Computed tomography of the chest with model-based iterative reconstruction using a radiation exposure similar to chest X-ray examination: preliminary observations
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The purpose of this study was to assess the diagnostic image quality of ultra-low-dose chest computed tomography (ULD-CT) obtained with a radiation dose comparable to chest radiography and reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in comparison with standard dose diagnostic CT (SDD-CT) or low-dose diagnostic CT (LDD-CT) reconstructed with FBP alone.
Unenhanced chest CT images of 42 patients acquired with ULD-CT were compared with images obtained with SDD-CT or LDD-CT in the same examination. Noise measurements and image quality, based on conspicuity of chest lesions on all CT data sets were assessed on a five-point scale.
The radiation dose of ULD-CT was 0.16 ± 0.006 mSv compared with 11.2 ± 2.7 mSv for SDD-CT (P < 0.0001) and 2.7 ± 0.9 mSv for LDD-CT. Image quality of ULD-CT increased significantly when using MBIR compared with FBP or ASIR (P < 0.001). ULD-CT reconstructed with MBIR enabled to detect as many non-calcified pulmonary nodules as seen on SDD-CT or LDD-CT. However, image quality of ULD-CT was clearly inferior for characterisation of ground glass opacities or emphysema.
Model-based iterative reconstruction allows detection of pulmonary nodules with ULD-CT with radiation exposure in the range of a posterior to anterior (PA) and lateral chest X-ray.
• Radiation dose is a key concern with the increased use of thoracic CT
• Ultra-low-dose chest CT approximates the radiation dose of conventional chest radiography
• Ultra-low-dose chest CT can be of diagnostic quality
• Solid pulmonary nodules are clearly depicted on ultra-low-dose chest CT
KeywordsComputed tomography Chest Low dose Pulmonary nodules Model-based iterative reconstruction (MBIR)
Ultra-low-dose chest CT
Standard-dose diagnostic CT
Low-dose diagnostic CT
Filtered back projection
Adaptive statistical iterative reconstruction
Model-based iterative reconstruction
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