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Purpose Stereotactic body radiotherapy (SBRT) delivers ablative doses with excellent local control. However, implementing SBRT for abdominal and pelvic tumors has been limited by the risk for treatment‐related gastrointestinal toxicity. MRI‐guided radiotherapy may ameliorate these risks and increase the therapeutic ratio. We report the clinical outcomes of stereotactic MRI‐guided adaptive radiotherapy (SMART) for primary and metastatic tumors in the abdomen and pelvis. Methods From November 2014 to August 2017, the first 106 consecutive patients with 121 tumors in the abdomen and pelvis were treated with SMART at a single institution. Of the cohort, 41.5%, 15.1%, and 43.4% had primary, locally recurrent, and oligometastatic tumors, respectively. SMART was delivered using a tri‐cobalt‐60 gantry with on‐board 0.35 Tesla MRI with respiratory breath‐hold and daily adaptive re‐planning when anatomically necessary. A median of 40Gy in five fractions was prescribed. The Common Terminology Criteria for Adverse Events v.4.03 was used to score treatment‐related toxicities. Local control (LC), progression‐free survival (PFS), and overall survival (OS) were estimated using Kaplan–Meier method. Results Of the 510 treatments, seventy‐one (13.9%) were adapted. Fatigue, nausea, and pain were the most common acute toxicities. 0.9 and 0% of patients experienced acute grade three and four toxicities, respectively. 5.2 and 2.1% of patients experienced late grade three and four toxicities, respectively. After a median follow‐up of 20.4 months, the 2‐year LC rate was 74% on a per‐lesion basis. Two‐year LC was 96% for lesions that were treated with BED10≥100 versus 69% for BED10, Implementing stereotactic body radiotherapy for abdominal and pelvic tumors has been limited by risk for treatment‐related gastrointestinal toxicity. In the largest reported clinical series to date of stereotactic magnetic resonance image‐guided adaptive radiotherapy, favorable local control and progression‐free survival were observed with minimal morbidity.

Purpose To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR‐guided radiotherapy system. Methods Ten patients with head‐and‐neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post‐processing. The images were rigidly registered and landmark‐based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone‐tissue, soft tissue, or air‐tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed. Results The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0–1 mm. 66% of the discrepancies were

PURPOSE The goal of this study was to predict soft tissue sarcoma response to radiotherapy (RT) using longitudinal diffusion-weighted MRI (DWI). A novel deep-learning prediction framework along with generative adversarial network (GAN)-based data augmentation was investigated for the response prediction. METHODS Thirty soft tissue sarcoma patients who were treated with five-fraction hypofractionated radiation therapy (RT, 6Gy×5) underwent diffusion-weighted MRI three times throughout the RT course using an MR-guided radiotherapy system. Pathologic treatment effect (TE) scores, ranging from 0-100%, were obtained from the post-RT surgical specimen as a surrogate of patient treatment response. Patients were divided into three classes based on the TE score (TE ≤ 20%, 20%

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.

Simple Summary Stereotactic body radiation therapy (SBRT) has become a standard of care option for prostate cancer patients, utilizing large fractionated dose to shorten treatment times. However, genitourinary (GU) toxicity associated with urethral injury remains prevalent due to non-trivial urethra delineation and sparing at treatment planning and treatment delivery. The aim of our study was to evaluate two optimized urethral MRI sequences (3D HASTE and 3D TSE) with a 0.35T MR-guided radiotherapy (MRgRT) system for urethral visibility and delineation. Among 11 prostate cancer patients, a radiation oncologist qualitatively scored MRgRT 3D HASTE as having the best urethra visibility, superior to CT, clinical MRgRT 3D bSSFP, MRgRT 3D TSE, and similar to diagnostic 3T (2D/3D) T2-weighetd MRI. Moreover, urethra contours from different imaging and clinical workflows demonstrated significant urethra localization variability. Optimized 3D MRgRT HASTE can provide urethral visualization and delineation within an MRgRT workflow for urethral sparing, avoiding cross-modality/system registration errors. Abstract Purpose: To evaluate urethral contours from two optimized urethral MRI sequences with an MR-guided radiotherapy system (MRgRT). Methods: Eleven prostate cancer patients were scanned on a MRgRT system using optimized urethral 3D HASTE and 3D TSE. A resident radiation oncologist contoured the prostatic urethra on the patients’ planning CT, diagnostic 3T T2w MRI, and both urethral MRIs. An attending radiation oncologist reviewed/edited the resident’s contours and additionally contoured the prostatic urethra on the clinical planning MRgRT MRI (bSSFP). For each image, the resident radiation oncologist, attending radiation oncologist, and a senior medical physicist qualitatively scored the prostatic urethra visibility. Using MRgRT 3D HASTE-based contouring workflow as baseline, prostatic urethra contours drawn on CT, diagnostic MRI, clinical bSSFP and 3D TSE were evaluated relative to the contour on 3D HASTE using 95th percentile Hausdorff distance (HD95), mean-distance-to-agreement (MDA), and DICE coefficient. Additionally, prostatic urethra contrast-to-noise-ratios (CNR) were calculated for all images. Results: For two out of three observers, the urethra visibility score for 3D HASTE was significantly higher than CT, and clinical bSSFP, but was not significantly different from diagnostic MRI. The mean HD95/MDA/DICE values were 11.35 ± 3.55 mm/5.77 ± 2.69 mm/0.07 ± 0.08 for CT, 7.62 ± 2.75 mm/3.83 ± 1.47 mm/0.12 ± 0.10 for CT + diagnostic MRI, 5.49 ± 2.32 mm/2.18 ± 1.19 mm/0.35 ± 0.19 for 3D TSE, and 6.34 ± 2.89 mm/2.65 ± 1.31 mm/0.21 ± 0.12 for clinical bSSFP. The CNR for 3D HASTE was significantly higher than CT, diagnostic MRI, and clinical bSSFP, but was not significantly different from 3D TSE. Conclusion: The urethra’s visibility scores showed optimized urethral MRgRT 3D HASTE was superior to the other tested methodologies. The prostatic urethra contours demonstrated significant variability from different imaging and workflows. Urethra contouring uncertainty introduced by cross-modality registration and sub-optimal imaging contrast may lead to significant treatment degradation when urethral sparing is implemented to minimize genitourinary toxicity.

Background Stereotactic body radiotherapy (SBRT) is becoming increasingly used in treating localized prostate cancer (PCa), with evidence showing similar toxicity and efficacy profiles when compared with longer courses of definitive radiation. Magnetic resonance imaging (MRI)-guided radiotherapy has multiple potential advantages over standard computed tomography (CT)-guided radiotherapy, including enhanced prostate visualization (abrogating the need for fiducials and MRI fusion), enhanced identification of the urethra, the ability to track the prostate in real-time, and the capacity to perform online adaptive planning. However, it is unknown whether these potential advantages translate into improved outcomes. This phase III randomized superiority trial is designed to prospectively evaluate whether toxicity is lower after MRI-guided versus CT-guided SBRT. Methods Three hundred men with localized PCa will be randomized in a 1:1 ratio to SBRT using CT or MRI guidance. Randomization will be stratified by baseline International Prostate Symptom Score (IPSS) (≤15 or > 15) and prostate gland volume (≤50 cc or > 50 cc). Five fractions of 8 Gy will be delivered to the prostate over the course of fourteen days, with or without hormonal therapy and elective nodal radiotherapy (to a dose of 5 Gy per fraction) as per the investigator’s discretion. The primary endpoint is the incidence of physician-reported acute grade ≥ 2 genitourinary (GU) toxicity (during the first 90 days after SBRT), as assessed by the CTCAE version 4.03 scale. Secondary clinical endpoints include incidence of acute grade ≥ 2 gastrointestinal (GI) toxicity, 5-year cumulative incidences of physician-reported late grade ≥ 2 GU and GI toxicity, temporal changes in patient-reported quality of life (QOL) outcomes, 5-year biochemical recurrence-free survival and the proportion of fractions of MRI-guided SBRT in which online adaptive radiotherapy is used. Discussion The MIRAGE trial is the first randomized trial comparing MRI-guided with standard CT-guided SBRT for localized PCa. The primary hypothesis is that MRI-guided SBRT will lead to an improvement in the cumulative incidence of acute grade ≥ 2 GU toxicity when compared to CT-guided SBRT. The pragmatic superiority design focused on an acute toxicity endpoint will allow an early comparison of the two technologies. Trial registration Clinicaltrials.gov identifier: NCT04384770. Date of registration: May 12, 2020. https://clinicaltrials.gov/ct2/show/NCT04384770 Protocol version Version 2.1, Aug 28, 2020.

Purpose: Stereotactic magnetic resonance image–guided adaptive radiation therapy (SMART) is an emerging technique that shows promise in the treatment of pancreatic cancer and other abdominopelvic malignancies. However, it is unknown whether the time-limited nature of on-table adaptive planning may result in dosimetrically suboptimal plans. The purpose of this study was to quantitatively address that question through systemic retrospective replanning of treated on-table adaptive pancreatic cancer cases. Methods and Materials: Of 74 consecutive adapted fractions, 30 were retrospectively replanned based on deficiencies in planning target volume (PTV) and gross tumor volume (GTV) coverage or doses to organs-at-risk (OARs) that exceeded ideal constraints. Retrospective plans were created by adjusting dose-volume objectives in an iterative fashion until deemed optimized. The goal of replanning was to improve PTV/GTV coverage while keeping the dose to gastrointestinal OARs the same or lower or to reduce OAR doses while keeping PTV coverage the same or higher. The global maximum dose was required to be maintained within 2% of that of the treated adaptive plan to eliminate it as a confounding factor. A threshold of 5% improvement in PTV coverage or 5% decrease in OAR dose was used to define a clinically significant improvement. Results: Of the 30 replans, 7 obtained at least 5% PTV coverage improvement. The average increase in PTV coverage for these plans was 11%. No plans were clinically significantly improved in terms of OAR sparing. Changes in beam-on time did not show any correlation. Statistical analysis via a linear mixed-effects model with a nested random effect suggested that both GTV and PTV coverage were improved over SMART process plans by 0.91 cc (P = .02) and 2.03 cc (P < .001), respectively. Conclusions: Dosimetric plan quality of at least 10% of SMART fractions may be improved through more extensive replanning than is currently performed on-table. Further work is needed to develop an automated replanning workflow to streamline the in-depth replanning process to better fit into an on-table adaptive workflow.

Purpose The clinical efficacy of radiation therapy is mechanistically linked to ionization-induced free radicals that cause cell and tissue injury through direct and indirect mechanisms. Free radical reaction dynamics are influenced by many factors and can be manipulated by static weak magnetic fields (WMF) that perturb singlet-triplet state interconversion. Our study exploits this phenomenon to directly increase ionizing radiation (IR) dose absorption in tumors by combining WMF with radiotherapy as a new and effective method to improve treatment. Methods and Materials Coils were custom made to produce both homogeneous and gradient magnetic fields. The gradient coil enabled simultaneous in vitro assessment of free radical/reactive oxygen species (ROS) reactivity across multiple field strengths from 6 to 66 G. First, increases in ionizing radiation-induced free radical concentrations using oxidant-sensitive fluorescent dyes in a cell-free system were measured and verified. Next, human and murine cancer cell lines were evaluated in in vitro and in vivo models following exposure to clinically relevant doses of ionizing radiation in combination with WMF. Results Cellular responses to IR and WMF were field strength- and cell line-dependent. WMF was able to enhance IR effects on ROS formation, DNA double strand break formation, cell death, and tumor growth. Conclusions We demonstrate that the external presence of a magnetic field enhances radiation-induced cancer cell injury and death in vitro and in vivo. The effect extends beyond the timeframe when free radicals are induced in the presence of radiation into the window when endogenous free radicals are produced and therefore extends the applicability of this novel adjunct to cancer therapy in the context of radiation treatment.

Simple Summary Geometric variations of patients receiving stereotactic body radiotherapy (SBRT) after radical prostatectomy were evaluated in this study. With specific bladder filling and rectal emptying patient instructions, CTV shape and volume remain relatively stable and dose coverage is well maintained whilst maintaining OAR dose constraints in most treatment fractions. However, target coverage and OAR doses can be further improved by MR-guided online adaptive planning to account for interfractional geometric variations. Abstract Purpose: To evaluate geometric variations of patients receiving stereotactic body radiotherapy (SBRT) after radical prostatectomy and the dosimetric benefits of stereotactic MRI guided adaptive radiotherapy (SMART) to compensate for these variations. Materials/Methods: The CTV and OAR were contoured on 55 MRI setup scans of 11 patients treated with an MR-LINAC and enrolled in a phase II trial of post-prostatectomy SBRT. All patients followed institutional bladder and rectum preparation protocols and received five fractions of 6−6.8 Gy to the prostate bed. Interfractional changes in volume were calculated and shape deformation was quantified by the Dice similar coefficient (DSC). Changes in CTV-V95%, bladder and rectum maximum dose, V32.5Gy and V27.5Gy were predicted by recalculating the initial plan on daily MRI. SMART was retrospectively simulated if the predicted dose exceeded pre-set criteria. Results: The CTV volume and shape remained stable with a median volumetric change of 3.0% (IQR −3.0% to 11.5%) and DSC of 0.83 (IQR 0.79 to 0.88). Relatively large volumetric changes in bladder (median −24.5%, IQR −34.6% to 14.5%) and rectum (median 5.4%, IQR − 9.7% to 20.7%) were observed while shape changes were moderate (median DSC of 0.79 and 0.73, respectively). The median CTV-V95% was 98.4% (IQR 94.9% to 99.6%) for the predicted doses. However, SMART would have been deemed beneficial for 78.2% of the 55 fractions based on target undercoverage (16.4%), exceeding OAR constraints (50.9%), or both (10.9%). Simulated SMART improved the dosimetry and met dosimetric criteria in all fractions. Moderate correlations were observed between the CTV-V95% and target DSC (R2 = 0.73) and bladder mean dose versus volumetric changes (R2 = 0.61). Conclusions: Interfractional dosimetric variations resulting from anatomic deformation are commonly encountered with post-prostatectomy RT and can be mitigated with SMART.

Background and purpose To prospectively determine the feasibility, safety, and efficacy of stereotactic body radiation therapy (SBRT) to primary and secondary liver tumors with MR-guided radiation therapy (MRgRT). Materials and methods Treatment plans with a conventional CT-guided linear accelerator and a MRI-guided tri-60Co teletherapy unit (MR-Co) were generated and compared for patients undergoing liver-directed SBRT from 2015 to 2017. If dosimetric parameters were met on MR-Co, patients were treated with MRgRT. The highest priority constraint was >1000 cc or >800 cc of normal liver receiving Results Of 23 patients screened, 20 patients (8 primary, 12 secondary) and 25 liver tumors underwent MR-guided SBRT to a median dose of 54 Gy (range 11.5-60) in a median of 3 fractions (range 1-5). With a median follow up of 18.9 months, the 1- and 2-year estimate of local control were 94.7% and 79.6%, respectively. A difference in local control between single and multiple lesions or BED ≥100Gy10 and BED Conclusion MR-guided SBRT is a viable and safe option in the delivery of ultrahypofractionated ablative radiation treatment to primary and secondary liver tumors resulting in high rates of local control and very favorable toxicity profiles.

Purpose To modify and evaluate an automatic American College of Radiology (ACR) phantom analysis toolbox for ACR quality assurance (QA) on a low-field MR guided radiotherapy system (ViewRay). Methods An open-source toolbox was modified for ACR QA of a 0.35T MRI system (ViewRay MRIdian). A total of 17 ACR datasets were evaluated, including 10 datasets acquired from different systems across the world, and 7 datasets acquired at our center between 2014 and 2020. All required ACR tests, geometric accuracy (GA), high-contrast spatial resolution (HCSR), slice thickness accuracy (ST), slice position accuracy (SP), percent integral uniformity (PIU), percentage signal ghosting (PSG), and low-contrast object detectability (LCOD), were assessed manually and using the toolbox automatically. Measurements between manual and automatic analysis were compared. Precision, recall, and accuracy were calculated, where the manual results were used as the ground truth. Results The software took less than 2 minutes to complete all seven tests, which usually requires 40 minutes or more if analyzed manually. Overall, the automatic measurement was consistent with the manual result. The absolute differences between the two measurements were 0.72±0.66 (mm), 0.01±0.03, 0.50±0.60 (mm), 0.39±0.41 (mm), 1.01±1.00 (%), 0.0016±0.0019, and 2.79±2.29 for the seven tests. The precision of the automatic toolbox was 100% for all tests, indicating that a test would 100% pass a manual analysis if it had passed the automatic analysis. Recall and accuracy were ≥96% for GA, HCSR, SP, PIU, PSG, and LCOD tests, and 91% for the ST test. Conclusion An automatic ACR QA tool was adopted and evaluated for the low-field MR guided radiotherapy (MRgRT) system. Overall, the toolbox provided comparable results as manual analysis, and reduced the processing time from over 40 minutes to less than 2 minutes. This toolbox holds the potential to be widely adopted either as a second check tool or partially replace human measurement for MRgRT programs using the same system.

Purpose On-board magnetic resonance imaging (MRI) greatly enhances real-time target tracking capability during radiotherapy treatments. However, multislice and volumetric MRI techniques are frame rate limited and introduce unacceptable latency between the target moving out of position and the beam being turned off. We present a technique to estimate continuous volumetric tissue motion using motion models built from a repeated acquisition of a stack of MR slices. Applications including multislice target visualization and out-of-slice motion estimation during MRI-guided radiotherapy are demonstrated. Methods Eight healthy volunteer studies were performed using a 0.35 T MRI-guided radiotherapy system. Images were acquired at three frames per second in an interleaved fashion across ten adjacent sagittal slice positions covering 4.5 cm using a balanced steady-state-free precession sequence. A previously published five-dimensional (5D) linear motion model used for MRI-guided radiotherapy gating was extended to include multiple slices. This model utilizes an external respiratory bellows signal recorded during imaging to simultaneously estimate motion across all imaged slices. For comparison to an image-based approach, the manifold learning technique local linear embedding (LLE) was used to derive a respiratory surrogate for motion modeling. Manifolds for every slice were aligned during LLE in a group-wise fashion, enabling motion estimation outside the current imaged slice using a motion model, a process which we denote as mSGA. Additionally, a method is developed to evaluate out-of-slice motion estimates. The multislice motion model was evaluated in a single slice with each newly acquired image using a leave-one-out approach. Model-generated gating decision accuracy and beam-on positive predictive value (PPV) are reported along with the median and 95th percentile distance between model and ground truth target centroids. Results The average model gating decision accuracy and PPV across all volunteer studies was 93.7% and 92.8% using the 5D model, and 96.8% and 96.1% using the mSGA model, respectively. The median and 95th percentile distance between model and ground truth target centroids was 0.91 and 2.90 mm, respectively, using the 5D model and 0.58 and 1.49 mm using the mSGA model, averaged over all eight subjects. The mSGA motion model provided a statistically significant improvement across all evaluation metrics compared to the external surrogate-based 5D model. Conclusion The proposed techniques for out-of-slice target motion estimation demonstrated accuracy likely sufficient for clinical use. Results indicate the mSGA model may provide higher accuracy, however, the external surrogate-based model allows for unbiased in vivo accuracy evaluation.

Purpose To develop and validate a technique for radiation therapy gating using slow (≤1 frame per second) magnetic resonance imaging (MRI) and a motion model. Proposed uses of the technique include radiation therapy gating using T2-weighted images and conducting additional imaging studies during gated treatments. Methods and Materials The technique uses a physiologically guided breathing motion model to interpolate deformed target position between 2-dimensional (2D) MRI images acquired every 1 to 3 seconds. The model is parameterized by a 1-dimensional respiratory bellows surrogate and is continuously updated with the most recently acquired 2D images. A phantom and 8 volunteers were imaged with a 0.35T MRI-guided radiation therapy system. A balanced steady-state free precession sequence with a 2D frame rate of 3 frames per second was used to evaluate the technique. The accuracy and beam-on positive predictive value (PPV) of the model-based gating decisions were evaluated using the gating decisions derived from imaging as a ground truth. A T2-weighted gating offline proof-of-concept study using a half-Fourier, single-shot, turbo-spin echo sequence is reported. Results Model-interpolated gating accuracy, beam-on PPV, and median absolute distances between model and image-tracked target centroids were, on average, 98.3%, 98.4%, and 0.33 mm, respectively, in the balanced steady-state free precession phantom studies and 93.7%, 92.1%, and 0.86 mm, respectively, in the volunteer studies. T2 model-interpolated gating in 6 volunteers yielded an average accuracy and PPV of 94.3% and 92.5%, respectively, and the mean absolute median distance between modeled and imaged target centroids was 0.86 mm. Conclusions This work demonstrates the concept of model-interpolated gating for MRI-guided radiation therapy. The technique was found to be potentially sufficiently accurate for clinical use. Further development is needed to accommodate out-of-plane motion and the use of an internal MR-based respiratory surrogate.

Purpose The purpose of this study was to introduce a compressed sensing and parallel imaging-combined technique to reduce the acquisition time of planning MRI for MR-guided radiotherapy (MRgRT) systems. Methods and materials A variable-density Poisson-Disk (VDPD) undersampling acquisition along with compressed sensing reconstruction technique was developed and compared with the current planning MR protocol, which uses an optimized balanced steady-state free precession sequence with 7.5-fold (7.5×) acceleration achieved by GRAPPA and partial Fourier. The image quality of GRAPPA and VDPD with 7.5× and 15× acceleration was compared with fully sampled images on a phantom. Two volunteers were recruited to compare the in vivo imaging performance. Ten patients with abdominal tumors were scanned using the conventional GRAPPA 7.5× (25 s) and the proposed VDPD 15× (12.5 s) sequences. Three readers scored the two approaches in terms of the quality for organ and tumor delineation. The gross tumor volume (GTV) and two kidneys were contoured. Differences in centroid location and contour volumes, Dice coefficients, and mean distance-to-agreement (MDA) between contours draw on the two techniques were calculated. All studies were performed on a 0.35 T MRgRT system. Results In the phantom study, VDPD with 15× acceleration rate had lower noise level than GRAPPA with 7.5× acceleration. In both the phantom and volunteer study, noise amplification was apparent when the acceleration rate was increased from 7.5× to 15× in the GRAPPA acquisition, whereas it was minimally increased using the VDPD approach. In the patient study, no significant difference was found for the scoring and contouring statistics between the two techniques, whereas VDPD only took half the scan time as GRAPPA. Volume difference for the GTV and two kidneys between GRAPPA 7.5× and VDPD 15× was around 7.6%, 1.3%, and 2.8%, respectively; while the Dice index was approximately 0.85, 0.92, and 0.90, respectively. Conclusion The proposed technique reduced the acquisition time by half and provided comparable or improved image quality than the standard planning MRI protocol.

Purpose A critical step in adaptive radiotherapy (ART) workflow is deformably registering the simulation CT with the daily or weekly volumetric imaging. Quantifying the deformable image registration accuracy under these circumstances is a complex task due to the lack of known ground-truth landmark correspondences between the source data and target data. Generating landmarks manually (using experts) is time-consuming, and limited by image quality and observer variability. While image similarity metrics (ISM) may be used as an alternative approach to quantify the registration error, there is a need to characterize the ISM values by developing a non-linear cost function and translate them to physical distance measures in order to enable fast, quantitative comparison of registration performance. Methods In this paper, we present a proof-of-concept methodology for automated quantification of DIR performance. A non-linear cost function was developed as a combination of ISM values and governed by the following two expectations for an accurate registration: (1) the deformed data obtained from transforming the simulation CT data with the deformation vector field (DVF) should match the target image data with near perfect similarity, and (2) the similarity between the simulation CT and deformed data should match the similarity between the simulation CT and the target image data. A deep neural network (DNN) was developed that translated the cost function values to actual physical distance measure. To train the neural network, patient-specific biomechanical models of the head-and-neck anatomy were employed. The biomechanical model anatomy was systematically deformed to represent changes in patient posture and physiological regression. Volumetric source and target images with known ground-truth deformations vector fields were then generated, representing the daily or weekly imaging data. Annotated data was then fed through a supervised machine learning process, iteratively optimizing a non-linear model able to predict the target registration error (TRE) for given ISM values. The cost function for sub-volumes enclosing critical radiotherapy structures in the head-and-neck region were computed and compared with the ground truth TRE values. Results When examining different combinations of registration parameters for a single DIR, the neural network was able to quantify DIR error to within a single voxel for 95% of the sub-volumes examined. In addition, correlations between the neural network predicted error and the ground-truth TRE for the Planning Target Volume and the parotid contours were consistently observed to be >0.9. For variations in posture and tumor regression for 10 different patients, patient-specific neural networks predicted the TRE to within a single voxel >90% on average. Conclusions The formulation presented in this paper demonstrates the ability for fast, accurate quantification of registration performance. DNN provided the necessary level of abstraction to estimate a quantified TRE from the ISM expectations described above, when sufficiently trained on annotated data. In addition, biomechanical models facilitated the DNN with the required variations in the patient posture and physiological regression. With further development and validation on clinical patient data, such networks have potential impact in patient and site-specific optimization, and stream-lining clinical registration validation. This article is protected by copyright. All rights reserved.

To report a single-institutional experience with the use of magnetic resonance imaging (MRI)-guided radiotherapy for cancers of the head and neck. Between October 2014 and October 2016, 18 patients with newly diagnosed cancers of the head and neck were prospectively enrolled on an institutional registry trial investigating the feasibility and efficacy of external-beam radiotherapy delivered using on-board MRI. All patients had biopsy-proven evidence of malignancy, measurable disease, and the ability to provide consent. None had previously received any treatment. Median dose was 70 Gy (range 54–70 Gy). MRI scans were obtained as part of an image-guided registration protocol for alignment prior to and during each treatment. Concurrent chemotherapy was administered to 14 patients (78%). Patient-reported outcomes were assessed using the University of Washington quality of life instrument. Seventeen of 18 patients completed the planned intensity-modulated radiotherapy (IMRT) treatment of which 15 (83%) had a complete response and 2 (11%) had a partial response based on initial post-therapy positron emission tomography (PET) at 3 months. The 1-year estimates of progression-free survival, overall survival, and local–regional control were 95, 96, and 95%, respectively. There were no treatment-related fatalities. The incidence of grade 3+ acute toxicity was 44%. The proportion of patients rating their health-related quality of life as “very good” or “outstanding” at 6 months and 1 year after completion of radiation therapy was 60 and 70%, respectively. MRI-guided radiotherapy achieves clinical outcomes comparable to contemporary series reporting on IMRT for head and neck cancer.

Background and purpose Second malignancies (SM) after external beam radiotherapy (EBRT) or brachytherapy (BT) for prostate cancer (PCa) are rare but serious sequelae. Materials and methods The Surveillance, Epidemiology, and End Results (SEER) database was used to identify men diagnosed with cT1-2N0M0 PCa between 1999 and 2005, who underwent EBRT, BT or radical prostatectomy (RP). Patients with time interval to second malignancy or follow-up shorter than five and two years were excluded for solid and hematopoietic SM analyses respectively. Risks for solid and hematopoietic SM were evaluated via the multivariate Fine and Gray proportional hazards model. Results EBRT and BT resulted in similar increases in solid and hematopoietic SM compared to RP. In subgroup analysis stratified by treatment modality, only the EBRT cohort demonstrated significantly decreased solid and hematopoietic SM in years 2002–2005 compared to years 1999–2001, with adjusted-hazard ratios of 0.752 ( p =0.001) and 0.815 ( p =0.018) respectively. Conclusions EBRT and BT resulted in statistically equivalent increase in both solid and hematopoietic SM compared to RP. EBRT in more recent years resulted in significantly decreased solid and hematopoietic SM, coinciding with increased utilization of IMRT.

Purpose To develop and evaluate a fast patient localization tool using megavoltage (MV)-topogram on helical tomotherapy. Methods and Materials Eighty-one MV-topogram pairs for 18 pelvis patients undergoing radiation were acquired weekly under an institutional review board–approved clinical trial. The MV-topogram imaging protocol requires 2 orthogonal acquisitions at static gantry angles of 0 degrees and 90 degrees for a programed scan length. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference images (digitally reconstructed topograms, digitally reconstructed topograms) were generated using the planning computed tomography and tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the digitally reconstructed topogram using bony landmark on commercial MIM software. The daily shifts in 3 translational directions determined from MV-topograms were compared with the megavoltage computed tomography (MVCT) based patient shifts. Linear-regression and two one-sided tests equivalence tests were performed to investigate the relation and equivalence between the 2 techniques. Seventy-eight MV-topogram pairs for 19 head and neck patients were included to validate the finding. Results The magnitudes of alignment differences of (MVCT − MV-topogram) (and standard deviations) were −0.3 ± 2.1, −0.8 ± 2.4, and 1.6 ± 1.7 mm for pelvis and 0.6 ± 1.2, 0.8 ± 4.2, 1.6 ± 2.6 mm for head and neck; the linear-regression coefficients between 2 imaging techniques were 1.18, 1.10, 0.94, and 0.86, 0.63, 0.38 in the lateral, longitudinal, vertical directions for pelvis and head and neck, respectively. The acquisition time for a pair of MV-topograms was up to 12.7 times less than MVCT scans (coarse scan mode) while covering longer longitudinal length. Conclusions MV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis and H&N patients. The MV-topogram can be used as an alternative or complimentary tool for bony landmark-based patient alignment on tomotherapy.

PURPOSE Motion prediction can compensate for latency in image-guided radiotherapy and has been an active area of research. However, motion predictions are subject to error and variations. We have developed and evaluated a novel motion prediction confidence estimation framework to improve the efficacy and robustness of prediction-based radiotherapy gating decision-making. The specific scenario of adaptive gating in magnetic resonance imaging (MRI)-guided radiotherapy is studied as an example, but the method generalizes to other modalities and motion management setups. METHODS The proposed prediction confidence estimator is based on a generic training/testing paradigm and consists of a weighted combination of three components: the prediction model's goodness of fit, variation in the prediction using a leave-one-out process and the velocity of the tracked target. Roughly, these terms quantify respectively the consistency between prediction and the training data, the robustness of model inference, and the stability due to target speed. The weight parameters and the action level in triggering beam-off decision are optimized. The method is assessed and validated in 8 healthy volunteer and 13 patient studies using a 0.35T MRI-guided radiotherapy system predicting 0.25-0.33 s ahead. The effect of the action level on the predicted gating decision accuracy, beam-on positive predictive value (PPV) and median distance between the predicted and ground-truth target centroids were evaluated. Statistical significance was evaluated using a paired t-test. The tradeoff between these performance metrics and gating duty cycle was assessed. RESULTS Use of the confidence estimator threshold increased gating accuracy by up to 2.42%, increased PPV by up to 3.00%, and reduced the median centroid distance up to 0.28 mm. The confidence estimator threshold on average increased gating accuracy to 96.5% (P = 2.08 × 10-4 ), increased PPV to 96.7% (P = 1.46 × 10-5 ), reduced the median centroid distance to 0.54 mm (P = 1.71 × 10-5 ) at the cost of reducing the gating duty cycle by 14.3% to 48.5%. Hyperparameter tuning revealed that contrary to intuition, the velocity term offered only minimal performance improvement in some cases but also introduced potential stability issues. The combination of goodness of fit and leave-one-out prediction variation provided the most effective confidence estimator, yielding universally better performance in gating decisions. CONCLUSION Confidence estimation utilizing prediction model fitness criterion and validation principles can complement prediction methods to guide MRI-guided radiotherapy gating. Results from both volunteer and patient studies showed improved gating quality.

Purpose Lung elastography aims at measuring the lung parenchymal tissue elasticity for applications ranging from diagnostic purposes to biomechanically guided deformations. Characterizing the lung tissue elasticity requires four-dimensional (4D) lung motion as an input, which is currently estimated by deformably registering 4D computed tomography (4DCT) datasets. Since 4DCT imaging is widely used only in a radiotherapy treatment setup, there is a need to predict the elasticity distribution in the absence of 4D imaging for applications within and outside of radiotherapy domain. Methods In this paper, we present a machine learning-based method that predicts the three-dimensional (3D) lung tissue elasticity distribution for a given end-expiration 3DCT. The method to predict the lung tissue elasticity from an end-expiration 3DCT employed a deep neural network that predicts the tissue elasticity for the given CT dataset. For training and validation purposes, we employed five-dimensional CT (5DCT) datasets and a finite element biomechanical lung model. The 5DCT model was first used to generate end-expiration lung geometry, which was taken as the source lung geometry for biomechanical modeling. The deformation vector field pointing from end expiration to end inhalation was computed from the 5DCT model and taken as input in order to solve for the lung tissue elasticity. An inverse elasticity estimation process was employed, where we iteratively solved for the lung elasticity distribution until the model reproduced the ground-truth deformation vector field. The machine learning process uses a specific type of learning process, namely a constrained generalized adversarial neural network (cGAN) that learned the lung tissue elasticity in a supervised manner. The biomechanically estimated tissue elasticity together with the end-exhalation CT was the input for the supervised learning. The trained cGAN generated the elasticity from a given breath-hold CT image. The elasticity estimated was validated in two approaches. In the first approach, a L2-norm-based direct comparison was employed between the estimated elasticity and the ground-truth elasticity. In the second approach, we generated a synthetic four-dimensional CT (4DCT0 using a lung biomechanical model and the estimated elasticity and compared the deformations with the ground-truth 4D deformations using three image similarity metrics: mutual Information (MI), structured similarity index (SSIM), and normalized cross correlation (NCC). Results The results show that a cGAN-based machine learning approach was effective in computing the lung tissue elasticity given the end-expiration CT datasets. For the training data set, we obtained a learning accuracy of 0.44 ± 0.2 KPa. For the validation dataset, consisting of 13 4D datasets, we were able to obtain an accuracy of 0.87 ± 0.4 KPa. These results show that the cGAN-generated elasticity correlates well with that of the underlying ground-truth elasticity. We then integrated the estimated elasticity with the biomechanical model and applied the same boundary conditions in order to generate the end inhalation CT. The cGAN-generated images were very similar to that of the original end inhalation CT. The average value of the MI is 1.77 indicating the high local symmetricity between the ground truth and the cGAN elasticity-generated end inhalation CT data. The average value of the structural similarity for the 13 patients was observed to be 0.89 indicating the high structural integrity of the cGAN elasticity-generated end inhalation CT. Finally, the average NCC value of 0.97 indicates that potential variations in the contrast and brightness of the cGAN elasticity-generated end inhalation CT and the ground-truth end inhalation CT. Conclusion The cGAN-generated lung tissue elasticity given an end-expiration CT image can be computed in near real time. Using the lung tissue elasticity along with a biomechanical model, 4D lung deformations can be generated from a given end-expiration CT image within clinically acceptable numerical accuracy.

INTRODUCTION AND OBJECTIVES:Salvage prostate bed radiotherapy (PBRT) results in about 70% 5 yr freedom from progression (FFP). A three arm randomized trial was designed to determine whether there a...

Purpose To investigate the accuracy of 4D dose accumulation using projection of dose calculated on the end-exhalation, mid-ventilation, or average intensity breathing phase CT scan, versus dose accumulation performed using full Monte Carlo dose recalculation on every breathing phase. Methods Radiotherapy plans for 10 patients with stage I-II lung cancer were analyzed. All patients had respiratory-correlated computed tomography (4D-CT) performed as part of an IRB-approved research protocol. Stereotactic body radiotherapy (SBRT) plans were optimized using the dose calculated by a commercially-available Monte Carlo algorithm on the end-exhalation 4D-CT phase. 4D dose accumulations using deformable registration were performed with a commercially available tool that projected the planned dose onto every breathing phase without recalculation, as well as with a Monte Carlo recalculation of the dose on all breathing phases. The 3D planned dose (3D-EX), the 3D dose calculated on the average intensity image (3D-AVE), and the 4D accumulations of the dose calculated on the end-exhalation phase CT (4D-PR-EX), the mid-ventilation phase CT (4D-PR-MID), and the average intensity image (4D-PR-AVE), respectively, were compared against the accumulation of the Monte Carlo dose recalculated on every phase. Plan evaluation metrics relating to target volumes and critical structures relevant for lung SBRT were analyzed. Results Plan evaluation metrics tabulated using 4D-PR-EX, 4D-PR-MID, and 4D-PR-AVE differed from those tabulated using Monte Carlo recalculation on every phase by an average of 0.14±0.70 Gy, -0.11±0.51 Gy, and 0.00±0.62 Gy, respectively. Plan evaluation metrics calculated from 3D-EX and 3D-AVE were acceptably accurate for target volumes and most critical structures, however deviations of between 8 and 13 Gy were observed for the proximal bronchial trees of 3 patients. Conclusions The accuracy of 4D dose accumulated by projecting the dose calculated on the end-exhale, mid-ventilation, and average intensity images has been presented for 10 lung cancer SRBT plans. These methods involving projection without re-calculation may be sufficiently accurate compared to 4D dose accumulated from Monte Carlo recalculation on every phase, depending on institutional protocols. Projection of the dose calculated on the mid-ventilation scan was found to be statistically significantly more accurate than projection of the dose calculated on end-exhalation when considering target volume dose metrics. Use of 4D dose accumulation should be considered when evaluating normal tissue complication probabilities as well as in clinical situations where target volumes are directly inferior to mobile critical structures. This article is protected by copyright. All rights reserved.

Purpose: Magnetic resonance imaging (MRI) guidance in radiation therapy brings real-time imaging and adaptive planning into the treatment vault where it can account for interfraction and intrafraction movement of soft tissue. The only commercially available MRI-guided radiation therapy device is a three-head 60Co and MRI system with an integrated treatment planning system (TPS). Couch attenuation of the beam of up to 20% is well modeled in the TPS. Variations in the patient’s day-to-day position introduce discrepancies in the actual couch attenuation as modeled in the treatment plan. For this reason, the authors’ institution avoids plans with beams that pass through or near the couch edges. This study investigates the effects of differential beam attenuation by the couch due to couch shifts in order to determine whether couch edge avoidance restrictions can be lifted. Couch shifts were simulated using a Monte Carlo treatment planning system and ion chamber measurements performed for validation. Methods: A total of 27 plans from 23 patients were investigated. Couch shifts of 1 and 2 cm were introduced in combinations of lateral and vertical directions to simulate patient position variations giving 16 shifted plans per reference plan. The 1 and 2 cm shifts were based on shifts recorded in 320 treatment fractions. Results: Following TG176 recommendations for measurement methods, couch attenuation measurements agreed with TPS modeled attenuation to within 2.1%. Planning target volume D95 changed less than 1% for 1 and 2 cm couch shifts in only the x-direction and less than 3% for all directions. Conclusions: Dosimetry of all plans tested was robust to couch shifts up to ±2 cm. In general, couch shifts resulted in clinically insignificant dosimetric deviations. It is conceivable that in certain cases with large systematic couch shifts and plans that are particularly sensitive to shifts, dosimetric changes might rise to a clinically significant level.

Purpose: Volumetric modulated arc therapy (VMAT) is a widely employed radiation therapy technique, showing comparable dosimetry to static beam intensity modulated radiation therapy (IMRT) with reduced monitor units and treatment time. However, the current VMAT optimization has various greedy heuristics employed for an empirical solution, which jeopardizes plan consistency and quality. The authors introduce a novel direct aperture optimization method for VMAT to overcome these limitations. Methods: The comprehensive VMAT (comVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term to penalize the difference between the optimized dose and the prescribed dose, as well as an anisotropic total variation term to promote piecewise continuity in the fluence maps, preparing it for direct aperture optimization. A level set function was used to describe the aperture shapes and the difference between aperture shapes at adjacent angles was penalized to control MLC motion range. A proximal-class optimization solver was adopted to solve the large scale optimization problem, and an alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc comVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme case, a lung (LNG) case, and two head and neck cases—one with three PTVs (H&N3PTV) and one with foue PTVs (H&N4PTV)—to test the efficacy. The plans were optimized using an alternating optimization strategy. The plans were compared against the clinical VMAT (clnVMAT) plans utilizing two overlapping coplanar arcs for treatment. Results: The optimization of the comVMAT plans had converged within 600 iterations of the block minimization algorithm. comVMAT plans were able to consistently reduce the dose to all organs-at-risk (OARs) as compared to the clnVMAT plans. On average, comVMAT plans reduced the max and mean OAR dose by 6.59% and 7.45%, respectively, of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages measured by D95, D98, and D99 were within 0.25% of the prescription dose. By comprehensively optimizing all beams, the comVMAT optimizer gained the freedom to allow some selected beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel nongreedy VMAT approach simultaneously optimizes all beams in an arc and then directly generates deliverable apertures. The single arc VMAT approach thus fully utilizes the digital Linac’s capability in dose rate and gantry rotation speed modulation. In practice, the new single VMAT algorithm generates plans superior to existing VMAT algorithms utilizing two arcs.

Purpose This study aimed to evaluate the potential of megavoltage-topogram (MV-topogram)–based alignment as an alternative to megavoltage computed tomography (MVCT) in reducing setup time and imaging dose for patients with malignant pleural mesothelioma who are receiving TomoTherapy. Methods and Materials Twelve patients were enrolled in an ongoing institutional review board approved clinical trial at our institute. Patients were set up with a clinical protocol using red lasers. Anteroposterior (AP) and lateral (LAT) MV-topograms were acquired using gantry angles of 0°/90° with a 1 mm collimator opening, all multileaf collimator leaves open, a couch speed of 4 cm/s, and a 12.5-second scanning time. Routine MVCT scans were performed immediately afterward. The MV-topograms were reconstructed and enhanced using contrast-limited adaptive histogram equalization. Anteroposterior and LAT kilovoltage digital reconstructed topogram images were reconstructed based on TomoTherapy geometry from computed tomography simulation scans. Registrations between MV-topograms and kilovoltage-digital reconstructed topogram images were performed manually, and patients' daily shifts were recorded. Results were compared against the corresponding daily MVCT shifts. MV-topogram and MVCT doses were measured and recorded using an ion chamber on a cheese phantom with depths between 1 and 14 cm, as well as the times required to acquire the 2 image modalities. Results The mean and standard deviation of shift discrepancies between MV-topogram and MVCT were 0.74 ± 2.08, –0.09 ± 4.46, and 0.45 ± 3.57 mm in the LAT, longitudinal, and vertical directions, respectively. The MVCT imaging doses measured were 14.74 to 26.92 times higher than the MV-topogram doses, depending on depth. On average, MV-topograms with a mean scan length of 50 cm achieved a 5-fold image acquisition time savings over MVCT, with a mean scan length of 38 cm. Conclusions MV-topograms has the potential to provide alignment performance equivalent to that of MVCT for patients with mesothelioma, with a significant reduction in imaging dose and acquisition time.

PURPOSE: To demonstrate the preliminary feasibility of a longitudinal diffusion magnetic resonance imaging (MRI) strategy for assessing patient response to radiotherapy at 0.35 T using an MRI‐guided radiotherapy system (ViewRay). METHODS: Six patients (three head and neck cancer, three sarcoma) who underwent fractionated radiotherapy were enrolled in this study. A 2D multislice spin echo single‐shot echo planar imaging diffusion pulse sequence was implemented on the ViewRay system and tested in phantom studies. The same pulse sequence was used to acquire longitudinal diffusion data (every 2–5 fractions) on the six patients throughout the entire course of radiotherapy. The reproducibility of the apparent diffusion coefficient (ADC) measurements was assessed using reference regions and the temporal variations of the tumor ADC values were evaluated. RESULTS: In diffusion phantom studies, the ADC values measured on the ViewRay system matched well with reference ADC values with

We evaluated the feasibility of planning stereotactic body radiotherapy (SBRT) for large central early-stage non-small cell lung cancer with a tri-cobalt-60 (tri-(60)Co) system equipped with real-time magnetic resonance imaging (MRI) guidance, as compared to linear accelerator (LINAC)-based SBRT. In all, 20 patients with large central early-stage non-small cell lung cancer who were treated between 2010 and 2015 with LINAC-based SBRT were replanned using a tri-(60)Co system for a prescription dose of 50Gy in 4 fractions. Doses to organs at risk were evaluated based on established MD Anderson constraints for central lung SBRT. R100 values were calculated as the total tissue volume receiving 100% of the dose (V100) divided by the planning target volume and compared to assess dose conformity. Dosimetric comparisons between LINAC-based and tri-(60)Co SBRT plans were performed using Student׳s t-test and Wilcoxon Ranks test. Blinded reviews by radiation oncologists were performed to assess the suitability of both plans for clinical delivery. The mean planning target volume was 48.3cc (range: 12.1 to 139.4cc). Of the tri-(60)Co SBRT plans, a mean 97.4% of dosimetric parameters per patient met MD Anderson dose constraints, whereas a mean 98.8% of dosimetric parameters per patient were met with LINAC-based SBRT planning (p = 0.056). R100 values were similar between both plans (1.20 vs 1.21, p = 0.79). Upon blinded review by 4 radiation oncologists, an average of 90% of the tri-(60)Co SBRT plans were considered acceptable for clinical delivery compared with 100% of the corresponding LINAC-based SBRT plans (p = 0.17). SBRT planning using the tri-(60)Co system with built-in MRI is feasible and achieves clinically acceptable plans for most central lung patients, with similar target dose conformity and organ at risk dosimetry. The added benefit of real-time MRI-guided therapy may further optimize tumor targeting while improving normal tissue sparing, which warrants further investigation in a prospective feasibility clinical trial.

Our goal was to geometrically validate the use of mega-voltage orthogonal scout images (MV topograms) as a fast and low-dose alternative to mega-voltage computed tomography (MVCT) for daily patient localization on the TomoTherapy system. To achieve this, anthropomorphic head and pelvis phantoms were imaged on a 16-slice kilo-voltage computed tomography (kVCT) scanner to synthesize kilo-voltage digitally reconstructed topograms (kV-DRT) in the Tomotherapy detector geometry. MV topograms were generated for couch speeds of 1-4 cm s(-1) in 1 cm s(-1) increments with static gantry angles in the anterior-posterior and left-lateral directions. Phantoms were rigidly translated in the anterior-posterior (AP), superior-inferior (SI), and lateral (LAT) directions to simulate potential setup errors. Image quality improvement was demonstrated by estimating the noise level in the unenhanced and enhanced MV topograms using a principle component analysis-based noise level estimation algorithm. Average noise levels for the head phantom were reduced by 2.53 HU (AP) and 0.18 HU (LAT). The pelvis phantom exhibited average noise level reduction of 1.98 HU (AP) and 0.48 HU (LAT). Mattes Mutual Information rigid registration was used to register enhanced MV topograms with corresponding kV-DRT. Registration results were compared to the known rigid displacements, which assessed the MV topogram localization's sensitivity to daily positioning errors. Reduced noise levels in the MV topograms enhanced the registration results so that registration errors were

Radiation therapy is an effective, personalized cancer treatment that has benefited from technological advances associated with the growing ability to identify and target tumors with accuracy and precision. Given that these advances have played a central role in the success of radiation therapy as a major component of comprehensive cancer care, the American Society for Radiation Oncology (ASTRO), the American Association of Physicists in Medicine (AAPM), and the National Cancer Institute (NCI) sponsored a workshop entitled "Technology for Innovation in Radiation Oncology," which took place at the National Institutes of Health (NIH) in Bethesda, Maryland, on June 13 and 14, 2013. The purpose of this workshop was to discuss emerging technology for the field and to recognize areas for greater research investment. Expert clinicians and scientists discussed innovative technology in radiation oncology, in particular as to how these technologies are being developed and translated to clinical practice in the face of current and future challenges and opportunities. Technologies encompassed topics in functional imaging, treatment devices, nanotechnology, and information technology. The technical, quality, and safety performance of these technologies were also considered. A major theme of the workshop was the growing importance of innovation in the domain of process automation and oncology informatics. The technologically advanced nature of radiation therapy treatments predisposes radiation oncology research teams to take on informatics research initiatives. In addition, the discussion on technology development was balanced with a parallel conversation regarding the need for evidence of efficacy and effectiveness. The linkage between the need for evidence and the efforts in informatics research was clearly identified as synergistic.

Purpose The purpose of this study was to investigate the dosimetric feasibility of liver stereotactic body radiation therapy (SBRT) using a teletherapy system equipped with 3 rotating 60 Co sources (tri- 60 Co system) and a built-in magnetic resonance imager (MRI). We hypothesized tumor size and location would be predictive of favorable dosimetry with tri- 60 Co SBRT. Methods and materials The primary study population consisted of 11 patients treated with SBRT for malignant hepatic lesions whose linear accelerator (LINAC)–based SBRT plans met all mandatory Radiation Therapy Oncology Group (RTOG) 1112 organ-at-risk (OAR) constraints. The secondary study population included 5 additional patients whose plans did not meet the mandatory constraints. Patients received 36 to 60 Gy in 3 to 5 fractions. Tri- 60 Co system SBRT plans were planned with ViewRay system software. Results All patients in the primary study population had tri- 60 Co SBRT plans that passed all RTOG constraints, with similar planning target volume coverage and OAR doses to LINAC plans. Mean liver doses and V 10Gy to the liver, although easily meeting RTOG 1112 guidelines, were significantly higher with tri- 60 Co plans. When the 5 additional patients were included in a univariate analysis, the tri- 60 Co SBRT plans were still equally able to pass RTOG constraints, although they did have inferior ability to pass more stringent liver and kidney constraints ( P 60 Co SBRT plan to meet these constraints depended on lesion location and size. Patients with smaller or more peripheral lesions (as defined by distance from the aorta, chest wall, liver dome, and relative lesion volume) were significantly more likely to have tri- 60 Co plans that spared the liver and kidney as well as LINAC plans did ( P Conclusions It is dosimetrically feasible to perform liver SBRT with a tri- 60 Co system with a built-in MRI. Patients with smaller or more peripheral lesions are more likely to have optimal liver and kidney sparing, with the added benefit of MRI guidance, when receiving tri- 60 Co–based SBRT.

Purpose The purpose of this study was to systematically monitor anatomic variations and their dosimetric consequences during intensity modulated radiation therapy (IMRT) for head and neck (H&N) cancer by using a graphics processing unit (GPU)-based deformable image registration (DIR) framework. Methods and Materials Eleven IMRT H&N patients undergoing IMRT with daily megavoltage computed tomography (CT) and weekly kilovoltage CT (kVCT) scans were included in this analysis. Pretreatment kVCTs were automatically registered with their corresponding planning CTs through a GPU-based DIR framework. The deformation of each contoured structure in the H&N region was computed to account for nonrigid change in the patient setup. The Jacobian determinant of the planning target volumes and the surrounding critical structures were used to quantify anatomical volume changes. The actual delivered dose was calculated accounting for the organ deformation. The dose distribution uncertainties due to registration errors were estimated using a landmark-based gamma evaluation. Results Dramatic interfractional anatomic changes were observed. During the treatment course of 6 to 7 weeks, the parotid gland volumes changed up to 34.7%, and the center-of-mass displacement of the 2 parotid glands varied in the range of 0.9 to 8.8 mm. For the primary treatment volume, the cumulative minimum and mean and equivalent uniform doses assessed by the weekly kVCTs were lower than the planned doses by up to 14.9% ( P =.14), 2% ( P =.39), and 7.3% ( P =.05), respectively. The cumulative mean doses were significantly higher than the planned dose for the left parotid ( P =.03) and right parotid glands ( P =.006). The computation including DIR and dose accumulation was ultrafast (∼45 seconds) with registration accuracy at the subvoxel level. Conclusions A systematic analysis of anatomic variations in the H&N region and their dosimetric consequences is critical in improving treatment efficacy. Nearly real-time assessment of anatomic and dosimetric variations is feasible using the GPU-based DIR framework. Clinical implementation of this technology may enable timely plan adaptation and improved outcome.

Locally advanced pancreatic cancer (LAPC) is characterized by poor prognosis and low response durability with standard-of-care chemotherapy or chemoradiotherapy treatment. Stereotactic body radiation therapy (SBRT), which has a shorter treatment course than conventionally fractionated radiotherapy and allows for better integration with systemic therapy, may confer a survival benefit but is limited by gastrointestinal toxicity. Stereotactic MRI-guided adaptive radiation therapy (SMART) has recently gained attention for its potential to increase treatment precision and thus minimize this toxicity through continuous real-time soft-tissue imaging during radiotherapy. The case presented here illustrates the promising outcome of a 69-year-old male patient with LAPC treated with SMART with daily adaptive planning and respiratory-gated technique.

We present a case of durable local control achieved in a patient treated with stereotactic magnetic resonance-guided adaptive radiation therapy (SMART) for an abdominal lymph node in the setting of oligometastatic breast cancer. A 50-year-old woman with a history of triple positive metastatic invasive ductal carcinoma of the left breast, stage IV (T3N2M1), underwent neoadjuvant chemotherapy, mastectomy, adjuvant radiotherapy and maintenance hormonal treatment with HER2 targeted therapies. At 20 months after definitive treatment of her primary, imaging showed an isolated progressive enlargement of lymph nodes between hepatic segment V/IVB and the neck of the pancreas. Radiofrequency ablation was considered, however, this approach was decided not to be optimal due to the proximity to stomach, and pancreatic duct. The patient was treated with SMART for 40 Gray in 5 fractions. Two and a half years later, the patient remains without evidence of disease progression. She experienced Grade 2 acute and late toxicity that was successfully managed with medications. This experience shows that SMART is a feasible and effective treatment to control theabdominal oligometastatic disease for breast cancer.

Purpose To develop a practical workflow for retrospectively analyzing target and normal tissue dose–volume endpoints for various intensity modulated radiation therapy (IMRT) delivery techniques; to develop technique-specific planning goals to improve plan consistency and quality when feasible. Methods and Materials A total of 165 consecutive head-and-neck patients from our patient registry were selected and retrospectively analyzed. All IMRT plans were generated using the same dose–volume guidelines for TomoTherapy (Tomo, Accuray), TrueBeam (TB, Varian) using fixed-field IMRT (TB_IMRT) or RAPIDARC (TB_RAPIDARC), or Siemens Oncor (Siemens_IMRT, Siemens). A MATLAB-based dose–volume extraction and analysis tool was developed to export dosimetric endpoints for each patient. With a fair stratification of patient cohort, the variation of achieved dosimetric endpoints was analyzed among different treatment techniques. Upon identification of statistically significant variations, technique-specific planning goals were derived from dynamically accumulated institutional data. Results Retrospective analysis showed that although all techniques yielded comparable target coverage, the doses to the critical structures differed. The maximum cord doses were 34.1 ± 2.6, 42.7 ± 2.1, 43.3 ± 2.0, and 45.1 ± 1.6 Gy for Tomo, TB_IMRT, TB_RAPIDARC, and Siemens_IMRT plans, respectively. Analyses of variance showed significant differences for the maximum cord doses but no significant differences for other selected structures among the investigated IMRT delivery techniques. Subsequently, a refined technique-specific dose–volume guideline for maximum cord dose was derived at a confidence level of 95%. The dosimetric plans that failed the refined technique-specific planning goals were reoptimized according to the refined constraints. We observed better cord sparing with minimal variations for the target coverage and other organ at risk sparing for the Tomo cases, and higher parotid doses for C-arm linear accelerator–based IMRT and RAPIDARC plans. Conclusion Patient registry–based processes allowed easy and systematic dosimetric assessment of treatment plan quality and consistency. Our analysis revealed the dependence of certain dosimetric endpoints on the treatment techniques. Technique-specific refinement of planning goals may lead to improvement in plan consistency and plan quality.

Purpose To perform a preliminary exploration with a simplistic mathematical cancer stem cell (CSC) interaction model to determine whether the tumor-intrinsic heterogeneity and dynamic equilibrium between CSCs and differentiated cancer cells (DCCs) can better explain radiation therapy treatment response with a dual-compartment linear-quadratic (DLQ) model. Methods and Materials The radiosensitivity parameters of CSCs and DCCs for cancer cell lines including glioblastoma multiforme (GBM), non–small cell lung cancer, melanoma, osteosarcoma, and prostate, cervical, and breast cancer were determined by performing robust least-square fitting using the DLQ model on published clonogenic survival data. Fitting performance was compared with the single-compartment LQ (SLQ) and universal survival curve models. The fitting results were then used in an ordinary differential equation describing the kinetics of DCCs and CSCs in response to 2- to 14.3-Gy fractionated treatments. The total dose to achieve tumor control and the fraction size that achieved the least normal biological equivalent dose were calculated. Results Smaller cell survival fitting errors were observed using DLQ, with the exception of melanoma, which had a low α/β = 0.16 in SLQ. Ordinary differential equation simulation indicated lower normal tissue biological equivalent dose to achieve the same tumor control with a hypofractionated approach for 4 cell lines for the DLQ model, in contrast to SLQ, which favored 2 Gy per fraction for all cells except melanoma. The DLQ model indicated greater tumor radioresistance than SLQ, but the radioresistance was overcome by hypofractionation, other than the GBM cells, which responded poorly to all fractionations. Conclusion The distinct radiosensitivity and dynamics between CSCs and DCCs in radiation therapy response could perhaps be one possible explanation for the heterogeneous intertumor response to hypofractionation and in some cases superior outcome from stereotactic ablative radiation therapy. The DLQ model also predicted the remarkable GBM radioresistance, a result that is highly consistent with clinical observations. The radioresistance putatively stemmed from accelerated DCC regrowth that rapidly restored compartmental equilibrium between CSCs and DCCs.

OBJECTIVE:To evaluate variations in intra- and interfractional tumour motion, and the effect on internal target volume (ITV) contour accuracy, using deformable image registration of real-time two-dimensional-sagittal cine-mode MRI acquired during lung stereotactic bodyradiation therapy (SBRT) treatments. METHODS:Five lung tumour patients underwent free-breathing SBRT treatments on the ViewRay system, with dose prescribed to a planning target volume (defined as a 3-6 mm expansion of the 4DCT-ITV). Sagittal slice cine-MR images (3.5 × 3.5 mm2 pixels) were acquired through the centre of the tumour at 4 frames per second throughout the treatments (3-4 fractions of 21-32 min). Tumour gross tumour volumes (GTVs) were contoured on the first frame of the MR cine and tracked for the first 20 min of each treatment using offline optical-flow based deformable registration implemented on a GPU cluster. A ground truth ITV (MR-ITV20min) was formed by taking the union of tracked GTV contours. Pseudo-ITVs were generated from unions of the GTV contours tracked over 10 s segments of image data (MR-ITV10s). RESULTS:Differences were observed in the magnitude of median tumour displacement between days of treatments. MR-ITV10s areas were as small as 46% of the MR-ITV20min. CONCLUSION:An ITV offers a "snapshot" of breathing motion for the brief period of time the tumour is imaged on a specific day. Real-time MRI over prolonged periods of time and over multiple treatment fractions shows that ITV size varies. Further work is required to investigate the dosimetric effect of these results. Advances in knowledge: Five lung tumour patients underwent free-breathing MRI-guided SBRT treatments, and their tumours tracked using deformable registration of cine-mode MRI. The results indicate that variability of both intra- and interfractional breathing amplitude should be taken into account during planning of lung radiotherapy.

Background and purpose Growing evidence suggested the coexistence of cancer stem cells (CSCs) within solid tumors. We aimed to study radiosensitivity parameters for the CSCs and differentiated tumor cells (TCs) and the correlation of the fractions of CSCs to the overall tumor radioresistance. Material and methods Surviving fractions of breast cancer cell lines were analyzed using a dual-compartment Linear-quadratic model with independent fitting parameters: radiosensitive αTC, βTC, αCSC, βCSC, and fraction of CSCs f. The overall tumor radio-resistance, the biological effective doses and tumor control probability were estimated as a function of CSC fraction for different fractionation regimens. The pooled clinical outcome data were fitted to the single- and dual-compartment linear-quadric models. Results CSCs were more radioresistant characterized by smaller α compared to TCs: αTC = 0.1 ± 0.2, αCSC = 0.04 ± 0.07 for MCF-7 (f = 0.1%), αTC = 0.08 ± 0.25, αCSC = 0.04 ± 0.18 for SUM159PT (f = 2.46%). Higher f values were correlated with increasing radioresistance in cell lines. Analysis of clinical outcome data is in accordance of a dual-compartment CSC model prediction. Higher percentage of BCSCs resulted in more overall tumor radioresistance and less biological effectiveness. Conclusions Percentage of CSCs strongly correlated to overall tumor radioresistance. This observation suggested potential individualized radiotherapy to account for heterogeneous population of CSCs and their distinct radiosensitivity for breast cancer.

Purpose Lung diseases are commonly associated with changes in lung tissue's biomechanical properties. Functional imaging techniques, such as elastography, have shown great promise in measuring tissue's biomechanical properties, which could expand the utility and effectiveness of radiotherapy treatment planning. We present a novel methodology for characterizing a key biomechanical property, parenchymal elasticity, derived solely from 4DCT datasets. Methods Specifically, end-inhalation and end-exhalation breathing phases of the 4DCT datasets were deformably registered and the resulting displacement maps were considered to be ground-truth. A mid-exhalation image was also prepared for verification purposes. A GPU-based biomechanical model was then generated from the patient end-exhalation dataset and used as a forward model to iteratively solve for the elasticity distribution. Displacements at the surface of the lungs were applied as boundary constraints for the model-guided tissue elastography, while the inner voxels were allowed to deform according to the linear elastic forces within the biomechanical model. A convergence criteria of 10% maximum deformation was employed for the iterative process. Results The lung tissue elasticity estimation was documented for a set of 15 4DCT patient datasets. Maximum lung deformations were observed to be between 6 and 31 mm. Our results showed that, on average, 89.91 ± 4.85% convergence was observed. A validation study consisting of mid-exhalation breathing phases illustrated an accuracy of 87.13 ± 10.62%. Structural similarity, normalized cross-correlation, and mutual information were used to quantify the degree of similarity between the following image pairs: (a) the model-generated end-exhalation and ground-truth end-exhalation, and (b) model-generated mid-exhalation images and ground-truth mid-exhalation. Conclusions Overall, the results suggest that the lung elasticity can be measured with approximately 90% convergence using routinely acquired clinical 4DCT scans, indicating the potential for a lung elastography implementation within the radiotherapy clinical workflow. The regional lung elasticity found here can lead to improved tissue sparing radiotherapy treatment plans, and more precise monitoring of treatment response.

Purpose To optimize and evaluate the respiratory motion-resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK-4D-MRI) method in a 0.35 T MRI-guided radiotherapy (MRgRT) system. Methods and materials The study included seven patients with abdominal tumors treated on the MRgRT system. ROCK-4D-MRI and 2D-CINE, was performed immediately after one of the treatment fractions. Motion quantification based on 4D-MRI was compared with those based on 2D-CINE. The image quality of 4D-MRI was evaluated against 4D-CT. The gross tumor volumes (GTV) were defined based on individual respiratory phases of both 4D-MRI and 4D-CT and compared for their variability over the respiratory cycle. Result The motion measurements based on 4D-MRI matched well with 2D-CINE, with differences of 1.04 ± 0.52 mm in the superior–inferior and 0.54 ± 0.21 mm in the anterior–posterior directions. The image quality scores of 4D-MRI were significantly higher than 4D-CT, with better tumor contrast (3.29 ± 0.76 vs. 1.86 ± 0.90) and less motion artifacts (3.57 ± 0.53 vs. 2.29 ± 0.95). The GTVs were more consistent in 4D-MRI than in 4D-CT, with significantly smaller GTV variability (9.31 ± 4.58% vs. 34.27 ± 23.33%). Conclusion Our study demonstrated the clinical feasibility of using the ROCK-4D-MRI to acquire high quality, respiratory motion-resolved 4D-MRI in a low-field MRgRT system. The 4D-MRI image could provide accurate dynamic information for radiotherapy treatment planning.

Purpose: To develop a practical triggering system based on pre‐selected respiratory amplitudes to guide prospectively the image acquisition of 4DMRI to track abdominal tumor motion for radiotherapytreatment planning.Methods: The proposed triggering scheme consists of a preparation stage and an acquisition stage. Immediately prior to MRI acquisition, the preparation stage monitors the respiration via an external respiratory belt. Based on the respiratory amplitude and status (i.e., inhalation↑ or exhalation↓), the respiration cycle is equally divided into N respiratory states. For example, in the 4‐state case, the 4 respiratory states are 5%↓″, 50%↑, 95%↑ and 50%↓. The 5%↓ and 95%↑ are used instead of 0% and 100% to improve the robustness of the triggering system. Each state is associated with a trigger which starts image acquisition for one and only one slice. A complete 4DMRI imageset requires N dynamic scans. In each dynamic scan, all slices are acquired once and each is in a specific respiratory state. In different dynamic scans, each slice is associated with different respiratory states to form a 4D dataset. For proof‐of‐principle, the triggering system was integrated into a T2‐weighted turbo spin echo sequence (TE=100ms, TR=7122ms) on a clinical 1.5T MRI (Philips Achieva) scanner. The 4‐state case was tested on a healthy subject. Results: Plots of the physiology data recorded and exported from the scanner clearly verified that triggers occurred at the expected locations. Four T2‐weighted images from a representative slice recorded the liver motion corresponding to the 4 respiratory states. Conclusions: Our results confirmed that the newly‐developed system could trigger prospectively to guide 4DMRI image acquisition to achieve T2 weighting, which has a better tumor‐tissue contrast than those offered by previous 4DMRI techniques with T1 or T2/T1 weighting. This is a first report of a pure T2‐weighted 4DMRI to track respiration induced abdominal motion.

Purpose: To validate a four‐dimensional radiotherapy (4DRT) planning based on a synthesized CT image compensating for tumor motion, accounting for tumor rotation, deformation and distortion due to motion artifacts, and producing realistic normal tissue density in motion‐tracking beam eye view. Methods: 4D computed tomography (4DCT) images of six patients with peripheral lung lesions in mid or lower lobs (motion range: 0.5–3.5cm and size: 1.5±2.0 cm(3)) were used. A customized program was used for simulating the patient anatomy with a motion‐compensated tumor using 4DCT by aligning the tumor and averaging the 4DCT into a static 3.5DCT image. The gross tumor volume (GTV) was delineated semiautomatically using a threshold algorithm. Variation of GTV in each phase CT was assessed across all phases. 3DRT plans were generated using 3.5DCT and 4DCT and compared for validation. An integrated dose volume histogram (iDVH) from all phase plans and dose warping using deformable image registration (DIR) were used for evaluating 4D plans and comparing with 3.5D plans. Results: The range of tumor volume variation over the mean within a breathing cycle was 87%±46%. The 3.5DCT produced an ‘averaged’ GTV, more reliable than that from any phase CT. The results show that the 3.5D plan is equivalent to the 4D plan, except for low dose area, using the iDVH evaluation. On average, the percentage difference for the areas under the DVH and iDVH is 4.3%±2.7%, while 2/3 of the difference results from low dose region blow D20%. Using DIR‐based dose warping, PTV coverage varies due to DIR uncertainty for the small lesions. Conclusions: The 3.5D plan is equivalent to the 4D plan for peripheral lung lesions, yet requires much less clinical workload. The 3.5D plan accounts for tumor motion and tumor variation for a more reliable delineation, and for realistic normal tissue representation for motion tracking.

TPS786 Background: Standard dose radiation therapy has been unsuccessful in inoperable pancreatic cancer; with a negative study (LAP07) for conventional chemoradiation and dropping of the stereotactic body radiation therapy arm in Alliance A021501. Recently, reports of using high dose ablative radiation therapy has been associated with increased survival in retrospective studies. Moreover, technological advances with MRI-guided radiation therapy offer improved targeting and the ability to change the radiation delivery on a daily fashion; allowing ablative radiation doses over one week. However, it is not clear whether this can be done safely on a multiinstitutional basis. Methods: We are conducting the largest prospective study of ablative radiation therapy in pancreatic cancer. The study is a single arm, multi-institutional phase II, industry sponsored study to investigate the safety and efficacy of Stereotactic, MR guided, on-table-Adaptive Radiation Therapy (SMART). Eligibility criteria include locally advanced and borderline resectable pancreatic cancer patients with ECOG PS of 0 or 1; who have non-metastatic disease after a minimum of 3 months of any systemic therapy; including investigational agents. Patients will receive MR-guided radiation therapy to a dose of 50 Gy / 5 fractions; with maximum tumor coverage delivered each fraction that allows keeping the gastrointestinal organs at risk to a dose of 33 Gy or less. Primary endpoint is grade 3 of higher gastrointestinal toxicity at 90 days. Secondary endpoints are overall survival at 2 years, distant progression free survival at 6 months, and changes in patient related quality of life at 3 and 12 months. Target sample size was calculated to show at a significance level 0.05, a reduction of the toxicity rate to 8% or lower by using SMART compared with 15.8%, the toxicity rate of conventionally delivered chemoradiation at a power level 0.8. Given an expected 15% drop-out, the enrollment goal is 133. Descriptive statistics will be used for secondary objectives. The study opened in January, 2019 and is currently opened at 4 centers; with other US and international sites pending. Sponsored by Viewray, Inc. Clinical trial information: NCT03621644.

Purpose: Validating the usage of deformable image registration (dir) for daily patient positioning is critical for adaptive radiotherapy (RT) applications pertaining to head and neck (HN) radiotherapy. The authors present a methodology for generating biomechanically realistic ground-truth data for validating dir algorithms for HN anatomy by (a) developing a high-resolution deformable biomechanical HN model from a planning CT, (b) simulating deformations for a range of interfraction posture changes and physiological regression, and (c) generating subsequent CT images representing the deformed anatomy. Methods: The biomechanical model was developed using HN kVCT datasets and the corresponding structure contours. The voxels inside a given 3D contour boundary were clustered using a graphics processing unit (GPU) based algorithm that accounted for inconsistencies and gaps in the boundary to form a volumetric structure. While the bony anatomy was modeled as rigid body, the muscle and soft tissue structures were modeled as mass–spring-damper models with elastic material properties that corresponded to the underlying contoured anatomies. Within a given muscle structure, the voxels were classified using a uniform grid and a normalized mass was assigned to each voxel based on its Hounsfield number. The soft tissue deformation for a given skeletal actuation was performed using an implicit Euler integration with each iteration split into two substeps: one for the muscle structures and the other for the remaining soft tissues. Posture changes were simulated by articulating the skeletal structure and enabling the soft structures to deform accordingly. Physiological changes representing tumor regression were simulated by reducing the target volume and enabling the surrounding soft structures to deform accordingly. Finally, the authors also discuss a new approach to generate kVCT images representing the deformed anatomy that accounts for gaps and antialiasing artifacts that may be caused by the biomechanical deformation process. Accuracy and stability of the model response were validated using ground-truth simulations representing soft tissue behavior under local and global deformations. Numerical accuracy of the HN deformations was analyzed by applying nonrigid skeletal transformations acquired from interfraction kVCT images to the model’s skeletal structures and comparing the subsequent soft tissue deformations of the model with the clinical anatomy. Results: The GPU based framework enabled the model deformation to be performed at 60 frames/s, facilitating simulations of posture changes and physiological regressions at interactive speeds. The soft tissue response was accurate with a R 2 value of >0.98 when compared to ground-truth global and local force deformation analysis. The deformation of the HN anatomy by the model agreed with the clinically observed deformations with an average correlation coefficient of 0.956. For a clinically relevant range of posture and physiological changes, the model deformations stabilized with an uncertainty of less than 0.01 mm. Conclusions: Documenting dose delivery for HN radiotherapy is essential accounting for posture and physiological changes. The biomechanical model discussed in this paper was able to deform in real-time, allowing interactive simulations and visualization of such changes. The model would allow patient specific validations of the dir method and has the potential to be a significant aid in adaptive radiotherapy techniques.

Radiographic changes occur in over half of patients treated with stereotactic body radiotherapy (SBRT) to the lung, correlating histopathologically with injury. We quantified radiographic density changes (ie, fibrosis) at 3, 6, and 12 months and investigated the relationship between these volumes and clinical and dosimetric parameters. The study population consisted of patients treated with SBRT to the lung for stage I primary lung cancers (n = 39) or oligometastatic lesions (n = 17). Fractionation schemes included 3 fractions of 12, 14, or 18 gray (Gy) and 4 fractions of 12 or 12.5 Gy prescribed to cover 95% of the planning target volume (PTV). Planning computed tomography (CT) scans were rigidly registered to follow-up CT scans obtained at intervals of 3, 6, and 12 months. Fibrotic volumes were contoured on the follow-up scans. Associations between the volume of fibrosis and clinical and dosimetric parameters were investigated using univariate linear regression. Scans were available for 65 and 47 lesions at 6 and 12 months, respectively. Age, years since quitting smoking, and GOLD Global Initiative for Chronic Obstructive Lung Disease score were significantly associated with increasing volume of fibrosis (P < .05). Total dose, dose per fraction, PTV, and volumetric parameters (V0-V55) were also significantly associated with increasing volumes of fibrosis (P < .01). For dosimetric parameters, the effect was largest for V55. Age, significant smoking history, and GOLD score were significantly associated with increasing volumes of fibrosis following SBRT. In a multivariate model adjusted for age and smoking history, V10 through V50 and PTV size remained significant predictors of fibrotic volume. Further, there is a strong dose-response relationship between the volume of lung exposed to a certain dose and the fibrotic volume. The predominant kinetic patterns of fibrosis demonstrate peaking fibrotic volumes at 6 and 12 months. These results provide insight for expectations of fibrosis after SBRT.

Purpose To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments.

Purpose To investigate the dosimetric improvements in stereotactic body radiation therapy for patients with larger or central lung tumors using a highly noncoplanar 4π planning system. Methods and Materials This study involved 12 patients with centrally located or larger lung tumors previously treated with 7- to 9-field static beam intensity modulated radiation therapy to 50 Gy. They were replanned using volumetric modulated arc therapy and 4π plans, in which a column generation method was used to optimize the beam orientation and the fluence map. Maximum doses to the heart, esophagus, trachea/bronchus, and spinal cord, as well as the 50% isodose volume, the lung volumes receiving 20, 10, and 5 Gy were minimized and compared against the clinical plans. A dose escalation study was performed to determine whether a higher prescription dose to the tumor would be achievable using 4π without violating dose limits set by the clinical plans. The deliverability of 4π plans was preliminarily tested. Results Using 4π plans, the maximum heart, esophagus, trachea, bronchus and spinal cord doses were reduced by 32%, 72%, 37%, 44%, and 53% ( P ≤.001), respectively, and R 50 was reduced by more than 50%. Lung V 20 , V 10 , and V 5 were reduced by 64%, 53%, and 32% ( P ≤.001), respectively. The improved sparing of organs at risk was achieved while also improving planning target volume (PTV) coverage. The minimal PTV doses were increased by the 4π plans by 12% ( P =.002). Consequently, escalated PTV doses of 68 to 70 Gy were achieved in all patients. Conclusions We have shown that there is a large potential for plan quality improvement and dose escalation for patients with larger or centrally located lung tumors using noncoplanar beams with sufficient quality and quantity. Compared against the clinical volumetric modulated arc therapy and static intensity modulated radiation therapy plans, the 4π plans yielded significantly and consistently improved tumor coverage and critical organ sparing. Given the known challenges in central structure dose constraints in stereotactic body radiation therapy to the lung, 4π planning may increase efficacy and reduce toxicity.

Purpose To report a single-institutional experience using magnetic resonance imaging (MRI) guided radiation therapy for the reirradiation of recurrent and second cancers of the head and neck. Methods and materials Between October 2014 and August 2016, 13 consecutive patients with recurrent or new primary cancers of the head and neck that occurred in a previously irradiated field were prospectively enrolled in an institutional registry trial to investigate the feasibility and efficacy of MRI guided radiation therapy using a 0.35-T MRI scanner with a cobalt-60 radiation therapy source called the ViewRay system (ViewRay Inc., Cleveland, OH). Eligibility criteria included biopsy-proven evidence of recurrent or new primary squamous cell carcinoma of the head and neck, measurable disease, and previous radiation to >60 Gy. MRI guided reirradiation was delivered either using intensity modulated radiation therapy with conventional fractionation to a median dose of 66 Gy or stereotactic body radiation therapy (SBRT) using 7 to 8 Gy fractions on nonconsecutive days to a median dose of 40 Gy. Two patients (17%) received concurrent chemotherapy. Results The 1- and 2-year estimates of in-field control were 72% and 72%, respectively. A total of 227 daily MRI scans were obtained to guide reirradiation. The 2-year estimates of overall survival and progression-free survival were 53% and 59%, respectively. There were no treatment-related fatalities or hospitalizations. Complications included skin desquamation, odynophagia, otitis externa, keratitis and/or conjunctivitis, and 1 case of aspiration pneumonia. Conclusions Our preliminary findings show that reirradiation with MRI guided radiation therapy results in effective disease control with relatively low morbidity for patients with recurrent and second primary cancers of the head and neck. The superior soft tissue resolution of the MRI scans that were used for planning and delivery has the potential to improve the therapeutic ratio.

ObjectiveTo evaluate the feasibility of on-board diffusion-weighted imaging (DWI) with an integrated low-field MRI radiotherapy system to assess responses to neoadjuvant chemoradiation (NAC) in rectal cancer.MethodsA spin echo-based planar imaging diffusion sequence on a 0.35-T MRI radiotherapy system was acquired over the course of NAC. The apparent diffusion coefficients (ADCs) from the tumour regions of interest (ROIs) were calculated. A functional diffusion map (fDM) was created showing a pixelwise ADC analysis of the ROI over the course of treatment. Surgical pathology was correlated with ADC data.ResultsConsecutive patients treated on a 0.35-T MRI radiotherapy system were evaluated. Patient A had the worst pathological response to NAC with a tumour regression score of 1 and was the only patient with a negative slope in the change of ADC values over the entire course of NAC, and during both the first and second half of NAC. The fDM from the first half of NAC for Patient A showed discrete dark areas in the tumour ROI, reflecting subregions with decreasing ADC values during NAC. Patient C had the most favourable pathological response to NAC with a Grade 3 response and was the only patient who had an increase in the slope in the change of ADC values from the first to the second half of NAC.ConclusionDWI using a low-field MRI radiotherapy system for evaluating the responses to NAC is feasible. Advances in knowledge: ADC values obtained using a 0.35-T MRI radiotherapy system over the course of NAC for rectal cancer correlate with pathological responses.

Magnetic Resonance Imaging (MRI) has been a part of radiation therapy for many years, but its role is expanding. MR provides soft tissue contrast that is superior to what can be obtained with computed tomography (CT), the modality used most often to support radiation therapy treatment simulation. There are a number of critical challenges to employing MR for simulation imaging, namely the reduced spatial fidelity, and the lack of a direct relationship between MR image values and electron density, a quantity needed for dose calculations, as well as a difference between MR image values and the attenuation of kV X-rays, used to aid in patient positioning. These challenges are being met by clinics and companies, to the extent that the exclusive use of MR for simulation is now possible in a number of treatment sites. While MR has been used for simulation, it has only recently been introduced into the treatment room. Integrating MR with patient positioning and monitoring before and during treatment, respectively, would potentially improve radiation therapy treatment accuracy, enabling tighter uncertainty margins and ultimately improving outcomes. The challenges of integrating a MRI system with radiation treatment delivery have been recently met by radiation therapy equipment manufacturers, providing the radiation oncology community with an opportunity to deliver radiation doses with unparalleled accuracy.