Assessment of heart-substructures auto-contouring accuracy for application in heart-sparing radiotherapy for lung cancer.

Objectives: We validated an auto-contouring algorithm for heart substructures in lung cancer patients, aiming to establish its accuracy and reliability for radiotherapy (RT) planning. We focus on contouring an amalgamated set of subregions in the base of the heart considered to be a new organ at risk, the cardiac avoidance area (CAA), to enable maximum dose limit implementation in lung RT planning. Methods: The study validates a deep-learning model specifically adapted for auto-contouring the CAA (which includes the right atrium, aortic valve root, and proximal segments of the left and right coronary arteries). Geometric, dosimetric, quantitative, and qualitative validation measures are reported. Comparison with manual contours, including assessment of interobserver variability, and robustness testing over 198 cases are also conducted. Results: Geometric validation shows that auto-contouring performance lies within the expected range of manual observer variability despite being slightly poorer than the average of manual observers (mean surface distance for CAA of 1.6 vs 1.2 mm, dice similarity coefficient of 0.86 vs 0.88). Dosimetric validation demonstrates consistency between plans optimized using auto-contours and manual contours. Robustness testing confirms acceptable contours in all cases, with 80% rated as "Good" and the remaining 20% as "Useful." Conclusions: The auto-contouring algorithm for heart substructures in lung cancer patients demonstrates acceptable and comparable performance to human observers. Advances in knowledge: Accurate and reliable auto-contouring results for the CAA facilitate the implementation of a maximum dose limit to this region in lung RT planning, which has now been introduced in the routine setting at our institution.

Demystifying the Results of RTOG 0617: Identification of Dose Sensitive Cardiac Subregions Associated With Overall Survival.

INTRODUCTION: The RTOG 0617 trial presented a worse survival for patients with lung cancer treated in the high-dose (74 Gy) arm. In multivariable models, radiation level and whole-heart volumetric dose parameters were associated with survival. In this work, we consider heart subregions to explain the observed survival difference between radiation levels. METHODS: Voxel-based analysis identified anatomical regions where the dose was associated with survival. Bootstrapping clinical and dosimetric variables into an elastic net model selected variables associated with survival. Multivariable Cox regression survival models assessed the significance of dose to the heart subregion, compared with whole heart v5 and v30. Finally, the trial outcome was assessed after propensity score matching of patients on lung dose, heart subregion dose, and tumor volume. RESULTS: A total of 458 patients were eligible for voxel-based analysis. A region of significance (p < 0.001) was identified in the base of the heart. Bootstrapping selected mean lung dose, radiation level, log tumor volume, and heart region dose. The multivariable Cox model exhibited dose to the heart region (p = 0.02), and tumor volume (p = 0.03) were significantly associated with survival, and radiation level was not significant (p = 0.07). The models exhibited that whole heart v5 and v30 were not associated with survival, with radiation level being significant (p < 0.05). In the matched cohort, no significant survival difference was seen between radiation levels. CONCLUSIONS: Dose to the base of the heart is associated with overall survival, partly removing the radiation level effect, and explaining that worse survival in the high-dose arm is owing, in part, to the heart subregion dose. By defining a heart avoidance region, future dose escalation trials may be feasible.

Cardiac Function Modifies the Impact of Heart Base Dose on Survival: A Voxel-Wise Analysis of Patients With Lung Cancer From the PET-Plan Trial.

INTRODUCTION: Heart dose has emerged as an independent predictor of overall survival in patients with NSCLC treated with radiotherapy. Several studies have identified the base of the heart as a region of enhanced dose sensitivity and a potential target for cardiac sparing. We present a dosimetric analysis of overall survival in the multicenter, randomized PET-Plan trial (NCT00697333) and for the first time include left ventricular ejection fraction (EF) at baseline as a metric of cardiac function. METHODS: A total of 205 patients with inoperable stage II or III NSCLC treated with 60 to 72 Gy in 2 Gy fractions were included in this study. A voxel-wise image-based data mining methodology was used to identify anatomical regions where higher dose was significantly associated with worse overall survival. Univariable and multivariable Cox proportional hazards models tested the association of survival with dose to the identified region, established prognostic factors, and baseline cardiac function. RESULTS: A total of 172 patients remained after processing and censoring for follow-up. At 2-years posttreatment, a highly significant region was identified within the base of the heart (p < 0.005), centered on the origin of the left coronary artery and the region of the atrioventricular node. In multivariable analysis, the number of positron emission tomography-positive nodes (p = 0.02, hazard ratio = 1.13, 95% confidence interval: 1.02-1.25) and mean dose to the cardiac subregion (p = 0.02, hazard ratio = 1.11 Gy-1, 95% confidence interval: 1.02-1.21) were significantly associated with overall survival. There was a significant interaction between EF and region dose (p = 0.04) for survival, with contrast plots revealing a larger effect of region dose on survival in patients with lower EF values. CONCLUSIONS: This work validates previous image-based data mining studies by revealing a strong association between dose to the base of the heart and overall survival. For the first time, an interaction between baseline cardiac health and heart base dose was identified, potentially suggesting preexisting cardiac dysfunction exacerbates the impact of heart dose on survival.

Heart dose and cardiac comorbidities influence death with a cardiac cause following hypofractionated radiotherapy for lung cancer.

Background: There is increasing evidence of cardiac toxicity of thoracic radiotherapy however, it is difficult to draw conclusions on cardiac dose constraints due to the heterogeneity of published studies. Moreover, few studies record data on cause of death. The aim of this paper is to investigate the relationship between conventional cardiac dosimetric parameters and death with cardiac causes using data from the UK national cause of death registry. Methods: Data on cancer diagnosis, treatment and cause of death following radical lung cancer radiotherapy were obtained from Public Health England for all patients treated at the Christie NHS Foundation Trust between 1/1/10 and 31/12/16. Individuals with metastatic disease and those who received multiple courses of thoracic radiotherapy where excluded. All patients who received > 45Gy in 20 fractions were included. Cardiac cause of death was defined as the following ICD-10 codes on death certificate: I20-I25; I30-I32; I34-I37; I40-I52. Cardiac V5Gy, V30Gy, V50Gy and mean heart dose (MHD) were extracted. Cumulative incidence of death with cardiac causes were plotted for each cardiac dosimetric parameter. Multi-variable Fine and Gray competing risk analysis was used to model predictors for cardiac death with non-cardiac death as a competing risk. Results: Cardiac dosimetric parameters were available for 967 individuals, 110 died with a cardiac cause (11.4%). Patients with a cardiac comorbidity had an increased risk of death with a cardiac cause compared with those without a cardiac comorbidity (2-year cumulative incidence 21.3% v 6.2%, p<0.001). In patients with a pre-existing cardiac comorbidity, heart V30Gy ≥ 15% was associated with higher cumulative incidence of death with a cardiac cause compared to patients with heart V30Gy <15% (2-year rate 25.8% v 17.3%, p=0.05). In patients without a cardiac comorbidity, after adjusting for tumour and cardiac risk factors, MHD (aHR 1.07, 1.01-1.13, p=0.021), heart V5Gy (aHR 1.01, 1-1.13, p=0.05) and heart V30Gy (aHR 1.04, 1-1.07, p=0.039) were associated with cardiac death. Conclusion: The effect of cardiac radiation dose on cardiac-related death following thoracic radiotherapy is different in patients with and without cardiac comorbidities. Therefore patients' cardiovascular risk factors should be identified and managed alongside radiotherapy for lung cancer.

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves.

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

Role of Real-World Data in Assessing Cardiac Toxicity After Lung Cancer Radiotherapy.

Radiation-induced heart disease (RIHD) is a recent concern in patients with lung cancer after being treated with radiotherapy. Most of information we have in the field of cardiac toxicity comes from studies utilizing real-world data (RWD) as randomized controlled trials (RCTs) are generally not practical in this field. This article is a narrative review of the literature using RWD to study RIHD in patients with lung cancer following radiotherapy, summarizing heart dosimetric factors associated with outcome, strength, and limitations of the RWD studies, and how RWD can be used to assess a change to cardiac dose constraints.

Impact of Introducing Intensity Modulated Radiotherapy on Curative Intent Radiotherapy and Survival for Lung Cancer.

Background: Lung cancer survival remains poor. The introduction of Intensity-Modulated Radiotherapy (IMRT) allows treatment of more complex tumours as it improves conformity around the tumour and greater normal tissue sparing. However, there is limited evidence assessing the clinical impact of IMRT. In this study, we evaluated whether the introduction of IMRT had an influence on the proportion of patients treated with curative-intent radiotherapy over time, and whether this had an effect on patient survival. Materials and Methods: Patients treated with thoracic radiotherapy at our institute between 2005 and 2020 were retrospectively identified and grouped into three time periods: A) 2005-2008 (pre-IMRT), B) 2009-2012 (selective use of IMRT), and C) 2013-2020 (full access to IMRT). Data on performance status (PS), stage, age, gross tumour volume (GTV), planning target volume (PTV) and survival were collected. The proportion of patients treated with a curative dose between these periods was compared. Multivariable survival models were fitted to evaluate the hazard for patients treated in each time period, adjusting for PS, stage, age and tumour volume. Results: 12,499 patients were included in the analysis (n=2675 (A), n=3127 (B), and n=6697 (C)). The proportion of patients treated with curative-intent radiotherapy increased between the 3 time periods, from 38.1% to 50.2% to 65.6% (p<0.001). When stage IV patients were excluded, this increased to 40.1% to 58.1% to 82.9% (p<0.001). This trend was seen across all PS and stages. The GTV size increased across the time periods and PTV size decreased. Patients treated with curative-intent during period C had a survival improvement compared to time period A when adjusting for clinical variables (HR=0.725 (0.632-0.831), p<0.001). Conclusion: IMRT was associated with to more patients receiving curative-intent radiotherapy. In addition, it facilitated the treatment of larger tumours that historically would have been treated palliatively. Despite treating larger, more complex tumours with curative-intent, a survival benefit was seen for patients treated when full access to IMRT was available (2013-2020). This study highlights the impact of IMRT on thoracic oncology practice, accepting that improved survival may also be attributed to a number of other contributing factors, including improvements in staging, other technological radiotherapy advances and changes to systemic treatment.

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.

Cardiac Toxicity of Thoracic Radiotherapy: Existing Evidence and Future Directions.

The impact of radiotherapy on the heart has become an area of interest in recent years. Many different cardiac dose-volume constraints have been associated with cardiac toxicity and survival; however, no consistent constraint has been found. Many patients undergoing treatment for lung cancer have risk factors for cardiovascular disease or known cardiac comorbidities; however, there is little evidence on the effects of radiotherapy on the heart in these patients. We aim to provide a summary of the existing literature on cardiac toxicity of lung cancer radiotherapy, propose strategies to avoid and manage cardiac toxicity, and suggest avenues for future research.

Novel Methodology to Investigate the Effect of Radiation Dose to Heart Substructures on Overall Survival.

PURPOSE: For patients with lung cancer treated with radiation therapy, a dose to the heart is associated with excess mortality; however, it is often not feasible to spare the whole heart. Our aim is to define cardiac substructures and dose thresholds that optimally reduce early mortality. METHODS AND MATERIALS: Fourteen cardiac substructures were delineated on 5 template patients with representative anatomies. One thousand one hundred sixty-one patients with non-small cell lung cancer were registered nonrigidly to these 5 template anatomies, and their radiation therapy doses were mapped. Mean and maximum dose to each substructure were extracted, and the means were evaluated as input to prediction models. The cohort was bootstrapped into 2 variable reduction techniques: elastic net least absolute shrinkage and selection operator and the random survival forest model. Each method was optimized to extract variables contributing most to overall survival, and model coefficients were evaluated to select these substructures. The most important variables common to both models were selected and evaluated in multivariable Cox-proportional hazard models. A threshold dose was defined, and Kaplan-Meier survival curves plotted. RESULTS: Nine hundred seventy-eight patients remained after visual quality assurance of the registration. Ranking the model coefficients across the bootstraps selected the maximum dose to the right atrium, right coronary artery, and ascending aorta as the most important factors associated with survival. The maximum dose to the combined cardiac region showed significance in the multivariable model, a hazard ratio of 1.01/Gy, and P = .03 after accounting for tumor volume (P < .001), N stage (P < .01), and performance status (P = .01). The optimal threshold for the maximum dose, equivalent dose in 2-Gy fractions, was 23 Gy. Kaplan-Meier survival curves showed a significant split (log-rank P = .008). CONCLUSIONS: The maximum dose to the combined cardiac region encompassing the right atrium, right coronary artery, and ascending aorta was found to have the greatest effect on patient survival. A maximum equivalent dose in 2-Gy fractions of 23 Gy was identified for consideration as a dose limit in future studies.

Dose surface maps of the heart can identify regions associated with worse survival for lung cancer patients treated with radiotherapy.

BACKGROUND AND PURPOSE: For lung cancer patients treated with radiotherapy, radiation dose to the heart has been associated with overall survival, with volumetric dose statistics widely presented. However, critical cardiac structures are present on the hearts surface, where this approach may be sub-optimal. In this work we present a methodology for creating cardiac surface dose maps and identify regions where excess dose is associated with in worse overall survival. MATERIAL AND METHODS: A modified cylindrical coordinate system was implemented to map the cardiac surface dose for lung cancer patients. Validation was performed by mapping the cardiac chambers for 55 patients, fitting a point spread function (PSF) to the blurred edge. To account for this uncertainty, dose maps were blurred by a 2D-Gaussian with width described by the PSF. Permutation testing identified regions where excess dose was associated with worse patient survival. The 99th percentile of the max t-value then defined a cardiac surface region to extract dose, from each patient, to be analysed in a multivariable cox-proportional hazards survival model. RESULTS: Cardiac surface maps were created for 648 lung cancer patients. Cardiac surface dose maps were blurred with a 2D- Gaussian filter of size σφ = 4.3° and σy = 1.3units to account for mapping uncertainties. Permutation testing identified significant differences across the surface of the right atria, p < 0.001, at all timepoints. The median dose to the region defined by the 99th percentile of the maximum t-value was 18.5 Gy. Multivariable analysis showed the dose to this region was significantly associated with survival, hazard ratio 1.01 Gy-1, p = 0.03, controlling for confounding variables. CONCLUSIONS: Cardiac surface mapping was successfully implemented and identified a region where excess dose was associated with worse patient survival. This region extended over the right atria, potentially suggesting an interaction with the hearts electrical conduction system.

The evolving role of radiotherapy in non-small cell lung cancer.

Lung cancer is the most commonly diagnosed cancer and biggest cause of cancer mortality worldwide with non-small cell lung cancer (NSCLC) accounting for most cases. Radiotherapy (RT) plays a key role in its management and is used at least once in over half of patients in both curative and palliative treatments. This narrative review will demonstrate how the evolution of RT for NSCLC has been underpinned by improvements in RT technology. These improvements have facilitated geometric individualization, increasingly accurate treatment and now offer the ability to deliver truly individualized RT. In this review, we summarize and discuss recent developments in the field of advanced RT in early stage, locally advanced and metastatic NSCLC. We highlight limitations in current approaches and discuss future potential treatment strategies for patients with NSCLC.

Stereotactic radiosurgery for the treatment of brain metastases: impact of cerebral disease burden on survival.

Stereotactic radiosurgery (SRS) for brain metastases has been carried out at the Leeds Gamma Knife Centre since March 2009. The aim of this study was to examine the outcomes and toxicity in our initial cohort of patients. The medical records of patients with brain metastases referred to the Leeds Gamma Knife Centre between March 2009 and July 2010 were retrospectively reviewed. Data on survival, primary tumour, Karnofsky performance status, time from diagnosis to identification of brain metastases, previous treatment for brain metastases and results of staging prior to SRS were recorded. Patients were followed up with regular magnetic resonance imaging of the brain for a minimum of 6 months and data on toxicity and oral steroid dose were recorded. Statistical analysis was carried out using SPSS v14.0. Survival curves were compared using the Log Rank test. Fifty eight patients (19 male) had a median survival of 50.4 weeks (95% CI, 32.6-68.2 weeks). Lung (36%) and breast (27%) were the most common primary tumours. Patients with a total volume of metastases treated < 5000 mm(3) (p = 0.007) or between 5000 mm(3) and 10,000 mm(3) (p = 0.01) had significantly improved survival compared with patients with a total treated volume > 10,000 mm(3). In addition, largest treated lesion < 5000 mm(3) was a positive prognostic factor. Patients with a single metastasis did not survive significantly longer than those with multiple metastases. Steroid dose dropped significantly after SRS (p < 0.01) and was the same or less in 91% of patients. There were only three cases of grade 3 toxicity. Our study reports survival comparable with other series on radiosurgery and demonstrates a significant decrease in steroid dose following treatment. It also shows that the size of the largest treated metastasis and total volume of metastatic disease seemed a better predictor of outcome than number of metastases treated.