Navigation of tumor location and intersegmental planes utilizing mixed reality in video-assisted thoracic surgery for non-small cell lung cancer: a case of right S2 segmentectomy

Background: With the increasing detection of small lung cancers using computed tomography (CT), ensuring precise tumor margins in sublobar resections has gained prominence. Although conventional tumor marking methods have demonstrated efficacy, they may carry inherent risks or lack the desired level of accuracy. In this paper, we present an innovative approach utilizing mixed reality (MR) to enhance lung cancer segmentectomy. Case Description: A man in his 70s was diagnosed with lung adenocarcinoma, presenting as a 2.1 cm pure ground-glass nodule (GGN) in segment 2 (S2) of the right upper lobe, detected on routine followup CT scans at a local clinic for adrenal insufficiency. We utilized MR to facilitate video-assisted thoracic surgery (VATS) for a right S2 segmentectomy. This approach involves superimposing a dynamic threedimensional (3D) lung model onto the actual surgical field, enabling the surgical team to precisely locate the tumor and delineate segmental boundaries. In contrast to the conventional indocyanine green (ICG) method, which often yielded ambiguous delineation, our MR-assisted approach consistently demonstrated clear accuracy. Notably, certain challenges, such as achieving optimal alignment of the 3D model, were encountered. Nevertheless, the undeniable advantages of MR are evident throughout the procedure. Conclusions: We herein reported the pioneering use of MR-assisted segmentectomy for lung cancer. This novel approach shows promise in enhancing precision, safety, and innovation in thoracic surgery by overcoming conventional limitations.