Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario

Purpose. Considering that intraocular pressure (IOP) is an important confounding factor in corneal biomechanical evaluation, the notion of matching IOP should be introduced to eliminate any potential bias. This study aimed to assess the capability of a novel parameter set (NPS) derived from IOP-matc...

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Main Authors: Dan Lin, Lei Tian, Shu Zhang, Like Wang, Ying Jie, Yongjin Zhou
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Journal of Ophthalmology
Online Access:http://dx.doi.org/10.1155/2020/6530279
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author Dan Lin
Lei Tian
Shu Zhang
Like Wang
Ying Jie
Yongjin Zhou
author_facet Dan Lin
Lei Tian
Shu Zhang
Like Wang
Ying Jie
Yongjin Zhou
author_sort Dan Lin
collection DOAJ
description Purpose. Considering that intraocular pressure (IOP) is an important confounding factor in corneal biomechanical evaluation, the notion of matching IOP should be introduced to eliminate any potential bias. This study aimed to assess the capability of a novel parameter set (NPS) derived from IOP-matched scenario to diagnose keratoconus. Methods. Seventy samples (training set; 35 keratoconus and 35 normal corneas; pairwise matching for IOP) were used to determine NPS by forward logistic regression. A large validation dataset comprising 62 matching samples (31 keratoconus and 31 normal corneas) and 203 unmatching samples (112 keratoconus and 91 normal corneas) was used to evaluate its clinical significance. To further assess its diagnosis capability, NPS was compared with the other two prior biomechanical indexes. Results. NPS was comprised of three biomechanical parameters, namely, DA Ratio Max 1 mm (DRM1), the first applanation time (AT1), and an energy loading parameter (Eload). NPS was successfully applied to the validation dataset, with a higher accuracy of 96.8% and 95.6% in the IOP-matched and -unmatched scenarios, respectively. More surprisingly, accuracy of NPS was 95.5% in the combined validation, an improvement compared to the two prior biomechanical indexes. Conclusions. This is the first study taking IOP bias into consideration to determine a biomechanical parameter set. Our study shows that NPS indeed offers comparable performance in keratoconus diagnosis. Translational Relevance. Determining a parameter set after eliminating the influence from IOP is useful in revealing the essential differences between keratoconus and normal corneas and possibly facilitating further progress in keratoconus diagnosis.
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spelling doaj-art-bd29d03e51164873b8fc6bc0f19b518a2025-02-03T01:20:20ZengWileyJournal of Ophthalmology2090-004X2090-00582020-01-01202010.1155/2020/65302796530279Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched ScenarioDan Lin0Lei Tian1Shu Zhang2Like Wang3Ying Jie4Yongjin Zhou5Shenzhen University, Health Science Center, School of Biomedical Engineering, Xueyuan Avenue 1066, Shenzhen 518055, ChinaBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, ChinaShenzhen University, Health Science Center, School of Biomedical Engineering, Xueyuan Avenue 1066, Shenzhen 518055, ChinaShenzhen University, Health Science Center, School of Biomedical Engineering, Xueyuan Avenue 1066, Shenzhen 518055, ChinaBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, ChinaShenzhen University, Health Science Center, School of Biomedical Engineering, Xueyuan Avenue 1066, Shenzhen 518055, ChinaPurpose. Considering that intraocular pressure (IOP) is an important confounding factor in corneal biomechanical evaluation, the notion of matching IOP should be introduced to eliminate any potential bias. This study aimed to assess the capability of a novel parameter set (NPS) derived from IOP-matched scenario to diagnose keratoconus. Methods. Seventy samples (training set; 35 keratoconus and 35 normal corneas; pairwise matching for IOP) were used to determine NPS by forward logistic regression. A large validation dataset comprising 62 matching samples (31 keratoconus and 31 normal corneas) and 203 unmatching samples (112 keratoconus and 91 normal corneas) was used to evaluate its clinical significance. To further assess its diagnosis capability, NPS was compared with the other two prior biomechanical indexes. Results. NPS was comprised of three biomechanical parameters, namely, DA Ratio Max 1 mm (DRM1), the first applanation time (AT1), and an energy loading parameter (Eload). NPS was successfully applied to the validation dataset, with a higher accuracy of 96.8% and 95.6% in the IOP-matched and -unmatched scenarios, respectively. More surprisingly, accuracy of NPS was 95.5% in the combined validation, an improvement compared to the two prior biomechanical indexes. Conclusions. This is the first study taking IOP bias into consideration to determine a biomechanical parameter set. Our study shows that NPS indeed offers comparable performance in keratoconus diagnosis. Translational Relevance. Determining a parameter set after eliminating the influence from IOP is useful in revealing the essential differences between keratoconus and normal corneas and possibly facilitating further progress in keratoconus diagnosis.http://dx.doi.org/10.1155/2020/6530279
spellingShingle Dan Lin
Lei Tian
Shu Zhang
Like Wang
Ying Jie
Yongjin Zhou
Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
Journal of Ophthalmology
title Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
title_full Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
title_fullStr Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
title_full_unstemmed Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
title_short Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario
title_sort keratoconus diagnosis validation of a novel parameter set derived from iop matched scenario
url http://dx.doi.org/10.1155/2020/6530279
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