Beat-to-beat estimation of the continuous left and right cardiac elastance from metrics commonly available in clinical settings.

Introduction: Functional time-varying cardiac elastances (FTVE) contain a rich amount of information about the specific cardiac state of a patient. However, a FTVE waveform is very invasive to directly measure, and is thus currently not used in clinical practice. This paper presents a method for the estimation of a patient specific FTVE, using only metrics that are currently available in a clinical setting.

Algorithmic processing of pressure waveforms to facilitate estimation of cardiac elastance.

Background: Cardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them. Information about the cardiac elastance, which can be used to estimate it, can be found in the downstream pressure waveforms of the aortic pressure (P(ao)) and the pulmonary artery (P(pa)). However these pressure waveforms are typically noisy and biased, and require processing in order to locate the specific information required for cardiac elastance estimations.

Validation of subject-specific cardiovascular system models from porcine measurements.

A previously validated mathematical model of the cardiovascular system (CVS) is made subject-specific using an iterative, proportional gain-based identification method. Prior works utilised a complete set of experimentally measured data that is not clinically typical or applicable. In this paper, parameters are identified using proportional gain-based control and a minimal, clinically available set of measurements.

Clinical detection and monitoring of acute pulmonary embolism: proof of concept of a computer-based method.

Background: The diagnostic ability of computer-based methods for cardiovascular system (CVS) monitoring offers significant clinical potential. This research tests the clinical applicability of a newly improved computer-based method for the proof of concept case of tracking changes in important hemodynamic indices due to the influence acute pulmonary embolism (APE).

Methods: Hemodynamic measurements from a porcine model of APE were used to validate the method.

A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients.

Intensive insulin therapy (IIT) and tight glycaemic control (TGC), particularly in intensive care unit (ICU), are the subjects of increasing and controversial debate in recent years. Model-based TGC has shown potential in delivering safe and tight glycaemic management, all the while limiting hypoglycaemia. A comprehensive, more physiologically relevant Intensive Control Insulin-Nutrition-Glucose (ICING) model is presented and validated using data from critically ill patients.

Tight glycemic control in critical care--the leading role of insulin sensitivity and patient variability: a review and model-based analysis.

Tight glycemic control (TGC) has emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and costs. However, repeating initial successful TGC trials that reduced mortality and other outcomes has proven difficult with more failures than successes. Hence, there has been growing debate over the necessity of TGC, its goals, the risk of severe hypoglycemia, and target cohorts.

Design and clinical pilot testing of the model-based dynamic insulin sensitivity and secretion test (DISST).

Background: Insulin resistance is a significant risk factor in the pathogenesis of type 2 diabetes. This article presents pilot study results of the dynamic insulin sensitivity and secretion test (DISST), a high-resolution, low-intensity test to diagnose insulin sensitivity (IS) and characterize pancreatic insulin secretion in response to a (small) glucose challenge. This pilot study examines the effect of glucose and insulin dose on the DISST, and tests its repeatability.

Cardiac output estimation using pulmonary mechanics in mechanically ventilated patients.

The application of positive end expiratory pressure (PEEP) in mechanically ventilated (MV) patients with acute respiratory distress syndrome (ARDS) decreases cardiac output (CO). Accurate measurement of CO is highly invasive and is not ideal for all MV critically ill patients. However, the link between the PEEP used in MV, and CO provides an opportunity to assess CO via MV therapy and other existing measurements, creating a CO measure without further invasiveness.

Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: animal experiments and proof of concept.

A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis-a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases.

In vitro evaluation of surface based non-invasive breast cancer screening with digital image based Elasto tomography (DIET).

Digital Image-based Elasto Tomography (DIET) is a non-invasive breast cancer screening modality that induces vibrations into a breast and images its surface motion with digital cameras. Disturbances in the motion are caused by areas of higher stiffness within the breast, potentially cancerous tumors. A concept is presented to detect the angular location of a tumor by analyzing the phase delay of the vibrations on the surface.

An image based vibration sensor for soft tissue modal analysis in a Digital Image Elasto Tomography (DIET) system.

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, based on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A feasibility analysis for a non-invasive image based modal analysis system is presented that is able to robustly and rapidly identify resonant frequencies in soft tissue.

A three-compartment model of the C-peptide-insulin dynamic during the DIST test.

Dynamic insulin sensitivity (SI) tests often utilise model-based parameter estimation. This research analyses the impact of expanding the typically used two-compartment model of insulin and C-peptide kinetics to incorporate a hepatic third compartment. The proposed model requires only four C-peptide assays to simulate endogenous insulin production (uen), greatly reducing the cost and clinical burden.

Independent cohort cross-validation of the real-time DISTq estimation of insulin sensitivity.

Insulin sensitivity (SI) is useful in the diagnosis, screening and treatment of diabetes. However, most current tests cannot provide an accurate, immediate or real-time estimate. The DISTq method does not require insulin or C-peptide assays like most SI tests, thus enabling real-time, low-cost SI estimation.

Modelling acute renal failure using blood and breath biomarkers in rats.

This paper compares three methods for estimating renal function, as tested in rats. Acute renal failure (ARF) was induced via a 60-min bilateral renal artery clamp in 8 Sprague-Dawley rats and renal function was monitored for 1 week post-surgery. A two-compartment model was developed for estimating glomerular filtration via a bolus injection of a radio-labelled inulin tracer, and was compared with an estimated creatinine clearance method, modified using the Cockcroft-Gault equation for rats.

Dynamic functional residual capacity can be estimated using a stress-strain approach.

Background: Acute Respiratory Distress Syndrome (ARDS) results in collapse of alveolar units and loss of lung volume at the end of expiration. Mechanical ventilation is used to treat patients with ARDS or Acute Lung Injury (ALI), with the end objective being to increase the dynamic functional residual capacity (dFRC), and thus increasing overall functional residual capacity (FRC). Simple methods to estimate dFRC at a given positive end expiratory pressure (PEEP) level in patients with ARDS/ALI currently does not exist.

Development of a model-based clinical sepsis biomarker for critically ill patients.

Sepsis occurs frequently in the intensive care unit (ICU) and is a leading cause of admission, mortality, and cost. Treatment guidelines recommend early intervention, however positive blood culture results may take up to 48 h. Insulin sensitivity (S(I)) is known to decrease with worsening condition and could thus be used to aid diagnosis.

DISTq: An Iterative Analysis of Glucose Data for Low-Cost, Real-Time and Accurate Estimation of Insulin Sensitivity.

Insulin sensitivity (SI) estimation has numerous uses in medical and clinical situations. However, highresolution tests that are useful for clinical diagnosis and monitoring are often too intensive, long and costly for regular use. Simpler tests that mitigate these issues are not accurate enough for many clinical diagnostic or monitoring scenarios.

A minimal C-peptide sampling method to capture peak and total prehepatic insulin secretion in model-based experimental insulin sensitivity studies.

Aims And Background: Model-based insulin sensitivity testing via the intravenous glucose tolerance test (IVGTT) or similar is clinically very intensive due to the need for frequent sampling to accurately capture the dynamics of insulin secretion and clearance. The goal of this study was to significantly reduce the number of samples required in intravenous glucose tolerance test protocols to accurately identify C-peptide and insulin secretion characteristics.

Methods: Frequently sampled IVGTT data from 12 subjects [5 normal glucose-tolerant (NGT) and 7 type 2 diabetes mellitus (T2DM)] were analyzed to calculate insulin and C-peptide secretion using a well-accepted C-peptide model.

Screening for diabetic retinopathy using computer vision and physiological markers.

Background: Hyperglycemia and diabetes result in vascular complications, most notably diabetic retinopathy (DR). The prevalence of DR is growing and is a leading cause of blindness and/or visual impairment in developed countries. Current methods of detecting, screening, and monitoring DR are based on subjective human evaluation, which is also slow and time-consuming.

The identification of insulin saturation effects during the dynamic insulin sensitivity test.

Background: Many insulin sensitivity (SI) tests identify a sensitivity metric that is proportional to the total available insulin and measured glucose disposal despite general acceptance that insulin action is saturable. Accounting for insulin action saturation may aid inter-participant and/or inter-test comparisons of insulin efficiency, and model-based glycaemic regulation.

Method: Eighteen subjects participated in 46 dynamic insulin sensitivity tests (DIST, low-dose 40-50 minute insulin-modified IVGTT).

Model-based prediction of the patient-specific response to adrenaline.

A model for the cardiovascular and circulatory systems has previously been validated in simulated cardiac and circulatory disease states. It has also been shown to accurately capture the main hemodynamic trends in porcine models of pulmonary embolism and PEEP (positive end-expiratory pressure) titrations at different volemic levels. In this research, the existing model and parameter identification process are used to study the effect of different adrenaline doses in healthy and critically ill patient populations, and to develop a means of predicting the hemodynamic response to adrenaline.

A minimal model of lung mechanics and model-based markers for optimizing ventilator treatment in ARDS patients.

A majority of patients admitted to the Intensive Care Unit (ICU) require some form of respiratory support. In the case of Acute Respiratory Distress Syndrome (ARDS), the patient often requires full intervention from a mechanical ventilator. ARDS is also associated with mortality rate as high as 70%.

A subcutaneous insulin pharmacokinetic model for computer simulation in a diabetes decision support role: validation and simulation.

Objective: The goal of this study was to validate a previously derived and identified physiological subcutaneous (SC) insulin absorption model for computer simulation in a clinical diabetes decision support role using published pharmacokinetic summary measures.

Methods: Validation was performed using maximal plasma insulin concentration (C(max)) and time to maximal concentration (t(max) pharmacokinetic summary measures. Values were either reported or estimated from 37 pharmacokinetic studies over six modeled insulin types.

A subcutaneous insulin pharmacokinetic model for computer simulation in a diabetes decision support role: model structure and parameter identification.

Objective: The goal of this study was to develop a unified physiological subcutaneous (SC) insulin absorption model for computer simulation in a clinical diabetes decision support role. The model must model the plasma insulin appearance of a wide range of current insulins, especially monomer insulin and insulin glargine, utilizing common chemical states and transport rates, where appropriate.

Methods: A compartmental model was developed with 13 patient-specific model parameters covering six diverse insulin types [rapid-acting, regular, neutral protamine Hagedorn (NPH), lente, ultralente, and glargine insulin].

A benchmark data set for model-based glycemic control in critical care.

Background: Hyperglycemia is prevalent in critical care. That tight control saves lives is becoming more clear, but the "how" and "for whom" in repeating the initial results remain elusive. Model-based methods can provide tight, patient-specific control, as well as providing significant insight into the etiology and evolution of this condition.