Differentiation of persistent pulmonary subsolid nodules with a solid component smaller than 6 mm: to be invasive adenocarcinoma or not to be?

J Thorac Dis 2020;12(5):1754-1757 | http://dx.doi. org/10.21037/jtd-20-1645 As the utilization of low-dose chest computed tomography (LDCT) has increased in daily clinical practice, many physicians and radiologists often encounter persistent pulmonary subsolid nodules (SSNs) (1,2). Extensive research has explored the clinical, radiological, and pathological characteristics of SSNs, significantly advancing our knowledge of this category of pulmonary nodules (3-5). As a prime theme on pulmonary SSNs, accurately differentiating pulmonary invasive adenocarcinomas (IACs) from minimally invasive adenocarcinoma (MIA)/preinvasive lesions using CT examinations is of vital importance, since this distinction can determine the management of patients with those nodules. Specifically, early-stage lung cancers, which pathologically represent MIA/preinvasive lesions and radiologically manifest as SSNs with a solid component <6 mm in most cases, may be removed through limited resection instead of lobectomy, which is the surgical standard for lung cancer (6,7). Furthermore, the policy of conservative management with regular CT followup as long as SSNs remain stable, with surgical resection performed if they grow, is increasingly accepted in medical communities (3,8,9). The key issue in this management strategy is that only highly invasive lesions such as IACs should be surgically resected, while MIA/preinvasive lesions may be managed through follow-up examinations, eventually improving patients’ prognosis and avoiding unnecessary surgery (3,9). However, it is challenging to distinguish between IACs and MIA/preinvasive lesions through imaging studies alone because substantial overlap exists between these two categories (10,11). A large body of research has explored this topic, using a variety of analytic methods including qualitative and quantitative assessments (12-14), radiomics-based assessments (15,16), and in recent years, deep-learning algorithms (17,18). Recently, Qi et al. published an interesting study on the differentiation of IACs from MIAs/preinvasive lesions in SSNs with a solid component <6 mm, including pure ground-glass nodules (PGGNs) and part-solid nodules (PSNs), using both qualitative and quantitative imaging features on CT (19). They evaluated 316 surgically-resected SSNs (260 PGGNs, 47 PSNs with a solid component < 6 mm, and 9 SSNs with cystic airspaces) from 287 patients. Excluding the SSNs with cystic airspaces, 307 SSNs were dichotomized according to whether they were IACs (n=195) or MIA/preinvasive lesions (n=112). The authors found that the mass of SSNs was the only significant feature differentiating IACs from MIA/preinvasive lesions, and 283.2 mg was the optimal cutoff value for distinguishing IACs from MIA/preinvasive lesions. The result that the mass of SSNs was the only significant factor differentiating IACs from MIA/preinvasive lesions (19) is in line with previous studies (20,21). However, there are substantial differences in the optimal cutoff value among those studies (283.2 mg in the study of Qi et al. vs. 386 mg Editorial