Abstract

Regional specific lung volume change (sVol), defined as the regional tidal volume divided by the regional end-expiratory gas volume, is a key variable in lung mechanics and in the pathogenesis of ventilator-induced lung injury. Despite the usefulness of PET to study regional lung function, there is no established method to assess sVol with PET. We present a method to measure sVol from respiratory-gated PET images of inhaled (13)N-nitrogen ((13)NN), validate the method against regional specific ventilation (sV), and study the effect of region-of-interest (ROI) volume and orientation on the sVol-sV relationship. Four supine sheep were mechanically ventilated (tidal volume V(T) = 8 mL/kg, respiratory rate adjusted to normocapnia) at low (n = 2, positive end-expiratory pressure = 0) and high (n = 2, positive end-expiratory pressure adjusted to achieve a plateau pressure of 30 cm H(2)O) lung volumes. Respiratory-gated PET scans were obtained after inhaled (13)NN equilibration both at baseline and after a period of mechanical ventilation. We calculated sVol from (13)NN-derived regional fractional gas content at end-inspiration (F(EI)) and end-expiration (F(EE)) using the formula sVol = (F(EI) - F(EE))/(F(EE)[1 - F(EI)]). sV was computed as the inverse of the subsequent (13)NN washout curve time constant. ROIs were defined by dividing the lung field with equally spaced coronal, sagittal, and transverse planes, perpendicular to the ventrodorsal, laterolateral, and cephalocaudal axes, respectively. sVol-sV linear regressions for ROIs based on the ventrodorsal axis yielded the highest R(2) (range, 0.71-0.92 for mean ROI volumes from 7 to 162 mL), the cephalocaudal axis the next highest (R(2) = 0.77-0.88 for mean ROI volumes from 38 to 162 mL), and the laterolateral axis the lowest (R(2) = 0.65-0.83 for mean ROI volumes from 8 to 162 mL). ROIs based on the ventrodorsal axis yielded lower standard errors of estimates of sVol from sV than those based on the laterolateral axis or the cephalocaudal axis. sVol can be computed with PET using the proposed method and is highly correlated with sV. Errors in sVol are smaller for larger ROIs and for orientations based on the ventrodorsal axis.

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