Image quality in CT thorax: effect of altering reconstruction algorithm and tube load.
Bharti KatariaMischa WoisetschlägerJonas Nilsson AlthénMichael SandborgÖrjan SmedbyPublished in: Radiation protection dosimetry (2024)
Non-linear properties of iterative reconstruction (IR) algorithms can alter image texture. We evaluated the effect of a model-based IR algorithm (advanced modelled iterative reconstruction; ADMIRE) and dose on computed tomography thorax image quality. Dual-source scanner data were acquired at 20, 45 and 65 reference mAs in 20 patients. Images reconstructed with filtered back projection (FBP) and ADMIRE Strengths 3-5 were assessed independently by six radiologists and analysed using an ordinal logistic regression model. For all image criteria studied, the effects of tube load 20 mAs and all ADMIRE strengths were significant (p < 0.001) when compared to reference categories 65 mAs and FBP. Increase in tube load from 45 to 65 mAs showed image quality improvement in three of six criteria. Replacing FBP with ADMIRE significantly improves perceived image quality for all criteria studied, potentially permitting a dose reduction of almost 70% without loss in image quality.
Keyphrases
- image quality
- deep learning
- computed tomography
- artificial intelligence
- dual energy
- machine learning
- convolutional neural network
- quality improvement
- end stage renal disease
- positron emission tomography
- ejection fraction
- big data
- newly diagnosed
- chronic kidney disease
- contrast enhanced
- magnetic resonance imaging
- depressive symptoms
- physical activity
- solid state
- patient safety
- data analysis
- magnetic resonance
- patient reported
- optical coherence tomography