Retrospective evaluation of decision-making for pancreatic stereotactic MR-guided adaptive radiotherapy

Quality and Safety Considerations for Adaptive Radiation Therapy: An ASTRO White Paper

PURPOSE

Adaptive radiation therapy (ART) is the latest topic in a series of white papers published by the American Society for Radiation Oncology addressing quality processes and patient safety. ART widens the therapeutic index by improving the precision of radiation dose to targets, allowing for dose escalation and/or minimization of dose to normal tissue. ART is performed via offline or online methods; offline ART is the process of replanning a patient's treatment plan between fractions, whereas online ART involves plan adjustment with the patient on the treatment table. This is achieved with in-room imaging capable of assessing anatomic changes and the ability to reoptimize the treatment plan rapidly during the treatment session. Although ART has occurred in its simplest forms in clinical practice for decades, recent technological developments have enabled more clinical applications of ART. With increased clinical prevalence, compressed timelines, and the associated complexity of ART, quality and safety considerations are an important focus area.

METHODS

The American Society for Radiation Oncology convened an interdisciplinary task force to provide expert consensus on key workflows and processes for ART. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale, from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters selecting "strongly agree" or "agree" indicated consensus. Content not meeting this threshold was removed or revised.

SUMMARY

Establishing and maintaining an adaptive program requires a team-based approach, appropriately trained and credentialed specialists, significant resources, specialized technology, and implementation time. A comprehensive quality assurance program must be developed, using established guidance, to make sure all forms of ART are performed in a safe and effective manner. Patient safety when delivering ART is everyone's responsibility, and professional organizations, regulators, vendors, and end users must demonstrate a clear commitment to working together to deliver the highest levels of quality and safety.

Future of Multidisciplinary Team in the Context of Adaptive Therapy

The implementation and early adoption of online adaptive radiotherapy (oART) has required the presence of clinicians, physicists and radiation therapists (RTT) at the treatment console. The impact on each of them is unique to their profession and must be considered for safe and efficient implementation. In the short term future, widespread adoption will depend on the development of innovative workflows, and rethinking of traditional roles and responsibilities may be required. For the future, technologies such as artificial intelligence promise to change the workflow significantly in terms of speed, automation and decision-making. However, overall communication within the team will persist in being one of the most important aspects.

A reference-point-method-based online proton treatment plan re-optimization strategy and a novel solution to planning constraint infeasibility problem

Objective. Propose a highly automated treatment plan re-optimization strategy suitable for online adaptive proton therapy. The strategy includes a rapid re-optimization method that generates quality replans and a novel solution that efficiently addresses the planning constraint infeasibility issue that can significantly prolong the re-optimization process.Approach. We propose a systematic reference point method (RPM) model that minimizes the l-infinity norm from the initial treatment plan in the daily objective space for online re-optimization. This model minimizes the largest objective value deviation among the objectives of the daily replan from their reference values, leading to a daily replan similar to the initial plan. Whether a set of planning constraints is feasible with respect to the daily anatomy cannot be known before solving the corresponding optimization problem. The conventional trial-and-error-based relaxation process can cost a significant amount of time. To that end, we propose an optimization problem that first estimates the magnitude of daily violation of each planning constraint. Guided by the violation magnitude and clinical importance of the constraints, the constraints are then iteratively converted into objectives based on their priority until the infeasibility issue is solved.Main results.The proposed RPM-based strategy generated replans similar to the offline manual replans within the online time requirement for six head and neck and four breast patients. The average targetD95and relevant organ at risk sparing parameter differences between the RPM replans and clinical offline replans were -0.23, -1.62 Gy for head and neck cases and 0.29, -0.39 Gy for breast cases. The proposed constraint relaxation solution made the RPM problem feasible after one round of relaxation for all four patients who encountered the infeasibility issue.Significance. We proposed a novel RPM-based re-optimization strategy and demonstrated its effectiveness on complex cases, regardless of whether constraint infeasibility is encountered.

The Radiation Therapist profession through the lens of new technology: A practice development paper based on the ESTRO Radiation Therapist Workshops

Technological advances in radiation therapy impact on the role and scope of practice of the radiation therapist. The European Society of Radiotherapy and Oncology (ESTRO) recently held two workshops on this topic and this position paper reflects the outcome of this workshop, which included radiation therapists from all global regions. Workflows, quality assurance, research, IGRT and ART as well as clinical decision making are the areas of radiation therapist practice that will be highly influenced by advancing technology in the near future. This position paper captures the opportunities that this will bring to the radiation therapist profession, to the practice of radiation therapy and ultimately to patient care.

Pancreatic SABR using peritumoral fiducials, triggered imaging and breath-hold

Background: We aim to present our linear accelerator-based workflow for pancreatic stereotactic ablative radiotherapy (SABR) in order to address the following issues: intrafractional organ motion management, Cone Beam CT (CBCT) image quality, residual errors with dosimetric consequences, treatment time, and clinical results. Methods: Between 2016 and 2021, 14 patients with locally advanced pancreatic cancer were treated with induction chemotherapy and SABR using volumetric modulated arc therapy (VMAT). Internal target volume (ITV) concept (5), phase-gated (4), or breath hold (5) techniques were used. Treatment was verified by CBCT before and after irradiation, while tumor motion was monitored and controlled by kV triggered imaging and beam hold using peritumoral surgical clips. Beam interruptions and treatment time were recorded. The CBCT image quality was scored and supplemented by an agreement analysis (Krippendorff's-α) of breath-hold CBCT images to determine the position of OARs relative to the planning risk volumes (PRV). Residual errors and their dosimetry impact were also calculated. Progression free (PFS) and overall survival (OS) were assessed by the Kaplan-Meier analysis with acute and late toxicity reporting (CTCAEv4). Results: On average, beams were interrupted once (range: 0-3) per treatment session on triggered imaging. The total median treatment time was 16.7 ± 10.8 min, significantly less for breath-hold vs. phase-gated sessions (18.8 ± 6.2 vs. 26.5 ± 13.4, p < 0.001). The best image quality was achieved by breath hold CBCT. The Krippendorff's-α test showed a strong agreement among five radiation therapists (mean K-α value: 0.8 (97.5%). The mean residual errors were <0.2 cm in each direction resulting in an average difference of <2% in dosimetry for OAR and target volume. Two patients received offline adaptation. The median OS/PFS after induction chemotherapy and SABR was 20/12 months and 15/8 months. No Gr. ≥2 acute/late RT-related toxicity was noted. Conclusion: Linear accelerator based pancreatic SABR with the combination of CBCT and triggered imaging + beam hold is feasible. Peritumoral fiducials improve utility while breath-hold CBCT provides the best image quality at a reasonable treatment time with offline adaptation possibilities. In well-selected cases, it can be an effective alternative in clinics where CBCT/MRI-guided online adaptive workflow is not available.

Online adaptive planning methods for intensity-modulated radiotherapy

Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.

Identifying predictors of on-table adaptation for pancreas stereotactic body radiotherapy (SBRT)

Purpose

To identify any clinical or dosimetric parameters that predict which individuals may benefit from on-table adaptation during pancreas stereotactic body radiotherapy (SBRT) with MRI-guided radiotherapy.

Methods and materials

This was a retrospective study of patients undergoing MRI-guided SBRT from 2016 to 2022. Pre-treatment clinical variables and dosimetric parameters on the patient's simulation scan were recorded for each SBRT course, and their ability to predict for on-table adaptation was analyzed using ordinal logistic regression. The outcome measure was number of fractions adapted.

Results

Sixty-three SBRT courses consisting of 315 fractions were analyzed. Median prescription dose was 40 Gy in five fractions (range, 33-50 Gy); 52% and 48% of courses were prescribed ≤40 Gy and >40 Gy, respectively. The median minimum dose delivered to 95% (D95) of the gross tumor volume (GTV) and planning target volume (PTV) was 40.1 Gy and 37.0 Gy, respectively. Median number of fractions adapted per course was three, with 58% (183 out of 315) total fractions adapted. On univariable analysis, the prescription dose (>40 Gy vs ≤40 Gy), GTV volume, stomach V20 and V25, duodenum V20 and dose maximum, large bowel V33 and V35, GTV dose minimum, PTV dose minimum, and gradient index were significant determinants for adaptation (all p < 0.05). On multivariable analysis, only the prescription dose was significant (adjusted odds ratio 19.7, p = 0.005), but did not remain significant after multiple test correction (p = 0.08).

Conclusions

The likelihood of needing on-table adaptation could not be reliably predicted a priori using pre-treatment clinical characteristics, dosimetry to nearby organs at risk, or other dosimetric parameters based on the patient's anatomy at the time of simulation, suggesting the critical importance of day-to-day variations in anatomy and increasing access to adaptive technology for pancreas SBRT. A higher (ablative) prescription dose was associated with increased use of adaptation.

Prediction of adaptive strategies based on deformation vector field features for MR-guided adaptive radiotherapy of prostate cancer

BACKGROUND

The selection of adaptive strategies in MR-guided adaptive radiotherapy (MRgART) usually relies on subjective review of anatomical changes. However, this kind of review may lead to improper selection of adaptive strategy for some fractions.

PURPOSE

The purpose of this study was to develop prediction models based on deformation vector field (DVF) features for automatic and accurate strategy selection, using prostate cancer as an example.

METHODS

100 fractions of 20 prostate cancer patients were retrospectively selected in this study. Treatment plans using both adapt to position (ATP) strategy and adapt to shape (ATS) strategy were generated. Optimal adaptive strategy was determined according to dosimetric evaluation. DVFs of the deformable image registration (DIR) of daily MRI and CT simulation scans were extracted. The shape, first order statistics, and spatial features were extracted from the DVFs, subjected to further selection using the minimum redundancy maximum relevance (mRMR) method. The number of features (F_n ) was hyper-tuned using bootstrapping method, and then F_n indicating a peak area under the curve (AUC) value was used to construct three prediction models.

RESULTS

According to subjective review, the ATS strategy was adopted for all 100 fractions. However, the evaluation results showed that the ATP strategy could have met the clinical requirements for 23 (23%) fractions. The three prediction models showed high prediction performance, with the best performing model achieving an AUC value of 0.896, corresponding accuracy (ACC), sensitivity (SEN) and specificity (SPC) of 0.9, 0.958, and 0.667, respectively. The features used to construct prediction models included four features extracted from y direction of DVF (DVF_y ) and mask, one feature from z direction of DVF (DVF_z ). It indicated that the deformation along the anterior-posterior direction had a greater impact on determining the adaptive strategy than other directions.

CONCLUSIONS

DVF-feature-based models could accurately predict the adaptive strategy and avoid unnecessary selection of time-consuming ATS strategy, which consequently improves the efficiency of the MRgART process.

The delivered dose assessment in pancreas SBRT with the target position determined using an in-house position monitoring system

PURPOSE

This study assessed the delivered dose accuracy in pancreas SBRT by incorporating the real-time target position determined using an in-house position monitoring system.

METHODS AND MATERIALS

An online image-based position monitoring system, SeedTracker, was developed to monitor radiopaque marker positions using monoscopic x-ray images, available from the Elekta XVI imaging system. This system was applied to patients receiving SBRT for pancreatic cancer on the MASTERPLAN Pilot trial (ACTRN 12617001642370). All patients were implanted pre-treatment with at least three peri-tumoral radiopaque markers for target localisation. During treatment delivery, marker positions were compared to expected positions delineated from the planning CT. The position tolerance of ±3mm from the expected position of the markers was set to trigger a gating event (GE) during treatment. The dosimetric impact of position deviations and actual dose delivered with position corrections was assessed by convolving the plan control point dose matrices with temporal target positions determined during treatment.

RESULTS

Eight patients were treated within this study. At least one GE was observed in 38% of the treatment fractions and more than one GE was observed in 10% of the fractions. The position deviations resulted in the mean(range) difference of -0.1(-1.1 - 0.4)Gy in minimum dose to tumour and 1.9(-0.1- 4.6)Gy increase to Dmax to duodenum compared to planned dose. In actual treatment delivery with the patient realignment, the mean difference of tumour min dose and duodenal Dmax was reduced to 0.1(-1.0 - 1.1)Gy and 1.1 (-0.7 - 3.3)Gy respectively compared to the planned dose.

CONCLUSIONS

The in-house real-time position monitoring system improved the treatment accuracy of pancreatic SBRT in a general-purpose linac and enabled assessment of delivered dose by incorporating the temporal target position during delivery. The intrafraction motion impacts the dose to tumour even if target position is maintained within a 3mm position tolerance.

Evolution of Radiation Therapy in Pancreas Cancer Management toward MRI-Guided Adaptive Radiation Therapy

Pancreas cancer has a poor prognosis despite aggressive treatment and is the fourth leading cause of cancer death in the United States. At diagnosis, most patients have either metastatic or locally advanced disease. In this article, we review the evolution of treatments in locally advanced pancreas cancer (LAPC) and discuss the various radiation therapy fractionation schemes. Furthermore, we examine the data supporting dose escalation and the delivery of ablative biologically effective doses in the setting of LAPC. Finally, we review the role of MRI-guided radiation therapy in escalating dose while sparing organs at risk in the era of stereotactic magnetic resonance-guided adaptive radiation therapy.

Patient positioning and immobilization procedures for hybrid MR-Linac systems

Hybrid magnetic resonance (MR)-guided linear accelerators represent a new horizon in the field of radiation oncology. By harnessing the favorable combination of on-board MR-imaging with the possibility to daily recalculate the treatment plan based on real-time anatomy, the accuracy in target and organs-at-risk identification is expected to be improved, with the aim to provide the best tailored treatment. To date, two main MR-linac hybrid machines are available, Elekta Unity and Viewray MRIdian. Of note, compared to conventional linacs, these devices raise practical issues due to the positioning phase for the need to include the coil in the immobilization procedure and in order to perform the best reproducible positioning, also in light of the potentially longer treatment time. Given the relative novelty of this technology, there are few literature data regarding the procedures and the workflows for patient positioning and immobilization for MR-guided daily adaptive radiotherapy. In the present narrative review, we resume the currently available literature and provide an overview of the positioning and setup procedures for all the anatomical districts for hybrid MR-linac systems.

Comparison of Daily Online Plan Adaptation Strategies for a Cohort of Pancreatic Cancer Patients Treated with SBRT

PURPOSE

To study the trade-offs of three online strategies to adapt treatment plans of patients with locally advanced pancreatic carcinoma (LAPC) treated using the CyberKnife with tumor tracking.

METHODS AND MATERIALS

A total of 35 planning computed tomography scans and 98 daily in-room computed tomography scans were collected from 35 patients with LAPC. Planned dose distributions, optimized with VOLO, were evaluated on manually contoured daily anatomies to collect daily doses. Three strategies were tested to adapt treatment plans: (1) unrestricted full replanning using a patient-specific plan template, (2) time-restricted replanning on organs at risk (OARs) within 3 cm from the planning target volume (PTV) structure, and (3) dose realignment optimization to stay within OAR constraints. Dose distributions resulting from each plan adaptation strategy were dosimetrically compared by means of gross tumor volume (GTV), PTV coverage, and OAR tolerances.

RESULTS

Planned doses did not result in dose-constraint violations for 28 of 98 daily anatomies. None of the suggested plan adaptation strategies improved planned doses significantly for this subset. For 70 of the 98 reported violations, the median (interquartile range) PTV coverage of the planned dose was 84% (76% to 86%). After plan adaptation, unrestricted replanning achieved clinically acceptable plans in 93% of these fractions, time-restricted replanning in 90%, and dose realignment in 74%, at median computational times of 8.5, 3, and 0.5 minutes. Over all 98 fractions, PTV coverage was reduced: -1% (-3% to 1%), -2% (-5% to 0%), and -2% (-8% to 0%) after each strategy, respectively. In 3 of 70 fractions, none of the suggested strategies achieved clinically acceptable OAR dose volumes.

CONCLUSIONS

Unrestricted replanning was the most time-consuming method but reached the highest number of successfully adapted plans. Time-restricted replanning and dose realignment resulted in a high number of plans within dose constraints. Depending on the resources available, an adaptive strategy can be selected for each patient to address the specific anatomic challenges on the treatment day. The increase in the complexity of the strategy corresponds with an increasing number of successfully adapted plans.

Clinical outcomes of stereotactic magnetic resonance image-guided adaptive radiotherapy for primary and metastatic tumors in the abdomen and pelvis

Purpose

Stereotactic body radiotherapy (SBRT) delivers ablative doses with excellent local control. However, implementing SBRT for abdominal and pelvic tumors has been limited by the risk for treatment‐related gastrointestinal toxicity. MRI‐guided radiotherapy may ameliorate these risks and increase the therapeutic ratio. We report the clinical outcomes of stereotactic MRI‐guided adaptive radiotherapy (SMART) for primary and metastatic tumors in the abdomen and pelvis.

Methods

From November 2014 to August 2017, the first 106 consecutive patients with 121 tumors in the abdomen and pelvis were treated with SMART at a single institution. Of the cohort, 41.5%, 15.1%, and 43.4% had primary, locally recurrent, and oligometastatic tumors, respectively. SMART was delivered using a tri‐cobalt‐60 gantry with on‐board 0.35 Tesla MRI with respiratory breath‐hold and daily adaptive re‐planning when anatomically necessary. A median of 40Gy in five fractions was prescribed. The Common Terminology Criteria for Adverse Events v.4.03 was used to score treatment‐related toxicities. Local control (LC), progression‐free survival (PFS), and overall survival (OS) were estimated using Kaplan–Meier method.

Results

Of the 510 treatments, seventy‐one (13.9%) were adapted. Fatigue, nausea, and pain were the most common acute toxicities. 0.9 and 0% of patients experienced acute grade three and four toxicities, respectively. 5.2 and 2.1% of patients experienced late grade three and four toxicities, respectively. After a median follow‐up of 20.4 months, the 2‐year LC rate was 74% on a per‐lesion basis. Two‐year LC was 96% for lesions that were treated with BED₁₀≥100 versus 69% for BED₁₀<100 (p = 0.02). PFS was significantly different between patients with and without locally controlled tumors (2‐year PFS 21 vs. 8%, p = 0.03). Two‐year OS was 57% for the entire cohort.

Conclusions

Favorable LC and PFS outcomes were observed with minimal morbidity for tumors in the abdomen and pelvis treated with SMART. Future prospective clinical trials to validate these findings are warranted.

Dosimetric Quality of Online Adapted Pancreatic Cancer Treatment Plans on an MRI-Guided Radiation Therapy System

Purpose

Stereotactic magnetic resonance image–guided adaptive radiation therapy (SMART) is an emerging technique that shows promise in the treatment of pancreatic cancer and other abdominopelvic malignancies. However, it is unknown whether the time-limited nature of on-table adaptive planning may result in dosimetrically suboptimal plans. The purpose of this study was to quantitatively address that question through systemic retrospective replanning of treated on-table adaptive pancreatic cancer cases.

Methods and Materials

Of 74 consecutive adapted fractions, 30 were retrospectively replanned based on deficiencies in planning target volume (PTV) and gross tumor volume (GTV) coverage or doses to organs-at-risk (OARs) that exceeded ideal constraints. Retrospective plans were created by adjusting dose-volume objectives in an iterative fashion until deemed optimized. The goal of replanning was to improve PTV/GTV coverage while keeping the dose to gastrointestinal OARs the same or lower or to reduce OAR doses while keeping PTV coverage the same or higher. The global maximum dose was required to be maintained within 2% of that of the treated adaptive plan to eliminate it as a confounding factor. A threshold of 5% improvement in PTV coverage or 5% decrease in OAR dose was used to define a clinically significant improvement.

Results

Of the 30 replans, 7 obtained at least 5% PTV coverage improvement. The average increase in PTV coverage for these plans was 11%. No plans were clinically significantly improved in terms of OAR sparing. Changes in beam-on time did not show any correlation. Statistical analysis via a linear mixed-effects model with a nested random effect suggested that both GTV and PTV coverage were improved over SMART process plans by 0.91 cc (P = .02) and 2.03 cc (P < .001), respectively.

Conclusions

Dosimetric plan quality of at least 10% of SMART fractions may be improved through more extensive replanning than is currently performed on-table. Further work is needed to develop an automated replanning workflow to streamline the in-depth replanning process to better fit into an on-table adaptive workflow.

MR-Guided Radiotherapy for Liver Malignancies

MR guided radiotherapy represents one of the most promising recent technological innovations in the field. The possibility to better visualize therapy volumes, coupled with the innovative online adaptive radiotherapy and motion management approaches, paves the way to more efficient treatment delivery and may be translated in better clinical outcomes both in terms of response and reduced toxicity. The aim of this review is to present the existing evidence about MRgRT applications for liver malignancies, discussing the potential clinical advantages and the current pitfalls of this new technology.

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

In the past few years, radiotherapy (RT) has experienced a major technological innovation with the development of hybrid machines combining magnetic resonance (MR) imaging and linear accelerators. This new technology for MR-guided cancer treatment has the potential to revolutionize the field of adaptive RT due to the opportunity to provide high-resolution, real-time MR imaging before and during treatment application. However, from a technical point of view, several challenges remain which need to be tackled to ensure safe and robust real-time adaptive MR-guided RT delivery. In this manuscript, several technical challenges to MR-guided RT are discussed. Starting with magnetic field strength tradeoffs, the potential and limitations for purely MR-based RT workflows are discussed. Furthermore, the current status of real-time 3D MR imaging and its potential for real-time RT are summarized. Finally, the potential of quantitative MR imaging for future biological RT adaptation is highlighted.

Inhalation anesthesia and shielding devices to allow accurate preclinical irradiation of mice with clinical linac-based systems: Design and dosimetric characteristics

This technical note describes two devices to enable accurate irradiation of mice on clinical linac-based systems. To study the effects of radiation in murine, preclinical animal models, controlled and accurate dosing is important. This is not only important when specific volumes need to be irradiated, but also when the whole animal body is irradiated. To enable both purposes, we designed two devices. One device to administer Total Body Irradiation (TBI) simultaneously to six, free walking mice, and a second device, denoted as target box, in which we irradiate specific parts of the mice whilst organs-at-risk (OAR) are protected. In this latter device, we can position the mice in multiple ways. One configuration allows to sedate twelve mice simultaneously by isoflurane inhalation anesthesia and protect the body by lead shielding to allow radiation of the head only. Alternatively, the target box can be used to sedate maximal 4 mice simultaneously to irradiate the flank or paws only. All these setups allow high experimental throughput and thus a minimal occupation of the clinical equipment. As measured, the delivered radiation dosages in the regions of interest were accurate for both devices. In this technical note, we describe the design and build of these devices.

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.

Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology

The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.

Ablative 5-Fraction Stereotactic Magnetic Resonance-Guided Radiation Therapy With On-Table Adaptive Replanning and Elective Nodal Irradiation for Inoperable Pancreas Cancer

PURPOSE

Radiation therapy dose escalation using stereotactic body radiation therapy may significantly improve both local control (LC) and overall survival (OS) for patients with inoperable pancreas cancer. However, ablative dose cannot be routinely offered because of the risk of causing severe injury to adjacent normal organs. Stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) represents a novel technique that may achieve safe delivery of ablative dose and improve long-term outcomes.

METHODS AND MATERIALS

We performed a single institution retrospective analysis of 35 consecutive pancreatic cancer patients treated with SMART in mid-inspiration breath hold on an MR-linear accelerator. Most had locally advanced disease (80%) and received induction chemotherapy (91.4%) for a median 3.9 months before stereotactic body radiation therapy. All were prescribed 5 fractions delivered in consecutive days to a median total dose of 50 Gy (BED₁₀ 100 Gy₁₀), typically with a 120% to 130% hotspot. Elective nodal irradiation was delivered to 20 (57.1%) patients. No patient had fiducial markers placed and all were treated with continuous intrafraction MR visualization and automatic beam triggering.

RESULTS

With median follow-up of 10.3 months from SMART, acute (2.9%) and late (2.9%) grade 3 toxicities were uncommon. One-year LC, distant metastasis-free survival, progression-free survival, cause-specific survival, and OS were 87.8%, 63.1%, 52.4%, 77.6%, and 58.9%, respectively.

CONCLUSIONS

To our knowledge, this is the first report of 5-fraction pancreas SMART delivered on an MR-linear accelerator. We observed minimal severe treatment-related toxicity and encouraging early LC. Prospective confirmation of feasibility and long-term clinical outcomes of dose intensified SMART is warranted.

CT-based multi-organ segmentation using a 3D self-attention U-net network for pancreatic radiotherapy

PURPOSE

Segmentation of organs-at-risk (OARs) is a weak link in radiotherapeutic treatment planning process because the manual contouring action is labor-intensive and time-consuming. This work aimed to develop a deep learning-based method for rapid and accurate pancreatic multi-organ segmentation that can expedite the treatment planning process.

METHODS

We retrospectively investigated one hundred patients with computed tomography (CT) simulation scanned and contours delineated. Eight OARs including large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach were the target organs to be segmented. The proposed three-dimensional (3D) deep attention U-Net is featured with a deep attention strategy to effectively differentiate multiple organs. Performance of the proposed method was evaluated using six metrics, including Dice similarity coefficient (DSC), sensitivity, specificity, Hausdorff distance 95% (HD95), mean surface distance (MSD) and residual mean square distance (RMSD).

RESULTS

The contours generated by the proposed method closely resemble the ground-truth manual contours, as evidenced by encouraging quantitative results in terms of DSC, sensitivity, specificity, HD95, MSD and RMSD. For DSC, mean values of 0.91 ± 0.03, 0.89 ± 0.06, 0.86 ± 0.06, 0.95 ± 0.02, 0.95 ± 0.02, 0.96 ± 0.01, 0.87 ± 0.05 and 0.93 ± 0.03 were achieved for large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach, respectively.

CONCLUSIONS

The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs. The method could potentially be used in pancreatic adaptive radiotherapy to increase dose delivery accuracy and minimize gastrointestinal toxicity.

Development and evaluation of machine learning models for voxel dose predictions in online adaptive magnetic resonance guided radiation therapy

PURPOSE

Daily online adaptive plan quality in magnetic resonance imaging guided radiation therapy (MRgRT) is difficult to assess in relation to the fully optimized, high quality plans traditionally established offline. Machine learning prediction models developed in this work are capable of predicting 3D dose distributions, enabling the evaluation of online adaptive plan quality to better inform adaptive decision-making in MRgRT.

METHODS

Artificial neural networks predicted 3D dose distributions from input variables related to patient anatomy, geometry, and target/organ-at-risk relationships in over 300 treatment plans from 53 patients receiving adaptive, linac-based MRgRT for abdominal cancers. The models do not include any beam related variables such as beam angles or fluence and were optimized to balance errors related to raw dose and specific plan quality metrics used to guide daily online adaptive decisions.

RESULTS

Averaged over all plans, the dose prediction error and the absolute error were 0.1 ± 3.4 Gy (0.1 ± 6.2%) and 3.5 ± 2.4 Gy (6.4 ± 4.3%) respectively. Plan metric prediction errors were -0.1 ± 1.5%, -0.5 ± 2.1%, -0.9 ± 2.2 Gy, and 0.1 ± 2.7 Gy for V95, V100, D95, and Dmean respectively. Plan metric prediction absolute errors were 1.1 ± 1.1%, 1.5 ± 1.5%, 1.9 ± 1.4 Gy, and 2.2 ± 1.6 Gy. Approximately 10% (25) of the plans studied were clearly identified by the prediction models as inferior quality plans needing further optimization and refinement.

CONCLUSION

Machine learning prediction models for treatment plan 3D dose distributions in online adaptive MRgRT were developed and tested. Clinical integration of the models requires minimal effort, producing 3D dose predictions for a new patient's plan using only target and OAR structures as inputs. These models can enable improved workflows for MRgRT through more informed plan optimization and plan quality assessment in real time.

Basics and Frontiers on Pancreatic Cancer for Radiation Oncology: Target Delineation, SBRT, SIB technique, MRgRT, Particle Therapy, Immunotherapy and Clinical Guidelines

Pancreatic cancer represents a modern oncological urgency. Its management is aimed to both distal and local disease control. Resectability is the cornerstone of treatment aim. It influences the clinical presentation’s definitions as up-front resectable, borderline resectable and locally advanced (unresectable). The main treatment categories are neoadjuvant (preoperative), definitive and adjuvant (postoperative). This review will focus on (i) the current indications by the available national and international guidelines; (ii) the current standard indications for target volume delineation in radiotherapy (RT); (iii) the emerging modern technologies (including particle therapy and Magnetic Resonance [MR]-guided-RT); (iv) stereotactic body radiotherapy (SBRT), as the most promising technical delivery application of RT in this framework; (v) a particularly promising dose delivery technique called simultaneous integrated boost (SIB); and (vi) a multimodal integration opportunity: the combination of RT with immunotherapy.

Carbon ion radiotherapy in pancreatic cancer: A review of clinical data

Despite all efforts, pancreatic cancer remains a highly lethal disease. Only surgical resection offers a realistic chance of survival. But at diagnosis the majority of patients suffer from unresectable disease. Whereas guidelines clearly recommend systemic treatments in metastatic disease, data is limited to support a specific treatment option for locally advanced or borderline resectable pancreatic cancer. Therefore, there is an urgent need to improve treatment schemes addressing patients that suffer from unresectable pancreatic cancer. Chemotherapy, photon radiotherapy and combinations of both have shown improved local control rates but there is still a lack of evidence demonstrating an overall survival benefit of photon radiotherapy if no surgical resection is achieved. Impressive results of Japanese Phase I/II-trials investigating carbon ion radiotherapy in pancreatic cancer attracted global attention. Several studies have been initiated to validate and intensify this promising issue. This review gives an overview of the evidence and current use of carbon ion radiotherapy in pancreatic cancer.

Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks

PURPOSE

The recently introduced MR-Linac enables MRI-guided Online Adaptive Radiation Therapy (MRgOART) of pancreatic cancer, for which fast and accurate segmentation of the gross tumor volume (GTV) is essential. This work aims to develop an algorithm allowing automatic segmentation of the pancreatic GTV based on multi-parametric MRI using deep neural networks.

METHODS

We employed a square-window based convolutional neural network (CNN) architecture with three convolutional layer blocks. The model was trained using about 245,000 normal and 230,000 tumor patches extracted from 37 DCE MRI sets acquired in 27 patients with data augmentation. These images were bias corrected, intensity standardized, and resampled to a fixed voxel size of 1 × 1 × 3 mm³. The trained model was tested on 19 DCE MRI sets from another 13 patients, and the model-generated GTVs were compared with the manually segmented GTVs by experienced radiologist and radiation oncologists based on Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), and Mean Surface Distance (MSD).

RESULTS

The mean values and standard deviations of the performance metrics on the test set were DSC = 0.73 ± 0.09, HD = 8.11 ± 4.09 mm, and MSD = 1.82 ± 0.84 mm. The interobserver variations were estimated to be DSC = 0.71 ± 0.08, HD = 7.36 ± 2.72 mm, and MSD = 1.78 ± 0.66 mm, which had no significant difference with model performance at p values of 0.6, 0.52, and 0.88, respectively.

CONCLUSION

We developed a CNN-based model for auto-segmentation of pancreatic GTV in multi-parametric MRI. Model performance was comparable to expert radiation oncologists. This model provides a framework to incorporate multimodality images and daily MRI for GTV auto-segmentation in MRgOART.

Magnetic resonance-guided radiation therapy: A review

Magnetic resonance-guided radiation therapy (MRgRT) is a promising approach to improving clinical outcomes for patients treated with radiation therapy. The roles of image guidance, adaptive planning and magnetic resonance imaging in radiation therapy have been increasing over the last two decades. Technical advances have led to the feasible combination of magnetic resonance imaging and radiation therapy technologies, leading to improved soft-tissue visualisation, assessment of inter- and intrafraction motion, motion management, online adaptive radiation therapy and the incorporation of functional information into treatment. MRgRT can potentially transform radiation oncology by improving tumour control and quality of life after radiation therapy and increasing convenience of treatment by shortening treatment courses for patients. Multiple groups have developed clinical implementations of MRgRT predominantly in the abdomen and pelvis, with patients having been treated since 2014. While studies of MRgRT have primarily been dosimetric so far, an increasing number of trials are underway examining the potential clinical benefits of MRgRT, with coordinated efforts to rigorously evaluate the benefits of the promising technology. This review discusses the current implementations, studies, potential benefits and challenges of MRgRT.

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom

Background and purpose

Magnetic resonance imaging (MRI) has gained popularity in radiation therapy simulation because it provides superior soft tissue contrast, which facilitates more accurate target delineation compared with computed tomography (CT) and does not expose the patient to ionizing radiation. However, image registration errors in commercial software have not been widely reported. Here we evaluated the accuracy of deformable image registration (DIR) by using a physical phantom for MRI.

Methods and materials

We used the “Wuphantom” for end‐to‐end testing of DIR accuracy for MRI. This acrylic phantom is filled with water and includes several fillable inserts to simulate various tissue shapes and properties. Deformations and changes in anatomic locations are simulated by changing the rotations of the phantom and inserts. We used Varian Velocity DIR software (v4.0) and CT (head and neck protocol) and MR (T1‐ and T2‐weighted head protocol) images to test DIR accuracy between image modalities (MRI vs CT) and within the same image modality (MRI vs MRI) in 11 rotation deformation scenarios. Large inserts filled with Mobil DTE oil were used to simulate fatty tissue, and small inserts filled with agarose gel were used to simulate tissues slightly denser than water (e.g., prostate). Contours of all inserts were generated before DIR to provide a baseline for contour size and shape. DIR was done with the MR Correctable Deformable DIR method, and all deformed contours were compared with the original contours. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were used to quantitatively validate DIR accuracy. We also used large and small regions of interest (ROIs) during between‐modality DIR tests to simulate validation of DIR accuracy for organs at risk (OARs) and propagation of individual clinical target volume (CTV) contours.

Results

No significant differences in DIR accuracy were found for T1:T1 and T2:T2 comparisons (P > 0.05). DIR was less accurate for between‐modality comparisons than for same‐modality comparisons, and was less accurate for T1 vs CT than for T2 vs CT (P < 0.001). For between‐modality comparisons, use of a small ROI improved DIR accuracy for both T1 and T2 images.

Conclusion

The simple design of the Wuphantom allows seamless testing of DIR; here we validated the accuracy of MRI DIR in end‐to‐end testing. T2 images had superior DIR accuracy compared with T1 images. Use of small ROIs improves DIR accuracy for target contour propagation.

Patterns of practice of adaptive re-planning for anatomic variances during cone-beam CT guided radiotherapy

PURPOSE

Substantial, unanticipated anatomic variances during cone-beam CT (CBCT)-guided radiotherapy can potentially impact treatment accuracy and clinical outcomes. This study assessed patterns of practice of CBCT variances reported by RTTs and subsequent interventions for multiple-disease sites.

METHODS

A chart review was conducted at a large cancer centre for patients treated with daily online CBCT-guided radiotherapy. Patients selected for review were identified via RTT-reported variances that then triggered offline multi-disciplinary assessment. Cases were categorized by the type of anatomic variance observed on CBCT and any further interventions recorded such as un-scheduled adaptive re-planning.

RESULTS

Over a 1-year period, 287 variances from 261 patients were identified (6.2% of the 4207 patients treated with daily CBCT-guided radiotherapy), most often occurring within the first 5 fractions of the treatment course. Of these variances, 21% (59/287) were re-planned and 3.5% (10/287) discontinued treatment altogether. Lung was the most frequent disease-site (27% of 287 variances) reported with IGRT-related variances although head and neck and sarcoma were most frequently re-planned (19% of 59 re-plans for each site). Technical or clinical rationales for re-planning were not routinely documented in patient medical records. All disease-sites had numerous categories of variances. Three of the four most frequent categories were for tumor-related changes on CBCT, and the re-planning rate was highest for tumor progression at 25%. Normal tissue variances were the second most frequency category, and re-planned in 14% of those cases.

CONCLUSION

RTTs identified a wide range of anatomic variances during CBCT-guided radiotherapy. In a minority of cases, these substantially altered the care plan including ad hoc adaptive re-planning or treatment discontinuation. Improved understanding of the clinical decisions in these cases would aid in developing more routine, systematic adaptive strategies.

The transformation of radiation oncology using real-time magnetic resonance guidance: A review

Radiation therapy (RT) is an essential component of effective cancer care and is used across nearly all cancer types. The delivery of RT is becoming more precise through rapid advances in both computing and imaging. The direct integration of magnetic resonance imaging (MRI) with linear accelerators represents an exciting development with the potential to dramatically impact cancer research and treatment. These impacts extend beyond improved imaging and dose deposition. Real-time MRI-guided RT is actively transforming the work flows and capabilities of virtually every aspect of RT. It has the opportunity to change entirely the delivery methods and response assessments of numerous malignancies. This review intends to approach the topic of MRI-based RT guidance from a vendor neutral and international perspective. It also aims to provide an introduction to this topic targeted towards oncologists without a speciality focus in RT. Speciality implications, areas for physician education and research opportunities are identified as they are associated with MRI-guided RT. The uniquely disruptive implications of MRI-guided RT are discussed and placed in context. We further aim to describe and outline important future changes to the speciality of radiation oncology that will occur with MRI-guided RT. The impacts on RT caused by MRI guidance include target identification, RT planning, quality assurance, treatment delivery, training, clinical workflow, tumour response assessment and treatment scheduling. In addition, entirely novel research areas that may be enabled by MRI guidance are identified for future investigation.

A model-based patient selection tool to identify who may be at risk of exceeding dose tolerances during pancreatic SBRT

PURPOSE

Locally advanced pancreatic cancer (LAPC) patients are prone to experience daily anatomical variations, which can lead to additional doses in organs-at-risk (OAR) during SBRT. A patient selection tool was developed to identify who may be at risk of exceeding dose tolerances, by quantifying the dosimetric impact of daily variations using an OAR motion model.

MATERIALS AND METHODS

The study included 133 CT scans from 35 LAPC patients. By following a leave-one-out approach, an OAR motion model trained with the remaining 34 subjects variations was used to simulate organ deformations on the left-out patient planning CT anatomy. Dose-volume histograms obtained from planned doses sampled on simulated organs resulted in the probability of exceeding OAR dose-constraints due to anatomical variations. Simulated probabilities were clustered with a threshold per organ according to clinical observations. If the prediction of at least one OAR was above the established thresholds, the patient was classified as being at risk.

RESULTS

Clinically, in 20/35 patients at least one OAR exceeded dose-constraints in the daily CTs. The model-based prediction had an accuracy of 89%, 71%, 91% in estimating the risk of exceeding dose tolerances for the duodenum, stomach and bowel, respectively. By combining the three predictions, our approach resulted in a correct patient classification for 29/35 patients (83%) when compared with clinical observations.

CONCLUSIONS

Our model-based patient selection tool is able to predict who might be at risk of exceeding dose-constraints during SBRT. It is a promising tool to tailor LAPC treatments, e.g. by employing online adaptive SBRT; and hence, to minimize toxicity of patients being at risk.

Clinical Outcomes Using Magnetic Resonance-Guided Stereotactic Body Radiation Therapy in Patients With Locally Advanced Cholangiocarcinoma

Purpose

Previous studies have shown that stereotactic ablative radiation therapy (SABR) increases local control for cholangiocarcinoma, but gastrointestinal toxicity resulting from this treatment approach remains a concern. SABR using magnetic resonance–guided radiation therapy (MRgRT) may improve the therapeutic ratio of treatment for cholangiocarcinoma patients given the radiosensitivity of neighboring gastrointestinal organs.

Methods

Seventeen consecutive patients with unresectable locally advanced cholangiocarcinoma were treated with SABR using MRgRT between May 2015 and August 2017, subsequent to our previously reported series of patients treated using a standard Linac with cone beam computed tomography. Twelve patients presented with extrahepatic cholangiocarcinoma and 5 patients with intrahepatic tumors. MRgRT-based SABR was administered at a median dose of 40 Gy in 5 fractions.

Results

The median overall survival (OS) was 18.5 months, with a 1-year OS of 76% and 2-year OS of 46.1%. Three of the 17 patients progressed locally, yielding a 1-year local control of 85.6% and a 2-year local control of 73.3%. Although 12 of 17 patients experienced an acute grade 1 toxicity, none experienced acute grade 2 toxicities. One patient had an acute grade 3 duodenal ulcer with perforation (6%), and one patient had a late radiation-related toxicity grade 2 gastritis/colitis.

Conclusions

Our findings demonstrate diminished toxicity and excellent overall survival and local control. The clinical outcomes and safety profile of SABR delivered with MRgRT suggest that MRgRT is a promising treatment approach for treating cholangiocarcinoma.

Plan-library supported automated replanning for online-adaptive intensity-modulated proton therapy of cervical cancer

Background: Intensity-modulated proton therapy is sensitive to inter-fraction variations, including density changes along the pencil-beam paths and variations in organ-shape and location. Large day-to-day variations are seen for cervical cancer patients. The purpose of this study was to develop and evaluate a novel method for online selection of a plan from a patient-specific library of prior plans for different anatomies, and adapt it for the daily anatomy. Material and methods: The patient-specific library of prior plans accounting for altered target geometries was generated using a pretreatment established target motion model. Each fraction, the best fitting prior plan was selected. This prior plan was adapted using (1) a restoration of spot-positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast optimization of the spot-weights with the reference point method (RPM) to obtain a Pareto-optimal plan for the daily anatomy. Spot addition and spot-weight optimization could be repeated iteratively. The patient cohort consisted of six patients with in total 23 repeat-CT scans, with a prescribed dose of 45 Gy(RBE) to the primary tumor and the nodal CTV. Using a 1-plan-library (one prior plan based on all motion in the motion model) was compared to choosing from a 2-plan-library (two prior plans based on part of the motion). Results: Applying the prior-plan adaptation method with one iteration of adding spots resulted in clinically acceptable target coverage ( V95%≥95% and V107%≤2% ) for 37/46 plans using the 1-plan-library and 41/46 plans for the 2-plan-library. When adding spots twice, the 2-plan-library approach could obtain acceptable coverage for all scans, while the 1-plan-library approach showed V107%>2% for 3/46 plans. Similar OAR results were obtained. Conclusion: The automated prior-plan adaptation method can successfully adapt for the large day-to-day variations observed in cervical cancer patients.

Proton beam therapy for tumors of the upper abdomen

Proton radiotherapy has clear dosimetric advantages over photon radiotherapy. In contrast to photons, which are absorbed exponentially, protons have a finite range dependent on the initial proton energy. Protons therefore do not deposit dose beyond the tumor, resulting in great conformality, and offers the promise of dose escalation to increase tumor control while minimizing toxicity. In this review, we discuss the rationale for using proton radiotherapy in the treatment of upper abdominal tumors-hepatocellular carcinomas, cholangiocarcinomas and pancreatic cancers. We also review the clinical outcomes and technical challenges of using proton radiotherapy for the treatment of these malignancies. Finally, we discuss the ongoing clinical trials implementing proton radiotherapy for the treatment of primary liver and pancreatic tumors.

Practical Clinical Workflows for Online and Offline Adaptive Radiation Therapy

Adaptive radiotherapy emerged over 20 years ago and is now an established clinical practice in a number of organ sites. No one solution for adaptive therapy exists. Rather, adaptive radiotherapy is a process which combines multiple tools for imaging, assessment of need for adaptation, treatment planning, and quality assurance of this process. Workflow is therefore a critical aspect to ensure safe, effective, and efficient implementation of adaptive radiotherapy. In this work, we discuss the tools for online and offline adaptive radiotherapy and introduce workflow concepts for these types of adaptive radiotherapy. Common themes and differences between the workflows are introduced and controversies and areas of active research are discussed.

Keeping Up with the Hybrid Magnetic Resonance Linear Accelerators: How Do Radiation Therapists Stay Current in the Era of Hybrid Technologies?

The benefits of integrating magnetic resonance imaging (MRI) into radiotherapy planning have long been extolled, first appearing in the literature as early as 1986. Most often described as a tool to be used when registered to a planning computed tomography to improve target and organ at risk delineation, the use of MRI for on-board image guidance and as a sole imaging modality throughout the entire radiotherapy pathway is quickly becoming a reality for appropriately selected patient populations in academic centres throughout the world. With the commercialization of these integrated magnetic resonance - radiotherapy delivery systems, an MRI-only workflow will prove beneficial, with MRI being used for treatment planning, localization, and on-treatment plan adaptation. Despite these technological advancements, recent surveys indicate uptake of MRI in radiotherapy as a routine practice has proven challenging. Reasons cited for this slow uptake were primarily related to health economics and/or accessibility. Furthermore, these surveys, like much of the academic literature, shy away from focusing on safe, sustainable staffing models enabled by comprehensive and appropriate education and training. In stark contrast to conebeam computed tomography guided therapy, magnetic resonance - radiotherapy systems are currently being operated by teams of physicians, radiographers, and physicists because of the diverse and complex tasks required to deliver treatment. The pace of innovation in RT remains high and unfortunately the window of opportunity to implement appropriate education continues to narrow. It is vital that we establish a framework to future-proof our profession. In the era of magnetic resonance-guided radiotherapy, we have yet to address the question of how to devise a consensus on the requisite knowledge, skills, and competence for radiation therapists and therapy radiographers using and/or operating MRI that provides guidance, without becoming prohibitively costly or time consuming.

The role of biological dose-escalation for pancreatic cancer

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High local control rates even for LAPC with biological dose-escalation using SBRT.

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MR-guided adaptive SBRT optimal technique pursuing further dose-escalation.

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High-dose constraints of adjacent OARs will remain the limiting factor.

The role of chemo-radiotherapy for treatment of locally advanced pancreatic cancer (LAPC) has been discussed for many years, and the absence of an overall survival benefit compared to gemcitabine chemotherapy alone in the recent LAP07 study seems to have increased the controversy. However, even in this study, chemo-radiotherapy resulted in decreased local progression (p = 0.03). In combination with increased efficacy of novel systemic therapy consisting of oxaliplatin, irinotecan, fluorouracil and leucovorin (FOLFIRINOX), radiation dose-escalation may show to be beneficial in LAPC. Stereotactic body radiation therapy (SBRT) can be expected to be the most suitable approach to perform local radiation dose-escalation, and has been shown to be both effective and tolerable at doses of 25–35 Gy in 3–5 fractions. Whether further dose-escalation for LAPC will be both feasible and useful is debatable, because of dose restrictions to adjacent critical organs at risk, and the observation that thus far a benefit of delivering BED₁₀ in excess of 70 Gy has not shown to improve local control significantly. If an attempt to further dose-escalate is performed, stereotactic MR-guided adaptive radiation therapy (SMART) theoretically has the highest potential. In addition to superior soft-tissue setup without the need for implanted fiducial markers and online MR-guidance during delivery with minimal safety margins, daily plan adaptation directed at avoiding undue high doses to critical organs such as the duodenum, stomach and bowel are advantages of this technique over current SBRT. This paper aims to illustrate the SMART technique, which has been delivered in 300 fractions for LAPC or locally recurrent pancreatic cancer at Amsterdam UMC since early 2016.