Purpose Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity. Methods and Materials Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose—volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose—volume and ventilation-based dose—function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods. Results A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose—function metrics (range P=.093-.250) than for their dose—volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose—function metrics (range, 0.569-0.620) than for their dose—volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose—function metrics compared to dose—volume metrics that approached significance (range, P=.118-.155). Conclusions To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests that incorporating ventilation-based functional imaging can improve prediction for radiation pneumonitis. We present an important first step toward validating the use of 4DCT-based ventilation imaging in thoracic treatment planning.

Purpose To determine the incidence of and risk factors for radiation pneumonitis (RP) after stereotactic ablative radiation therapy (SABR) to the lung in patients who had previously undergone conventional thoracic radiation therapy. Methods and Materials Seventy-two patients who had previously received conventionally fractionated radiation therapy to the thorax were treated with SABR (50 Gy in 4 fractions) for recurrent disease or secondary parenchymal lung cancer (T <4 cm, N0, M0, or Mx). Severe (grade ≥3) RP and potential predictive factors were analyzed by univariate and multivariate logistic regression analyses. A scoring system was established to predict the risk of RP. Results At a median follow-up time of 16 months after SABR (range, 4-56 months), 15 patients had severe RP (14 [18.9%] grade 3 and 1 [1.4%] grade 5) and 1 patient (1.4%) had a local recurrence. In univariate analyses, Eastern Cooperative Oncology Group performance status (ECOG PS) before SABR, forced expiratory volume in 1 second (FEV1), and previous planning target volume (PTV) location were associated with the incidence of severe RP. The V10 and mean lung dose (MLD) of the previous plan and the V10-V40 and MLD of the composite plan were also related to RP. Multivariate analysis revealed that ECOG PS scores of 2-3 before SABR (P=.009), FEV1 ≤65% before SABR (P=.012), V20 ≥30% of the composite plan (P=.021), and an initial PTV in the bilateral mediastinum (P=.025) were all associated with RP. Conclusions We found that severe RP was relatively common, occurring in 20.8% of patients, and could be predicted by an ECOG PS score of 2-3, an FEV1 ≤ 65%, a previous PTV spanning the bilateral mediastinum, and V20 ≥30% on composite (previous RT + SABR) plans. Prospective studies are needed to validate these predictors and the scoring system on which they are based.

We did not find a consistent pattern of ventilation change as a function of radiation dose. Pretreatment ventilation was significantly lower for lobes that contained tumor, due to occlusion of the central airway. The weekly lobe ventilation data indicated that when tumor volume shrinks, ventilation increases, and when the thoracic anatomy is not visibly changed, ventilation is likely to remain unchanged.

Purpose To determine whether single nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor beta, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGFβ, TNFα, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiotherapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (Grade ≥3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate (MV) analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGFβ, VEGF, TNFα, XRCC1 and APEX1. With smoking status included in the MV model, the SNPs significantly associated with increased risk of RP were in genes for TGFβ, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk versus <10% risk of RP when exposed to high MLDs.

Stereotactic body radiation therapy (SBRT) has emerged as an effective, noninvasive treatment option for primary liver cancer and metastatic disease occurring in the liver. Although SBRT can be highly effective for establishing local control in hepatic malignancies, a tradeoff exists between tumor control and normal tissue complications. The objective of the present study was to review the normal tissue dose-volume effects for SBRT-induced liver and gastrointestinal toxicities and derive normal tissue complication probability models.