Artificial Intelligence Iterative Reconstruction in Computed Tomography Angiography: An Evaluation on Pulmonary Arteries and Aorta With Routine Dose Settings

Abstract

Objective The objective of this study is to investigate whether a newly introduced deep learning–based iterative reconstruction algorithm, namely, the artificial intelligence iterative reconstruction (AIIR), has a clinical value in computed tomography angiography (CTA), especially for visualizing vascular structures and related lesions, with routine dose settings. Methods A total of 63 patients were retrospectively collected from the triple rule-out CTA examinations, where both pulmonary and aortic data were available for each patient and were taken as the example for investigation. The images were reconstructed using the filtered back projection (FBP), hybrid iterative reconstruction (HIR), and the AIIR. The visibility of vasculature and pulmonary emboli and the general image quality were assessed. Results Artificial intelligence iterative reconstruction resulted in significantly (P < 0.001) lower noise as well as higher signal-to-noise ratio and contrast-to-noise ratio compared with FBP and HIR. Besides, AIIR achieved the highest subjective scores on general image quality (P < 0.05). For the vasculature visibility, AIIR offered the best vessel conspicuity, especially for the small vessels (P < 0.05). Also, >90% of emboli on the AIIR images were graded as sharp (score 5), whereas <15% of emboli on FBP and HIR images were scored 5. Conclusion As demonstrated for pulmonary and aortic CTAs, AIIR improves the image quality and offers a better depiction for vascular structures compared with FBP and HIR. The visibility of the pulmonary emboli was also increased by AIIR.

Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction

“…We applied DLIR to CTPA studies in suspected PE. Our results are in line with those that have been described for various cardiovascular CT applications including coronary CTA 19 – 23 , CT for planning of transcatheter aortic valve repair 24 , 25 , CT of the aorta 26 , head and neck CT angiography 27 and triple-rule-out CT 28 . In the field of thoracic imaging, several previous studies have investigated the value of DLIR with regards to pulmonary imaging and lung nodule detection.…”

“…Previously, DLIR has been shown to improve image denoising and increase image quality beyond the levels of achieved with iterative reconstruction techniques in various cardiovascular CT applications including coronary CTA 18 – 23 , CT for planning of transcatheter aortic valve repair 24 , 25 , CT of the aorta 26 , head and neck CT angiography 27 and triple-rule-out CT 28 . There are very limited data about DLIR in CTPA despite this being one of the most commonly performed cardiovascular CT examinations.…”