A Lung Computed Tomographic Assessment of Positive End-Expiratory Pressure–induced Lung Overdistension

Abstract

The aim of this study was to assess positive end-expiratory pressure (PEEP)-induced lung overdistension and alveolar recruitment in six patients with acute lung injury (ALI) using a computed tomographic (CT) scan method. Lung overdistension was first determined in six healthy volunteers in whom CT sections were obtained at FRC and at TLC with a positive airway pressure of 30 cm H2O. In patients, lung volumes were quantified by the analysis of the frequency distribution of CT numbers on the entire lung at zero end-expiratory pressure (ZEEP) and PEEP. In healthy volunteers at FRC, the distribution of the density histograms was monophasic with a peak at -791 +/- 12 Hounsfield units (HU). The lowest CT number observed was -912 HU. At TLC, lung volume increased by 79 +/- 35% and the peak CT number decreased to -886 +/- 26 HU. More than 70% of the increase in lung volume was located below -900 HU, suggesting that this value can be considered as the threshold separating normal aeration from overdistension. In patients with ALI, at ZEEP the distribution of density histograms was either monophasic (n = 3) or biphasic (n = 3). The mean CT number was -319 +/- 34 HU. At PEEP 13 +/- 3 cm H2O, lung volume increased by 47 +/- 19% whereas mean CT number decreased to -538 +/- 171 HU. PEEP induced a mean alveolar recruitment of 320 +/- 160 ml and a mean lung overdistension of 238 +/- 320 ml. In conclusion, overdistended lung parenchyma of healthy volunteers is characterized by a CT number below -900 HU. This threshold can be used in patients with ALI for differentiating PEEP-induced alveolar recruitment from lung overdistension.

Modification in CSF specific gravity in acutely decompensated cirrhosis and acute on chronic liver failure independent of encephalopathy, evidences for an early blood-CSF barrier dysfunction in cirrhosis

“…Quantitative brain CT analysis was performed using the Brainview software (Institut National des Télécommunications) [17]. Briefly, this validated software [17,18] is aimed to analyze DICOM images acquired from cerebral CT scans by performing automatical segmentation excluding extracranial compartments on each slices. Interactive slice-by-slice segmentation allows to delineate different anatomical regions.…”

“…CT scanning and post-processing analysis by a dedicated software, Brainview (Institut Nationale des Télécommunications [15,17,18]), has already been used to assess SG in patients for the evaluation of brain edema [15,19,20]. Thus, studying CSF-SG allows this question to be addressed.…”

Computed Tomography Studies of Lung Mechanics

“…Regional aeration patterns from CT data were used to shed light on the distinct shape of the whole lung pressure-volume curve in patients with ALI (19), and a classification scheme for different types of ALI based on CT and other characteristics with different therapeutic and prognostic features has been proposed (46,47). Subsequent studies using high-speed scanning during brief breathholds have examined whole lung and lobar changes in lung air and tissue volumes (34,48,49), and have further emphasized the regional heterogeneity of the disease process and the importance of whole lung imaging for accurate assessment of regional behavior.…”

3D segmentation and visualization of lung and its structures using CT images of the thorax

“…This image is based on the principle that every internal structure of the human body possesses a determined radiologic density value, expressed in Hounsfield Units. The pulmonary densities adopted in this work are: hyper aerated (−1000 to −950 HU), normally aerated (−950 to −50 HU), poorly aerated (−500 to −100 HU), not aerated (−100 to 100 HU) and bone region (600 to 2000 HU) [27,28]. The distribution of these density bands is shown in Figure 1(b), in which the red color represents the hyper aerated region, the dark blue the normally aerated areas, the light blue represents the poorly aerated areas, and the black the non aerate areas, while the green represents the bone region and the white the non-classified area.…”