Cinematic rendering in CT angiography: a pictorial review of clinical applications
With the rapid advancement of multi-detector computed tomography (MDCT) and image post-processing technologies, CT angiography (CTA) has become a cornerstone in the diagnosis of vascular diseases. Despite its widespread use, conventional volume rendering (VR) is limited in depth perception, visualization of fine tissue textures, and differentiation of complex, overlapping anatomical structures. Cinematic rendering (CR), a next-generation visualization technique, utilizes a global illumination model to achieve photorealistic 3D reconstructions. This pictorial review is structured around representative CTA cases to illustrate the principles, clinical applications, and potential future directions of cinematic rendering in vascular imaging. CRITICAL RELEVANCE STATEMENT: By reviewing the clinical applications of cinematic rendering in CT angiography, we summarize its advantages in visualizing complex vascular anatomy and explore its integration with emerging technologies, highlighting its role in optimizing preoperative planning and advancing precision medicine. KEY POINTS: Cinematic rendering employs global illumination and high dynamic range to surpass traditional volume rendering, enhancing anatomical realism for effective vascular diagnosis and lesion detection. Cinematic rendering transforms complex data into intuitive three-dimensional visualizations, reducing cognitive load for clinicians and facilitating both medical education and patient communication. Integration with artificial intelligence and mixed reality holds the potential to advance cinematic rendering from morphological displays to intelligent, interactive tools for preoperative planning.
Authors
- Yingxia Yang
- Zhen-Peng Peng
- Lei Ding (ORCID: https://orcid.org/0000-0002-8626-9638)
- Chen Li-na
- Chong‐ze Yang (ORCID: https://orcid.org/0000-0003-1564-7635)
- Hua-song Cai
- Ming-jie Chen
- Xiao-fang Chen
- Shi-Ting Feng (ORCID: https://orcid.org/0000-0002-0869-7290)
Institutions
- Sun Yat-sen University (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Siemens Healthcare (United States) (US)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-05-21
- DOI
- https://doi.org/10.1186/s13244-026-02310-8
- Primary Topic
- Anatomy and Medical Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China