Treatment plan quality during online adaptive re-planning

Measurement and Incorporation of Laryngeal Motion Using cine-MRI on an MR-Linear Accelerator to Generate Radiation Therapy Plans for Early-stage Squamous Cell Cancers of the Glottis

Purpose

Swallow-related motion of the larynx is most significant in the cranio-caudal directions and of` short duration. Conventional target definition for radical radiation therapy includes coverage of the whole larynx. This study longitudinally examined respiration- and swallow-related laryngeal motions using cine-magnetic resonance imaging. We further analyzed the dosimetry to organs at risk by comparing 3D-conformal radiation therapy (3D-CRT), volumetric modulated arc therapy (VMAT), and intensity modulated radiation therapy (IMRT) techniques.

Methods

Fifteen patients with T1-2 N0 glottic squamous cell carcinomas were prospectively recruited for up to 3 cine-MRI scans on the Elekta Unity MR-Linear accelerator, at the beginning, middle, and end of a course of radical radiation therapy. Swallow frequency and motion of the hyoid bone, cricoid and thyroid cartilages, and vocal cords were recorded during swallow and rest. Adapted treatment volumes consisted of gross tumor volume + 0.5-1 cm to a clinical target volume with an additional internal target volume (ITV) for personalized resting-motion. Swallow-related motion was deemed infrequent and was not accounted for in the ITV. We compared radiation therapy plans for 3D-CRT (whole larynx), VMAT (whole larynx), and VMAT and IMRT (ITV for resting motion).

Results

Resting- and swallow-related motions were most prominent in the cranio-caudal plane. There were no significant changes in the magnitude of motion over the course of radiation therapy. There was a trend of a progressive reduction in the frequency of swallow. Treatment of partial larynx volumes with intensity modulated methods significantly reduced the dose to carotid arteries, compared with treatment of whole larynx volumes. Robustness analysis demonstrated that when accounting for intrafraction swallow, the total dose delivered to the ITV/planning target volume was maintained at above 95%.

Conclusions

Swallow-related motions are infrequent and accounting for resting motion in an ITV is sufficient. VMAT/IMRT techniques that treat more conformal targets can significantly spare critical organs at risk such as the carotid arteries and thyroid gland, potentially reducing the risk of carotid artery stenosis-related complications and other long-term complications.

MRI-Guided Radiation Therapy-An Emerging and Disruptive Process of Care: Healthcare Economic and Policy Considerations

MRI-guided radiation therapy (MRgRT) is an emerging, innovative technology that provides opportunities to transform and improve the current clinical care process in radiation oncology. As with many new technologies in radiation oncology, careful evaluation from a healthcare economic and policy perspective is required for its successful implementation. In this review article, we describe the current evidence surrounding MRgRT, framing it within the context of value within the healthcare system. Additionally, we highlight areas in which MRgRT may disrupt the current process of care, and discuss the evidence thresholds and timeline required for the widespread adoption of this promising technology.

Full daily re-optimization improves plan quality during online adaptive radiotherapy

Background and purpose

Daily online treatment plan adaptation requires a fast workflow and planning process. Current online planning consists of adaptation of a predefined reference plan, which might be suboptimal in cases of large anatomic changes. The aim of this study was to investigate plan quality differences between the current online re-planning approach and a complete re-optimization.

Material and methods

Magnetic resonance linear accelerator reference plans for ten prostate cancer patients were automatically generated using particle swarm optimization (PSO). Adapted plans were created for each fraction using (1) the current re-planning approach and (2) full PSO re-optimization and evaluated overall compliance with institutional dose-volume criteria compared to (3) clinically delivered fractions. Relative volume differences between reference and daily anatomy were assessed for planning target volumes (PTV60, PTV57.6), rectum and bladder and correlated with dose-volume results.

Results

The PSO approach showed significantly higher adherence to dose-volume criteria than the reference approach and clinical fractions (p < 0.001). In 74 % of PSO plans at most one criterion failed compared to 56 % in the reference approach and 41 % in clinical plans. A fair correlation between PTV60 D98% and relative bladder volume change was observed for the reference approach. Bladder volume reductions larger than 50 % compared to the reference plan recurrently decreased PTV60 D98% below 56 Gy.

Conclusion

Complete re-optimization maintained target coverage and organs at risk sparing even after large anatomic variations. Re-planning based on daily magnetic resonance imaging was sufficient for small variations, while large variations led to decreasing target coverage and organ-at-risk sparing.

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.

Impact of intrafraction motion in pancreatic cancer treatments with MR-guided adaptive radiation therapy

Purpose

The total time of radiation treatment delivery for pancreatic cancer patients with daily online adaptive radiation therapy (ART) on an MR-Linac can range from 50 to 90 min. During this period, the target and normal tissues undergo changes due to respiration and physiologic organ motion. We evaluated the dosimetric impact of the intrafraction physiological organ changes.

Methods

Ten locally advanced pancreatic cancer patients were treated with 50 Gy in five fractions with intensity-modulated respiratory-gated radiation therapy on a 0.35-T MR-Linac. Patients received both pre- and post-treatment volumetric MRIs for each fraction. Gastrointestinal organs at risk (GI-OARs) were delineated on the pre-treatment MRI during the online ART process and retrospectively on the post-treatment MRI. The treated dose distribution for each adaptive plan was assessed on the post-treatment anatomy. Prescribed dose volume histogram metrics for the scheduled plan on the pre-treatment anatomy, the adapted plan on the pre-treatment anatomy, and the adapted plan on post-treatment anatomy were compared to the OAR-defined criteria for adaptation: the volume of the GI-OAR receiving greater than 33 Gy (V33Gy) should be ≤1 cubic centimeter.

Results

Across the 50 adapted plans for the 10 patients studied, 70% were adapted to meet the duodenum constraint, 74% for the stomach, 12% for the colon, and 48% for the small bowel. Owing to intrafraction organ motion, at the time of post-treatment imaging, the adaptive criteria were exceeded for the duodenum in 62% of fractions, the stomach in 36%, the colon in 10%, and the small bowel in 48%. Compared to the scheduled plan, the post-treatment plans showed a decrease in the V33Gy, demonstrating the benefit of plan adaptation for 66% of the fractions for the duodenum, 95% for the stomach, 100% for the colon, and 79% for the small bowel.

Conclusion

Post-treatment images demonstrated that over the course of the adaptive plan generation and delivery, the GI-OARs moved from their isotoxic low-dose region and nearer to the dose-escalated high-dose region, exceeding dose-volume constraints. Intrafraction motion can have a significant dosimetric impact; therefore, measures to mitigate this motion are needed. Despite consistent intrafraction motion, plan adaptation still provides a dosimetric benefit.

Online adaptive radiotherapy: Assessment of planning technique and its impact on longitudinal plan quality robustness in pancreatic cancer

BACKGROUND AND PURPOSE

Planning on a static dataset that reflects the simulation day anatomy is routine for SBRT. We hypothesize the quality of on-table adaptive plans is similar to the baseline plan when delivering stereotactic MR-guided adaptive radiotherapy (SMART) for pancreatic cancer (PCa).

MATERIALS AND METHODS

Sixty-seven inoperable PCa patients were prescribed 50 Gy/5-fraction SMART. Baseline planning included: 3-5 mm gastrointestinal (GI) PRV, 50 Gy optimization target (PTVopt) based on GI PRV, conformality rings, and contracted GTV to guide the hotspot. For each adaptation, GI anatomy was re-contoured, followed by re-optimization. Plan quality was evaluated for target coverage (TC = PTVopt V100%/volume), PTV D90% and D80%, homogeneity index (HI = PTVopt D2%/D98%), prescription isodose/target volume (PITV), low-dose conformity (D2cm = maximum dose at 2 cm from PTVopt/Rx dose), and gradient index (R50%=50% Rx isodose volume/PTVopt volume).A novel global planning metric, termed the Pancreas Adaptive Radiotherapy Score (PARTS), was developed and implemented based on GI OAR sparing, PTV/GTV coverage, and conformality. Adaptive robustness (baseline to fraction 1) and stability (difference between two fractions with highest GI PRV variation) were quantified.

RESULTS

OAR constraints were met on all baseline (n = 67) and adaptive (n = 318) plans. Coverage for baseline/adaptive plans was mean ± SD at 44.9 ± 5.8 Gy/44.3 ± 5.5 Gy (PTV D80%), 50.1 ± 4.2 Gy/49.1 ± 4.7 Gy (PTVopt D80%), and 80%±18%/74%±18% (TC), respectively. Mean homogeneity and conformality for baseline/adaptive plans were 0.87 ± 0.25/0.81 ± 0.30 (PITV), 3.81 ± 1.87/3.87 ± 2.0 (R50%), 1.53 ± 0.23/1.55 ± 0.23 (HI), and 58%±7%/59%±7% (D2cm), respectively. PARTS was found to be a sensitive metric due to its additive influence of geometry changes on PARTS' sub-metrics. There were no statistical differences (p > 0.05) for stability, except for PARTS (p = 0.04, median difference -0.6%). Statistical differences for robustness when significant were small for most metrics (<2.0% median). Median adaptive re-optimizations were 2.

CONCLUSION

We describe a 5-fraction ablative SMART planning approach for PCa that is robust and stable during on-table adaption, due to gradients controlled by a GI PRV technique and the use of rings. These findings are noteworthy given that daily interfraction anatomic GI OAR differences are routine, thus necessitating on-table adaptation. This work supports feasibility towards utilizing a patient-independent, template on-table adaptive approach.

Patient-specific quality assurance strategies for synthetic computed tomography in magnetic resonance-only radiotherapy of the abdomen

Background and purpose

The superior tissue contrast of magnetic resonance (MR) compared to computed tomography (CT) led to an increasing interest towards MR-only radiotherapy. For the latter, the dose calculation should be performed on a synthetic CT (sCT). Patient-specific quality assurance (PSQA) methods have not been established yet and this study aimed to assess several software-based solutions.

Materials and methods

A retrospective study was performed on 20 patients treated at an MR-Linac, which were selected to evenly cover four subcategories: (i) standard, (ii) air pockets, (iii) lung and (iv) implant cases. The neural network (NN) CycleGAN was adopted to generate a reference sCT, which was then compared to four PSQA methods: (A) water override of body, (B) five tissue classes with bulk densities, (C) sCT generated by a separate NN (pix2pix) and (D) deformed CT.

Results

The evaluation of the dose endpoints demonstrated that while all methods A-D provided statistically equivalent results (p = 0.05) within the 2% level for the standard cases (i), only the methods C-D guaranteed the same result over the whole cohort. The bulk densities override was shown to be a valuable method in absence of lung tissue within the beam path.

Conclusion

The observations of this study suggested that the use of an additional sCT generated by a separate NN was an appropriate tool to perform PSQA of a sCT in an MR-only workflow at an MR-Linac. The time and dose endpoints requirements were respected, namely within 10 min and 2%.

Synthetic computed tomography for low-field magnetic resonance-only radiotherapy in head-and-neck cancer using residual vision transformers

Background and purpose

Synthetic computed tomography (sCT) scans are necessary for dose calculation in magnetic resonance (MR)-only radiotherapy. While deep learning (DL) has shown remarkable performance in generating sCT scans from MR images, research has predominantly focused on high-field MR images. This study presents the first implementation of a DL model for sCT generation in head-and-neck (HN) cancer using low-field MR images. Specifically, the use of vision transformers (ViTs) was explored.

Materials and methods

The dataset consisted of 31 patients, resulting in 196 pairs of deformably-registered computed tomography (dCT) and MR scans. The latter were obtained using a balanced steady-state precession sequence on a 0.35T scanner. Residual ViTs were trained on 2D axial, sagittal, and coronal slices, respectively, and the final sCTs were generated by averaging the models' outputs. Different image similarity metrics, dose volume histogram (DVH) deviations, and gamma analyses were computed on the test set (n = 6). The overlap between auto-contours on sCT scans and manual contours on MR images was evaluated for different organs-at-risk using the Dice score.

Results

The median [range] value of the test mean absolute error was 57 [37-74] HU. DVH deviations were below 1% for all structures. The median gamma passing rates exceeded 94% in the 2%/2mm analysis (threshold = 90%). The median Dice scores were above 0.7 for all organs-at-risk.

Conclusions

The clinical applicability of DL-based sCT generation from low-field MR images in HN cancer was proved. High sCT-dCT similarity and dose metric accuracy were achieved, and sCT suitability for organs-at-risk auto-delineation was shown.

Knowledge-based adaptive planning quality assurance using dosimetric indicators for stereotactic adaptive radiotherapy for pancreatic cancer

INTRODUCTION

We aimed to develop knowledge-based tools for robust adaptive radiotherapy (ART) planning to determine on-table adaptive DVH metric variations or planning process errors for stereotactic pancreatic ART. We developed volume-based dosimetric identifiers to identify deviations of ART plans from simulation plans.

MATERIALS AND METHODS

Two patient cohorts who were treated on MR-Linac for pancreas cancer were included in this retrospective study; a training cohort and a validation cohort. All patients received 50 Gy in 5 fractions. PTV-OPT was generated by subtracting the critical organs plus a 5 mm-margin from PTV. Several metrics that potentially can identify failure-modes were calculated including PTV & PTV_OPT V95% and PTV & PTV_OPT D95%/D5%. The difference between each DVH metric in each adaptive plan with the DVH metric in simulation plan was calculated. The 95% confidence interval (CI) of the variations in each DVH metric was calculated for the patient training cohort. Variations in DVH metrics that exceeded the 95% CI for all fractions in training and validation cohort were flagged for retrospective investigation for root-cause analysis to determine their predictive power for identifying failure-modes.

RESULTS

The CIs for the PTV & PTV_OPT V95% and PTV & PTV_OPT D95%/D5% were ± 13%, ± 5%, ± 0.1, ± 0.03, respectively. We estimated the positive predictive value and negative predictive value of our method to be 77% and 89%, respectively, for the training cohort, and 80% for both in the validation cohort.

DISCUSSION

We developed dosimetric indicators for ART planning QA to identify population-based deviations or planning errors during online adaptive process for stereotactic pancreatic ART. This technology may be useful as an ART clinical trial QA tool and improve overall ART quality at an institution.

MRI-LINAC: A transformative technology in radiation oncology

Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.

Machine-learning-based prediction of the effectiveness of the delivered dose by exhale-gated radiotherapy for locally advanced lung cancer: The additional value of geometric over dosimetric parameters alone

Purpose

This study aimed to assess interfraction stability of the delivered dose distribution by exhale-gated volumetric modulated arc therapy (VMAT) or intensity-modulated arc therapy (IMAT) for lung cancer and to determine dominant prognostic dosimetric and geometric factors.

Methods

Clinical target volume (CTV_Plan) from the planning CT was deformed to the exhale-gated daily CBCT scans to determine CTV_i, treated by the respective dose fraction. The equivalent uniform dose of the CTV_i was determined by the power law (gEUD_i) and cell survival model (EUD_iSF) as effectiveness measure for the delivered dose distribution. The following prognostic factors were analyzed: (I) minimum dose within the CTV_i (D_{min_i}), (II) Hausdorff distance (HDD_i) between CTV_i and CTV_Plan, (III) doses and deformations at the point in CTV_Plan at which the global minimum dose over all fractions per patient occurs (PD_{min_global_i}), and (IV) deformations at the point over all CTV_i margins per patient with the largest Hausdorff distance (HDPw_orst). Prognostic value and generalizability of the prognostic factors were examined using cross-validated random forest or multilayer perceptron neural network (MLP) classifiers. Dose accumulation was performed using back deformation of the dose distribution from CTV_i to CTV_Plan.

Results

Altogether, 218 dose fractions (10 patients) were evaluated. There was a significant interpatient heterogeneity between the distributions of the normalized gEUD_i values (p<0.0001, Kruskal-Wallis tests). Accumulated gEUD over all fractions per patient was 1.004-1.023 times of the prescribed dose. Accumulation led to tolerance of ~20% of fractions with gEUD_i <93% of the prescribed dose. Normalized D_min >60% was associated with predicted gEUD values above 95%. D_min had the highest importance for predicting the gEUD over all analyzed prognostic parameters by out-of-bag loss reduction using the random forest procedure. Cross-validated random forest classifier based on D_min as the sole input had the largest Pearson correlation coefficient (R=0.897) in comparison to classifiers using additional input variables. The neural network performed better than the random forest classifier, and the gEUD values predicted by the MLP classifier with D_min as the sole input were correlated with the gEUD values characterized by R=0.933 (95% CI, 0.913-0.948). The performance of the full MLP model with all geometric input parameters was slightly better (R=0.952) than that based on D_min (p=0.0034, Z-test).

Conclusion

Accumulated dose distributions over the treatment series were robust against interfraction CTV deformations using exhale gating and online image guidance. D_min was the most important parameter for gEUD prediction for a single fraction. All other parameters did not lead to a markedly improved generalizable prediction. Dosimetric information, especially location and value of D_min within the CTV _i , are vital information for image-guided radiation treatment.

Auto-detection of necessity for MRI-guided online adaptive replanning using a machine learning classifier

PURPOSE

MRI-guided adaptive radiation therapy (MRgART), particularly daily online adaptive replanning (OLAR) can substantially improve radiation therapy delivery, however, it can be labor-intensive and time-consuming. Currently, the decision to perform OLAR for a treatment fraction is determined subjectively. In this work, we develop a machine learning algorithm based on structural similarity index measure (SSIM) and change in entropy to quickly and objectively determine whether OLAR is necessary for a daily MRI set.

METHODS

A total of 109 daily MRI sets acquired on a 1.5T MR-Linac during MRgART for 22 pancreatic cancer patients each treated with five fractions were retrospectively analyzed. For each daily MRI set, OLAR and reposition (No-OLAR) plans were created and the superior plan with the daily fraction determined per clinical dose-volume criteria. SSIM and entropy maps were extracted from each daily MRI set, with respect to its reference (e.g., dry-run) MRI in the region enclosed by 50-100% isodose surfaces. A total of six common features were extracted from SSIM maps. Pearson's rank correlation coefficient was utilized to rule out redundant SSIM features. A t-test was used to determine significant SSIM features which were combined with the change in entropy to develop anensemble machine classifier with fivefold cross validation. The performance of the classifier was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

A machine learning classifier model using two SSIM features (mean and full width at half maximum) and change in entropy was determined to be able to significantly discriminate between No-OLAR and OLAR groups. The obtained machine learning ensemble classifier can predict OLAR necessity with a cross validated AUC of 0.93. Misclassification was found primarily for No-OLAR cases with dosimetric plan quality closely comparable to the corresponding OLAR plans, thus, are not a major practical concern.

CONCLUSION

A machine learning classifier based on simple first-order image features, that is, SSIM features and change in entropy, was developed to determine when OLAR is necessary for a daily MRI set with practical acceptable prediction accuracy. This classifier may be implemented in the MRgART process to automatically and objectively determine if OLAR is required following daily MRI.

An independent Monte Carlo-based IMRT QA tool for a 0.35 T MRI-guided linear accelerator

PURPOSE

To develop an independent log file-based intensity-modulated radiation therapy (IMRT) quality assurance (QA) tool for the 0.35 T magnetic resonance-linac (MR-linac) and investigate the ability of various IMRT plan complexity metrics to predict the QA results. Complexity metrics related to tissue heterogeneity were also introduced.

METHODS

The tool for particle simulation (TOPAS) Monte Carlo code was utilized with a previously validated linac head model. A cohort of 29 treatment plans was selected for IMRT QA using the developed QA tool and the vendor-supplied adaptive QA (AQA) tool. For 27 independent patient cases, various IMRT plan complexity metrics were calculated to assess the deliverability of these plans. A correlation between the gamma pass rates (GPRs) from the AQA results and calculated IMRT complexity metrics was determined using the Pearson correlation coefficients. Tissue heterogeneity complexity metrics were calculated based on the gradient of the Hounsfield units.

RESULTS

The median and interquartile range for the TOPAS GPRs (3%/3 mm criteria) were 97.24% and 3.75%, respectively, and were 99.54% and 0.36% for the AQA tool, respectively. The computational time for TOPAS ranged from 4 to 8 h to achieve a statistical uncertainty of <1.5%, whereas the AQA tool had an average calculation time of a few minutes. Of the 23 calculated IMRT plan complexity metrics, the AQA GPRs had correlations with 7 out of 23 of the calculated metrics. Strong correlations (|r| > 0.7) were found between the GPRs and the heterogeneity complexity metrics introduced in this work.

CONCLUSIONS

An independent MC and log file-based IMRT QA tool was successfully developed and can be clinically deployed for offline QA. The complexity metrics will supplement QA reports and provide information regarding plan complexity.

Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate

Background

Hybrid magnetic resonance (MR)-Linac systems have recently been introduced into clinical practice. The systems allow online adaption of the treatment plan with the aim of compensating for interfractional anatomical changes. The aim of this study was to evaluate the dose volume histogram (DVH)-based dosimetric benefits of online adaptive MR-guided radiotherapy (oMRgRT) across different tumor entities and to investigate which subgroup of plans improved the most from adaption.

Methods

Fifty patients treated with oMRgRT for five different tumor entities (liver, lung, multiple abdominal lymph nodes, pancreas, and prostate) were included in this retrospective analysis. Various target volume (gross tumor volume GTV, clinical target volume CTV, and planning target volume PTV) and organs at risk (OAR) related DVH parameters were compared between the dose distributions before and after plan adaption.

Results

All subgroups clearly benefited from online plan adaption in terms of improved PTV coverage. For the liver, lung and abdominal lymph nodes cases, a consistent improvement in GTV coverage was found, while many fractions of the prostate subgroup showed acceptable CTV coverage even before plan adaption. The largest median improvements in GTV near-minimum dose (D_98%) were found for the liver (6.3%, p < 0.001), lung (3.9%, p < 0.001), and abdominal lymph nodes (6.8%, p < 0.001) subgroups. Regarding OAR sparing, the largest median OAR dose reduction during plan adaption was found for the pancreas subgroup (-87.0%). However, in the pancreas subgroup an optimal GTV coverage was not always achieved because sparing of OARs was prioritized.

Conclusion

With online plan adaptation, it was possible to achieve significant improvements in target volume coverage and OAR sparing for various tumor entities and account for interfractional anatomical changes.

Plan quality in radiotherapy treatment planning - Review of the factors and challenges

A high-quality treatment plan aims to best achieve the clinical prescription, balancing high target dose to maximise tumour control against sufficiently low organ-at-risk dose for acceptably low toxicity. Treatment planning (TP) includes multiple steps from simulation/imaging and segmentation to technical plan production and reporting. Consistent quality across this process requires close collaboration and communication between clinical and technical experts, to clearly understand clinical requirements and priorities and also practical uncertainties, limitations and compromises. TP quality depends on many aspects, starting from commissioning and quality management of the treatment planning system (TPS), including its measured input data and detailed understanding of TPS models and limitations. It requires rigorous quality assurance of the whole planning process and it links to plan deliverability, assessable by measurement-based verification. This review highlights some factors influencing plan quality, for consideration for optimal plan construction and hence optimal outcomes for each patient. It also indicates some challenges, sources of difference and current developments. The topics considered include: the evolution of TP techniques; dose prescription issues; tools and methods to evaluate plan quality; and some aspects of practical TP. The understanding of what constitutes a high-quality treatment plan continues to evolve with new techniques, delivery methods and related evidence-based science. This review summarises the current position, noting developments in the concept and the need for further robust tools to help achieve it.

Magnetic Resonance Guided Radiotherapy for Head and Neck Cancers

Radiotherapy is an integral component of head/neck squamous cell carcinomas (HNSCCs) treatment, and technological developments including advances in image-guided radiotherapy over the past decades have offered improvements in the technical treatment of these cancers. Integration of magnetic resonance imaging (MRI) into image guidance through the development of MR-guided radiotherapy (MRgRT) offers further potential for refinement of the techniques by which HNSCCs are treated. This article provides an overview of the literature supporting the current use of MRgRT for HNSCC, challenges with its use, and developing research areas.

Dosimetric comparison of MR-guided adaptive IMRT versus 3DOF-VMAT for prostate stereotactic radiotherapy

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Prostate SBRT are treated using MR-guided adaptive IMRT (A-IMRT) and VMAT based on translation correction (3DOF-VMAT) at our institution.

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Comparison of reference and delivered dose between adaptive-IMRT and 3DOF-VMAT to assess the effect of interfractional motion.

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Despite large interfractional changes, prostate received clinically acceptable dose with a margin of 5 mm through either A-IMRT or 3DOF-VMAT.

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A-IMRT was more superior than 3DOF-VMAT in sparing the rectum in the high dose region; no difference between the two systems was observed for bladder.

Introduction

Methods & Materials

Results

Conclusions

Proposal and Evaluation of a Physician-Free, Real-Time On-Table Adaptive Radiotherapy (PF-ROAR) Workflow for the MRIdian MR-Guided LINAC

With the implementation of MR-LINACs, real-time adaptive radiotherapy has become a possibility within the clinic. However, the process of adapting a patient’s plan is time consuming and often requires input from the entire clinical team, which translates to decreased throughput and limited patient access. In this study, the authors propose and simulate a workflow to address these inefficiencies in staffing and patient throughput. Two physicians, three radiation therapists (RTT), and a research fellow each adapted bladder and bowel contours for 20 fractions from 10 representative patient plans. Contouring ability was compared via calculation of a Dice Similarity Index (DSI). The DSI for bladder and bowel based on each potential physician–therapist pair, as well as an inter-physician comparison, exhibited good overlap amongst all comparisons (p = 0.868). Plan quality was compared through calculation of the conformity index (CI), as well as an evaluation of the plan’s dose to a ‘gold standard’ set of structures. Overall, non-physician plans passed 91.2% of the time. Of the eight non-physician plans that failed their clinical evaluation, six also failed their evaluation against the ‘gold standard’. Another two plans that passed their clinical evaluation subsequently failed in their evaluation against the ‘gold standard’. Thus, the PF-ROAR process has a success rate of 97.5%, with 78/80 plans correctly adapted to the gold standard or halted at treatment. These findings suggest that a physician-free workflow can be well tolerated provided RTTs continue to develop knowledge of MR anatomy and careful attention is given to understanding the complexity of the plan prior to treatment.

Patterns of Care, Tolerability, and Safety of the First Cohort of Patients Treated on a Novel High-Field MR-Linac Within the MOMENTUM Study: Initial Results From a Prospective Multi-Institutional Registry

PURPOSE

High-field magnetic resonance-linear accelerators (MR-Linacs), linear accelerators combined with a diagnostic magnetic resonance imaging (MRI) scanner and online adaptive workflow, potentially give rise to novel online anatomic and response adaptive radiation therapy paradigms. The first high-field (1.5T) MR-Linac received regulatory approval in late 2018, and little is known about clinical use, patient tolerability of daily high-field MRI, and toxicity of treatments. Herein we report the initial experience within the MOMENTUM Study (NCT04075305), a prospective international registry of the MR-Linac Consortium.

METHODS AND MATERIALS

Patients were included between February 2019 and October 2020 at 7 institutions in 4 countries. We used descriptive statistics to describe the patterns of care, tolerability (the percentage of patients discontinuing their course early), and safety (grade 3-5 Common Terminology Criteria for Adverse Events v.5 acute toxicity within 3 months after the end of treatment).

RESULTS

A total 943 patients participated in the MOMENTUM Study, 702 of whom had complete baseline data at the time of this analysis. Patients were primarily male (79%) with a median age of 68 years (range, 22-93) and were treated for 39 different indications. The most frequent indications were prostate (40%), oligometastatic lymph node (17%), brain (12%), and rectal (10%) cancers. The median number of fractions was 5 (range, 1-35). Six patients discontinued MR-Linac treatments, but none due to an inability to tolerate repeated high-field MRI. Of the 415 patients with complete data on acute toxicity at 3-month follow-up, 18 (4%) patients experienced grade 3 acute toxicity related to radiation. No grade 4 or 5 acute toxicity related to radiation was observed.

CONCLUSIONS

In the first 21 months of our study, patterns of care were diverse with respect to clinical utilization, body sites, and radiation prescriptions. No patient discontinued treatment due to inability to tolerate daily high-field MRI scans, and the acute radiation toxicity experience was encouraging.

Operating procedures, risk management and challenges during implementation of adaptive and non-adaptive MR-guided radiotherapy: 1-year single-center experience

BACKGROUND

Main purpose was to describe procedures and identify challenges in the implementation process of adaptive and non-adaptive MR-guided radiotherapy (MRgRT), especially new risks in workflow due to the new technique. We herein report the single center experience for the implementation of (MRgRT) and present an overview on our treatment practice.

METHODS

Descriptive statistics were used to summarize clinical and technical characteristics of treatment and patient characteristics including sites treated between April 2019 and end of March 2020 after ethical approval. A risk analysis was performed to identify risks of the online adaptive workflow.

RESULTS

A summary of the processes on the MR-Linac including workflows, quality assurance and possible pitfalls is presented. 111 patients with 124 courses were treated during the first year of MR-guided radiotherapy. The most commonly treated site was the abdomen (42% of all treatment courses). 73% of the courses were daily online adapted and a high number of treatment courses (75%) were treated with stereotactic body irradiation. Only 4/382 fractions could not be treated due to a failing online adaptive quality assurance. In the risk analysis for errors, the two risks with the highest risk priority number were both in the contouring category, making it the most critical step in the workflow.

CONCLUSION

Although challenging, establishment of MRgRT as a routinely used technique at our department was successful for all sites and daily o-ART was feasible from the first day on. However, ongoing research and reports will have to inform us on the optimal indications for MRgRT because careful patient selection is necessary as it continues to be a time-consuming treatment technique with restricted availability. After risk analysis, the most critical workflow category was the contouring process, which resembles the need of experienced staff and safety check paths.

Dosimetric benefits of daily treatment plan adaptation for prostate cancer stereotactic body radiotherapy

BACKGROUND

Hypofractionation is increasingly being applied in radiotherapy for prostate cancer, requiring higher accuracy of daily treatment deliveries than in conventional image-guided radiotherapy (IGRT). Different adaptive radiotherapy (ART) strategies were evaluated with regard to dosimetric benefits.

METHODS

Treatments plans for 32 patients were retrospectively generated and analyzed according to the PACE-C trial treatment scheme (40 Gy in 5 fractions). Using a previously trained cycle-generative adversarial network algorithm, synthetic CT (sCT) were generated out of five daily cone-beam CT. Dose calculation on sCT was performed for four different adaptation approaches: IGRT without adaptation, adaptation via segment aperture morphing (SAM) and segment weight optimization (ART1) or additional shape optimization (ART2) as well as a full re-optimization (ART3). Dose distributions were evaluated regarding dose-volume parameters and a penalty score.

RESULTS

Compared to the IGRT approach, the ART1, ART2 and ART3 approaches substantially reduced the V37Gy(bladder) and V36Gy(rectum) from a mean of 7.4cm3 and 2.0cm3 to (5.9cm3, 6.1cm3, 5.2cm3) as well as to (1.4cm3, 1.4cm3, 1.0cm3), respectively. Plan adaptation required on average 2.6 min for the ART1 approach and yielded doses to the rectum being insignificantly different from the ART2 approach. Based on an accumulation over the total patient collective, a penalty score revealed dosimetric violations reduced by 79.2%, 75.7% and 93.2% through adaptation.

CONCLUSION

Treatment plan adaptation was demonstrated to adequately restore relevant dose criteria on a daily basis. While for SAM adaptation approaches dosimetric benefits were realized through ensuring sufficient target coverage, a full re-optimization mainly improved OAR sparing which helps to guide the decision of when to apply which adaptation strategy.

Dosimetric comparison of MR-linac-based IMRT and conventional VMAT treatment plans for prostate cancer

Background

The aim of this study was to evaluate and compare the performance of intensity modulated radiation therapy (IMRT) plans, planned for low-field strength magnetic resonance (MR) guided linear accelerator (linac) delivery (labelled IMRT MRL plans), and clinical conventional volumetric modulated arc therapy (VMAT) plans, for the treatment of prostate cancer (PCa). Both plans used the original planning target volume (PTV) margins. Additionally, the potential dosimetric benefits of MR-guidance were estimated, by creating IMRT MRL plans using smaller PTV margins.

Materials and methods

20 PCa patients previously treated with conventional VMAT were considered. For each patient, two different IMRT MRL plans using the low-field MR-linac treatment planning system were created: one with original (orig.) PTV margins and the other with reduced (red.) PTV margins. Dose indices related to target coverage, as well as dose-volume histogram (DVH) parameters for the target and organs at risk (OAR) were compared. Additionally, the estimated treatment delivery times and the number of monitor units (MU) of each plan were evaluated.

Results

The dose distribution in the high dose region and the target volume DVH parameters (D_98%, D_50%, D_2% and V_95%) were similar for all three types of treatment plans, with deviations below 1% in most cases. Both IMRT MRL plans (orig. and red. PTV margins) showed similar homogeneity indices (HI), however worse values for the conformity index (CI) were also found when compared to VMAT. The IMRT MRL plans showed similar OAR sparing when the orig. PTV margins were used but a significantly better sparing was feasible when red. PTV margins were applied. Higher number of MU and longer predicted treatment delivery times were seen for both IMRT MRL plans.

Conclusions

A comparable plan quality between VMAT and IMRT MRL plans was achieved, when applying the same PTV margin. However, online MR-guided adaptive radiotherapy allows for a reduction of PTV margins. With a red. PTV margin, better sparing of the surrounding tissues can be achieved, while maintaining adequate target coverage. Nonetheless, longer treatment delivery times, characteristic for the IMRT technique, have to be expected.

ESTRO-ACROP recommendations on the clinical implementation of hybrid MR-linac systems in radiation oncology

Online magnetic resonance-guided radiotherapy (oMRgRT) represents one of the most innovative applications of current image-guided radiation therapy (IGRT). The revolutionary concept of oMRgRT systems is the ability to acquire MR images for adaptive treatment planning and also online imaging during treatment delivery. The daily adaptive planning strategies allow to improve targeting accuracy while avoiding critical structures. This ESTRO-ACROP recommendation aims to provide an overview of available systems and guidance for best practice in the implementation phase of hybrid MR-linac systems. Unlike the implementation of other radiotherapy techniques, oMRgRT adds the MR environment to the daily practice of radiotherapy, which might be a new experience for many centers. New issues and challenges that need to be thoroughly explored before starting clinical treatments will be highlighted.

Adaptive Magnetic Resonance-Guided Stereotactic Body Radiotherapy: The Next Step in the Treatment of Renal Cell Carcinoma

Adaptive MR-guided radiotherapy (MRgRT) is a new treatment paradigm and its role as a non-invasive treatment option for renal cell carcinoma is evolving. The early clinical experience to date shows that real-time plan adaptation based on the daily MRI anatomy can lead to improved target coverage and normal tissue sparing. Continued technological innovations will further mitigate the challenges of organ motion and enable more advanced treatment adaptation, and potentially lead to enhanced oncologic outcomes and preservation of renal function. Future applications look promising to make a positive clinical impact and further the personalization of radiotherapy in the management of renal cell carcinoma.

Benefit of replanning in MR-guided online adaptive radiation therapy in the treatment of liver metastasis

PURPOSE

To assess the effects of daily adaptive MR-guided replanning in stereotactic body radiation therapy (SBRT) of liver metastases based on a patient individual longitudinal dosimetric analysis.

METHODS

Fifteen patients assigned to SBRT for oligometastatic liver metastases underwent daily MR-guided target localization and on-table treatment plan re-optimization. Gross tumor volume (GTV) and organs at risk (OARs) were adapted to the anatomy-of-the-day. A reoptimized plan (RP) and a rigidly shifted baseline plan (sBP) without re-optimization were generated for each fraction. After extraction of DVH parameters for GTV, planning target volume (PTV), and OARs (stomach, duodenum, bowel, liver, heart) plans were compared on a per-patient basis.

RESULTS

Median pre-treatment GTV and PTV were 14.9 cc (interquartile range (IQR): 7.7-32.9) and 62.7 cc (IQR: 42.4-105.5) respectively. SBRT with RP improved PTV coverage (V100%) for 47/75 of the fractions and reduced doses to the most proximal OARs (D1cc, Dmean) in 33/75 fractions compared to sBP. RP significantly improved PTV coverage (V100%) for metastases within close proximity to an OAR by 4.0% (≤ 0.2 cm distance from the edge of the PTV to the edge of the OAR; n = 7; p = 0.01), but only by 0.2% for metastases farther away from OAR (> 2 cm distance; n = 7; p = 0.37). No acute grade 3 treatment-related toxicities were observed.

CONCLUSIONS

MR-guided online replanning SBRT improved target coverage and OAR sparing for liver metastases with a distance from the edge of the PTV to the nearest luminal OAR < 2 cm. Only marginal improvements in target coverage were observed for target distant to critical OARs, indicating that these patients do not benefit from daily adaptive replanning.

Feasibility and Early Clinical Experience of Online Adaptive MR-Guided Radiotherapy of Liver Tumors

PURPOSE

To assess the feasibility and early results of online adaptive MR-guided radiotherapy (oMRgRT) of liver tumors.

METHODS

We retrospectively examined consecutive patients with primary or secondary liver lesions treated at our institution using a 0.35T hybrid MR-Linac (Viewray Inc., Mountain View, CA, USA). Online-adaptive treatment planning was used to account for interfractional anatomical changes, and real-time intrafractional motion management using online 2D cine MRI was performed using a respiratory gating approach. Treatment response and toxicity were assessed during follow-up.

RESULTS

Eleven patients and a total of 15 lesions were evaluated. Histologies included cholangiocarcinomas and metastases of neuroendocrine tumors, colorectal carcinomas, sarcomas and a gastrointestinal stroma tumor. The median BED₁₀ of the PTV prescription doses was 84.4 Gy (range 59.5-112.5 Gy) applied in 3-5 fractions and the mean GTV BED₁₀ was in median 147.9 Gy (range 71.7-200.5 Gy). Online plan adaptation was performed in 98% of fractions. The median overall treatment duration was 53 min. The treatment was feasible and successfully completed in all patients. After a median follow-up of five months, no local failure occurred and no ≥ grade two toxicity was observed. OMRgRT resulted in better PTV coverage and fewer OAR constraint violations.

CONCLUSION

Early results of MR-linac based oMRgRT for the primary and secondary liver tumors are promising. The treatment was feasible in all cases and well tolerated with minimal toxicity. The technique should be compared to conventional SBRT in further studies to assess the advantages of the technique.

MR-Guided Radiotherapy for Head and Neck Cancer: Current Developments, Perspectives, and Challenges

Based on the development of new hybrid machines consisting of an MRI and a linear accelerator, magnetic resonance image guided radiotherapy (MRgRT) has revolutionized the field of adaptive treatment in recent years. Although an increasing number of studies have been published, investigating technical and clinical aspects of this technique for various indications, utilizations of MRgRT for adaptive treatment of head and neck cancer (HNC) remains in its infancy. Yet, the possible benefits of this novel technology for HNC patients, allowing for better soft-tissue delineation, intra- and interfractional treatment monitoring and more frequent plan adaptations appear more than obvious. At the same time, new technical, clinical, and logistic challenges emerge. The purpose of this article is to summarize and discuss the rationale, recent developments, and future perspectives of this promising radiotherapy modality for treating HNC.

Trimodality PET/CT/MRI and Radiotherapy: A Mini-Review

Computed tomography (CT) has revolutionized external radiotherapy by making it possible to visualize and segment the tumors and the organs at risk in a three-dimensional way. However, if CT is a now a standard, it presents some limitations, notably concerning tumor characterization and delineation. Its association with functional and anatomical images, that are positron emission tomography (PET) and magnetic resonance imaging (MRI), surpasses its limits. This association can be in the form of a trimodality PET/CT/MRI. The objective of this mini-review is to describe the process of performing this PET/CT/MRI trimodality for radiotherapy and its potential clinical applications. Trimodality can be performed in two ways, either a PET/MRI fused to a planning CT (possibly with a pseudo-CT generated from the MRI for the planning), or a PET/CT fused to an MRI and then registered to a planning CT (possibly the CT of PET/CT if calibrated for radiotherapy). These examinations should be performed in the treatment position, and in the second case, a patient transfer system can be used between the PET/CT and MRI to limit movement. If trimodality requires adapted equipment, notably compatible MRI equipment with high-performance dedicated coils, it allows the advantages of the three techniques to be combined with a synergistic effect while limiting their disadvantages when carried out separately. Trimodality is already possible in clinical routine and can have a high clinical impact and good inter-observer agreement, notably for head and neck cancers, brain tumor, prostate cancer, cervical cancer.

Comparison of beam segment versus full plan re-optimization in daily magnetic resonance imaging-guided online-adaptive radiotherapy

The optimal approach for magnetic resonance imaging-guided online adaptive radiotherapy is currently unknown and needs to consider patient on-couch time constraints. The aim of this study was to compare two different plan optimization approaches. The comparison was performed in 238 clinically applied online-adapted treatment plans from 55 patients, in which the approach of re-optimization was selected based on the physician’s choice. For 33 patients where both optimization approaches were used at least once, the median treatment planning dose metrics of both target and organ at risk differed less than 1%. Therefore, we concluded that beam segment weight optimization was chosen adequately for most patients without compromising plan quality.

MR-guided radiotherapy of moving targets

INTRODUCTION

Hybrid magnetic resonance (MR) linear accelerators (MR-Linacs) for radiotherapy allow for the visualization and tracking of moving target volumes during the entire treatment. This makes gated treatments possible, decreasing the irradiated volumes and thus sparing healthy tissue from unnecessary radiation dose. Conventionally, tumors that are subject to respiration motion are treated by irradiating the entire area of potential target presence (internal target volume, ITV). This study presents three patient cases (lung, adrenal gland, and liver tumors) treated with gated MR-guided radiotherapy and compares the treatment plans retrospectively with conventional ITV plans.

MATERIALS AND METHODS

The gross tumor volume was delineated on MR and computed tomography (CT) images of the patients, and MR-Linac treatment plans were generated using additional clinical and planning target volume margins. The motion of the gross tumor volume was evaluated on two-dimensional cine-MRI images during the entire MR-Linac treatment. Based on the motion analysis, standard ITV-based plans were retrospectively created and compared by means of irradiated target volumes and dose-volume parameters.

RESULTS

For the MR-Linac plans, the irradiated treatment volumes were reduced by an average of 62% across the three cases, and for one case the ITV-based target volume would have overlapped with a critical organ. Target volume coverage was much better and the lung and adrenal MR-Linac plans revealed superior sparing of the organs at risks thanks to gated treatments.

CONCLUSION

Dosimetrically beneficial treatment plans with promising clinical outcomes can be applied when using gated MR-guided radiotherapy. Future studies will reveal which patients will benefit most from this technique. To utilize the full potential of online adaptive, individualized MR-guided therapy, the close collaboration of radio-oncology and radiology is needed.

Using prediction models to evaluate magnetic resonance image guided radiation therapy plans

Comprehensive analysis of daily, online adaptive plan quality and safety in magnetic resonance imaging (MRI) guided radiation therapy is critical to its widespread use. Artificial neural network models developed with offline plans created after simulation were used to analyze and compare online plans that were adapted and reoptimized in real time prior to treatment. Roughly one third of ⁶⁰Co adapted plans were of inferior quality relative to fully optimized, offline plans, but MRI-linac adapted plans were essentially equivalent to offline plans. The models also enabled clear justification that MRI-linac plans are superior to ⁶⁰Co in an overwhelming majority of cases.