Lattice retinal degeneration is a common peripheral retinal degenerative condition and is widely recognized as a significant precursor to retinal detachment, resulting in severe visual loss. Recent advances in deep learning technologies have driven the development and adoption of automated screening systems for lattice retinal degeneration using ultra-widefield fundus imaging. These systems have demonstrated notable success in large-scale screening of peripheral retinal diseases, offering valuable support for the early identification and risk stratification of lattice degeneration. Currently, retinal laser photocoagulation remains the mainstay treatment for lattice degeneration. This intervention effectively mitigates the risk of rhegmatogenous retinal detachment. However, controversies persist regarding the optimal selection of treatment candidates and the evaluation of therapeutic efficacy. In the future, the continuous evolution of imaging analysis techniques and artificial intelligence holds promise for the development of personalized and precision-based intervention strategies. Such advancements are expected to provide more robust evidence to guide the diagnosis and treatment of lattice retinal degeneration, ultimately improving patient outcomes.
Diffuse choroidal retinal atrophy (DCA) is a type of myopic macular disease that presents with yellowish-white atrophic changes at the posterior pole of the eyeball. DCA is an important critical feature in the diagnosis of pathological myopia. Early intervention and treatment of this disease are of great significance in delaying the progression of pathological myopia and reducing the impairment of visual function. Ophthalmic imaging data can be used to diagnose the disease, and color fundus photography is the most simple and intuitive. Choroidal thickness is also a key indicator in the diagnosis of DCA, but the diagnostic critical value of choroidal thickness has not been clearly defined. With the development and popularization of artificial intelligence technology, the analysis of lesion imaging data is more objective and accurate. In the future, it is expected to actively establish a standard quantitative evaluation system for DCA by means of artificial intelligence to achieve early detection, early diagnosis and early treatment of pathological myopia.