2018
DOI: 10.1097/ico.0000000000001799
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Classification of Limbal Stem Cell Deficiency Using Clinical and Confocal Grading

Abstract: Purpose: To grade the severity of limbal stem cell deficiency (LSCD) based on the extent of clinical presentation and central cornea basal epithelial cell density (BCD). Methods: This is a retrospective observational case-control study of forty-eight eyes of 35 patients with LSCD and 9 eyes of 7 normal subjects were included. Confocal images of the central cornea were acquired. A clinical scoring system was created based on the extent of limbal and corneal surface involvement. LSCD was graded as mild, modera… Show more

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Cited by 32 publications
(18 citation statements)
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“…LSCD is thought to be one of the most challenging corneal diseases to diagnose and relates to the disruption of LSCs niche causing corneal opacity and vision loss. 30 Therefore, the vast number of stem cells and materials has been investigated for LSCD treatment purposes during the last several decades. 6 The first case of oral mucosa tissue sheets use for the treatment of eye burns was shown by Ballen in the early 1970s.…”
Section: Discussionmentioning
confidence: 99%
“…LSCD is thought to be one of the most challenging corneal diseases to diagnose and relates to the disruption of LSCs niche causing corneal opacity and vision loss. 30 Therefore, the vast number of stem cells and materials has been investigated for LSCD treatment purposes during the last several decades. 6 The first case of oral mucosa tissue sheets use for the treatment of eye burns was shown by Ballen in the early 1970s.…”
Section: Discussionmentioning
confidence: 99%
“…Some major advantages are its non-invasiveness, its time-efficiency, its high reproducibility and its allowance for multiple replicates in both cross-sectional and longitudinal studies [ 60, 61 ]. Although normative values are available [ 62 ] and the technique seems very promising [ 63 ], outcomes seem to vary between different research groups and remains a topic of discussion [ 64 ]. Automated classification shows representative results [ 65 ].…”
Section: Resultsmentioning
confidence: 99%
“…The proposed classification algorithm: Rclassify, which is an extension to the Relief algorithm. The major drawback of Relief algorithm is its limitation to binary classification and also its jeopardizing of losing data [40], our proposed method Rclassify is more robust against incomplete data. Rclassify is characterized by its filtering technique that can analyze intrinsic data features regardless of the classifier type.…”
Section: Feature Selectionmentioning
confidence: 99%