Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Cirous Dehghani, Nicola Pritchard, Katie Edwards, Anthony W. Russell, Rayaz Malik, Nathan Efron

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

PURPOSE: The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). METHODS: Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. RESULTS: For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm, 16.0 ± 3.9 mm/mm, and 16.5 ± 3.6 mm/mm, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87-0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland-Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). CONCLUSIONS: Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

Original languageEnglish
Pages (from-to)696-702
Number of pages7
JournalCornea
Volume33
Issue number7
DOIs
Publication statusPublished - 2014
Externally publishedYes

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Nerve Fibers
Nerve Tissue
Diabetic Neuropathies
Peripheral Nervous System Diseases
Confocal Microscopy
Software

Keywords

  • corneal confocal microscopy
  • corneal nerve fiber length
  • diabetic neuropathy
  • morphometric analysis

ASJC Scopus subject areas

  • Ophthalmology

Cite this

Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes. / Dehghani, Cirous; Pritchard, Nicola; Edwards, Katie; Russell, Anthony W.; Malik, Rayaz; Efron, Nathan.

In: Cornea, Vol. 33, No. 7, 2014, p. 696-702.

Research output: Contribution to journalArticle

Dehghani, Cirous ; Pritchard, Nicola ; Edwards, Katie ; Russell, Anthony W. ; Malik, Rayaz ; Efron, Nathan. / Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes. In: Cornea. 2014 ; Vol. 33, No. 7. pp. 696-702.
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AB - PURPOSE: The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). METHODS: Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. RESULTS: For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm, 16.0 ± 3.9 mm/mm, and 16.5 ± 3.6 mm/mm, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87-0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland-Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). CONCLUSIONS: Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

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