Comparison of Choroidal Thickness Measurements Using Semiautomated and Manual Segmentation Methods

This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners. The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation meth...

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Published inOptometry and vision science Vol. 97; no. 2; pp. 121 - 127
Main Authors Zhao, Mei, Alonso-Caneiro, David, Lee, Roger, Cheong, Allen M. Y., Yu, Wing-Yan, Wong, Ho-Yin, Lam, Andrew K. C.
Format Journal Article
LanguageEnglish
Published United States Lippincott Williams & Wilkins 01.02.2020
Subjects
Online AccessGet full text
ISSN1040-5488
1538-9235
1538-9235
DOI10.1097/OPX.0000000000001473

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Abstract This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners. The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods. Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately. The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method. With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced.
AbstractList This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners.SIGNIFICANCEThis study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners.The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods.PURPOSEThe purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods.Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately.METHODSOptical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately.The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method.RESULTSThe between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method.With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced.CONCLUSIONSWith the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced.
This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners. The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods. Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately. The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method. With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced.
Author Yu, Wing-Yan
Lam, Andrew K. C.
Alonso-Caneiro, David
Wong, Ho-Yin
Cheong, Allen M. Y.
Zhao, Mei
Lee, Roger
AuthorAffiliation Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia
Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China
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Cites_doi 10.1364/BOE.4.000397
10.1016/j.exer.2015.03.002
10.1136/bjophthalmol-2015-307169
10.1007/s10792-014-9962-4
10.1097/IAE.0b013e3181be0a83
10.1001/jamaophthalmol.2013.7288
10.1016/j.clae.2017.09.010
10.1364/BOE.3.000086
10.1007/s00417-011-1708-7
10.1364/BOE.4.002795
10.1167/iovs.10-6024
10.1007/s00417-017-3723-9
10.1167/iovs.13-11732
10.1016/j.ophtha.2010.09.012
10.1097/IAE.0000000000001516
10.1097/OPX.0000000000000985
10.1364/OE.20.007564
10.1016/j.cmpb.2017.11.002
10.1167/iovs.12-10578
10.1371/journal.pone.0193324
10.1038/s41598-018-26635-7
10.1371/journal.pone.0161535
10.1186/s12886-015-0110-3
10.1016/j.compmedimag.2018.01.001
10.1038/eye.2017.210
10.1167/iovs.12-10311
10.1167/iovs.18-24665
10.1167/iovs.11-8076
10.1136/bjophthalmol-2015-307985
10.1167/iovs.12-11521
10.1016/j.ajo.2011.03.008
10.1167/iovs.15-16446
10.1097/IAE.0000000000001756
10.1136/bjophthalmol-2013-304000
10.1167/iovs.15-17102
10.1016/j.ajo.2011.12.013
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References (bib34-20230823) 2015; 135
(bib26-20230823) 2016; 100
(bib31-20230823) 2018; 8
(bib12-20230823) 2015; 35
(bib11-20230823) 2015; 15
(bib14-20230823) 2011; 249
(bib22-20230823) 2013; 4
(bib23-20230823) 2018; 63
(bib25-20230823) 2016; 93
(bib17-20230823) 2012; 3
(bib7-20230823) 2017; 6
(bib28-20230823) 2012; 20
(bib39-20230823) 2016; 100
(bib27-20230823) 2018; 13
(bib2-20230823) 2011; 152
(bib29-20230823) 2014; 2014
(bib1-20230823) 2009; 29
(bib30-20230823) 2013; 4
(bib10-20230823) 2014; 2014
(bib15-20230823) 2017; 255
(bib5-20230823) 2016; 11
(bib19-20230823) 2012; 53
(bib32-20230823) 2013; 54
(bib38-20230823) 2012; 153
(bib4-20230823) 2017; 40
(bib35-20230823) 2018; 32
(bib6-20230823) 2015; 56
(bib18-20230823) 2012
(bib40-20230823) 2018; 38
(bib13-20230823) 2018; 38
(bib3-20230823) 2011; 118
(bib24-20230823) 2018; 158
(bib37-20230823) 2011; 52
(bib8-20230823) 2014; 132
(bib9-20230823) 2018; 59
(bib20-20230823) 2013; 54
(bib21-20230823) 2013; 54
(bib16-20230823) 2014; 98
(bib36-20230823) 2011; 52
(bib33-20230823) 2015; 56
References_xml – volume: 4
  start-page: 397
  year: 2013
  ident: bib22-20230823
  article-title: Automatic Segmentation of the Choroid in Enhanced Depth Imaging Optical Coherence Tomography Images
  publication-title: Biomed Opt Express
  doi: 10.1364/BOE.4.000397
– volume: 135
  start-page: 164
  year: 2015
  ident: bib34-20230823
  article-title: Peripapillary Choroidal Thickness in Childhood
  publication-title: Exp Eye Res
  doi: 10.1016/j.exer.2015.03.002
– volume: 100
  start-page: 677
  year: 2016
  ident: bib39-20230823
  article-title: Choroidal Maps in Non-exudative Age-related Macular Degeneration
  publication-title: Br J Ophthalmol
  doi: 10.1136/bjophthalmol-2015-307169
– volume: 35
  start-page: 403
  year: 2015
  ident: bib12-20230823
  article-title: Choroidal Thickness in Relation to Sex, Age, Refractive Error, and Axial Length in Healthy Turkish Subjects
  publication-title: Int Ophthalmol
  doi: 10.1007/s10792-014-9962-4
– volume: 29
  start-page: 1469
  year: 2009
  ident: bib1-20230823
  article-title: Enhanced Depth Imaging Optical Coherence Tomography of the Choroid in Central Serous Chorioretinopathy
  publication-title: Retina
  doi: 10.1097/IAE.0b013e3181be0a83
– volume: 132
  start-page: 174
  year: 2014
  ident: bib8-20230823
  article-title: Characterization of the Choroid-scleral Junction and Suprachoroidal Layer in Healthy Individuals on Enhanced-depth Imaging Optical Coherence Tomography
  publication-title: JAMA Ophthalmol
  doi: 10.1001/jamaophthalmol.2013.7288
– volume: 40
  start-page: 417
  year: 2017
  ident: bib4-20230823
  article-title: Choroidal Thickness and Axial Length Changes in Myopic Children Treated with Orthokeratology
  publication-title: Cont Lens Anterior Eye
  doi: 10.1016/j.clae.2017.09.010
– volume: 3
  start-page: 86
  year: 2012
  ident: bib17-20230823
  article-title: Automated Choroidal Segmentation of 1060 nm OCT in Healthy and Pathologic Eyes Using a Statistical Model
  publication-title: Biomed Opt Express
  doi: 10.1364/BOE.3.000086
– volume: 249
  start-page: 1485
  year: 2011
  ident: bib14-20230823
  article-title: Choroidal Thickness Measurement in Healthy Japanese Subjects by Three-dimensional High-penetration Optical Coherence Tomography
  publication-title: Graefes Arch Clin Exp Ophthalmol
  doi: 10.1007/s00417-011-1708-7
– volume: 2014
  start-page: 479268
  year: 2014
  ident: bib29-20230823
  article-title: Segmentation of Choroidal Boundary in Enhanced Depth Imaging OCTs Using a Multiresolution Texture Based Modeling in Graph Cuts
  publication-title: Comput Math Methods Med
– volume: 4
  start-page: 2795
  year: 2013
  ident: bib30-20230823
  article-title: Automatic Segmentation of Choroidal Thickness in Optical Coherence Tomography
  publication-title: Biomed Opt Express
  doi: 10.1364/BOE.4.002795
– volume: 52
  start-page: 2267
  year: 2011
  ident: bib36-20230823
  article-title: Repeatability of Manual Subfoveal Choroidal Thickness Measurements in Healthy Subjects Using the Technique of Enhanced Depth Imaging Optical Coherence Tomography
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.10-6024
– volume: 255
  start-page: 1957
  year: 2017
  ident: bib15-20230823
  article-title: Mapping Diurnal Changes in Choroidal, Haller's and Sattler's Layer Thickness Using 3-dimensional 1060-nm Optical Coherence Tomography
  publication-title: Graefes Arch Clin Exp Ophthalmol
  doi: 10.1007/s00417-017-3723-9
– volume: 54
  start-page: 3586
  year: 2013
  ident: bib32-20230823
  article-title: Choroidal Thickness in Childhood
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.13-11732
– volume: 118
  start-page: 840
  year: 2011
  ident: bib3-20230823
  article-title: Choroidal Thickness in Polypoidal Choroidal Vasculopathy and Exudative Age-related Macular Degeneration
  publication-title: Ophthalmology
  doi: 10.1016/j.ophtha.2010.09.012
– volume: 38
  start-page: 173
  year: 2018
  ident: bib40-20230823
  article-title: Choroidal Thickness in Diabetic Retinopathy Assessed with Swept-source Optical Coherence Tomography
  publication-title: Retina
  doi: 10.1097/IAE.0000000000001516
– volume: 93
  start-page: 1387
  year: 2016
  ident: bib25-20230823
  article-title: Validation of Macular Choroidal Thickness Measurements from Automated SD-OCT Image Segmentation
  publication-title: Optom Vis Sci
  doi: 10.1097/OPX.0000000000000985
– volume: 20
  start-page: 7564
  year: 2012
  ident: bib28-20230823
  article-title: Automated Measurement of Choroidal Thickness in the Human Eye by Polarization Sensitive Optical Coherence Tomography
  publication-title: Opt Express
  doi: 10.1364/OE.20.007564
– volume: 158
  start-page: 161
  year: 2018
  ident: bib24-20230823
  article-title: Automated Choroid Segmentation of Three-dimensional SD-OCT Images by Incorporating EDI-OCT Images
  publication-title: Comput Methods Programs Biomed
  doi: 10.1016/j.cmpb.2017.11.002
– volume: 54
  start-page: 1722
  year: 2013
  ident: bib20-20230823
  article-title: Semiautomated Segmentation of the Choroid in Spectral-domain Optical Coherence Tomography Volume Scans
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.12-10578
– volume: 13
  start-page: e0193324
  year: 2018
  ident: bib27-20230823
  article-title: Automated Quantification of Haller's Layer in Choroid Using Swept-source Optical Coherence Tomography
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0193324
– volume: 8
  start-page: 8200
  year: 2018
  ident: bib31-20230823
  article-title: Daily Morning Light Therapy Is Associated with an Increase in Choroidal Thickness in Healthy Young Adults
  publication-title: Sci Rep
  doi: 10.1038/s41598-018-26635-7
– volume: 11
  start-page: e0161535
  year: 2016
  ident: bib5-20230823
  article-title: Optical Defocus Rapidly Changes Choroidal Thickness in Schoolchildren
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0161535
– volume: 15
  start-page: 122
  year: 2015
  ident: bib11-20230823
  article-title: Swept-source Optical Coherence Tomography Imaging of Macular Retinal and Choroidal Structures in Healthy Eyes
  publication-title: BMC Ophthalmol
  doi: 10.1186/s12886-015-0110-3
– volume: 63
  start-page: 41
  year: 2018
  ident: bib23-20230823
  article-title: An Automated Method for Choroidal Thickness Measurement from Enhanced Depth Imaging Optical Coherence Tomography Images
  publication-title: Comput Med Imaging Graph
  doi: 10.1016/j.compmedimag.2018.01.001
– volume: 32
  start-page: 433
  year: 2018
  ident: bib35-20230823
  article-title: A Novel and Faster Method of Manual Grading to Measure Choroidal Thickness Using Optical Coherence Tomography
  publication-title: Eye (Lond)
  doi: 10.1038/eye.2017.210
– volume: 53
  start-page: 7510
  year: 2012
  ident: bib19-20230823
  article-title: Automated Segmentation of the Choroid from Clinical SD-OCT
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.12-10311
– volume: 59
  start-page: 4404
  year: 2018
  ident: bib9-20230823
  article-title: Posterior Choroidal Stroma Reduces Accuracy of Automated Segmentation of Outer Choroidal Boundary in Swept Source Optical Coherence Tomography
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.18-24665
– volume: 2014
  start-page: 639160
  year: 2014
  ident: bib10-20230823
  article-title: Correlation of Choroidal Thickness and Volume Measurements with Axial Length and Age Using Swept Source Optical Coherence Tomography and Optical Low-coherence Reflectometry
  publication-title: Biomed Res Int
– volume: 52
  start-page: 9555
  year: 2011
  ident: bib37-20230823
  article-title: Choroidal Thickness in Healthy Chinese Subjects
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.11-8076
– start-page: 5360
  year: 2012
  ident: bib18-20230823
  article-title: Automatic Measurements of Choroidal Thickness in EDI-OCT Images
  publication-title: Conf Proc IEEE Eng Med Biol Soc
– volume: 100
  start-page: 1372
  year: 2016
  ident: bib26-20230823
  article-title: Choroidal Thickness Maps from Spectral Domain and Swept Source Optical Coherence Tomography: Algorithmic versus Ground Truth Annotation
  publication-title: Br J Ophthalmol
  doi: 10.1136/bjophthalmol-2015-307985
– volume: 6
  start-page: 94
  year: 2017
  ident: bib7-20230823
  article-title: Past, Present, and Future Concepts of the Choroidal Scleral Interface Morphology on Optical Coherence Tomography
  publication-title: Asia Pac J Ophthalmol
– volume: 54
  start-page: 2864
  year: 2013
  ident: bib21-20230823
  article-title: Comparative Analysis of Repeatability of Manual and Automated Choroidal Thickness Measurements in Nonneovascular Age-related Macular Degeneration
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.12-11521
– volume: 152
  start-page: 663
  year: 2011
  ident: bib2-20230823
  article-title: Analysis of Choroidal Thickness in Age-related Macular Degeneration Using Spectral-domain Optical Coherence Tomography
  publication-title: Am J Ophthalmol
  doi: 10.1016/j.ajo.2011.03.008
– volume: 56
  start-page: 3103
  year: 2015
  ident: bib6-20230823
  article-title: Longitudinal Changes in Choroidal Thickness and Eye Growth in Childhood
  publication-title: Invest Ophth Vis Sci
  doi: 10.1167/iovs.15-16446
– volume: 38
  start-page: 1620
  year: 2018
  ident: bib13-20230823
  article-title: Interocular Asymmetry in Choroidal Thickness and Retinal Sensitivity in High Myopia
  publication-title: Retina
  doi: 10.1097/IAE.0000000000001756
– volume: 98
  start-page: 339
  year: 2014
  ident: bib16-20230823
  article-title: Topographic Variation of Choroidal and Retinal Thicknesses at the Macula in Healthy Adults
  publication-title: Br J Ophthalmol
  doi: 10.1136/bjophthalmol-2013-304000
– volume: 56
  start-page: 6414
  year: 2015
  ident: bib33-20230823
  article-title: Regional Changes in Choroidal Thickness Associated with Accommodation
  publication-title: Invest Ophthalmol Vis Sci
  doi: 10.1167/iovs.15-17102
– volume: 153
  start-page: 1133
  year: 2012
  ident: bib38-20230823
  article-title: Macular Choroidal Thickness and Volume in Eyes with Angioid Streaks Measured by Swept Source Optical Coherence Tomography
  publication-title: Am J Ophthalmol
  doi: 10.1016/j.ajo.2011.12.013
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Snippet This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced...
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SubjectTerms Adult
Choroid - anatomy & histology
Choroid - diagnostic imaging
Female
Healthy Volunteers
Humans
Male
Organ Size
Reproducibility of Results
Retrospective Studies
Tomography, Optical Coherence - methods
Young Adult
Title Comparison of Choroidal Thickness Measurements Using Semiautomated and Manual Segmentation Methods
URI https://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&AN=00006324-202002000-00012
https://www.ncbi.nlm.nih.gov/pubmed/32011585
https://www.proquest.com/docview/2350373986
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