Improving image quality with model-based iterative reconstruction algorithm for chest CT in children with reduced...

Area of Science:

• Radiology
• Medical Imaging
• Pediatric Imaging

Background:

• Pediatric chest CT often requires a balance between image quality and radiation dose.
• Reducing contrast medium (CM) concentration can impact image quality.
• Iterative reconstruction techniques aim to improve image quality at lower radiation doses.

Purpose of the Study:

• To evaluate the effectiveness of model-based iterative reconstruction (MBIR) in enhancing image quality for pediatric chest CT scans.
• To assess MBIR's performance with reduced contrast medium (CM) concentration.
• To compare MBIR with adaptive statistical iterative reconstruction (ASIR) in pediatric patients.

Main Methods:

• Fifty-six children underwent low-dose enhanced chest CT with reduced CM (270 mgI/ml) at 100 kVp, reconstructed with 50% ASIR and MBIR.
• A control group of 56 children received standard chest CT (320 mgI/ml) at 120 kVp, reconstructed with ASIR only.
• Image quality was assessed subjectively (noise, enhancement, lesion conspicuity) and objectively (SNR, CNR).

Main Results:

• No significant difference in radiation dose between groups.
• The study group used 19.7% less CM, with diagnostic enhancement achieved.
• MBIR significantly reduced image noise by 58.6% and increased SNR (143.6%) and CNR (165.7%) compared to ASIR in the control group.
• ASIR images from both groups showed similar quality.

Conclusions:

• MBIR effectively improves image quality in low-radiation-dose pediatric chest CT.
• The use of MBIR allows for a reduction in contrast medium dose by 19.3% while maintaining diagnostic image quality.
• MBIR represents a valuable tool for optimizing pediatric chest CT protocols.