作为视网膜病变或早产严重程度的函数的P-Score变化
Sarthak V Shah1, Arthur R Brant1, Cindy S Zhao1
1Byers Eye Institute, Horngren Family Vitreoretinal Center, Department of Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States.
Investigative ophthalmology & visual science
|February 27, 2026
概括
在早产视网膜病变 (ROP) 中,P-分数的变化随着疾病的严重程度而增加. 每次会议的多张图像对于准确的ROP诊断至关重要,特别是在严重的情况下.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 新生儿科学 新生儿科学
背景情况:
- 早产视网膜病变 (ROP) 是儿童失明的主要原因.
- 准确的ROP分级对于及时治疗和预防视力丧失至关重要.
- P-分数分级是ROP评估的关键组成部分,但其变异性尚未完全理解.
研究的目的:
- 评估在早产视网膜病变 (ROP) 中P分数分级 (P-Var) 的会话内变异性.
- 为了评估P-Var随着ROP严重程度的增加而发生的变化.
- 为了确定有限的图像采样对ROP分类准确性的影响.
主要方法:
- 分析了20名ROP患者的视网膜图像.
- 九名蒙面评分员评估了来自129次成像会议的1597张图像.
- 使用范围,级别间可靠性和协议指标来测量变性.
- 概率模型评估了图像采样对分类的影响.
主要成果:
- 在单个眼睛成像会议内观察到显著的P-score变化.
- 随着ROP血管疾病的恶化和整体严重程度的恶化,可变性增加.
- 级别之间的一致性很好 (ICC = 0.68),但确切的P-score一致性只有28.5%.
- 概率模型显示,有限的图像采样 (<5个视图/眼睛) 可以导致错误分类,特别是在加眼睛.
结论:
- 在单次ROP成像检查中存在P-score变异性,随着疾病的严重程度而升级.
- 准确的ROP分类需要每次会议多张图像,特别是在患有更严重疾病的眼睛.
- 这些发现强调了全面的成像协议在ROP诊断中的重要性.
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