Evaluating Image Quality and Radiation Dose in Low-Dose Thoraco-Abdominal CT Angiography with a Tin Filter for Patients with Aortic Disease

Author:

Oh Chang Hoon1ORCID,Cho Soo Buem2,Kwon Hyeyoung3

Affiliation:

1. Department of Radiology, Ewha Womans Mokdong Hospital, College of Medicine, Ewha Womans University, Seoul 07985, Republic of Korea

2. Department of Radiology, Ewha Womans Seoul Hospital, College of Medicine, Ewha Womans University, Seoul 07804, Republic of Korea

3. Department of Radiology, Chungnam University Hospital, School of Medicine, Chungnam University, Daejeon 35015, Republic of Korea

Abstract

Background: We aimed to compared radiation exposure and image quality between tin-filter-based and standard dose thoraco-abdominal computed tomography angiography (TACTA) protocols, aiming to address a gap in the existing literature. Methods: In this retrospective study, ninety consecutive patients undergoing TACTA were included. Of these, 45 followed a routine standard-dose protocol (ST100kV), and 45 underwent a low-dose protocol with a tin filter (TF100kV). Radiation metrics were compared. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and figure of merit (FOM) were calculated for the thoracic and abdominal aorta and right common iliac artery. Two independent readers assessed the image noise, image contrast, sharpness, and subjective image quality. Results: The mean dose for the TF100kV group was significantly lower (DLP 128.25 ± 18.18 mGy*cm vs. 662.75 ± 181.29, p < 0.001; CTDIvol 1.83 ± 0.25 mGy vs. 9.28 ± 2.17, p = 0.001), with an effective dose close to 2.3 mSv (2.31 ± 0.33 mSv; p < 0.001). The TF100kV group demonstrated greater dose efficiency (FOM, thoracic aorta: 36.70 ± 22.77 vs. 13.96 ± 13.18 mSv−1, p < 0.001) compared to the ST100kV group. Conclusions: Dedicated low-dose TACTA using a tin filter can significantly reduce the radiation dose while maintaining sufficient diagnostic image quality.

Funder

Ewha Womans University Research Grant

Publisher

MDPI AG

Reference18 articles.

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2. The evolution of image reconstruction for CT—From filtered back projection to artificial intelligence;Willemink;Eur. Radiol.,2019

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