薄板样条法与高斯插值法在x连锁色素性视网膜炎患者视觉山生成中的比较。

IF 2.6 3区 医学 Q2 OPHTHALMOLOGY Translational Vision Science & Technology Pub Date : 2024-12-02 DOI:10.1167/tvst.13.12.26
A Yasin Alibhai, Lucas R De Pretto, Antonio Yaghy, Kwang Min Woo, Naira Raquel Dos Santos Xilau, Haleema Siddiqui, Christopher A Pandiscio, Alex Homer, Darin Curtiss, Nadia K Waheed
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引用次数: 0

摘要

目的:比较薄板样条法(TPS)与高斯插值法(Gaussian interpolation)在x连锁色素性视网膜炎(XLRP)患者产生视力山(hov)的效果。方法:采用八达通900 Pro对39例XLRP患者78只眼进行视野数据采集。采用TPS、高斯和通用克里格插值方法生成hov。计算整个网格的体积(VTot)、30度区域(V30)和体积比(VRatio)。采用Pearson相关和Bland-Altman一致限(LOA)分析来评估一致性。通过将插值值与实际测量值进行比较,利用欠采样网格来评估插值的准确性。结果:三种方法之间存在强正相关(R < 0.99, P < 0.001), LOA分析显示三种方法之间差异极小。高斯插值效果最好(P < 0.0001)。结论:TPS法和高斯插值法在XLRP患者的hov生成中表现出高度的一致性。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事项,考虑到速度、可及性、实施的便利性以及微调插值的能力。翻译相关性:准确的HOV分析是监测和评估视野丧失进展的关键。TPS和高斯插值方法在生成XLRP患者的HOV表示方面同样有效。方法的选择可以根据研究人员或临床医生的具体需要,实现更个性化的治疗策略和更好的疾病管理。
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Comparing the Thin Plate Spline and Gaussian Interpolation Methods in Generating Hill of Visions for X-Linked Retinitis Pigmentosa Patients.

Purpose: 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).

Methods: 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.

Results: 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).

Conclusions: 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.

Translational relevance: 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.

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来源期刊
Translational Vision Science & Technology
Translational Vision Science & Technology Engineering-Biomedical Engineering
CiteScore
5.70
自引率
3.30%
发文量
346
审稿时长
25 weeks
期刊介绍: Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.
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