Performance evaluation of using shorter contrast injection and 70 kVp with deep learning image reconstruction for reduced contrast medium dose and radiation dose in coronary CT angiography for children: a pilot study
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY(2021)
摘要
Background: Iterative reconstruction algorithms are often used to reduce image noise in low-dose coronary computed tomography angiography (CCTA) but encounter limitations. The newly introduced deep learning image reconstruction (DLIR) algorithm may provide new opportunities. We assessed the image quality and diagnostic performance of DLIR in low radiation dose and contrast medium dose CCTA of pediatric patients with 70 kVp and a shortened injection protocol. Methods: This was a prospective study. A total of 27 consecutive arrhythmic pediatric patients were enrolled in the study group and underwent CCTA using a prospective ECG-triggered single-beat protocol: tube voltage 70 kVp, automatic tube current modulation for a noise index (NI) of 22, and contrast dose of 0.4-0.6 mL/kg. Images were reconstructed with DLIR. They were compared with 27 matched patients in the control group scanned with 80 kVp, a lower NI setting (NI=19), and a higher contrast dose (0.8-1.2 mL/kg). The images in the control group were reconstructed using the adaptive statistical iterative reconstruction (ASIR-V) algorithm. The image contrast, image quality, and diagnostic confidence were assessed by 2 experienced radiologists using a 5-point scale (1: nondiagnostic and 5: excellent). The CT value and standard deviation of the aorta and perivascular tissue were measured, and the contrast-to-noise ratio (CNR) for the aorta was calculated. The contrast medium and radiation doses were compared. Results: The study and control groups had similar image contrast scores (4.75 +/- 0.57 vs. 4.78 +/- 0.42), image quality scores (3.67 +/- 0.47 vs. 3.44 +/- 0.51), and diagnostic confidence (4.74 +/- 0.44 vs. 4.74 +/- 0.45) (all P>0.05). There was an adequate enhancement in the aorta (614.74 +/- 127.73 vs. 705.89 +/- 111.20 HU) and similar CNR (20.34 +/- 4.64 vs. 20.99 +/- 4.14) in both groups. The image noise of the study group was lower in the aorta (30.61 +/- 3.88 vs. 34.77 +/- 3.49) and similar in perivascular tissue (27.66 +/- 6.24 vs. 27.55 +/- 3.33) compared with the control group. The study group reduced the total contrast medium dose by 53% to 15.07 +/- 3.68 mL and radiation dose by 36% to 0.57 +/- 0.31 mSv. Conclusions: The DLIR algorithm in CCTA for children using 70 kVp tube voltage with a shortened contrast medium injection protocol maintains image quality and diagnostic confidence while significantly reducing contrast medium dose and radiation dose compared with the use of the conventional CCTA protocol.
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关键词
Tomography,X-ray computed,coronary angiography,child,deep learning,image reconstruction
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