Department of Eye & Vision Science, Institute of Ageing and Chronic Disease, University of Liverpool, 6 West Derby Street, Liverpool, L7 8TX, United Kingdom.
Malawi-Liverpool Wellcome Trust Clinical Research Programme, Queen Elizabeth Central Hospital, Blantyre, Malawi.
Sci Rep. 2017 Dec 1;7(1):16792. doi: 10.1038/s41598-017-16620-x.
Manual grading of lesions in retinal images is relevant to clinical management and clinical trials, but it is time-consuming and expensive. Furthermore, it collects only limited information - such as lesion size or frequency. The spatial distribution of lesions is ignored, even though it may contribute to the overall clinical assessment of disease severity, and correspond to microvascular and physiological topography. Capillary non-perfusion (CNP) lesions are central to the pathogenesis of major causes of vision loss. Here we propose a novel method to analyse CNP using spatial statistical modelling. This quantifies the percentage of CNP-pixels in each of 48 sectors and then characterises the spatial distribution with goniometric functions. We applied our spatial approach to a set of images from patients with malarial retinopathy, and found it compares favourably with the raw percentage of CNP-pixels and also with manual grading. Furthermore, we were able to quantify a biological characteristic of macular CNP in malaria that had previously only been described subjectively: clustering at the temporal raphe. Microvascular location is likely to be biologically relevant to many diseases, and so our spatial approach may be applicable to a diverse range of pathological features in the retina and other organs.
视网膜图像病变的手动分级与临床管理和临床试验有关，但既耗时又昂贵。此外，它只能收集有限的信息，如病变大小或频率。病变的空间分布被忽略了，尽管它可能有助于对疾病严重程度的整体临床评估，并与微血管和生理拓扑相对应。毛细血管无灌注（CNP）病变是导致视力丧失的主要原因的发病机制的核心。在这里，我们提出了一种使用空间统计建模分析 CNP 的新方法。该方法定量分析了每个 48 个扇区中 CNP-像素的百分比，然后用测角函数来描述空间分布。我们将我们的空间方法应用于一组来自疟疾性视网膜病变患者的图像，发现它与原始 CNP-像素百分比以及手动分级相比具有优势。此外，我们能够量化疟疾中黄斑 CNP 的一个生物学特征，该特征以前只能主观描述：在 temporal raphe 处聚集。微血管位置可能与许多疾病具有生物学相关性，因此我们的空间方法可能适用于视网膜和其他器官中多种病理特征。
