Surgical resection of early cancer provides the best likelihood for cure. Therefore, the challenge surgeons are faced with is to diagnose cancer early enough to allow a safe and complete surgical resection. In patients with lung cancer, moreover, accurate preoperative staging is as important as an early diagnosis because treatment options and prognosis differ considerably by the stage of the disease. Today, several different noninvasive imaging techniques are available for preoperative staging of early lung cancer, each with advantages and disadvantages. For instance, chest computed tomography (CT) can provide superb anatomical details (high sensitivity) but has a low specificity in identifying malignant lesions. However, positron emission tomography (PET), especially when combined with CT, has a much higher sensitivity and specificity. Nevertheless, according to published guidelines, abnormal findings should always be confirmed by tissue diagnosis to ensure correct preoperative staging.1 However, techniques of tissue diagnosis are characterized by a wide range of accuracy and morbidity. On one end of the range, the gold standard of nodal dissection has high yield and invasiveness, whereas, at the other end of the range, needle-sampling techniques have minimal invasiveness but have been shown to have a low negative predictive value, which could expose a patient to a potentially nontherapeutic resection.2,3 Hence, it seems worth exploring potential research avenues to better delineate the role of newer techniques, such as endobronchial ultrasonography-guided transbronchial needle aspiration (EBUS-TBNA), in the staging algorithm for patients with lung cancer, to exploit the advantages of their minimal invasiveness, while determining their potential negative predictive value.