Spectral imaging in ophthalmology refers to techniques that capture information across multiple wavelengths of light, allowing analysis of tissue composition and function beyond standard colour images. It can involve hyperspectral or multispectral systems.
Principles
By recording reflectance or fluorescence at many discrete wavelengths, spectral imaging generates a spectrum for each pixel. Different tissues and molecules have distinct spectral signatures, enabling contrast based on biochemical properties.
- Can be implemented with tunable filters, prisms, or interferometers
- Data cubes provide spatial and spectral information simultaneously
- Processing algorithms separate contributions from various chromophores
- Acquisition speed and data size are key practical considerations
Potential Applications
Spectral imaging is being explored for early detection of retinal disease, assessment of oxygenation, and improved visualisation of lesions or drusen. It may enhance screening and monitoring by revealing subtle functional changes before structural damage is obvious.
- Research use currently exceeds routine clinical deployment
- May help differentiate benign from malignant or active from quiescent lesions
- Could inform personalised treatment strategies based on tissue metabolism
- Requires robust calibration and standardisation for clinical adoption
