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Background  Indirect calorimetry is the standard method for estimating energy expenditure in clinical research. Few studies have evaluated indirect calorimetry in infants by comparing it with simultaneous direct calorimetry. Our purpose was (1) to compare the energy expenditure of preterm infants determined by these two methods, direct calorimetry and indirect calorimetry; and (2) to examine the effect of body position, supine or prone, on energy expenditure. Study Design  We measured energy expenditure by simultaneous direct (heat loss by gradient-layer calorimeter corrected for heat storage) and indirect calorimetry (whole-body oxygen consumption and carbon dioxide production) in 15 growing preterm infants during two consecutive interfeeding intervals, once in the supine position and once in the prone position. Results  The mean energy expenditure for all measurements in both positions did not differ significantly by the method used: 2.82 (standard deviation [SD] 0.42) kcal/kg/h by direct calorimetry and 2.78 (SD 0.48) kcal/kg/h by indirect calorimetry. The energy expenditure was significantly lower, by 10%, in the prone than in the supine position, whether examined by direct calorimetry (2.67 vs. 2.97 kcal/kg/h, p  < 0.001) or indirect calorimetry (2.64 vs. 2.92 kcal/kg/h, p  = 0.017). Conclusion  Direct calorimetry and indirect calorimetry gave similar estimates of energy expenditure. Energy expenditure was 10% lower in the prone position than in the supine position., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

Despite the potential utility of clinical breast examination (CBE), doctors' palpation skills are often inadequate and difficult to train. CBE sensitivity ranges from 39-59%, in part because current training does not effectively teach tactile skills. To address CBE training limitations, we developed a breast examination training model with 15 dynamically controlled lumps, set to desired hardness within underlying rib and muscle structures, in a silicone breast. In an experiment of 48 medical students, training with the dynamic model increased lump detection by 1.35 lumps compared to 0.60 lumps for a traditional breast model (P=0.008), reduced false positives by -0.70 lumps compared to +0.42 lumps (P=0.0277), and demonstrated skill transfer with a 1.17 lump detection improvement on the traditional device compared to only a 0.17 lump detection improvement by traditional device trainees on the dynamic device (P<0.001). Findings demonstrate the advantage of the dynamic model over conventional models in training CBE tactile skills.

Rationale and Objectives: Detection of endocardial and epicardial borders of the left ventricle (LV) using various imaging modalities is time-consuming and prone to interpretive error. An automatic border detection algorithm is presented that is used with ultrafast computed tomographic images of the heart to compute cavity volumes., Methods: The basal-level slice is identified, and the algorithm automatically detects the endocardial and epicardial borders of images from the basal to the apical levels. From these, the ventricular areas and chamber volumes are computed. The algorithm uses the Fuzzy Hough Transform, region-growing schemes, and optimal border-detection techniques. The cross-sectional areas and the chamber volumes computed with this technique were compared with those from manually traced images using canine hearts in vitro (n = 8) and studies in clinical patients (n = 27)., Results: Though the correlation was good (r = .88), the algorithm overestimated the LV epicardial area by 4.8 +/- 6.4 cm2, though this error was not statistically different from zero (P > .05). There was no difference in endocardial areas (r = .95, P > .05). The algorithm tended to underestimate the end-diastolic volume (r = .94) and the end-systolic volume (r = .94), although these errors were not statistically different from zero (P > .05). The algorithm tended to underestimate the ejection fraction (r = .80), although this error was not statistically different from zero (P > .05)., Conclusions: Automatic detection of myocardial borders provides the clinician with a useful tool for calculating chamber volumes and ejection fractions. The algorithm, with the corrections suggested, provides an accurate estimation of areas and volumes. This algorithm may be useful for contour border identification with ultrasound, positron-emission tomography, magnetic resonance imaging, and other imaging modalities in the heart, as well as other structures.

We have developed and validated a gradient-layer calorimeter for direct measurement of energy expenditure of preterm infants. Infant calorimeters must be operated and tested differently from adult calorimeters, because the calorimeter must be warmed during operation to limit heat loss from the infant, the calorimeter wall temperature (which is selected on the basis of the infant's maturity) must be precisely controlled, and energy expenditure (heat output) is typically < 10 W. We calibrated our calorimeter by varying the heat produced by a dry source (manikin or light bulb) with airflow (n = 42) and without airflow (n = 8) at various water jacket temperatures (n = 7) and by a wet source (combustion of ethyl alcohol) with airflow (n = 9). With no air moving, qc = 0.740 Vc + 0.029 Twj-0.697, where qc (W) is the estimated output of the heat source measured by the calorimeter, Vc (mV) is the gradient-layer voltage of the calorimeter, and Twj (degree C) is the temperature of the water jacket surrounding the walls of the device. From this equation and enthalpy calculations, the slope and intercept of the regression line relating the estimated heat production to the actual heat produced from alcohol combustion are 1.029 +/- 0.046 and -0.549 +/- 0.484 (SE), respectively. The slope is not significantly different from unity, and the intercept is not significantly different from zero. Thus we can accurately estimate the energy expenditure of preterm infants from the equations describing our calorimeter, and we can accurately resolve the total heat output into a dry (nonevaporative) component and a wet (evaporative) component.

Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final (improved) estimate of the true borders with other (subsequently used) image processing techniques. They present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough transform algorithm as part of a larger procedure to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications.

Quantitative evaluation of cardiac function from cardiac images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. This method is susceptible to great variability that depends on the experience and knowledge of the particular operator tracing the contours. The particular imaging modality that is used may also add tracing difficulties. Cine-computed tomography (cine-CT) is an imaging modality capable of providing high quality cross-sectional images of the heart. CT images, however, are cluttered, i.e., objects that are not of interest, such as the chest wall, liver, stomach, are also visible in the image. To decrease this variability, investigators have developed computer-assisted or near-automatic techniques for tracing these contours. All of these techniques, however, require some operator intervention to confidently identify myocardial borders. The authors present a new algorithm that automatically finds the heart within the chest, and then proceeds to outline (detect) the myocardial contours. Information at each tomographic slice is used to estimate the contours at the next tomographic slice, thus allowing the algorithm to work in near-apical cross-sectional images where the myocardial borders are often difficult to identify. The algorithm does not require operator input and can be used in a batch mode to process large quantities of data. An evaluation and correction phase is included to allow an operator to view the results and selectively correct portions of contours. The authors tested the algorithm by automatically identifying the myocardial borders of 27 cardiac images obtained from three human subjects and quantitatively comparing these automatically determined borders with those traced by an experienced cardiologist.

In order to assess regional diastolic function of the left ventricle (LV), we use LV cine-CT images to build finite element models. To quantitatively evaluate the accuracy of our geometric reconstruction technique used in building these models, we introduce a new measure of shape-similarity, and compare and contrast the results obtained from the new measure to the results obtained from traditional shape-similarity measures. All of these measures are used to compare the endocardial and epicardial LV contours obtained from cine-CT images of canine hearts with those obtained from video images of the same hearts. Our results show that our imaging procedure accurately reproduces shape, and further suggest that the new descriptor has the sensitivity and resolution required to distinguish between images separated by as little as 3 mm.

To quantify the immediate isocapnic respiratory response to baroreceptor stimulation, pressure in the isolated externally perfused carotid sinuses (CS) of 24 vagotomized alpha-chloralose-anesthetized dogs was increased selectively during either inspiration or expiration as a step (from time of onset to end of respiratory phase) or a pulse (500 ms). The rise time (150 ms), base-line pressure (80 mmHg), and stimulus magnitude (40 mmHg) were similar for the two stimuli. The time of stimulus onset (delay), expressed as a percent of control time of inspiration (TI) or expiration (TE), was varied. TI, TE, and tidal volume (VT) were expressed as percent changes from control. Stimuli delivered early in inspiration lengthened TI [23.5 +/- 6.4% (SE) for step and 11.7 +/- 6.3% for pulse stimuli at 5% delay] more effectively than late stimuli. VT was essentially unaltered. In contrast, step stimuli delivered during expiration caused a lengthening of TE (32.7 +/- 6.3% at 5% delay) that did not depend on the delay (up to 75%). Very late (85%) pulse stimuli lengthened TE (15.2 +/- 5.7%) more effectively than early stimuli. For both stimuli, the expiratory VT was unaltered. When the responses are compared before and after separation of the blood supply of the carotid bodies from the CS region and when they are compared before and after inhibition of reflex systemic hypotension by ganglionic blockade, the observed responses were shown to be due solely to CS baroreceptor stimulation and not to alterations in carotid body blood flow or reflex changes in systemic cardiovascular variables.

An in vitro comparison of the hydrodynamic characteristics of the Edwards-Duromedics (DM) and St Jude (SJ) bi-leaflet aortic valve prostheses is presented. Aortic valves 27 mm in diameter were mounted in a pulse duplicator simulating physiological pulsatile flow using a glycerol solution as the blood analogue fluid. Mean trans-valvular pressure difference (TPD) in systole, the per cent regurgitation (PCR) and the projected valve orifice area (VOA) were compared at a range of flow rates and heart rates to reflect the functioning of the valve under resting as well as exercise conditions. Our results showed that the TDP for DM (0.99 +/- 0.28 kPa) valve was slightly larger than the SJ (0.81 +/- 0.19 kPa) valve (mean difference of 0.18 +/- 0.26 kPa, P less than 0.05). However, the PCR for the DM (13.6 +/- 7.8) valve was smaller than the SJ (17.9 +/- 9.0) valve (mean difference of 4.3 +/- 4.2%, P less than 0.01). Moreover, VOA for the DM (2.51 +/- 0.10 cm2) valve was smaller than the SJ (3.13 +/- 0.04 cm2) valve (mean difference of 0.63 +/- 0.10 cm3, P less than 0.001).