Literature DB >> 14638735

Automated measurement of microaneurysm turnover.

Keith A Goatman1, Michael J Cree, John A Olson, John V Forrester, Peter F Sharp.   

Abstract

PURPOSE: An automated system for the measurement of microaneurysm (MA) turnover was developed and compared with manual measurement. The system analyses serial fluorescein angiogram (FA) or red-free (RF) fundus images; fluorescein angiography was used in this study because it is the more sensitive test for MAs. Previous studies have shown that the absolute number of MAs observed does not reflect the dynamic temporal nature of the MA population. In this study, almost half of the MAs present at baseline had regressed after a year and been replaced by new lesions elsewhere.
METHODS: Two clinical datasets were used to evaluate the performance of the automated turnover measurement system. The first consisted of 10 patients who had two fluorescein angiograms acquired a year apart. These data were analyzed, both manually and using the automated system, to investigate the inter- and intraobserver variations associated with manual measurement and to assess the performance of the automated system. The second dataset contained FAs from a further 25 patients. This dataset was analyzed only with the automated system to investigate some properties of microaneurysm turnover, in particular the differing detection sensitivities of new, static and regressed microaneurysms.
RESULTS: Manual measurements exhibited large inter- and intraobserver variation. The sensitivity and specificity of the automated system were similar to those of the human observers. However, the automated measurements were more consistent-an important condition for accurate turnover quantification. Regressed MAs were more difficult to detect reliably than new MAs, which were themselves more difficult to detect reliably than static MAs.
CONCLUSIONS: The automated system was shown to be fast, reliable, and repeatable, making it suitable for processing large numbers of images. Performance was similar to that of trained manual observers.

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Mesh:

Year:  2003        PMID: 14638735     DOI: 10.1167/iovs.02-0951

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  7 in total

1.  Classification of human retinal microaneurysms using adaptive optics scanning light ophthalmoscope fluorescein angiography.

Authors:  Michael Dubow; Alexander Pinhas; Nishit Shah; Robert F Cooper; Alexander Gan; Ronald C Gentile; Vernon Hendrix; Yusufu N Sulai; Joseph Carroll; Toco Y P Chui; Joseph B Walsh; Rishard Weitz; Alfredo Dubra; Richard B Rosen
Journal:  Invest Ophthalmol Vis Sci       Date:  2014-03-04       Impact factor: 4.799

2.  AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images.

Authors:  Qian Zhang; Konstantina Sampani; Mengjia Xu; Shengze Cai; Yixiang Deng; He Li; Jennifer K Sun; George Em Karniadakis
Journal:  Transl Vis Sci Technol       Date:  2022-08-01       Impact factor: 3.048

3.  Microaneurysm turnover at the macula predicts risk of development of clinically significant macular edema in persons with mild nonproliferative diabetic retinopathy.

Authors:  Maria Luisa Ribeiro; Sandrina G Nunes; José G Cunha-Vaz
Journal:  Diabetes Care       Date:  2012-11-30       Impact factor: 19.112

4.  Noninvasive detection of microaneurysms in diabetic retinopathy by swept-source optical coherence tomography.

Authors:  Sarah Cheng; Theodore Leng
Journal:  Clin Ophthalmol       Date:  2016-09-16

5.  Estimation of Diabetic Retinal Microaneurysm Perfusion Parameters Based on Computational Fluid Dynamics Modeling of Adaptive Optics Scanning Laser Ophthalmoscopy.

Authors:  Miguel O Bernabeu; Yang Lu; Omar Abu-Qamar; Lloyd P Aiello; Jennifer K Sun
Journal:  Front Physiol       Date:  2018-09-07       Impact factor: 4.566

Review 6.  The Role of Inflammation in Diabetic Retinopathy.

Authors:  John V Forrester; Lucia Kuffova; Mirela Delibegovic
Journal:  Front Immunol       Date:  2020-11-06       Impact factor: 7.561

7.  Noninvasive temporal detection of early retinal vascular changes during diabetes.

Authors:  Mohammad Ali Saghiri; Andrew Suscha; Shoujian Wang; Ali Mohammad Saghiri; Christine M Sorenson; Nader Sheibani
Journal:  Sci Rep       Date:  2020-10-15       Impact factor: 4.996

  7 in total

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