• 摘要: 随着心脑血管疾病发病率持续上升,亟须高效、无创且高分辨率的影像技术支持其早期诊断与精准干预。光学相干层析成像 (Optical coherence tomography, OCT)作为一种非侵入、高分辨率的成像技术,近年来在心脑血管疾病临床中的应用不断拓展。本文系统综述了OCT技术及其探头的发展,深入分析其在脑动脉瘤识别、动脉粥样斑块评估及支架术前规划与术后监测等方面的研究进展,并总结了OCT与人工智能相结合的关键模式与发展趋势。最后,对OCT在未来心脑血管疾病诊疗中的应用前景进行了展望。

       

      Abstract:
      Significance Cardiovascular and cerebrovascular diseases remain leading causes of global mortality and morbidity, imposing a substantial clinical and socioeconomic burden. These diseases require accurate early diagnosis and minimally invasive image-guided intervention. Optical coherence tomography (OCT) is a high-resolution optical imaging modality based on low-coherence interferometry. It provides real-time cross-sectional imaging with micrometer-scale resolution, enabling detailed visualization of vascular microstructures. OCT operates without ionizing radiation and demonstrates strong resistance to metallic artifacts, making it particularly suitable for intravascular applications where stents and calcifications are frequently present. Owing to these advantages, OCT has become an essential tool for lesion characterization and interventional guidance. It enables precise evaluation of atherosclerotic plaques, arterial dissection, aneurysm morphology, stent deployment quality, and post-procedural vascular healing, thereby providing critical microstructural information for precision diagnosis and treatment planning.
      Progress  From a technical perspective, OCT is categorized into time-domain OCT (TD-OCT) and Fourier-domain OCT (FD-OCT) according to signal acquisition and reconstruction strategies. TD-OCT relies on mechanical reference-arm scanning to obtain depth-resolved signals, which limits imaging speed and sensitivity. In contrast, FD-OCT reconstructs depth information through Fourier transformation of spectral interference signals without mechanical delay scanning. This approach significantly improves signal-to-noise ratio, imaging speed, and sensitivity. As a result, FD-OCT has largely replaced TD-OCT in clinical practice and has enabled high-throughput intravascular imaging during percutaneous interventions. Fiber-based endoscopic OCT probes are the core components for intravascular imaging systems. These probes are generally classified into side-view and forward-view configurations based on imaging geometry. Side-view probes are widely used in coronary and cerebrovascular imaging, providing 360-degree circumferential visualization of vessel walls and enabling accurate assessment of lumen morphology and plaque distribution. Continuous advances in microfabrication and optical design have reduced probe diameters to below 0.5 mm, allowing safe navigation in small and tortuous vessels while maintaining imaging stability. Forward-view probes, on the other hand, are more suitable for anatomical navigation and lesion targeting, particularly in complex vascular geometries and preclinical cerebrovascular or gastrointestinal applications where directional imaging is required. In recent years, multimodal OCT probe systems have emerged as an important research direction. These systems integrate OCT with complementary imaging modalities such as ultrasound, photoacoustic imaging, fluorescence lifetime imaging, and near-infrared spectroscopy. Such integration enables simultaneous acquisition of structural, functional, and molecular information, overcoming the intrinsic limitation of OCT in penetration depth and biochemical specificity. Multimodal imaging significantly improves the comprehensive assessment of vulnerable plaques by combining morphological features with compositional and functional biomarkers.
      Clinically, OCT has been widely adopted in cardiovascular and cerebrovascular diseases. It provides high-resolution visualization of plaque microstructures, including lipid-rich necrotic cores, fibrous caps, calcification patterns, microvessels, and intraluminal thrombi. These features are essential for distinguishing stable plaques from vulnerable plaques that are prone to rupture. In coronary artery intervention, OCT plays a critical role in stent optimization. It allows quantitative assessment of stent expansion, malapposition, under-expansion, edge dissection, tissue prolapse, and neointimal hyperplasia. These measurements directly inform procedural decisions such as balloon sizing, post-dilation strategy, and implantation optimization, ultimately improving procedural safety and long-term outcomes. In cerebrovascular applications, OCT has demonstrated increasing clinical value in aneurysm evaluation, intracranial atherosclerosis assessment, and flow-diverter treatment monitoring. It enables detailed visualization of aneurysm wall microstructure, evaluation of stent apposition in tortuous intracranial vessels, and assessment of endothelial healing after endovascular treatment. These capabilities provide critical information for rupture risk stratification and postoperative outcome prediction, which are difficult to achieve with conventional imaging modalities.
      Conclusions Recent OCT systems show a clear evolution toward platform integration, multimodal fusion, and artificial intelligence (AI)-assisted analysis. Commercial systems developed by major manufacturers such as Abbott, Terumo, and Zeiss support rapid pullback imaging, automated lumen and stent analysis, and real-time image enhancement. These improvements significantly increase procedural efficiency and reduce operator dependence. Meanwhile, AI-driven OCT analysis has developed rapidly. Deep learning models based on convolutional neural networks and transformer architectures have been applied to vessel segmentation, plaque classification, calcification quantification, stent detection, and lesion identification. These models enable automated pixel-level segmentation and frame-level classification, improving both diagnostic accuracy and inter-observer consistency. Furthermore, AI systems facilitate large-scale quantitative analysis, enabling new opportunities for imaging biomarkers and outcome prediction models.
      Prospects Despite these advances, several challenges remain in OCT technology and clinical translation. Limited imaging penetration restricts visualization of deep vessel wall structures. Metal-induced shadowing still affects quantitative evaluation in heavily calcified lesions. In addition, variability in imaging protocols and lack of standardized datasets hinder large-scale clinical validation of AI models. Interpretability and generalization of AI algorithms across institutions also remain important issues for clinical adoption. OCT has become an indispensable high-resolution intravascular imaging technology in cardiovascular and cerebrovascular precision medicine. Future development will focus on ultra-miniaturized probes with diameters below 0.3 mm, faster imaging systems with higher frame rates, deeper penetration imaging through optimized light sources, and improved multimodal real-time fusion platforms. Advances in artifact suppression techniques will further enhance image quality in complex vascular environments. In parallel, interpretable and robust AI models with strong cross-center generalization capability will promote the transformation of OCT from an image interpretation tool into an integrated clinical decision-support system. With continuous technological innovation and clinical translation, OCT is expected to significantly improve early detection of vulnerable plaques, refine interventional strategies, and reduce adverse cardiovascular and cerebrovascular events. These developments will ultimately support the advancement of precision and personalized medicine in vascular diseases.