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Dark-blood” Imaging in Coronary CT Angiography Using Dual layer Detector Spectral CT: Effect on Image Quality and Vessel Wall Visibility

管腔(解剖学) 医学 图像质量 核医学 对比度(视觉) 图像噪声 卡帕 放射科 人工智能 光学 物理 内科学 图像(数学) 数学 计算机科学 几何学
作者
Xiaodan Li,Xingyu Chen,Wen‐Cheng Chen,Chunhong Hu,Min Li,Zhixin Sun
出处
期刊:Current Medical Imaging Reviews [Bentham Science Publishers]
卷期号:21
标识
DOI:10.2174/0115734056361930251016081026
摘要

Introduction: To explore the potential of a newly developed subtraction technique in coronary computed tomography angiography (CCTA) for improving image quality and vessel wall visibility without introducing misregistration artifacts. Methods: Fifty-six patients who underwent CCTA scans using dual-layer detector spectral CT (SDCT) were retrospectively enrolled. Dark-blood images were generated by subtracting virtual non-contrast (VNC) datasets from 70-keV datasets. Qualitative evaluation of dark-blood images included assessments of image quality, inner-wall visualization, and outer-wall visualization. Quantitative parameters were compared between conventional CCTA images and dark-blood images. The quantitative assessment involved evaluating contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). SNR_wall, SNR_lumen, SNR_periaortic fat, CNR_wall-lumen, and CNR_wall-periaortic fat were calculated. Two experienced radiologists independently evaluated the images, and inter-rater variability was assessed. Results: Patients were categorized into three groups based on plaque types: Group A (calcified plaques, n=88), Group B (non-calcified plaques, n=15), and Group C (vessels without plaque, n=56). Dark-blood images of non-calcified plaques and vessels without plaque exhibited higher image quality and inner-wall visualization scores compared to calcified plaques (all p <0.05). The subjective scores of radiologists showed good consistency (all kappa values > 0.7). Compared to conventional images, dark-blood images demonstrated higher quantitative scores in terms of SNRwall, SNRlumen, SNRperiaortic fat, CNRwall-lumen, and CNRwall-periaortic fat (all p <0.001). Discussion: The dark-blood technique enabled superior coronary wall assessment without misregistration artifacts, overcoming a key limitation of prior subtraction CCTA. RCA motion artifacts remain a technical challenge that warrants phase-specific protocol optimization in our study. Conclusion: Dark-blood images derived from SDCT demonstrated improved image quality of coronary arteries without misregistration artifacts and enhanced visualization of the coronary vessel wall.

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