Chan Tatjana, Richter Henning, Del Chicca Francesca
Department of Diagnostics and Clinical Services, Clinic for Diagnostic Imaging, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Front Vet Sci. 2024 May 13;11:1357596. doi: 10.3389/fvets.2024.1357596. eCollection 2024.
Diffusion-weighted imaging is increasingly available for brain investigation. Image interpretation of intracranial space-occupying lesions often includes the derived apparent diffusion coefficient (ADC) analysis. In human medicine, ADC can help discriminate between benign and malignant lesions in intracranial tumors. This study investigates the difference in ADC values depending on the sample strategies of image analysis. MRI examination, including diffusion-weighted images of canine and feline patients presented between 2015 and 2020, were reviewed retrospectively. Patients with single, large intracranial space-occupying lesions were included. Lesions homogeneity was subjectively scored. ADC values were calculated using six different methods of sampling (M1-M6) on the ADC map. M1 included as much as possible of the lesion on a maximum of five consecutive slices; M2 included five central and five peripheral ROIs; M3 included a single ROI on the solid part of the lesion; M4 included three central ROIs on one slice; M5 included three central ROIs on different slices; and M6 included one large ROI on the entire lesion. A total of 201 animals of various breeds, genders, and ages were analyzed. ADC values differed significantly between M5 against M2 (peripheral) ( < 0.001), M5 against M6 ( = 0.009), and M4 against M2 (peripheral) ( = 0.005). When lesions scored as homogeneous in all sequences were excluded, an additional significant difference in three further sampling methods was present ( < 0.005). ADC of single, large, intracranial space-occupying lesions differed significantly in half of the tested methods of sampling. Excluding homogeneous lesions, additional significant differences among the sampling methods were present. The obtained results should increase awareness of the variability of the ADC, depending on the sample strategies used.
扩散加权成像在脑部检查中越来越常用。颅内占位性病变的图像解读通常包括对导出的表观扩散系数（ADC）的分析。在人类医学中，ADC有助于区分颅内肿瘤的良性和恶性病变。本研究调查了根据图像分析的采样策略，ADC值的差异。回顾性分析了2015年至2020年间犬猫患者的MRI检查，包括扩散加权图像。纳入患有单个大型颅内占位性病变的患者。对病变的同质性进行主观评分。在ADC图上使用六种不同的采样方法（M1 - M6）计算ADC值。M1在最多五张连续切片上尽可能多地包含病变；M2包括五个中央和五个周边感兴趣区（ROI）；M3在病变的实性部分包含一个单一ROI；M4在一张切片上包括三个中央ROI；M5在不同切片上包括三个中央ROI；M6在整个病变上包括一个大ROI。共分析了201只不同品种、性别和年龄的动物。M5与M2（周边）（<0.001）、M5与M6（=0.009）以及M4与M2（周边）（=0.005）之间的ADC值差异显著。当排除在所有序列中评分均为均匀的病变时，在另外三种采样方法中也存在显著差异（<0.005）。在一半的测试采样方法中，单个大型颅内占位性病变的ADC差异显著。排除均匀病变后，采样方法之间还存在其他显著差异。根据所使用的采样策略，获得的结果应提高对ADC变异性的认识。
