Wang Bingjie, Brown Richard, Chhablani Jay, Pi Shaohua
Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
UPMC Vision Institute, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Biomed Opt Express. 2023 Sep 29;14(10):5528-5538. doi: 10.1364/BOE.506422. eCollection 2023 Oct 1.
Central serous chorioretinopathy (CSCR) leads to the accumulation of subretinal fluid and retinal thickness change, which can be readily detected in clinics using optical coherence tomography (OCT). However, current quantification methods usually require sophisticated processing such as retinal layer segmentations, and volumetric visualization of structural changes is generally challenging, which can hinder fast and accurate assessment of disease progression and/or treatment efficacy. In this study, we developed an algorithm that can register the OCT scans acquired from different visits without requiring prior layer segmentation and calculated the three-dimensional (3-D) structural change maps for patients with CSCR. Our results demonstrate that this tool can be useful in monitoring the progression of CSCR and revealing the resolution of pathologies following treatment automatically with minimal pre-processing.
中心性浆液性脉络膜视网膜病变（CSCR）会导致视网膜下液积聚和视网膜厚度改变，这在临床上使用光学相干断层扫描（OCT）很容易检测到。然而，目前的量化方法通常需要复杂的处理，如视网膜层分割，并且结构变化的体积可视化通常具有挑战性，这可能会阻碍对疾病进展和/或治疗效果的快速准确评估。在本研究中，我们开发了一种算法，该算法可以在无需事先进行层分割的情况下对不同就诊时获取的OCT扫描进行配准，并为CSCR患者计算三维（3-D）结构变化图。我们的结果表明，该工具可用于监测CSCR的进展，并以最少的预处理自动揭示治疗后病变的消退情况。
