The introduction of robotic-assisted techniques in thoracic surgery has dramatically transformed the paradigm of personalized treatment methodologies for early-stage lung cancer. This method allows for precise surgery while ensuring oncological radicality with less invasiveness, which is crucial for preserving functionality, especially since each patient presents a unique medical condition. Harmonizing these advanced technologies with the principles of personalized medicine has the potential to revolutionize the treatment of early-stage lung cancer and set new standards for patient care and prognosis.

The goal of this Research Topic is to dissect the integration of robotic-assisted techniques within personalized medicine for early-stage lung cancer, which focuses on improving patient-specific outcomes, minimizing surgical impact, and optimizing recovery. We aim to uncover how these methods can be tailored to individual patient profiles, thereby enhancing surgical precision and outcomes. The objective extends to understanding the potential of robotic surgery in delivering personalized care, with a focus on technological innovation, adaptability in surgical practice, and improved prognostic models for early-stage lung cancer patients.

Specifically, submissions including but not limited to the following sub-topics are highly welcome:
• Advances in robotic technology for complex thoracic surgery
• Comparative outcomes of robotic vs. traditional video-assisted thoracic surgery
• Three-dimensional image simulation for robotic-assisted thoracic surgery (RATS)
• Single port RATS
• Impact of recent clinical trials (e.g., JCOG0802) on RATS
• Single-setting robotic lung nodule diagnosis and resection
• Tumor localization for robotic lung resection
• Enhanced recovery after surgery (ERAS) for RATS
• Training protocols for RATS
• Management for complications during RATS
• Economic analysis of RATS

Please note: Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

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Frontiers in Oncology

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