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

Baseline shift corrections towards the heart: External validation of the impact on survival in early-stage NSCLC patients

PURPOSE

To externally validate Johnson-Hart et al. findings: the association of tumor baseline shifts towards the heart with overall survival (OS) in SBRT for NSCLC. Further analysis included investigating the presence of interfractional heart baseline shifts and the association of OS with heart dose change during treatment.

METHODS

Data from 416 SBRT early-stage NSCLC patients was collected. Pearson's correlations (PCCs) between clinical variables and treatment-averaged tumor shifts towards/away from the heart were explored. Validation of published multivariable Cox model was performed. PCCs between heart and tumor baseline shifts were analyzed. Dose accumulation was performed following daily CBCT-to-pCT deformable registration. Maximum heart dose (D0) was computed for planned and accumulated doses. Differences in OS according to shifts towards/away from the heart or D0 increase/decrease were analyzed. Significant D0 differences between patients with D0 increase/decrease and different tumor locations were explored.

RESULTS

Tumor shifts towards/away from the heart showed no significant association with OS (p = 0.91). Distance between PTV and heart correlated significantly (PCC = 0.18) with shifts to the heart. Cox model did not validate in our cohort. Heart presented baseline shifts positively correlated with tumor baseline shifts in all three directions (PCC ≥ 0.38; p < 0.001). Counterintuitively, patients experiencing increased D0 during treatment showed significantly better OS (p = 0.0077). Upper-lobe tumor patients with increased D0 had lower D0 than those with decreased D0 (right-upper-lobe p ≤ 0.018).

CONCLUSIONS

In our SBRT cohort, the shifts towards the heart were not associated with worse OS. Moderate correlations were found between tumor and heart baseline shifts in each direction. Moreover, the distance between the PTV and the heart showed a significant correlation with shifts to the heart.

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.

More than one way to skin a dose volume: the impact of dose-surface map calculation approach on study reproducibility

Objective.Dose-surface maps (DSMs) provide spatial representations of the radiation dose to organ surfaces during radiotherapy and are a valuable tool for identifying dose deposition patterns that are predictive of radiation toxicities. Over the years, many different DSM calculation approaches have been introduced and used in dose-outcome studies. However, little consideration has been given to how these calculation approaches may be impacting the reproducibility of studies in the field. Therefore, we conducted an investigation to determine the level of equivalence of DSMs calculated with different approaches and their subsequent impact on study results.Approach.Rectum and bladder DSMs were calculated for 20 prostate radiotherapy patients using combinations of the most common slice orientation and spacing styles in the literature. Equivalence of differently calculated DSMs was evaluated using pixel-wise comparisons and DSM features (rectum only). Finally, mock cohort comparison studies were conducted with DSMs calculated using each approach to determine the level of dosimetric study reproducibility between calculation approaches.Main results.We found that rectum DSMs calculated using the planar and non-coplanar orientation styles were non-equivalent in the posterior rectal region and that equivalence of DSMs calculated with different slice spacing styles was conditional on the choice of inter-slice distance used. DSM features were highly sensitive to choice of slice orientation style and DSM sampling resolution. Finally, while general result trends were consistent between the comparison studies performed using different DSMs, statisitically significant subregions and features could vary greatly in position and magnitude.Significance.We have determined that DSMs calculated with different calculation approaches are frequently non-equivalent and can lead to differing conclusions between studies performed using the same dataset. We recommend that the DSM research community work to establish consensus calculation approaches to ensure reproducibility within the field.

Selective sparing of bladder and rectum sub-regions in radiotherapy of prostate cancer combining knowledge-based automatic planning and multicriteria optimization

Background and Purpose

The association between dose to selected bladder and rectum symptom-related sub-regions (SRS) and late toxicity after prostate cancer radiotherapy has been evidenced by voxel-wise analyses. The aim of the current study was to explore the feasibility of combining knowledge-based (KB) and multi-criteria optimization (MCO) to spare SRSs without compromising planning target volume (PTV) dose delivery, including pelvic-node irradiation.

Materials and Methods

Forty-five previously treated patients (74.2 Gy/28fr) were selected and SRSs (in the bladder, associated with late dysuria/hematuria/retention; in the rectum, associated with bleeding) were generated using deformable registration. A KB model was used to obtain clinically suitable plans (KB-plan). KB-plans were further optimized using MCO, aiming to reduce dose to the SRSs while safeguarding target dose coverage, homogeneity and avoiding worsening dose volume histograms of the whole bladder, rectum and other organs at risk. The resulting MCO-generated plans were examined to identify the best-compromise plan (KB + MCO-plan).

Results

The mean SRS dose decreased in almost all patients for each SRS. D1% also decreased in the large majority, less frequently for dysuria/bleeding SRS. Mean differences were statistically significant (p < 0.05) and ranged between 1.3 and 2.2 Gy with maximum reduction of mean dose up to 3-5 Gy for the four SRSs. The better sparing of SRSs was obtained without compromising PTVs coverage.

Conclusions

Selectively sparing SRSs without compromising PTV coverage is feasible and has the potential to reduce toxicities in prostate cancer radiotherapy. Further investigation to better quantify the expected risk reduction of late toxicities is warranted.

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.

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.

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.

Technical note: rtdsm-An open-source software for radiotherapy dose-surface map generation and analysis

BACKGROUND

Dose-outcome studies in radiation oncology have historically excluded spatial information due to dose-volume histograms being the most dominant source of dosimetric information. In recent years, dose-surface maps (DSMs) have become increasingly popular for characterization of spatial dose distributions and identification of radiosensitive subregions for hollow organs. However, methodological variations and lack of open-source, publicly offered code-sharing between research groups have limited reproducibility and wider adoption.

PURPOSE

This paper presents rtdsm, an open-source software for DSM calculation with the intent to improve the reproducibility of and the access to DSM-based research in medical physics and radiation oncology.

METHODS

A literature review was conducted to identify essential functionalities and prevailing calculation approaches to guide development. The described software has been designed to calculate DSMs from DICOM data with a high degree of user customizability and to facilitate DSM feature analysis. Core functionalities include DSM calculation, equivalent dose conversions, common DSM feature extraction, and simple DSM accumulation.

RESULTS

A number of use cases were used to qualitatively and quantitatively demonstrate the use and usefulness of rtdsm. Specifically, two DSM slicing methods, planar and noncoplanar, were implemented and tested, and the effects of method choice on output DSMs were demonstrated. An example comparison of DSMs from two different treatments was used to highlight the use cases of various built-in analysis functions for equivalent dose conversion and DSM feature extraction.

CONCLUSIONS

We developed and implemented rtdsm as a standalone software that provides all essential functionalities required to perform a DSM-based study. It has been made freely accessible under an open-source license on Github to encourage collaboration and community use.

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.

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.

Image-based data mining applies to data collected from children

PURPOSE

Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses that has been successfully applied in adult data. Because anatomic variability and side effects of interest differ for children compared to adults, we investigated the feasibility of IBDM for pediatric analyses.

METHODS

We tested IBDM with CT images and dose distributions collected from 167 children (aged 10 months to 20 years) who received proton radiotherapy for primary brain tumors. We used data from four reference patients to assess IBDM sensitivity to reference selection. We quantified spatial-normalization accuracy via contour distances and deviations of the centers-of-mass of brain substructures. We performed dose comparisons with simplified and modified clinical dose distributions with a simulated effect, assessing their accuracy via sensitivity, positive predictive value (PPV) and Dice similarity coefficient (DSC).

RESULTS

Spatial normalizations and dose comparisons were insensitive to reference selection. Normalization discrepancies were small (average contour distance < 2.5 mm, average center-of-mass deviation < 6 mm). Dose comparisons identified differences (p < 0.01) in 81% of simplified and all modified clinical dose distributions. The DSCs for simplified doses were high (peak frequency magnitudes of 0.9-1.0). However, the PPVs and DSCs were low (maximum 0.3 and 0.4, respectively) in the modified clinical tests.

CONCLUSIONS

IBDM is feasible for childhood late-effects research. Our findings may inform cohort selection in future studies of pediatric radiotherapy dose responses and facilitate treatment planning to reduce treatment-related toxicities and improve quality of life among childhood cancer survivors.

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

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Cardiotoxicity is a common complication of lung cancer radiotherapy.

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Segmentation of cardiac substructures is time-consuming and challenging.

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Deep learning segmentation tools can perform this task in 3D and 4D scans.

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Performance is high when assessed geometrically, dosimetrically and clinically.

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Auto-segmentation tools may accelerate clinical workflows and enable research.

Background

Emerging data suggest that dose-sparing several key cardiac regions is prognostically beneficial in lung cancer radiotherapy. The cardiac substructures are challenging to contour due to their complex geometry, poor soft tissue definition on computed tomography (CT) and cardiorespiratory motion artefact. A neural network was previously trained to generate the cardiac substructures using three-dimensional radiotherapy planning CT scans (3D-CT). In this study, the performance of that tool on the average intensity projection from four-dimensional (4D) CT scans (4D-AVE), now commonly used in lung radiotherapy, was evaluated.

Materials and Methods

The 4D-AVE of n=20 patients completing radiotherapy for lung cancer 2015–2020 underwent manual and automated cardiac substructure segmentation. Manual and automated substructures were compared geometrically and dosimetrically. Two senior clinicians also qualitatively assessed the auto-segmentation tool’s output.

Results

Geometric comparison of the automated and manual segmentations exhibited high levels of similarity across parameters, including volume difference (11.8% overall) and Dice similarity coefficient (0.85 overall), and were consistent with 3D-CT performance. Differences in mean (median 0.2 Gy, range −1.6–0.3 Gy) and maximum (median 0.4 Gy, range −2.2–0.9 Gy) doses to substructures were generally small. Nearly all structures (99.5 %) were deemed to be appropriate for clinical use without further editing.

Conclusions

Cardiac substructure auto-segmentation using a deep learning-based tool trained on a 3D-CT dataset was feasible on the 4D-AVE scan, meaning this tool is suitable for use on 4D-CT radiotherapy planning scans. Application of this tool would increase the practicality of routine clinical cardiac substructure delineation, and enable further cardiac radiation effects research.

A Comparison of Isotoxic Dose-escalated Radiotherapy in Lung Cancer with Moderate Deep Inspiration Breath Hold, Mid-ventilation and Internal Target Volume Techniques

AIMS

With interest in normal tissue sparing and dose-escalated radiotherapy in the treatment of inoperable locally advanced non-small cell lung cancer, this study investigated the impact of motion-managed moderate deep inspiration breath hold (mDIBH) on normal tissue sparing and dose-escalation potential and compared this to planning with a four-dimensional motion-encompassing internal target volume or motion-compensating mid-ventilation approach.

MATERIALS AND METHODS

Twenty-one patients underwent four-dimensional and mDIBH planning computed tomography scans. Internal and mid-ventilation target volumes were generated on the four-dimensional scan, with mDIBH target volumes generated on the mDIBH scan. Isotoxic target dose-escalation guidelines were used to generate six plans per patient: three with a target dose cap and three without. Target dose-escalation potential, normal tissue complication probability and differences in pre-specified dose-volume metrics were evaluated for the three motion-management techniques.

RESULTS

The mean total lung volume was significantly greater with mDIBH compared with four-dimensional scans. Lung dose (mean and V21 Gy) and mean heart dose were significantly reduced with mDIBH in comparison with four-dimensional-based approaches, and this translated to a significant reduction in heart and lung normal tissue complication probability with mDIBH. In 20/21 patients, the trial target prescription dose cap of 79.2 Gy was achievable with all motion-management techniques.

CONCLUSION

mDIBH aids lung and heart dose sparing in isotoxic dose-escalated radiotherapy compared with four-dimensional planning techniques. Given concerns about lung and cardiac toxicity, particularly in an era of consolidation immunotherapy, reduced normal tissue doses may be advantageous for treatment tolerance and outcome.

Major adverse cardiac event risk prediction model incorporating baseline cardiac disease, hypertension, and logarithmic left anterior descending coronary artery radiation dose in lung cancer (CHyLL)

BACKGROUND AND PURPOSE

In patients with locally advanced non-small cell lung cancer (LA-NSCLC) post-radiotherapy, mean heart dose (MHD) and the percent of left anterior descending (LAD) coronary artery receiving ≥15Gy (LADV15) are associated with major adverse cardiac events (MACE). We developed a MACE prediction model in this population.

MATERIALS AND METHODS

Total 701 patients with LA-NSCLC treated with curative-intent radiotherapy reviewed, split by diagnosis date into "development" (n=500) and later (n=201) "test" cohorts. Development patients were analyzed using a multivariable Cox-proportional hazard model with backward elimination scheme (Bonferroni-adjusted α=0.025). Potential predictors were selected a priori: age, coronary heart disease (CHD), Framingham Risk, hypertension, MHD, LADV15, intensity modulated radiotherapy use, and CHD and LADV15 interaction (CHD:LADV15). Cardiac doses as quadratic, square root, and logarithmic (ln[X+1]) forms were explored. Models were internally validated with bootstrapping.

RESULTS

Final model incorporated CHD, Hypertension, Logarithmic LADV15, and CHD:ln[LADV15+1] (CHyLL; β coefficients: 5.51, 1.28, 1.48, -1.36; all p<0.006; bootstrapping c-index: 0.80; test cohort c-index: 0.76). Possible risk score range: 0-8.11. MACE incidence was 6.8% and 23.6% at 48 months (p=0.041), and survival rates were 51.6% and 35.0% (p=0.099), in the low-risk (score <5.00) and high-risk (score ≥5) test groups, respectively. Using the model, calculated LADV15 constraints for patients without CHD were 11.3% and 28.3% for those with and without hypertension, respectively, to remain low-risk.

CONCLUSIONS

Pre-existing CHD, hypertension, and LADV15 were important factors in predicting MACE after radiotherapy. CHyLL has the potential to estimate personalized LADV15 constraints based on cardiac risk factors and acceptable MACE thresholds.

Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer

BACKGROUND AND PURPOSE

To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, for predicting weekly anatomical changes of lung tumor and esophagus during definitive radiotherapy, incorporate the potential tumor shrinkage into a predictive treatment planning paradigm, and improve the therapeutic ratio.

METHODS AND MATERIALS

Seq2Seq starts with the primary tumor and esophagus observed on the planning CT to predict their geometric evolution during radiotherapy on a weekly basis, and subsequently updates the predictions with new snapshots acquired via weekly CBCTs. Seq2Seq is equipped with convolutional long short term memory to analyze the spatial-temporal changes of longitudinal images, trained and validated using a dataset including sixty patients. Predictive plans were optimized according to each weekly prediction and made ready for weekly deployment to mitigate the clinical burden of online weekly replanning.

RESULTS

Seq2Seq tracks structural changes well: DICE between predicted and actual weekly tumor and esophagus were (0.83 ± 0.10, 0.79 ± 0.14, 0.78 ± 0.12, 0.77 ± 0.12, 0.75 ± 0.12, 0.71 ± 0.17), and (0.72 ± 0.16, 0.73 ± 0.11, 0.75 ± 0.08, 0.74 ± 0.09, 0.72 ± 0.14, 0.71 ± 0.14), respectively, while the average Hausdorff distances were within 2 mm. Evaluating dose to the actual weekly tumor and esophagus, a 4.2 Gy reduction in esophagus mean dose while maintaining 60 Gy tumor coverage was achieved with the predictive weekly plans, compared to the plan optimized using the initial tumor and esophagus alone, primarily due to noticeable tumor shrinkage during radiotherapy.

CONCLUSION

It is feasible to predict the longitudinal changes of tumor and esophagus with the Seq2Seq, which could lead to improving the efficiency and effectiveness of lung adaptive radiotherapy.

Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations

For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose distribution, and potentially its correlation with anatomy, can provide more robust associations with toxicity and seed more general NTCP models. Such approaches are culminating in the application of computationally intensive processes such as machine learning and the application of neural networks. The opportunities these approaches have for individualising treatment, predicting toxicity and expanding the solution space for radiation therapy are substantial and have clearly widespread and disruptive potential. Impediments to reaching that potential include issues associated with data collection, model generalisation and validation. This review examines the role of spatial models of complication and summarises relevant published studies. Sources of data for these studies, appropriate statistical methodology frameworks for processing spatial dose information and extracting relevant features are described. Spatial complication modelling is consolidated as a pathway to guiding future developments towards effective, complication-free radiotherapy treatment.

Dosimetric impact from cardiac motion to heart substructures in thoracic cancer patients treated with a magnetic resonance guided radiotherapy system

Few studies have examined the cardiac volume and radiation dose differences among cardiac phases during radiation therapy (RT). Such information is crucial to dose reconstruction and understanding of RT related cardiac toxicity. In a cohort of nine patients, we studied the changes in the volume and doses of several cardiac substructures between the end-diastolic and end-systolic phases based on the clinical magnetic resonance-guided RT (MRgRT) treatment plans. Significant differences in the volume and dose between the two phases were observed. Onboard cardiac cine MRI holds promise for patient-specific cardiac sparing treatment designs.