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Purpose Hypofractionated (>5 fraction) stereotactic radiation therapy (HSRT) may allow for ablative biologically equivalent dose to tumors with a lower risk of organ-at-risk (OAR) toxicity in central thoracic tumors. Adaptive planning may further improve OAR sparing while maintaining planning target volume (PTV) coverage. We hypothesized that midtreatment adaptive replanning would offer dosimetric advantages during HSRT for central thorax malignancies using magnetic resonance imaging (MRI)–guided radiation therapy. Methods and Materials Twelve patients with central thorax tumors received HSRT using MRI-guided radiation therapy. Clinically delivered regimens were 60 Gy in 12 fractions or 62.5 Gy in 10 fractions, with low-field magnetic resonance (0.35 T) volumetric setup imaging acquired at each fraction. Daily gross tumor volume (GTV) and OARs were retrospectively redefined on fraction 1, 6, and 10 MRIs, and GTV response was recorded. Simulated initial plans prescribed a dose of 60 Gy in 12 fractions based on fraction 1 MRI. Midtreatment adaptive plans were created based on fraction 6 anatomy-of-the-day. All plans were created using an isotoxicity approach with a goal of 95% PTV coverage, subject to hard OAR constraints, to represent clinically ideal OAR sparing. Plans were then compared for projected OAR sparing and PTV coverage. Results Patients demonstrated significant on-treatment MRI-defined GTV reduction (median 41.8%; range 16.7%-65.7%). At fraction 6, median reduction was 26.7%. All initial plans met OAR constraints. Initial plan application to fraction 6 and fraction 10 anatomy resulted in 8 OAR violations (5 of 13 patients) and 10 OAR violations (6 of 13 patients). All fraction 6 violations persisted at fraction 10. Midpoint adaptive planning reversed 100% of midpoint OAR violations and tended to reduce the magnitude of OAR violations incurred at fraction 10. In 40% of fractions (2 of 5) in which OAR violation resulted from initial plan application to fraction 6 anatomy, PTV coverage was increased concomitant with violation reversal. Conclusions Midtreatment adaptive planning based on tumor response may be dosimetrically advantageous for sparing of surrounding critical structures in HSRT for central thorax malignancies and could be applied using either an online or offline paradigm.

Purpose We sought to evaluate the feasibility and tolerability of a novel accelerated partial breast irradiation regimen delivered in a single fraction postoperatively. Methods and Materials We enrolled 50 patients with low-risk, hormone-sensitive breast cancer from 2015 to 2018 on a prospective phase 1/2 trial to receive single-fraction, high-gradient partial-breast irradiation (SFHGPBI) 2 to 8 weeks after lumpectomy for node-negative, invasive, or in situ breast cancer. The high gradient was achieved by prescribing 20 Gy to the surgical bed and 5 Gy to the breast tissue within 1 cm of the surgical bed simultaneously in 1 fraction using external beam. Results The median age was 65 (range, 52-84). Ten patients (20%) had small-volume ductal carcinoma in situ while the remainder had stage I disease. At a median follow-up of 25 months, we evaluated toxicity, patient- and physician-reported cosmesis, patient-reported quality of life (QOL), and initial tumor control. There was no Common Terminology Criteria for Adverse Events v4.0 grade 3+ toxicity. Only 34% of patients experienced grade 1 erythema. Good-to-excellent pretreatment cosmesis was present in 100% and 98% per physicians and patients, respectively, and did not change post-SFHGPBI. Quantitative cosmesis by percentage of breast retraction assessment significantly improved over time during the post-SFHGPBI period per mixed repeated measures modeling (P = .0026). QOL per European Organization for Research and Treatment of Cancer QOL Questionnaires C30 and BR-23 did not decline other than temporarily in the systemic therapy effects and hair loss domains, both of which returned to pretreatment values. There was 1 noninvasive in-breast recurrence in a separate untreated quadrant 18 months post-SFHGPBI and 1 isolated axillary recurrence 30 months post-SFHGPBI, both salvaged successfully. There were no distant recurrences or cancer-related deaths observed. Conclusions Accelerated partial-breast irradiation delivered in a single fraction postoperatively using external beam techniques is a novel, feasible, well-tolerated regimen. SFHGPBI does not adversely affect cosmesis or QOL as reported by both physicians and patients. Initial tumor control rates are excellent, with longer follow-up required to confirm efficacy.

Purpose To use magnetic resonance image guided radiation therapy (MR-IGRT) for accelerated partial-breast irradiation (APBI) to ( 1 ) determine intrafractional motion of the breast surgical cavity; and ( 2 ) assess delivered dose versus planned dose. Methods and Materials Thirty women with breast cancer (stages 0-I) who underwent breast-conserving surgery were enrolled in a prospective registry evaluating APBI using a 0.35-T MR-IGRT system. Clinical target volume was defined as the surgical cavity plus a 1-cm margin (excluding chest wall, pectoral muscles, and 5 mm from skin). No additional margin was added for the planning target volume (PTV). A volumetric MR image was acquired before each fraction, and patients were set up to the surgical cavity as visualized on MR imaging. To determine the delivered dose for each fraction, the electron density map and contours from the computed tomography simulation were transferred to the pretreatment MR image via rigid registration. Intrafractional motion of the surgical cavity was determined by applying a tracking algorithm to the cavity contour as visualized on cine MR. Results Median PTV volume was reduced by 52% when using no PTV margin compared with a 1-cm PTV margin used conventionally. The mean (± standard deviation) difference between planned and delivered dose to the PTV (V95) was 0.6% ± 0.1%. The mean cavity displacement in the anterior–posterior and superior–inferior directions was 0.6 ± 0.4 mm and 0.6 ± 0.3 mm, respectively. The mean margin required for at least 90% of the cavity to be contained by the margin for 90% of the time was 0.7 mm (5th-95th percentile: 0-2.7 mm). Conclusion Minimal intrafractional motion was observed, and the mean difference between planned and delivered dose was less than 1%. Assessment of efficacy and cosmesis of this MR-guided APBI approach is under way.

PURPOSE: This work describes a commercial treatment planning system, its technical features, and its capabilities for creating (60)Co intensity modulated radiation therapy (IMRT) treatment plans for a magnetic resonance image guidance radiation therapy (MR-IGRT) system. METHODS AND MATERIALS: The ViewRay treatment planning system (Oakwood Village, OH) was used to create (60)Co IMRT treatment plans for 33 cancer patients with disease in the abdominal, pelvic, thorax, and head and neck regions using physician-specified patient-specific target coverage and organ at risk (OAR) objectives. Backup plans using a third-party linear accelerator (linac)-based planning system were also created. Plans were evaluated by attending physicians and approved for treatment. The (60)Co and linac plans were compared by evaluating conformity numbers (CN) with 100% and 95% of prescription reference doses and heterogeneity indices (HI) for planning target volumes (PTVs) and maximum, mean, and dose-volume histogram (DVH) values for OARs. RESULTS: All (60)Co IMRT plans achieved PTV coverage and OAR sparing that were similar to linac plans. PTV conformity for (60)Co was within 20 Gy. The mean doses for all (60)Co plan OARs were within clinical tolerances. CONCLUSIONS: A commercial (60)Co MR-IGRT device can produce highly conformal IMRT treatment plans similar in quality to linac IMRT for a variety of disease sites. Additional work is in progress to evaluate the clinical benefit of other novel features of this MR-IGRT system.

Purpose To characterize potential advantages of online-adaptive magnetic resonance (MR)-guided stereotactic body radiation therapy (SBRT) to treat oligometastatic disease of the non-liver abdomen and central thorax. Methods and Materials Ten patients treated with RT for unresectable primary or oligometastatic disease of the non-liver abdomen (n=5) or central thorax (n=5) underwent imaging throughout treatment on a clinical MR image guided RT system. The SBRT plans were created on the basis of tumor/organ at risk (OAR) anatomy at initial computed tomography simulation (P I ), and simulated adaptive plans were created on the basis of observed MR image set tumor/OAR "anatomy of the day" (P A ). Each P A was planned under workflow constraints to simulate online-adaptive RT. Prescribed dose was 50 Gy/5 fractions, with goal coverage of 95% planning target volume (PTV) by 95% of the prescription, subject to hard OAR constraints. The P I was applied to each MR dataset and compared with P A to evaluate changes in dose delivered to tumor/OARs, with dose escalation when possible. Results Hard OAR constraints were met for all P Is based on anatomy from initial computed tomography simulation, and all P As based on anatomy from each daily MR image set. Application of the P I to anatomy of the day caused OAR constraint violation in 19 of 30 cases. Adaptive planning increased PTV coverage in 21 of 30 cases, including 14 cases in which hard OAR constraints were violated by the nonadaptive plan. For 9 P A cases, decreased PTV coverage was required to meet hard OAR constraints that would have been violated in a nonadaptive setting. Conclusions Online-adaptive MRI-guided SBRT may allow PTV dose escalation and/or simultaneous OAR sparing compared with nonadaptive SBRT. A prospective clinical trial is underway at our institution to evaluate clinical outcomes of this technique.

Purpose To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiation therapy (MR-IGRT) through reporting of our initial clinical experience and workflow considerations. Methods and Materials The first clinically deployed online adaptive MR-IGRT system consisted of a split 0.35T MR scanner straddling a ring gantry with 3 multileaf collimator-equipped 60 Co heads. The unit is supported by a Monte Carlo–based treatment planning system that allows real-time adaptive planning with the patient on the table. All patients undergo computed tomography and MR imaging (MRI) simulation for initial treatment planning. A volumetric MRI scan is acquired for each patient at the daily treatment setup. Deformable registration is performed using the planning computed tomography data set, which allows for the transfer of the initial contours and the electron density map to the daily MRI scan. The deformed electron density map is then used to recalculate the original plan on the daily MRI scan for physician evaluation. Recontouring and plan reoptimization are performed when required, and patient-specific quality assurance (QA) is performed using an independent in-house software system. Results The first online adaptive MR-IGRT treatments consisted of 5 patients with abdominopelvic malignancies. The clinical setting included neoadjuvant colorectal (n=3), unresectable gastric (n=1), and unresectable pheochromocytoma (n=1). Recontouring and reoptimization were deemed necessary for 3 of 5 patients, and the initial plan was deemed sufficient for 2 of the 5 patients. The reasons for plan adaptation included tumor progression or regression and a change in small bowel anatomy. In a subsequently expanded cohort of 170 fractions (20 patients), 52 fractions (30.6%) were reoptimized online, and 92 fractions (54.1%) were treated with an online-adapted or previously adapted plan. The median time for recontouring, reoptimization, and QA was 26 minutes. Conclusion Online adaptive MR-IGRT has been successfully implemented with planning and QA workflow suitable for routine clinical application. Clinical trials are in development to formally evaluate adaptive treatments for a variety of disease sites.

This work describes a commercial treatment planning system, its technical features, and its capabilities for creating (60)Co intensity modulated radiation therapy (IMRT) treatment plans for a magnetic resonance image guidance radiation therapy (MR-IGRT) system.The ViewRay treatment planning system (Oakwood Village, OH) was used to create (60)Co IMRT treatment plans for 33 cancer patients with disease in the abdominal, pelvic, thorax, and head and neck regions using physician-specified patient-specific target coverage and organ at risk (OAR) objectives. Backup plans using a third-party linear accelerator (linac)-based planning system were also created. Plans were evaluated by attending physicians and approved for treatment. The (60)Co and linac plans were compared by evaluating conformity numbers (CN) with 100% and 95% of prescription reference doses and heterogeneity indices (HI) for planning target volumes (PTVs) and maximum, mean, and dose-volume histogram (DVH) values for OARs.All (60)Co IMRT plans achieved PTV coverage and OAR sparing that were similar to linac plans. PTV conformity for (60)Co was within1% and 3% of linac plans for 100% and 95% prescription reference isodoses, respectively, and heterogeneity was on average 4% greater. Comparisons of OAR mean dose showed generally better sparing with linac plans in the low-dose range20 Gy, but comparable sparing for organs with mean doses20 Gy. The mean doses for all (60)Co plan OARs were within clinical tolerances.A commercial (60)Co MR-IGRT device can produce highly conformal IMRT treatment plans similar in quality to linac IMRT for a variety of disease sites. Additional work is in progress to evaluate the clinical benefit of other novel features of this MR-IGRT system.

Materials/Methods: Two TPS (Philips Pinnacle 9.0 and Varian Eclipse 10.0) were evaluated using phantom geometries constructed from Solid Water (Gammex) and lung equivalent material (0.28 g/cm3). The phantom consisted of 3 cm Solid Water, 11 cm lung equivalent material, and 4 cm of Solid Water, with a 2 cm x 2 cm cylinder of Solid Water located at 10 cm depth along the central axis to represent a lung tumor (FIGURE 1). Planar dose measurements were taken with film for a 10MV FFF beam at four lung/tissue interfaces (3 cm, 9 cm, 11 cm, and 14 cm depth) and at mid-tumor (10 cm depth) for two field sizes (MLC shaped 2x2 cm2, and a jaw collimated 4x4 cm2). Most other calculated planes had less than 3% of pixels exceeding the gamma criteria. The Eclipse calculated dose was marginally more accurate than the Pinnacle dose calculations. One exception was the Eclipse calculated dose exceeded measured dose by 7% along the central axis for the 2x2 cm2 field at the plane distal to the lung tissue. Profile comparisons of both TPSs to film measurements are given in FIGURE 2a and 2b. Film measurements differed from ion chamber measurements in the center of the Solid Water cylinder by less than 1.5% for both field sizes. 3cm

manually segmenting the spinal cord on selected images and applying interleaved extrapolations to the entire spinal cord is not always accurate and frequently requires manual adjustment. We previously demonstrated the feasibility and validation of a fully automatic atlas-based segmentation system to the brain in patients with intracranial tumors [1]. Here we introduce an innovative method to contour the spinal canal with complete automaticity. The purpose herein is to determine the feasibility of this system for treatment planning in CT images of oncology patients undergoing radiotherapy. Materials/Methods: Previous atlas-based, non-rigid registration methods have been readily applied to anatomic structures regular in shape and characteristically stationary. The brain has worked well for these algorithms due to its immobility in the cranial compartment and its relatively uniform shape. To employ automatic segmentation techniques to wider anatomical regions, we have innovated a method that accounts for local variations in plasticity and rigidity. Central to this system was to develop an intelligent atlas that can be trained to know which anatomic regions are relatively pliable and consequently liable to change shape (lungs, muscle, adipose tissue) and which anatomic regions are relatively rigid and stationary ( fibrous tissue, bone). Thus, the deformation algorithm automatically adjusts the stiffness of the transformation to permit larger displacements over compliant regions and smaller displacements over less compliant regions [2]. From a single CT image set, we created a digital atlas by manually contouring the cervical-, thoracic-, and lumbar spinal column and subsequently training the atlas for regional pliability. We then employed this completely automatic segmentation system to deform the atlas and provide contours of the entire spinal canals in CT images of 3 patients being planned for radiotherapy. The resulting contours were reviewed by a radiologist and radiation oncologist. Results: The automatic segmentation system was easily applied to the 3 patients in this study. The figure shows representative CT images of the spinal column sagittally (panel A) and axially (panel B) with automatically-generated contours shown in dotted lines. The contours were deemed extremely satisfactory by the reviewing radiologist and radiation oncologist and were subjectively ascertained to require minimal, if any, adjustment for treatment planning. Conclusions: This novel automatic segmentation method proved effective for contouring the spinal canal in a small group of radiation oncology patients. Having a robust, reliable system to automatically and ef ficiently segment the spine is especially significant, considering the advent of real-time radiation planning and the importance in monitoring dose delivery. These results impart broader implications for utilizing automatic segmentation in the regions of the thorax and abdomen, where the anatomical architecture displays varying levels of plasticity. References

1A 330 1A 49 100.0 % 0.022 ± 0.033 (0.259) mu Pass Pass Pass Pass 1B 300 1B 79 100.0 % 0.035 ± 0.058 (0.391) mu Pass Pass Pass Pass 1C 270 1C 66 100.0 % 0.032 ± 0.077 (0.398) mu Pass Pass Pass Pass 1D 240 1D 108 100.0 % 0.045 ± 0.078 (0.516) mu Pass Pass Pass Pass 1E 210 1E 44 100.0 % 0.018 ± 0.037 (0.276) mu Pass Pass Pass Pass 1F 210 1F 42 100.0 % 0.013 ± 0.013 (0.158) mu Pass Pass Pass Pass 1 - Pass Rate = the percentage of the number of pixels with error less than the 2 percent of the maximal fluence (in mu) of the