MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.

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.

Glioblastoma (GBM) has a poor survival rate even with aggressive surgery, concomitant radiation therapy (RT), and adjuvant chemotherapy. Standard-of-care RT involves irradiating a lower dose to the hyperintense lesion in T2-weighted fluid-attenuated inversion recovery MRI (T2w/FLAIR) and a higher dose to the enhancing tumor on contrast-enhanced, T1-weighted MRI (CE-T1w). While there have been several attempts to segment pre-surgical brain tumors, there have been minimal efforts to segment post-surgical tumors, which are complicated by a resection cavity and postoperative blood products, and tools are needed to assist physicians in generating treatment contours and assessing treated patients on follow up. This report is one of the first to train and test multiple deep learning models for the purpose of post-surgical brain tumor segmentation for RT planning and longitudinal tracking. Post-surgical FLAIR and CE-T1w MRIs, as well as their corresponding RT targets (GTV1 and GTV2, respectively) from 225 GBM patients treated with standard RT were trained on multiple deep learning models including: Unet, ResUnet, Swin-Unet, 3D Unet, and Swin-UNETR. These models were tested on an independent dataset of 30 GBM patients with the Dice metric used to evaluate segmentation accuracy. Finally, the best-performing segmentation model was integrated into our longitudinal tracking web application to assign automated structured reporting scores using change in percent cutoffs of lesion volume. The 3D Unet was our best-performing model with mean Dice scores of 0.72 for GTV1 and 0.73 for GTV2 with a standard deviation of 0.17 for both in the test dataset. We have successfully developed a lightweight post-surgical segmentation model for RT planning and longitudinal tracking.

Objective: To determine the toxicity reduction required to justify the added costs of MRI-guided radiotherapy (MR-IGRT) over CT-based image guided radiotherapy (CT-IGRT) for the treatment of localized prostate cancer. Methods: The costs of delivering prostate cancer radiotherapy with MR-IGRT and CT-IGRT in conventional 39 fractions and stereotactic body radiotherapy (SBRT) 5 fractions schedules were determined using literature values and cost accounting from two institutions. Gastrointestinal and genitourinary toxicity rates associated with CT-IGRT were summarized from 20 studies. Toxicity-related costs and utilities were obtained from literature values and cost databases. Markov modeling was used to determine the savings per patient for every 1% relative reduction in acute and chronic toxicities by MR-IGRT over 15 years. The costs and quality adjusted life years (QALYs) saved with toxicity reduction were juxtaposed with the cost increase of MR-IGRT to determine toxicity reduction thresholds for cost-effectiveness. One way sensitivity analyses were performed. Standard $100,000 and $50,000 per QALY ratios were used. Results: The added cost of MR-IGRT was $1,459 per course of SBRT and $10,129 per course of conventionally fractionated radiotherapy. Relative toxicity reductions of 7 and 14% are required for SBRT to be cost-effective using $100,000 and $50,000 per QALY, respectively. Conventional radiotherapy requires relative toxicity reductions of 50 and 94% to be cost-effective. Conclusion: From a healthcare perspective, MR-IGRT can reasonably be expected to be cost-effective. Hypofractionated schedules, such a five fraction SBRT, are most likely to be cost-effective as they require only slight reductions in toxicity (7–14%). Advances in knowledge: This is the first detailed economic assessment of MR-IGRT, and it suggests that MR-IGRT can be cost-effective for prostate cancer treatment through toxicity reduction alone.

Vestibular schwannomas (VS) are benign tumors arising from cranial nerve VIII that account for 8–10% of all intracranial tumors and are the most common tumors of the cerebellopontine angle. These tumors are typically managed with observation, radiation therapy, or microsurgical resection. Of the VS that are irradiated, there is a subset of tumors that are radioresistant and continue to grow; the mechanisms behind this phenomenon are not fully understood. In this review, the authors summarize how radiation causes cellular and DNA injury that can activate (1) checkpoints in the cell cycle to initiate cell cycle arrest and DNA repair and (2) key events that lead to cell death. In addition, we discuss the current knowledge of VS radiobiology and how it may contribute to clinical outcomes. A better understanding of VS radiobiology can help optimize existing treatment protocols and lead to new therapies to overcome radioresistance.