OBJECTIVE: Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows real-time monitoring of regional lung ventilation ([Formula: see text]) in intensive care patients at bedside. However, for improved guidance of ventilation therapy it would be beneficial to obtain regional ventilation-to-perfusion ratio ([Formula: see text]) by EIT. APPROACH: In order to further explore the feasibility, we first evaluate a model-based approach, based on semi-negative matrix factorization and a gamma-variate model, to extract regional lung perfusion ([Formula: see text]) from EIT measurements. Subsequently, a combined validation of both [Formula: see text] and [Formula: see text] measured by EIT against single-photon emission computed tomography (SPECT) is performed on data acquired as part of a porcine animal trial. Four pigs were ventilated at two different levels of positive end-expiratory pressure (PEEP 0 and 15 cm H2O, respectively) in randomized order. Repeated injections of an EIT contrast agent (NaCl 10%) and simultaneous SPECT measurements of [Formula: see text] (81mKr gas) and [Formula: see text] (99mTc-labeled albumin) were performed. MAIN RESULTS: Both [Formula: see text] and [Formula: see text] from EIT and SPECT were compared by correlation analysis. Very strong (r 2 = 0.94 to 0.95) correlations were found for [Formula: see text] and [Formula: see text] in the dorsal-ventral direction at both PEEP levels. Moderate (r 2 = 0.36 to 0.46) and moderate to strong (r 2 = 0.61 to 0.82) correlations resulted for [Formula: see text] and [Formula: see text] in the right-left direction, respectively. SIGNIFICANCE: The results of combined validation indicate that monitoring of [Formula: see text] and [Formula: see text] by EIT is possible. However, care should be taken when trying to quantify [Formula: see text] by EIT, as imaging artefacts and model bias may void necessary spatial matching.
OBJECTIVE: Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows real-time monitoring of regional lung ventilation ([Formula: see text]) in intensive care patients at bedside. However, for improved guidance of ventilation therapy it would be beneficial to obtain regional ventilation-to-perfusion ratio ([Formula: see text]) by EIT. APPROACH: In order to further explore the feasibility, we first evaluate a model-based approach, based on semi-negative matrix factorization and a gamma-variate model, to extract regional lung perfusion ([Formula: see text]) from EIT measurements. Subsequently, a combined validation of both [Formula: see text] and [Formula: see text] measured by EIT against single-photon emission computed tomography (SPECT) is performed on data acquired as part of a porcine animal trial. Four pigs were ventilated at two different levels of positive end-expiratory pressure (PEEP 0 and 15 cm H2O, respectively) in randomized order. Repeated injections of an EIT contrast agent (NaCl 10%) and simultaneous SPECT measurements of [Formula: see text] (81mKr gas) and [Formula: see text] (99mTc-labeled albumin) were performed. MAIN RESULTS: Both [Formula: see text] and [Formula: see text] from EIT and SPECT were compared by correlation analysis. Very strong (r 2 = 0.94 to 0.95) correlations were found for [Formula: see text] and [Formula: see text] in the dorsal-ventral direction at both PEEP levels. Moderate (r 2 = 0.36 to 0.46) and moderate to strong (r 2 = 0.61 to 0.82) correlations resulted for [Formula: see text] and [Formula: see text] in the right-left direction, respectively. SIGNIFICANCE: The results of combined validation indicate that monitoring of [Formula: see text] and [Formula: see text] by EIT is possible. However, care should be taken when trying to quantify [Formula: see text] by EIT, as imaging artefacts and model bias may void necessary spatial matching.
Authors: Paolo Pelosi; Lorenzo Ball; Carmen S V Barbas; Rinaldo Bellomo; Karen E A Burns; Sharon Einav; Luciano Gattinoni; John G Laffey; John J Marini; Sheila N Myatra; Marcus J Schultz; Jean Louis Teboul; Patricia R M Rocco Journal: Crit Care Date: 2021-07-16 Impact factor: 9.097