Factors affecting post-treatment radiation-induced lung disease in patients receiving stereotactic body radiotherapy to lung

The aim of the study is to investigate factors that may cause radiation-induced lung disease (RILD) in patients undergoing stereotactic body radiotherapy (SBRT) for lung tumors. Medical records of patients treated between May 2018 and June 2019 with SBRT were retrospectively evaluated. All patients should have a diagnosis of either primary non-small cell lung cancer (NSCLC) or less than three metastases to lung from another primary. The median treatment dose was 50 Gy in 4-5 fractions. Tumor response and RILD were evaluated in thoracic computer tomography (CT) using RECIST criteria. 82 patients with 97 lung lesions were treated. The median age was 68 years (IQR = 62-76). With a median follow-up of 7.2 months (3-18 months), three patients had grade 3 radiation pneumonitis (RP). RILD was observed in 52% of cases. Patients who had RILD had a higher risk of symptomatic RP (p = 0.007). In multivariate analyses older age, previous lung radiotherapy history, and median planning treatment volume (PTV) D95 value of ≥ 48 Gy were associated with RILD. Local recurrence (LR) was observed in 5.1% of cases. There was no difference in overall survival and LR with the presence of RILD. Older age, previous lung radiotherapy history, and median PTV D95 value of ≥ 48 Gy seems to be associated with post-SBRT RILD.

Technical Note: Identification of CT Texture Features Robust to Tumor Size Variations for Normal Lung Texture Analysis

Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (RILD). For these features to be clinically useful, they should be robust to tumor size variations and not correlated with the normal lung volume of interest, i.e., the volume of the peri-tumoral region (PTR). CT images of 14 lung cancer patients were studied. Different sizes of gross tumor volumes (GTVs) were simulated and placed in the lung contralateral to the tumor. 27 texture features [nine from intensity histogram, eight from the gray-level co-occurrence matrix (GLCM) and ten from the gray-level run-length matrix (GLRM)] were extracted from the PTR. The Bland-Altman analysis was applied to measure the normalized range of agreement (nRoA) for each feature when GTV size varied. A feature was considered as robust when its nRoA was less than the threshold (100%). Sixteen texture features were identified as robust. None of the robust features was correlated with the volume of the PTR. No feature showed statistically significant differences (P<0.05) on GTV locations. We identified 16 robust normal lung CT texture features that can be further examined for the prediction of RILD.