摘要

Objectives: 1. Describe the emergence of real-time imaging in energy-based device (EBD) treatments with microfocused ultrasound as the original paradigm. 2. Explain the clinical rationale for integrating ultrasound imaging with RF microneedling, 3. Evaluate emerging evidence supporting ultrasound-guided EBD workflows. 4. Formulate a framework for implementing imaging-guided protocols as a standard of care. 5. Discuss the potential of AI-enhanced imaging systems to standardize EBD safety and outcomes. Introduction: Energy-based devices (EBD) have transformed aesthetic medicine, yet complications continue to emerge as treatments become more powerful, more diverse, and more widely adopted. Microfocused ultrasound was the first EBD platform to integrate real-time imaging, establishing a new treatment paradigm to visualize tissue planes and treatment depth. This foundational concept has catalyzed a broader movement toward imaging-assisted procedures across the aesthetic field. Recent technological advances, including in radiofrequency microneedling, have renewed interest in precision targeting. Materials / method: As global utilization has surged, so too has scrutiny, exemplified by recent safety advisories in the United States, highlighting the risk of off-target thermal injury. These concerns underscore a critical need to improve procedural safety through better visualization, device-tissue matching, and operator guidance. Integrating ultrasound imaging with RF microneedling represents a natural next step, enabling practitioners to confirm needle depth, avoid neurovascular anatomy, and personalize energy delivery based on real-time tissue assessment. Results: This presentation will examine the scientific rationale, evolving evidence base and future clinical implications of ultrasound-guided EBD. By exploring innovations, challenges and emerging AI-driven solutions, we will examine a framework through which imaging guidance may become the new standard of care for safe, ethical and effective aesthetic device therapy. Conclusion: Looking ahead, machine learning and AI-augmented imaging hold the potential to redefine how lasers and EBD interface with human tissue. Automated structure recognition, real-time safety alerts and intelligent treatment-planning overlays may soon support clinicians in achieving safer, more consistent outcomes. Combined with standardized imaging-guided protocols, these tools could elevate both ethical practice and procedural efficacy, ultimately reducing variability in operator performance.