Korean J Ophthalmol.  2019 Jun;33(3):279-286. 10.3341/kjo.2019.0004.

Spatial and Temporal Characteristics of Visual Field Progression in Glaucoma Assessed by Parallel Factor Analysis

• Kim S
• Shon K
• Sung KR

• KMID: 2448868
• DOI: http://doi.org/10.3341/kjo.2019.0004

Abstract

PURPOSE
To explore spatial and temporal characteristics of glaucomatous visual field (VF) progression through multi-way decomposition of data.
METHODS
Six serial VF exams with intervals of 6.0 ± 1.0 months in 121 pre-perimetric glaucoma eyes and 80 perimetric glaucoma eyes were arranged into a three-dimensional cube. The data were decomposed using parallel factor analysis.
RESULTS
Three tri-linear components (i.e., spatial scores, temporal loadings, and subject-specific loadings) were identified. Component 1 clearly showed differences between superior and inferior hemispheres, linear trends over time, and wide variability in perimetric glaucoma. Findings were compatible with well-known characteristics of glaucomatous VF defects. Component 2 showed nasal and central areas in contrast with superior, inferior, and temporal peripheral locations, whereas component 3 showed a contrast between nasal and temporal hemispheres. Both components 2 and 3 failed to show clear temporal trends.
CONCLUSIONS
Identification of spatio-temporal patterns shows new possibilities for a multi-way decomposition methodology for earlier diagnosis and prediction of glaucomatous VF progression.

Keyword

Glaucoma; Multi-way decomposition; Parallel factor analysis; Visual fields

MeSH Terms

Diagnosis
Factor Analysis, Statistical*
Glaucoma*
Visual Fields*

Figure

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  Fig. 1 Diagram representing the parallel factor analysis model. VF = visual field.

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  Fig. 2 Goodness of fit (%) with varying number of components (the number under each point denotes the number of components included in the analysis).

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  Fig. 3 Spatial scores of three components. (A) Component 1, (B) component 2, and (C) component 3 are arranged to match visual field locations (both eyes presented as the right eye). (D) Reference map of visual field locations. SN = superonasal; ST = superotemporal; IN = inferonasal; IT = inferotemporal.

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  Fig. 4 Temporal loadings of three components. (A) Component 1 showed clear linear pattern. (B) Component 2 and (C) component 3 did not show the same trend (time 1 = initial follow-up, time 6 = last follow-up).

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  Fig. 5 Histogram of subject loadings by group. PG subjects had wider and subnormal distributions compared to PPG subjects in (A) component 1, (B) component 2, and (C) component 3. (A) Component 1 showed clear variability. PPG = pre-perimetric glaucoma; PG = perimetric glaucoma.

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