Maximilian Pfau, Jasleen K Jolly, Jason Charng, Leon von der Emde, Philipp L Müller, Georg Ansari, Kristina Pfau, Fred K Chen, Zhichao Wu
{"title":"中焦显微透视测量的多中心规范数据。","authors":"Maximilian Pfau, Jasleen K Jolly, Jason Charng, Leon von der Emde, Philipp L Müller, Georg Ansari, Kristina Pfau, Fred K Chen, Zhichao Wu","doi":"10.1167/iovs.65.12.27","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to provide a large, multi-center normative dataset for the Macular Integrity Assessment (MAIA) microperimeter and compare the goodness-of-fit and prediction interval calibration-error for a panel of hill-of-vision models.</p><p><strong>Methods: </strong>Microperimetry examinations of healthy eyes from five independent study groups and one previously available dataset were included (1137 tests from 531 eyes of 432 participants [223 women and 209 men]). Linear mixed models (LMMs) were fitted to the data to obtain interpretable hill-of-vision models. A panel of regression models to predict normative data was compared using cross-validation with site-wise splits. The mean absolute error (MAE) and miscalibration area (area between the calibration curve and the ideal diagonal) were evaluated as the performance measures.</p><p><strong>Results: </strong>Based on the parameters \"participant age,\" \"eccentricity from the fovea,\" \"overlap with the central fixation target,\" and \"eccentricity along the four principal meridians,\" a Bayesian mixed model had the lowest MAE (2.13 decibel [dB]; 95% confidence interval [CI] = 1.9-2.36 dB) and miscalibration area (0.13; 95% CI = 0.07-0.19). However, a parsimonious linear model provided a comparable MAE (2.17 dB; 95% CI = 1.93-2.4 dB) and a similar miscalibration area (0.14; 95% CI = 0.08-0.2).</p><p><strong>Conclusions: </strong>Normal variations in visual sensitivity on mesopic microperimetry can be effectively explained by a linear model that includes age and eccentricity. The dataset and a code vignette are provided for estimating normative values across a large range of retinal locations, applicable to customized testing patterns.</p>","PeriodicalId":14620,"journal":{"name":"Investigative ophthalmology & visual science","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11512566/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multicenter Normative Data for Mesopic Microperimetry.\",\"authors\":\"Maximilian Pfau, Jasleen K Jolly, Jason Charng, Leon von der Emde, Philipp L Müller, Georg Ansari, Kristina Pfau, Fred K Chen, Zhichao Wu\",\"doi\":\"10.1167/iovs.65.12.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The purpose of this study was to provide a large, multi-center normative dataset for the Macular Integrity Assessment (MAIA) microperimeter and compare the goodness-of-fit and prediction interval calibration-error for a panel of hill-of-vision models.</p><p><strong>Methods: </strong>Microperimetry examinations of healthy eyes from five independent study groups and one previously available dataset were included (1137 tests from 531 eyes of 432 participants [223 women and 209 men]). Linear mixed models (LMMs) were fitted to the data to obtain interpretable hill-of-vision models. A panel of regression models to predict normative data was compared using cross-validation with site-wise splits. The mean absolute error (MAE) and miscalibration area (area between the calibration curve and the ideal diagonal) were evaluated as the performance measures.</p><p><strong>Results: </strong>Based on the parameters \\\"participant age,\\\" \\\"eccentricity from the fovea,\\\" \\\"overlap with the central fixation target,\\\" and \\\"eccentricity along the four principal meridians,\\\" a Bayesian mixed model had the lowest MAE (2.13 decibel [dB]; 95% confidence interval [CI] = 1.9-2.36 dB) and miscalibration area (0.13; 95% CI = 0.07-0.19). However, a parsimonious linear model provided a comparable MAE (2.17 dB; 95% CI = 1.93-2.4 dB) and a similar miscalibration area (0.14; 95% CI = 0.08-0.2).</p><p><strong>Conclusions: </strong>Normal variations in visual sensitivity on mesopic microperimetry can be effectively explained by a linear model that includes age and eccentricity. The dataset and a code vignette are provided for estimating normative values across a large range of retinal locations, applicable to customized testing patterns.</p>\",\"PeriodicalId\":14620,\"journal\":{\"name\":\"Investigative ophthalmology & visual science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11512566/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Investigative ophthalmology & visual science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1167/iovs.65.12.27\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Investigative ophthalmology & visual science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1167/iovs.65.12.27","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
Multicenter Normative Data for Mesopic Microperimetry.
Purpose: The purpose of this study was to provide a large, multi-center normative dataset for the Macular Integrity Assessment (MAIA) microperimeter and compare the goodness-of-fit and prediction interval calibration-error for a panel of hill-of-vision models.
Methods: Microperimetry examinations of healthy eyes from five independent study groups and one previously available dataset were included (1137 tests from 531 eyes of 432 participants [223 women and 209 men]). Linear mixed models (LMMs) were fitted to the data to obtain interpretable hill-of-vision models. A panel of regression models to predict normative data was compared using cross-validation with site-wise splits. The mean absolute error (MAE) and miscalibration area (area between the calibration curve and the ideal diagonal) were evaluated as the performance measures.
Results: Based on the parameters "participant age," "eccentricity from the fovea," "overlap with the central fixation target," and "eccentricity along the four principal meridians," a Bayesian mixed model had the lowest MAE (2.13 decibel [dB]; 95% confidence interval [CI] = 1.9-2.36 dB) and miscalibration area (0.13; 95% CI = 0.07-0.19). However, a parsimonious linear model provided a comparable MAE (2.17 dB; 95% CI = 1.93-2.4 dB) and a similar miscalibration area (0.14; 95% CI = 0.08-0.2).
Conclusions: Normal variations in visual sensitivity on mesopic microperimetry can be effectively explained by a linear model that includes age and eccentricity. The dataset and a code vignette are provided for estimating normative values across a large range of retinal locations, applicable to customized testing patterns.
期刊介绍:
Investigative Ophthalmology & Visual Science (IOVS), published as ready online, is a peer-reviewed academic journal of the Association for Research in Vision and Ophthalmology (ARVO). IOVS features original research, mostly pertaining to clinical and laboratory ophthalmology and vision research in general.