Abstract: Central serous chorioretinopathy(CSC) is a common disease that mainly affects central vision in young and middle-aged man, characterized by macular serous detachment. Although most of them can spontaneously subside, they have a high recurrence rate and are easy to evolve into chronic forms, resulting in permanent damage to the pigment cortex and photoreceptor cells of the retina, leading to irreversible long-term visual impairment and seriously affecting the quality of life of patients. Due to the unknown etiology of CSC and the diversity of clinical features, there is no unified classification and treatment method. Multimodal imaging techniques including fundus autofluorescence, fluorescein angiography, indocyanine green angiography, optical coherence tomography, and optical coherence tomography angiography have more systematically described the prognosis of CSC, their combination with machine learning technology can improve clinical efficiency. The purpose of this study was to comprehensively summarize prognostic biomarkers of CSC by using multi-mode imaging, so as to evaluate patients' prognosis and treatment response more systematically, thereby better guiding clinical treatment selection.