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.

Background: The use of stereotactic body radiation therapy (SBRT) is widely utilized for treatment of localized prostate cancer. Magnetic-resonance-guided radiotherapy (MRgRT) was introduced in 2014 and has recently been implemented in SBRT for prostate cancer as it provides an opportunity for smaller margins and adaptive daily planning. Currently, the only publications of MRgRT for prostate SBRT describe European clinical experiences which utilized adaptive planning. However, adaptive planning adds significantly to the time required for daily treatment. Objectives: Since prostate SBRT has demonstrated acceptable toxicity for several years, we did not consider daily adaptation critical to the process of prostate SBRT. After Institutional Review Board approval, we analyzed and now report our experience using MRgRT without adaptation. Methods: Between 25 September 2019 and 21 December 2020, 35 consecutive patients were treated with MRgRT prostate SBRT at our center. Patients treated with MRgRT included favorable intermediate risk (43%) and unfavorable intermediate risk (54%), and only one patient had low-risk prostate cancer. Nine patients (25%) received adjuvant leuprolide for a median of 4.5 months (range 4–6 m). Our clinical pathway allows for a maximum prostate gland volume of 60 cc; median prostate volume of this cohort was 35.0 cc (range 17–58.4 cc). Median pre-treatment PSA was 6.30 (range 2.55–16.77). Each patient was treated with 36.25 Gy delivered in five fractions over 2 weeks with urethral sparing to a maximal dose of 35 Gy. Target volumes included the prostate gland and proximal seminal vesicles with a 3 mm margin. Results: Median follow-up as of 26 May 2021 was 11.97 months (range 4.37–19.80). First follow-up data are available for all patients, with a median of 1.10 month from completion of treatment (0.63–3.40). The median PSA at first visit was 2.75 (range 0.02–9.00) with a median AUA symptom score of 9 (range 1–24). Second follow-up data are available for 34 patients at a median of 4.45 months (range 2.57–8.90). At second follow-up, the median PSA was 1.60 (range 0.02–5.40) with a median AUA symptom score of 6 (range 1–33). Seventeen patients had third follow-up data with a median of 9.77 months (range 4.70–12.33) after SBRT. The median PSA was 1.13 (range 0.02–4.73) with an AUA score of 9 (2–22) at the third follow-up. We observed a statistically significant decrease in PSA between pre-treatment and at first follow-up (p < 0.005). The most common toxicity was grade 2 urethritis, managed in all cases by tamsulosin. One patient developed grade 2 tenesmus relieved by topical steroids. No cases of grade ≥ 3 toxicity were seen in our patient population. Conclusions: By avoiding the extra time required for plan adaptation, MRgRT without daily adaptation allows for successful prostate SBRT with manageable toxicity. We continue to reserve our limited adaptive treatment slots for preoperative pancreatic and ultra-central lung SBRT patients, which require time-intensive respiratory gating and adaptive planning.

Background/Objectives: Pancreatic cancer (PC) is a diagnosis with a poor prognosis which can be associated with significant distress and may hinder a patient’s ability to understand treatment details. Educating patients based on their learning preferences (LPs) and emotions may allow for personalized, enhanced care. Methods: This prospective project enrolled patients with non-metastatic PC. Phase 1 utilized the Learning Preference Barometer (LPB) and Emotional Journey Barometer (EJB), which are digital instruments co-designed by CANCER101 (C101) and the Health Collaboratory, to assess patient LPs and emotional states. Phase 2 provided information prescriptions aligned with LPs through C101’s Prescription to Learn^® (P2L) platform. Collected data included demographics, treatment, LPs (auditory, kinesthetic, linguistic, visual), patient engagement with P2L, and patient emotional states with qualitative verbal validation. Descriptive variables were used to report outcomes. Results: Primary LPs in the 47 participating patients were as follows: linguistic 45%, visual 34%, auditory 11%, and kinesthetic 9%, with secondary preferences in the majority (53%). Those patients (66%) who accessed P2L had linguistic and visual preferences; the majority accessed 1- 2 resources out of the 25 provided. Resources accessed aligned to 88% of patient LPs. The majority of patients (60%) initiated treatment prior to initial EJB, and 40% were treatment naive. Common baseline emotions were optimistic (47% vs. 36%, respectively), satisfied (11% vs. 25%), acceptance (11% vs. 11%), and overwhelmed (5% vs. 11%). Conclusions: Assessing LPs and emotional state allows for personalized patient education and clinical encounters for PC patients. Future work includes examining the effects of personalized approaches on patient satisfaction, decision-making, health outcomes, and the overall patient–clinician relationship.