Alibhai A Yasin, De Pretto Lucas R, Yaghy Antonio, Woo Kwang Min, Dos Santos Xilau Naira Raquel, Siddiqui Haleema, Pandiscio Christopher A, Homer Alex, Curtiss Darin, Waheed Nadia K
Boston Image Reading Center, Boston, MA, USA.
New England Eye Center, Tufts Medical Center, Boston, MA, USA.
Transl Vis Sci Technol. 2024 Dec 2;13(12):26. doi: 10.1167/tvst.13.12.26.
To compare the efficacy of thin plate spline (TPS) and Gaussian interpolation methods in generating hill of visions (HOVs) for patients with X-linked retinitis pigmentosa (XLRP).
Visual field data from 78 eyes of 39 patients with XLRP were acquired using the Octopus 900 Pro. TPS, Gaussian, and Universal Kriging interpolation methods were implemented to generate HOVs. The volume of the entire grid (VTot), a 30-degree region (V30), and the volume ratio (VRatio) were calculated. Pearson correlation and Bland-Altman limit of agreement (LOA) analysis were performed to assess the concordance. An undersampled grid was used to assess the accuracy of the interpolation by comparing the interpolated value to the actual measured value.
There were strong positive correlations (R > 0.99, P < 0.001), and LOA analysis revealed minimal differences between the three methods. Gaussian interpolation performed the fastest (P < 0.0001).
TPS and Gaussian interpolation methods demonstrated a high degree of concordance in generating HOVs for patients with XLRP. The choice of methods depends on the specific needs and priorities of researchers and clinicians, factoring in speed, accessibility, ease of implementation, and the ability to fine-tune the interpolation.
Accurate HOV analysis is crucial for monitoring and assessing visual field loss progression. TPS and Gaussian interpolation methods are equally effective in generating HOV representations for patients with XLRP. The choice of method can be based on specific needs of researchers or clinicians, enabling more personalized treatment strategies and better disease management.
比较薄板样条法(TPS)和高斯插值法在为X连锁视网膜色素变性(XLRP)患者生成视力山丘(HOV)方面的疗效。
使用Octopus 900 Pro获取39例XLRP患者78只眼的视野数据。采用TPS、高斯和通用克里金插值法生成HOV。计算整个网格的体积(VTot)、30度区域的体积(V30)和体积比(VRatio)。进行Pearson相关性分析和Bland-Altman一致性界限(LOA)分析以评估一致性。使用欠采样网格通过将插值结果与实际测量值进行比较来评估插值的准确性。
存在强正相关(R>0.99,P<0.001),并且LOA分析显示三种方法之间差异极小。高斯插值执行速度最快(P<0.0001)。
TPS和高斯插值法在为XLRP患者生成HOV方面显示出高度一致性。方法的选择取决于研究人员和临床医生的具体需求和优先级,要考虑速度、可及性、实施的简易程度以及微调插值的能力。
准确的HOV分析对于监测和评估视野丧失进展至关重要。TPS和高斯插值法在为XLRP患者生成HOV表示方面同样有效。方法的选择可以基于研究人员或临床医生的特定需求,从而实现更个性化的治疗策略和更好的疾病管理。