Radiation Pneumonitis In Patients Research Articles

Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease

Objectives: We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may provide objective imaging biomarkers for lung parenchyma integrity, potentially forecasting the risk of RP. Materials and Methods: A retrospective study was performed on medical records of 175 patients diagnosed with NSCLC who had received thoracic radiotherapy. Three indices were utilized to measure the morphometric complexity of the lung parenchyma: box-counting fractal dimension, lacunarity, and minimum spanning tree (MST) fractal dimension. Patients were dichotomized into two groups at median values. Cox proportional hazard models were constructed to estimate the hazard ratios for grade ≥ 2 or grade ≥ 3 RP. Results and Conclusions: We found significant associations between lung parenchymal morphometric complexity and RP incidence. In univariate Cox-proportional hazard analysis, patients with a lower MST fractal dimension had a significantly higher hazard ratio of 2.296 (95% CI: 1.348–3.910) for grade ≥ 2 RP. When adjusted for age, sex, smoking status, category of the underlying lung disease, category of radiotherapy technique, clinical stage, histology, and DLCO, patients with a lower MST fractal dimension showed a significantly higher hazard ratio of 3.292 (95% CI: 1.722–6.294) for grade ≥ 2 RP and 7.952 (95% CI: 1.722 36.733) for grade ≥ 3 RP than those with a higher MST fractal dimension. Patients with lower lacunarity exhibited a significantly lower hazard ratio of 0.091 (95% CI: 0.015–0.573) for grade ≥ 3 RP in the adjusted model. We speculated that the lung tissue integrity is captured by morphometric complexity measures, particularly by the MST fractal dimension. We suggest the MST fractal dimension as an imaging biomarker for predicting the occurrence of symptomatic RP after thoracic radiotherapy.

Predictive Value of Simulated CT Radiomics Combined with Ipsilateral Lung Dosimetry Parameters for Radiation Pneumonitis in Patients with Esophageal Cancer: A Machine Learning-Based Retrospective Study.

To explore how non-surgical esophageal cancer patients can identify high-risk factors for radiation-induced pneumonitis after receiving radiotherapy. We retrospectively included 228 esophageal cancer patients who were unable to undergo surgical treatment but received radiotherapy for the first time. By retrospective analysis and identifying potential risk factors for symptomatic radiation-induced pneumonitis (ie ≥grade 2), as well as delineating the affected lung as an area of interest on localized CT and extracting radiomics features, along with extracting dosimetric parameters from the affected lung area. After feature screening, patients were randomly divided into training and testing sets in a 7-to-3 ratio, and a prediction model was established using machine learning algorithms. Finally, the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to validate the predictive performance of the model. A total of 54 cases of symptomatic radiation pneumonitis occurred in this study, with a total incidence rate of 23.68%. The results of multivariate analysis showed that the occurrence of symptomatic radiation pneumonitis was significantly correlated with the mean lung dose (MLD), esophageal PTVD90, esophageal PTVV50, V5, V10, V15, and V20 in patients. The machine learning prediction model constructed based on candidate prediction variables has a prediction performance interval between 0.751 (95% CI: 0.700-0.802) and 0.891 (95% CI: 0.840-0.942) in the training and validation sets, respectively. Among them, the RFM algorithm has the best prediction performance for radiation-induced pneumonitis, with 0.891 (95% CI: 0.840-0.942) and 0.887 (95% CI: 0.836-0.938) in the training and validation sets, respectively. The combination of localization CT radiomics features and diseased lung dosimetry parameters has good predictive value for radiation-induced pneumonitis in esophageal cancer patients after radiotherapy. Especially, the radiation-induced pneumonitis prediction model constructed using RF algorithm can be more effectively used to guide clinical decision-making in esophageal cancer patients.

CT-based different regions of interest radiomics analysis for acute radiation pneumonitis in patients with locally advanced NSCLC after chemoradiotherapy

PurposeTo establish a radiomics model using radiomics features from different region of interests (ROI) based on dosimetry-related regions in enhanced computed tomography (CT) simulated images to predict radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC). MethodsOur retrospective study was conducted based on a cohort of 236 NSCLC patients (59 of them with RP≥2) who were treated in 2 institutions and divided into the primary cohort (n = 182,46 of them with RP≥2) and external validation cohort (n = 54,13 of them with RP≥2). Radiomic features extracted from three ROIs were defined as the whole lung (WL), the dose volume histogram (DVH) of the lung V20 (V20_Lung) and the DVH of the V30 of lung minus the planning target volume (PTV) (V30 Lung-PTV). A total of 107 radiomics features were extracted from each ROIs. The U test, correlation coefficient and least absolute shrinkage and selection operator (LASSO) were performed for features selection. Six models based on different classification algorithms were developed to select the best radiomics model (R model).In addition, we built a dosimetry model then combined it with the best R model to create a mixed model (R+D model) The receiver operating characteristic (ROC) curve was delineated to assess the predictive efficacy of the models. Decision curve analysis could benefit from the model proposals through the assessment of clinical utility. ResultsAmong the three ROIs, the best R model constructed from the LightGBM algorithm demonstrated the strongest discriminative ability in the ROI of V30 Lung-PTV. The corresponding area under the curve (AUC) value was 0.930 (95 % confidence interval (CI): 0.829–0.941). The D model, R model and R+D model achieved AUC values of 0.798 (95 %CI: 0.732–0.865), 0.930 (95 %CI: 0.829–0.941) and 0.940 (95 %CI: 0.906–0.974) in primary cohort, and in external validation cohort, the AUC values were 0.793 (95 %CI:0.637–0.949), 0.887 (95 %CI:0.810–0.993), 0.951 (95CI%:0.891–1.000). Decision curve demonstrate that R+D model could benefit for patients through the assessment of clinical utility. ConclusionThe radiomics model was able to predict the acute RP more effectively in comparison with the traditional dosimetry model. Especially the radiomics model based on the V30 Lung-PTV region was able to achieve a higher accuracy when compared to the other regions.

In-hospital outcomes and mortality of drug-induced pneumonitis and radiation pneumonitis in patients with thoracic cancer.

12042 Background: Pneumonitis is one of the challenging adverse events in thoracic oncology patients undergoing cancer therapy. The cancer treatments, including targeted agents, systemic chemotherapy, immune-checkpoint inhibitors, and radiation therapy have recently advanced, however, the data on incidence of drug-induced and radiation pneumonitis (DP and RP) and their association with in-hospital outcomes is limited. Methods: Data from the National Inpatient Sample Database from 2016 to 2019 were analyzed. Adult patients with primary lung cancer were included and categorized into three groups: (1). Patients without pneumonitis, (2). Patients with DP, (3). Patients with RP. Outcomes included in-hospital mortality, intensive care unit (ICU) admission, and hospital length of stay (LOS). Data were extracted using ICD-10 codes. Results: Our analysis included 1,631,940 hospitalized primary lung cancer patients (based on a weighted sample). Among all, 4,515 patients had DP, and 16,905 patients had RP. Overall, 69.3% had smoking history, however, no significant difference between DP and RP. There was a higher prevalence of chronic obstructive pulmonary disease (COPD) in RP than DP (66.5% vs 53.2%; p<0.05) (Table). The in-hospital mortality rate was highest in DP compared to other groups. Coarsened exact matching method was used to balance covariates between non-pneumonitis and pneumonitis patients (DP and RP). Multivariate logistic regression showed that pneumonitis patients had higher odds of intubation (OR: 1.57; 95% CI: 1.24-1.99; p<0.05) and mortality (OR: 1.48; 95% CI: 1.28-1.71; p<0.05) than non-pneumonitis. Pneumonitis patients also had 23% longer length of stay than non-pneumonitis patients. We then compared the outcomes between DP and RP using the same matching algorithm, however, there was no significant difference in the outcomes between the two groups. Over the study years, the trend for DP significantly increased, whereas the RP trend was stable. Conclusions: Hospitalized pneumonitis patients had relatively poor clinical outcomes compared to patients without pneumonitis. The trend of hospitalized drug-induced pneumonitis is increasingly common. [Table: see text]

The incidence of and risk factors for radiation pneumonitis in patients treated with simultaneous bevacizumab and thoracic radiotherapy

BackgroundFirst-line chemotherapy combined with bevacizumab is one of the standard treatment modes for patients with advanced non-small cell lung cancer (NSCLC). Thoracic radiotherapy (TRT) can provide significant local control and survival benefits to patients during the treatment of advanced NSCLC. However, the safety of adding TRT has always been controversial, especially because of the occurrence of radiation pneumonia (RP) during bevacizumab treatment. Therefore, in this study, we used an expanded sample size to evaluate the incidence of RP when using bevacizumab in combination with TRT.Patients and methodsUsing an institutional query system, all medical records of patients with NSCLC who received TRT during first-line chemotherapy combined with bevacizumab from 2017 to 2020 at Shandong Cancer Hospital and Institute were reviewed. RP was diagnosed via computed tomography and was classified according to the RTOG toxicity scoring system. The risk factors for RP were identified using univariate and multivariate analyses. The Kaplan–Meier method was used to calculate progression-free survival (PFS) and overall survival (OS).ResultsUltimately, 119 patients were included. Thirty-eight (31.9%) patients developed Grade ≥ 2 RP, of whom 27 (68.1%) had Grade 2 RP and 11 (9.2%) had Grade 3 RP. No patients developed Grade 4 or 5 RP. The median time for RP occurrence was 2.7 months (range 1.2–5.4 months). In univariate analysis, male, age, KPS score, V20 > 16.9%, V5 > 33.6%, PTV (planning target volume)-dose > 57.2 Gy, and PTV-volume > 183.85 cm3 were correlated with the occurrence of RP. In multivariate analysis, male, V20 > 16.9%, and PTV-volume > 183.85 cm3 were identified as independent predictors of RP occurrence. The mPFS of all patients was 14.27 (95% CI, 13.1–16.1) months. The one-year and two-year PFS rates were 64.9% and 20.1%, respectively. The mOS of all patients was 37.09 (95% CI, 33.8–42.0) months. The one-year survival rate of all patients was 95%, and the two-year survival rate was 71.4%.ConclusionsThe incidence of Grade ≥ 2 RP in NSCLC patients who received both bevacizumab and TRT was 31.9%. Restricting factors such as V20 and PTV will help reduce the risk of RP in these patients. For patients who receive both bevacizumab and TRT, caution should be exercised when increasing TRT, and treatment strategies should be optimized to reduce the incidence of RP.

Clinical predictors of severe radiation pneumonitis in patients undergoing thoracic radiotherapy for lung cancer

Clinical predictors of severe radiation pneumonitis in patients undergoing thoracic radiotherapy for lung cancer

Timing of Radiation Pneumonitis in Patients with Stage 3 Non-Small-Cell Lung Cancer Receiving Consolidation Durvalumab after Chemoradiation

Purpose. Consolidation with durvalumab is standard of care in the management of unresectable stage 3 non-small-cell lung cancer (NSCLC) postchemoradiation, and pneumonitis is an independent potential treatment complication of both treatment strategies. This study seeks to determine the timing of radiation pneumonitis (RP) by receipt of durvalumab. In addition, we reviewed the preventative strategies guided by pathophysiology of pneumonitis. Methods. We identified patients with unresectable Stage 3 NSCLC who developed grade ≥2 RP after chemoradiotherapy. Time-to-RP was defined from date of completion of radiotherapy to date of radiological diagnosis of RP and accompanying clinical symptoms. Early RP was defined as RP within 2 months of completion of radiotherapy. Differences in time-to-RP by receipt of durvalumab were evaluated using Wilcoxon rank-sum test. Differences in those who had early vs late RP by receipt of durvalumab was evaluated using Fisher’s exact test. Logistic regression was used to evaluate patient and treatment factors associated with early RP. Results. Of the 144 patients with Stage 3 NSCLC who had definitive chemoradiotherapy, 31 (22%) developed grade ≥2 RP and were included in the study. There was one patient with grade 5 RP. The median age of the cohort was 67 years (range 41–87). The mean lung dose, V5Gy, and V20Gy were 15.8Gy (SD = 1.56), 60.14% (SD 2.73), and 29.96% (SD 1.82), respectively. Twelve (39%) patients received durvalumab. The median time-to-RP was 3.4 months (range: 1.7–7.2) and 2.3 months (range: 0.6–9.6) in patients who had durvalumab and no durvalumab, respectively (P=0.01). 83% (10/12) of patients who had durvalumab and 58% (11/19) of patients who did not have durvalumab had late RP (P=0.14). No other patient and treatment factors were associated with early RP. Conclusion. Patients on durvalumab may have late-onset RP; therefore, further studies with larger cohort of patients and development of new predictive models that incorporate evolving management are needed should preventative strategies of RP be considered in routine clinical practice.

Safety and Efficacy of HL301 In Radiation Pneumonitis in Patients With Unresectable Non-Small Cell Lung Cancer Receiving Curative Concurrent Chemoradiotherapy: A Multicenter, Randomized, Double-Blinded, Placebo-Controlled, Phase 2a Clinical Trial

Objective: We aimed to investigate the safety and efficacy of HL301, a standardized combination product of seven medicinal plants, in radiation pneumonitis in patients with unresectable non-small cell lung cancer (NSCLC) undergoing curative concurrent chemoradiotherapy.Methods: The target accrual was 87 and a total of 63 patients were enrolled due to poor accrual rate. We randomly assigned the 63 patients to receive a placebo (arm A), or 1200 mg HL301 (arm B), or 1800 mg HL301 (arm C). Patients received weekly paclitaxel and carboplatin concurrently with intensity-modulated radiotherapy at 60–66 Gy in conventional fractionation. Durvalumab was administered as maintenance treatment according to standard clinical practice. HL301 was administered orally, daily for 12 weeks. The primary endpoint was incidence of grade ≥2 radiation pneumonitis at 24 weeks post-chemoradiotherapy.Results: The baseline characteristics of the patients were well balanced. The drug was tolerable with a compliance rate of 86.6%, 86.2%, and 88.8% in arms A, B, and C, respectively (P = 0.874). None of the patients experienced severe drug-related adverse events. No significant difference in the rate of adverse events were observed between the treatment arms. The incidence of grade ≥2 radiation pneumonitis at 24 weeks post-chemoradiotherapy was 37.5% (95% CI, 18.5–61.4%), 55.6% (95% CI, 33.7–75.4%), and 52.4% (95% CI, 32.4–71.7%) in arms A, B, and C, respectively (P=0.535).Conclusion: This is the first exploratory clinical trial to test the safety and efficacy of HL301 in patients with NSCLC. Safety and feasibility of HL301 were established but no signals of efficacy in reducing RP was observed in this dose level.

DNA Repair Genetics and the Risk of Radiation Pneumonitis in Patients With Lung Cancer: A Systematic Review and Meta-analysis

AimsERCC1 rs11615 and ERCC2 rs238406 single nuclear polymorphism (SNPs) are known for their association with treatment outcome, likely related to radiosensitivity of both tumor and normal tissue in patients with non-small-cell lung cancer. This study aimed to review the effect of 1) these ERCC1/2 SNPs and 2) other SNPs of DNA repair genes on radiation pneumonitis (RP) in patients with lung cancer. Materials and methodsSNPs of our interest included ERCC1 rs11615 and ERCC2 rs238406 and other genes of DNA repair pathways that are functional and biologically active. DNA repair SNPs reported by at least two independent studies were pooled for meta-analysis. The study endpoint was radiation pneumonitis (RP) after radiotherapy. Recessive, dominant, homozygous, heterozygous, and allelic genotype models were used where appropriate. ResultsA total of 16 studies (3080 patients) were identified from the systematic review and 12 studies (2090 patients) on 11 SNPs were included in the meta-analysis. The SNPs were ATM rs189037, ATM rs373759, NEIL1 rs4462560, NEIL1 rs7402844, APE1 rs1130409, XRCC3 rs861539, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, ERCC2 rs13181, and XRCC1 rs25487. ERCC1 rs11615 (236 patients) and ERCC2 rs238406 (254 patients) were not significantly associated with RP. Using the allelic model, the G allele for NEIL1 gene was significantly associated with a reduced odds of developing symptomatic (grade ≥2) RP compared to the C allele for rs7402844 (OR 0.70, 95% CI: 0.49, 0.99, P = 0.04). Similarly, the T allele for APE1 gene was significantly associated with a reduced odds of developing symptomatic (grade ≥2) RP compared to the G allele for rs1130409 (OR 0.59, 95% CI: 0.43, 0.81, P = 0.001). ConclusionGenetic variation in the DNA repair pathway genes may play a significant role in the risk of developing radiation pneumonitis in patients with lung cancer. Further studies are needed on genotypic features of DNA repair pathway genes and their association with treatment sensitivity, as such knowledge may guide personalized radiation dose prescription.

Novel model integrating computed tomography-based image markers with genetic markers for discriminating radiation pneumonitis in patients with unresectable stage III non-small cell lung cancer receiving radiotherapy: a retrospective multi-center radiogenomics study

BackgroundChemoradiotherapy is a critical treatment for patients with locally advanced and unresectable non-small cell lung cancer (NSCLC), and it is essential to identify high-risk patients as early as possible owing to the high incidence of radiation pneumonitis (RP). Increasing attention is being paid to the effects of endogenous factors for RP. This study aimed to investigate the value of computed tomography (CT)-based radiomics combined with genomics in analyzing the risk of grade ≥ 2 RP in unresectable stage III NSCLC.MethodsIn this retrospective multi-center observational study, 100 patients with unresectable stage III NSCLC who were treated with chemoradiotherapy were analyzed. Radiomics features of the entire lung were extracted from pre-radiotherapy CT images. The least absolute shrinkage and selection operator algorithm was used for optimal feature selection to calculate the Rad-score for predicting grade ≥ 2 RP. Genomic DNA was extracted from formalin-fixed paraffin-embedded pretreatment biopsy tissues. Univariate and multivariate logistic regression analyses were performed to identify predictors of RP for model development. The area under the receiver operating characteristic curve was used to evaluate the predictive capacity of the model. Statistical comparisons of the area under the curve values between different models were performed using the DeLong test. Calibration and decision curves were used to demonstrate discriminatory and clinical benefit ratios, respectively.ResultsThe Rad-score was constructed from nine radiomic features to predict grade ≥ 2 RP. Multivariate analysis demonstrated that histology, Rad-score, and XRCC1 (rs25487) allele mutation were independent high-risk factors correlated with RP. The area under the curve of the integrated model combining clinical factors, radiomics, and genomics was significantly higher than that of any single model (0.827 versus 0.594, 0.738, or 0.641). Calibration and decision curve analyses confirmed the satisfactory clinical feasibility and utility of the nomogram.ConclusionHistology, Rad-score, and XRCC1 (rs25487) allele mutation could predict grade ≥ 2 RP in patients with locally advanced unresectable NSCLC after chemoradiotherapy, and the integrated model combining clinical factors, radiomics, and genomics demonstrated the best predictive efficacy.

Dosimetric predictors of radiation pneumonitis in patients with prior immunotherapy exposure: A multi-institutional analysis

Background and purposeCombining immune checkpoint inhibitors (ICIs) and thoracic radiotherapy (TRT) may magnify the radiation pneumonitis (RP) risk. Dosimetric parameters can predict RP, but dosimetric data in context of immunotherapy are very scarce. To address this knowledge gap, we performed a large multicenter investigation to identify dosimetric predictors of RP in this under-studied population. Materials and methodsAll lung cancer patients from five institutions who underwent conventionally-fractionated thoracic intensity-modulated radiotherapy with prior ICI receipt were retrospectively compiled. RP was defined per CTCAE v5.0. Statistics utilized logistic regression modeling and receiver operating characteristic (ROC) analysis. ResultsThe vast majority of the 192 patients (median follow-up 14.7 months) had non-small cell lung cancer, received PD-1 inhibitors, and did not receive concurrent systemic therapy with TRT. Grades 1–5 RP occurred in 21.9%, 25.0%, 8.3%, 1.6%, and 1.0%, respectively. The mean MLD for patients with grades 1–5 RP was 10.7, 11.6, 12.6, 14.7, and 12.8 Gy, respectively. On multivariable analysis, tumor location and mean lung dose (MLD) significantly predicted for any-grade and grade ≥ 2 pneumonitis. Only MLD significantly predicted for grade ≥ 3 RP. ROC analysis was able to pictorially model RP risk probabilities for a variety of MLD thresholds, which can be an assistive tool during TRT treatment planning. ConclusionThis study, by far the largest to date of dosimetric predictors of RP in the immunotherapy era, illustrates that MLD is the most critical dose-volume parameter influencing RP risk. These data may provide a basis for revising lung dose constraints in efforts to better prevent RP in this rapidly expanding ICI/TRT population.

Dose-Volume Predictors of Radiation Pneumonitis After Thoracic Hypofractionated Radiation Therapy

Purpose/Objective(s)Hypofractionated radiation therapy (HFRT) is a common treatment for thoracic tumors, typically delivered as 60 Gy in 15 fractions. We aimed to identify dosimetric risk factors associated with radiation pneumonitis in patients receiving HFRT at 4 Gy per fraction, focusing on lung V20, mean lung dose (MLD), and lung V5 as potential predictors of grade ≥2 pneumonitis. Materials/MethodsAll patients were treated with thoracic HFRT to 60 Gy in 15 fractions or 72 Gy in 18 fractions at a single healthcare system from 2013-2020. Tumors near critical structures (trachea, proximal tracheobronchial tree, esophagus, spinal cord, or heart) were considered central (within 2 cm), while those closer were classified as ultra-central (within 1 cm). The primary endpoint was grade ≥2 pneumonitis. Logistic regression analyses, adjusting for target size and dosimetric variables, were used to establish a dose threshold associated with <20% risk of grade ≥2 pneumonitis. ResultsOver a median 24.3-month follow-up, 18 patients (16.8%) developed grade ≥2 radiation pneumonitis, with no significant difference between the two dose regimens (17.3% vs. 16.3%, p=0.88). Four patients (3.7%) experienced grade ≥3 pneumonitis, including two grade 5 cases. Patients with grade ≥2 pneumonitis had significantly higher lung V20 (mean 23.4% vs. 14.5%, p<0.001), MLD (mean 13.0 Gy vs. 9.5 Gy, p<0.001), and lung V5 (mean 49.6% vs. 40.6%, p=0.01). Dose thresholds for a 20% risk of grade ≥2 pneumonitis were lung V20 <17.7%, MLD <10.6 Gy, and V5 <41.3%. Multivariable analysis revealed a significant association between lung V20 and grade ≥2 pneumonitis (adjusted OR 1.48, p=0.03). ConclusionTo minimize the risk of grade ≥2 radiation pneumonitis when delivering 4 Gy per fraction at either 60 Gy or 72 Gy, it is advisable to maintain lung V20<17.7%. MLD<10.6 Gy and V5<41.3% can also be considered as lower-priority constraints. However, further validation is necessary before incorporating these constraints into clinical practice or trial planning guidelines.

Analysis of the risk factors of radiation pneumonitis in patients after radiotherapy for esophageal squamous cell carcinoma.

To predict the risk factors of radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC) who received radiotherapy. From January 2015 to October 2021, 477 ESCC patients were enrolled and were assessed retrospectively. All these patients received radiotherapy for primary lesions or mediastinal metastatic lymph nodes. Clinical efficacy and adverse events (AEs) were observed. Univariate analysis identified clinical and dosimetric factors associated with the development of RP, and multivariate logistic regression analysis identified independent potential risk factors associated with the development of RP. Nomograms were constructed to predict RP based on the results of multivariate logistic regression analysis. Among the 477 ESCC patients, the incidence of RP was 22.2%, and the incidence of grade 4 or higher RP was 1.5%. Univariate analysis indicated that chronic obstructive pulmonary disease (COPD), pulmonary infection, leucopenia, PTV volume, V5, V20, V30 and MLD affected the occurrence of RP. The multivariate logistic regression analysis indicated that COPD (OR:1.821, 95%CI:1.111-2.985; P=0.017), pulmonary infection (OR:2.528, 95%CI:1.530-4.177; P<0.001), higher V20 (OR: 1.129, 95% CI:1.006-1.266; P=0.029) were significant independent predictors of RP in ESCC patients. COPD, pulmonary infection, V20 have been integrated for the RP nomogram. The rate of RP was significantly reduced in the V20<21.45% group. Further analysis indicated that the old age, diabetes, higher V20, and higher MLD were risk factors for grade 4 or higher RP. The area under the curve (AUC) value for V20 was 0.73 (95% CI, 0.567-0.893, P < 0.05). We have determined the risk factors of RP and grade 4 or higher RP in ESCC patients after radiotherapy. MLD, V20, COPD were independent factors for RP. It was necessary to take measures to reduce or avoid the occurrence of RP for patients with these risk factors at the early stage.

Risk factor analysis of the development of severe radiation pneumonitis in patients with non-small cell lung cancer treated with curative radiotherapy, with focus on underlying pulmonary disease

BackgroundWe aim to identify the multifaceted risk factors that can affect the development of severe radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC) treated with curative high-dose radiotherapy with or without concurrent chemotherapy.MethodsWe retrospectively reviewed the medical records of 175 patients with stage-I-III NSCLC treated with curative thoracic X-ray radiotherapy at the Korea University Guro Hospital between June 2019 and June 2022. Treatment-related complications were evaluated using the Common Terminology Criteria for Adverse Events (version 4.03).ResultsThe median follow-up duration was 15 months (range: 3–47 months). Idiopathic pulmonary fibrosis (IPF) as an underlying lung disease (P < 0.001) and clinical stage, regarded as the concurrent use of chemotherapy (P = 0.009), were associated with a high rate of severe RP. In multivariate analyses adjusting confounding variables, the presence of IPF as an underlying disease was significantly associated with severe RP (odds ratio [95% confidence interval] = 48.4 [9.09–347]; P < 0.001). In a subgroup analysis of stage-I-II NSCLC, the incidence of severe RP in the control, chronic obstructive pulmonary disease (COPD), and IPF groups was 3.2%, 4.3%, and 42.9%, respectively (P < 0.001). The incidence of severe RP was 15.2%, 10.7%, and 75.0% in the control, COPD, and IPF groups, respectively (P < 0.001) in the stage-III NSCLC group.ConclusionsThis study revealed that IPF as an underlying lung disease and the concurrent use of chemotherapy are associated with a high rate of severe RP. In contrast, COPD did not increase the risk of pulmonary toxicity after receiving curative high-dose radiotherapy.

The Role of CT-Based Radiomics Nomogram in Differential Diagnosis of Immune Checkpoint Inhibitor-Related Pneumonitis from Radiation Pneumonitis for Patients with ESCC

The combination of immunotherapy and chemoradiotherapy has widely used for patients with esophageal squamous cell carcinoma (ESCC) and induced treatment-related adverse effects, particularly immune checkpoint inhibitor-related pneumonitis (CIP) and radiation pneumonitis (RP). The aim of this study is to differentiate between CIP and RP by the CT radiomics and clinical or radiological parameters. A total of 76 ESCC patients with pneumonitis were enrolled in this retrospective study and divided into training dataset (n = 53) and validation dataset (n = 23). A total of 837 radiomics features were extracted from regions of interest (ROIs) based on the lung parenchyma window of CT images. A radiomics signature was constructed on the basis of the predictive features by the least absolute shrinkage and selection operator (LASSO). A logistic regression was applied to develop radiomics nomogram. Receiver operating characteristics (ROC) curve and area under the curve (AUC) were applied to evaluate the performance of pneumonitis etiology identification. No significant difference was detected between training dataset and validation dataset. The radiomics signature which was made up of four radiomics features shown a favorable performance on differentiating between CIP and RP with the α-binormal-based and empirical AUC = 0.831 and 0.843. Patients with RP had a close relationship with location (p = 0.003) and shape of lesions (p = 0.002). The nomogram that combined with radiomics signature and clinical factors improved the classifying performance on discrimination in the training dataset (AUCαbin = 0.963 and AUCemp = 0.964). The results were verified in the validation dataset with AUC = 0.967 and 0.964. CT-based radiomics features have potential values for differentiating between patients with CIP and RP. Addition of bilateral changes and sharp border produced superior model performance on classifying, which could be a useful method to improve related clinical decision-making.

Ipsilateral lung dose as a correlative measure for radiation pneumonitis in patients treated with definitive concurrent radiochemotherapy.

Mean lung dose (MLD) and percent of total lung (TL) volume that receive a dose greater than 20 Gy (V20) have been the most validated parameters in the prediction of radiation pneumonitis (RP). However, these parameters present mean values of TL parenchyma and predict the right and the left lung as a unique functional organ unit, not take into account the difference in function and dose density between the lungs. Furthermore, there have been very limited data evaluating ipsilateral lung dosimetric constraints in addition to TL parameters to predict RP in non-small cell lung cancer (NSCLC) patients treated with radiochemotherapy (RCT). Between 2010 and 2017, clinical-radiological findings of NSCLC patients treated with RCT were evaluated in terms of RP, retrospectively. MLD, V20, and V30 values of ipsilateral lung were assessed from dose-volume histogram and registered. The primary endpoint was to assess the relation between ipsilateral lung dose constraints and RP risk. There were 75 patients. There was ≥Grade 2 RP in 33 cases (%44). In univariate analysis, ipsilateral MLD, ipsilateral V20, ipsilateral V30, and TL V30 were found to be significant. Ipsilateral MLD and PTV were found to be the independent risk factors for RP. Cutoff values for RP risk were determined as 18Gy, 35%, and 28% for ipsilateral MLD, ipsilateral V20, and ipsilateral V30, respectively. Predictive values for ipsilateral MLD and ipsilateral V20 were higher than TL. In NSCLC patients treated with RCT, MLD, V20, and V30 values of ipsilateral lung parameters might increase the predictability of RP risk in addition to TL parameters. Cutoff values for RP risk were determined as 18Gy, 35%, and 28% for ipsilateral MLD, ipsilateral V20, and ipsilateral V30, respectively. Predictive values for ipsilateral MLD and ipsilateral V20 were higher than TL.

Incidence and Treatment Outcome of Radiation Pneumonitis in Patients With Limited-stage Small Cell Lung Cancer Treated With Concurrent Accelerated Hyperfractionated Radiation Therapy and Chemotherapy

PurposeThis study aimed to clarify the characteristics of and evaluate the risk factors for radiation pneumonitis (RP) induced by chemoradiation therapy (CRT) using accelerated hyperfractionated (AHF) radiation therapy (RT) in patients with limited-stage small cell lung cancer (LS-SCLC). Methods and MaterialsBetween September 2002 and February 2018, 125 patients with LS-SCLC were treated with early concurrent CRT using AHF-RT. Chemotherapy was comprised of carboplatin/cisplatin with etoposide. RT was administered twice daily (45 Gy/30 fractions). We collected data regarding onset and treatment outcomes for RP, and analyzed the relationship between RP and total lung dose–volume histogram findings. Uni- and multivariate analyses were performed to assess patient- and treatment-related factors for grade ≥2 RP. ResultsThe median age of patients was 65 years, and 73.6% of participants were men. In addition, 20% and 80.0% of participants presented with disease stage II and III, respectively. The median follow-up time was 73.1 months. Grades 1, 2, and 3 RP were observed in 69, 17, and 12 patients, respectively. Grades 4 to 5 RP were not observed. RP was treated with corticosteroids in patients with grade ≥2 RP, without recurrence. The median time from initiation of RT to onset of RP was 147 days. Three patients developed RP within 59 days, 6 within 60 to 89 days, 16 within 90 to 119 days, 29 within 120 to 149 days, 24 within 150 to 179 days, and 20 within ≥180 days. Among the dose–volume histogram parameters, the percentage of lung volume receiving >30 Gy (V30) was most strongly related to the incidence of grade ≥2 RP, and the optimal threshold to predict RP incidence was V30 ≥20%. On multivariate analysis, V30 ≥20% was an independent risk factor for grade ≥2 RP. ConclusionsThe incidence of grade ≥2 RP correlated strongly with a V30 of ≥20%. Contrarily, the onset of RP induced by concurrent CRT using AHF-RT may occur later. RP is manageable in patients with LS-SCLC.

Risk of Radiation Pneumonitis in Patients Receiving Osimertinib and Thoracic Radiotherapy

Risk of Radiation Pneumonitis in Patients Receiving Osimertinib and Thoracic Radiotherapy

Dosimetric Risk Factors for Radiation Pneumonitis in Patients with Prior Receipt of Immune Checkpoint Inhibitors: A Retrospective Study

<h3>Purpose/Objective(s)</h3> Dosimetric parameters (e.g., mean lung dose (MLD), V20, and V5) can predict radiation pneumonitis (RP). Constraints thereof were formulated before the era of combined immune checkpoint inhibitors (ICIs) and radiotherapy, which could amplify the RP risk. Dosimetric predictors of acute RP (aRP) in the context of ICIs are urgently needed because no data exist thus far. <h3>Materials/Methods</h3> All included patients underwent thoracic irradiation, previously received ICIs, and followed-up at least once. Logistic regression models examined predictors of aRP (including a priori evaluation of MLD, V20, and V5), and their discriminative capacity was assessed by receiver operating characteristic analysis. <h3>Results</h3> Median follow-up of the 40 patients was 5.3 months. Cancers were lung (80%) or esophageal (20%). ICIs were PD-1 (85%) or PD-L1 (15%) inhibitors (median 4 cycles). Patients underwent definitive (n=19), consolidative (n=14), or palliative (n=7) radiotherapy; the median equivalent dose in 2 Gy fractions (EQD2) was 60 Gy (IQR, 51.8-64 Gy). Grades 1-5 aRP occurred in 25%, 17.5%, 15%, 2.5%, and 5%, respectively. The only variables associated with any-grade aRP were V20 (p=0.014) and MLD (p=0.026), and only V20 with grade ≥2 aRP (p=0.035). Graphs were constructed showing the incrementally increasing risk of aRP based on V20 and MLD, V20=5.2% and MDL=4.0Gy would predict for a 50% risk of ≥ grade 1 pneumonia, and V20=19.3% would predict for a 50% risk for grade 2 pneumonia. <h3>Conclusion</h3> This is the first study illustrating that V20 and MLD may impact aRP in the setting of prior ICIs. If these results are validated by larger studies with more homogeneous populations, the commonly accepted V20/MLD dose constraints could require revision if utilized in the setting of ICIs.

VMAT-Based Planning Allows Sparing of a Spatial Dose Pattern Associated with Radiation Pneumonitis in Patients Treated with Radiotherapy for a Locally Advanced Lung Cancer

<h3>Purpose/Objective(s)</h3> In patients treated with radiotherapy for a locally advanced lung cancer, respect of dose constraints to organs at risks (OARs) insufficiently protects patients from acute pulmonary toxicity (APT), such toxicities being associated with a potential impact on treatment's completion and the patients' quality of life. Dosimetric planning doesn't take into account regional lung functionality. An APT prediction model combining usual dosimetry features with the mean dose (DMean_Pmap) received by a voxel-based volume (Pmap) localized in the posterior right lung has been previously developed. A DMean_Pmap ≥ 30.3Gy was associated with a higher risk of APT. In the present study, the authors aim to demonstrate the possibility of decreasing the DMean_Pmap via a volumetric arc therapy (VMAT)-based adapted planning and evaluate the impact on the risk of APT. <h3>Materials/Methods</h3> Among the 207 patients included in the initial study, only patients who presented with an APT ≥ grade 2 and with a probability of APT (Prob_APT) ≥ 8% based on the prediction model were included. Dosimetry planning was optimized with a new constraint (DMean_Pmap < 30.3Gy) added to the usual constraints. Initial and optimized treatment plans were compared using the T-test for independent variables and the non-parametric Mann-Whitney U test otherwise, regarding both doses to OARs and PTV (Planning Target Volume) coverage. Conformity and heterogeneity indexes were also compared. Risk of APT was recalculated using the new dosimetric features and the APT prediction model. <h3>Results</h3> Dosimetric optimization was considered successful for 27 out of the 44 included patients (61.4%), meaning the dosimetric constraint on the Pmap region was achieved without compromising the PTV coverage (p = 0.61). Optimization significantly decreased median DMean_Pmap from 28.8Gy (IC95% 24.2-33.4) to 22.1Gy (IC95% 18.3-26.0). When recomputing the risk of APT using the new dosimetric features, optimization significantly reduced the risk of APT (p < 0.0001) by reclassifying 43.2% (19/44) of the patients. <h3>Conclusion</h3> Our approach appears as both easily implementable on a daily basis and efficient at reducing the risk of APT. Regional radiosensitivity should be considered in usual lung dose constraints, opening the possibility of an easily implementable adaptive dosimetry planning.