MR-Guided Radiotherapy for Brain and Spine Tumors

Optimization of treatment workflow for 0.35T MR-Linac system

PURPOSE

This study presents a novel and comprehensive framework for evaluating magnetic resonance guided radiotherapy (MRgRT) workflow by integrating the Failure Modes and Effects Analysis (FMEA) approach with Time-Driven Activity-Based Costing (TDABC). We assess the workflow for safety, quality, and economic implications, providing a holistic understanding of the MRgRT implementation. The aim is to offer valuable insights to healthcare practitioners and administrators, facilitating informed decision-making regarding the 0.35T MRIdian MR-Linac system's clinical workflow.

METHODS

For FMEA, a multidisciplinary team followed the TG-100 methodology to assess the MRgRT workflow's potential failure modes. Following the mitigation of primary failure modes and workflow optimization, a treatment process was established for TDABC analysis. The TDABC was applied to both MRgRT and computed tomography guided RT (CTgRT) for typical five-fraction stereotactic body RT (SBRT) treatments, assessing total workflow and costs associated between the two treatment workflows.

RESULTS

A total of 279 failure modes were identified, with 31 categorized as high-risk, 55 as medium-risk, and the rest as low-risk. The top 20% risk priority numbers (RPN) were determined for each radiation oncology care team member. Total MRgRT and CTgRT costs were assessed. Implementing technological advancements, such as real-time multi leaf collimator (MLC) tracking with volumetric modulated arc therapy (VMAT), auto-segmentation, and increasing the Linac dose rate, led to significant cost savings for MRgRT.

CONCLUSION

In this study, we integrated FMEA with TDABC to comprehensively evaluate the workflow and the associated costs of MRgRT compared to conventional CTgRT for five-fraction SBRT treatments. FMEA analysis identified critical failure modes, offering insights to enhance patient safety. TDABC analysis revealed that while MRgRT provides unique advantages, it may involve higher costs. Our findings underscore the importance of exploring cost-effective strategies and key technological advancements to ensure the widespread adoption and financial sustainability of MRgRT in clinical practice.

Validation of daily 0.35 T diffusion-weighted MRI for MRI-guided glioblastoma radiotherapy

BACKGROUND

MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment.

PURPOSE

Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared with turbo spin echo (TSE)-DWI scans at 0.35 Tesla (T) and compared the apparent diffusion coefficient (ADC) values and distortion of EPI-DWI on 0.35 T MRI-Linac compared to high-field diagnostic MRI scanners.

METHODS

The calibrated National Institute of Standards and Technology (NIST)/Quantitative Imaging Biomarkers Alliance (QIBA) Diffusion Phantom was scanned on a 0.35 T MRI-Linac, and 1.5 T and 3 T MRI with EPI-DWI. Five patients were scanned on a 0.35 T MRI-Linac with a TSE-DWI sequence, and five other patients were scanned with EPI-DWI on a 0.35 T MRI-Linac and a 3 T MRI. The quality of images was compared between the TSE-DWI and EPI-DWI on the 0.35 T MRI-Linac assessing signal-to-noise ratios and presence of artifacts. EPI-DWI ADC values and distortion magnitude were measured and compared between 0.35 T MRI-Linac and high-field MRI for both phantom and patient studies.

RESULTS

The average ADC differences between EPI-DWI acquired on the 0.35 T MRI-Linac, 1.5 T and 3 T MRI scanners and published references in the phantom study were 1.7%, 0.4% and 1.0%, respectively. Comparing the ADC values based on EPI-DWI in glioblastoma tumors, there was a 3.36% difference between 0.35 and 3 T measurements. Susceptibility-induced distortions in the EPI-DWI phantoms were 0.46 ± 1.51 mm for 0.35 MRI-Linac, 0.98 ± 0.51 mm for 1.5 T MRI and 1.14 ± 1.88 mm for 3 T MRI; for patients -0.47 ± 0.78 mm for 0.35 T and 1.73 ± 2.11 mm for 3 T MRIs. The mean deformable registration distortion for a phantom was 1.1 ± 0.22 mm, 3.5 ± 0.39 mm and 4.7 ± 0.37 mm for the 0.35 T MRI-Linac, 1.5 T MRI, and 3 T MRI scanners, respectively; for patients this distortion was -0.46 ± 0.57 mm for 0.35 T and 4.2 ± 0.41 mm for 3 T. EPI-DWI 0.35 T MRI-Linac images showed higher SNR and lack of artifacts compared with TSE-DWI, especially at higher b-values up to 1000 s/mm2.

CONCLUSION

EPI-DWI on a 0.35 T MRI-Linac showed superior image quality compared with TSE-DWI, minor and less distortions than high-field diagnostic scanners, and comparable ADC values in phantoms and glioblastoma tumors. EPI-DWI should be investigated on the 0.35 T MRI-Linac for prediction of early response in patients with glioblastoma.

Validation of echo planar imaging based diffusion-weighted magnetic resonance imaging on a 0.35 T MR-Linac

Background and Purpose

The feasibility of acquiring diffusion-weighted imaging (DWI) images on an MR-Linac for quantitative response assessment during radiotherapy was explored. DWI data obtained with a Spin Echo Echo Planar Imaging sequence adapted for a 0.35 T MR-Linac were examined and compared with DWI data from a conventional 3 T scanner.

Materials and Methods

Apparent diffusion coefficient (ADC) measurements and a distortion correction technique were investigated using DWI-calibrated phantoms and in the brains of seven volunteers. All DWI utilized two phase-encoding directions for distortion correction and off-resonance field estimation. ADC maps in the brain were analyzed for automatically segmented normal tissues.

Results

Phantom ADC measurements on the MR-Linac were within a 3 % margin of those recorded by the 3 T scanner. The maximum distortion observed in the phantom was 2.0 mm prior to correction and 1.1 mm post-correction on the MR-Linac, compared to 6.0 mm before correction and 3.6 mm after correction at 3 T. In vivo, the average ADC values for gray and white matter exhibited variations of 14 % and 4 %, respectively, for different selections of b-values on the MR-Linac. Distortions in brain images before correction, estimated through the off-resonance field, reached 2.7 mm on the MR-Linac and 12 mm at 3 T.

Conclusion

Accurate ADC measurements are achievable on a 0.35 T MR-Linac, both in phantom and in vivo. The selection of b-values significantly influences ADC values in vivo. DWI on the MR-Linac demonstrated lower distortion levels, with a maximum distortion reduced to 1.1 mm after correction.

Implementation and evaluation of a dynamic contrast-enhanced MR perfusion protocol for glioblastoma using a 0.35 T MRI-Linac system

PURPOSE

MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35 T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3D-T1w) and dynamic contrast-enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35 T MRI-Linac.

METHODS AND MATERIALS

The protocol implemented was used to acquire 3D-T1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0.35 T MRI-Linac. The detection of post-contrast-enhanced volumes was evaluated by comparing the 3DT1w images from the 0.35 T MRI-Linac to images obtained using a 3 T scanner. The DCE data were tested temporally and spatially using data from a flow phantom and patients. Ktrans maps were derived from DCE at three time points (a week before treatment-Pre RT, four weeks through treatment-Mid RT, and three weeks after treatment-Post RT) and were validated with patients' treatment outcomes.

RESULTS

The 3D-T1w contrast-enhancement volumes were visually and volumetrically similar between 0.35 T MRI-Linac and 3 T. DCE images showed temporal stability, and associated Ktrans maps were consistent with patient response to treatment. On average, Ktrans values showed a 54 % decrease and 8.6 % increase for a responder and non-responder respectively when Pre RT and Mid RT images were compared.

CONCLUSION

Our findings support the feasibility of obtaining post-contrast 3D-T1w and DCE data from patients with glioblastoma using a 0.35 T MRI-Linac system.

Dose Calculation Accuracy of Beam Models in RadCalc for a 1.5 T MR-Linac

The purpose of this study is to evaluate RadCalc, an independent dose verification software, for patient-specific quality assurance (PSQA) in online adaptive planning with a magnetic resonance linear accelerator (MR-linac) of a 1.5 T. Version 7.1.4 of RadCalc to introduce the capability to establish a beam model that incorporates MR field characteristics. A total of six models were established, with one using manufacturer-provided data and the others differing in percentage depth dose (PDD) data sources. Overall, two models utilized PDD data from the treatment planning system (TPS), and three used commissioned PDD data from gantry angles of 0° and 270°. Simple tests on a virtual water phantom assessed dose-calculation accuracy, revealing percentage differences ranging from -0.5% to -20.6%. Excluding models with significant differences, clinical tests on 575 adaptive plans (prostate, liver, and breast) showed percentage differences of -0.51%, 1.12%, and 4.10%, respectively. The doses calculated using RadCalc demonstrated similar trends to those of the PSQA-based measurements. The newly released version of RadCalc enables beam modeling that considers the characteristics of the 1.5 T magnetic field. The accuracy of the software in calculating doses at 1.5 T magnetic fields has been verified, thereby making it a reliable and effective tool for PSQA in adaptive plans.

Dosimetric comparison of glioblastoma radiotherapy treatment plans on a low-field MRI-guided linear accelerator compared to conventional C-arm linear accelerator

INTRODUCTION

Magnetic resonance imaging (MRI)-guided radiation therapy has proven to provide many benefits such as real-time tracking, dose escalation, and the ability to perform online adaptive therapy. The objective of this study is to compare curative treatment plans for glioblastoma tumors on a low-field MR-guided linac vs a C-arm linac and evaluate if they are comparable in terms of coverage, organ at risk sparing, delivery time, and deliverability.

METHODS

This is a retrospective study that consisted of 15 previously treated patients who received radiation therapy for glioblastoma on a C-arm linac. The CT simulation data used for the original clinical plans was imported into the MR-linac treatment planning system (TPS) and utilized for MR-linac plan generation. The plans were evaluated utilizing the dose volumetric histogram (DVH) and isodose lines, then compared in terms of plan quality consisting of PTV coverage, dose distributions, and OAR constraints. Statistical analysis was performed to compare differences between the two planning techniques. QA was performed on a subset of the plans to verify deliverability.

RESULTS

Plans generated on the MR-linac were more heterogenous compared to C-arm linac plans. A statistically significant difference was found in the homogeneity index (HI) and the PTV V105% volume (cc) values. The volume of the normal brain receiving 30 Gy also showed a statistically significant (p = 0.0479) difference, where on average an additional 41.5 cc's of the normal brain tissue received 30 Gy in the MR-linac plans. The maximum dose to the normal brain structure also increased in the MR-linac plans on average by 2.6 Gy (p = 0.0002). Similarly, the average maximum dose to the scalp 4 mm structure was 6.5 Gy higher in the MR-linac plans compared to C-arm linac plans (p = 0.0103). The total MU's were higher in the MR-linac plans compared to the C-arm linac plans (p = 0.0015).

CONCLUSIONS

Both MR-linac and C-arm linac plans met constraints for PTV coverage and OAR sparing, were deliverable, and resulted to be clinically acceptable. However, our study showed that MR-linac plans were not as conformal or as homogenous as C-arm linac plans utilizing noncoplanar beams.

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.

An improved F98 glioblastoma rat model to evaluate novel treatment strategies incorporating the standard of care

Glioblastoma (GB) is the most common and malignant primary brain tumor in adults with a median survival of 12-15 months. The F98 Fischer rat model is one of the most frequently used animal models for GB studies. However, suboptimal inoculation leads to extra-axial and extracranial tumor formations, affecting its translational value. We aim to improve the F98 rat model by incorporating MRI-guided (hypo)fractionated radiotherapy (3 x 9 Gy) and concomitant temozolomide chemotherapy, mimicking the current standard of care. To minimize undesired tumor growth, we reduced the number of inoculated cells (starting from 20 000 to 500 F98 cells), slowed the withdrawal of the syringe post-inoculation, and irradiated the inoculation track separately. Our results reveal that reducing the number of F98 GB cells correlates with a diminished risk of extra-axial and extracranial tumor growth. However, this introduces higher variability in days until GB confirmation and uniformity in GB growth. To strike a balance, the model inoculated with 5000 F98 cells displayed the best results and was chosen as the most favorable. In conclusion, our improved model offers enhanced translational potential, paving the way for more accurate and reliable assessments of novel adjuvant therapeutic approaches for GB.

MRI-Guided Adaptive Radiation Therapy

Magnetic resonance imaging-guided radiation therapy (MRIgRT) has improved soft tissue contrast over computed tomography (CT) based image-guided RT. Superior visualization of the target and surrounding radiosensitive structures has the potential to improve oncological outcomes partly due to safer dose-escalation and adaptive planning. In this review, we highlight the workflow of adaptive MRIgRT planning, which includes simulation imaging, daily MRI, identifying isocenter shifts, contouring, plan optimization, quality control, and delivery. Increased utilization of MRIgRT will depend on addressing technical limitations of this technology, while addressing treatment efficacy, cost-effectiveness, and workflow training.

Anatomical changes in resection cavity during brain radiotherapy

BACKGROUND AND PURPOSE

Brain tumors are in general treated with a maximal safe resection followed by radiotherapy of remaining tumor including the resection cavity (RC) and chemotherapy. Anatomical changes of the RC during radiotherapy can have impact on the coverage of the target volume. The aim of the current study was to quantify the potential changes of the RC and to identify risk factors for RC changes.

MATERIALS AND METHODS

Sixteen patients treated with pencil beam scanning proton therapy between October 2019 and April 2020 were retrospectively analyzed. The RC was delineated on pre-treatment computed tomography (CT) and magnetic resonance imaging, and weekly CT-scans during treatment. Isotropic expansions were applied to the pre-treatment RC (1-5 mm). The percentage of volume of the RC during treatment within the expanded pre-treatment volumes was quantified. Potential risk factors (volume of RC, time interval surgery-radiotherapy and relationship of RC to the ventricles) were evaluated using Spearman's rank correlation coefficient.

RESULTS

The average variation in relative RC volume during treatment was 26.1% (SD 34.6%). An expansion of 4 mm was required to cover > 95% of the RC volume in > 90% of patients. There was a significant relationship between the absolute volume of the pre-treatment RC and the volume changes during treatment (Spearman's ρ = - 0.644; p = 0.007).

CONCLUSION

RCs are dynamic after surgery. Potentially, an additional margin in brain cancer patients with an RC should be considered, to avoid insufficient target coverage. Future research on local recurrence patterns is recommended.

A Deep Learning Approach for Automatic Segmentation during Daily MRI-Linac Radiotherapy of Glioblastoma

Glioblastoma changes during chemoradiotherapy are inferred from high-field MRI before and after treatment but are rarely investigated during radiotherapy. The purpose of this study was to develop a deep learning network to automatically segment glioblastoma tumors on daily treatment set-up scans from the first glioblastoma patients treated on MRI-linac. Glioblastoma patients were prospectively imaged daily during chemoradiotherapy on 0.35T MRI-linac. Tumor and edema (tumor lesion) and resection cavity kinetics throughout the treatment were manually segmented on these daily MRI. Utilizing a convolutional neural network, an automatic segmentation deep learning network was built. A nine-fold cross-validation schema was used to train the network using 80:10:10 for training, validation, and testing. Thirty-six glioblastoma patients were imaged pre-treatment and 30 times during radiotherapy (n = 31 volumes, total of 930 MRIs). The average tumor lesion and resection cavity volumes were 94.56 ± 64.68 cc and 72.44 ± 35.08 cc, respectively. The average Dice similarity coefficient between manual and auto-segmentation for tumor lesion and resection cavity across all patients was 0.67 and 0.84, respectively. This is the first brain lesion segmentation network developed for MRI-linac. The network performed comparably to the only other published network for auto-segmentation of post-operative glioblastoma lesions. Segmented volumes can be utilized for adaptive radiotherapy and propagated across multiple MRI contrasts to create a prognostic model for glioblastoma based on multiparametric MRI.

Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Clinical Applications of Magnetic Resonance-Guided Radiotherapy: A Narrative Review

Magnetic resonance-guided radiotherapy (MRgRT) represents a promising new image guidance technology for radiation treatment delivery combining an onboard MRI scanner with radiation delivery technology. By enabling real-time low-field or high-field MRI acquisition, it facilitates improved soft tissue delineation, adaptive treatment, and motion management. Now that MRgRT has been available for nearly a decade, research has shown the technology can be used to effectively shrink treatment margins to either decrease toxicity (in breast, prostate cancer, and pancreatic cancer) or facilitate dose-escalation and improved oncologic outcomes (in pancreatic and liver cancer), as well as enabling indications that require clear soft tissue delineation and gating (lung and cardiac ablation). In doing so, the use of MRgRT has the potential to significantly improve the outcomes and quality of life of the patients it treats. The present narrative review aims to describe the rationale for MRgRT, the current and forthcoming state of technology, existing studies, and future directions for the advancement of MRgRT, including associated challenges.

An exploratory analysis of MR-guided fractionated stereotactic radiotherapy in patients with brain metastases

Purpose

To assess the feasibility and potential benefits of online adaptive MR-guided fractionated stereotatic radiotherapy (FSRT) in patients with brain metastases (BMs).

Methods and materials

Twenty-eight consecutive patients with BMs were treated with FSRT of 30 Gy in 5 fractions on the 1.5 T MR-Linac. The FSRT fractions employed daily MR scans and the contours were utilized to create each adapted plan. The brain lesions and perilesional edema were delineated on MR images of pre-treatment simulation (Fx0) and all fractions (Fx1, Fx2, Fx3, Fx4 and Fx5) to evaluate the inter-fractional changes. These changes were quantified using absolute/relative volume, Dice similarity coefficient (DSC) and Hausdorff distance (HD) metrics. Planning target volume (PTV) coverage and organ at risk (OAR) constraints were used to compare non-adaptive and adaptive plans.

Results

A total of 28 patients with 88 lesions were evaluated, and 23 patients (23/28, 82.1%) had primary lung adenocarcinoma. Significant tumor volume reduction had been found during FSRT compared to Fx0 for all 88 lesions (median -0.75%, -5.33%, -9.32%, -17.96% and -27.73% at Fx1, Fx2, Fx3, Fx4 and Fx5, p < 0.05). There were 47 (47/88, 53.4%) lesions being accompanied by perilesional edema and the inter-fractional changes were significantly different compared to those without perilesional edema (p < 0.001). Patients with multiple lesions (13/28, 46.4%) had more significant inter-fractional tumor changes than those with single lesion (15/28, 53.6%), including tumor volume reduction and anatomical shift (p < 0.001). PTV coverage of non-adaptive plans was below the prescribed coverage in 26/140 fractions (19%), with 12 (9%) failing by more than 10%. All 140 adaptive fractions met prescribed target coverage. The adaptive plans also had lower dose to whole brain than non-adaptive plans (p < 0.001).

Conclusions

Significant inter-fractional tumor changes could be found during FSRT in patients with BMs treated on the 1.5 T MR-Linac. Daily MR-guided re-optimization of treatment plans showed dosimetric benefit in patients with perilesional edema or multiple lesions.

Stereotactic Magnetic Resonance-Guided Adaptive and Non-Adaptive Radiotherapy on Combination MR-Linear Accelerators: Current Practice and Future Directions

Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care.

Simulated Adaptive Radiotherapy for Shrinking Glioblastoma Resection Cavities on a Hybrid MRI-Linear Accelerator

During radiation therapy (RT) of glioblastoma, daily MRI with combination MRI-linear accelerator (MRI-Linac) systems has demonstrated significant anatomic changes, including evolving post-surgical cavity shrinkage. Cognitive function RT for brain tumors is correlated with radiation doses to healthy brain structures, especially the hippocampi. Therefore, this study investigates whether adaptive planning to the shrinking target could reduce normal brain RT dose with the goal of improving post-RT function. We evaluated 10 glioblastoma patients previously treated on a 0.35T MRI-Linac with a prescription of 60 Gy delivered in 30 fractions over six weeks without adaptation ("static plan") with concurrent temozolomide chemotherapy. Six weekly plans were created per patient. Reductions in the radiation dose to uninvolved hippocampi (maximum and mean) and brain (mean) were observed for weekly adaptive plans. The dose (Gy) to the hippocampi for static vs. weekly adaptive plans were, respectively: max 21 ± 13.7 vs. 15.2 ± 8.2 (p = 0.003) and mean 12.5 ± 6.7 vs. 8.4 ± 4.0 (p = 0.036). The mean brain dose was 20.6 ± 6.0 for static planning vs. 18.7 ± 6.8 for weekly adaptive planning (p = 0.005). Weekly adaptive re-planning has the potential to spare the brain and hippocampi from high-dose radiation, possibly reducing the neurocognitive side effects of RT for eligible patients.

Neural Network in the Analysis of the MR Signal as an Image Segmentation Tool for the Determination of T1 and T2 Relaxation Times with Application to Cancer Cell Culture

Artificial intelligence has been entering medical research. Today, manufacturers of diagnostic instruments are including algorithms based on neural networks. Neural networks are quickly entering all branches of medical research and beyond. Analyzing the PubMed database from the last 5 years (2017 to 2021), we see that the number of responses to the query "neural network in medicine" exceeds 10,500 papers. Deep learning algorithms are of particular importance in oncology. This paper presents the use of neural networks to analyze the magnetic resonance imaging (MRI) images used to determine MRI relaxometry of the samples. Relaxometry is becoming an increasingly common tool in diagnostics. The aim of this work was to optimize the processing time of DICOM images by using a neural network implemented in the MATLAB package by The MathWorks with the patternnet function. The application of a neural network helps to eliminate spaces in which there are no objects with characteristics matching the phenomenon of longitudinal or transverse MRI relaxation. The result of this work is the elimination of aerated spaces in MRI images. The whole algorithm was implemented as an application in the MATLAB package.

Adoption of Hybrid MRI-Linac Systems for the Treatment of Brain Tumors: A Systematic Review of the Current Literature Regarding Clinical and Technical Features

BACKGROUND

Possible advantages of magnetic resonance (MR)-guided radiation therapy (MRgRT) for the treatment of brain tumors include improved definition of treatment volumes and organs at risk (OARs) that could allow margin reductions, resulting in limited dose to the OARs and/or dose escalation to target volumes. Recently, hybrid systems integrating a linear accelerator and an magnetic resonance imaging (MRI) scan (MRI-linacs, MRL) have been introduced, that could potentially lead to a fully MRI-based treatment workflow.

METHODS

We performed a systematic review of the published literature regarding the adoption of MRL for the treatment of primary or secondary brain tumors (last update November 3, 2022), retrieving a total of 2487 records; after a selection based on title and abstracts, the full text of 74 articles was analyzed, finally resulting in the 52 papers included in this review.

RESULTS AND DISCUSSION

Several solutions have been implemented to achieve a paradigm shift from CT-based radiotherapy to MRgRT, such as the management of geometric integrity and the definition of synthetic CT models that estimate electron density. Multiple sequences have been optimized to acquire images with adequate quality with on-board MR scanner in limited times. Various sophisticated algorithms have been developed to compensate the impact of magnetic field on dose distribution and calculate daily adaptive plans in a few minutes with satisfactory dosimetric parameters for the treatment of primary brain tumors and cerebral metastases. Dosimetric studies and preliminary clinical experiences demonstrated the feasibility of treating brain lesions with MRL.

CONCLUSIONS

The adoption of an MRI-only workflow is feasible and could offer several advantages for the treatment of brain tumors, including superior image quality for lesions and OARs and the possibility to adapt the treatment plan on the basis of daily MRI. The growing body of clinical data will clarify the potential benefit in terms of toxicity and response to treatment.

Imaging of GBM in the Age of Molecular Markers and MRI Guided Adaptive Radiation Therapy

Glioblastoma (GBM) continues to be one of the most lethal malignancies and is almost always fatal. In this review article, the role of radiation therapy, systemic therapy, as well as the molecular basis of classifying GBM is described. Technological advances in the treatment of GBM are outlined as well as the diagnostic imaging characteristics of this tumor. In addition, factors that affect prognosis such as differentiating progression from treatment effect is discussed. The role of MRI guided radiation therapy and how this technology may provide a mechanism to improve the care of patients with this disease are described.

MRI-guided Radiotherapy (MRgRT) for treatment of Oligometastases: Review of clinical applications and challenges

PURPOSE

Early clinical results on the application of magnetic resonance imaging (MRI) coupled with a linear accelerator to deliver MR-guided radiation therapy (MRgRT) have demonstrated feasibility for safe delivery of stereotactic body radiotherapy (SBRT) in treatment of oligometastatic disease. Here we set out to review the clinical evidence and challenges associated with MRgRT in this setting.

METHODS AND MATERIALS

We performed a systematic review of the literature pertaining to clinical experiences and trials on the use of MRgRT primarily for the treatment of oligometastatic cancers. We reviewed the opportunities and challenges associated with the use of MRgRT.

RESULTS

Benefits of MRgRT pertaining to superior soft-tissue contrast, real-time imaging and gating, and online adaptive radiotherapy facilitate safe and effective dose escalation to oligometastatic tumors while simultaneously sparing surrounding healthy tissues. Challenges concerning further need for clinical evidence and technical considerations related to planning, delivery, quality assurance (QA) of hypofractionated doses, and safety in the MRI environment must be considered.

CONCLUSIONS

The promising early indications of safety and effectiveness of MRgRT for SBRT-based treatment of oligometastatic disease in multiple treatment locations should lead to further clinical evidence to demonstrate the benefit of this technology.

Machine learning in neuro-oncology: toward novel development fields

PURPOSE

Artificial Intelligence (AI) involves several and different techniques able to elaborate a large amount of data responding to a specific planned outcome. There are several possible applications of this technology in neuro-oncology.

METHODS

We reviewed, according to PRISMA guidelines, available studies adopting AI in different fields of neuro-oncology including neuro-radiology, pathology, surgery, radiation therapy, and systemic treatments.

RESULTS

Neuro-radiology presented the major number of studies assessing AI. However, this technology is being successfully tested also in other operative settings including surgery and radiation therapy. In this context, AI shows to significantly reduce resources and costs maintaining an elevated qualitative standard. Pathological diagnosis and development of novel systemic treatments are other two fields in which AI showed promising preliminary data.

CONCLUSION

It is likely that AI will be quickly included in some aspects of daily clinical practice. Possible applications of these techniques are impressive and cover all aspects of neuro-oncology.

CT-MR Image Fusion for Post-Implant Dosimetry Analysis in Brain Tumor Seed Implantation- a Preliminary Study

Purpose

To calculate and evaluate postimplant dosimetry (PID) with CT-MR fusion technique after brain tumor brachytherapy and compare the result with CT-based PID.

Methods and Materials

16 brain tumor patients received MR-guided intervention with Iodine-125 (¹²⁵I) seed implantation entered this preliminary study for PID evaluation. Registration and fusion of CT and MR images of the same patients were performed one day after operation. Seeds identification and targets delineation were carried out on CT, MR, and CT-MR fusion images, each. The number and location of seeds on MR or CT- MR fusion images were compared with those of actually implanted seeds. Clinical target volume (CTV) and dosimetric parameters such as %D90, %V100 and external V100 were measured and calculated. In addition, the correlation of the fusion to CT CTV ratio and other factors were analyzed.

Results

The numbers of fusion seeds were not significantly different compared with reference seeds (t =1.76, p >0.05). The difference between reference seeds numbers and truly extracted MR seeds numbers was statistically significant (t =3.91, p <0.05). All dosimetric parameters showed significant differences between the two techniques (p <0.05). The mean CTV delineated on fusion images was 34.3 ± 33.6, smaller than that on CT images. The mean values of external V100, %V100 and %D90 on fusion images were larger than those on CT images. Correlation analysis showed that the fusion-CT V100 ratio was positively and significantly correlated with the fusion-CT volume ratio.

Conclusions

This preliminary study indicated that CT-MR fusion-based PID exhibited good accuracy for ¹²⁵I brain tumor brachytherapy dosimetry when compared to CT-based PID and merits further research to establish best-outcome protocols.

Dosimetric feasibility of hippocampal avoidance whole brain radiotherapy with an MRI-guided linear accelerator

Purpose/Objective(s)

Whole brain radiotherapy with hippocampal avoidance (HA‐WBRT) is a technique utilized to treat metastatic brain disease while preserving memory and neurocognitive function. We hypothesized that the treatment planning and delivery of HA‐WBRT plans is feasible with an MRI‐guided linear accelerator (linac) and compared plan results with clinical non‐MRI‐guided C‐Arm linac plans.

Materials/Methods

Twelve HA‐WBRT patients treated on a non‐MRI‐guided C‐Arm linac were selected for retrospective analysis. Treatment plans were developed using a 0.35T MRI‐guided linac system for comparison to clinical plans. Treatment planning goals were defined as provided in the Phase II Trial NRG CC001. MRI‐guided radiotherapy (MRgRT) treatment plans were developed by a dosimetrist and compared with clinical plans. quality assurance (QA) plans were generated and delivered on the MRI‐guided linac to a cylindrical diode detector array. Planning target volume (PTV) coverage was normalized to ∼95% to provide a control point for comparison of dose to the organs at risk.

Results

MRgRT plans were deliverable and met all clinical goals. Mean values demonstrated that the clinical plans were less heterogeneous than MRgRT plans with mean PTV V37.5 Gy of 0.00% and 0.03% (p = 0.013), respectively. Average hippocampi maximum doses were 14.19 ± 1.29 Gy and 15.00 ± 1.51 Gy, respectively. The gamma analysis comparing planned and measured doses resulted in a mean of 99.9% ± 0.12% of passing points (3%/2mm criteria). MRgRT plans had an average of 38.33 beams with average total delivery time and beam‐on time of 13.7 (11.2–17.5) min and 4.1 (3.2–5.4) min, respectively. Clinical plan delivery times ranged from 3 to 7 min depending on the number of noncoplanar arcs. Planning time between the clinical and MRgRT plans was comparable.

Conclusion

This study demonstrates that HA‐WBRT can be treated using an MRI‐guided linear accelerator with comparable treatment plan quality and delivery accuracy.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.