ArticleEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2020
Comparison of thick- and thin-slice images in thoracoabdominal trauma CT: a retrospective analysis.
Article in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Deep learning for acute rib fracture detection in CT data: a systematic review and meta-analysis.The British journal of radiology · 2024Pooled it
- Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT.NPJ digital medicine · 2024Article
- Implementation of artificial intelligence in the histological assessment of pulmonary subsolid nodules.Translational lung cancer research · 2021Article
- Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet.EBioMedicine · 2020Article
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9 authors at 1 institution in 1 country.
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Abstract
purposeTo compare thick (5 mm) and thin slice images (1.5 mm) of lung, soft tissue, and bone window in thoracoabdominal trauma computed tomography. MATERIALS AND
methods167 Patients that underwent thoracoabdominal trauma CT between November 2014 and December 2015 were included in the study. CT data were reconstructed in a transverse direction with 5 mm and 1.5 mm slice images of lung, soft tissue, and bone window. Two blinded raters (radiologists) evaluated the collected data by detecting predefined injuries in different organ areas. Reconstruction and evaluation times as well as detected injuries were noted and compared.
resultsReconstruction and evaluation times were significantly higher with 1.5 mm thin-slice images, and the effect strength according to Rosenthal displayed a strong effect of 0.61 (< 0.1 small effect, 0.3 middle effect, and > 0.5 strong effect). Average evaluation time differences were 62.7 s (33.9 s-91.5 s) in bone window between 1.5 mm and 3 mm for rater 1 (p < 0.001) and 71.4 s (43.1 s-99.7 s) for rater 2 (p < 0.001). Average time differences between 1.5 mm and 5 mm were 68,7 s (43.9 s-93.5 s) for rater 1 and 75.3 s (44.7 s-105.9 s) for rater 2 in lung window (p < 0.001) and 66.6 s (28.8 s-104.4 s) for rater 1 and 114 s (74.4 s-153.6 s) for rater 2 in soft-tissue window (p < 0.001). There was no significant difference regarding soft-tissue and lung injuries, except non-significant improvement in the detection of bone fractures.
conclusionThin-slice images do not bring any significant benefit in thoracoabdominal trauma CT of soft-tissue and lung injuries, but they can be helpful for the diagnosis of bone fractures and incidental findings.
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