Nakamitsu Yuki, Kuroda Masahiro, Shimizu Yudai, Kuroda Kazuhiro, Yoshimura Yuuki, Yoshida Suzuka, Nakamura Yoshihide, Fukumura Yuka, Kamizaki Ryo, Al-Hammad Wlla E, Oita Masataka, Tanabe Yoshinori, Sugimoto Kohei, Sugianto Irfan, Barham Majd, Tekiki Nouha, Asaumi Junichi
Radiological Technology, Graduate School of Health Sciences, Okayama University, Okayama 700-8558, Japan.
Department of Oral and Maxillofacial Radiology, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama University, Okayama 700-8558, Japan.
J Clin Med. 2024 Mar 20;13(6):1783. doi: 10.3390/jcm13061783.
Our initial clinical study using simple diffusion kurtosis imaging (SDI), which simultaneously produces a diffusion kurtosis image (DKI) and an apparent diffusion coefficient map, confirmed the usefulness of SDI for tumor diagnosis. However, the obtained DKI had noticeable variability in the mean kurtosis (MK) values, which is inherent to SDI. We aimed to improve this variability in SDI by preprocessing with three different filters (Gaussian [G], median [M], and nonlocal mean) of the diffusion-weighted images used for SDI. The usefulness of filter parameters for diagnosis was examined in basic and clinical studies involving 13 patients with head and neck tumors. The filter parameters, which did not change the median MK value, but reduced the variability and significantly homogenized the MK values in tumor and normal tissues in both basic and clinical studies, were identified. In the receiver operating characteristic curve analysis for distinguishing tumors from normal tissues using MK values, the area under curve values significantly improved from 0.627 without filters to 0.641 with G (σ = 0.5) and 0.638 with M (radius = 0.5). Thus, image pretreatment with G and M for SDI was shown to be useful for improving tumor diagnosis in clinical practice.
我们最初使用简单扩散峰度成像（SDI）的临床研究，该技术可同时生成扩散峰度图像（DKI）和表观扩散系数图，证实了SDI在肿瘤诊断中的有用性。然而，所获得的DKI在平均峰度（MK）值上存在明显的变异性，这是SDI所固有的。我们旨在通过对用于SDI的扩散加权图像进行三种不同滤波器（高斯[G]、中值[M]和非局部均值）的预处理来改善SDI中的这种变异性。在涉及13例头颈部肿瘤患者的基础和临床研究中，检验了滤波器参数对诊断的有用性。确定了在基础和临床研究中既不改变中值MK值，又能降低变异性并显著使肿瘤和正常组织中的MK值均匀化的滤波器参数。在使用MK值区分肿瘤与正常组织的受试者工作特征曲线分析中，曲线下面积值从无滤波器时的0.627显著提高到使用G（σ = 0.5）时的0.641和使用M（半径 = 0.5）时的0.638。因此，对SDI使用G和M进行图像预处理被证明在临床实践中对改善肿瘤诊断是有用的。
