Subsequent to the widespread use of multidetector computed tomography (MDCT) and the growing interest in lung cancer screening, small pulmonary nodules are more frequently detected. Moreover, the global disease burden of lung cancer is on the rise [
1]. A solitary pulmonary nodule (SPN) is defined as a rounded opacity in the lung, well or poorly defined, measuring up to 3 cm in diameter [
2]. The differential diagnosis for SPNs is extremely broad, including both benign and malignant causes. Recognition of early lung cancers is vital since stage at diagnosis is crucial for prognosis. Estimation of the probability of malignancy is a diagnostic challenge, but is crucial for follow-up or further work-up. First step in this assessment is an evaluation of the clinical parameters such as signs and symptoms, patient age, smoking history, exposure, family history, associated lung diseases, and previous clinical history [
3]. Second step is the imaging evaluation. Size, growth, and doubling time are key factors in assessing the malignant potential of a nodule. The likelihood of malignancy positively correlates with nodule diameter: as the diameter increases, so does the likelihood of malignancy. Malignancy, however, is not excluded in small nodules. Lack of growth does not always indicate benignity since adenocarcinomas (in particular those presenting as subsolid nodule) can be slow-growing tumours. Moreover some benign lesions, e.g. intrapulmonary lymph nodes, may show growth and have a volume doubling time in the range of malignant nodules [
4]. Although imaging features of benign and malignant nodules show overlap, careful evaluation of morphologic features is an essential element of pulmonary nodule assessment. Nodule morphology should be evaluated on contiguous thin sections in axial, sagittal, and coronal planes. Investigation of nodule metabolism with 18F–fluorodeoxyglucose (FDG) positron emission tomography (PET) can have an additional value, but one needs to keep in mind that small nodules (< 8 mm), adenocarcinoma precursors and invasive adenocarcinomas with lepidic growth, as well as carcinoids can show low or no uptake [
5]. In these lesions morphological assessment is crucial in order not to delay diagnosis. A recent study by Chung et al. [
6] on a large set of subsolid nodules from lung cancer screening trials, showed that careful assessment of morphology in subsolid nodules could tremendously increase identification of malignant lesions. This result emphasises the importance of morphology as additional parameter to size and growth in regard to assessing likelihood of malignancy.
Several quantitative prediction models have been developed to assist in assessing the likelihood of malignancy. Different models exist for screen-detected nodules and nodules detected in non-screening populations, including models from Gurney [
3,
7], the Mayo Clinic [
8], Herder [
9], Veterans Association [
10], Peking University People’s Hospital (PKUPH) [
11], Brock University [
12], and Bayesian Malignancy Calculator by Soardi [
13]. Whereas in more recent nodule calculators new features are taken into account (e.g. uptake on PET, contrast enhancement, volume doubling time), the number of morphologic features remains limited. Moreover variability among the features exists between different models. Likelihood of malignancy and odds ratios from these nodule calculators are summarised in Table
1.
Table 1
Likelihood and odds ratios for malignancy regarding morphological features in solitary pulmonary nodules
Population | Non-screen | Non-screen | Non-screen | Screen-detected | Non-screen |
Number of nodules studied | Literature review | 629 | 371 | 12,029 | 343 |
Morphological features |
Subsolid | | | | No spiculation Ground glass: OR 0.74 (CI 0.40–1.35) Part-solid: OR 1.40 (CI 0.72–2.74) With Spiculation Ground glass: OR 0.88 (CI 0.48–1.62) Part-solid: OR 1.46 (CI 0.74–2.88) | |
Smooth | LHR 0.30 (CI 0.20–0.41) | | OR 0.245 (CI 0.133–0.451) | | LHR 0.293 (smooth, elliptical, polygonal) |
Lobulated | LHR 0.74 (CI 0.64–0.84) | OR 2.520 (CI 1.423–4.433) | | | LHR 0.735 (minimally lobulated) LHR 1.888 (deeply lobulated) |
Spiculated | LHR 5.54 (CI 5.46–5.63) | OR 5.789 (CI 3.332–10.057) | OR 2.088 (CI 1.055–4.135) | OR 2.17 (CI 1.16–4.05) | LHR 7.884 |
Calcification | LHR 0.01 (CI 0–0.03) | | OR 0.199 (CI 0.067–0.587) | | |
Cavitation | | OR 3.05 (CI 1.078–8.646) | | | |
This pictorial review focuses on the morphologic evaluation of the solitary pulmonary nodule, with a 5-step approach and evaluation of 15 features (Table
2). Although these morphologic features are discussed one at a time, in practice a single nodule can show a variety of different features and combination of features is often even more powerful.
Table 2
Step-wise approach for morphological assessment of the solitary pulmonary nodule
Density | 1. Solid 2. Subsolid |
Shape | 3. Round or oval 4. Triangular or polygonal |
Margins | 5. Smooth 6. Lobulated 7. Spiculated |
Internal characteristics | 8. Fat 9. Calcification 10. Cavitation |
Complex findings | 11. Pleural retraction 12. Air bronchogram 13. Bubble like lucencies 14. Cystic Airspace 15. Vascular convergence |