Wu Jingpu, Huang Qianqi, Shen Yiqing, Guo Pengfei, Zhou Jinyuan, Jiang Shanshan
Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Int J Imaging Syst Technol. 2024 Mar;34(2). doi: 10.1002/ima.23027. Epub 2024 Jan 30.
Compressed sensing (CS) is a novel technique for MRI acceleration. The purpose of this paper was to assess the effects of CS on the radiomic features extracted from amide proton transfer-weighted (APTw) images. Brain tumor MRI data of 40 scans were studied. Standard images using sensitivity encoding (SENSE) with an acceleration factor (AF) of 2 were used as the gold standard, and APTw images using SENSE with CS (CS-SENSE) with an AF of 4 were assessed. Regions of interest (ROIs), including normal tissue, edema, liquefactive necrosis, and tumor, were manually drawn, and the effects of CS-SENSE on radiomics were assessed for each ROI category. An intraclass correlation coefficient (ICC) was first calculated for each feature extracted from APTw images with SENSE and CS-SENSE for all ROIs. Different filters were applied to the original images, and the effects of these filters on the ICCs were further compared between APTw images with SENSE and CS-SENSE. Feature deviations were also provided for a more comprehensive evaluation of the effects of CS-SENSE on radiomic features. The ROI-based comparison showed that most radiomic features extracted from CS-SENSE-APTw images and SENSE-APTw images had moderate or greater reliabilities (ICC ≥ 0.5) for all four ROIs and all eight image sets with different filters. Tumor showed significantly higher ICCs than normal tissue, edema, and liquefactive necrosis. Compared to the original images, filters (such as Exponential or Square) may improve the reliability of radiomic features extracted from CS-SENSE-APTw and SENSE-APTw images.
压缩感知（CS）是一种用于磁共振成像（MRI）加速的新技术。本文旨在评估CS对从酰胺质子转移加权（APTw）图像中提取的放射组学特征的影响。研究了40次扫描的脑肿瘤MRI数据。使用加速因子（AF）为2的灵敏度编码（SENSE）标准图像作为金标准，并评估了AF为4的使用CS的SENSE（CS-SENSE）的APTw图像。手动绘制包括正常组织、水肿、液化坏死和肿瘤在内的感兴趣区域（ROI），并针对每个ROI类别评估CS-SENSE对放射组学的影响。首先针对从所有ROI的APTw图像中使用SENSE和CS-SENSE提取的每个特征计算组内相关系数（ICC）。对原始图像应用不同的滤波器，并进一步比较这些滤波器对SENSE和CS-SENSE的APTw图像之间ICC的影响。还提供了特征偏差，以更全面地评估CS-SENSE对放射组学特征 的影响。基于ROI的比较表明，从CS-SENSE-APTw图像和SENSE-APTw图像中提取的大多数放射组学特征对于所有四个ROI以及所有八个具有不同滤波器的图像集都具有中等或更高的可靠性（ICC≥0.5）。肿瘤的ICC显著高于正常组织、水肿和液化坏死。与原始图像相比，滤波器（如指数或平方）可能会提高从CS-SENSE-APTw和SENSE-APTw图像中提取的放射组学特征的可靠性。
