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Volume Averaging of Spectral-Domain Optical Coherence Tomography Impacts Retinal Segmentation in Children

View Article: PubMed Central - PubMed

ABSTRACT

Purpose: To determine the influence of volume averaging on retinal layer thickness measures acquired with spectral-domain optical coherence tomography (SD-OCT) in children.

Methods: Macular SD-OCT images were acquired using three different volume settings (i.e., 1, 3, and 9 volumes) in children enrolled in a prospective OCT study. Total retinal thickness and five inner layers were measured around an Early Treatment Diabetic Retinopathy Scale (ETDRS) grid using beta version automated segmentation software for the Spectralis. The magnitude of manual segmentation required to correct the automated segmentation was classified as either minor (<12 lines adjusted), moderate (>12 and <25 lines adjusted), severe (>26 and <48 lines adjusted), or fail (>48 lines adjusted or could not adjust due to poor image quality). The frequency of each edit classification was assessed for each volume setting. Thickness, paired difference, and 95% limits of agreement of each anatomic quadrant were compared across volume density.

Results: Seventy-five subjects (median age 11.8 years, range 4.3–18.5 years) contributed 75 eyes. Less than 5% of the 9- and 3-volume scans required more than minor manual segmentation corrections, compared with 71% of 1-volume scans. The inner (3 mm) region demonstrated similar measures across all layers, regardless of volume number. The 1-volume scans demonstrated greater variability of the retinal nerve fiber layer (RNLF) thickness, compared with the other volumes in the outer (6 mm) region.

Conclusions: In children, volume averaging of SD-OCT acquisitions reduce retinal layer segmentation errors.

Translational relevance: This study highlights the importance of volume averaging when acquiring macula volumes intended for multilayer segmentation.

No MeSH data available.


Related in: MedlinePlus

Example of an automated segmentation error, requiring a minor amount of manual correction, occurring in a 3-volume (ART of 3) scan.
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i2164-2591-5-4-12-f04: Example of an automated segmentation error, requiring a minor amount of manual correction, occurring in a 3-volume (ART of 3) scan.

Mentions: The magnitude of manual segmentation required to correct the automated segmentation was classified as either minor (<12 segmentation lines adjusted, see Fig. 4), moderate (>12 and <25 lines adjusted), severe (>26 and <48 lines adjusted), or fail (>48 lines adjusted or could not discriminate the layers due to low quality sections). The frequency of each edit classification was assessed for each volume density.


Volume Averaging of Spectral-Domain Optical Coherence Tomography Impacts Retinal Segmentation in Children
Example of an automated segmentation error, requiring a minor amount of manual correction, occurring in a 3-volume (ART of 3) scan.
© Copyright Policy - cc-by-nc-nd
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4997888&req=5

i2164-2591-5-4-12-f04: Example of an automated segmentation error, requiring a minor amount of manual correction, occurring in a 3-volume (ART of 3) scan.
Mentions: The magnitude of manual segmentation required to correct the automated segmentation was classified as either minor (<12 segmentation lines adjusted, see Fig. 4), moderate (>12 and <25 lines adjusted), severe (>26 and <48 lines adjusted), or fail (>48 lines adjusted or could not discriminate the layers due to low quality sections). The frequency of each edit classification was assessed for each volume density.

View Article: PubMed Central - PubMed

ABSTRACT

Purpose: To determine the influence of volume averaging on retinal layer thickness measures acquired with spectral-domain optical coherence tomography (SD-OCT) in children.

Methods: Macular SD-OCT images were acquired using three different volume settings (i.e., 1, 3, and 9 volumes) in children enrolled in a prospective OCT study. Total retinal thickness and five inner layers were measured around an Early Treatment Diabetic Retinopathy Scale (ETDRS) grid using beta version automated segmentation software for the Spectralis. The magnitude of manual segmentation required to correct the automated segmentation was classified as either minor (&lt;12 lines adjusted), moderate (&gt;12 and &lt;25 lines adjusted), severe (&gt;26 and &lt;48 lines adjusted), or fail (&gt;48 lines adjusted or could not adjust due to poor image quality). The frequency of each edit classification was assessed for each volume setting. Thickness, paired difference, and 95% limits of agreement of each anatomic quadrant were compared across volume density.

Results: Seventy-five subjects (median age 11.8 years, range 4.3&ndash;18.5 years) contributed 75 eyes. Less than 5% of the 9- and 3-volume scans required more than minor manual segmentation corrections, compared with 71% of 1-volume scans. The inner (3 mm) region demonstrated similar measures across all layers, regardless of volume number. The 1-volume scans demonstrated greater variability of the retinal nerve fiber layer (RNLF) thickness, compared with the other volumes in the outer (6 mm) region.

Conclusions: In children, volume averaging of SD-OCT acquisitions reduce retinal layer segmentation errors.

Translational relevance: This study highlights the importance of volume averaging when acquiring macula volumes intended for multilayer segmentation.

No MeSH data available.


Related in: MedlinePlus