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Iterative reconstruction Vs. deep learning image reconstruction: comparison of image quality and diagnostic accuracy of arterial stenosis in low-dose lower extremity CT angiography

Br J Radiol. 2022 Nov 7:20220196. doi: 10.1259/bjr.20220196. Online ahead of print.


OBJECTIVE: To compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithms.

METHODS: Forty-six patients undergoing low-dose lower-extremity CTA were enrolled. Images were reconstructed using ASIR-V (blending factor of 50% (AV-50) and 100% (AV-100)) and DLIR (medium (DL-M), and high (DL-H)). CT values and standard deviation (SD) of the aorta, psoas, popliteal artery, popliteal and ankle muscles were measured. The edge-rise-distance (ERD) and edge-rise-slope (ERS) were calculated. The degrees of granularity and edge blurring were assessed using a 5-point scale. The stenosis degrees were measured on the four reconstructions, and their mean-square-errors (MSE) against that of digital subtraction angiography (DSA) were calculated and compared.

RESULTS: For both ASIR-V and DLIR, higher reconstruction intensity generated lower noise and higher SNR and CNR values. The SD values in AV-100 images were significantly lower than other reconstructions. The two DLIR image groups had higher ERS and lower ERD (DL-M:1.79 ± 0.37 mm and DL-H:1.82 ± 0.38 mm vs AV-50:1.96 ± 0.39 mm and AV-100:2.01 ± 0.36 mm, p = 0.014) than ASIR-V images. The overall image quality of DLIR was rated higher than ASIR-V (DL-M:0.83 ± 0.61, DL-H:0.41 ± 0.62, AV-50:1.85 ± 0.60 and AV-100:2.37 ± 0.77, p < 0.001), with DL-H having the highest overall image quality score. For stenosis measurement, DL-H had the lowest MSE compared to DSA among all reconstruction groups.

CONCLUSION: DLIR images had higher image quality ratings with lower image noise and sharper vessel walls in low-dose lower-extremity CTA, and DL-H provides the best overall image quality and highest accuracy in diagnosing artery stenoses.

PMID:36341682 | DOI:10.1259/bjr.20220196

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