Huang Chongfei, Ying Shihong, Huang Meixiang, Qiu Chenhui, Lu Fang, Peng Zhiyi, Kong Dexing
School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China.
Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310030, China.
Diagnostics (Basel). 2023 Mar 18;13(6):1170. doi: 10.3390/diagnostics13061170.
Voxel-wise quantitative assessment of typical characteristics in three-dimensional (3D) multiphase computed tomography (CT) imaging, especially arterial phase hyperenhancement (APHE) and subsequent washout (WO), is crucial for the diagnosis and therapy of hepatocellular carcinoma (HCC). However, this process is still missing in practice. Radiologists often visually estimate these features, which limit the diagnostic accuracy due to subjective interpretation and qualitative assessment. Quantitative assessment is one of the solutions to this problem. However, performing voxel-wise assessment in 3D is difficult due to the misalignments between images caused by respiratory and other physiological motions. In this paper, based on the Liver Imaging Reporting and Data System (v2018), we propose a registration-based quantitative model for the 3D voxel-wise assessment of image characteristics through multiple CT imaging phases. Specifically, we selected three phases from sequential CT imaging phases, i.e., pre-contrast phase (Pre), arterial phase (AP), delayed phase (DP), and then registered Pre and DP images to the AP image to extract and assess the major imaging characteristics. An iterative reweighted local cross-correlation was applied in the proposed registration model to construct the fidelity term for comparison of intensity features across different imaging phases, which is challenging due to their distinct intensity appearance. Experiments on clinical dataset showed that the means of dice similarity coefficient of liver were 98.6% and 98.1%, those of surface distance were 0.38 and 0.54 mm, and those of Hausdorff distance were 4.34 and 6.16 mm, indicating that quantitative estimation can be accomplished with high accuracy. For the classification of APHE, the result obtained by our method was consistent with those acquired by experts. For the WO, the effectiveness of the model was verified in terms of WO volume ratio.
在三维（3D）多期计算机断层扫描（CT）成像中，对典型特征进行体素级定量评估，尤其是动脉期高增强（APHE）和随后的廓清（WO），对于肝细胞癌（HCC）的诊断和治疗至关重要。然而，在实际应用中这一过程仍然缺失。放射科医生通常通过视觉估计这些特征，由于主观解读和定性评估，这限制了诊断准确性。定量评估是解决这一问题的方法之一。然而，由于呼吸和其他生理运动导致图像之间的错位，在3D中进行体素级评估很困难。在本文中，基于肝脏影像报告和数据系统（v2018），我们提出了一种基于配准的定量模型，用于通过多个CT成像期对图像特征进行3D体素级评估。具体而言，我们从连续的CT成像期选择了三个期，即平扫期（Pre）、动脉期（AP）、延迟期（DP），然后将Pre和DP图像配准到AP图像，以提取和评估主要成像特征。在所提出的配准模型中应用了迭代加权局部互相关，以构建保真度项，用于比较不同成像期的强度特征，由于它们不同的强度表现，这具有挑战性。在临床数据集上的实验表明，肝脏的骰子相似系数均值分别为98.6%和98.1%，表面距离均值分别为0.38和0.54毫米，豪斯多夫距离均值分别为4.34和6.16毫米，表明可以高精度地完成定量估计。对于APHE的分类，我们的方法得到的结果与专家获得的结果一致。对于WO，在WO体积比方面验证了模型的有效性。
