Validation of an established deep learning auto-segmentation tool for cardiac substructures in 4D radiotherapy planning scans

Cardiotoxicity following thoracic radiotherapy for lung cancer

Radiotherapy is the standard of care treatment for unresectable NSCLC, combined with concurrent chemotherapy and adjuvant immunotherapy. Despite technological advances in radiotherapy planning and delivery, the risk of damage to surrounding thoracic tissues remains high. Cardiac problems, including arrhythmia, heart failure and ischaemic events, occur in 20% of patients with lung cancer who undergo radiotherapy. As survival rates improve incrementally for this cohort, minimising the cardiovascular morbidity of RT is increasingly important. Problematically, the reporting of cardiac endpoints has been poor in thoracic radiotherapy clinical trials, and retrospective studies have been limited by the lack of standardisation of nomenclature and endpoints. How baseline cardiovascular profile and cardiac substructure radiation dose distribution impact the risk of cardiotoxicity is incompletely understood. As Thoracic Oncology departments seek to expand the indications for radiotherapy, and as the patient cohort becomes older and more comorbid, there is a pressing need for cardiotoxicity to be comprehensively characterised with sophisticated oncology, physics and cardio-oncology evaluations. This review synthesises the evidence base for cardiotoxicity in conventional radiotherapy, focusing on lung cancer, including current data, unmet clinical needs, and future scientific directions.

Cardiac Complications of Radiation Therapy

Radiation therapy is a critical component in managing many malignancies by improving local control and survival. The benefits of radiation may come at the expense of unintended radiation injury to the surrounding normal tissues, with the heart being one of the most affected organs in thoracic radiation treatments. As cancer survivors live longer, radiation-induced cardiotoxicity (RICT) is now increasingly recognized. In this review, we highlight the spectrum and pathophysiology of RICT. We summarize contemporary recommendations for risk stratification, screening, prevention, and management of RICT. We briefly highlight novel applications for radiation to treat some cardiac conditions such as resistant arrhythmias.

Cardiac substructure delineation in radiation therapy - A state-of-the-art review

Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.

Radiation Oncology Opinions and Practice on Cardiotoxicity in Lung Cancer: A Cross-sectional Study by the International Cardio-oncology Society

AIMS

Symptomatic radiation cardiotoxicity affects up to 30% patients with lung cancer and several heart substructure doses are associated with reduced overall survival. A greater focus on minimising cardiotoxicity is now possible due to advancements in radiotherapy technology and the new discipline of cardio-oncology, but uptake of emerging data has not been ascertained. A global cross-sectional analysis of Radiation Oncologists who treat lung cancer was therefore conducted by the International Cardio-Oncology Society in order to establish the impact of recently published literature and guidelines on practice.

MATERIALS AND METHODS

A bespoke questionnaire was designed following an extensive review of the literature and from recurring relevant themes presented at Radiation Oncology and Cardio-Oncology research meetings. Six question domains were retained following consensus discussions among the investigators, comprising 55 multiple choice stems: guidelines, cardiovascular assessment, cardiology investigations, radiotherapy planning strategies, primary prevention prescribing and local cardio-oncology service access. An invitation was sent to all Radiation Oncologists registered with ICOS and to Radiation Oncology colleagues of the investigators.

RESULTS

In total 118 participants were recruited and 92% were consultant physicians. The ICOS 2021 expert consensus statement was rated as the most useful position paper, followed by the joint ESC-ESTRO 2022 guideline. The majority (80%) of participants indicated that a detailed cardiovascular history was advisable. Although 69% of respondents deemed the availability of cardiac substructure auto-segmentation to be very/quite important, it was implemented by only a few, with the most common being the left anterior descending coronary artery V15. A distinct cardio-oncology service was available to 39% participants, while the remainder utilised general cardiology services.

CONCLUSION

The uptake of recent guidelines on cardiovascular optimisation is good, but access to cardiology investigations and consultations, and auto-segmentation, represent barriers to modifying radiotherapy practices in lung cancer to reduce the risk of radiation cardiotoxicity.

The influence of cardiac substructure dose on survival in a large lung cancer stereotactic radiotherapy cohort using a robust personalized contour analysis

BACKGROUND/PURPOSE

Radiation-induced cardiac toxicity in lung cancer patients has received increased attention since RTOG 0617. However, large cohort studies with accurate cardiac substructure (CS) contours are lacking, limiting our understanding of the potential influence of individual CSs. Here, we analyse the correlation between CS dose and overall survival (OS) while accounting for deep learning (DL) contouring uncertainty, α / β uncertainty and different modelling approaches.

MATERIALS/METHODS

This single institution, retrospective cohort study includes 730 patients (early-stage tumours (I or II). All treated: 2009-2019), who received stereotactic body radiotherapy (≥ 5 Gy per fraction). A DL model was trained on 70 manually contoured patients to create 12 cardio-vascular structures. Structures with median dice score above 0.8 and mean surface distance (MSD) <2 mm during testing, were further analysed. Patientspecific CS dose was used to find the correlation between CS dose and OS with elastic net and random survival forest models (with and without confounding clinical factors). The influence of delineation-induced dose uncertainty on OS was investigated by expanding/contracting the DL-created contours using the MSD ± 2 standard deviations.

RESULTS

Eight CS contours met the required performance level. The left atrium (LA) mean dose was significant for OS and an LA mean dose of 3.3 Gy (in EQD2) was found as a significant dose stratum.

CONCLUSION

Explicitly accounting for input parameter uncertainty in lung cancer survival modelling was crucial in robustly identifying critical CS dose parameters. Using this robust methodology, LA mean dose was revealed as the most influential CS dose parameter.

Baseline Cardiac Parameters as Biomarkers of Radiation Cardiotoxicity in Lung Cancer: An NI-HEART Analysis

Background

Radiation-induced cardiotoxicity poses a significant challenge in lung cancer management because of the close anatomical proximity of the heart to the lungs, compounded by a high prevalence of cardiovascular risk factors among patients.

Objectives

The aim of this study was to assess the predictive value of routinely available clinical and imaging-based cardiac parameters in identifying "high risk" patients for major adverse cardiac events (MACE) and mortality following radiation therapy (RT).

Methods

The medical records of patients who underwent definitive RT for non-small cell lung cancer using modern planning techniques at a single center between 2015 and 2020 were retrospectively reviewed. Cardiac events were verified by cardiologists, and mortality data were confirmed with the national registry. Cardiac substructures were autosegmented on RT planning scans for retrospective structure and dose analysis, and their correlation with clinical factors was examined. Fine-Gray models were used to analyze relationships while considering the competing risk for death.

Results

Among 478 patients included in the study, 77 (16%) developed 88 MACE, with a median time to event of 16.3 months. A higher burden of pre-existing cardiac diseases was associated with an increased cumulative incidence of MACE (55% [95% CI: 12%-20%] vs 16% [95% CI: 35%-71%]; P < 0.001). Left atrial and left ventricular enlargement on RT planning scans was associated with cumulative incidence of atrial arrhythmia (14% [95% CI: 9%-20%] vs 4% [95% CI: 2%-8%]; P = 0.001) and heart failure (13% [95% CI: 8%-18%] vs 6% [95% CI: 3%-10%]; P = 0.007) at 5 years, respectively. However, myocardial infarction was not associated with the presence of coronary calcium (4.2% [95% CI: 2%-7%] vs 0% [95% CI: 0%-0%]; P = 0.094). No cardiac imaging metrics were found to be both clinically and statistically associated with survival.

Conclusions

The present findings suggest that cardiac history and RT planning scan parameters may offer potential utility in prospectively evaluating cardiotoxicity risk following RT for patients with lung cancer.

Autocontouring of primary lung lesions and nodal disease for radiotherapy based only on computed tomography images

Background and purpose

In many clinics, positron-emission tomography is unavailable and clinician time extremely limited. Here we describe a deep-learning model for autocontouring gross disease for patients undergoing palliative radiotherapy for primary lung lesions and/or hilar/mediastinal nodal disease, based only on computed tomography (CT) images.

Materials and methods

An autocontouring model (nnU-Net) was trained to contour gross disease in 379 cases (352 training, 27 test); 11 further test cases from an external centre were also included. Anchor-point-based post-processing was applied to remove extraneous autocontoured regions. The autocontours were evaluated quantitatively in terms of volume similarity (Dice similarity coefficient [DSC], surface Dice coefficient, 95th percentile Hausdorff distance [HD95], and mean surface distance), and scored for usability by two consultant oncologists. The magnitude of treatment margin needed to account for geometric discrepancies was also assessed.

Results

The anchor point process successfully removed all erroneous regions from the autocontoured disease, and identified two cases to be excluded from further analysis due to 'missed' disease. The average DSC and HD95 were 0.8 ± 0.1 and 10.5 ± 7.3 mm, respectively. A 10-mm uniform margin-distance applied to the autocontoured region was found to yield "full coverage" (sensitivity > 0.99) of the clinical contour for 64 % of cases. Ninety-seven percent of evaluated autocontours were scored by both clinicians as requiring no or minor edits.

Conclusions

Our autocontouring model was shown to produce clinically usable disease outlines, based on CT alone, for approximately two-thirds of patients undergoing lung radiotherapy. Further work is necessary to improve this before clinical implementation.

Pulmonary vein dose and risk of atrial fibrillation in patients with non-small cell lung cancer following definitive radiotherapy: An NI-HEART analysis

BACKGROUND AND PURPOSE

Symptomatic arrhythmia is common following radiotherapy for non-small cell lung cancer (NSCLC), frequently resulting in morbidity and hospitalization. Modern treatment planning technology theoretically allows sparing of cardiac substructures. Atrial fibrillation (AF) comprises the majority of post-radiotherapy arrhythmias, but efforts to prevent this cardiotoxicity have been limited as the causative cardiac substructure is not known. In this study we investigated if incidental radiation dose to the pulmonary veins (PVs) is associated with AF.

MATERIAL AND METHODS

A single-centre study of patients completing contemporary (chemo)radiation for NSCLC, with modern planning techniques. Oncology, cardiology and death records were examined, and AF events were verified by a cardiologist. Cardiac substructures were contoured on planning scans for retrospective dose analysis.

RESULTS

In 420 eligible patients with NSCLC treated with intensity-modulated (70%) or 3D-conformal (30%) radiotherapy with a median OS of 21.8 months (IQR 10.8-35.1), there were 26 cases of new AF (6%). All cases were grade 3 except two cases of grade 4. Dose metrics for both the left (V55) and right (V10) PVs were associated with the incidence of new AF. Metrics remained statistically significant after accounting for the competing risk of death and cardiovascular covariables for both the left (HR 1.02, 95%CI 1.00-1.03, p = 0.005) and right (HR 1.01 (95%CI 1.00-1.02, p = 0.033) PVs.

CONCLUSION

Radiation dose to the PVs during treatment of NSCLC was associated with the onset of AF. Actively sparing the PVs during treatment planning could reduce the incidence of AF during follow-up, and screening for AF may be warranted for select cases.

How to contour the different heart subregions for future deep-learning modeling of the heart: A practical pictorial proposal for radiation oncologists

There are currently no accurate rules for manually delineating the subregions of the heart (cavities, vessels, aortic/mitral valves, Planning organ at Risk Volumes for coronary arteries) with the perspective of deep-learning based modeling. Our objective was to present a practical pictorial view for radiation oncologists, based on the RTOG atlas and anatomical complementary considerations for the cases where the RTOG guidelines are missing.

An open source auto-segmentation algorithm for delineating heart and substructures - Development and validation within a multicenter lung cancer cohort

BACKGROUND AND PURPOSE

Irradiation of the heart in thoracic cancers raises toxicity concerns. For accurate dose estimation, automated heart and substructure segmentation is potentially useful. In this study, a hybrid automatic segmentation is developed. The accuracy of delineation and dose predictions were evaluated, testing the method's potential within heart toxicity studies.

MATERIALS AND METHODS

The hybrid segmentation method delineated the heart, four chambers, three large vessels, and the coronary arteries. The method consisted of a nnU-net heart segmentation and partly atlas- and model-based segmentation of the substructures. The nnU-net training and atlas segmentation was based on lung cancer patients and was validated against a national consensus dataset of 12 patients with breast cancer. The accuracy of dose predictions between manual and auto-segmented heart and substructures was evaluated by transferring the dose distribution of 240 previously treated lung cancer patients to the consensus data set.

RESULTS

The hybrid auto-segmentation method performed well with a heart dice similarity coefficient (DSC) of 0.95, with no statistically significant difference between the automatic and manual delineations. The DSC for the chambers varied from 0.78-0.86 for the automatic segmentation and was comparable with the inter-observer variability. Most importantly, the automatic segmentation was as precise as the clinical experts in predicting the dose distribution to the heart and all substructures.

CONCLUSION

The hybrid segmentation method performed well in delineating the heart and substructures. The prediction of dose by the automatic segmentation was aligned with the manual delineations, enabling measurement of heart and substructure dose in large cohorts. The delineation algorithm will be available for download.

The Association of Incidental Radiation Dose to the Heart Base with Overall Survival and Cardiac Events after Curative-intent Radiotherapy for Non-small Cell Lung Cancer: Results from the NI-HEART Study

AIMS

Cardiac disease is a dose-limiting toxicity in non-small cell lung cancer radiotherapy. The dose to the heart base has been associated with poor survival in multiple institutional and clinical trial datasets using unsupervised, voxel-based analysis. Validation has not been undertaken in a cohort with individual patient delineations of the cardiac base or for the endpoint of cardiac events. The purpose of this study was to assess the association of heart base radiation dose with overall survival and the risk of cardiac events with individual heart base contours.

MATERIALS AND METHODS

Patients treated between 2015 and 2020 were reviewed for baseline patient, tumour and cardiac details and both cancer and cardiac outcomes as part of the NI-HEART study. Three cardiologists verified cardiac events including atrial fibrillation, heart failure and acute coronary syndrome. Cardiac substructure delineations were completed using a validated deep learning-based autosegmentation tool and a composite cardiac base structure was generated. Cox and Fine-Gray regressions were undertaken for the risk of death and cardiac events.

RESULTS

Of 478 eligible patients, most received 55 Gy/20 fractions (96%) without chemotherapy (58%), planned with intensity-modulated radiotherapy (71%). Pre-existing cardiovascular morbidity was common (78% two or more risk factors, 46% one or more established disease). The median follow-up was 21.1 months. Dichotomised at the median, a higher heart base Dmax was associated with poorer survival on Kaplan-Meier analysis (20.2 months versus 28.3 months; hazard ratio 1.40, 95% confidence interval 1.14-1.75, P = 0.0017) and statistical significance was retained in multivariate analyses. Furthermore, heart base Dmax was associated with pooled cardiac events in a multivariate analysis (hazard ratio 1.75, 95% confidence interval 1.03-2.97, P = 0.04).

CONCLUSIONS

Heart base Dmax was associated with the rate of death and cardiac events after adjusting for patient, tumour and cardiovascular factors in the NI-HEART study. This validates the findings from previous unsupervised analytical approaches. The heart base could be considered as a potential sub-organ at risk towards reducing radiation cardiotoxicity.

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.

Refining critical structure contouring in STereotactic Arrhythmia Radioablation (STAR): Benchmark results and consensus guidelines from the STOPSTORM.eu consortium

BACKGROUND AND PURPOSE

In patients with recurrent ventricular tachycardia (VT), STereotactic Arrhythmia Radioablation (STAR) shows promising results. The STOPSTORM.eu consortium was established to investigate and harmonise STAR treatment in Europe. The primary goals of this benchmark study were to standardise contouring of organs at risk (OAR) for STAR, including detailed substructures of the heart, and accredit each participating centre.

MATERIALS AND METHODS

Centres within the STOPSTORM.eu consortium were asked to delineate 31 OAR in three STAR cases. Delineation was reviewed by the consortium expert panel and after a dedicated workshop feedback and accreditation was provided to all participants. Further quantitative analysis was performed by calculating DICE similarity coefficients (DSC), median distance to agreement (MDA), and 95th percentile distance to agreement (HD95).

RESULTS

Twenty centres participated in this study. Based on DSC, MDA and HD95, the delineations of well-known OAR in radiotherapy were similar, such as lungs (median DSC = 0.96, median MDA = 0.1 mm and median HD95 = 1.1 mm) and aorta (median DSC = 0.90, median MDA = 0.1 mm and median HD95 = 1.5 mm). Some centres did not include the gastro-oesophageal junction, leading to differences in stomach and oesophagus delineations. For cardiac substructures, such as chambers (median DSC = 0.83, median MDA = 0.2 mm and median HD95 = 0.5 mm), valves (median DSC = 0.16, median MDA = 4.6 mm and median HD95 = 16.0 mm), coronary arteries (median DSC = 0.4, median MDA = 0.7 mm and median HD95 = 8.3 mm) and the sinoatrial and atrioventricular nodes (median DSC = 0.29, median MDA = 4.4 mm and median HD95 = 11.4 mm), deviations between centres occurred more frequently. After the dedicated workshop all centres were accredited and contouring consensus guidelines for STAR were established.

CONCLUSION

This STOPSTORM multi-centre critical structure contouring benchmark study showed high agreement for standard radiotherapy OAR. However, for cardiac substructures larger disagreement in contouring occurred, which may have significant impact on STAR treatment planning and dosimetry evaluation. To standardize OAR contouring, consensus guidelines for critical structure contouring in STAR were established.

Development of a comprehensive cardiac atlas on a 1.5 Tesla Magnetic Resonance Linear Accelerator

Background and purpose

The 1.5 Tesla (T) Magnetic Resonance Linear Accelerator (MRL) provides an innovative modality for improved cardiac imaging when planning radiation treatment. No MRL based cardiac atlases currently exist, thus, we sought to comprehensively characterize cardiac substructures, including the conduction system, from cardiac images acquired using a 1.5 T MRL and provide contouring guidelines.

Materials and methods

Five volunteers were enrolled in a prospective protocol (NCT03500081) and were imaged on the 1.5 T MRL with Half Fourier Single-Shot Turbo Spin-Echo (HASTE) and 3D Balanced Steady-State Free Precession (bSSFP) sequences in axial, short axis, and vertical long axis. Cardiac anatomy was contoured by (AS) and confirmed by a board certified cardiologist (JR) with expertise in cardiac MR imaging.

Results

A total of five volunteers had images acquired with the HASTE sequence, with 21 contours created on each image. One of these volunteers had additional images obtained with 3D bSSFP sequences in the axial plane and additional images obtained with HASTE sequences in the key cardiac planes. Contouring guidelines were created and outlined. 15-16 contours were made for the short axis and vertical long axis. The cardiac conduction system was demonstrated with eleven representative contours. There was reasonable variation of contour volume across volunteers, with structures more clearly delineated on the 3D bSSFP sequence.

Conclusions

We present a comprehensive cardiac atlas using novel images acquired prospectively on a 1.5 T MRL. This cardiac atlas provides a novel resource for radiation oncologists in delineating cardiac structures for treatment with radiotherapy, with special focus on the cardiac conduction system.

Association between statin therapy dose intensity and radiation cardiotoxicity in non-small cell lung cancer: Results from the NI-HEART study

INTRODUCTION

Radiation cardiotoxicity is a dose-limiting toxicity and major survivorship issue for patients with non-small cell lung cancer (NSCLC) completing curative-intent radiotherapy, however patients' cardiovascular baseline is not routinely optimised prior to treatment. In this study we examined the impact of statin therapy on overall survival and post-radiotherapy cardiac events.

METHODS

Patients treated between 2015-2020 at a regional center were identified. Clinical notes were interrogated for baseline patient, tumor and cardiac details, and both follow-up cancer control and cardiac events. Three cardiologists verified cardiac events. Radiotherapy planning scans were retrieved for application of validated deep learning-based autosegmentation. Pre-specified Cox regression analyses were generated with varying degrees of adjustment for overall survival. Fine and Gray regression for the risk of cardiac events, accounting for the competing risk of death and cardiac covariables was undertaken.

RESULTS

Statin therapy was prescribed to 59% of the 478 included patients. The majority (88%) of patients not prescribed a statin had at least one indication for statin therapy according to cardiovascular guidelines. In total, 340 patients (71%) died and 79 patients (17%) experienced a cardiac event. High-intensity (HR 0.68, 95%CI 0.50-0.91, p = 0.012) and medium-intensity (HR 0.70, 95%CI 0.51-0.97, p = 0.033) statin therapy were associated with improved overall survival after adjustment for patient, cancer, treatment, response and cardiovascular clinical factors. There were no consistent differences in the rate or grade of cardiac events according to statin intensity.

CONCLUSIONS

Statin therapy is associated with improved overall survival in patients receiving curative-intent radiotherapy for NSCLC, and there is evidence of a dose-response relationship. This study highlights the importance of a pre-treatment cardiovascular risk assessment in this cohort. Further studies are needed to examine if statin therapy is cardioprotective in patients undergoing treatment for NSCLC with considerable incidental cardiac radiation dose and a low baseline cardiac risk.

Radiation therapy in the thoracic region: Radio-induced cardiovascular disease, cardiac delineation and sparing, cardiac dose constraints, and cardiac implantable electronic devices

Radiation therapy in the thoracic region may deliver incidental ionizing radiation to the surrounding healthy structures, including the heart. Radio-induced heart toxicity has long been a concern in breast cancer and Hodgkin's lymphoma and was deemed a long-term event. However, recent data highlight the need to limit the dose to the heart in less favorable thoracic cancers too, such as lung and esophageal cancers in which incidental irradiation led to increased mortality. This article will summarize available cardiac dose constraints in various clinical settings and the types of radio-induced cardiovascular diseases encountered as well as delineation of cardiac subheadings and management of cardiac devices. Although still not completely deciphered, heart dose constraints remain intensively investigated and the mean dose to the heart is no longer the only dosimetric parameter to consider since the left anterior descending artery as well as the left ventricle should also be part of dosimetry constraints.

Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy

BACKGROUND AND PURPOSE

Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segmentation tool for automatic delineation of cardiac structures and subsequent dose evaluation, with potential application in clinical settings and large-scale radiation-related cardiotoxicity studies.

MATERIALS AND METHODS

A recently developed hybrid method for automatic segmentation of 18 cardiac structures, combining deep learning, multi-atlas mapping and geometric segmentation of small challenging substructures, was independently validated on 30 lung cancer cases. These included anatomical and imaging variations, such as tumour abutting heart, lung collapse and metal artefacts. Automatic segmentations were compared with manual contours of the 18 structures using quantitative metrics, including Dice similarity coefficient (DSC), mean distance to agreement (MDA) and dose comparisons.

RESULTS

A comparison of manual and automatic contours across all cases showed a median DSC of 0.75-0.93 and a median MDA of 2.09-3.34 mm for whole heart and chambers. The median MDA for great vessels, coronary arteries, cardiac valves, sinoatrial and atrioventricular conduction nodes was 3.01-8.54 mm. For the 27 cases treated with curative intent (planned target volume dose ≥50 Gy), the median dose difference was -1.12 to 0.57 Gy (absolute difference of 1.13-3.25%) for the mean dose to heart and chambers; and -2.25 to 4.45 Gy (absolute difference of 0.94-6.79%) for the mean dose to substructures.

CONCLUSION

The novel hybrid automatic segmentation tool reported high accuracy and consistency over a validation set with challenging anatomical and imaging variations. This has promising applications in substructure dose calculations of large-scale datasets and for future studies on long-term cardiac toxicity.

Open-source, fully-automated hybrid cardiac substructure segmentation: development and optimisation

Radiotherapy for thoracic and breast tumours is associated with a range of cardiotoxicities. Emerging evidence suggests cardiac substructure doses may be more predictive of specific outcomes, however, quantitative data necessary to develop clinical planning constraints is lacking. Retrospective analysis of patient data is required, which relies on accurate segmentation of cardiac substructures. In this study, a novel model was designed to deliver reliable, accurate, and anatomically consistent segmentation of 18 cardiac substructures on computed tomography (CT) scans. Thirty manually contoured CT scans were included. The proposed multi-stage method leverages deep learning (DL), multi-atlas mapping, and geometric modelling to automatically segment the whole heart, cardiac chambers, great vessels, heart valves, coronary arteries, and conduction nodes. Segmentation performance was evaluated using the Dice similarity coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD), and volume ratio. Performance was reliable, with no errors observed and acceptable variation in accuracy between cases, including in challenging cases with imaging artefacts and atypical patient anatomy. The median DSC range was 0.81-0.93 for whole heart and cardiac chambers, 0.43-0.76 for great vessels and conduction nodes, and 0.22-0.53 for heart valves. For all structures the median MDA was below 6 mm, median HD ranged 7.7-19.7 mm, and median volume ratio was close to one (0.95-1.49) for all structures except the left main coronary artery (2.07). The fully automatic algorithm takes between 9 and 23 min per case. The proposed fully-automatic method accurately delineates cardiac substructures on radiotherapy planning CT scans. Robust and anatomically consistent segmentations, particularly for smaller structures, represents a major advantage of the proposed segmentation approach. The open-source software will facilitate more precise evaluation of cardiac doses and risks from available clinical datasets.

Association of cardiac calcium burden with overall survival after radiotherapy for non-small cell lung cancer

Background and purpose

Coronary calcifications are associated with coronary artery disease in patients undergoing radiotherapy (RT) for non-small cell lung cancer (NSCLC). We quantified calcifications in the coronary arteries and aorta and investigated their relationship with overall survival (OS) in patients treated with definitive RT (Def-RT) or post-operative RT (PORT).

Materials and methods

We analyzed 263 NSCLC patients treated from 2004 to 2017. Calcium burden was ascertained with a Hounsfield unit (HU) cutoff of > 130 in addition to a deep learning (DL) plaque estimator. The HU cutoff volumes were defined for coronary arteries (Plaque_Coro) and coronary arteries and aorta combined (Plaque_Coro+Ao), while the DL estimator ranged from 0 (no plaque) to 3 (high plaque). Patient and treatment characteristics were explored for association with OS.

Results

The median Plaque_Coro and Plaque_Coro+Ao was 0.75 cm³ and 0.87 cm³ in the Def-RT group and 0.03 cm³ and 0.52 cm³ in the PORT group. The median DL estimator was 2 in both cohorts. In Def-RT, large Plaque_Coro (HR:1.11 (95%CI:1.04-1.19); p = 0.008), and Plaque_Coro+Ao (HR:1.06 (95%CI:1.02-1.11); p = 0.03), and poor Karnofsky Performance Status (HR: 0.97 (95%CI: 0.94-0.99); p = 0.03) were associated with worse OS. No relationship was identified between the plaque volumes and OS in PORT, or between the DL plaque estimator and OS in either Def-RT or PORT.

Conclusions

Coronary artery calcification assessed from RT planning CT scans was significantly associated with OS in patients who underwent Def-RT for NSCLC. This HU thresholding method can be straightforwardly implemented such that the role of calcifications can be further explored.