研究目的
To provide a baseline longitudinal quantification of retinal thickness in the Royal College of Surgeons (RCS) rat using spectral-domain optical coherence tomography (SD-OCT) to overcome the limitations of postmortem anatomic assessments for longitudinal studies.
研究成果
SD-OCT enables longitudinal quantification of retinal degeneration in RCS rats, with TR and ONL+ thickness decreasing significantly. The HRL correlates with disorganized outer segments and debris. This provides a baseline for future therapeutic assessments, complementing histology.
研究不足
The study was restricted to the posterior retina (up to 40° from optic nerve head), and manual segmentation became challenging as the ONL became hyperreflective and isoreflective with other layers over time. RPE thickness measurements showed variation due to hyperreflectance issues.
1:Experimental Design and Method Selection:
The study used SD-OCT for in vivo imaging to quantify retinal layer thicknesses longitudinally in RCS rats, comparing them to Long-Evans control rats. Histologic sections were used for correlation.
2:Sample Selection and Data Sources:
Pigmented RCS rats (RCS-p+/Lav) and wild-type Long-Evans rats were used. RCS rats were imaged weekly from P17 to P60 and at P90, with 7-10 rats per time point. Long-Evans rats were imaged at P30, P60, and P90, with 4 rats per time point.
3:List of Experimental Equipment and Materials:
SD-OCT device (Envisu R2200-HR, Bioptigen), sedation drugs (ketamine, xylazine), pupil dilation agents (tropicamide, phenylephrine), artificial tears, histology equipment (microtome, microscope, stains).
4:Experimental Procedures and Operational Workflow:
Pupils were dilated, sedation induced, and SD-OCT scans (horizontal and vertical linear scans centered on optic nerve) captured. Images were exported, registered, averaged, and manually segmented using custom software. Histology involved enucleation, fixation, sectioning, staining, and microscopy.
5:Data Analysis Methods:
Manual segmentation quantified TR, ONL+, INL, RPE, and HRL thicknesses. Intraclass correlation coefficients assessed variability. Statistical analysis included 2-way ANOVA and best-fit equations for thickness changes over time.
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