QuizWise 20

  1. Which of the following can cause segmentation error?
    a. Staphyloma
    b. Epi retinal membrane
    c. Retinal vein occlusion
    d. Vitritis
    e. All of the above
  2. What does the red and blue lines indicate in the image?
a. Anterior boundary of RNFL and posterior boundary of GCL
b. ILM and anterior boundary of GCL
c. ILM and posterior boundary of GCL
d. Internal limiting membrane(ILM) and posterior boundary of RNFL

3. The segmentation error in the following image is due to

a. Sub hyaloid haemorrhage
b. Intra retinal haemorrhage
c. Discoedema
d. Hard exudates

4. In which of the following conditions, auto segmentation is routinely found to be accurate?
a. Neovascular Age Related Macular Degeneration
b. Central Serous Retinopathy
c. Glaucoma
d. Retinoschisis
e. Mild Asteroid hyalosis

5. Which of the following OCT is less prone to segmentation error?
a. Stratus OCT
b. Cirrus OCT
c. Spectralis OCT
d. Polarisation- sensitive OCT

6. Which of the following factor is not associated with artifacts in OCT scanning?
a. Decentration error
b. Posterior vitreous detachment
c. Large pupils
d. Media opacity  

Answers :

  1. e.
    The reasons for segmentation error on SDOCT are multifactorial. Automated segmentation can be impaired by pathologic conditions that alter the normal shape of the retinal layers. In cases of macular oedema (diabetic retinopathy, retinal vein occlusion, etc.), the presence of hard exudates can cause segmentation breakdown. The presence of epiretinal membrane or a highly reflective posterior hyaloid can provoke inner retinal boundary misidentification. If low SNR (signal: noise ratio) or significant media opacities are present, there might be incorrect identification of the inner boundary. Incorrect delineation of retinal boundaries by the segmentation software results in automated retinal thickness measurement errors and erroneous thickness maps displays. Artifacts have been associated with image decentration, epiretinal membranes, long axial length, poor visual acuity, cataract, and advanced glaucoma.

 Reference: Georgieva et al. Optical Coherence Tomography – Segmentation Performance and Retinal Thickness Measurement Errors. European Ophthalmic Review, 2012; 6(2):78 82 DOI:10.17925/EOR.2012.06.02.78

Mansberger et al. Automated Segmentation Errors When Using OCT to Measure RNFL Thickness in Glaucoma Am J Ophthalmol 2017; 174:1-8. DOI: 10.1016/j.ajo.2016.10.020

2. d.
Spectral Domain Optical Coherence Tomography (SD OCT) imaging is used for quantitative analysis of RNFL thickness. Inbuilt software algorithm in SD OCT detects anterior and posterior boundaries of RNFL based on the change in reflectivity at each of these interfaces. After segmentation, two- dimensional thickness maps are generated. If the software fails to delineate the retinal boundaries correctly (i.e. segmentation break- down), it will result in thickness measurement error which may lead to incorrect diagnosis of glaucoma.

Reference: Georgieva et al. Optical Coherence Tomography – Segmentation Performance and Retinal Thickness Measurement Errors. European Ophthalmic Review, 2012; 6(2):78 82 DOI:10.17925/EOR.2012.06.02.78

3. c.
Like other SD OCT devices, the Spectralis in built algorithms are not specifically designed to autosegment papilloedema. It is likely that oedema and vessel artifact lead to error in the average RNFL thickness automated values. In papilloedema, where the interface between the retinal layers is disturbed by oedema. Optic disc swelling can be monitored by repeated assessments of the RNFL thickness.

 Reference:  Aojula et al. Segmentation error in spectral domain optical coherence tomography measures of the RNFL thickness in idiopathic intracranial hypertension. BMC Ophthalmology (2017) 17:257 DOI 10.1186/s12886-017-0652-7

4. e.
Autosegmentation has been found to be inaccurate in some retinal pathologies such as neovascular age related macular degeneration and central serous retinopathy and in optic nerve head pathologies such as glaucoma.

Reference:  Aojula et al. Segmentation error in spectral domain optical coherence tomography measures of the RNFL thickness in idiopathic intracranial hypertension. BMC Ophthalmology (2017) 17:257 DOI 10.1186/s12886-017-0652-7

5. d.
Polarization-sensitive OCT, which is not currently commercially available, has the potential to delineate the RNFL boundary better, based on pigment differences in the retinal layers and less prone to Segmentation error.

Reference:  Aojula et al. Segmentation error in spectral domain optical coherence tomography measures of the RNFL thickness in idiopathic intracranial hypertension. BMC Ophthalmology (2017) 17:257 DOI 10.1186/s12886-017-0652-7

6. c.
A number of factors have been associated with artifacts in OCT scanning including decentration error, refractive error, posterior vitreous detachment artifacts, reduced visual acuity, small pupils, presence of media opacities, advanced stage of glaucoma and dry eyes.

Reference:  Aojula et al. Segmentation error in spectral domain optical coherence tomography measures of the RNFL thickness in idiopathic intracranial hypertension. BMC Ophthalmology (2017) 17:257 DOI 10.1186/s12886-017-0652-7

× Hello!
%d bloggers like this: