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In Vivo Multimodal Imaging and Analysis of Mouse Laser-Induced Choroidal Neovascularization Model
Published on: January 21, 2018
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Detection of Choroidal Neovascularization Using Optical Tissue Transparency.
Xiao-Hong Ma1, Wen-Yang Feng2, Ke Xiao1
1Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China.
Translational Vision Science & Technology
|June 15, 2023
Summary
Optical tissue transparency with light-sheet fluorescence microscopy offers advanced 3D visualization for detecting choroidal neovascularization (CNV) lesions. This method provides valuable quantitative data for CNV research.
Area of Science:
- Ophthalmology
- Biomedical Imaging
- Histopathology
Background:
- Optical tissue transparency (OTT) enables whole-tissue block visualization.
- Choroidal neovascularization (CNV) is a significant cause of vision loss.
- Accurate detection and quantification of CNV are crucial for research and treatment.
Purpose of the Study:
- To evaluate the utility of OTT combined with light-sheet fluorescence microscopy (LSFM) for detecting and quantifying CNV lesions.
- To compare the efficacy of OTT with LSFM against established imaging modalities for CNV assessment.
Main Methods:
- CNV models were imaged using OTT with LSFM, H&E staining, choroidal flatmount immunofluorescence, and various optical coherence tomography angiography (OCTA) techniques.
- The rate of change in CNV was calculated between week 1 and week 2 post-laser photocoagulation.
- Quantitative comparisons were made between the different imaging methods.
Main Results:
- OTT with LSFM provided comprehensive three-dimensional (3D) visualization of entire CNV lesions.
- The rate of CNV change detected by OTT with LSFM was 33.05%, which was higher than most OCTA metrics but lower than H&E and choroidal flatmount.
- Specific OCTA metrics showed lower rates of change (e.g., vessel diameter index at 7.74%).
Conclusions:
- OTT with LSFM is a valuable tool for obtaining detailed visualized and quantified information on CNV.
- This technique holds promise for future human clinical trials in CNV detection and research.
