Magnetic Resonance Image-Guided Radiotherapy (MRIgRT): A 4.5-Year Clinical Experience

Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen

BACKGROUND

Manual contour corrections during fractionated magnetic resonance (MR)-guided radiotherapy (MRgRT) are time-consuming. Conventional population models for deep learning auto-segmentation might be suboptimal for MRgRT at MR-Linacs since they do not incorporate manual segmentation from treatment planning and previous fractions.

PURPOSE

In this work, we investigate patient-specific (PS) auto-segmentation methods leveraging expert-segmented planning and prior fraction MR images (MRIs) to improve auto-segmentation on consecutive treatment days.

MATERIALS AND METHODS

Data from 151 abdominal cancer patients treated at a 0.35 T MR-Linac (151 planning and 215 fraction MRIs) were included. Population baseline models (BMs) were trained on 107 planning MRIs for one-class segmentation of the aorta, bowel, duodenum, kidneys, liver, spinal canal, and stomach. PS models were obtained by fine-tuning the BMs using the planning MRI (PS BM $\text{PS}_{\mathrm{BM}}$ ). Maximal improvement by continuously updating the PS models was investigated by adding the first four out of five fraction MRIs (PS BM F4 $\text{PS}_{\mathrm{BM}}^{\operatorname{F4}}$ ). Similarly, PS models without BM were trained (PS no BM $\text{PS}_{\mathrm{no BM}}$ andPS no BM F4 $\text{PS}_{\mathrm{no BM}}^{\operatorname{F4}}$ ). All hyperparameters were optimized using 23 patients, and the methods were tested on the remaining 21 patients. Evaluation involved Dice similarity coefficient (DSC), average (HD avg $\text{HD}_{\rm avg}$ ) and the 95th percentile (HD95) Hausdorff distance. A qualitative contour assessment by a radiation oncologist was performed for BM,PS BM $\text{PS}_{\mathrm{BM}}$ , andPS no BM $\text{PS}_{\mathrm{no BM}}$ .

RESULTS

PS BM F4 $\text{PS}_{\mathrm{BM}}^{\operatorname{F4}}$ andPS BM $\text{PS}_{\mathrm{BM}}$ networks had the best geometric performance.PS no BM $\text{PS}_{\mathrm{no BM}}$ and BMs showed similar DSC and HDs values, howeverPS no BM F4 $\text{PS}_{\mathrm{no BM}}^{\operatorname{F4}}$ models outperformed BMs.PS BM $\text{PS}_{\mathrm{BM}}$ predictions scored the best in the qualitative evaluation, followed by the BMs andPS no BM $\text{PS}_{\mathrm{no BM}}$  models.

CONCLUSION

Personalized auto-segmentation models outperformed the population BMs. In most cases,PS BM $\text{PS}_{\mathrm{BM}}$ delineations were judged to be directly usable for treatment adaptation without further corrections, suggesting a potential time saving during fractionated treatment.

AutoCorNN: An Unsupervised Physics-Aware Deep Learning Model for Geometric Distortion Correction of Brain MRI Images Towards MR-Only Stereotactic Radiosurgery

Geometric distortions in brain MRI images arising from susceptibility artifacts at air-tissue interfaces pose a significant challenge for high-precision radiation therapy modalities like stereotactic radiosurgery, necessitating sub-millimeter accuracy. To achieve this goal, we developed AutoCorNN, an unsupervised physics-aware deep-learning model for correcting geometric distortions. Two publicly available datasets, the MPI-Leipzig Mind-Brain-Body with 318 subjects, and the Vestibular Schwannoma-SEG dataset, encompassing 242 patients were utilized. AutoCorNN integrates two 2D convolutional encoder-decoder neural networks with the forward physical model of MRI signal generation to predict undistorted MR and field map images from distorted MR input. The network is trained in an unsupervised manner by minimizing the mean absolute error between the measured and estimated k-space data, without requiring ground truth images during training or deployment. The model was evaluated on vestibular schwannoma cases. AutoCorNN achieved a peak signal-to-noise ratio (PSNR) of 41.35 ± 0.02 dB, a root mean square error (RMSE) of 0.02 ± 0.003, and a structural similarity index (SSIM) of 0.99 ± 0.02 outperforming uncorrected and B0-mapping correction methods. Geometric distortions of about 1.6 mm were observed at the air-tissue interfaces at the air canal and nasal cavity borders. Geometrically, distortion correction increased the target volume from 3.12 ± 0.52 cc to 3.84 ± 0.54 cc. Dosimetrically, AutoCorNN improved target coverage (0.96 ± 0.01 to 0.97 ± 0.02), conformity index (0.92 ± 0.03 to 0.94 ± 0.03), and reduced dose gradients outside the target. AutoCorNN achieves accurate geometric distortion correction comparable to conventional iterative methods while offering substantial computational acceleration, enabling precise target delineation and conformal dose delivery for improved radiation therapy outcomes.

Evolving Trends and Patterns of Utilization of Magnetic Resonance-Guided Radiotherapy at a Single Institution, 2018-2024

Background/Objectives: Over the past decade, significant advances have been made in image-guided radiotherapy (RT) particularly with the introduction of magnetic resonance (MR)-guided radiotherapy (MRgRT). However, the optimal clinical applications of MRgRT are still evolving. The intent of this analysis was to describe our institutional MRgRT utilization patterns and evolution therein, specifically as an early adopter within a center endowed with multiple other technology platforms. Materials/Methods: We retrospectively evaluated patterns of MRgRT utilization for patients treated with a 0.35-Tesla MR-Linac at our institution from April 2018 to April 2024. We analyzed changes in utilization across six annualized periods: Period 1 (April 2018-April 2019) through Period 6 (April 2023-April 2024). We defined ultra-hypofractionation (UHfx) as 5 or fewer fractions with a minimum fractional dose of 5 Gy. Electronic health records were reviewed, and data were extracted related to patient, tumor, and treatment characteristics. Results: A total of 823 treatment courses were delivered to 712 patients treated for 854 lesions. The most commonly treated sites were the pancreas (242 [29.4%]), thorax (172; 20.9%), abdominopelvic lymph nodes (107; 13.0%), liver (72; 8.7%), and adrenal glands (68; 8.3%). The median total prescribed dose of 50 Gy in five fractions (fxs) was typically delivered in consecutive days with automatic beam gating in inspiration breath hold. The median biologically effective dose (α/β = 10, BED10) was 94.4 Gy with nearly half (404, 49.1%) of all courses at a prescribed BED10 ≥ 100 Gy, which is widely regarded as a highly effective ablative dose. Courses in Period 6 vs. Period 1 more often had a prescribed BED10 ≥ 100 Gy (60.2% vs. 41.6%; p = 0.004). Of the 6036 total delivered fxs, nearly half (2643, 43.8%) required at least one fx of on-table adaptive radiotherapy (oART), most commonly for pancreatic tumors (1081, 17.9%). UHfx was used in over three quarters of all courses (630, 76.5%) with 472 (57.4%) of these requiring oART for at least one fraction. The relative utilization of oART increased significantly from Period 1 to Period 6 (37.6% to 85.0%; p < 0.001); a similar increase in the use of UHfx (66.3% to 89.5%; p < 0.001) was also observed. The median total in-room time for oART decreased from 81 min in Period 1 to 45 min in Period 6, while for non-oART, it remained stable around 40 min across all periods. Conclusions: Our institution implemented MRgRT with a priority for targeting mobile extracranial tumors in challenging anatomic locations that are frequently treated with dose escalation, require enhanced soft-tissue visualization, and could benefit from an ablative radiotherapy approach. Over the period under evaluation, the use of high-dose ablative doses (BED10 ≥ 100 Gy), oART and UHfx (including single-fraction ablation) increased significantly, underscoring both a swift learning curve and ability to optimize processes to maximize throughput and efficiency.

Abdominal synthetic CT generation for MR-only radiotherapy using structure-conserving loss and transformer-based cycle-GAN

Purpose

Recent deep-learning based synthetic computed tomography (sCT) generation using magnetic resonance (MR) images have shown promising results. However, generating sCT for the abdominal region poses challenges due to the patient motion, including respiration and peristalsis. To address these challenges, this study investigated an unsupervised learning approach using a transformer-based cycle-GAN with structure-preserving loss for abdominal cancer patients.

Method

A total of 120 T2 MR images scanned by 1.5 T Unity MR-Linac and their corresponding CT images for abdominal cancer patient were collected. Patient data were aligned using rigid registration. The study employed a cycle-GAN architecture, incorporating the modified Swin-UNETR as a generator. Modality-independent neighborhood descriptor (MIND) loss was used for geometric consistency. Image quality was compared between sCT and planning CT, using metrics including mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structure similarity index measure (SSIM) and Kullback-Leibler (KL) divergence. Dosimetric evaluation was evaluated between sCT and planning CT, using gamma analysis and relative dose volume histogram differences for each organ-at-risks, utilizing treatment plan. A comparison study was conducted between original, Swin-UNETR-only, MIND-only, and proposed cycle-GAN.

Results

The MAE, PSNR, SSIM and KL divergence of original cycle-GAN and proposed method were 86.1 HU, 26.48 dB, 0.828, 0.448 and 79.52 HU, 27.05 dB, 0.845, 0.230, respectively. The MAE and PSNR were statistically significant. The global gamma passing rates of the proposed method at 1%/1 mm, 2%/2 mm, and 3%/3 mm were 86.1 ± 5.9%, 97.1 ± 2.7%, and 98.9 ± 1.0%, respectively.

Conclusion

The proposed method significantly improves image metric of sCT for the abdomen patients than original cycle-GAN. Local gamma analysis was slightly higher for proposed method. This study showed the improvement of sCT using transformer and structure preserving loss even with the complex anatomy of the abdomen.

Study protocol: Optimising patient positioning for the planning of accelerated partial breast radiotherapy for the integrated magnetic resonance linear accelerator: OPRAH MRL

BACKGROUND

Accelerated partial breast irradiation (APBI) is an accepted treatment option for early breast cancer. Treatment delivered on the Magnetic Resonance integrated Linear Accelerator (MRL) provides the added assurance of improved soft tissue visibility, important in the delivery of APBI. This technique can be delivered in both the supine and prone positions, however current literature suggests that prone treatment on the MRL is infeasible due to physical limitations with bore size. This study aims to investigate the feasibility of positioning patients on a custom designed prone breast board compared with supine positioning on a personalised vacuum bag. Geometric distortion, the relative position of Organs at Risk (OAR) to the tumour bed and breathing motion (intrafraction motion) will be compared between the supine and prone positions. The study will also investigate the positional impact on dosimetry, patient experience, and position preference.

METHODS

Up to 30 patients will be recruited over a 12-month period for participation in this Human Research Ethics Committee approved exploratory cohort study. Patients will be scanned on the magnetic resonance imaging (MRI) Simulator in both the supine and prone positions as per current standard of care for APBI simulation. Supine and prone positioning comparisons will all be assessed on de-identified MRI image pairs, acquired using appropriate software. Patient experience will be explored through completion of a short, anonymous electronic survey. Descriptive statistics will be used for reporting of results with categorical, parametric/non-parametric tests applied (data format dependent). Survey results will be interpreted by comparison of percentage frequencies across the Likert scales. Thematic content analysis will be used to interpret qualitative data from the open-ended survey questions.

DISCUSSION

The results of this study will be used to assess the feasibility of treating patients with APBI in the prone position on a custom designed board on the MRL. It may also be used to assist with identification of patients who would benefit from this position over supine without the need to perform both scans. Patient experience and technical considerations will be utilised to develop a tool to assist in this process. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN1262400067583. Registered 28th of May 2024. https://www.anzctr.org.au/ACTRN12624000679583.aspx.

Bringing online adaptive radiotherapy to a standard C-arm linac

Current online adaptive radiotherapy (oART) workflows require dedicated equipment. Our aim was to develop and implement an oART workflow for a C-arm linac which can be performed using standard clinically available tools. A workflow was successfully developed and implemented. Three patients receiving palliative radiotherapy for bladder cancer were treated, with 33 of 35 total fractions being delivered with the cone-beam computed tomography (CBCT)-guided oART workflow. Average oART fraction duration was 24 min from start of CBCT acquisition to end of beam on. This work shows how oART could be performed without dedicated equipment, broadening oART availability for application at existing treatment machines.

The Role of MRI in Breast Cancer and Breast Conservation Therapy

Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

Feasibility and Acute Toxicity of Hypo-Fractionated Radiotherapy on 0.35T MR-LINAC: The First Prospective Study in Spain

This observational, descriptive, longitudinal, and prospective basket-type study (Registry #5289) prospectively evaluated the feasibility and acute toxicity of hypo-fractionated radiotherapy on the first 0.35T MR-LINAC in Spain. A total of 37 patients were included between August and December 2023, primarily with prostate tumors (59.46%), followed by pancreatic tumors (32.44%). Treatment regimens typically involved extreme hypo-fractionated radiotherapy, with precise dose delivery verified through quality assurance measures. Acute toxicity assessment at treatment completion revealed manageable cystitis, with one case persisting at the three-month follow-up. Gastrointestinal toxicity was minimal. For pancreatic tumors, daily adaptation of organ-at-risk (OAR) and gross tumor volume (GTV) was practiced, with median doses to OAR within acceptable limits. Three patients experienced gastrointestinal toxicity, mainly nausea. Overall, the study demonstrates the feasibility and safety of extreme hypo-fractionated radiotherapy on a 0.35T MR-LINAC, especially for challenging anatomical sites like prostate and pancreatic tumors. These findings support the feasibility of MR-LINAC-based radiotherapy in delivering precise treatments with minimal toxicity, highlighting its potential for optimizing cancer treatment strategies.

SC-GAN: Structure-completion generative adversarial network for synthetic CT generation from MR images with truncated anatomy

Creating synthetic CT (sCT) from magnetic resonance (MR) images enables MR-based treatment planning in radiation therapy. However, the MR images used for MR-guided adaptive planning are often truncated in the boundary regions due to the limited field of view and the need for sequence optimization. Consequently, the sCT generated from these truncated MR images lacks complete anatomic information, leading to dose calculation error for MR-based adaptive planning. We propose a novel structure-completion generative adversarial network (SC-GAN) to generate sCT with full anatomic details from the truncated MR images. To enable anatomy compensation, we expand input channels of the CT generator by including a body mask and introduce a truncation loss between sCT and real CT. The body mask for each patient was automatically created from the simulation CT scans and transformed to daily MR images by rigid registration as another input for our SC-GAN in addition to the MR images. The truncation loss was constructed by implementing either an auto-segmentor or an edge detector to penalize the difference in body outlines between sCT and real CT. The experimental results show that our SC-GAN achieved much improved accuracy of sCT generation in both truncated and untruncated regions compared to the original cycleGAN and conditional GAN methods.

Stereotactic body radiation therapy for liver metastases in oligometastatic disease

Oligometastatic cancers designate cancers in which the number of metastases is less than five, corresponding to a particular biological entity whose prognosis is situated between a localized and metastatic disease. The liver is one of the main sites of metastases. When patients are not suitable for surgery, stereotactic body radiotherapy provides high local control rate, although these data come mainly from retrospective studies, with no phase III study results. The need for a high therapeutic dose (biologically effective dose greater than 100Gy) while respecting the constraints on the organs at risk, and the management of respiratory movements require expertise and sufficient technical prerequisites. The emergence of new techniques such as MRI-guided radiotherapy could further increase the effectiveness of stereotactic radiotherapy of liver metastases, and thus improve the prognosis of these oligometastatic cancers.

MR-LINAC, a New Partner in Radiation Oncology: Current Landscape

Technological advances in radiation oncology are oriented towards improving treatment precision and tumor control. Among these advances, magnetic-resonance-image-guided radiation therapy (MRgRT) stands out, with technological advances to deliver targeted treatments adapted to a tumor's anatomy on the day while minimizing incidental exposure to organs at risk, offering an unprecedented therapeutic advantage compared to X-ray-based IGRT delivery systems. This new technology changes the traditional workflow in radiation oncology and requires an evolution in team coordination to administer more precise treatments. Once implemented, it paves the way for newer indication for radiation therapy to safely deliver higher doses than ever before, with better preservation of healthy tissues to optimize patient outcomes. In this narrative review, we assess the technical aspects of the novel linear accelerators that can deliver MRgRT and summarize the available published experience to date, focusing on oncological results and future challenges.

Intrafraction Motion Management With MR-Guided Radiation Therapy

High quality radiation therapy requires highly accurate and precise dose delivery. MR-guided radiotherapy (MRgRT), integrating an MRI scanner with a linear accelerator, offers excellent quality images in the treatment room without subjecting patient to ionizing radiation. MRgRT therefore provides a powerful tool for intrafraction motion management. This paper summarizes different sources of intrafraction motion for different disease sites and describes the MR imaging techniques available to visualize and quantify intrafraction motion. It provides an overview of MR guided motion management strategies and of the current technical capabilities of the commercially available MRgRT systems. It describes how these motion management capabilities are currently being used in clinical studies, protocols and provides a future outlook.

Preliminary study of cine-MRI compression in MR-guided radiotherapy

Background

Cine-magnetic resonance imaging (MRI) is currently used in real-time tumor tracking during magnetic resonance (MR)-guided radiotherapy. As a type of MRI specified for motion tracking, a few minutes' acquisition results in thousands of 2-dimensional (2D) images. For MR-guided radiotherapy consisting of multiple treatment fractions, the large number of cine-MRI images would be disproportionate to the tight clinical data storage available. To alleviate this issue, the feasibility of compression of cine-MRI via video encoders was investigated in this study.

Methods

The cine-MRI images were first sorted into 3 sequences according to their plane orientations. Then, each sequence was reordered according to their acquisition times [time-based (TB)] or content similarities [similarity-based (SB)]. As a result, 3 sequences were obtained for 3 plan orientations. Next, the obtained sequences were processed by a video encoder and the corresponding 3 video files were achieved. We employed 3 popular video encoders: Motion JPEG (M-JPEG), Advanced Video Coding (AVC), and High Efficiency Video Coding (HEVC). The performances of the sequence reordering methods and video encoders were evaluated based on a total of 150 image sets.

Results

The mean correlation quantities for SB sequences were higher than those for TB sequences by 3% (sagittal), 2% (coronal), and 1% (transverse), respectively. The average compression ratio (CR) yielded by the SB sequences was higher than that achieved by the TB sequences. Comparing with M-JPEG, the CRs obtained by AVC and HEVC were increased by 58% and 62% (sagittal), 16% and 23% (coronal), and 48% and 56% (transverse), respectively. Among the 3 video encoders, the highest CRs and restoration accuracy were achieved by HEVC.

Conclusions

HEVC with inter-frame coding is more effective in reducing the redundant information in consecutive images. It is feasible to implement the video encoder for high-performance cine-MRI compression.

Prior knowledge based deep learning auto-segmentation in magnetic resonance imaging-guided radiotherapy of prostate cancer

Background and purpose

Automation is desirable for organ segmentation in radiotherapy. This study compared deep learning methods for auto-segmentation of organs-at-risk (OARs) and clinical target volume (CTV) in prostate cancer patients undergoing fractionated magnetic resonance (MR)-guided adaptive radiation therapy. Models predicting dense displacement fields (DDFMs) between planning and fraction images were compared to patient-specific (PSM) and baseline (BM) segmentation models.

Materials and methods

A dataset of 92 patients with planning and fraction MR images (MRIs) from two institutions were used. DDFMs were trained to predict dense displacement fields (DDFs) between the planning and fraction images, which were subsequently used to propagate the planning contours of the bladder, rectum, and CTV to the daily MRI. The training was performed either with true planning-fraction image pairs or with planning images and their counterparts deformed by known DDFs. The BMs were trained on 53 planning images, while to generate PSMs, the BMs were fine-tuned using the planning image of a given single patient. The evaluation included Dice similarity coefficient (DSC), the average (HDavg) and the 95th percentile (HD95) Hausdorff distance (HD).

Results

The DDFMs with DSCs for bladder/rectum of 0.76/0.76 performed worse than PSMs (0.91/0.90) and BMs (0.89/0.88). The same trend was observed for HDs. For CTV, DDFM and PSM performed similarly yielding DSCs of 0.87 and 0.84, respectively.

Conclusions

DDFMs were found suitable for CTV delineation after rigid alignment. However, for OARs they were outperformed by PSMs, as they predicted only limited deformations even in the presence of substantial anatomical changes.

Initial clinical experience building a dual CT- and MR-guided adaptive radiotherapy program

Introduction

Our institution was the first in the world to clinically implement MR-guided adaptive radiotherapy (MRgART) in 2014. In 2021, we installed a CT-guided adaptive radiotherapy (CTgART) unit, becoming one of the first clinics in the world to build a dual-modality ART clinic. Herein we review factors that lead to the development of a high-volume dual-modality ART program and treatment census over an initial, one-year period.

Materials and Methods

The clinical adaptive service at our institution is enabled with both MRgART (MRIdian, ViewRay, Inc, Mountain View, CA) and CTgART (ETHOS, Varian Medical Systems, Palo Alto, CA) platforms. We analyzed patient and treatment information including disease sites treated, radiation dose and fractionation, and treatment times for patients on these two platforms. Additionally, we reviewed our institutional workflow for creating, verifying, and implementing a new adaptive workflow on either platform.

Results

From October 2021 to September 2022, 256 patients were treated with adaptive intent at our institution, 186 with MRgART and 70 with CTgART. The majority (106/186) of patients treated with MRgART had pancreatic cancer, and the most common sites treated with CTgART were pelvis (23/70) and abdomen (20/70). 93.0% of treatments on the MRgART platform were stereotactic body radiotherapy (SBRT), whereas only 72.9% of treatments on the CTgART platform were SBRT. Abdominal gated cases were allotted a longer time on the CTgART platform compared to the MRgART platform, whereas pelvic cases were allotted a shorter time on the CTgART platform when compared to the MRgART platform. Our adaptive implementation technique has led to six open clinical trials using MRgART and seven using CTgART.

Conclusions

We demonstrate the successful development of a dual platform ART program in our clinic. Ongoing efforts are needed to continue the development and integration of ART across platforms and disease sites to maximize access and evidence for this technique worldwide.

Recent advances progress in radiotherapy for breast cancer after breast-conserving surgery: a review

Adjuvant radiotherapy after breast-conserving surgery has become an integral part of the treatment of breast cancer. In recent years, the development of radiotherapy technology has made great progress in this field, including the comparison of the curative effects of various radiotherapy techniques and the performance of the segmentation times. The choice of radiotherapy technology needs to be co-determined by clinical evidence practice and evaluated for each individual patient to achieve precision radiotherapy. This article discusses the treatment effects of different radiotherapy, techniques, the risk of second cancers and short-range radiation therapy techniques after breast-conserving surgery such as hypo fractionated whole breast irradiation and accelerated partial breast irradiation. The choice of radiotherapy regimen needs to be based on the individual condition of the patient, and the general principle is to focus on the target area and reduce the irradiation of the normal tissues and organs. Short-range radiotherapy and hypofractionated are superior to conventional radiotherapy and are expected to become the mainstream treatment after breast-conserving surgery.

Electron stream effect in 0.35 Tesla magnetic resonance image guided radiotherapy for breast cancer

Purpose

This research aimed to analyze electron stream effect (ESE) during magnetic resonance image guided radiotherapy (MRgRT) for breast cancer patients on a MR-Linac (0.35 Tesla, 6MV), with a focus on the prevention of redundant radiation exposure.

Materials and methods

RANDO phantom was used with and without the breast attachment in order to represent the patients after breast conserving surgery (BCS) and those received modified radical mastectomy (MRM). The prescription dose is 40.05 Gy in fifteen fractions for whole breast irradiation (WBI) or 20 Gy single shot for partial breast irradiation (PBI). Thirteen different portals of intensity-modulated radiation therapy were created. And then we evaluated dose distribution in five areas (on the skin of the tip of the nose, the chin, the neck, the abdomen and the thyroid.) outside of the irradiated field with and without 0.35 Tesla. In addition, we added a piece of bolus with the thickness of 1cm on the skin in order to compare the ESE difference with and without a bolus. Lastly, we loaded two patients' images for PBI comparison.

Results

We found that 0.35 Tesla caused redundant doses to the skin of the chin and the neck as high as 9.79% and 5.59% of the prescription dose in the BCS RANDO model, respectively. For RANDO phantom without the breast accessory (simulating MRM), the maximal dose increase were 8.71% and 4.67% of the prescription dose to the skin of the chin and the neck, respectively. Furthermore, the bolus we added efficiently decrease the unnecessary dose caused by ESE up to 59.8%.

Conclusion

We report the first physical investigation on successful avoidance of superfluous doses on a 0.35T MR-Linac for breast cancer patients. Future studies of MRgRT on the individual body shape and its association with ESE influence is warranted.

Deep learning for automated contouring of neurovascular structures on magnetic resonance imaging for prostate cancer patients

Background and purpose

Manual contouring of neurovascular structures on prostate magnetic resonance imaging (MRI) is labor-intensive and prone to considerable interrater disagreement. Our aim is to contour neurovascular structures automatically on prostate MRI by deep learning (DL) to improve workflow and interrater agreement.

Materials and methods

Segmentation of neurovascular structures was performed on pre-treatment 3.0 T MRI data of 131 prostate cancer patients (training [n = 105] and testing [n = 26]). The neurovascular structures include the penile bulb (PB), corpora cavernosa (CCs), internal pudendal arteries (IPAs), and neurovascular bundles (NVBs). Two DL networks, nnU-Net and DeepMedic, were trained for auto-contouring on prostate MRI and evaluated using volumetric Dice similarity coefficient (DSC), mean surface distances (MSD), Hausdorff distances, and surface DSC. Three radiation oncologists evaluated the DL-generated contours and performed corrections when necessary. Interrater agreement was assessed and the time required for manual correction was recorded.

Results

nnU-Net achieved a median DSC of 0.92 (IQR: 0.90-0.93) for the PB, 0.90 (IQR: 0.86-0.92) for the CCs, 0.79 (IQR: 0.77-0.83) for the IPAs, and 0.77 (IQR: 0.72-0.81) for the NVBs, which outperformed DeepMedic for each structure (p < 0.03). nnU-Net showed a median MSD of 0.24 mm for the IPAs and 0.71 mm for the NVBs. The median interrater DSC ranged from 0.93 to 1.00, with the majority of cases (68.9%) requiring manual correction times under two minutes.

Conclusions

DL enables reliable auto-contouring of neurovascular structures on pre-treatment MRI data, easing the clinical workflow in neurovascular-sparing MR-guided radiotherapy.

Clinical application of MR-Linac in tumor radiotherapy: a systematic review

Recent years have seen both a fresh knowledge of cancer and impressive advancements in its treatment. However, the clinical treatment paradigm of cancer is still difficult to implement in the twenty-first century due to the rise in its prevalence. Radiotherapy (RT) is a crucial component of cancer treatment that is helpful for almost all cancer types. The accuracy of RT dosage delivery is increasing as a result of the quick development of computer and imaging technology. The use of image-guided radiation (IGRT) has improved cancer outcomes and decreased toxicity. Online adaptive radiotherapy will be made possible by magnetic resonance imaging-guided radiotherapy (MRgRT) using a magnetic resonance linear accelerator (MR-Linac), which will enhance the visibility of malignancies. This review's objectives are to examine the benefits of MR-Linac as a treatment approach from the perspective of various cancer patients' prognoses and to suggest prospective development areas for additional study.

Evaluation of therapeutic radiographer contouring for magnetic resonance image guided online adaptive prostate radiotherapy

BACKGROUND AND PURPOSE

The implementation of MRI-guided online adaptive radiotherapy has facilitated the extension of therapeutic radiographers' roles to include contouring, thus releasing the clinician from attending daily treatment. Following undergoing a specifically designed training programme, an online interobserver variability study was performed.

MATERIALS AND METHODS

117 images from six patients treated on a MR Linac were contoured online by either radiographer or clinician and the same images contoured offline by the alternate profession. Dice similarity coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) and volume metrics were used to analyse contours. Additionally, the online radiographer contours and optimised plans (n = 59) were analysed using the offline clinician defined contours. After clinical implementation of radiographer contouring, target volume comparison and dose analysis was performed on 20 contours from five patients.

RESULTS

Comparison of the radiographers' and clinicians' contours resulted in a median (range) DSC of 0.92 (0.86 - 0.99), median (range) MDA of 0.98 mm (0.2-1.7) and median (range) HD of 6.3 mm (2.5-11.5) for all 117 fractions. There was no significant difference in volume size between the two groups. Of the 59 plans created with radiographer online contours and overlaid with clinicians' offline contours, 39 met mandatory dose constraints and 12 were acceptable because 95 % of the high dose PTV was covered by 95 % dose, or the high dose PTV was within 3 % of online plan. A clinician blindly reviewed the eight remaining fractions and, using trial quality assurance metrics, deemed all to be acceptable. Following clinical implementation of radiographer contouring, the median (range) DSC of CTV was 0.93 (0.88-1.0), median (range) MDA was 0.8 mm (0.04-1.18) and HD was 5.15 mm (2.09-8.54) respectively. Of the 20 plans created using radiographer online contours overlaid with clinicians' offline contours, 18 met the dosimetric success criteria, the remaining 2 were deemed acceptable by a clinician.

CONCLUSION

Radiographer and clinician prostate and seminal vesicle contours on MRI for an online adaptive workflow are comparable and produce clinically acceptable plans. Radiographer contouring for prostate treatment on a MR-linac can be effectively introduced with appropriate training and evaluation. A DSC threshold for target structures could be implemented to streamline future training.

Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation

BACKGROUND

Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerators (MR-Linacs) can administer a tailored radiation dose at each treatment fraction. Daily MR imaging followed by organ and target segmentation adjustments allow to capture anatomical changes, improve target volume coverage, and reduce the risk of side effects. The introduction of automatic segmentation techniques could help to further improve the online adaptive workflow by shortening the re-contouring time and reducing intra- and inter-observer variability. In fractionated RT, prior knowledge, such as planning images and manual expert contours, is usually available before irradiation, but not used by current artificial intelligence-based autocontouring approaches.

PURPOSE

The goal of this study was to train convolutional neural networks (CNNs) for automatic segmentation of bladder, rectum (organs at risk, OARs), and clinical target volume (CTV) for prostate cancer patients treated at 0.35 T MR-Linacs. Furthermore, we tested the CNNs generalization on data from independent facilities and compared them with the MR-Linac treatment planning system (TPS) propagated structures currently used in clinics. Finally, expert planning delineations were utilized for patient- (PS) and facility-specific (FS) transfer learning to improve auto-segmentation of CTV and OARs on fraction images.

METHODS

In this study, data from fractionated treatments at 0.35 T MR-Linacs were leveraged to develop a 3D U-Net-based automatic segmentation. Cohort C1 had 73 planning images and cohort C2 had 19 planning and 240 fraction images. The baseline models (BMs) were trained solely on C1 planning data using 53 MRIs for training and 10 for validation. To assess their accuracy, the models were tested on three data subsets: (i) 10 C1 planning images not used for training, (ii) 19 C2 planning, and (iii) 240 C2 fraction images. BMs also served as a starting point for FS and PS transfer learning, where the planning images from C2 were used for network parameter fine tuning. The segmentation output of the different trained models was compared against expert ground truth by means of geometric metrics. Moreover, a trained physician graded the network segmentations as well as the segmentations propagated by the clinical TPS.

RESULTS

The BMs showed dice similarity coefficients (DSC) of 0.88(4) and 0.93(3) for the rectum and the bladder, respectively, independent of the facility. CTV segmentation with the BM was the best for intermediate- and high-risk cancer patients from C1 with DSC=0.84(5) and worst for C2 with DSC=0.74(7). The PS transfer learning brought a significant improvement in the CTV segmentation, yielding DSC=0.72(4) for post-prostatectomy and low-risk patients and DSC=0.88(5) for intermediate- and high-risk patients. The FS training did not improve the segmentation accuracy considerably. The physician's assessment of the TPS-propagated versus network-generated structures showed a clear advantage of the latter.

CONCLUSIONS

The obtained results showed that the presented segmentation technique has potential to improve automatic segmentation for MR-guided RT.

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.

Focused Ultrasound and Ultrasound Stimulated Microbubbles in Radiotherapy Enhancement for Cancer Treatment

Radiation therapy (RT) has been the standard of care for treating a multitude of cancer types. However, ionizing radiation has adverse short and long-term side effects which have resulted in treatment complications for decades. Thus, advances in enhancing the effects of RT have been the primary focus of research in radiation oncology. To avoid the usage of high radiation doses, treatment modalities such as high-intensity focused ultrasound can be implemented to reduce the radiation doses required to destroy cancer cells. In the past few years, the use of focused ultrasound (FUS) has demonstrated immense success in a number of applications as it capitalizes on spatial specificity. It allows ultrasound energy to be delivered to a targeted focal area without harming the surrounding tissue. FUS combined with RT has specifically demonstrated experimental evidence in its application resulting in enhanced cell death and tumor cure. Ultrasound-stimulated microbubbles have recently proved to be a novel way of enhancing RT as a radioenhancing agent on its own, or as a delivery vector for radiosensitizing agents such as oxygen. In this mini-review article, we discuss the bio-effects of FUS and RT in various preclinical models and highlight the applicability of this combined therapy in clinical settings.

MRI-GUIDED RADIOTHERAPY FOR PROSTATE CANCER: A NEW PARADIGM

Radiotherapy is one of the key treatment modalities for primary prostate cancer. During the last decade, significant advances were made in radiotherapy technology leading to increasing both physical and biological precision. Being a loco-regional treatment approach, radiotherapy requires accurate target dose deposition while sparing surrounding healthy tissue. Conventional radiotherapy is based on computerized tomography (CT) images both for radiotherapy planning and image-guidance, however, shortcomings of CT as soft tissue imaging tool are well known. Nowadays, our ability to further escalate radiotherapy dose using hypofractionation is limited by uncertainties in CT-based image guidance and verification. Magnetic resonance imaging (MRI) is a well established imaging method for pelvic organs. In prostate cancer specifically, MRI accurately depicts prostate zonal anatomy, rectum, bladder, and pelvic floor structures with previously unseen precision owing to its sharp soft tissue contrast. The advantages of including MRI in the clinical workflow of prostate cancer radiotherapy are multifold. MRI allows for true adaptive radiotherapy to unfold based on daily MRI images taken before, during and after each radiotherapy fraction. It enables accurate dose escalation to the prostate and intraprostatic tumor lesions. Technically, MRI high-strength magnetic field and linear accelerator high energy electromagnetic beams are hardly compatible, and important efforts were made to overcome these technical challenges and integrate MRI and linear accelerator into one single treatment device, called MRI-linac. Different systems are produced by two leading vendors in the field and currently, there are around 100 MRI-linacs worldwide in clinical operations. In this narrative review paper, we discuss historical perspective of image guidance in radiotherapy, basic elements of MRI, current clinical developments in MRI-guided prostate cancer radiotherapy, and challenges associated with the use of MRI-linac in clinical practice.

Practical guidelines of online MR-guided adaptive radiotherapy

The first magnetic resonance (MR)-guided radiotherapy system in Japan was installed in May 2017. Implementation of online MR-guided adaptive radiotherapy (MRgART) began in February 2018. Online MRgART offers greater treatment accuracy owing to the high soft-tissue contrast in MR-images (MRI), compared to that in X-ray imaging. The Japanese Society for Magnetic Resonance in Medicine (JSMRM), Japan Society of Medical Physics (JSMP), Japan Radiological Society (JRS), Japanese Society of Radiological Technology (JSRT), and Japanese Society for Radiation Oncology (JASTRO) jointly established the comprehensive practical guidelines for online MRgART. These guidelines propose the essential requirements for clinical implementation of online MRgART with respect to equipment, personnel, institutional environment, practice guidance, and quality assurance/quality control (QA/QC). The minimum requirements for related equipment and QA/QC tools, recommendations for safe operation of MRI system, and the implementation system are described. The accuracy of monitor chamber and detector in dose measurements should be confirmed because of the presence of magnetic field. The ionization chamber should be MR-compatible. Non-MR-compatible devices should be used in an area that is not affected by the static magnetic field (outside the five Gauss line), and their operation should be checked to ensure that they do not affect the MR image quality. Dose verification should be performed using an independent dose verification system that has been confirmed to be reliable through commissioning. This guideline proposes the checklists to ensure the safety of online MRgART. Successful clinical implementation of online MRgART requires close collaboration between physician, radiological technologist, nurse, and medical physicist.

Treatment-integrated imaging, radiomics, and personalised radiotherapy: the future is at hand

Since the introduction of computed tomography for planning purposes in the 1970s, we have been observing a continuous development of different imaging methods in radiotherapy. The current achievements of imaging technologies in radiotherapy enable more than just improvement of accuracy on the planning stage. Through integrating imaging with treatment machines, they allow advanced control methods of dose delivery during the treatment. This article reviews how the integration of existing and novel forms of imaging changes radiotherapy and how these advances can allow a more individualised approach to cancer therapy. We believe that the significant challenge for the next decade is the continued integration of a range of different imaging devices into linear accelerators. These imaging modalities should show intra-fraction changes in body morphology and inter-fraction metabolic changes. As the use of these more advanced, integrated machines grows, radiotherapy delivery will become more accurate, thus resulting in better clinical outcomes: higher cure rates with fewer side effects.

Clinical adoption patterns of 0.35 Tesla MR-guided radiation therapy in Europe and Asia

Background

Magnetic resonance-guided radiotherapy (MRgRT) utilization is rapidly expanding, driven by advanced capabilities including better soft tissue imaging, continuous intrafraction target visualization, automatic triggered beam delivery, and the availability of on-table adaptive replanning. Our objective was to describe patterns of 0.35 Tesla (T)-MRgRT utilization in Europe and Asia among early adopters of this novel technology.

Methods

Anonymized administrative data from all 0.35T-MRgRT treatment systems in Europe and Asia were extracted for patients who completed treatment from 2015 to 2020. Detailed treatment information was analyzed for all MR-linear accelerators (linac) and -cobalt systems.

Results

From 2015 through the end of 2020, there were 5796 completed treatment courses delivered in 46,389 individual fractions. 23.5% of fractions were adapted. Ultra-hypofractionated (UHfx) dose schedules (1–5 fractions) were delivered for 63.5% of courses, with 57.8% of UHfx fractions adapted on-table. The most commonly treated tumor types were prostate (23.5%), liver (14.5%), lung (12.3%), pancreas (11.2%), and breast (8.0%), with increasing compound annual growth rates (CAGRs) in numbers of courses from 2015 through 2020 (pancreas: 157.1%; prostate: 120.9%; lung: 136.0%; liver: 134.2%).

Conclusions

This is the first comprehensive study reporting patterns of utilization among early adopters of a 0.35T-MRgRT system in Europe and Asia. Intrafraction MR image-guidance, advanced motion management, and increasing adoption of on-table adaptive RT have accelerated a transition to UHfx regimens. MRgRT has been predominantly used to treat tumors in the upper abdomen, pelvis and lungs, and increasingly with adaptive replanning, which is a radical departure from legacy radiotherapy practices.

A Prospective Study of Stereotactic Body Radiotherapy (SBRT) with Concomitant Whole-Pelvic Radiotherapy (WPRT) for High-Risk Localized Prostate Cancer Patients Using 1.5 Tesla Magnetic Resonance Guidance: The Preliminary Clinical Outcome

Background: Conventionally fractionated whole-pelvic nodal radiotherapy (WPRT) improves clinical outcome compared to prostate-only RT in high-risk prostate cancer (HR-PC). MR-guided stereotactic body radiotherapy (MRgSBRT) with concomitant WPRT represents a novel radiotherapy (RT) paradigm for HR-PC, potentially improving online image guidance and clinical outcomes. This study aims to report the preliminary clinical experiences and treatment outcome of 1.5 Tesla adaptive MRgSBRT with concomitant WPRT in HR-PC patients. Materials and methods: Forty-two consecutive HR-PC patients (72.5 ± 6.8 years) were prospectively enrolled, treated by online adaptive MRgSBRT (8 Gy(prostate)/5 Gy(WPRT) × 5 fractions) combined with androgen deprivation therapy (ADT) and followed up (median: 251 days, range: 20−609 days). Clinical outcomes were measured by gastrointestinal (GI) and genitourinary (GU) toxicities according to the Common Terminology Criteria for Adverse Events (CTCAE) Scale v. 5.0, patient-reported quality of life (QoL) with EPIC (Expanded Prostate Cancer Index Composite) questionnaire, and prostate-specific antigen (PSA) responses. Results: All MRgSBRT fractions achieved planning objectives and dose specifications of the targets and organs at risk, and they were successfully delivered. The maximum cumulative acute GI/GU grade 1 and 2 toxicity rates were 19.0%/81.0% and 2.4%/7.1%, respectively. The subacute (>30 days) GI/GU grade 1 and 2 toxicity rates were 21.4%/64.3% and 2.4%/2.4%, respectively. No grade 3 toxicities were reported. QoL showed insignificant changes in urinary, bowel, sexual, and hormonal domain scores during the follow-up period. All patients had early post-MRgSBRT biochemical responses, while biochemical recurrence (PSA nadir + 2 ng/mL) occurred in one patient at month 18. Conclusions: To our knowledge, this is the first prospective study that showed the clinical outcomes of MRgSBRT with concomitant WPRT in HR-PC patients. The early results suggested favorable treatment-related toxicities and encouraging patient-reported QoLs, but long-term follow-up is needed to confirm our early results.

Towards Accurate and Precise Image-Guided Radiotherapy: Clinical Applications of the MR-Linac

Advances in image-guided radiotherapy have brought about improved oncologic outcomes and reduced toxicity. The next generation of image guidance in the form of magnetic resonance imaging (MRI) will improve visualization of tumors and make radiation treatment adaptation possible. In this review, we discuss the role that MRI plays in radiotherapy, with a focus on the integration of MRI with the linear accelerator. The MR linear accelerator (MR-Linac) will provide real-time imaging, help assess motion management, and provide online adaptive therapy. Potential advantages and the current state of these MR-Linacs are highlighted, with a discussion of six different clinical scenarios, leading into a discussion on the future role of these machines in clinical workflows.

A mask-compatible, radiolucent, 8-channel head and neck receive array for MRI-guided radiotherapy treatments and pre-treatment simulation

Immobilization masks are used to prevent patient movement during head and neck (H&N) radiotherapy. Motion restriction is beneficial both during treatment, as well as in the pre-treatment simulation phase, where magnetic resonance imaging (MRI) is often used for target definition. However, the shape and size of the immobilization masks hinder the use of regular, close-fitting MRI receive arrays. In this work, we developed a mask-compatible 8-channel H&N array that consists of a single-channel baseplate, on which the mask can be secured, and a flexible 7-channel anterior element that follows the shape of the mask. The latter uses high impedance coils to achieve its flexibility and radiolucency. A fully-functional prototype was manufactured, its radiolucency was characterized, and the gain in imaging performance with respect to current clinical setups was quantified. Dosimetry measurements showed an overall dose change of −0.3%. Small, local deviations were up to −2.7% but had no clinically significant impact on a full treatment plan, as gamma pass rates (3%/3 mm) only slightly reduced from 97.9% to 97.6% (clinical acceptance criterion: ≥95%). The proposed H&N array improved the imaging performance with respect to three clinical setups. The H&N array more than doubled (+123%) and tripled (+246%) the signal-to-noise ratio with respect to the clinical MRI-simulation and MR-linac setups, respectively. G-factors were also lower with the proposed H&N array. The improved imaging performance resulted in a clearly visible signal-to-noise ratio improvement of clinically used TSE and DWI acquisitions. In conclusion, the 8-channel H&N array improves the imaging performance of MRI-simulation and MR-linac acquisitions, while dosimetry suggests that no clinically significant dose changes are induced.

Real-time MRI motion estimation through an unsupervised k-space-driven deformable registration network (KS-RegNet)

Purpose. Real-time three-dimensional (3D) magnetic resonance (MR) imaging is challenging because of slow MR signal acquisition, leading to highly under-sampled k-space data. Here, we proposed a deep learning-based, k-space-driven deformable registration network (KS-RegNet) for real-time 3D MR imaging. By incorporating prior information, KS-RegNet performs a deformable image registration between a fully-sampled prior image and on-board images acquired from highly-under-sampled k-space data, to generate high-quality on-board images for real-time motion tracking. Methods. KS-RegNet is an end-to-end, unsupervised network consisting of an input data generation block, a subsequent U-Net core block, and following operations to compute data fidelity and regularization losses. The input data involved a fully-sampled, complex-valued prior image, and the k-space data of an on-board, real-time MR image (MRI). From the k-space data, under-sampled real-time MRI was reconstructed by the data generation block to input into the U-Net core. In addition, to train the U-Net core to learn the under-sampling artifacts, the k-space data of the prior image was intentionally under-sampled using the same readout trajectory as the real-time MRI, and reconstructed to serve an additional input. The U-Net core predicted a deformation vector field that deforms the prior MRI to on-board real-time MRI. To avoid adverse effects of quantifying image similarity on the artifacts-ridden images, the data fidelity loss of deformation was evaluated directly in k-space. Results. Compared with Elastix and other deep learning network architectures, KS-RegNet demonstrated better and more stable performance. The average (±s.d.) DICE coefficients of KS-RegNet on a cardiac dataset for the 5- , 9- , and 13-spoke k-space acquisitions were 0.884 ± 0.025, 0.889 ± 0.024, and 0.894 ± 0.022, respectively; and the corresponding average (±s.d.) center-of-mass errors (COMEs) were 1.21 ± 1.09, 1.29 ± 1.22, and 1.01 ± 0.86 mm, respectively. KS-RegNet also provided the best performance on an abdominal dataset. Conclusion. KS-RegNet allows real-time MRI generation with sub-second latency. It enables potential real-time MR-guided soft tissue tracking, tumor localization, and radiotherapy plan adaptation.

Integrated MRI-guided radiotherapy - opportunities and challenges

MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach.

Impact of Using Unedited CT-Based DIR-Propagated Autocontours on Online ART for Pancreatic SBRT

Purpose

To determine the dosimetric impact of using unedited autocontours in daily plan adaptation of patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiotherapy using tumor tracking.

Materials and Methods

The study included 98 daily CT scans of 35 LAPC patients. All scans were manually contoured (MAN), and included the PTV and main organs-at-risk (OAR): stomach, duodenum and bowel. Precision and MIM deformable image registration (DIR) methods followed by contour propagation were used to generate autocontour sets on the daily CT scans. Autocontours remained unedited, and were compared to MAN on the whole organs and at 3, 1 and 0.5 cm from the PTV. Manual and autocontoured OAR were used to generate daily plans using the VOLO™ optimizer, and were compared to non-adapted plans. Resulting planned doses were compared based on PTV coverage and OAR dose-constraints.

Results

Overall, both algorithms reported a high agreement between unclipped MAN and autocontours, but showed worse results when being evaluated on the clipped structures at 1 cm and 0.5 cm from the PTV. Replanning with unedited autocontours resulted in better OAR sparing than non-adapted plans for 95% and 84% plans optimized using Precision and MIM autocontours, respectively, and obeyed OAR constraints in 64% and 56% of replans.

Conclusion

For the majority of fractions, manual correction of autocontours could be avoided or be limited to the region closest to the PTV. This practice could further reduce the overall timings of adaptive radiotherapy workflows for patients with LAPC.

Neoadjuvant Chemoradiotherapy for Locally Advanced Gastric Cancer: Where Are We at?

Simple Summary

More than 50% of gastric cancer are at least locally advanced at presentation. For such patients, a multimodal approach rather than mere surgical resection leads to better long-term prognosis. Neoadjuvant chemoradiotherapy is one of the common treatment strategies for local advanced gastric cancer. Based on the experience and evidence from esophago-gastric cancers, the incorporation of systemic and locoregional therapy has shown superior disease control and reduced local recurrence. However, the optimal chemotherapy regimen, patient selection, technical consideration and potential biomarkers are still under investigation. Furthermore, the comparison of neoadjuvant chemoradiotherapy with neoadjuvant/perioperative chemotherapy is also an important issue to be answered. In the review article, we addressed the current available evidence to provide a comprehensive understanding and the use of neoadjuvant chemoradiotherapy for locally advanced gastric cancer. Future studies and ongoing trials will be necessary to determine the best candidate and the role of newer systemic and radiation therapies in such patients. NCRT is a feasible treatment option for LAGC, with the ability to achieve favorable disease control and enable higher radical resection rates over those afforded by perioperative chemotherapy or surgery alone. Large clinical trials examining the comparative efficacy of NCRT and NCT are underway. The discrepancy between the satisfactory pCR rates associated with NCRT and the nonsignificant association between NCRT and survival warrants further exploration. Furthermore, newer therapies such as immunotherapy and adaptive radiotherapy may be implemented in con-junction with NCRT, and the development of useful biomarkers may ultimately lead to the de-velopment of personalized treatments for LAGC. These research directions may lead to the dis-covery of the optimal approach to administering NCRT to patients with LAGC. They may also aid in the determination of the optimal candidates for undergoing NCRT.

Abstract

Locally advanced gastric cancer (LAGC) has a poor prognosis with surgical resection alone, and neoadjuvant treatment has been recommended to improve surgical and oncological outcomes. Although neoadjuvant chemotherapy has been established to be effective for LAGC, the role of neoadjuvant chemoradiotherapy (NCRT) remains under investigation. Clinical experience and research evidence on esophagogastric junction adenocarcinoma (e.g., cardia gastric cancers) indicate that the likelihood of achieving sustainable local control is higher through NCRT than through resection alone. Furthermore, NCRT also has an acceptable treatment-related toxicity and adverse event profile. In particular, it increases the likelihood of achieving an R0 resection and a pathological complete response (pCR). Moreover, NCRT results in higher overall and recurrence-free survival rates than surgery alone; however, evidence on the survival benefits of NCRT versus neoadjuvant chemotherapy (NCT) remains conflicting. For noncardia gastric cancer, the efficacy of NCRT has mostly been reported in retrospective studies, and several large clinical trials are ongoing. Consequently, NCRT might play a more essential role in unresectable LAGC, for which NCT alone may not be adequate to attain disease control. The continual improvements in systemic treatments, radiotherapy techniques, and emerging biomarkers can also lead to improved personalized therapy for NCRT. To elucidate the contributions of NCRT to gastric cancer treatment in the future, the efficacy, potential toxicity, predictive biomarkers, and clinical considerations for implementing NCRT in different types of LAGC were reviewed.

Registration-guided deep learning image segmentation for cone beam CT-based online adaptive radiotherapy

PURPOSE

Adaptive radiotherapy (ART), especially online ART, effectively accounts for positioning errors and anatomical changes. One key component of online ART process is accurately and efficiently delineating organs at risk (OARs) and targets on online images, such as Cone Beam Computed Tomography (CBCT). Direct application of deep learning (DL)-based segmentation to CBCT images suffered from issues such as low image quality and limited available contour labels for training. To overcome these obstacles to online CBCT segmentation, we propose a registration-guided DL (RgDL) segmentation framework that integrates image registration algorithms and DL segmentation models.

METHODS

The RgDL framework is composed of two components: image registration and registration-guided DL segmentation. The image registration algorithm transforms / deforms planning contours, which were subsequently used as guidance by the DL model to obtain accurate final segmentations. We had two implementations of the proposed framework-Rig-RgDL (Rig for rigid body) and Def-RgDL (Def for deformable)-with rigid body (RB) registration or deformable image registration (DIR) as the registration algorithm, respectively, and U-Net as the DL model architecture. The two implementations of RgDL framework were trained and evaluated on seven OARs in an institutional clinical Head and Neck (HN) dataset.

RESULTS

Compared to the baseline approaches using the registration or the DL alone, RgDLs achieved more accurate segmentation, as measured by higher mean Dice similarity coefficients (DSC) and other distance-based metrics. Rig-RgDL achieved a DSC of 84.5% on seven OARs on average, higher than RB or DL alone by 4.5% and 4.7%. The average DSC of Def-RgDL was 86.5%, higher than DIR or DL alone by 2.4% and 6.7%. The inference time required by the DL model component to generate final segmentations of seven OARs was less than one second in RgDL. By examining the contours from RgDLs and DL case by case, we found that RgDL was less susceptible to image artifacts. We also studied how the performances of RgDL and DL vary with the size of the training dataset. The DSC of DL dropped by 12.1% as the number of training data decreased from 22 to 5, while RgDL only dropped by 3.4%.

CONCLUSION

By incorporating the patient-specific registration guidance to a population-based DL segmentation model, RgDL framework overcame the obstacles associated with online CBCT segmentation, including low image quality and insufficient training data, and achieved better segmentation accuracy than baseline methods. The resulting segmentation accuracy and efficiency show promise for applying this RgDL framework for online ART. This article is protected by copyright. All rights reserved.

Acquisition repeatability of MRI radiomics features in the head and neck: a dual-3D-sequence multi-scan study

Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer (HNC), a group of malignancies associated with high heterogeneity. However, the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck (HN) tissues. In particular, feature repeatability of radiomics in magnetic resonance imaging (MRI) acquisition, which is considered a crucial confounding factor of radiomics feature reliability, is still sparsely investigated. This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers, aiming for potential magnetic resonance-guided radiotherapy (MRgRT) treatment of HNC. Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5 T MRI simulator. The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient (ICC), whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation (CV). The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types, tissues, and pulse sequences. Only a small fraction of features showed excellent acquisition repeatability (ICC > 0.9) and low within-subject variability. Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans. This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.

MR-guided adaptive versus ITV-based stereotactic body radiotherapy for hepatic metastases (MAESTRO): a randomized controlled phase II trial

Background

Stereotactic body radiotherapy (SBRT) is an established local treatment method for patients with hepatic oligometastasis or oligoprogression. Liver metastases often occur in close proximity to radiosensitive organs at risk (OARs). This limits the possibility to apply sufficiently high doses needed for optimal local control. Online MR-guided radiotherapy (oMRgRT) is expected to hold potential to improve hepatic SBRT by offering superior soft-tissue contrast for enhanced target identification as well as the benefit of gating and daily real-time adaptive treatment. The MAESTRO trial therefore aims to assess the potential advantages of adaptive, gated MR-guided SBRT compared to conventional SBRT at a standard linac using an ITV (internal target volume) approach.

Methods

This trial is conducted as a prospective, randomized, three-armed phase II study in 82 patients with hepatic metastases (solid malignant tumor, 1–3 hepatic metastases confirmed by magnetic resonance imaging (MRI), maximum diameter of each metastasis ≤ 5 cm (in case of 3 metastases: sum of diameters ≤ 12 cm), age ≥ 18 years, Karnofsky Performance Score ≥ 60%). If a biologically effective dose (BED) ≥ 100 Gy (α/β = 10 Gy) is feasible based on ITV-based planning, patients will be randomized to either MRgRT or ITV-based SBRT. If a lesion cannot be treated with a BED ≥ 100 Gy, the patient will be treated with MRgRT at the highest possible dose. Primary endpoint is the non-inferiority of MRgRT at the MRIdian Linac® system compared to ITV-based SBRT regarding hepatobiliary and gastrointestinal toxicity CTCAE III or higher. Secondary outcomes investigated are local, locoregional (intrahepatic) and distant tumor control, progression-free survival, overall survival, possible increase of BED using MRgRT if the BED is limited with ITV-based SBRT, treatment-related toxicity, quality of life, dosimetric parameters of radiotherapy plans as well as morphological and functional changes in MRI. Potential prognostic biomarkers will also be evaluated.

Discussion

MRgRT is known to be both highly cost- and labor-intensive. The MAESTRO trial aims to provide randomized, higher-level evidence for the dosimetric and possible consecutive clinical benefit of MR-guided, on-table adaptive and gated SBRT for dose escalation in critically located hepatic metastases adjacent to radiosensitive OARs.

Trial registration

The study has been prospectively registered on August 30th, 2021: Clinicaltrials.gov, “Magnetic Resonance-guided Adaptive Stereotactic Body Radiotherapy for Hepatic Metastases (MAESTRO)”, NCT05027711.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02033-2.

Use of magnetic resonance image-guided radiotherapy for breast cancer: a scoping review

In recent years, we have seen the integration of magnetic resonance imaging (MRI) simulators into radiotherapy centres and the emergence MR linear accelerators (MR-linac). Currently, there are limited studies to demonstrate the clinical effectiveness of MRI guided radiotherapy (MRIgRT) treatment for breast cancer patients. The objective of this scoping review was to identify and map the existing evidence surrounding the clinical implementation of MRIgRT for breast cancer patients. We also identified the challenges and knowledge gaps in the literature. The scoping review was reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) extension for Scoping Reviews reporting guidelines. Titles and abstracts were screened by two independent reviewers. Quantitative and qualitative data were extracted and summarised using thematically organised tables. Results identify that accelerated partial breast irradiation (APBI) is the most common form of treatment for MRIgRT. The presence of the magnet does not affect target coverage or violate organ at risk (OAR) constraints compared to standard radiotherapy methods. Consideration is advised for skin and chest wall (CW) due to the electron return effect (ERE) and areas such as armpit and chin due to the electron stream effect (ESE). Clinically, bolus has been used to protect and prevent unwanted dose in these areas. Overall treatment for APBI on the MR-linac is feasible.

An abdominal phantom with anthropomorphic organ motion and multimodal imaging contrast for MR-guided radiotherapy

Purpose. Improvements in image-guided radiotherapy (IGRT) enable accurate and precise treatment of moving tumors in the abdomen while simultaneously sparing healthy tissue. However, the lack of validation tools for newly developed MR-guided radiotherapy hybrid devices such as the MR-Linac is an open issue. This study presents a custom developed abdominal phantom with respiratory organ motion and multimodal imaging contrast to perform end-to-end tests for IGRT treatment planning scenarios.Methods. The abdominal phantom contains deformable and anatomically shaped liver and kidney models made of Ni-DTPA and KCl-doped agarose mixtures that can be reproducibly positioned within the phantom. Organ models are wrapped in foil to avoid ion exchange with the surrounding agarose and to provide stable T1 and T2 relaxation times as well as HU numbers. Breathing motion is realized by a diaphragm connected to an actuator that is hydraulically controlled via a programmable logic controller. With this system, artificial and patient-specific breathing patterns can be carried out. In 1.5 T magnetic resonance imaging (MRI), diaphragm, liver and kidney motion was measured and compared to the breathing motion of a healthy male volunteer for different breathing amplitudes including shallow, normal and deep breathing.Results. The constructed abdominal phantom demonstrated organ-equivalent intensity values in CT as well as in MRI. T1-weighted (T1w) and T2-weighted (T2w) relaxation times for 1.5 T and CT numbers were 552.9 ms, 48.2 ms and 48.8 HU (liver) as well as 950.42 ms, 79 ms and 28.2 HU (kidney), respectively. These values were stable for more than six months. Extracted breathing motion from a healthy volunteer revealed a liver to diaphragm motion ratio (LDMR) of 64.4% and a kidney to diaphragm motion ratio (KDMR) of 30.7%. Well-comparable values were obtained for the phantom (LDMR: 65.5%, KDMR: 27.5%).Conclusions. The abdominal phantom demonstrated anthropomorphic T1 and T2 relaxation times as well as HU numbers and physiological motion pattern in MRI and CT. This allows for wide use in the validation of IGRT including MRgRT.

A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer

Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.

Radiation therapy for prostate cancer: What's the best in 2021

Radiotherapy is highly involved in the management of prostate cancer. Its features and potential applications experienced a radical evolution over last decades, as they are associated to the continuous evolution of available technology and current oncological innovations. Some application of radiotherapy like brachytherapy have been recently enriched by innovative features and multidisciplinary dedications. In this report we aim to put some questions regarding the following issues regarding multiple aspects of modern application of radiation oncology: the current application of radiation oncology; the modern role of stereotactic body radiotherapy (SBRT) for both the management of primary lesions and for lymph-nodal recurrence; the management of the oligometastatic presentations; the role of brachytherapy; the aid played by the application of the organ at risk spacer (spacer OAR), fiducial markers, electromagnetic tracking systems and on-line Magnetic Resonance guided radiotherapy (MRgRT), and the role of the new opportunity represented by radiomic analysis.

Technical Note: Toward implementation of MR-guided radiation therapy for Laryngeal cancer with healthy volunteer imaging and a custom MR-CT larynx phantom

PURPOSE

Internal motion of the larynx can cause normal tissue toxicity and/or tumor underdosage during radiotherapy. MR-guided radiation therapy (MRgRT) provides improved soft-tissue contrast for patient setup, and real-time gating of radiation based on cine imaging of tumor motion, potentially making it an advantageous modality for laryngeal treatments. However, there are potential concerns regarding the small target size, proximity to heterogeneous tissue interfaces in the airway that may cause dosimetric errors in the presence of the magnetic field, and uncertainty about the ability of MR-linear accelerator (MR-Linac) systems to visualize and track laryngeal motion. To date, there have been no reports of the use of MRgRT for laryngeal treatments.

METHODS

A healthy volunteer was imaged on a ViewRay MRIdian MR-Linac. Organs-at-risk and a laryngeal pseudo target were contoured and used to generate a stereotactic body radiotherapy plan. A custom phantom was created using 3D-printing based on structures delineated on the volunteer images to construct an enclosure containing the target and airway anatomy, with a gap for radiochromic film, and filled with gelatin . The treatment plan was mapped onto the phantom and delivered dose assessed on radiochromic film with global normalization and a 10% dose threshold. A cine MR of the volunteer was acquired to assess the magnitude of larynx motion with speaking and swallowing, and system's ability to gate radiation.

RESULTS

A clinically acceptable laryngeal treatment plan and larynx phantom that was MR and CT-visible were successfully created. The delivered dose had good agreement with the treatment plan with a gamma passing rate of 96.5% (3%/2mm). The MR-Linac was able to visualize, track, and gate larynx motion.

CONCLUSIONS

The MRgRT workflow for laryngeal treatments was assessed and performed in preparation for clinical implementation on the MR-Linac, demonstrating that it is feasible to treat laryngeal cancer patients on the MR-Linac. This article is protected by copyright. All rights reserved.

Role of radiotherapy in the management of bladder cancer: Recommendations of the French society for radiation oncology

We present the recommendations of the French society of oncological radiotherapy on the indications and techniques for external beam radiotherapy for bladder cancer.

Comparison of Library of Plans with two daily adaptive strategies for whole bladder radiotherapy

Background and purpose

Whole bladder radiotherapy is challenging due to inter- and intrafraction size and shape changes. To account for these changes, currently a Library of Plans (LoP) technique is often applied, but daily adaptive radiotherapy is also increasingly becoming available. The aim of this study was to compare LoP with two magnetic resonance imaging guided radiotherapy (MRgRT) strategies by comparing target coverage and volume of healthy tissue inside the planning target volume (PTV) for whole bladder treatments.

Methods and materials

Data from 25 MRgRT lymph node oligometastases treatments (125 fractions) were used, with three MRI scans acquired at each fraction at 0, 15 and 30 min. Bladders were delineated and used to evaluate three strategies: 1) LoP with two plans for a 15 min fraction, 2) MRgRT_15min for a 15 min fraction and 3) MRgRT_30min for a 30 min fraction. The volumes of healthy tissue inside and bladder outside the PTV were analyzed on the simulated post-treatment images.

Results

MRgRT_30min had 120% and 121% more healthy tissue inside the PTV than LoP and MRgRT_15min. For LoP slightly more target outside the PTV was found than for MRgRT_30min and MRgRT_15min, with median 0% (range 0-23%) compared to 0% (0-20%) and 0% (0-10%), respectively.

Conclusions

Taking into account both target coverage and volume of healthy tissue inside the PTV, MRgRT_15min performed better than LoP and MRgRT_30min for whole bladder treatments. A 15 min daily adaptive radiotherapy workflow is needed to potentially benefit from replanning compared to LoP.

Prone vs. supine accelerated partial breast irradiation on an MR-Linac: A planning study

BACKGROUND AND PURPOSE

Accelerated partial breast irradiation (APBI) may benefit from the MR-Linac for target definition, patient setup, and motion monitoring. In this planning study, we investigated whether prone or supine position is dosimetrically beneficial for APBI on an MR-Linac and we evaluated patient comfort.

MATERIALS AND METHODS

Twenty-patients (9 postoperative, 11 preoperative) with a DCIS or breast tumor <3 cm underwent 1.5 T MRI in prone and supine position. The tumor or tumor bed was delineated as GTV and a 2 cm CTV-margin and 0.5 cm PTV-margin were added. 1.5 T MR-Linac treatment plans (5 × 5.2 Gy) with 11 beams were created for both positions in each patient. We evaluated the number of plans that achieved the planning constraints and performed a dosimetric comparison between prone and supine position using the Wilcoxon signed-rank test (p-value <0.01 for significance). Patient experience during scanning was evaluated with a questionnaire.

RESULTS

All 40 plans met the target coverage and OAR constraints, regardless of position. Heart D_mean was not significantly different (1.07 vs. 0.79 Gy, p-value: 0.027). V5Gy to the ipsilateral lung (4.4% vs. 9.8% median, p-value 0.009) and estimated delivery time (362 vs. 392 s, p-value: 0.003) were significantly lower for prone position. PTV coverage and dose to other OAR were comparable between positions. The majority of patients (13/20) preferred supine position.

CONCLUSION

APBI on the MR-Linac is dosimetrically feasible in prone and supine position. Mean heart dose was similar in both positions. Ipsilateral lung V5Gy was lower in prone position.

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.