In silico evaluation of a control system and algorithm for automated insulin infusion in the ICU setting.

BACKGROUND: It is known that tight control of glucose in the Intensive Care Unit reduces morbidity and mortality not only in diabetic patients but also in those non-diabetics who become transiently hyperglycemic. Taking advantage of a recently marketed subcutaneous glucose sensor we designed an Automatic Insulin Infusion System (AIIS) for inpatient treatment, and tested its stability under simulated clinical conditions. METHODS: The system included: reference glucose, glucose sensor, insulin and glucose infusion controllers and emergency infusion logic. We carried out computer simulations using Matlab/Simulink, in both common and worst-case conditions. RESULTS: The system was capable of controlling glucose levels without entering in a phase of catastrophic instability, even under severe simulated challenges. Care was taken to include in all simulations the 5-10 minute delay of the subcutaneous glucose signal when compared to the real-time serum glucose signal, a well-known characteristic of all subcutaneous glucose sensors. CONCLUSIONS: When tested in-Silico, a commercially available subcutaneous glucose sensor allowed the stable functioning of a proportional-derivative Automatic Insulin Infusion System, which was able to maintain glucose within acceptable limits when using a well-established glucose response model simulating a patient. Testing of the system in vivo using animal models is now warranted.

Enhancement of visual perception with use of dynamic cues.

UNLABELLED: Institutional review board approval and signed informed consent were not needed, as medical images included in public databases were used in this study. The purpose of this study was to improve the detection of microcalcifications on mammograms and lung nodules on chest radiographs by using the dynamic cues algorithm and the motion and flickering sensitivity of the human visual system (HVS). Different sets of mammograms from the Mammographic Image Analysis Society database and chest radiographs from the Japanese Society of Radiological Technology database were presented statically, as is standard, and in a video sequence generated with the dynamic cues algorithm. Nine observers were asked to rate the presence of abnormalities with a five-point scale (1, definitely not present; 5, definitely present). The data were analyzed with receiver operating characteristic (ROC) techniques and the Dorfman-Berbaum-Metz method. The video sequence generated with the dynamic cues algorithm increased the rate of detection of microcalcifications by 10.2% (P = .002) compared with that obtained with the standard static method, as measured by the area under the ROC curve. Similar results were obtained for lung nodules, with an increase of 12.3% (P = .0054). The increase in the rate of correct detection did not come just from the image contrast change produced by the algorithm but also from the fact that image frames generated with the dynamic cues algorithm were put together in a video sequence so that the motion sensitivity of the HVS could be used to facilitate the detection of low-contrast objects. SUPPLEMENTAL MATERIAL: http://radiology.rsnajnls.org/cgi/content/full/250/2/551/DC1.

Magnetic resonance imaging for nondestructive analysis of wine grapes.

Magnetic resonance imaging (MRI) was used to study the growth and ripening of grape berries for three varieties. The results show that this technique allows the visualization of internal characteristics of berries using noninvasive procedures in order to obtain the volume and degrees Brix distribution within a cluster. Samples of Cabernet Sauvignon, Carmenère, and Chardonnay varieties collected over the 2002 season were analyzed. Calibration models were developed to correlate soluble solids (degrees Brix) against spin-lattice relaxation time t(1) and spin-spin relaxation time t(2). The correlation of degrees Brix and t(1) was R(2) = 0.75 for Cabernet Sauvignon, R(2) = 0.8 for Carmenère, and R(2) = 0.65 for Chardonnay. In the case of t(2) the correlation was significantly lower. Reconstruction techniques for the three-dimensional representation of clusters were developed, allowing an interactive visualization of the bunches. The method also provides volume measurements of single berries and their distribution within the cluster with an accuracy of 3% and R(2) = 0.98. These results show the potential of MRI in the wine industry for both monitoring and research. Not only does it provide quantitative information about the berries such as volume and degrees Brix distributions, but it can also be used to support the sampling procedures by providing a better cluster characterization.