Mihalek Ivana, De Bruyn Hanna, Glavan Tomislav, Lancos Annie M, Ciolfi Caitlin M, Malendowicz Katarzyna, Aslaksen Sigrid, Molday Laurie L, Molday Robert S, Fulton Anne B
Department of Molecular Medicine and Biotechnology, Faculty of Medicine, University of Rijeka, Rijeka, Croatia.
Department of Ophthalmology, Boston Children's Hospital, Boston, MA, USA.
Transl Vis Sci Technol. 2025 Mar 3;14(3):16. doi: 10.1167/tvst.14.3.16.
To score real-world fundus autofluorescence (FAF) images of pediatric patients with ABCA4-related Stargardt disease (STGD1), in a way that is automatable, scales with the disease progression, and is applicable to a wide time interval in the natural history of the disease.
We developed the score based on a series of Optos wide-field FAF images of pediatric STGD1 patients (73 images; 14 individuals) and controls (27 images; 8 individuals). The patients' images were obtained over up to 6 years, and the controls over up to 5 years. In each image, we manually selected an artifact-free region, within which we evaluated an average of the pixel-level intensity score, constructed so that the average increases with progression of the disease.
The score we propose provides a statistically robust measure of disease progression (91% Spearman correlation with the absolute age, 97% with the estimated time from onset, when averaged over both eyes), comparable across timepoints and patients.
FAF is a reliable tool in STGD1 diagnostics, but its quantitative description must be modified to be applicable to tracking the disease progression. Analyzing images obtained in the course of clinical care of pediatric patients poses special challenges that make complete automation difficult.
Our methodology provides a quantitative tool for investigating the natural progression of the Stargardt disease, and, potentially, the effects of genotype, environment, and therapeutic intervention on its course.
以一种可自动化、随疾病进展而变化且适用于疾病自然史中广泛时间间隔的方式,对患有ABCA4相关的斯塔加特病(STGD1)的儿科患者的真实世界眼底自发荧光(FAF)图像进行评分。
我们基于一系列儿科STGD1患者(73张图像;14名个体)和对照(27张图像;8名个体)的Optos广角FAF图像开发了该评分系统。患者的图像采集时间长达6年,对照的图像采集时间长达5年。在每张图像中,我们手动选择一个无伪影区域,在该区域内评估像素级强度评分的平均值,该评分的构建方式使得平均值随疾病进展而增加。
我们提出的评分系统为疾病进展提供了一种统计学上稳健的测量方法(与绝对年龄的斯皮尔曼相关性为91%,与估计发病时间的相关性为97%,双眼平均),在不同时间点和患者之间具有可比性。
FAF是STGD1诊断中的可靠工具,但其定量描述必须进行修改以适用于跟踪疾病进展。分析儿科患者临床护理过程中获得的图像带来了特殊挑战,使得完全自动化变得困难。
我们的方法提供了一种定量工具,用于研究斯塔加特病的自然进展,以及潜在地研究基因型、环境和治疗干预对其病程的影响。