Observational studyBMC anesthesiology2016
Lung hyperaeration assessment by computed tomography: correction of reconstruction-induced bias.
Observational study in BMC anesthesiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Case Report: Chronic eosinophilic pneumonia with acute-like presentation and diagnostic challenges.Frontiers in medicine · 2026Article
- Effect of slice thickness on quantitative analysis of interstitial lung disease: a retrospective volumetric chest CT study.La Radiologia medica · 2025Article
- Early versus late intubation in COVID-19 patients failing helmet CPAP: A quantitative computed tomography study.Respiratory physiology & neurobiology · 2022Article
- Extension of Collagen Deposition in COVID-19 Post Mortem Lung Samples and Computed Tomography Analysis Findings.International journal of molecular sciences · 2021Article
- An Experimental Pre-Post Study on the Efficacy of Respiratory Physiotherapy in Severe Critically III COVID-19 Patients.Journal of clinical medicine · 2021Article
- Automatic Lung Segmentation and Quantification of Aeration in Computed Tomography of the Chest Using 3D Transfer Learning.Frontiers in physiology · 2021Article
- Magnetic Resonance Imaging for Quantitative Assessment of Lung Aeration: A Pilot Translational Study.Frontiers in physiology · 2018Article
- Ultra-low-dose sequential computed tomography for quantitative lung aeration assessment-a translational study.Intensive care medicine experimental · 2017Article
- Lung imaging: how to get better look inside the lung.Annals of translational medicine · 2017Review
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Authors and funding
8 authors.
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Abstract
backgroundComputed tomography (CT) reconstruction parameters, such as slice thickness and convolution kernel, significantly affect the quantification of hyperaerated parenchyma (VHYPER%). The aim of this study was to investigate the mathematical relation between VHYPER% calculated at different reconstruction settings, in mechanically ventilated and spontaneously breathing patients with different lung pathology.
methodsIn this retrospective observational study, CT scans of patients of the intensive care unit and emergency department were collected from two CT scanners and analysed with different kernel-thickness combinations (reconstructions): 1.25 mm soft kernel, 5 mm soft kernel, 5 mm sharp kernel in the first scanner; 2.5 mm slice thickness with a smooth (B41s) and a sharp (B70s) kernel on the second scanner. A quantitative analysis was performed with Maluna® to assess lung aeration compartments as percent of total lung volume. CT variables calculated with different reconstructions were compared in pairs, and their mathematical relationship was analysed by using quadratic and power functions.
results43 subjects were included in the present analysis. Image reconstruction parameters influenced all the quantitative CT-derived variables. The most relevant changes occurred in the hyperaerated and normally aerated volume compartments. The application of a power correction formula led to a significant reduction in the bias between VHYPER% estimations (p < 0.001 in all cases). The bias in VHYPER% assessment did not differ between lung pathology nor ventilation mode groups (p > 0.15 in all cases).
conclusionsHyperaerated percent volume at different reconstruction settings can be described by a fixed mathematical relationship, independent of lung pathology, ventilation mode, and type of CT scanner.
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