Management of incidental nodules in lung cancer screening: ready for prime-time?

Abstract

Lung cancer is the leading cause of cancer-related mortality. Two independent trials from the USA and the Netherlands and Belgium demonstrated that annual low-dose computed tomography (LDCT) screening reduced mortality by 20% and 26%, respectively [1–3]. LDCT is therefore widely accepted as the preferred method for detecting pulmonary nodules, but raises an important clinical challenge concerning nodule evaluation and patient management [4–7]. Current pulmonary nodule evaluation and clinical management starts by estimating the probability of cancer (pCA) based on clinical (age, symptoms, smoking history, performance status, associated lung diseases, family history and previous clinical history) and radiological (size, growth and morphology) parameters, and takes into account the patient's preferences. Certain lung nodule features suggest a high likelihood of malignancy (such as spiculation, lobulation and pleural retraction) whereas others favour a benign aetiology (internal fat, calcifications and round shape) [8–10]. Furthermore, the likelihood of malignancy and nodule diameter are positively correlated. However, nodule size is not a reliable standalone malignancy biomarker as slow growing adenocarcinoma nodules will appear small, and benign lesions may show growth and volume doubling time in the range of malignant nodules [11]. Hence, the assessment of pulmonary nodules remains a diagnostic challenge. Cohorts with low to moderate malignancy risk lung nodules pose the clinical dilemma between invasive procedures and serial surveillance. A score that could reliably predict pulmonary nodule aetiology would improve patient management by minimising the number of invasive procedures and reducing healthcare costs and patients' discomfort [12]. To this end, patients with a probably benign nodule could be managed by serial surveillance avoiding invasive tests, whereas those patients with a probably malignant nodule could be stratified to the most appropriate treatment more quickly [13]. These authors previously developed a biomarker-driven lung nodule classifier based upon 222 subjects [14]. In this study, Silvestri et al. [15]. designed and implemented a multicentre, double-blinded, prospective, observational study with a retrospective evaluation to validate the accuracy of this lung nodule classifier.

Solitary Pulmonary Nodule: Is It Benign or Malignant?

“…Spiculated nodule margins have consistently been linked to lung cancer risk. 22 Lung cancer has been associated with lobulated margins, as in Figure 2 Fat in the solitary pulmonary nodule indicates benign lesions like pulmonary hamartomas, lipoid pneumonia, and lipomas. 18,23 CT scans show fat in 50% of pulmonary hamartomas.…”