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Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields.

Publication ,  Journal Article
Goldbaum, MH; Lee, I; Jang, G; Balasubramanian, M; Sample, PA; Weinreb, RN; Liebmann, JM; Girkin, CA; Anderson, DR; Zangwill, LM; Fredette, M-J ...
Published in: Invest Ophthalmol Vis Sci
September 25, 2012

PURPOSE: We evaluated Progression of Patterns (POP) for its ability to identify progression of glaucomatous visual field (VF) defects. METHODS: POP uses variational Bayesian independent component mixture model (VIM), a machine learning classifier (MLC) developed previously. VIM separated Swedish Interactive Thresholding Algorithm (SITA) VFs from a set of 2,085 normal and glaucomatous eyes into nine axes (VF patterns): seven glaucomatous. Stable glaucoma was simulated in a second set of 55 patient eyes with five VFs each, collected within four weeks. A third set of 628 eyes with 4,186 VFs (mean ± SD of 6.7 ± 1.7 VFs over 4.0 ± 1.4 years) was tested for progression. Tested eyes were placed into suspect and glaucoma categories at baseline, based on VFs and disk stereoscopic photographs; a subset of eyes had stereophotographic evidence of progressive glaucomatous optic neuropathy (PGON). Each sequence of fields was projected along seven VIM glaucoma axes. Linear regression (LR) slopes generated from projections onto each axis yielded a degree of confidence (DOC) that there was progression. At 95% specificity, progression cutoffs were established for POP, visual field index (VFI), and mean deviation (MD). Guided progression analysis (GPA) was also compared. RESULTS: POP identified a statistically similar number of eyes (P > 0.05) as progressing compared with VFI, MD, and GPA in suspects (3.8%, 2.7%, 5.6%, and 2.9%, respectively), and more eyes than GPA (P = 0.01) in glaucoma (16.0%, 15.3%, 12.0%, and 7.3%, respectively), and more eyes than GPA (P = 0.05) in PGON eyes (26.3%, 23.7%, 27.6%, and 14.5%, respectively). CONCLUSIONS: POP, with its display of DOC of progression and its identification of progressing VF defect pattern, adds to the information available to the clinician for detecting VF progression.

Duke Scholars

Published In

Invest Ophthalmol Vis Sci

DOI

EISSN

1552-5783

Publication Date

September 25, 2012

Volume

53

Issue

10

Start / End Page

6557 / 6567

Location

United States

Related Subject Headings

  • Visual Fields
  • Visual Field Tests
  • Visual Acuity
  • Vision Disorders
  • Retinal Ganglion Cells
  • Optic Nerve Diseases
  • Optic Disk
  • Ophthalmology & Optometry
  • Nerve Fibers
  • Middle Aged
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Goldbaum, M. H., Lee, I., Jang, G., Balasubramanian, M., Sample, P. A., Weinreb, R. N., … Bowd, C. (2012). Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields. Invest Ophthalmol Vis Sci, 53(10), 6557–6567. https://doi.org/10.1167/iovs.11-8363
Goldbaum, Michael H., Intae Lee, Giljin Jang, Madhusudhanan Balasubramanian, Pamela A. Sample, Robert N. Weinreb, Jeffrey M. Liebmann, et al. “Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields.Invest Ophthalmol Vis Sci 53, no. 10 (September 25, 2012): 6557–67. https://doi.org/10.1167/iovs.11-8363.
Goldbaum MH, Lee I, Jang G, Balasubramanian M, Sample PA, Weinreb RN, et al. Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields. Invest Ophthalmol Vis Sci. 2012 Sep 25;53(10):6557–67.
Goldbaum, Michael H., et al. “Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields.Invest Ophthalmol Vis Sci, vol. 53, no. 10, Sept. 2012, pp. 6557–67. Pubmed, doi:10.1167/iovs.11-8363.
Goldbaum MH, Lee I, Jang G, Balasubramanian M, Sample PA, Weinreb RN, Liebmann JM, Girkin CA, Anderson DR, Zangwill LM, Fredette M-J, Jung T-P, Medeiros FA, Bowd C. Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields. Invest Ophthalmol Vis Sci. 2012 Sep 25;53(10):6557–6567.

Published In

Invest Ophthalmol Vis Sci

DOI

EISSN

1552-5783

Publication Date

September 25, 2012

Volume

53

Issue

10

Start / End Page

6557 / 6567

Location

United States

Related Subject Headings

  • Visual Fields
  • Visual Field Tests
  • Visual Acuity
  • Vision Disorders
  • Retinal Ganglion Cells
  • Optic Nerve Diseases
  • Optic Disk
  • Ophthalmology & Optometry
  • Nerve Fibers
  • Middle Aged