Nomogram based on clinical characteristics and radiological features for the preoperative prediction of spread through air spaces in patients with clinical stage IA non-small cell lung cancer: a multicenter study

Abstract

Purpose: To investigate the value of clinical characteristics and radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC).

Methods: A total of 336 patients with NSCLC from our hospital were randomly divided into two groups, i.e., the training cohort (n = 236) and the internal validation cohort (n = 100) (7:3 ratio). Furthermore, 69 patients from two other hospitals were collected as the external validation cohort. Eight clinical patient characteristics were recorded, and 20 tumor radiological features were quantitatively measured and qualitatively analyzed. In the training cohort, the differences in clinical characteristics and radiological features were compared using univariate and multivariate analysis. A nomogram was created, and the predictive efficacy of the model was evaluated in the validation cohorts. The receiver operating characteristic curve and area under the curve (AUC) value were used to evaluate the discriminative ability of the model. In addition, the Hosmer-Lemeshow test and calibration curve were used to evaluate the goodness-of-fit of the model, and the decision curve was used to analyze the model's clinical application value.

Results: The best predictors included gender, the carcinoembryonic antigen (CEA), consolidation-to-tumor ratio (CTR), density type, and distal ribbon sign. Among these, the tumor density type [odds ratio (OR): 6.738] and distal ribbon sign (OR: 5.141) were independent risk factors for predicting the STAS status. Moreover, three different STAS prediction models were constructed, i.e., a clinical, radiological, and combined model. The clinical model comprised gender and the CEA, the radiological model included the CTR, density type, and distal ribbon sign, and the combined model comprised the above two models. A DeLong test results revealed that the combined model was superior to the clinical model in all three cohorts and superior to the radiological model in the external validation cohort; the cohort AUC values were 0.874, 0.822, and 0.810, respectively. The results also showed that the combined model had the highest diagnostic efficacy among the models. The Hosmer-Lemeshow test showed that the combined model showed a good fit in all three cohorts, and the calibration curve showed that the predicted probability value of the combined model was in good agreement with the actual STAS status. Finally, the decision curve showed that the combined model had a better clinical application value than the clinical and radiological models.

Conclusion: The nomogram created in this study, based on clinical characteristics and radiological features, has a high diagnostic efficiency for predicting the STAS status in patients with clinical stage IA NSCLC and may support the creation of personalized treatment strategies before surgery.

Keywords: Spread through air spaces; nomogram; non-small cell lung cancer; prediction; radiological.

Figure 1

The flow chart for patient selection. NSCLC, non-small cell lung cancer; CT, computed tomography; STAS, spread through air spaces.

Figure 2

The nomogram for the preoperative prediction of the spread through air spaces status based on clinical characteristics and radiological features in clinical stage IA non-small cell lung cancer. CEA, carcinoembryonic antigen; CTR, consolidation-to-tumor ratio; STAS, spread through air spaces, mGGN, mixed ground-glass nodule.

Figure 3-4-5

The receiver operation characteristic curve analysis of the clinical, radiological, and combined models in the three cohorts. (Figure 3) The training cohort, (Figure 4) the internal validation cohort, and (Figure 5) the external validation cohort. AUC, area under the curve.

Figure 6-7-8

The calibration curves of the combined model in the three cohorts. (Figure 6) The training cohort, (Figure 7) the internal validation cohort, and (Figure 8) the external validation cohort.

Figure 9-10-11

The decision curve shows that the combined model has better clinical application value than the clinical and radiological models in the three cohorts. (Figure 9) The training cohort, (Figure 10) the internal validation cohort, and (Figure 11) the external validation cohort.

Figure 12-13

A 58-year-old male patient with lung adenocarcinoma and a positive spread through air spaces status. The sagittal non-contrast computed tomography image shows a solid nodule in the right lower lobe of the lung (Figure 12), consolidation-to-tumor ratio ≥50%, with distal ribbon sign (red arrow), lobulation sign, spiculation sign (yellow arrow), and multiple pleural tags (green arrow). (Figure 13) The photomicrograph (hematoxylin and eosin stained, magnification x100) shows detached micropapillary clusters of tumor cells (arrows) in the alveolar beyond the edge (dark line) of the main tumor (star).

Figure 14-15

A 67-year-old female patient with lung adenocarcinoma and a negative spread through air spaces (STAS) status. (Figure 14) The axial non-contrast computed tomography image shows a mixed ground-glass nodule in the right lower lobe of the lung, with the longest interface length of the entire tumor and solid component being 1.80 cm and 5.57 mm, respectively; consolidation-to-tumor ratio <50%, with an irregular shape and a well-defined interface. (Figure 15) The pathological section indicated a negative STAS status; that is, there were no free tumor cell clusters in the alveolar cavity outside the edge of the main lesion. The photomicrograph (hematoxylin and eosin stained, magnification x40) shows clean alveolar spaces adjacent to the boundary (dashed line) of the tumor (star).

Supplementary Figure 1

Show a same patient, a 53-year-old female patient with lung adenocarcinoma and positive STAS status. The axial non-contrast computed tomography shows a solid nodule in the right middle lobe of the lung, CTR ≥50%, with distal ribbon sign (a, red arrow), lobulation sigh (a, green arrow), interlobar pleura indentation sigh (b, blue arrow), bronchial change (b and c, yellow arrow), spiculation sigh (c, purple arrow). The maximal intensity projection (d) shows a vascular convergence sign (black arrow), lobulation sigh (green arrow) and distal ribbon sigh (red arrow). STAS, spread through air spaces; CTR, consolidation-to-tumor ratio.

Supplementary Figure 2

Shows a 77-year-old female patient with lung adenocarcinoma and negative STAS status. The axial non-contrast computed tomography shows a mixed ground glass nodule in the left upper lobe of the lung (green arrow) with satellite lesion sign (red arrow), the distance between the nodule and the satellite lesion is 1.03 cm. STAS, spread through air spaces.

Supplementary Figure 3

Shows a 74-year-old male patient with invasive mucinous adenocarcinoma and negative STAS status. The axial non-contrast computed tomography shows a solid nodule in the left lower lobe of the lung with halo sign (yellow arrow) and vacuole sign (blue arrow). STAS, spread through air spaces.

Supplementary Figure 4

Shows a 62-year-old female patient with invasive adenocarcinoma and negative STAS status. The axial non-contrast computed tomography shows a mixed ground glass nodule in the right upper lobe of the lung with well-defined interface, pleural tags sigh (green arrow) and cavity or cystic airspace (red arrow). STAS, spread through air spaces.