The goal of this study was to compare the relative performance of two noninvasive ventilation sensing technologies on adults during artifacts. We recorded changes in transthoracic impedance and cross-sectional area of the abdomen (abd) and rib cage (rc) using impedance pneumography (IP) and respiratory inductance plethysmography (RIP) on ten adult subjects during natural breathing, motion artifact, simulated airway obstruction, yawning, snoring, apnea, and coughing. We used a pneumotachometer to measure air flow and tidal volume as the standard. We calibrated all sensors during natural breathing, and performed measurements during all maneuvers without changing the calibration parameters. No sensor provided the most-accurate measure of tidal volume for all maneuvers. Overall, the combination of inductance sensors [RIP(sum)] calibrated during an isovolume maneuver had a bias (weighted mean difference) as low or lower than all individual sensors and all combinations of sensors. The IP(rc) sensor had a bias as low or lower than any individual sensor. The cross-correlation coefficient between sensors was high during natural breathing, but decreased during artifacts. The cross correlation between sensor pairs was lower during artifacts without breathing than it was during maneuvers with breathing for four different sensor combinations. We tested a simple breath-detection algorithm on all sensors and found that RIP(sum) resulted in the fewest number of false breath detections, with sensitivity of 90.8% and positive predictivity of 93.6%.

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Two-dimensional response curves are an important experimental outcome in speech kinematics and other areas of research. These parameterized curves are usually obtained by recording the two-dimensional location of an object over time. In this setting, time is the independent variable and the x and y locations on specified coordinate axes define the multivariate response. Collections of such parameterized curves can be obtained either from one subject or from a number of different subjects, each producing one or several realizations of the response curve. When only one dependent variable is observed over time and no parametric model is specified, self-modeling regression (SEMOR) is an attractive modeling approach. SEMOR assumes that each of a collection of curves differs from a smooth, average shape function by some simple parametric transformation of the coordinate axes (usually linear). We will describe the extension of SEMOR to two-dimensional parameterized curves using affine transformations of a two-dimensional, time-parameterized shape function.

The objective of this study was to document the utility of computed tomography (CT) and a three‐dimensional (3‐D) radiotherapy treatment planning system for assessing the development of acute radiation pneumonitis in a canine model. Fourteen dogs were randomly assigned to a nonirradiated control group or one of three radiation dose groups receiving a single fraction of either 12, 15, or 18 Gy delivered to two‐thirds of the right hemithorax. CT and survey radiographs were performed in all dogs prior to and at defined intervals for up to 13 weeks following irradiation. All images were subjectively evaluated for development of radiation pneumonitis and CT images were quantitatively analyzed. Radiation pneumonitis was detected earlier with CT images than with radiographs. Quantitatively, functional lung volume and radiation pneumonitis lesion volume on CT images changed over time in all irradiated dogs. However, there was no statistically significant difference between the three radiation dose groups, but a marked difference between irradiated dogs and nonirradiated controls. These data suggest that CT is superior to survey radiography for the evaluation and quantification of acute radiation pneumonitis in this canine model. Quantification of acute radiation pneumonitis suggests future promise for evaluating the efficacy of modifiers to lessen the effects of irradiating normal lung tissue in this canine model. Radiat. Oncol. Invest. 6:128–134, 1998. © 1998 Wiley‐Liss, Inc.