Validation and implementation of low-cost dynamic insulin sensitivity tests

DTM2011 handbook/programme is given in files and also available as a hard copyObjective: Insulin sensitivity (SI) tests can provide important information for type 2 diabetes risk assessment and investigations of metabolism or pre-diabetes. Our group previously presented the dynamic insulin sensitivity and secretion test (DISST) and the real-time quick DISST (DISTq) as low-cost, low-burden and accurate alternatives to established tests. The DISST provides concurrent SI and endogenous insulin secretion (UN) metrics, the DISTq does not require insulin or C-peptide assays for SI identification, but can return an immediate result. This study validates the DISST and DISTq in comparison to the euglycemic, hyperinsulinemic clamp (EIC) Method: Fifty participants (with 10 BMI>30; 10 BMI>25, <30; and 5 BMI<25 of each gender) underwent the EIC and DISST. The DISST protocol requires 5 samples from a 30 minute protocol similar to the IM-IVGTT. Data from the DISST protocol was sufficient to identify SI using both the DISST and DISTq parameter identification methods and UN from the DISST. Result: DISST and DISTq SI values correlated well to the EIC (R=0.81 and R=0.76, respectively) and each other (R=0.84). UN values obtained during the DISST showed clinically relevant distinctions between participants, and clearly differentiated the beta-cell function of impaired glucose tolerant participants who had the same EIC SI. Participant acceptance of the protocol was high with very minor reported adverse effects. Conclusion: The DISST and DISTq correlated well against the EIC compared to most established insulin sensitivity tests. The DISST can better differentiate patients as it provides UN metrics that the EIC does not. A computer program makes uptake and use of the model-based DISST and DISTq tests straightforward for clinicians and researchers

The Dynamic Insulin Sensitivity and Secretion Test (DISST) - a novel measure of insulin sensitivity

Objective: To validate the methodology for the Dynamic Insulin Sensitivity and Secretion Test (DISST) and to demonstrate its potential in clinical and research settings. Methods: 123 men and women had routine clinical and biochemical measurements, an oral glucose tolerance test and a DISST. For the DISST, participants were cannulated for blood sampling and bolus administration. Blood samples were drawn at t=0, 10, 15, 25 and 35 minutes for measurement of glucose, insulin and C-peptide. A 10g bolus of intravenous glucose at t=5 minutes and 1U of intravenous insulin immediately after the t=15 minute sample were given. Fifty participants also had a hyperinsulinaemic euglycaemic clamp. Relationships between DISST insulin sensitivity (SI) and the clamp, and both DISST SI and secretion and other metabolic variables were measured. Results: A Bland-Altman plot showed little bias in the comparison of DISST with the clamp; with DISST underestimating the glucose clamp by 0.1·10-2·mg·l·kg-1·min-1·pmol-1 (90%CI -0.2 to 0). The correlation between SI as measured by DISST and the clamp was 0.82, the c unit for the ROC analysis for the two tests was 0.96. Metabolic variables showed significant correlations with DISST IS, and the second phase of insulin release. DISST also appears able to distinguish different insulin secretion patterns in individuals with identical SI values. Conclusions: DISST is a simple, dynamic test that compares favourably with the clamp in assessing SI and allows simultaneous assessment of insulin secretion. DISST has the potential to provide even more information about the pathophysiology of diabetes than more complicated tests

Separate modal analysis for tumor detection with a Digital Image Elasto Tomography (DIET) breast cancer screening system

Digital Image Elasto Tomography (DIET) is a non-invasive breast cancer screening modality that induces mechanical vibrations into a breast and images its surface mo- tion with digital cameras. A new approach in software based diagnosis of this surface motion is presented, focussing on the second natural frequency of the breast. Sepa- rate modal analysis is used to estimate the modal parameters using imaging data from silicone phantoms. The second natural frequency proves to be a reliable metric with the potential to clearly distinguish cancerous and healthy tissue as well as providing an approximate location for the tumor. Furthermore, thorough statistical analysis is performed to verify the results

Silicone breast phantoms for elastographic imaging evaluation

Purpose: Breast cancer is a major public health issue for women, and early detection significantly increases survival rate. Currently, there is increased research interest in elastographic soft-tissue imaging techniques based on the correlation between pathology and mechanical stiffness. Anthropomorphic breast phantoms are critical for in-vitro validation of emerging elastographic technologies. This research develops heterogeneous breast phantoms for use in testing elastographic imaging modalities. Methods: Mechanical property estimation of eight different elastomers is performed to determine storage moduli (E’) and damping ratios (ζ) using a dynamic mechanical analyzer (DMA). Dynamic compression testing was carried out isothermally at room temperature over a range of 4-50 Hz. Silicone compositions with physiologically realistic storage modulus were chosen for mimicking skin adipose, cancerous tumors and pectoral muscles and 13 anthropomorphic breast phantoms were constructed for in vitro trials of Digital Image Elasto Tomography (DIET) breast cancer screening system. A simpler fabrication was used to assess the possibility of multiple tumor detection using Magnetic Resonance Elastography (MRE). Results: Silicone materials with ranges of storage moduli (E’) from 2 to 570 kPa and damping ratios (ζ) from 0.03 to 0.56 were identified. The resulting phantoms were tested in two different elastographic breast cancer diagnostic modalities. A significant contrast was successfully identified between healthy tissues and cancerous tumors both in Magnetic Resonance Elastography (MRE) and Digital Image Elasto-tomography (DIET). Conclusions: The phantoms presented promise aid to researchers in elastographic imaging modalities for breast cancer detection and provide a foundation for silicone based phantom materials for mimicking soft tissues of other human organs

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 insulinmodified IVGTT). The data was used to identify and compare SI metrics from three models: a proportional model (SIL), a saturable model (SIS and Q50) and a model similar to the Minimal Model (SG and SIG). The three models are compared using inter-trial parameter repeatability, and fit to data. Results: The single variable proportional model produced the metric with least intra-subject variation: 13.8% vs 40.1%/55.6%, (SIS/I50) for the saturable model and 15.8%/88.2% (SIG/SG) for the third model. The average plasma insulin concentration at half maximum action (I50) was 139.3 mU·L-1, which is comparable to studies which use more robust stepped EIC protocols. Conclusions: The saturation model and method presented enables a reasonable estimation of an overall patient-specific saturation threshold, which is a unique result for a test of such low dose and duration. The detection of previously published population trends and significant bias above noise suggests that the model and method successfully detects actual saturation signals. Furthermore, the saturation model allowed closer fits to the clinical data than the other models, and the saturation parameter showed a moderate distinction between NGT and IFG-T2DM subgroups. However, the proposed model did not provide metrics of sufficient resolution to enable confidence in the method for either SI metric comparisons across dynamic tests or for glycamic control

Validation Study of a Novel Test For Measuring Insulin Sensitivity

Background: We have previously presented pilot work on a new, low-dose, low intensity, model-based dynamic insulin sensitivity test (DIST). Pilot tests showed good repeatability and the model insulin sensitivity (Si) was highly correlated to the euglycaemic clamp (EIC), (r = 0.98, N = 146). This test could thus be useful for assessing diabetes and cardiovascular disease risk, and in research on disease states such as PCOS, NASH, CRF, and dementia. Method: An ongoing validation trial of the DIST against the EIC, the OGTT and HOMA has enrolled 19 men and 21 women (N = 40) with a range of BMIs and age range of 21-60 years. The DIST requires 40 minutes and measures insulin sensitivity (Si) in response to a 10g iv glucose bolus and a 1U insulin bolus 10 minutes later. It samples plasma glucose, insulin and c-peptide 8 times during the test. The DIST provides an insulin sensitivity metric (Si) as well as measures of endogenous beta cell function. Results: The DIST Si range 1.11-22.79 L•mU-1•min-1, EIC range 1.97- 15.59 M•mU-1•l-1. Preliminary correlation of current Clamp ISI to DIST Si is R = 0.76. is promising, and further data will be presented as the study completes. We will also present data to show advantages of the DIST including assessment of Beta cell function, and modification of the DIST depending on the clinical need. Conclusions: For settings requiring high accuracy and low variability the full DIST (30 minutes, 5 samples, cost $300) can be used. Alternatively a DISTq can be performed at the bedside (e.g. in intensive care, at a very low cost$50) measuring only glucose samples with an accuracy less than the full DIST, but measurably better and more repeatable than OGTT or HOMA. Overall, this model-based approach offers significant potential to provide, new, low-cost and low-intensity methods of screening and testing for insulin sensitivity and metabolic risk

A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Validation and Simulation

Companion paper #2Objective: 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 (Cmax) and time to maximal concentration (tmax) pharmacokinetic summary measures. Values were either reported or estimated from 37 pharmacokinetic studies over six modeled insulin types. A validation comparison was made to equivalent pharmacokinetic summary measures calculated from model generated curves fitted to respective plasma insulin concentration data. The validation result was a measure of goodness of fit. Validation for each reported study was classified into one of four cases. Results: Of 37 model fits, 22 were validated on both the Cmax and the tmax summary measures. Another 6 model fits were partially validated on one measure only due to lack of reporting on the second measure with errors to reported or estimated ranges of <12%. Another 7 studies could not be validated on either measure because of inadequate reported clinical data. Finally, 2 separate model fits to data from the same study failed the validation with 90 and 71% error on tmax only, which was likely caused by protocol-based error. No model fit failed the validation on both measures

DISTq: Low-cost, Accurate and Real-Time Estimation of Insulin Sensitivity

Knowing insulin sensitivity (SI) can optimise glycaemic control, assess metabolic drug therapy, or define diabetes risk. The DISTq is a short, low dose IM-IVGTT that generates an estimate of SI immediately after a 40 minute test using only glucose measurements, subject’s physical attributes, and population parameter estimations. In this article, the DISTq is evaluated in clinical and in silics trials. In clinical trials, the test has shown a very strong correlation to the fully sampled DIST SI (R=0.91), (which also uses insulin and c-peptide assays) and a strong correlation to the euglycemic hyperinsulinaemic clamp (EIC) in in silico virtual trials (R=0.89). This study shows that population estimates can reduce the need for expensive insulin and c-peptide assays in obtaining an accurate, real-time estimation of SI

Evaluation of the Performances and Costs of a Spectrum of DIST Protocols

The strategic design of most insulin sensitivity (SI) tests maximises either accuracy or economy, but not both. Hence, accurate, large-scale screening isn’t feasible. The DIST was developed to better optimize both important metrics. The highly flexible DIST protocol samples insulin, glucose and C-peptide during a comparatively short test. Varying the sampling periods and assays, and utilising alternative computational methods enables a wide range of tests with different accuracy and economy tradeoffs. The result is a hierarchy of tests to facilitate low-cost screening. Eight variations of the DIST are evaluated against the fully-sampled test by correlating the SI and endogenous insulin production (Uen(t)) metrics. Five variations include sample and assay reductions and three utilise DISTq parameter estimations. The DISTq identification methods only require glucose assays and thus enable real-time analysis. Three DISTq methods were tested; the fully-sampled, the Short, and the 30 minute two-sample protocol. 218 DIST tests were completed on 84 participants to provide the data for this study. Methods that assayed insulin replicated the findings of the full DIST particularly well (R=0.89~0.92) while those that assayed C-peptide managed to best replicate endogenous insulin metrics (R=0.72~1.0). The three DISTq protocols correlated to the fully-sampled DIST at R=0.83, 0.77 and 0.71 respectively. As expected, test resolution increased with rising protocol cost and intensity. The ability of significantly less expensive tests to replicate the values of the fully-sampled DIST was relatively high (R=0.92 with four glucose and two insulin assays and 0.71 with only two glucose assays). Thus, an SI screening programme could achieve high resolution at a low cost by using a lower resolution DIST test. When an individual’s result is close to a diagnostic threshold stored test samples could be re-assayed for more species to allow a higher resolution analysis without the need for a second invasive clinical test. Hence, a single test can lead to several outcomes with this hierarchy approach, enabling large scale screening with high resolution only where required with minimal and feasible economic cost and only a single invasive clinical procedure