Iterative reconstruction algorithm improves the image quality without affecting quantitative measurements of computed...

Area of Science:

• Radiology
• Medical Imaging
• Quantitative Perfusion Imaging

Background:

• Computed tomography perfusion (CTP) is crucial for assessing upper abdominal organ perfusion.
• Reconstruction algorithms can influence quantitative perfusion values and image quality.
• Evaluating the impact of different algorithms is essential for accurate CTP analysis.

Purpose of the Study:

• To compare quantitative perfusion values and time-attenuation curves derived from different CTP reconstruction algorithms.
• To assess the effect of advanced modeled iterative reconstruction (ADMIRE) on upper abdominal CTP data.
• To evaluate image noise and signal-to-noise ratio (SNR) across various reconstruction settings.

Main Methods:

• Twenty-six CTP examinations of the upper abdomen were reconstructed using filtered back projection and ADMIRE with varying noise reduction.
• Quantitative perfusion parameters (blood flow, blood volume, time to peak) and time-attenuation curves were measured.
• Statistical analysis, including mixed-model analysis and Friedman's test, was employed to compare reconstructions.

Main Results:

• No significant differences were observed in quantitative perfusion measurements or time-attenuation curve AUC values across the four reconstructions for any tissue.
• Significant differences in image noise and SNR were found between the reconstruction algorithms.
• Iterative reconstructions with higher noise reduction demonstrated lower image noise and higher SNR.

Conclusions:

• ADMIRE does not significantly alter quantitative perfusion values or time-attenuation curves in upper abdominal CTP.
• Iterative reconstruction, particularly with increased noise reduction, enhances image quality by reducing noise and improving SNR.
• These findings support the use of iterative reconstruction in CTP for improved image quality without compromising quantitative accuracy.