Software for NIDEK OCT series
Long Axial Length Normative Database

Features

  • Analysis with axial length compensation
  • Based on data from normal eyes with long axial length
  • Data collected from Asian cases
  • Standard software for use with the RS-1 Glauvas
  • Optional software for use with the Retina Scan DuoTM2 and Mirante SLO/OCT

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Detailed Information

Long axial length normative database

The Long Axial Length Normative Database (LAL-NDB) presents analysis with axial length compensation, allowing greater confidence for glaucoma assessment in patients with axial myopia. The LAL-NDB was developed based on data from normal eyes with long axial length. Data were collected from Asian cases by measuring the disc and macular area to obtain retinal thickness values, such as full retinal, RNFL, and GCC thickness, which are important parameters for diagnosing glaucoma. The LAL-NDB can be used in the RS-1 Glauvas, Retina Scan DuoTM2, and Mirante SLO/OCT.*

With the retina map which captures both the disc and macula in a single shot, LAL-NDB analysis is performed for both the RNFL and GCC on a single OCT image, facilitating efficient diagnostic screening.

 

*The LAL-NDB is available for the RS-1 Glauvas and optional for the Retina Scan DuoTM2 and Mirante SLO/OCT.
Product/model name: Optical Coherence Tomography RS-1, Optical Coherence Tomography RS-330, Scanning Laser Ophthalmoscope Mirante

 

Sample analysis of a patient with long axial length

Normative database (NDB)

 

Long axial length normative database (LAL-NDB)

 
Better outcomes with LAL-NDB analysis

Switching normative databases and correcting scan width based on the axial length

 

For RS-1 Glauvas

When using the RS-1 Glauvas, the analyses using the LAL-NDB will be automatically selected and displayed when the axial length*1, a parameter for scan width correction, is 26 mm or longer.
For Retina Scan DuoTM2 and Mirante SLO/OCT
Manual entry of the actual axial length allows for automated selection of the optimal normative database to display analyses with scan width correction.

 

*1 The value of the axial length is obtained based on the results of the OCT image capture and differs from the actual measured value of the axial length.
*2 Gullstrand eye model with 24.38 mm axial length

Deep learning segmentation (DL segmentation) for better analytic outcomes

The accuracy of segmentation affects the outcomes of glaucoma analysis. DL segmentation reduces artifacts and errors in the normative database, even in eyes with opacities, thus decreasing false positives and enhancing clinic efficiency by reducing unnecessary follow-up visits.
Comparison of NDB and LAL-NDB
NDB LAL-NDB
Axial length Less than 26 mm 26 mm to less than 29 mm
Age 20 years to under 80 years 20 years to under 60 years
Race (Data n) Asian (130 individuals), Caucasian (90 individuals) Asian (112 individuals)
Scan pattern Macula map, disc map, retina map Macula map, disc map, retina map

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NOTE

The availability of products differs from country to country depending on the status of approval.
Specifications and design are subject to change without notice.