Dose to the cardio-pulmonary system and treatment-induced electrocardiogram abnormalities in locally advanced non-small cell lung cancer

A multicenter retrospective study of early cardiac toxicity in operable breast cancer patients receiving concurrent dual or mono anti-HER2 therapy with postoperative radiation therapy

PURPOSE

This study aims to assess whether dual anti-HER2 therapy with trastuzumab and pertuzumab increases early cardiac toxicity compared to trastuzumab alone in breast cancer (BC) patients receiving postoperative radiation therapy (RT).

METHODS

Consecutive operable BC patients receiving postoperative RT and trastuzumab with or without pertuzumab between January 2017 and September 2020 at seven tertiary hospitals in China were retrospectively reviewed. Cardiac examinations included echocardiography, electrocardiogram (ECG), NT-proBNP, and cTnI at baseline before RT and during the follow-up. The cardiac event is any new-onset symptomatic heart disease or abnormality in the cardiac examination after RT.

RESULTS

In total, 681 patients were enrolled in the analysis, of whom 567 were treated with trastuzumab-alone and 124 patients received dual anti-HER2 therapy. The median follow-up was 11 months. Multivariate analysis showed that left-sided breast cancer (HR 2.38; 95%CI 1.65-3.44, p < 0.001) and IMN RT (HR 1.47; 95 % CI 1.01-2.15, P-value = 0.047) are independent risk factors for ECG abnormalities. Age >50 years is an independent risk factor for developing LVDD (HR 5.16; 95%CI 1.17-22.73, P-value = 0.030). Dosimetric analysis showed that patients who developed subclinical cardiac events had increased mean heart dose (412.0 ± 249.6 vs. 347.2 ± 242.6 cGy, P-value = 0.010). Among right-sided patients or patients receiving anthracycline-based chemotherapy, the dual-targeted cohort had a higher risk of developing ECG abnormalities compared to the trastuzumab-only cohort.

CONCLUSION

Compared with trastuzumab-only, dual anti-HER2 therapy does not increase early cardiac toxicity in combination with postoperative RT in BC patients. Cardiac radiation exposure remains the primary risk factor for early toxicity.

Patient and treatment-related factors that influence dose to heart and heart substructures in left-sided breast cancer radiotherapy

BACKGROUND

Cardiac substructures are critical organs at risk in left-sided breast cancer radiotherapy being often overlooked during treatment planning. The treatment technique plays an important role in diminishing dose to critical structures. This review aims to analyze the impact of treatment- and patient-related factors on heart substructure dosimetry and to identify the gaps in literature regarding dosimetric reporting of cardiac substructures.

METHODS

A systematic search of the literature was conducted in Medline/Pubmed database incorporating data published over the past 10 years, leading to 81 eligible studies. Treatment-related factors analyzed for their impact on patient outcome included the number of treatment fields, field geometry, treatment time and monitor units. Additionally, patient-related parameters such as breast size and tumor shape were considered for cardiac dosimetry evaluation.

RESULTS

Limited number of fields appeared to be an advantage for mean heart dose reduction when tangential IMRT versus multiple fields IMRT was evaluated. Larger breast size (910.20 ± 439.80 cm3) is linked to larger treatment fields and higher heart doses. Internal mammary node irradiation further escalates cardiac substructures dosimetry treated with 3DCRT and IMRT/VMAT. Proton therapy delivers lower mean heart dose regardless of breathing condition (free or respiratory-gated).

CONCLUSION

The management of treatment- and patient-related factors must be taken into account regardless of the treatment technique when evaluating cardiac dose. Furthermore, the gap found in the literature regarding heart toxicity assessment in left-sided breast cancer patients emphasizes the need for cardiac substructure contouring to better manage and control radiation-induced cardiac toxicities in this patient group.

Cardiopulmonary Substructure Doses are Not Correlated With Cardiorespiratory Fitness Among Breast Cancer Survivors Treated With Contemporary Radiation Therapy

Purpose

Breast cancer radiation therapy (RT) techniques have historically delivered mean heart doses (MHDs) in the range of 5 Gy, which have been found to predispose patients to cardiopulmonary toxicities. The purpose of this study was to apply artificial intelligence (AI) cardiac substructure auto-segmentation to evaluate the corresponding substructure doses, whether there are laterality- and technique-specific differences in these doses, and if the doses are significantly associated with cardiorespiratory fitness after state-of-the-art RT planning and delivery for breast cancer.

Methods and Materials

Cardiopulmonary substructures were AI auto-segmented. Cardiorespiratory fitness was evaluated at a median of 2.3 (range, 1.1-9.8) years following RT from 2007 to 2021 among 65 breast cancer survivors. The associations between the mean dose to each of the 9 AI auto-segmented cardiopulmonary substructures, the contralateral, and the ipsilateral lung with cardiorespiratory fitness were evaluated using linear regression.

Results

The median MHD was 0.64 Gy (range, 0.12-7.1). Among the auto-segmented substructures, the highest mean doses were observed for the left ventricle (median, 0.88 Gy). The mean dose to each of the 11 structures was significantly higher for women treated with volumetric modulated arc therapy (MHD median, 3.8 Gy vs 0.57 Gy; P < .0001). Women with left-sided breast cancer had significantly higher MHDs (0.97 vs 0.38 Gy; P < .0001) due to higher doses in 3 of 4 cardiac chambers and also due to significantly higher pulmonary artery doses (median, 0.93 vs 0.32 Gy; P = .0003); women with right-sided breast cancer had significantly higher vena cava and right atrium doses (eg, right atrium median, 0.74 vs 0.29 Gy; P = .0002). No cardiopulmonary structure dose was significantly associated with reduced cardiorespiratory fitness after adjusting for age, chemotherapy agent, volumetric modulated arc therapy, RT position, and RT extent.

Conclusions

State-of-the-art breast cancer RT reduces cardiopulmonary dose, and there is a technique and cancer laterality RT dose dependence throughout the cardiopulmonary system.

Early and Accurate Detection of Radiation-induced Heart Damage by Cardiodynamicsgram

Cardiodynamicsgram (CDG) has emerged recently as a noninvasive spatiotemporal electrocardiographic method for subtle cardiac dynamics information analysis within electrocardiogram (ECG). This study explored the feasibility of CDG for detecting radiation-induced heart damage (RIHD) in a rat model. A single radiation dose of 40 Gy was delivered to the cardiac apex of female Wistar rats. First, CDG was generated through dynamic modeling of ECG signals using the deterministic learning algorithm. Furthermore, CDG indexes were calculated using the wavelet transform and entropy. In this model, CDG entropy indexes decreased significantly after radiotherapy. The shape of CDG changed significantly after radiotherapy (irregular shape) compared with controls (regular shape). Macrophage and fibrosis in myocardium of rats increased significantly after radiotherapy. CDG changes after radiotherapy were significantly correlated with histopathological changes and occurred significantly earlier than histopathological changes. This study provides an experimental basis for the clinical application of CDG for the early detection of RIHD.

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.

IA PULMONARY VEIN ATLAS FOR RADIOTHERAPY PLANNING

BACKGROUND AND PURPOSE

Cardiac arrhythmia is a recognised potential complication of thoracic radiotherapy, but the responsible cardiac substructures for arrhythmogenesis have not been identified. Arrhythmogenic tissue is commonly located in the pulmonary veins (PVs) of cardiology patients with arrhythmia, however these structures are not currently considered organs-at-risk during radiotherapy planning. A standardised approach to their delineation was developed and evaluated.

MATERIALS AND METHODS

The gross and radiological anatomy relevant to atrial fibrillation was derived from cardiology and radiology literature by a multidisciplinary team. A region of interest and contouring instructions for radiotherapy computed tomography scans were iteratively developed and subsequently evaluated. Radiation oncologists (n=5) and radiation technologists (n=2) contoured the PVs on the four-dimensional planning datasets of five patients with locally advanced lung cancer treated with 1.8-2.75 Gy fractions. Contours were compared to reference contours agreed by the researchers using geometric and dosimetric parameters.

RESULTS

The mean dose to the PVs was 35% prescription dose. Geometric and dosimetric similarity of the observer contours with reference contours was fair, with an overall mean Dice of 0.80 ± 0.02. The right superior PV (mean DSC 0.83 ± 0.02) had better overlap than the left (mean DSC 0.80 ± 0.03), but the inferior PVs were equivalent (mean DSC of 0.78). The mean difference in mean dose was 0.79 Gy ± 0.71 (1.46% ± 1.25).

CONCLUSION

A PV atlas with multidisciplinary approval led to reproducible delineation for radiotherapy planning, supporting the utility of the atlas in future clinical radiotherapy cardiotoxicity research encompassing arrhythmia endpoints.

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 &gt; 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&lt;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 &lt;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.

Murine models of radiation cardiotoxicity: A systematic review and recommendations for future studies

BACKGROUND AND PURPOSE

The effects of radiation on the heart are dependent on dose, fractionation, overall treatment time, and pre-existing cardiovascular pathology. Murine models have played a central role in improving our understanding of the radiation response of the heart yet a wide range of exposure parameters have been used. We evaluated the study design of published murine cardiac irradiation experiments to assess gaps in the literature and to suggest guidance for the harmonisation of future study reporting.

METHODS AND MATERIALS

A systematic review of mouse/rat studies published 1981-2021 that examined the effect of radiation on the heart was performed. The protocol was published on PROSPERO (CRD42021238921) and the findings were reported in accordance with the PRISMA guidance. Risk of bias was assessed using the SYRCLE checklist.

RESULTS

159 relevant full-text original articles were reviewed. The heart only was the target volume in 67% of the studies and simulation details were unavailable for 44% studies. Dosimetry methods were reported in 31% studies. The pulmonary effects of whole and partial heart irradiation were reported in 13% studies. Seventy-eight unique dose-fractionation schedules were evaluated. Large heterogeneity was observed in the endpoints measured, and the reporting standards were highly variable.

CONCLUSIONS

Current murine models of radiation cardiotoxicity cover a wide range of irradiation configurations and latency periods. There is a lack of evidence describing clinically relevant dose-fractionations, circulating biomarkers and radioprotectants. Recommendations for the consistent reporting of methods and results of in vivo cardiac irradiation studies are made to increase their suitability for informing the design of clinical studies.

Interdisciplinary Clinical Target Volume Generation for Cardiac Radioablation: Multicenter Benchmarking for the RAdiosurgery for VENtricular TAchycardia (RAVENTA) Trial

PURPOSE

Cardiac radioablation is a novel treatment option for therapy-refractory ventricular tachycardia (VT) ineligible for catheter ablation. Three-dimensional clinical target volume (CTV) definition is a key step, and this complex interdisciplinary procedure includes VT-substrate identification based on electroanatomical mapping (EAM) and its transfer to the planning computed tomography (PCT). Benchmarking of this process is necessary for multicenter clinical studies such as the RAVENTA trial.

METHODS AND MATERIALS

For benchmarking of the RAVENTA trial, patient data (epicrisis, electrocardiogram, high-resolution EAM, contrast-enhanced cardiac computed tomography, PCT) of 3 cases were sent to 5 university centers for independent CTV generation, subsequent structure analysis, and consensus finding. VT substrates were first defined on multiple EAM screenshots/videos and manually transferred to the PCT. The generated structure characteristics were then independently analyzed (volume, localization, surface distance and conformity). After subsequent discussion, consensus structures were defined.

RESULTS

VT substrate on the EAM showed visible variability in extent and localization for cases 1 and 2 and only minor variability for case 3. CTVs ranged from 6.7 to 22.9 cm3, 5.9 to 79.9 cm3, and 9.4 to 34.3 cm3; surface area varied from 1087 to 3285 mm2, 1077 to 9500 mm2, and 1620 to 4179 mm2, with a Hausdorff-distance of 15.7 to 39.5 mm, 23.1 to 43.5 mm, and 15.9 to 43.9 mm for cases 1 to 3, respectively. The absolute 3-dimensional center-of-mass difference was 5.8 to 28.0 mm, 8.4 to 26 mm, and 3.8 to 35.1 mm for cases 1 to 3, respectively. The entire process resulted in CTV structures with a conformity index of 0.2 to 0.83, 0.02 to 0.85, and 0.02 to 0.88 (ideal 1) with the consensus CTV as reference.

CONCLUSIONS

Multicenter efficacy endpoint assessment of cardiac radioablation for therapy-refractory VT requires consistent CTV transfer methods from the EAM to the PCT. VT substrate definition and CTVs were comparable with current clinical practice. Remarkable differences regarding the degree of agreement of the CTV definition on the EAM and the PCT were noted, indicating a loss of agreement during the transfer process between EAM and PCT. Cardiac radioablation should be performed under well-defined protocols and in clinical trials with benchmarking and consensus forming.

A Pilot Study of Safer Radiation Dosage to the Heart and Its Subregions

Background and Objectives: The real impact of ionizing radiation on the heart and poorer overall survival for patients with non small cell lung cancer (NSCLC) remains unclear. This study aims to determine the safe dose constraints to the heart’s subregions that could prevent patients’ early non-cancerous death and improve their quality of life. Methods and Materials: A retrospective cohort study was performed containing 51 consecutive patients diagnosed with stage III NSCLC and treated using 3D, Intensity-modulated radiation therapy (IMRT), and Volumetric modulated arc therapy (VMAT) radiotherapy. For a dosimetric analysis, these structures were chosen: heart, heart base (HB), and region of great blood vessels (GBV). Dose–volume histograms (DVH) were recorded for all mentioned structures. Maximum and mean doses to the heart, HB, the muscle mass of the HB, and GBV were obtained. V10–V60 (%) parameters were calculated from the DVH. After performed statistical analysis, logistic regression models were created, and critical doses calculated. Results: The critical dose for developing a fatal endpoint for HB was 30.5 Gy, while for GBV, it was 46.3 Gy. Increasing the average dose to the HB or GBV by 1 Gy from the critical dose further increases the possibility of early death by 22.0% and 15.8%, respectively. Conclusions: We suggest that the non-canonical sub-regions of the heart (HB and GBV) should be considered during the planning stage. Additional constraints of the heart subregions should be chosen accordingly, and we propose that the mean doses to these regions be 30.5 Gy and 46.3 Gy, respectively, or less. Extrapolated DVH curves for both regions may be used during the planning stage with care.

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.

Regional Responses in Radiation-Induced Normal Tissue Damage

Normal tissue side effects remain a major concern in radiotherapy. The improved precision of radiation dose delivery of recent technological developments in radiotherapy has the potential to reduce the radiation dose to organ regions that contribute the most to the development of side effects. This review discusses the contribution of regional variation in radiation responses in several organs. In the brain, various regions were found to contribute to radiation-induced neurocognitive dysfunction. In the parotid gland, the region containing the major ducts was found to be critical in hyposalivation. The heart and lung were each found to exhibit regional responses while also mutually affecting each other's response to radiation. Sub-structures critical for the development of side effects were identified in the pancreas and bladder. The presence of these regional responses is based on a non-uniform distribution of target cells or sub-structures critical for organ function. These characteristics are common to most organs in the body and we therefore hypothesize that regional responses in radiation-induced normal tissue damage may be a shared occurrence. Further investigations will offer new opportunities to reduce normal tissue side effects of radiotherapy using modern and high-precision technologies.

Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617

PURPOSE

Contouring inconsistencies are known but understudied in clinical radiation therapy trials. We applied auto-contouring to the Radiation Therapy Oncology Group (RTOG) 0617 dose escalation trial data. We hypothesized that the trial heart doses were higher than reported due to inconsistent and insufficient heart segmentation. We tested our hypothesis by comparing doses between deep-learning (DL) segmented hearts and trial hearts.

METHODS AND MATERIALS

The RTOG 0617 data were downloaded from The Cancer Imaging Archive; the 442 patients with trial hearts and dose distributions were included. All hearts were resegmented using our DL pipeline and quality assured to meet the requirements for clinical implementation. Dose (V5%, V30%, and mean heart dose) was compared between the 2 sets of hearts (Wilcoxon signed-rank test). Each dose metric was associated with overall survival (Cox proportional hazards). Lastly, 18 volume similarity metrics were assessed for the hearts and correlated with |Dose_DL - Dose_RTOG0617| (linear regression; significance: P ≤ .0028; corrected for 18 tests).

RESULTS

Dose metrics were significantly higher for DL hearts compared with trial hearts (eg, mean heart dose: 15 Gy vs 12 Gy; P = 5.8E-16). All 3 DL heart dose metrics were stronger overall survival predictors than those of the trial hearts (median, P = 2.8E-5 vs 2.0E-4). Thirteen similarity metrics explained |Dose_DL - Dose_RTOG0617|; the axial distance between the 2 centers of mass was the strongest predictor (CENT_Axial; median, R² = 0.47; P = 6.1E-62). CENT_Axial agreed with the qualitatively identified inconsistencies in the superior direction. The trial's qualitative heart contouring score was not correlated with |Dose_DL - Dose_RTOG0617| (median, R² = 0.01; P = .02) or with any of the similarity metrics (median, Rs = 0.13 [range, -0.22 to 0.31]).

CONCLUSIONS

Using a coherent heart definition, as enabled through our open-source DL algorithm, the trial heart doses in RTOG 0617 were found to be significantly higher than previously reported, which may have led to an even more rapid mortality accumulation. Auto-segmentation is likely to reduce contouring and dose inconsistencies and increase the quality of clinical RT trials.

Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes analysis

Background and purpose

Radiation dose to the cardio-pulmonary system is critical for radiotherapy-induced mortality in non-small cell lung cancer. Our goal was to automatically segment substructures of the cardio-pulmonary system for use in outcomes analyses for thoracic cancers. We built and validated a multi-label Deep Learning Segmentation (DLS) model for accurate auto-segmentation of twelve cardio-pulmonary substructures.

Materials and methods

The DLS model utilized a convolutional neural network for segmenting substructures from 217 thoracic radiotherapy Computed Tomography (CT) scans. The model was built in the presence of variable image characteristics such as the absence/presence of contrast. We quantitatively evaluated the final model against expert contours for a hold-out dataset of 24 CT scans using Dice Similarity Coefficient (DSC), 95th Percentile of Hausdorff Distance and Dose-volume Histograms (DVH). DLS contours of an additional 25 scans were qualitatively evaluated by a radiation oncologist to determine their clinical acceptability.

Results

The DLS model reduced segmentation time per patient from about one hour to 10 s. Quantitatively, the highest accuracy was observed for the Heart (median DSC = (0.96 (0.95–0.97)). The median DSC for the remaining structures was between 0.81 and 0.93. No statistically significant difference was found between DVH metrics of the auto-generated and manual contours (p-value ⩾ 0.69). The expert judged that, on average, 85% of contours were qualitatively equivalent to state-of-the-art manual contouring.

Conclusion

The cardio-pulmonary DLS model performed well both quantitatively and qualitatively for all structures. This model has been incorporated into an open-source tool for the community to use for treatment planning and clinical outcomes analysis.

Library of deep-learning image segmentation and outcomes model-implementations

An open-source library of implementations for deep-learning-based image segmentation and outcomes models based on radiotherapy and radiomics is presented. As oncology treatment planning becomes increasingly driven by automation, such a library of model implementations is crucial to (i) validate existing models on datasets collected at different institutions, (ii) automate segmentation, (iii) create ensembles for improving performance and (iv) incorporate validated models in the clinical workflow. Inclusion of deep-learning-based image segmentation and outcomes models in the same library provides a fully automated and reproduceable pipeline to estimate prognosis. The library was developed with the Computational Environment for Radiological Research (CERR) software platform. Centralizing model implementations in CERR builds upon its rich set of radiotherapy and radiomics tools and caters to the world-wide user base. CERR provides well-validated feature extraction pipelines for radiotherapy dosimetry and radiomics with fine control over the calculation settings, allowing users to select appropriate parameters used in model derivation. Models for automatic image segmentation are distributed via containers, allowing them to be deployed with a variety of scientific computing architectures. The library includes implementations of popular DVH-based models outlined in the Quantitative Analysis of Normal Tissue Effects in the Clinic effort and recently published literature. Radiomics models include features from the Image Biomarker Standardization Initiative and application-specific features found to be relevant across multiple sites and image modalities. The library is distributed as a module within CERR at https://www.github.com/cerr/CERR under the GNU-GPL copyleft with additional restrictions on clinical and commercial use and provision to dual license in future.