Early detection of lung cancer is the key to improving treatment and prognosis of this disease, and the advent of advances in computed tomography (CT) imaging and national screening programs have improved the detection rate of very small pulmonary lesions. As such, the management of this sub-centimetric and often sub-solid lesions has become quite challenging for clinicians, especially for choosing the most suitable diagnostic method. In clinical practice, to fulfill this diagnostic yield, transthoracic needle biopsy (TTNB) is often the first choice especially for peripheral nodules. For lesions for which TTNB could present technical difficulties or failed, other diagnostic strategies are needed. In this case, video-assisted thoracic surgery (VATS) is the gold standard to reach the diagnosis of lung nodules suspect of being malignant. Nonetheless it's often not easy the identification of such lesions during VATS because of their little dimensions, non-firm consistency, deep localization. In literature various marking techniques have been described, in order to improve intraoperative nodules detection and to reduce conversion rate to thoracotomy: CT-guided hookwire positioning, methylene blue staining, intra-operative ultrasound and electromagnetic navigation bronchoscopy are the most used. The scientific evidence on this matter is weak because there are no randomized clinical trials but only case series on single techniques with no comparison on efficacy, so there are no guidelines to refer. From this standing, in this article we conducted a narrative review of the existing literature on the subject, with the aim of outlining a framework as complete as possible. We analyzed strengths and weaknesses of the main techniques reported, so as to allow the clinician to orient himself with greater ease.
Keywords: Indeterminate pulmonary nodule; computed tomography-guided localization; intraoperative lung nodule identification; pulmonary nodule management; video-assisted thoracic surgery (VATS).
2021 Journal of Thoracic Disease. All rights reserved.