Objective: To present a novel algorithm for estimating recruitable alveolar collapse and hyperdistension based on electrical impedance tomography (EIT) during a decremental positive end-expiratory pressure (PEEP) titration. Design: Technical note with illustrative case reports. Setting: Respiratory intensive care unit. Patient: Patients with acute respiratory distress syndrome. Interventions: Lung recruitment and PEEP titration maneuver. Measurements and results: Simultaneous acquisition of EIT and X-ray computerized tomography (CT) data. We found good agreement (in terms of amount and spatial location) between the collapse estimated by EIT and CT for all levels of PEEP. The optimal PEEP values detected by EIT for patients 1 and 2 (keeping lung collapse \10%) were 19 and 17 cmH2O, respectively. Although pointing to the same non1dependent lung regions, EIT estimates of hyperdistension represent the functional deterioration of lung units, instead of their anatomical changes, and could not be compared directly with static CT estimates for hyperinflation. Conclusions: We described an EIT-based method for estimating recruitable alveolar collapse at the bedside, pointing out its regional distribution. Additionally, we proposed a measure of lung hyperdistension based on regional lung mechanics.