Subsolid pulmonary nodules: why not “watch and wait”?

Subsolid pulmonary nodules include both pure ground-glass nodules (GGNs) and part-solid (mixed) nodules (PSNs). Incidence of subsolid pulmonary nodules has increased due to improved computed tomography (CT) technology, implementation of lung cancer screening programs with low-dose CT (LDCT), and expanded use of CT. We now know that the greater the solid component of a subsolid pulmonary nodule, the greater the risk of malignancy and metastatic potential (1,2), the latter being practically negligible in pure GGNs (3). This editorial aims to address specific aspects on diagnostic and therapeutic management of subsolid pulmonary nodules, recognizing that such management is controversial and depends on different variables.

PSNs are lesions with recognized aggressiveness and metastatic potential, especially when their solid component is larger than 5–6 mm (4). In general, these lesions are managed more aggressively, both from a diagnostic and therapeutic perspective (5). Initially, percutaneous CT-guided biopsy is not recommended since the vast majority are adenocarcinomas, there is a significant sampling error risk when attempting percutaneous biopsies (given the difficulty in targeting both solid/invasive and ground-glass/non-invasive components), and that certain pathologic diagnoses (such as adenocarcinoma in situ, minimally invasive adenocarcinoma…) cannot be made in small specimens obtained percutaneously (6-9). In light of this, many institutions prefer not to subject patients to the unnecessary risk of a preoperative percutaneous biopsy. Therefore, surgical biopsy (which can also serve as a therapeutic procedure) is preferred.

Management of pure GGNs and PSNs with a small solid component (less than 5–6 mm) is more variable and controversial (5). Although some clinicians prefer to use an aggressive/invasive strategy in this setting as well, a more thoughtful “watch and wait” approach (always considering different factors beforehand) may be feasible due to their indolent course and good prognosis (3,10-13). This latter approach is partly justified given the reported 5-year-survival rate of 100% in surgically resected clinical N0 non-small cell lung cancer (NSCLC) pure GGNs and of 97.6% in PSN subcentimeter NSCLC (14).

Some current pulmonary nodule management guidelines in lung cancer screening programs (such as the latest version of Lung-RADS^®) (15) are recognizing that the persistence or even the slow growth of a pure GGN can be managed conservatively (“watch and wait”) and categorized as “clinical-radiologically benign” lesions. Lung-RADS “Category 2” nodules correspond to “benign” findings (based on imaging features or indolent behaviour, not based on pathologic characteristics), despite the fact that they most likely represent malignant (adenocarcinoma in situ or minimally invasive adenocarcinoma) or premalignant (atypical adenomatous hyperplasia) lesions. This concept of “clinical-radiological benignity” in a lung cancer screening scenario is emerging, represents a paradigm shift regarding “malignancy/benignity” categorization of lung nodules, and is being increasingly taken into account by lung nodule management guidelines. If all Lung-RADS category 2 nodules are aggressively managed, there is a high risk of increasing the rate of overdiagnosis (i.e., resecting indolent tumours with no metastatic potential that would never lead to the death of the patient). We should bear in mind that both surgery (16) and nodule marking procedures [with wire-hooks (17), coils (18), dye (19), radioactive materials (20)…] are not without risk.

When deciding the diagnostic and therapeutic strategy of pure GGNs and PSNs, it is crucial to take into account the patient’s age and comorbidities. One similar-looking GGN in two different individuals can be managed differently (i.e., surgically in one case and conservatively in the other case), being both approaches appropriate. In addition, the smoking history and the presence of multifocal GGNs are also factors that can influence their management, and may force physicians to be more cautious due to the likely probability of new pulmonary lesions appearing in subsequent CTs (thus requiring multiple lung resections). In any case, patients’ preferences need to be considered and a consensual decision should be made after all risks and benefits of each strategy have been explained and discussed.

A tool that is currently available and is very helpful in assessing the size and growth of the solid component is volumetry (consisting of 3D volumetric measurements of lung nodules obtained with specific software). Nodule size and interval growth are more objectively and accurately assessed with volumetry than on 2D measurements (21). The evidence supporting clinical use of volumetry is expanding, being currently incorporated in lung cancer screening nodule management algorithms [recent versions Lung-RADS (15), British Thoracic Society guidelines (22)…].

However, future directions run toward artificial intelligence and radiomics. Several new tools are being developed in order to assess the lung cancer risk of patients with lung nodules on LDCT scans and even in patients without lung nodules. Ardila et al. developed a cancer detection algorithm that identifies pulmonary nodules, processes the region surrounding them using deep learning, and accurately predicts lung cancer within 1 and 2 years (23). More recently, another deep learning algorithm that predicts lung cancer risk up to 6 years from a single LDCT scan without demographic and clinical data and without requiring any radiologists to annotate areas of interest has been published (24). This algorithm reached area under the receiver operating characteristic curves (AUCs) of 0.90 in predicting cancer within 1 year, although results will require confirmation in prospective clinical trials. There is no doubt that these accurate tools will help clinicians assess the risk of screening-detected or incidental GGNs, decide whether follow-up or lung resection is optimal, minimize invasive procedures of nodules that are at low risk, and probably help determine optimal timing for surgery.

Just as the treatment of lung cancer has been diversified in the last decade (immune checkpoint inhibitors, targeted therapies, neoadjuvant treatment in early stages…), the management of subsolid nodules should not be rigid and should take into account several clinical and technical variables, as well as patients’ preferences. These factors should certainly be discussed at a multidisciplinary tumour board. In large academic hospitals, with a high volume of lung nodules, and specially where lung cancer screening with LDCT is performed, the implementation of a specific board for pulmonary nodules (independent of the thoracic tumour board) should be recommended.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Translational Medicine. The article did not undergo external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-23-1794/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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References

1. Sun F, Huang Y, Yang X, et al. Solid component ratio influences prognosis of GGO-featured IA stage invasive lung adenocarcinoma. Cancer Imaging 2020;20:87. [Crossref] [PubMed]
2. Ichinose J, Kohno T, Fujimori S, et al. Invasiveness and malignant potential of pulmonary lesions presenting as pure ground-glass opacities. Ann Thorac Cardiovasc Surg 2014;20:347-52. [Crossref] [PubMed]
3. Lee SW, Leem CS, Kim TJ, et al. The long-term course of ground-glass opacities detected on thin-section computed tomography. Respir Med 2013;107:904-10. [Crossref] [PubMed]
4. MacMahon H, Naidich DP, Goo JM, et al. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017. Radiology 2017;284:228-43. [Crossref] [PubMed]
5. Kim BG, Um SW. A narrative review of the clinical approach to subsolid pulmonary nodules. Ann Transl Med 2023;11:217. [Crossref] [PubMed]
6. Shimizu K, Ikeda N, Tsuboi M, et al. Percutaneous CT-guided fine needle aspiration for lung cancer smaller than 2 cm and revealed by ground-glass opacity at CT. Lung Cancer 2006;51:173-9. [Crossref] [PubMed]
7. Inoue D, Gobara H, Hiraki T, et al. CT fluoroscopy-guided cutting needle biopsy of focal pure ground-glass opacity lung lesions: diagnostic yield in 83 lesions. Eur J Radiol 2012;81:354-9. [Crossref] [PubMed]
8. Kim JI, Park CM, Kim H, et al. Non-specific benign pathological results on transthoracic core-needle biopsy: how to differentiate false-negatives? Eur Radiol 2017;27:3888-95. [Crossref] [PubMed]
9. Borczuk AC. Assessment of invasion in lung adenocarcinoma classification, including adenocarcinoma in situ and minimally invasive adenocarcinoma. Mod Pathol 2012;25:S1-10. [Crossref] [PubMed]
10. Sawada S, Yamashita N, Sugimoto R, et al. Long-term Outcomes of Patients With Ground-Glass Opacities Detected Using CT Scanning. Chest 2017;151:308-15. [Crossref] [PubMed]
11. Kakinuma R, Noguchi M, Ashizawa K, et al. Natural History of Pulmonary Subsolid Nodules: A Prospective Multicenter Study. J Thorac Oncol 2016;11:1012-28. [Crossref] [PubMed]
12. Oh JY, Kwon SY, Yoon HI, et al. Clinical significance of a solitary ground-glass opacity (GGO) lesion of the lung detected by chest CT. Lung Cancer 2007;55:67-73. [Crossref] [PubMed]
13. Son JY, Lee HY, Lee KS, et al. Quantitative CT analysis of pulmonary ground-glass opacity nodules for the distinction of invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma. PLoS One 2014;9:e104066. [Crossref] [PubMed]
14. Hattori A, Matsunaga T, Hayashi T, et al. Prognostic Impact of the Findings on Thin-Section Computed Tomography in Patients with Subcentimeter Non-Small Cell Lung Cancer. J Thorac Oncol 2017;12:954-62. [Crossref] [PubMed]
15. American College of Radiology. Lung-RADS. [cited 2023 Jul 30]. Available online: https://www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/Lung-RADS-2022.pdf
16. Aokage K, Suzuki K, Saji H, et al. Segmentectomy for ground-glass-dominant lung cancer with a tumour diameter of 3 cm or less including ground-glass opacity (JCOG1211): a multicentre, single-arm, confirmatory, phase 3 trial. Lancet Respir Med 2023;11:540-9. [Crossref] [PubMed]
17. Miyoshi K, Toyooka S, Gobara H, et al. Clinical outcomes of short hook wire and suture marking system in thoracoscopic resection for pulmonary nodules. Eur J Cardiothorac Surg 2009;36:378-82. [Crossref] [PubMed]
18. Bommart S, Bourdin A, Marin G, et al. Impact of preoperative marking coils on surgical and pathologic management of impalpable lung nodules. Ann Thorac Surg 2014;97:414-8. [Crossref] [PubMed]
19. Geraci TC, Ferrari-Light D, Kent A, et al. Technique, Outcomes With Navigational Bronchoscopy Using Indocyanine Green for Robotic Segmentectomy. Ann Thorac Surg 2019;108:363-9. [Crossref] [PubMed]
20. Fra-Fernández S, Gorospe-Sarasúa L, Ajuria-Illarramendi O, et al. Preoperative radio-guided localization of lung nodules with I-125 seeds: experience with 32 patients at a single institution. Interact Cardiovasc Thorac Surg 2022;34:91-8. [Crossref] [PubMed]
21. Nair A, Dyer DS, Heuvelmans MA, et al. Contextualizing the Role of Volumetric Analysis in Pulmonary Nodule Assessment: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2023;220:314-29. [Crossref] [PubMed]
22. Callister ME, Baldwin DR, Akram AR, et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 2015;70:ii1-ii54. [Crossref] [PubMed]
23. Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med 2019;25:954-61. [Crossref] [PubMed]
24. Mikhael PG, Wohlwend J, Yala A, et al. Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography. J Clin Oncol 2023;41:2191-200. [Crossref] [PubMed]