Masaki Goto

Papers

Total Citations

H-Index

About

Masaki Goto is a pioneering thoracic surgeon whose work centers on advancing minimally invasive lung cancer surgery, with a particular focus on robotic-assisted techniques and intraoperative imaging. His most impactful research addresses the critical learning curve for robotic lobectomy, demonstrating that certified thoracic surgeons can safely transition to robot-assisted thoracic surgery (RATS) with outcomes comparable to conventional video-assisted thoracic surgery (VATS). This work, published in 2021 and garnering 8 citations, provides essential guidance for surgical teams adopting robotic platforms. Dr. Goto has also made notable contributions to fluorescence-guided thoracic surgery, tackling the growing challenge of achieving adequate surgical margins during sublobar resections for small pulmonary nodules. His 2021 paper on this subject, with 7 citations, highlights innovative solutions to ensure oncologic precision while preserving lung tissue. By systematically comparing RATS and VATS learning curves and advancing real-time tumor visualization techniques, Dr. Goto is helping shape the future of precision thoracic oncology. His research directly addresses the practical challenges faced by surgeons transitioning to robotic platforms, making his work invaluable for both established practitioners and trainees entering the field of minimally invasive thoracic surgery.