 50 brain tissue labels. The tissue metrics of Athena displayed no deviation from the literature value of healthy children. We show the variability of brain metrics in the male and female models. Finally, we offer an example of computing Specific Absorption Rate and Joule heating in a toddler/preschooler at 7 T MRI. Significance. This study introduces a female realistic high-resolution numerical model using MRI and CT scans of a 3.5 year-old female child, the use of which includes but is not limited to radiofrequency safety studies for medical devices (e.g. an implantable medical device safety in MRI), neurostimulation studies, and radiation dosimetry studies. This model will be open source and available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Second-Order Differential Dynamic Programming for Whole-Body MPC of Legged Robots

This paper presents the first use-case of full second-order Differential Dynamic Programming (DDP) with a whole-body model for model predictive control on legged robot hardware. Recent advances in the literature show that DDP can be simplified by exploiting the dynamics structure in the algorithm, allowing the use of reverse-mode derivative accumulation to efficiently compute dynamics sensitives. These advances allow DDP to be run at similar compute times as the iterative LQR (iLQR) algorithm, its first-order counterpart. Beyond a hardware implementation of these past theoretical developments, this paper provides a characterization of DDP vs. iLQR following push disturbances. One challenge is that DDP often requires regularization to ensure the algorithm improves its control law from iteration to iteration, and an expensive matrix reconditioning is often necessary. We explore a novel methodology to carry out this matrix reconditioning, which considers the local geometry of the cost landscape. The resulting controller is shown to achieve lower costs and withstand larger disturbances as compared to traditional regularization schemes.

Anesthetized guinea pig as a model for drug testing.

Based on the World Health Organization statistics, cardiovascular diseases represent the major cause of death worldwide. Although a wide range of treatment approaches and pharmaceuticals is available, the therapy is often not effective enough and therefore health risks for the patient persist. Thus, it is still essential to test new drug candidates for the treatment of various pathophysiological conditions related to cardiovascular system. In vivo models represent indispensable part of preclinical testing of such substances. Anesthetized guinea pig as a whole-body model allows to evaluate complex reactions of cardiovascular system to tested substance. Moreover, action potential of guinea pig cardiomyocyte is quite comparable to that of human. Hence, the results from this model are then quite well translatable to clinical medicine. Aim of this paper was to summarize the methodology of this model, including its advantages and/or limitations and risks, based on the effects of two substances with adrenergic activity on the ECG parameters. The model of anesthetized guinea pig proved to be valuable and suitable for testing of drugs with cardiovascular effects.