Hertel Alexander, Kuru Mustafa, Tollens Fabian, Tharmaseelan Hishan, Nörenberg Dominik, Rathmann Nils, Schoenberg Stefan O, Froelich Matthias F
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany.
Front Oncol. 2024 Oct 7;14:1444115. doi: 10.3389/fonc.2024.1444115. eCollection 2024.
The liver is a frequent location of metastatic disease in various malignant tumor entities. Computed tomography (CT) is the most frequently employed modality for initial diagnosis. However, liver metastases may only be delineated vaguely on CT. Calculating radiomics features in feature maps can unravel textures not visible to the human eye on a standard CT reconstruction (SCTR). This study aimed to investigate the comparative diagnostic accuracy of radiomics feature maps and SCTR for liver metastases.
Forty-seven patients with hepatic metastatic colorectal cancer were retrospectively enrolled. Whole-liver maps of original radiomics features were generated. A representative feature was selected for each feature class based on the visualization of example lesions from five patients. These maps and the conventional CT image data were viewed and evaluated by four readers in terms of liver parenchyma, number of lesions, visual contrast of lesions and diagnostic confidence. T-tests and chi²-tests were performed with a significance cut off of p<0.05 to compare the feature maps with SCRT, and the data were visualized as boxplots.
Regarding the number of lesions detected, SCTR showed superior performance compared to radiomics maps. However, the feature map for firstorder RootMeanSquared was ranked superior in terms of very high visual contrast in 57.4% of cases, compared to 41.0% in standard reconstructions (p < 0.001). All other radiomics maps ranked significantly lower in visual contrast when compared to SCTR. For diagnostic confidence, firstorder RootMeanSquared reached very high ratings in 47.9% of cases, compared to 62.8% for SCTR (p < 0.001). The conventional CT images showed superior results in all categories for the other features investigated.
The application of firstorder RootMeanSquared feature maps may help visualize faintly demarcated liver lesions by increasing visual contrast. However, reading of SCTR remains necessary for diagnostic confidence.
肝脏是各种恶性肿瘤实体中常见的转移部位。计算机断层扫描（CT）是初始诊断中最常用的检查方式。然而，肝脏转移瘤在CT上可能仅显示得较为模糊。在特征图中计算影像组学特征可以揭示在标准CT重建（SCTR）上肉眼不可见的纹理。本研究旨在探讨影像组学特征图和SCTR对肝脏转移瘤的比较诊断准确性。
回顾性纳入47例肝转移性结直肠癌患者。生成了原始影像组学特征的全肝图。根据来自5例患者的示例病变的可视化情况，为每个特征类别选择一个代表性特征。这4幅图和传统CT图像数据由4名阅片者从肝实质、病变数量、病变视觉对比度和诊断置信度方面进行观察和评估。进行t检验和卡方检验，显著性临界值为p<0.05，以比较特征图与SCRT，并将数据可视化为箱线图。
在检测到的病变数量方面，SCTR表现优于影像组学图。然而，一阶均方根特征图在57.4%的病例中视觉对比度非常高，而标准重建中这一比例为41.0%（p<0.001）。与SCTR相比，所有其他影像组学图在视觉对比度方面排名显著更低。在诊断置信度方面，一阶均方根在47.9%的病例中获得了非常高的评分，而SCTR为62.8%（p<0.001）。对于其他所研究的特征，传统CT图像在所有类别中均显示出更好的结果。
应用一阶均方根特征图可能有助于通过增加视觉对比度来可视化边界模糊的肝脏病变。然而，为了获得诊断置信度，仍然需要阅读SCTR。
