PT  - JOURNAL ARTICLE
AU  - Johanna Laura Mayer
AU  - Claus Peter Heußel
AU  - Hans-Ulrich Kauczor
AU  - Klaus Markstaller
AU  - Michael Puderbach
AU  - Oliver Weinheimer
AU  - Stefan Boehme
AU  - Erik Hartmann
AU  - Ulrich Klein
AU  - Bastian Schmack
AU  - Gregor Pahn
AU  - Wolfram Stiller
TI  - Four-dimensional (4D) quantification of ventilation using dynamic MDCT imaging in a porcine model of ARDS
DP  - 2014 Sep 01
TA  - European Respiratory Journal
PG  - P4973
VI  - 44
IP  - Suppl 58
4099  - http://erj.ersjournals.com/content/44/Suppl_58/P4973.short
4100  - http://erj.ersjournals.com/content/44/Suppl_58/P4973.full
SO  - Eur Respir J2014 Sep 01; 44
AB  - In acute lung injury (ARDS) oxygenation is essential. It is determined by the volume of lungs ventilated during the entire respiratory cycle. Therefore, the central objective of this study is an image-based quantification of ventilated lung volume in order to determine the part of recruitable atelectasis with the goal of optimizing ventilation strategies.Dynamic acquisitions of 11 mechanically ventilated pigs (PEEP 0 or 5 mbar) have been conducted using 128-slice MDCT before and after induction of ARDS by surfactant wash-out. Total acquisition time was 26s over a detector range of 8cm. At all-time points of the respiratory cycle, image volumes have been analyzed semi-automatically with a software (YACTA) developed in-house.YACTA-based analysis shows a strong correlation of cyclic variations induced by respiration and lung parenchyma density values of morphologically well-ventilated (WV) lung volume [-900; -501HU], hypoventilated (HV) volume [-500; -101HU] and atelectasis (A) [-100; 100HU]. While the volume of HV lungs shows no shift, the WV lung volume increases (57% to 67%) and A decreases (18% to 12%) by increasing PEEP after ARDS induction. ARDS-induced A varies during the breathing cycle which corresponds to cyclic recruitment of lung parenchyma.Through the use of dynamic CT and software-based evaluation it is possible to quantify effects of ARDS and the clinical effects of different automated mechanical ventilation regimes throughout the whole respiratory cycle for the first time. Translation of this setting into clinical treatment is technically feasible. It could make an important contribution to individualized optimization of ventilation parameters.