基于深度学习的T2 Flair序列提升白质高信号图像质量的价值
Value of T2 Flair sequence based on deep learning in improving image quality of white matter hyperintensities
赵如盛 1徐露露 1李青 1徐义程 2张久楼 1荣凡令1
作者信息
- 1. 南京医科大学第一附属医院放射科,南京 210029
- 2. 西门子医疗系统有限公司,上海 200126
- 折叠
摘要
目的 探讨基于深度学习重建(deep learning reconstruction,DLR)算法的T2液体衰减反转恢复(fluid-attenuated inversion recovery,Flair)序列在提升白质高信号(white matter hyperintensity,WMH)图像质量中的应用价值.材料与方法 前瞻性纳入临床怀疑脑缺血性疾病的患者50例.对患者分别行常规T2 Flair序列和基于DLR算法的高分辨T2 Flair序列扫描.其中DLR Flair序列选择保留未经DLR处理而采用常规重建算法的预处理图像(记为Pre-DLR).采用4分法对三组图像从图像锐利度、灰-白质对比度、脑脊液-脉络丛对比度、WMH显示以及整体图像质量五个方面进行主观评分;比较三组图像中WMH的检出数目和WMH的信噪比(signal-to-noise ratio,SNR)、对比噪声比(contrast-to-noise ratio,CNR).结果 主观评价中,DLR组图像在图像锐利度、灰-白质对比度、脑脊液-脉络丛对比度、WMH显示以及整体图像质量的各项评分中均高于常规组和Pre-DLR组(P均＜0.05);在WMH的计数方面,DLR组识别出的数量大于常规组(P＜0.05)而与Pre-DLR组差异无统计学意义.客观评价中,DLR组的WMH的SNR和CNR均高于常规组和Pre-DLR组(P均＜0.05).结论 与常规序列相比,结合DLR算法的高分辨T2 Flair序列可以实现在不增加扫描时间的前提下提高WMH图像质量、发现更多WMH微小病灶.
Abstract
Objective:To explore the application value of T2 fluid-attenuated inversion recovery(Flair)sequence based on deep learning reconstruction(DLR)algorithm in improving the image quality of white matter hyperintensities(WMH).Materials and Methods:Fifty patients with suspected cerebral ischemic disease were prospectively recruited.Both the conventional T2 FLAIR sequence and the high-resolution T2 Flair sequence,utilizing the DLR algorithm,were conducted on the patients.The DLR Flair sequence selected for this study retained the pre-processed images that have undergone conventional reconstruction algorithms without DLR processing(referred to as Pre-DLR).Subjective evaluations were performed on three groups of images using a 4-point scale to assess image sharpness,gray-white matter contrast,cerebrospinal fluid-choroid plexus contrast,WMH display,and overall image quality.Comparisons were made between the number of WMH detections,the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of WMH in three sets of images.Results:In the subjective evaluation,the DLR group of images scored higher than the conventional group and Pre-DLR group in terms of image sharpness,gray-white matter contrast,cerebrospinal fluid-choroid plexus contrast,WMH display,and overall image quality(all P＜0.05).In terms of WMH counting,the DLR group identified a higher number of WMHs than the conventional group(P＜0.05),while there was no statistical difference with the Pre-DLR group.In the objective evaluation,the DLR group showed higher SNR and CNR of WMH compared to the conventional group and Pre-DLR group(all P＜0.05).Conclusions:Compared to conventional sequences,the high-resolution T2 Flair sequence combined with the DLR algorithm can improve WMH image quality and detect more subtle WMH lesions without increasing scan time.
关键词
脑白质高信号/磁共振成像/深度学习/重建算法/高分辨率/图像质量Key words
white matter hyperintensities/magnetic resonance imaging/deep learning/reconstruction algorithm/high resolution/image quality引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据