Changes in pulmonary function after incidental lung irradiation for breast cancer: A prospective study.

PURPOSE

The aim of this study was to analyze changes in pulmonary function after radiation therapy (RT) for breast cancer.

METHODS AND MATERIALS

A total of 39 consecutive eligible women, who underwent postoperative irradiation for breast cancer, were entered in the study. Spirometry consisting of forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1), carbon monoxide diffusing capacity (DLCO), and gammagraphic (ventilation and perfusion) pulmonary function tests (PFT) were performed before RT and 6, 12, and 36 months afterwards. Dose-volume and perfusion-weighted parameters were obtained from 3D dose planning: Percentage of lung volume receiving more than a threshold dose (Vi) and between 2 dose levels (V(i-j)). The impact of clinical and dosimetric parameters on PFT changes (Delta PFT) after RT was evaluated by Pearson correlation coefficients and stepwise lineal regression analysis.

RESULTS

No significant differences on mean PFT basal values (before RT) with respect to age, smoking, or previous chemotherapy (CT) were found. All the PFT decreased at 6 to 12 months. Furthermore FVC, FEV(1), and ventilation recovered almost to their previous values, whereas DLCO and perfusion continued to decrease until 36 months (-3.3% and -6.6%, respectively). Perfusion-weighted and interval-scaled dose-volume parameters (pV(i-j)) showed better correlation with Delta PFT (only Delta perfusion reached statistically significance at 36 months). Multivariate analysis showed a significant relation between pV(10-20) and Delta perfusion at 3 years, with a multiple correlation coefficient of 0.48. There were no significant differences related to age, previous chemotherapy, concurrent tamoxifen and smoking, although a tendency toward more perfusion reduction in older and nonsmoker patients was seen.

CONCLUSIONS

Changes in FVC, FEV1 and ventilation were reversible, but not the perfusion and DLCO. We have not found a conclusive mathematical predictive model, provided that the best model only explained 48% of the variability. We suggest the use of dose-perfused volume and interval-scaled parameters (i.e., pV(10-20)) for further studies.