Lu Jie, Cheng Yuxuan, Li Jianqing, Liu Ziyu, Shen Mengxi, Zhang Qinqin, Liu Jeremy, Herrera Gissel, Hiya Farhan E, Morin Rosalyn, Joseph Joan, Gregori Giovanni, Rosenfeld Philip J, Wang Ruikang K
Department of Bioengineering, University of Washington, Seattle, Washington, USA.
Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, USA.
Biomed Opt Express. 2023 Feb 28;14(3):1292-1306. doi: 10.1364/BOE.485999. eCollection 2023 Mar 1.
Qualitative and quantitative assessments of calcified drusen are clinically important for determining the risk of disease progression in age-related macular degeneration (AMD). This paper reports the development of an automated algorithm to segment and quantify calcified drusen on swept-source optical coherence tomography (SS-OCT) images. The algorithm leverages the higher scattering property of calcified drusen compared with soft drusen. Calcified drusen have a higher optical attenuation coefficient (OAC), which results in a choroidal hypotransmission defect (hypoTD) below the calcified drusen. We show that it is possible to automatically segment calcified drusen from 3D SS-OCT scans by combining the OAC within drusen and the hypoTDs under drusen. We also propose a correction method for the segmentation of the retina pigment epithelium (RPE) overlying calcified drusen by automatically correcting the RPE by an amount of the OAC peak width along each A-line, leading to more accurate segmentation and quantification of drusen in general, and the calcified drusen in particular. A total of 29 eyes with nonexudative AMD and calcified drusen imaged with SS-OCT using the 6 × 6 mm scanning pattern were used in this study to test the performance of the proposed automated method. We demonstrated that the method achieved good agreement with the human expert graders in identifying the area of calcified drusen (Dice similarity coefficient: 68.27 ± 11.09%, correlation coefficient of the area measurements: r = 0.9422, the mean bias of the area measurements = 0.04781 mm).
对钙化性玻璃膜疣进行定性和定量评估对于确定年龄相关性黄斑变性(AMD)的疾病进展风险具有重要的临床意义。本文报告了一种自动算法的开发,用于在扫频光学相干断层扫描(SS-OCT)图像上分割和量化钙化性玻璃膜疣。该算法利用了钙化性玻璃膜疣与软性玻璃膜疣相比更高的散射特性。钙化性玻璃膜疣具有更高的光学衰减系数(OAC),这导致在钙化性玻璃膜疣下方出现脉络膜低透射缺陷(hypoTD)。我们表明,通过结合玻璃膜疣内的OAC和玻璃膜疣下方的hypoTD,可以从3D SS-OCT扫描中自动分割钙化性玻璃膜疣。我们还提出了一种校正方法,用于对覆盖钙化性玻璃膜疣的视网膜色素上皮(RPE)进行分割,通过沿每条A线自动校正RPE的OAC峰值宽度量,从而总体上实现更准确的玻璃膜疣分割和量化,尤其是钙化性玻璃膜疣。本研究共使用了29只患有非渗出性AMD且有钙化性玻璃膜疣的眼睛,采用6×6mm扫描模式进行SS-OCT成像,以测试所提出的自动化方法的性能。我们证明,该方法在识别钙化性玻璃膜疣面积方面与人类专家分级者具有良好的一致性(骰子相似系数:68.27±11.09%,面积测量的相关系数:r = 0.9422,面积测量的平均偏差 = 0.04781mm)。