Radiation Pneumonitis Research Articles

1801: Effect of lung dose and prophylactic clarithromycin on the development of radiation pneumonitis

1801: Effect of lung dose and prophylactic clarithromycin on the development of radiation pneumonitis

1422: Development of homodogy prediction method of radiation pneumonitis using lung CT ventilation image

1422: Development of homodogy prediction method of radiation pneumonitis using lung CT ventilation image

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.

Associations Between Mean Lung Dose and Prevalence of Radiation Pneumonitis in Elderly Lung Cancer Patients.

Pneumonitis is a serious radiotherapy complication. This study, which is a prerequisite for a prospective trial, aimed to identify the prevalence of pneumonitis and risk factors in elderly patients with lung cancer. Ninety-eight lung cancer patients aged ≥65 years were included. Seventeen factors were investigated regarding grade ≥2 pneumonitis at 24 weeks following radiotherapy. The prevalence of grade ≥2 pneumonitis at 24 weeks was 27.3%. On univariate analysis, a significant association was observed for mean (ipsilateral) lung dose (MLD; ≤13.0 vs. 13.1-20.0 vs. >20.0 Gy; 0% vs. 24.9% vs. 48.7%). Results were significant also for ≤13.0 vs. >13.0 Gy (0% vs. 37.1%) or ≤20.0 vs. >20.0 Gy (13.4% vs. 48.7%). MLD achieved significance on multivariate analysis. Elderly patients receiving MLDs >13.0 Gy, particularly >20.0 Gy, have a high risk of grade ≥2 pneumonitis. These results are important for designing a prospective trial.

Adipose-derived stem cells ameliorate radiation-induced lung injury by activating the DDAH1/ADMA/eNOS signaling pathway

BackgroundIonizing radiation-induced lung injury is caused by the initial inflammatory reaction and leads to advanced fibrosis of lung tissue. Adipose-derived stem cells (ASCs) are a type of mesenchymal stem cell that can differentiate into various functional cell types with broad application prospects in the treatment of tissue damage. The purpose of this study was to explore the protective effect of ASCs against radiation-induced lung injury and to provide a novel basis for prevention and treatment of radiation-induced lung injury. Materials and methodsFifty mice were randomly divided into a control group (Ctrl), radiation exposure group (IR), radiation exposure plus ASC treatment group (IR + ASC), radiation exposure plus L-257 group (IR + L-257), and radiation exposure plus ASC treatment and L-257 group (IR + ASC + L-257). Mice in IR, IR + ASC, and IR + ASC + L-257 groups were exposed to a single whole-body dose of 5 Gy X-rays (160 kV/25 mA, 1.25 Gy/min). Within 2 h after irradiation, mice in IR + ASC and IR + ASC + L-257 groups were injected with 5 × 106 ASCs via the tail vein. Mice in IR + L-257 and IR + ASC + L-257 groups were intraperitoneally injected with 30 mg/kg L-257 in 0.5 mL saline. ResultsThe mice in the IR group exhibited lung hemorrhage, edema, pulmonary fibrosis, and inflammatory cell infiltration, increased release of proinflammatory cytokines, elevation of oxidative stress and apoptosis, and inhibition of the dimethylarginine dimethylamino hydratase 1 (DDAH1)/ADMA/eNOS signaling pathway. ASC treatment alleviated radiation-induced oxidative stress, apoptosis, and inflammation, and restored the DDAH1/ADMA/eNOS signaling pathway. However, L-257 pretreatment offset the protective effect of ASCs against lung inflammation, oxidative stress, and apoptosis. ConclusionsThese data suggest that ASCs ameliorate radiation-induced lung injury, and the mechanism may be mediated through the DDAH1/ADMA/eNOS signaling pathway.

Long-term survival outcomes and quality of life of image-guided proton therapy for operable stage I non-small cell lung cancer: A phase 2 study

Background and purposeThis study evaluated long-term efficacy, safety, and changes in quality of life (QOL) of patients after image-guided proton therapy (IGPT) for operable stage I non-small cell lung cancer (NSCLC). Materials and methodsThis single-institutional prospective phase 2 study enrolled patients with operable histologically confirmed stage IA or IB NSCLC (7th edition of UICC). The prescribed dose was 66 Gy relative biological effectiveness equivalents (GyRBE) in 10 fractions for peripheral lesions, or 72.6 GyRBE in 22 fractions for central lesions. The primary endpoint was the 3-year overall survival (OS). The secondary endpoints included disease control, toxicity, and changes in QOL score. ResultsWe enrolled 43 patients (median age: 68 years; range, 47–79 years) between July 2013 to January 2021, of whom 41 (95 %) had peripheral lesions and 27 (63 %) were stage IA. OS, local control, and progression-free survival rates were 95 % (95 % CI: 83–99), 95 % (82–99), and 86 % (72–94), respectively, at 3 years, and 83 % (66–92), 95 % (82–99), and 77 % (60–88), respectively, at 7 years. Four patients (9 %) developed grade 2, and one patient (2 %) developed grade 3 radiation pneumonitis. No other grade 3 or higher adverse events were observed. In the QOL analysis, global QOL remained favorable; however, approximately 40 % of patients reported dyspnea at 3 and 24 months. ConclusionOur findings suggest that IGPT provides effective disease control and survival in operable stage I NSCLC, particularly for peripheral lesions. Moreover, toxicity associated with IGPT was minimal, and patients reported favorable QOL.

Hydrogen-rich solution alleviates acute radiation pneumonitis by regulating oxidative stress and macrophages polarization.

This study was aimed to investigate the effect of hydrogen-rich solution (HRS) on acute radiation pneumonitis (ARP) in rats. The ARP model was induced by X-ray irradiation. Histopathological changes were assessed using HE and Masson stains. Inflammatory cytokines were detected by ELISA. Immunohistochemistry and flow cytometry were performed to quantify macrophage (CD68) levels and the M2/M1 ratio. Western blot analysis, RT-qPCR, ELISA and flow cytometry were used to evaluate mitochondrial oxidative stress injury indicators. Immunofluorescence double staining was performed to colocalize CD68/LC3B and p-AMPK-α/CD68. The relative expression of proteins associated with autophagy activation and the adenosine 5'-monophosphate-activated protein kinase/mammalian target of rapamycin/Unc-51-like kinase 1 (AMPK/mTOR/ULK1) signaling pathway were detected by western blotting. ARP decreased body weight, increased the lung coefficient, collagen deposition and macrophage infiltration and promoted M1 polarization in rats. After HRS treatment, pathological damage was alleviated, and M1 polarization was inhibited. Furthermore, HRS treatment reversed the ARP-induced high levels of mitochondrial oxidative stress injury and autophagy inhibition. Importantly, the phosphorylation of AMPK-α was inhibited, the phosphorylation of mTOR and ULK1 was activated in ARP rats and this effect was reversed by HRS treatment. HRS inhibited M1 polarization and alleviated oxidative stress to activate autophagy in ARP rats by regulating the AMPK/mTOR/ULK1 signaling pathway.

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis

BackgroundPneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) radiation pneumonitis (RP), and infective pneumonitis (IP) is crucial for swift, appropriate, and tailored management to achieve optimal patient outcomes. However, correct diagnosis is often challenging, owing to overlapping clinical presentations and radiological patterns. MethodsIn this multi-centre study of 455 patients, we used machine learning with radiomic features extracted from chest CT imaging to develop and validate five models to distinguish CIP and RP from COVID-19, non-COVID-19 infective pneumonitis, and each other. Model performance was compared to that of two radiologists. ResultsModels to distinguish RP from COVID-19, CIP from COVID-19 and CIP from non-COVID-19 IP out-performed radiologists (test set AUCs of 0.92 vs 0.8 and 0.8; 0.68 vs 0.43 and 0.4; 0.71 vs 0.55 and 0.63 respectively). Models to distinguish RP from non-COVID-19 IP and CIP from RP were not superior to radiologists but demonstrated modest performance, with test set AUCs of 0.81 and 0.8 respectively. The CIP vs RP model performed less well on patients with prior exposure to both ICI and radiotherapy (AUC 0.54), though the radiologists also had difficulty distinguishing this test cohort (AUC values 0.6 and 0.6). ConclusionOur results demonstrate the potential utility of such tools as a second or concurrent reader to support oncologists, radiologists, and chest physicians in cases of diagnostic uncertainty. Further research is required for patients with exposure to both ICI and thoracic radiotherapy.

A Single-center Experience of Radiotherapy in Pediatric Ewing Sarcoma/Primitive Neuroectodermal Tumor of the Chest Wall.

To evaluate the treatment results, prognostic parameters, and treatment-related toxicity in patients with Ewing sarcoma (ES)/primitive neuroectodermal tumor (PNET) of the chest wall who underwent surgery, chemotherapy, and radiotherapy (RT) in a tertiary referral center. The data of 24 patients under 18 years of age with a histologic diagnosis of ES/PNET in the chest wall that received RT in our department between February 2003 and July 2020 were retrospectively evaluated. RT was applied to the primary site±whole involved chest wall and to the whole lung in patients with lung metastasis. The median age was 8.5 years (range: 1.5 to 17y), 15 (63%) patients were female and 9 were male (37%). The tumor localization was extrathoracic in 18 (75%) and intrathoracic in 6 (25%) patients. Mediastinal lymph node and distant metastasis (DM) was present in 5 (21%) and 4 (16%) cases at diagnosis, respectively. The median follow-up after RT was 47 months (range: 11 to 162mo). The 2-year and 5-year overall survival, event-free survival, local recurrence-free survival, and pleural recurrence-free survival were 83% and 48%, 48% and 42%, 74% and 48%, and 61% and 52%, respectively. The overall local control rate was 83% and the pleural control rate was 67%. RT was well tolerated, with 1 case of grade 3 acute dermatitis and 1 case of grade 3 subacute radiation pneumonitis. Late toxicity was observed in 3 (13%) cases. Long-term survival can be achieved with extended-field RT even in patients with ES/PNET of the chest wall with DM. The low toxicity rates allow us to draw the conclusion that RT with modern techniques is an effective and safe treatment modality for these patients.

Comparison of deep inspiration breath hold and free breathing intensity modulated proton therapy of locally advanced lung cancer

Background and purposeFor locally advanced non-small cell lung cancer (LA-NSCLC), intensity-modulated proton therapy (IMPT) can reduce organ at risk (OAR) doses compared to intensity-modulated radiotherapy (IMRT). Deep inspiration breath hold (DIBH) reduces OAR doses compared to free breathing (FB) in IMRT. In IMPT, differences in dose distributions and robustness between DIBH and FB are unclear. In this study, we compare DIBH to FB in IMPT, and IMPT to IMRT. Materials and methodsFortyone LA-NSCLC patients were prospectively included. 4D computed tomography images (4DCTs) and DIBH CTs were acquired for treatment planning and during weeks 1 and 3 of treatment. A new system for automated robust planning was developed and used to generate a FB and a DIBH IMPT plan for each patient. Plans were compared in terms of dose-volume parameters and normal tissue complication probabilities (NTCPs). Dose recalculations on repeat CTs were used to compare inter-fraction plan robustness. ResultsIn IMPT, DIBH reduced median lungs Dmean from 9.3 Gy(RBE) to 8.0 Gy(RBE) compared to FB, and radiation pneumonitis NTCP from 10.9 % to 9.4 % (p < 0.001). Inter-fraction plan robustness for DIBH and FB was similar. Median NTCPs for radiation pneumonitis and mortality were around 9 percentage points lower with IMPT than IMRT (p < 0.001). These differences were much larger than between FB and DIBH within each modality. ConclusionDIBH IMPT resulted in reduced lung dose and radiation pneumonitis NTCP compared to FB IMPT. Inter-fraction robustness was comparable. OAR doses were far lower in IMPT than IMRT.

143 Using ProKnow to explore the incidence of radiation pneumonitis in relation to GTV size in Stage III Non-Small Cell Lung Cancer (NSCLC) concurrent Chemoradiotherapy (cCRT) patients and its impact on survival. A Pilot Study

143 Using ProKnow to explore the incidence of radiation pneumonitis in relation to GTV size in Stage III Non-Small Cell Lung Cancer (NSCLC) concurrent Chemoradiotherapy (cCRT) patients and its impact on survival. A Pilot Study

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.

In-silico CT lung phantom generated from finite-element mesh.

Several lung diseases lead to alterations in regional lung mechanics, including ventilator- and radiation-induced lung injuries. Such alterations can lead to localized underventilation of the affected areas, resulting in the overdistension of the surrounding healthy regions. Thus, there has been growing interest in quantifying the dynamics of the lung parenchyma using regional biomechanical markers. Image registration through dynamic imaging has emerged as a powerful tool to assess lung parenchyma's kinematic and deformation behaviors during respiration. However, the difficulty in validating the image registration estimation of lung deformation, primarily due to the lack of ground-truth deformation data, has limited its use in clinical settings. To address this barrier, we developed a method to convert a finite-element (FE) mesh of the lung into a phantom computed tomography (CT) image, advantageously possessing ground-truth information included in the FE model. The phantom CT images generated from the FE mesh replicated the geometry of the lung and large airways that were included in the FE model. Using spatial frequency response, we investigated the effect of " imaging parameters" such as voxel size (resolution) and proximity threshold values on image quality. A series of high-quality phantom images generated from the FE model simulating the respiratory cycle will allow for the validation and evaluation of image registration-based estimations of lung deformation. In addition, the present method could be used to generate synthetic data needed to train machine-learning models to estimate kinematic biomarkers from medical images that could serve as important diagnostic tools to assess heterogeneous lung injuries.

Transcriptional Changes in Radiation-Induced Lung Injury: A Comparative Analysis of Two Radiation Doses for Preclinical Research.

In a recent stereotactic body radiation therapy animal model, radiation pneumonitis and radiation pulmonary fibrosis were observed at around 2 and 6 weeks, respectively. However, the molecular signature of this model remains unclear. This study aimed to examine the molecular characteristics at these two stages using RNA-seq analysis. Transcriptomic profiling revealed distinct transcriptional patterns for each stage. Inflammatory response and immune cell activation were involved in both stages. Cell cycle processes and response to type II interferons were observed during the inflammation stage. Extracellular matrix organization and immunoglobulin production were noted during the fibrosis stage. To investigate the impact of a 10 Gy difference on fibrosis progression, doses of 45, 55, and 65 Gy were tested. A dose of 65 Gy was selected and compared with 75 Gy. The 65 Gy dose induced inflammation and fibrosis as well as the 75 Gy dose, but with reduced lung damage, fewer inflammatory cells, and decreased collagen deposition, particularly during the inflammation stage. Transcriptomic analysis revealed significant overlap, but differences were observed and clarified in Gene Ontology and KEGG pathway analysis, potentially influenced by changes in interferon-gamma-mediated lipid metabolism. This suggests the suitability of 65 Gy for future preclinical basic and pharmaceutical research connected with radiation-induced lung injury.

From pixels to prognosis: unveiling radiomics models with SHAP and LIME for enhanced interpretability

Radiomics-based prediction models have shown promise in predicting Radiation Pneumonitis (RP), a common adverse outcome of chest irradiation. Τhis study looks into more than just RP: it also investigates a bigger shift in the way radiomics-based models work. By integrating multi-modal radiomic data, which includes a wide range of variables collected from medical images including cutting-edge PET/CT imaging, we have developed predictive models that capture the intricate nature of illness progression. Radiomic features were extracted using PyRadiomics, encompassing intensity, texture, and shape measures. The high-dimensional dataset formed the basis for our predictive models, primarily Gradient Boosting Machines (GBM)—XGBoost, LightGBM, and CatBoost. Performance evaluation metrics, including Multi-Modal AUC-ROC, Sensitivity, Specificity, and F1-Score, underscore the superiority of the Deep Neural Network (DNN) model. The DNN achieved a remarkable Multi-Modal AUC-ROC of 0.90, indicating superior discriminatory power. Sensitivity and specificity values of 0.85 and 0.91, respectively, highlight its effectiveness in detecting positive occurrences while accurately identifying negatives. External validation datasets, comprising retrospective patient data and a heterogeneous patient population, validate the robustness and generalizability of our models. The focus of our study is the application of sophisticated model interpretability methods, namely SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations), to improve the clarity and understanding of predictions. These methods allow clinicians to visualize the effects of features and provide localized explanations for every prediction, enhancing the comprehensibility of the model. This strengthens trust and collaboration between computational technologies and medical competence. The integration of data-driven analytics and medical domain expertise represents a significant shift in the profession, advancing us from analyzing pixel-level information to gaining valuable prognostic insights.

Clinical outcomes of interstitial lung abnormalities: a systematic review and meta-analysis

Interstitial lung abnormalities (ILA), incidental findings on computed tomography scans, have raised concerns due to their association with worse clinical outcomes. Our meta-analysis, which included studies up to April 2023 from PubMed/MEDLINE, Embase, and Cochrane Library, aimed to clarify the impact of ILA on mortality, lung cancer development, and complications from lung cancer treatments. Risk ratios (RR) with 95% confidence intervals (CI) were calculated for outcomes. Analyzing 10 studies on ILA prognosis and 9 on cancer treatment complications, we found that ILA significantly increases the risk of overall mortality (RR 2.62, 95% CI 1.94–3.54; I2 = 90%) and lung cancer development (RR 3.85, 95% CI 2.64–5.62; I2 = 22%). Additionally, cancer patients with ILA had higher risks of grade 2 radiation pneumonitis (RR 2.28, 95% CI 1.71–3.03; I2 = 0%) and immune checkpoint inhibitor-related interstitial lung disease (RR 3.05, 95% CI 1.37–6.77; I2 = 83%) compared with those without ILA. In conclusion, ILA significantly associates with increased mortality, lung cancer risk, and cancer treatment-related complications, highlighting the necessity for vigilant patient management and monitoring.

A deep learning model for translating CT to ventilation imaging: analysis of accuracy and impact on functional avoidance radiotherapy planning.

Radiotherapy planning incorporating functional lung images has the potential to reduce pulmonary toxicity. Free-breathing 4DCT-derived ventilation image (CTVI) may help quantify lung function. This study introduces a novel deep-learning model directly translating planning CT images into CTVI. We investigated the accuracy of generated images and the impact on functional avoidance planning. Paired planning CT and 4DCT scans from 48 patients with NSCLC were randomized to training (n = 41) and testing (n = 7) data sets. The ventilation maps were generated from 4DCT using a Jacobian-based algorithm to provide ground truth labels (CTVI4DCT). A 3D U-Net-based model was trained to map CT to synthetic CTVI (CTVISyn) and validated using fivefold cross-validation. The highest-performing model was applied to the testing set. Spearman's correlation (rs) and Dice similarity coefficient (DSC) determined voxel-wise and functional-wise concordance between CTVI4DCT and CTVISyn. Three plans were designed per patient in the testing set: one clinical plan without CTVI and two functional avoidance plans combined with CTVI4DCT or CTVISyn, aimed at sparing high-functional lungs defined as the top 50% of the percentile ventilation ranges. Dose-volume (DVH) parameters regarding the planning target volume (PTV) and organs at risk (OARs) were recorded. Radiation pneumonitis (RP) risk was estimated using a dose-function (DFH)-based normal tissue complication probability (NTCP) model. CTVISyn showed a mean rs value of 0.65 ± 0.04 compared to CTVI4DCT. Mean DSC values over the top 50% and 60% of ventilation ranges were 0.41 ± 0.07 and 0.52 ± 0.10, respectively. In the test set (n = 7), all patients' RP-risk benefited from CTVI4DCT-guided plans (Riskmean_4DCT_vs_Clinical: 29.24% vs. 49.12%, P = 0.016), and six patients benefited from CTVISyn-guided plans (Riskmean_Syn_vs_Clinical: 31.13% vs. 49.12%, P = 0.022). There were no significant differences in DVH and DFH metrics between CTVISyn and CTVI4DCT-guided plan (P > 0.05). Using deep-learning techniques, CTVISyn generated from planning CT exhibited a moderate-to-high correlation with CTVI4DCT. The CTVISyn-guided plans were comparable to the CTVI4DCT-guided plans, effectively reducing pulmonary toxicity in patients while maintaining acceptable plan quality. Further prospective trials are needed to validate these findings.

Application of dose-gradient function in reducing radiation induced lung injury in breast cancer radiotherapy.

Try to create a dose gradient function (DGF) and test its effectiveness in reducing radiation induced lung injury in breast cancer radiotherapy. Radiotherapy plans of 30 patients after breast-conserving surgery were included in the study. The dose gradient function was defined as DGH=VDVp3, then the area under the DGF curve of each plan was calculated in rectangular coordinate system, and the minimum area was used as the trigger factor, and other plans were triggered to optimize for area reduction. The dosimetric parameters of target area and organs at risk in 30 cases before and after re-optimization were compared. On the premise of ensuring that the target dose met the clinical requirements, the trigger factor obtained based on DGF could further reduce the V5, V10, V20, V30 and mean lung dose (MLD) of the ipsilateral lung in breast cancer radiotherapy, P < 0.01. And the D2cc and mean heart dose (MHD) of the heart were also reduced, P < 0.01. Besides, the NTCPs of the ipsilateral lung and the heart were also reduced, P < 0.01. The trigger factor obtained based on DGF is efficient in reducing radiation induced lung injury in breast cancer radiotherapy.

Safety and Efficacy of Moderate-Intensity Stereotactic Body Radiation Therapy for Ultra-Central Lung Tumor.

Background and Objectives: Ultra-central (UC) lung tumors are defined as those abutting the proximal bronchial tree. Stereotactic body radiation therapy (SBRT) for UC tumors is difficult because of concerns about severe toxicities. Therefore, we report the safety and efficacy of moderate-intensity SBRT for UC tumors at our institution. Materials and Methods: From January 2017 to May 2021, we treated 20 patients with UC tumors with SBRT at a dose of 45-60 Gy in 10 fractions. The primary endpoints were local control (LC) and overall survival (OS). Results: The median follow-up time was 15.8 months (range: 2.7-53.8 months). Ten of the 20 patients (50.0%) showed a complete response, five (25.0%) had a partial response, two (10.0%) had stable disease, and three (15.0%) showed progressive disease (PD). The response and disease control rates were 75.0% and 85.0%, respectively. Patients with PD showed local progression at median 8.3 months (range: 6.8-19.1 months) after SBRT. One-year and 2-year OS rates were 79.4% and 62.4%, respectively. One-year and 2-year LC rates are 87.1% and 76.2%, respectively. Eight patients died due to a non-radiation therapy related cause. One patient experienced grade 5 massive hemoptysis 6 months after SBRT, resulting in death. One patient experienced grade 2 esophageal pain and two experienced grade 2 radiation pneumonitis. Otherwise, no grade 3 or higher toxicities were reported. Conclusions: Moderate-intensity SBRT offers effective control of UC tumors and is a well-tolerated treatment for such tumors.

Synergizing the interaction of single nucleotide polymorphisms with dosiomics features to build a dual-omics model for the prediction of radiation pneumonitis

ObjectiveRadiation pneumonitis (RP) is the major dose-limiting toxicity of thoracic radiotherapy. This study aimed to developed a dual-omics (single nucleotide polymorphisms, SNP and dosiomics) prediction model for symptomatic RP. Materials and methodsThe potential SNPs, which are of significant difference between the RP grade ≥ 3 group and the RP grade ≤ 1 group, were selected from the whole exome sequencing SNPs using the Fisher’s exact test. Patients with lung cancer who received thoracic radiotherapy at our institution from 2009 to 2016 were enrolled for SNP selection and model construction. The factorization machine (FM) method was used to model the SNP epistasis effect, and to construct the RP prediction model (SNP-FM). The dosiomics features were extracted, and further selected using the minimum redundancy maximum relevance (mRMR) method. The selected dosiomics features were added to the SNP-FM model to construct the dual-omics model. ResultsFor SNP screening, peripheral blood samples of 28 patients with RP grade ≥ 3 and the matched 28 patients with RP grade ≤ 1 were sequenced. 81 SNPs were of significant difference (P < 0.015) and considered as potential SNPs. In addition, 21 radiation toxicity related SNPs were also included. For model construction, 400 eligible patients (including 108 RP grade ≥ 2) were enrolled. Single SNP showed no strong correlation with RP. On the other hand, the SNP-SNP interaction (epistasis effect) of 19 SNPs were modeled by the FM method, and achieved an area under the curve (AUC) of 0.76 in the testing group. In addition, 4 dosiomics features were selected and added to the model, and increased the AUC to 0.81. ConclusionsA novel dual-omics model by synergizing the SNP epistasis effect with dosiomics features was developed. The enhanced the RP prediction suggested its promising clinical utility in identifying the patients with severe RP during thoracic radiotherapy.