Monotone Signal Segments Analysis as a novel method of breath detection and breath-to-breath interval analysis in rat

Abstract

We applied a novel approach to respiratory waveform analysis -Monotone Signal Segments Analysis (MSSA) on 6-h recordings of respiratory signals in rats. To validate MSSA as a respiratory signal analysis tool we tested it by detecting: breaths and breath-to-breath intervals; by detecting respiratory timing and volume modes; and by detecting changes in respiratory pattern caused by lesions of monoaminergic systems in rats.MSSA differentiated three respiratory timing (tachypneic, eupneic, bradypneic-apneic), and three volume (artifacts, normovolemic, hypervolemic-sighs) modes. Lesion-induced respiratory pattern modulation was visible as shifts in the distributions of monotone signal segment amplitudes, and of breath-to-breath intervals. Specifically, noradrenergic lesion induced an increase in mean volume (p ≤ 0.03), with no change of the mean breath-to-breath interval duration (p ≥ 0.06). MSSA of timing modes detected noradrenergic lesion-induced interdependent changes in the balance of eupneic (decrease; p ≤ 0.02), and tachypneic (an increase; p ≤ 0.02) breath intervals with respect to control. In terms of breath durations within each timing mode, there was a tendency toward prolongation of the eupneic (p ≤ 0.08) and bradypneic-apneic (p ≤ 0.06) intervals. These results demonstrate that MSSA is sensitive to subtle shifts in respiratory rhythmogenesis not detectable by simple respiratory pattern descriptive statistics. MSSA represents a potentially valuable new tool for investigations of respiratory pattern control.

Nonlinear motion compensation using cubature Kalman filter forin vivofluorescence microendoscopy in peripheral lung cancer intervention

“…In animal-based cancer research, this technology enables researchers to detect cancerous tissues, to discern the expression of specific genes using different auxiliary dyes, and to observe tumor growth and treatment responses. 12 Therefore, motion correction on the microendoscopy image sequence clips helps improve the visualization and quantification of tissue characteristics. [1][2][3] In lung cancer applications, in vivo detection of fluorescencelabeled tumor cells coupled with image-guided intervention have added new dimensions for on-site peripheral lung cancer diagnosis 4-7 due to its extraordinary ability of providing micron-scale resolution images in tissues inaccessible to light microscopy.…”