โก Quick Summary
This narrative review highlights the transformative role of artificial intelligence (AI) in the treatment of adult spinal deformity (ASD), showcasing its potential to enhance surgical planning, predict outcomes, and personalize patient care. The findings suggest that AI tools can significantly improve accuracy and efficiency in ASD surgery, ultimately leading to better patient outcomes.
๐ Key Details
- ๐ Focus Areas: Preoperative decision-making, intraoperative execution, postoperative care
- ๐งฉ Technologies Reviewed: Predictive analytics, automated radiographic assessment, intraoperative navigation
- ๐ Key Findings: AI tools improve prediction of complications, length of stay, and functional outcomes
- ๐ค AI Applications: Personalized instrumentation, AR/VR platforms, AI-enhanced robotics
๐ Key Takeaways
- ๐ AI is enhancing decision-making in ASD surgery by providing data-driven insights.
- ๐ Machine learning algorithms outperform traditional models in predicting surgical outcomes.
- ๐ Automated radiographic platforms ensure reliable spinal alignment measurements.
- ๐ ๏ธ Personalized instrumentation leads to improved alignment fidelity during surgery.
- ๐ Intraoperative AR/VR platforms help standardize surgical execution and reduce variability.
- ๐ก Ongoing validation is essential for the widespread adoption of AI in clinical practice.
- ๐ฅ Current evidence supports the clinical utility of AI-assisted strategies in improving surgical safety.
- ๐ This review emphasizes the growing potential of AI as a cornerstone of precision spine surgery.
๐ Background
Adult spinal deformity (ASD) surgery is known for its complexity and high complication rates, presenting significant challenges in spine care. Traditional approaches often lead to variable outcomes, necessitating innovative solutions. The integration of artificial intelligence into surgical workflows offers a promising avenue to enhance planning, prediction, and personalization, ultimately improving patient care.
๐๏ธ Study
This narrative review synthesizes current literature and technologies related to the implementation of AI in ASD surgery. The authors conducted a comprehensive analysis focusing on various aspects, including predictive analytics, automated assessments, and patient engagement strategies. A representative case example of AI-assisted deformity correction is also presented to illustrate practical applications in clinical settings.
๐ Results
The review reveals that AI tools have shown strong potential in enhancing accuracy and efficiency across multiple domains of ASD surgery. Notably, machine learning algorithms have been found to outperform traditional statistical models in predicting complications, length of hospital stay, and functional outcomes. Additionally, automated radiographic platforms have demonstrated reliability in reproducing spinal alignment measurements, which supports effective surgical planning.
๐ Impact and Implications
The findings from this review indicate that AI is redefining the landscape of ASD surgery. By enhancing decision-making processes and reducing variability, AI enables a more personalized and data-driven approach to patient care. As the integration of AI technologies continues to evolve, we can anticipate significant improvements in surgical outcomes and patient safety, paving the way for a new era in spine surgery.
๐ฎ Conclusion
This review underscores the incredible potential of artificial intelligence in transforming ASD surgery. By improving decision-making, enhancing surgical precision, and enabling personalized care, AI is set to become a cornerstone of precision spine surgery. Continued research and validation are essential for the successful integration of these technologies into clinical practice, promising a brighter future for patients undergoing spinal surgery.
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Implementation of artificial intelligence (AI) in ASD treatment.
Abstract
BACKGROUND: Adult spinal deformity (ASD) surgery remains one of the most complex and complication-prone areas of spine care, with significant variability in outcomes and high complication rates. Recent advances in artificial intelligence (AI) have shown to be promising tools to address these challenges by improving planning, prediction, and personalization. This narrative review explores the role of AI across the surgical workflow for ASD, from preoperative decision-making to intraoperative execution and postoperative care.
METHODS: We conducted a comprehensive narrative review of current literature and technologies related to AI in ASD surgery. Focus areas included evidence synthesis, predictive analytics, automated radiographic assessment, intraoperative navigation, patient-specific implants, and digital patient engagement. We also present a representative case example of AI-assisted deformity correction to illustrate practical clinical application.
RESULTS: AI tools have demonstrated strong potential in improving accuracy and efficiency across various domains. Machine learning algorithms outperform traditional statistical models in predicting complications, length of stay, and functional outcomes. Automated radiographic platforms reliably reproduce spinal alignment measurements and support surgical planning. Personalized instrumentation has been associated with improved alignment fidelity. Lastly, Intraoperative AR/VR platforms and AI-enhanced robotics are helping to standardize execution and reduce variability.
CONCLUSIONS: AI is redefining the landscape of ASD surgery through its ability to enhance decision-making, reduce variability, and enable personalized, data-driven care. While widespread adoption requires ongoing validation and integration, current evidence supports the clinical utility of AI-assisted strategies in improving alignment outcomes and surgical safety. This review highlights the growing potential of AI to serve as a cornerstone of precision spine surgery.
Author: [‘Chatzis KD’, ‘Tretiakov P’, ‘Passias PG’]
Journal: N Am Spine Soc J
Citation: Chatzis KD, et al. Implementation of artificial intelligence (AI) in ASD treatment. Implementation of artificial intelligence (AI) in ASD treatment. 2025; 24:100787. doi: 10.1016/j.xnsj.2025.100787