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Longitudinal Assessment of Retinopathy of Prematurity (LONGROP) Study: Impacts of Viewing Time and Ability to Compare on Detection of Change
American Journal of Ophthalmology ( IF 4.1 ) Pub Date : 2024-10-24 , DOI: 10.1016/j.ajo.2024.10.015 Tatiana R. Rosenblatt, Hashem H Ghoraba, Marco Ji, Caroline R. Baumal, Audina M. Berrocal, Cagri Besirli, Kimberly Drenser, Anna Ells, C. Armitage Harper III, G. Baker Hubbard III, Eric Nudleman, Polly Quiram, Irena Tsui, Yoshihiro Yonekawa, Edward H. Wood, Jochen Kumm, Darius M. Moshfeghi
American Journal of Ophthalmology ( IF 4.1 ) Pub Date : 2024-10-24 , DOI: 10.1016/j.ajo.2024.10.015 Tatiana R. Rosenblatt, Hashem H Ghoraba, Marco Ji, Caroline R. Baumal, Audina M. Berrocal, Cagri Besirli, Kimberly Drenser, Anna Ells, C. Armitage Harper III, G. Baker Hubbard III, Eric Nudleman, Polly Quiram, Irena Tsui, Yoshihiro Yonekawa, Edward H. Wood, Jochen Kumm, Darius M. Moshfeghi
Purpose: This study compared two imaging grading techiques to assess the utility of longitudinal image-based analysis in retinopathy of prematurity (ROP) screening: 1) time-limited without image comparison (a proxy for bedside indirect ophthalmoscopy, termed sBIO) and time-unlimited with image comparison (for telemedicine grading, termed TELE) screening. We tested two hypotheses: 1) H1: TELE was superior to sBIO for the detection of change (Tempo)–same, better, or worse–and, 2) H2: granular data of change (e.g. at the image and feature level) is integrated by graders to achieve the Tempo assessment.
中文翻译:
早产儿视网膜病变纵向评估 (LONGROP) 研究:观看时间和比较能力对变化检测的影响
目的:本研究比较了两种影像学分级技术,以评估基于纵向图像的分析在早产儿视网膜病变 (ROP) 筛查中的效用: 1) 无图像比较的限时性(床旁间接检眼镜检查的代理,称为 sBIO)和无时间限制的图像比较(用于远程医疗分级,称为 TELE)筛查。我们测试了两个假设:1) H1:TELE 在检测变化 (Tempo) 方面优于 sBIO——相同、更好或更差——以及,2) H2:评分员整合变化的细粒度数据(例如在图像和特征级别)以实现 Tempo 评估。
更新日期:2024-10-24
中文翻译:
早产儿视网膜病变纵向评估 (LONGROP) 研究:观看时间和比较能力对变化检测的影响
目的:本研究比较了两种影像学分级技术,以评估基于纵向图像的分析在早产儿视网膜病变 (ROP) 筛查中的效用: 1) 无图像比较的限时性(床旁间接检眼镜检查的代理,称为 sBIO)和无时间限制的图像比较(用于远程医疗分级,称为 TELE)筛查。我们测试了两个假设:1) H1:TELE 在检测变化 (Tempo) 方面优于 sBIO——相同、更好或更差——以及,2) H2:评分员整合变化的细粒度数据(例如在图像和特征级别)以实现 Tempo 评估。