Risk Of Radiation Pneumonitis Research Articles

Computed chest radiography for total body irradiation: image quality and clinical feasibility

Objective. In myeloablative total body irradiation (TBI), lung shielding blocks are used to reduce the dose to the lungs and hence decrease the risk of radiation pneumonitis. Some centers are still using mega-Volt (MV) imaging with dedicated silver halide-based films during simulation and treatment for lung delineation and position verification. However, the availability of these films has recently become an issue. This study examines the clinical performance of a computed radiography (CR) solution in comparison to radiographic films and potential improvement of image quality by filtering and post-processing. Approach. We compared BaFBrI-based CR plates to radiographic films. First, images of an aluminum block were analyzed to assess filter impact on scatter reduction. Secondly, a dedicated image quality phantom was used to assess signal linearity, signal-to-noise ratio (SNR), contrast and spatial resolution. Ultimately, a clinical performance study involving two impartial observers was conducted on an anthropomorphic chest phantom, employing visual grading analysis (VGA). Various filter materials and positions as well as post-processing were examined, and the workflow between CR and film was compared. Main results. CR images exhibited high SNR and linearity but demonstrated lower spatial and contrast resolution when compared to film. However, filtering improved contrast resolution and SNR, while positioning filters inside the cassette additionally enhanced sharpness. Image processing improved VGA scores, while additional filtering also resulted in higher spine visibility scores. CR shortened TBI simulation by over 10 minutes for one patient, alongside a dose reduction by order of 0.1 Gy. Significance. This study highlights potential advantages of shifting from conventional radiographic film to CR for TBI. Overall, CR with the incorporation of processing and filtering proves to be suitable for TBI chest imaging. When compared to radiographic film, CR offers advantages such as reduced simulation time and dose delivery, re-usability of image plates and digital workflow integration.

Evaluation of Tumor Control and Normal Tissue Complication Probabilities in Patients Receiving Comprehensive Nodal Irradiation for Left-Sided Breast Cancer.

Women with left-sided breast cancer receiving adjuvant radiotherapy have increased incidence of cardiac mortality due to ischemic heart disease; to date, no threshold dose for late cardiac/pulmonary morbidity or mortality has been established. We investigated the likelihood of cardiac death and radiation pneumonitis in women with left-sided breast cancer who received comprehensive lymph node irradiation. The differences in dosimetric parameters between free-breathing (FB) and deep inspiration breath hold (DIBH) techniques were also addressed. Based on NTCP calculations, the probability of cardiac death was significantly reduced with the DIBH compared to the FB technique (p < 0.001). The risk of radiation pneumonitis was not clinically significant. There was no difference in coverage between FB and DIBH plans. Doses to healthy structures were significantly lower in DIBH plan than in FB plan for V20, V30, and ipsilateral total lung volume. Inspiratory gating reduces the dose absorbed by the heart without compromising the target range, thus reducing the likelihood of cardiac death.

Abstract 7396: Development of deep neural networks that guide more individualized radiotherapy to the lung

Abstract Introduction: Radiotherapy is dependent on an expert-based model that impedes implementation of many potentially useful applications that could aid decision makers. This model is a barrier to a learning healthcare system due to noise introduced by decision-maker variation. Surmounting this barrier will require compelling clinical outcome data and highly useful and accurate information systems. We sought to develop new augmented-intelligence capabilities to better predict both high-dose lung irradiation treatment efficacy (i.e., local tumor control) and toxicity (i.e., radiation-induced pneumonitis). Methods: We curated one of the largest datasets of lung stereotactic body radiotherapy (SBRT) datasets globally (~1200 cases). We input pre-therapy lung computed tomography (CT) images using a bounding box approach that captures the gross tumor volume and adjacent normal lung into a multi-task deep neural network to generate an image fingerprint that predicts local failures after treatment. Separately, we input axial slices from CT scans of the lung into convolutional neural network (CNN) and trained using an outcome per slice method. We then aggregated intra-patient slices into a recurrent neural network (RNN) to estimate individual patient risk for pneumonitis. We validated our findings with the independent study cohort. Risk scores for local failure and pneumonitis were combined with clinical variables to assess the relative contribution of the deep learning-derived image risk scores. Results: A total of 1045 patients met our eligibility criteria. Radiation treatments in patients with high local failure risk scores failed at a significantly higher rate than in patients with low scores; 3-year cumulative incidence of local failure in the internal study cohort was 20·3% (16·0-24·9) in patients with high scores and 5·7% (95% CI 3·5-8·8) in patients with low scores (hazard ratio [HR]=3·64 [95% CI 2·19-6·05], p&amp;lt;0·0001). Models that included the local failure risk score and clinical variables predicted treatment failures with a concordance index (C-index) of 0·72 (95% CI 0·67-0·77), a significant improvement compared with classical radiomics (p&amp;lt;0·0001) or clinical variables (p&amp;lt;0·0001) alone. Radiation pneumonitis risk scores were highly predictive of toxicity, with an accuracy and CI of 0.78 (95% CI 0.72-0.85). A model that includes dosimetry variates (V20), improved the CI to 0.85 (95% CI 0.80-0.90). Conclusions: The image-based deep learning frameworks developed herein represent the first opportunity to use medical images to individualize radiotherapy dose and toxicity predictions. Our results signify a new roadmap for deep learning-guided predictions and treatment guidance in the image-replete and highly standardized discipline of radiation oncology. A phase 2 study assessing machine-derived dose predictions is currently enrolling patients. Citation Format: Mohamed Abazeed. Development of deep neural networks that guide more individualized radiotherapy to the lung [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7396.

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.

Radiation pneumonitis after concurrent aumolertinib and thoracic radiotherapy in EGFR-mutant non-small cell lung cancer patients

BackgroundThe superior efficacy of concurrent thoracic radiotherapy (TRT) and epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) has been proven in locally advanced and advanced non-small cell lung cancer (NSCLC) patients with EGFR mutations. However, the high incidence of radiation pneumonitis (RP) reduced by concurrent TRT and TKIs has attracted widespread attention. Thus, this study was designed to investigate the rate and risk factors for RP in EGFR-positive NSCLC patients simultaneously treated with aumolertinib and TRT. MethodsWe retrospectively evaluated stage IIIA-IVB NSCLC patients treated with concurrent aumolertinib and TRT between May 2020 and December 2022 at Shandong Cancer Hospital and Institute, Shandong, China. RP was diagnosed by two senior radiologists and then graded from 1 to 5 according to the Common Terminology Criteria for Adverse Events v5.0. All risk factors were evaluated by univariate and multivariate logistic regression analyses.ResultsA total of 49 patients were included, the incidence of grade ≥ 2 RP was 42.9%. Grade 2 and 3 RP were observed in 28.6% and 14.3% of patients, respectively. Grade 4 to 5 RP were not observed. the gross total volume (GTV) ≥ 21 ml and ipsilateral lung V20 ≥ 25% were risk factors for RP. The median progression-free survival (PFS) in the first-line therapy group and second-line therapy group were 23.5 months and 17.2 months, respectively (p = 0.10).ConclusionsBetter local control is achieved with concurrent TRT and aumolertinib, and special attention should be given to controlling ipsilateral lung V20 and GTV to reduce the risk of RP.

Deep-Learning Model Prediction of Radiation Pneumonitis Using Pretreatment Chest Computed Tomography and Clinical Factors.

Objectives: This study aimed to build a comprehensive deep-learning model for the prediction of radiation pneumonitis using chest computed tomography (CT), clinical, dosimetric, and laboratory data. Introduction: Radiation therapy is an effective tool for treating patients with lung cancer. Despite its effectiveness, the risk of radiation pneumonitis limits its application. Although several studies have demonstrated models to predict radiation pneumonitis, no reliable model has been developed yet. Herein, we developed prediction models using pretreatment chest CT and various clinical data to assess the likelihood of radiation pneumonitis in lung cancer patients. Methods: This retrospective study analyzed 3-dimensional (3D) lung volume data from chest CT scans and 27 features including dosimetric, clinical, and laboratory data from 548 patients who were treated at our institution between 2010 and 2021. We developed a neural network, named MergeNet, which processes lung 3D CT, clinical, dosimetric, and laboratory data. The MergeNet integrates a convolutional neural network with subsequent fully connected layers. A support vector machine (SVM) and light gradient boosting machine (LGBM) model were also implemented for comparison. For comparison, the convolution-only neural network was implemented as well. Three-dimensional Resnet-10 network and 4-fold cross-validation were used. Results: Classification performance was quantified by using the area under the receiver operative characteristic curve (AUC) metrics. MergeNet showed the AUC of 0.689. SVM, LGBM, and convolution-only networks showed AUCs of 0.525, 0.541, and 0.550, respectively. Application of DeLong test to pairs of receiver operating characteristic curves respectively yielded P values of .001 for the MergeNet-SVM pair and 0.001 for the MergeNet-LGBM pair. Conclusion: The MergeNet model, which incorporates chest CT, clinical, dosimetric, and laboratory data, demonstrated superior performance compared to other models. However, since its prediction performance has not yet reached an efficient level for clinical application, further research is required. Contribution: This study showed that MergeNet may be an effective means to predict radiation pneumonitis. Various predictive factors can be used together for the radiation pneumonitis prediction task via the MergeNet.

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.

Decreased risk of radiation pneumonitis with concurrent use of renin-angiotensin system inhibitors in thoracic radiation therapy of lung cancer.

Radiation pneumonitis (RP) is the primary dose-limiting toxicity associated with radiotherapy. This study aimed to observe the effects of renin-angiotensin system inhibitors in Chinese patients with lung cancer who received thoracic radiation. Patients with lung cancer who received thoracic radiation at a total dose of ≥45 Gray between October 2017 and December 2022 were enrolled in this study. We retrospectively evaluated the factors influencing grade 2 or higher RP. A total of 320 patients were enrolled in this study; 62 patients were identified as angiotensin receptor blockers or angiotensin-converting enzyme inhibitor users. Additionally, 99 patients (30.9%) had grade 2 or higher RP, and the incidence in the renin-angiotensin system inhibitor group was 17.7% (11 out of 62 patients). Patients in the renin-angiotensin system inhibitors (RASi) group were older and had a higher percentage of males, lower percentage of ECOG score 0, higher percentage of hypertension, and higher percentage of adenocarcinoma than those in the non-RASi group. ECOG score [hazard ratio (HR) = 1.69, p = 0.009], history of smoking (HR = 1.76, p = 0.049), mean dose (HR = 3.63, p = 0.01), and RASi (HR = 0.3, p = 0.003) were independent predictive factors for RP. All subgroups benefited from RASi. This study showed that oral RASi administration has the potential to mitigate the incidence of grade 2 or higher RP in patients with lung cancer undergoing thoracic radiotherapy. To validate and further substantiate these findings, additional prospective research is warranted.

Association of Single Nucleotide Polymorphisms in Transforming Growth Factor-β1 Pathway and Risk of Radiation Pneumonitis in Lung Cancer Patients Treated with Thoracic Radiation Therapy

Several clinical and dosimetric parameters are known to be associated with radiation-induced lung toxicity, including radiation pneumonitis (RP). Also, single nucleotide polymorphisms (SNPs) of genes in TGF-β1 pathway have a notable association with the RP. However, studies on the predictive value of SNPs for RP are still limited. Herein, we tried to develop a novel integrated predictive model for severe RP in lung cancer patients. A total of 59 patients who were treated with definitive or preoperative radiotherapy for primary lung cancer and had DNA samples were included. Potentially functional and tagging SNPs of TGF-β1 (rs1800469, rs1800471, rs1982073, and rs11466345), BMP2 (rs235768, rs3178250, rs1979855, and rs170986), and BMP4 (rs17563, rs4898820, and rs762642) were genotyped. Logistic regression was performed to build severe (grade ≥2) RP prediction models, and best subset selection algorithm with L0 and L2 regulations was used for variable selection. Only clinical/dosimetric variables were evaluated in model 1, and those variables as well as SNPs were included in model 2. Using beta coefficient obtained by the logistic regression, a scoring system was also developed. With median follow-up of 39.7 months, severe RP occurred in 20.3% of patients. In model 1, age (>66) and PTV volume (≥300 cc) were significant factors (p = 0.016, OR 8.820 [95% CI, 1.730-63.800]; and p = 0.024, OR 7.440 [95% CI, 1.460-52.100], respectively). In model 2, the above two factors (p = 0.010, OR 16.200 [95% CI, 2.440-187.000] and p = 0.025, OR 10.100 [95% CI, 1.610-105.000]) and the AG/GG genotype in BMP2 rs1979855 were significant factors (p = 0.031, OR 7.260 [95% CI, 1.380-59.100]). The AUC was significantly higher in model 2 than in model 1 (0.822 vs. 0.741, p = 0.029). According to developed scoring system, patients with a score >2.8 are more likely to experience severe RP (AUC 0.829). BMP2 rs1979855 could serve as a reliable biomarker for predicting RP while significantly improving predictive power compared to when only clinical factors were used.

External validation of NTCP-models for radiation pneumonitis in lung cancer patients treated with chemoradiotherapy

PurposeNormal tissue complication probability (NTCP) models can be used to estimate the risk of radiation pneumonitis (RP). The aim of this study was to externally validate the most frequently used prediction models for RP, i.e., the QUANTEC and APPELT models, in a large cohort of lung cancer patients treated with IMRT or VMAT. [1–2] Methods and materialsThis prospective cohort study, included lung cancer patients treated between 2013 and 2018. A closed testing procedure was performed to test the need for model updating. To improve model performance, modification or removal of variables was considered. Performance measures included tests for goodness of fit, discrimination, and calibration. ResultsIn this cohort of 612 patients, the incidence of RP ≥ grade 2 was 14.5%. For the QUANTEC-model, recalibration was recommended which resulted in a revised intercept and adjusted regression coefficient (from 0.126 to 0.224) of the mean lung dose (MLD),. The APPELT-model needed revision including model updating with modification and elimination of variables. After revision, the New RP-model included the following predictors (and regression coefficients): MLD (B = 0.250), age (B = 0.049, and smoking status (B = 0.902). The discrimination of the updated APPELT-model was higher compared to the recalibrated QUANTEC-model (AUC: 0.79 vs. 0.73). ConclusionsThis study demonstrated that both the QUANTEC- and APPELT-model needed revision. Next to changes of the intercept and regression coefficients, the APPELT model improved further by model updating and performed better than the recalibrated QUANTEC model. This New RP-model is widely applicable containing non-tumour site specific variables, which can easily be collected.

Clinical features and risk factors for interstitial lung disease spreading in low-dose irradiated areas after definitive radiotherapy with or without durvalumab consolidation therapy for patients with non-small cell lung cancer

BackgroundThe current standard of care for patients with unresectable locally advanced non-small cell lung cancer (NSCLC) is chemoradiotherapy (CRT) combined with durvalumab consolidation therapy. However, radiotherapy (RT) always carries the risk of radiation pneumonitis (RP), which can preclude durvalumab continuation. In particular, the spread of interstitial lung disease (ILD) in low-dose areas or extending beyond the RT field often makes it difficult to determine the safety of continuation or rechallenging of durvalumab. Thus, we retrospectively analyzed ILD/RP after definitive RT with and without durvalumab, with assessment of radiologic features and dose distribution in RT.MethodsWe retrospectively evaluated the clinical records, CT imaging, and radiotherapy planning data of 74 patients with NSCLC who underwent definitive RT at our institution between July 2016 and July 2020. We assessed the risk factors for recurrence within one year and occurrence of ILD/RP.ResultsKaplan-Meier method showed that ≥ 7 cycles of durvalumab significantly improved 1-year progression free survival (PFS) (p < 0.001). Nineteen patients (26%) were diagnosed with ≥ Grade 2 and 7 (9.5%) with ≥ Grade 3 ILD/RP after completing RT. There was no significant correlation between durvalumab administration and ≥ Grade 2 ILD/RP. Twelve patients (16%) developed ILD/RP that spread outside the high-dose (> 40 Gy) area, of whom 8 (67%) had ≥ Grade 2 and 3 (25%) had Grade 3 symptoms. In unadjusted and multivariate Cox proportional-hazards models adjusted for V20 (proportion of the lung volume receiving ≥ 20 Gy), high HbA1c level was significantly correlated with ILD/RP pattern spreading outside the high-dose area (hazard ratio, 1.842; 95% confidence interval, 1.35–2.51).ConclusionsDurvalumab improved 1-year PFS without increasing the risk of ILD/RP. Diabetic factors were associated with ILD/RP distribution pattern spreading in the lower dose area or outside RT fields, with a high rate of symptoms. Further study of the clinical background of patients including diabetes is needed to safely increase the number of durvalumab doses after CRT.

A multiomics approach-based prediction of radiation pneumonia in lung cancer patients: impact on survival outcome.

To predict the risk of radiation pneumonitis (RP), a multiomics model was built to stratify lung cancer patients. Our study also investigated the impact of RP on survival. This study retrospectively collected 100 RP and 99 matched non-RP lung cancer patients treated with radiotherapy from two independent centres. They were divided into training (n = 175) and validation cohorts (n = 24). The radiomics, dosiomics and clinical features were extracted from planning CT and electronic medical records and were analysed by LASSO Cox regression. A multiomics prediction model was developed by the optimal algorithm. Overall survival (OS) between the RP, non-RP, mild RP, and severe RP groups was analysed by the Kaplan‒Meier method. Sixteen radiomics features, two dosiomics features, and one clinical feature were selected to build the best multiomics model. The optimal performance for predicting RP was the area under the receiver operating characteristic curve (AUC) of the testing set (0.94) and validation set (0.92). The RP patients were divided into mild (≤ 2 grade) and severe (> 2 grade) RP groups. The median OS was 31months for the non-RP group compared with 49months for the RP group (HR = 0.53, p = 0.0022). Among the RP subgroup, the median OS was 57months for the mild RP group and 25months for the severe RP group (HR = 3.72, p < 0.0001). The multiomics model contributed to improving the accuracy of RP prediction. Compared with the non-RP patients, the RP patients displayed longer OS, especially the mild RP patients.

Measurements of target volumes and organs at risk using DW‑MRI in patients with central lung cancer accompanied with atelectasis.

Accurate imaging-based tumor delineation is crucial for guiding the radiotherapy treatments of various solid tumors. Currently, several imaging procedures, including diffusion-weighted magnetic resonance imaging (DW-MRI), intensified computed tomography and positron emission tomography are routinely used for targeted tumor delineation. However, the performance of these imaging procedures has not yet been comprehensively evaluated. In order to address this matter, the present study was conducted in an aim to assess the use of DW-MRI in guiding radiotherapy treatments, by comparing its performance to that of other imaging procedures. Specifically, the exposure dosages to organs at risk, including the lungs, heart and spinal mencord, were evaluated using various radiotherapy regimes. The findings of the present study demonstrated that DW-MRI is a non-invasive and cost-effective imaging procedure that can be used to reduce lung exposure doses, minimizing the risk of radiation pneumonitis. The data further demonstrate the immense potential of the DW-MRI procedure in the precision radiotherapy of lung cancers.

CT ventilation image-guided helical Tomotherapy at sparing functional lungs for locally advanced lung cancer: analysis of dose-function metrics and the impact on pulmonary toxicity

PurposeCT ventilation image (CTVI)-guided radiotherapy that selectively avoids irradiating highly-functional lung regions has potential to reduce pulmonary toxicity. Considering Helical TomoTherapy (HT) has higher modulation capabilities, we investigated the capability and characteristic of HT at sparing functional lungs for locally advanced lung cancer.Methods and materialsPretreatment 4DCT scans were carried out for 17 patients. Local lung volume expansion (or contraction) during inspiration is related to the volume change at a given lung voxel and is used as a surrogate for ventilation. The ventilation maps were generated from two sets of CT images (peak-exhale and peak-inhale) by deformable registration and a Jacobian-based algorithm. Each ventilation map was normalized to percentile images. Six plans were designed for each patient: one anatomical plan without ventilation map and five functional plans incorporating ventilation map which designed to spare varying degrees of high-functional lungs that were defined as the top 10%, 20%, 30%, 40%, and 50% of the percentile ventilation ranges, respectively. The dosimetric and evaluation factors were recorded regarding planning target volume (PTV) and other organs at risk (OARs), with particular attention to the dose delivered to total lung and functional lungs. An established dose-function-based normal tissue complication probability (NTCP) model was used to estimate risk of radiation pneumonitis (RP) for each scenario.ResultsPatients were divided into a benefit group (8 patients) and a non-benefit group (9 patients) based on whether the RP-risk of functional plan was lower than that of anatomical plan. The distance between high-ventilated region and PTV, as well as tumor volume had significant differences between the two groups (P < 0.05). For patients in the benefit group, the mean value of fV5, fV10, fV20, and fMLD (functional V5, V10, V20, and mean lung dose, respectively) were significantly lower starting from top 30% functional plan than in anatomical plan (P < 0.05). With expand of avoidance region in functional plans, the dose coverage of PTV is not sacrificed (P > 0.05) but at the cost of increased dose received by OARs.ConclusionVentilation image-guided HT plans can reduce the dose received by highly-functional lung regions with a range up to top 50% ventilated area. The spatial distribution of ventilation and tumor size were critical factors to better select patients who could benefit from the functional plan.

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.

Systematic risk analysis of radiation pneumonitis in breast cancer: role of cotreatment with chemo-, endocrine, and targeted therapy

PurposeA major complication of sequential and concomitant chemoradiation in breast cancer treatment is interstitial pneumonitis induced by radiation therapy (RT), systemic therapy, or a combination of both. Dose and volume of co-irradiated lung tissue directly correlate with the risk of radiation pneumonitis. Especially in case of combined treatment, it is often unclear which of the used therapeutic agents promote pneumonitis.MethodsThis was a prospective monocentric study including 396 breast cancer patients. A systematic analysis of single and combined therapeutic measures was performed in order to identify treatment-related factors enhancing the risk of pneumonitis post RT.ResultsOverall incidence of pneumonitis of any grade was 38%; 28% were asymptomatic (grade 1) and 10% were symptomatic (> grade 1). Pneumonitis > grade 2 did not occur. Beside age, smoking status, and mean lung dose, the combined treatment with goserelin and tamoxifen significantly enhanced the risk of pneumonitis in a supra-additive pattern (odds ratio [OR] 4.38), whereas each agent alone or combined with other drugs only nonsignificantly contributed to a higher pneumonitis incidence post RT (OR 1.52 and OR 1.16, respectively). None of the other systemic treatments, including taxanes, increased radiation pneumonitis risk in sequential chemoradiation.ConclusionCommon treatment schedules in sequential chemoradiation following breast-conserving surgery only moderately increase lung toxicity, mainly as an asymptomatic complication, or to a minor extent, as transient pneumonitis ≤ grade 2. However, combined treatment with tamoxifen and the LHRH analog goserelin significantly increased the risk of pneumonitis in breast cancer patients after chemoradiation. Thus, closer surveillance of involved patients is advisable.

Radiation pneumonitis in relation to pulmonary function, dosimetric factors, TGFβ1 expression, and quality of life in breast cancer patients receiving post-operative radiotherapy: a prospective 6-month follow-up study.

To investigate development of radiation pneumonitis (RP) in relation to pulmonary function, dosimetric factors, and transforming growth factor beta-1 (TGFβ1) expression in irradiated breast cancer patients. A total of 49 breast cancer patients who received post-operative radiotherapy (RT) were evaluated in terms of pulmonary function tests (PFTs), quality of life (QoL), development of RP, dosimetric factors, cytokine levels, and lung high-resolution computed tomography (HRCT) before and after RT. ROC analysis was performed for performance of dosimetric factors in predicting RP, while frequencies of single nucleotide polymorphisms (SNPs) genotyped for TGFβ1 (rs11466345 and rs1800470) were also evaluated. All cases with RP (10.2%) recovered clinically at the end of third post-RT month. PFT and HRCT parameters were similar before and after RT overall, as well as by RP and the radiation field subgroups. ROC analysis revealed the significant role of the ipsilateral V5 (cutoff value of 45.9%, p = 0.039), V10 (29.4%, p = 0.015), V20 (23%, p = 0.017), and MLD (1200cGy, p = 0.030) in predicting RP. Higher post-RT TGFβ1 levels (p = 0.037) were noted overall and in patients with RP. Patient and control groups were similar in terms of frequencies of SNPs genotyped for TGFβ1 (rs11466345 and rs1800470). EORTC QLQ-C30 and QLQ-BR-23 scores were similar in patients with vs. without RP. Our findings revealed significant role of dosimetric factors including MLD, V20 as well as the low dose-volume metrics in predicting the risk of RP among breast cancer patients who received post-operative RT. Implementation of RT, extent of radiation field or the presence of RP had no significant impact on PFTs.

Development and validation of a random forest model for predicting radiation pneumonitis in lung cancer patients receiving moderately hypofractionated radiotherapy: a retrospective cohort study

Radiation pneumonitis (RP) is a type of toxicity commonly associated with thoracic radiation therapy. We sought to establish a random forest (RF) model and evaluate its ability to predict RP in patients with non-small cell lung cancer (NSCLC) receiving moderately hypofractionated radiotherapy (hypo-RT). A total of 106 patients with stage II-IVa NSCLC who received moderately hypofractionated helical tomotherapy (2.3-3.0 Gy/fraction) at Zhongshan Hospital were included. All enrolled patients were divided chronologically into the training (67 patients) and validation (39 patients) groups. Higher than or equal to grade 2 RP was defined as the end point. Logistic regression and RF models were established and compared using the receiver operating characteristic (ROC) and a confusion matrix in the training and validation groups. The cumulative incidence of the end point was 25.4% and 17.9% in the training and validation groups, respectively. Logistic regression models were constructed by dosage parameters of total lungs, ipsilateral or contralateral lungs, respectively. ROC analysis revealed that the dosimetric factors of total lungs yielded a superior classification performance than did that of the ipsilateral or contralateral lungs [area under the curve (AUC) =0.920, AUC =0.701, and AUC =0.661, respectively]. Furthermore, the RF model yielded a better prediction capacity than did the traditional logistic model based on the dosimetric factors of the total lungs (accuracy: 88.06%; precision: 84.62%; sensitivity: 64.71%; specificity: 96.00%). Moreover, the RF identified mean lung dose [MLD; mean decrease gini (MDG) =5.74], V20 (MDG =4.62), and V35 (MDG =3.08) of total lungs as the most common primary differentiators of RP. Our RF model established based on the dosimetric parameters of the total lungs could accurately predict the RP risk in patients with NSCLC treated with moderately hypofractionated tomotherapy.

Volumetric modulated arc therapy (VMAT) comparison to 3D-conformal technique in lung stereotactic ablative radiotherapy (SABR).

Stereotactic ablative radiotherapy (SABR) can be a curative option for non-small cell lung cancer (NSCLC) and oligometastatic lung disease. Volumetric modulated arc therapy (VMAT) has offered further advancements in terms of radiation dose shaping without compromising treatment times however there is potential for greater low-dose exposure to the lung. This study was to assess whether VMAT lung SABR would result in any increase to the dosimetry parameters compared with three-dimensional conformal radiotherapy (3D-CRT) that could confer increased risk of radiation pneumonitis. A total of 53 and 30 3D-CRT treatment plans of patients treated with 48 Gy in 4 fractions were compared. No statistically significant difference in planning target volumes between the VMAT 29.9 cc (range 12.4-58.5 cc) and 3D-CRT 31.2 cc (range 12.3-58.3 cc) P=0.79. The mean of total lung V5, ipsilateral lung V5 and contralateral lung V5 all showed a trend of being smaller in the VMAT treatment group- 14% versus 15.8%, 25.6% versus 30.4% and 1.6% versus 2.2%, respectively, but all were not statistically significant differences. Mean of the mean lung dose MLD, again showed a trend of being lower in the VMAT treatments but was also non-significant, 2.6 Gy versus 3.0 Gy, P=1.0. Mean V20 was the same in both cohorts, 3.3%. The dosimetry for 3D-CRT and VMAT plans were not significantly different including V5, and therefore we conclude that VMAT treatment is unlikely to be associated with an increased risk of radiation pneumonitis.

Association between DNA Repair Gene Pathway Polymorphisms and Risk of Radiation Pneumonitis: A Systematic Review and Meta-Analysis

<h3>Purpose/Objective(s)</h3> Radiation pneumonitis is a dose-limiting toxicity of radiotherapy. Genetic variation in this pathway affects post-radiotherapy DNA repair and subsequently the level of toxicity. Previous studies published within this area in lung cancer treatment have been inconsistent. Our meta-analysis therefore aimed at examining the effect of SNPs on radiation pneumonitis of lung cancer patients receiving radiotherapy. <h3>Materials/Methods</h3> We performed a systematic review of relevant studies published on or before 12 October 2021 on PubMed, Scopus, Embase, and Web of Science databases. Studies with genotyping data of lung cancer patients receiving radiotherapy were included. Conference abstracts, reviews, non-English articles, studies in which radiotherapy was used as a neoadjuvant therapy were excluded. Quality assessment was performed using the Newcastle-Ottawa Scale (NOS) by two independent reviewers. We calculated the pooled odds ratios and the 95% confidence intervals to evaluate the association between each DNA repair gene pathway polymorphism and all-grade radiation pneumonitis. The allelic, dominant, recessive, homozygous and heterozygous genotype models were used to assess the association. <h3>Results</h3> 706 studies were initially obtained after database searching and de-duplication. 15 studies (2964 patients) were included in the systematic review. The median follow-up time ranged from 3 months to 39.5 months. Under the allelic model, the G allele for NEIL1 gene was significantly associated with a reduced odds of developing radiation pneumonitis compared to the C allele for rs7402844 (OR 0.70, 95% CI: 0.49, 0.99, P = 0.04, I-square = 0%, total number of patients: 341). Similarly, the T allele for APE1 gene was significantly associated with a reduced odds of developing radiation pneumonitis compared to the G allele for rs1130409 (OR 0.59, 95% CI: 0.43, 0.81, P = 0.001, I-square = 0%, total number of patients: 432). Other SNPs were found to have no significant associations with all-grade radiation pneumonitis. <h3>Conclusion</h3> This systematic review and meta-analysis showed that two SNPs in the DNA repair gene pathway are significantly associated with the risks of developing radiation pneumonitis in lung cancer patients. Further cohort studies assessing a combination of DNA repair gene polymorphisms with a greater sample size are needed.