A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy.

BACKGROUND AND PURPOSE: Artificial Intelligence (AI) models in radiation therapy are being developed with increasing pace. Despite this, the radiation therapy community has not widely adopted these models in clinical practice. A cohesive guideline on how to develop, report and clinically validate AI algorithms might help bridge this gap. METHODS AND MATERIALS: A Delphi process with all co-authors was followed to determine which topics should be addressed in this comprehensive guideline. Separate sections of the guideline, including Statements, were written by subgroups of the authors and discussed with the whole group at several meetings. Statements were formulated and scored as highly recommended or recommended. RESULTS: The following topics were found most relevant: Decision making, image analysis, volume segmentation, treatment planning, patient specific quality assurance of treatment delivery, adaptive treatment, outcome prediction, training, validation and testing of AI model parameters, model availability for others to verify, model quality assurance/updates and upgrades, ethics. Key references were given together with an outlook on current hurdles and possibilities to overcome these. 19 Statements were formulated. CONCLUSION: A cohesive guideline has been written which addresses main topics regarding AI in radiation therapy. It will help to guide development, as well as transparent and consistent reporting and validation of new AI tools and facilitate adoption.

Stereotactic Body Radiotherapy for Centrally Located Inoperable Early-Stage NSCLC: EORTC 22113-08113 LungTech Phase II Trial Results.

INTRODUCTION: The international phase II single-arm LungTech trial 22113-08113 of the European Organization for Research and Treatment of Cancer assessed the safety and efficacy of stereotactic body radiotherapy (SBRT) in patients with centrally located early-stage NSCLC. METHODS: Patients with inoperable non-metastatic central NSCLC (T1-T3 N0 M0, ≤7cm) were included. After prospective central imaging review and radiation therapy quality assurance for any eligible patient, SBRT (8 × 7.5 Gy) was delivered. The primary endpoint was freedom from local progression probability three years after the start of SBRT. RESULTS: The trial was closed early due to poor accrual related to repeated safety-related pauses in recruitment. Between August 2015 and December 2017, 39 patients from six European countries were included and 31 were treated per protocol and analyzed. Patients were mainly male (58%) with a median age of 75 years. Baseline comorbidities were mainly respiratory (68%) and cardiac (48%). Median tumor size was 2.6 cm (range 1.2-5.5) and most cancers were T1 (51.6%) or T2a (38.7%) N0 M0 and of squamous cell origin (48.4%). Six patients (19.4%) had an ultracentral tumor location. The median follow-up was 3.6 years. The rates of 3-year freedom from local progression and overall survival were 81.5% (90% confidence interval [CI]: 62.7%-91.4%) and 61.1% (90% CI: 44.1%-74.4%), respectively. Cumulative incidence rates of local, regional, and distant progression at three years were 6.7% (90% CI: 1.6%-17.1%), 3.3% (90% CI: 0.4%-12.4%), and 29.8% (90% CI: 16.8%-44.1%), respectively. SBRT-related acute adverse events and late adverse events ≥ G3 were reported in 6.5% (n = 2, including one G5 pneumonitis in a patient with prior interstitial lung disease) and 19.4% (n = 6, including one lethal hemoptysis after a lung biopsy in a patient receiving anticoagulants), respectively. CONCLUSIONS: The LungTech trial suggests that SBRT with 8 × 7.5Gy for central lung tumors in inoperable patients is associated with acceptable local control rates. However, late severe adverse events may occur after completion of treatment. This SBRT regimen is a viable treatment option after a thorough risk-benefit discussion with patients. To minimize potentially fatal toxicity, careful management of dose constraints, and post-SBRT interventions is crucial.

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.

Dose-dependent changes in cardiac function, strain and remodelling in a preclinical model of heart base irradiation.

BACKGROUND AND PURPOSE: Radiation induced cardiotoxicity (RICT) is as an important sequela of radiotherapy to the thorax for patients. In this study, we aim to investigate the dose and fractionation response of RICT. We propose global longitudinal strain (GLS) as an early indicator of RICT and investigate myocardial deformation following irradiation. METHODS: RICT was investigated in female C57BL/6J mice in which the base of the heart was irradiated under image-guidance using a small animal radiation research platform (SARRP). Mice were randomly assigned to a treatment group: single-fraction dose of 16 Gy or 20 Gy, 3 consecutive fractions of 8.66 Gy, or sham irradiation; biological effective doses (BED) used were 101.3 Gy, 153.3 Gy and 101.3 Gy respectively. Longitudinal transthoracic echocardiography (TTE) was performed from baseline up to 50 weeks post-irradiation to detect structural and functional effects. RESULTS: Irradiation of the heart base leads to BED-dependent changes in systolic and diastolic function 50 weeks post-irradiation. GLS showed significant decreases in a BED-dependent manner for all irradiated animals, as early as 10 weeks after irradiation. Early changes in GLS indicate late changes in cardiac function. BED-independent increases were observed in the left ventricle (LV) mass and volume and myocardial fibrosis. CONCLUSIONS: Functional features of RICT displayed a BED dependence in this study. GLS showed an early change at 10 weeks post-irradiation. Cardiac remodelling was observed as increases in mass and volume of the LV, further supporting our hypothesis that dose to the base of the heart drives the global heart toxicity.

Voxel-based analysis: Roadmap for clinical translation.

Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.

Dose outside of the prostate is associated with improved outcomes for high-risk prostate cancer patients treated with brachytherapy boost.

Background: One in three high-risk prostate cancer patients treated with radiotherapy recur. Detection of lymph node metastasis and microscopic disease spread using conventional imaging is poor, and many patients are under-treated due to suboptimal seminal vesicle or lymph node irradiation. We use Image Based Data Mining (IBDM) to investigate association between dose distributions, and prognostic variables and biochemical recurrence (BCR) in prostate cancer patients treated with radiotherapy. We further test whether including dose information in risk-stratification models improves performance. Method: Planning CTs, dose distributions and clinical information were collected for 612 high-risk prostate cancer patients treated with conformal hypo-fractionated radiotherapy, intensity modulated radiotherapy (IMRT), or IMRT plus a single fraction high dose rate (HDR) brachytherapy boost. Dose distributions (including HDR boost) of all studied patients were mapped to a reference anatomy using the prostate delineations. Regions where dose distributions significantly differed between patients that did and did-not experience BCR were assessed voxel-wise using 1) a binary endpoint of BCR at four-years (dose only) and 2) Cox-IBDM (dose and prognostic variables). Regions where dose was associated with outcome were identified. Cox proportional-hazard models with and without region dose information were produced and the Akaike Information Criterion (AIC) was used to assess model performance. Results: No significant regions were observed for patients treated with hypo-fractionated radiotherapy or IMRT. Regions outside the target where higher dose was associated with lower BCR were observed for patients treated with brachytherapy boost. Cox-IBDM revealed that dose response was influenced by age and T-stage. A region at the seminal vesicle tips was identified in binary- and Cox-IBDM. Including the mean dose in this region in a risk-stratification model (hazard ratio=0.84, p=0.005) significantly reduced AIC values (p=0.019), indicating superior performance, compared with prognostic variables only. The region dose was lower in the brachytherapy boost patients compared with the external beam cohorts supporting the occurrence of marginal misses. Conclusion: Association was identified between BCR and dose outside of the target region in high-risk prostate cancer patients treated with IMRT plus brachytherapy boost. We show, for the first-time, that the importance of irradiating this region is linked to prognostic variables.

Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence.

Purpose: For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer. Methods: 199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported. Results: Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation). Conclusion: In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

Low muscle mass measured at T12 is a prognostic biomarker in unresectable oesophageal cancers receiving chemoradiotherapy.

BACKGROUND AND PURPOSE: Low muscle mass is an imaging biomarker of patient frailty that has been associated with increased toxicity and decreased survival in a number of cancers. Patients with unresectable oesophageal cancer receive chemoradiotherapy as standard of care. Muscle mass is not yet an established prognostic marker in this population. Muscle mass is usually assessed by segmenting skeletal muscle at the L3 vertebral level. But radiotherapy planning scans for oesophageal cancers do not always image this level, which has limited previous studies of body composition. Skeletal muscle is known to regulate immune function, but the association of muscle mass with lymphopenia in cancer patients has not been shown. MATERIALS AND METHODS: We retrospectively analyse 135 oesophageal cancer patients who received chemoradiotherapy and investigate the prognostic value of skeletal muscle area assessed at T12. We also examine the association between muscle mass and radiation-induced lymphopenia. RESULTS: We find that low muscle mass is associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.72 [0.53-0.97]). However, this effect interacts with body mass index (BMI) such that the prognostic value of low muscle mass is removed by high BMI. In our study, patients with low muscle mass were more prone to radiation-induced lymphopenia (75% vs. 50% in patients with high muscle mass). A significant decrease in circulating lymphocytes was associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.68 [0.47-0.99]). CONCLUSION: Our study shows that assessing muscle mass at T12 is feasible and provides prognostic information. Low muscle mass at T12 is associated with poorer overall survival and increased risk of radiation-induced lymphopenia. Muscle mass provides additional information over performance status and BMI. Low BMI patients are most affected by low muscle mass, highlighting the importance of close nutritional support in this population.

Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings.

PURPOSE: To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy. MATERIAL AND METHODS: Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI). RESULTS: 195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features. CONCLUSION: Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation.

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.

Spatial Gene Expression Changes in the Mouse Heart After Base-Targeted Irradiation.

PURPOSE: Radiation cardiotoxicity (RC) is a clinically significant adverse effect of treatment for patients with thoracic malignancies. Clinical studies in lung cancer have indicated that heart substructures are not uniformly radiosensitive, and that dose to the heart base drives RC. In this study, we aimed to characterize late changes in gene expression using spatial transcriptomics in a mouse model of base regional radiosensitivity. METHODS AND MATERIALS: An aged female C57BL/6 mouse was irradiated with 16 Gy delivered to the cranial third of the heart using a 6 × 9 mm parallel opposed beam geometry on a small animal radiation research platform, and a second mouse was sham-irradiated. After echocardiography, whole hearts were collected at 30 weeks for spatial transcriptomic analysis to map gene expression changes occurring in different regions of the partially irradiated heart. Cardiac regions were manually annotated on the capture slides and the gene expression profiles compared across different regions. RESULTS: Ejection fraction was reduced at 30 weeks after a 16 Gy irradiation to the heart base, compared with the sham-irradiated controls. There were markedly more significant gene expression changes within the irradiated regions compared with nonirradiated regions. Variation was observed in the transcriptomic effects of radiation on different cardiac base structures (eg, between the right atrium [n = 86 dysregulated genes], left atrium [n = 96 dysregulated genes], and the vasculature [n = 129 dysregulated genes]). Disrupted biological processes spanned extracellular matrix as well as circulatory, neuronal, and contractility activities. CONCLUSIONS: This is the first study to report spatially resolved gene expression changes in irradiated tissues. Examination of the regional radiation response in the heart can help to further our understanding of the cardiac base's radiosensitivity and support the development of actionable targets for pharmacologic intervention and biologically relevant dose constraints.

Bladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence.

Machine learning (ML) and artificial intelligence (AI) have demonstrated potential to improve the care of radiation oncology patients. Here we review recent advances applicable to the care of bladder cancer, with an eye towards studies that may suggest next steps in clinical implementation. Algorithms have been applied to clinical records, pathology, and radiology data to generate accurate predictive models for prognosis and clinical outcomes. AI has also shown increasing utility for auto-contouring and efficient creation of workflows involving multiple treatment plans. As technologies progress towards routine clinical use for bladder cancer patients, we also discuss emerging methods to improve interpretability and reliability of algorithms.

Feasibility of using a dual isocentre technique for treating cervical cancer on the 1.5 T MR-Linac.

Objective.Patients treated for cervical cancer exhibit large inter and intra-fraction anatomical changes. The Unity MR-Linac (MRL) can image these patients with MR prior to and during treatment which enables daily plan adaptation. However, the MRL has a limited treatment field in the sup/inf direction of 22 cm which can restrict the treatment of patients who require longer treatment fields. Here we explore potential adaptive workflows in combination with a dual isocentre approach, to widen the range of cervix patients that can benefit from this treatment.Approach.Ten cervical cancer patients were retrospectively planned with a dual isocentre technique to deliver 45 Gy in 25 fractions. 5 node-negative and 5 node-positive patients were planned using the EMBRACE II protocol. A 2 cm overlap region between the two isocentres was positioned entirely in the nodal region. A treatment workflow was simulated to account for inter-fraction anatomical change. Isocentre shifts of 3 and 6 mm were applied to investigate the effect of intra-fraction motion.Main results.Dual isocentre adapted plans ensured significantly better coverage than non-adapted (recalculated) plans with a larger benefit seen for the node-negative cases. The difference to the reference plan for the V4275 cGy to the ITV was -0.8 cGy and -8.2 cGy for the adapted and recalculated plans respectively. Movements superiorly did not affect the coverage of the ITV by more than 1%, but shifting it inferiorly caused the ITV coverage on the plan to reduce by ∼2.4% per mm.Significance.A dual isocentre technique for cervical cancer treatments and adaptive workflows have been demonstrated to recover the required plan quality for inter-fraction changes. This illustrates the feasibility of a dual isocentre technique for the MRL.

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.

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer.

Introduction: We hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT). Methods: The study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index. The ID was calculated as the product of the mean body dose and body volume. The weekly ID accounted for differences in fractionation. The worsening (end of radiotherapy versus baseline) of European Organisation for Research and Treatment of Cancer EORTC) Quality of Life Questionnaire (QLQ)-C30 scores in physical/role/social functioning and fatigue symptom scales were evaluated, and two outcome measures were defined as worsening in ≥2 (WS2) or ≥3 (WS3) scales, respectively. The weekly ID and clinical risk factors were tested in multivariable logistic regression analysis. Results: In REQUITE, WS2 was seen in 28% and WS3 in 16% of patients. The median weekly ID was 13.1 L·Gy/week [interquartile (IQ) range 10.2-19.3]. The weekly ID, diabetes, the use of intensity-modulated radiotherapy, and the dose per fraction were significantly associated with WS2 [AUC (area under the receiver operating characteristics curve) =0.59; 95% CI 0.55-0.63] and WS3 (AUC=0.60; 95% CI 0.55-0.64). The prevalence of WS2 (15.3%) and WS3 (6.1%) was lower in DUE-01, but the median weekly ID was higher (15.8 L·Gy/week; IQ range 13.2-19.3). The model for WS2 was validated with reduced discrimination (AUC=0.52 95% CI 0.47-0.61), The AUC for WS3 was 0.58. Conclusion: Increasing the weekly ID and the dose per fraction lead to the worsening of fatigue and functional outcomes in patients with localized PCa treated with EBRT.

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.

Suitability of propagated contours for adaptive replanning for head and neck radiotherapy.

PURPOSE: Adaptive radiotherapy relies on rapid recontouring for replanning. Contour propagation offers workflow efficiencies, but the impact of using unedited propagated OAR contours directly during re-optimisation is unclear. METHODS: Plans for ten head and neck patients were created on the planning CT scan. OAR contours for the spinal cord, brainstem, parotids and larynx were then propagated to five shading-corrected CBCTs equally spaced throughout treatment using five commercial packages. Two reference contours were created on the CBCTs by (1) a clinician and (2) a geometric consensus from the propagated contours. Treatment plans were re-optimised on each CBCT for each set of contours, and the DVH statistic differences to the reference contours were calculated. The spread of DVH statistic differences between the 5th and 95th percentiles was quantified. RESULTS: The spread of DVH statistic differences was 3.7 Gy compared to the clinician contour and 3.3 Gy compared to the consensus contour for the brainstem (and PRV) and 2.4 Gy and 2 Gy for the spinal cord (and PRV), across all 5 auto-contouring solutions. The parotids and larynx showed differences of 3.7 Gy compared to the clinician and 0.9 Gy to the consensus contour, with the larger difference for the clinician possibly caused by uncertainty in the clinician standard due to poor image quality on the CBCTs. CONCLUSIONS: Propagated OAR contours can be used safely for adaptive radiotherapy replanning, however, where organ doses are close to clinical tolerance then the contours should be reviewed for accuracy regardless of the propagation software used.

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.

The geometric and dosimetric effect of algorithm choice on propagated contours from CT to cone beam CTs.

PURPOSE: Adaptive radiotherapy relies of rapid re-contouring, online more so than offline. Intra-patient contour propagation via non-rigid registration offers a solution but can be of limited accuracy. However, the dosimetric significance of the inaccuracies is unknown. Here we evaluate the dosimetric reliability of contours generated by different commercially-available software packages. METHOD: Planning CT contours for ten head and neck cancer patients were propagated via five commercial packages to five CBCT scans acquired throughout treatment. The treatment plan was recalculated on each of the CBCTs for each set of propagated contours, and DVH parameters extracted for the spinal cord, brainstem, parotids and larynx. The propagated contours were compared to two gold standard contours: contours manually outlined and a consensus STAPLE contours generated from the propagated contours. Geometrical similarity was evaluated using mean distance to agreement (mDTA), Hausdorff distance, centroid agreement and Dice similarity coefficient. Dosimetric reliability was assessed against clinical constraints and comparing via the intraclass correlation coefficient (ICC). RESULTS: All propagated contours were similar to the STAPLE (mDTA < 1.0 mm) whilst larger differences were seen for the manual contours (mDTA < 3.0 mm). The dosimetric comparison showed that the propagated contours gave excellent dose estimates for most organs. The spinal cord reliability was moderate (ICC > 0.66). CONCLUSIONS: Large differences in geometric metrics rarely had a statistically significant impact on DVH parameters for the OARs studied. For that reason, propagated contours on treatment CBCT images are suitable for estimating dose to the OARs.