INTRODUCTION:Consensus contouring guidelines for intensity-modulated-radiation-therapy (IMRT) of patients with locally advanced cervix cancer (LACC) advise including the whole uterus in the target volume and adding generous planning-target-volumes (PTVs) to account for motion uncertainties of the gross-tumor-volume (GTV). The primary objective of this analysis was to assess the interfractional GTV motions using a magnetic-resonance-image (MRI) guided-Radiation-Therapy (MRgRT) system to investigate the margins required for MRgRT treatments. METHODS:125 daily set-up MRIs from five patients with LACC who received MRgRT were analyzed. The GTV, bladder, uterus, and rectum were contoured on all 125 MRIs. Tumor volume changes were calculated in cubic-centimeters (cc). The positional and volume changes of organs-at-risk (OARs) were calculated to assess their effect on GTV interfractional motion, these data were used to calculate adequate PTV margins. RESULTS:The tumor volume decreased in size during the course of MRgRT for all patients, from 34.0 % to 85.2 %. The interfractional average GTV displacement ranged from 0.46 cm to 0.94 cm. The PTV margins required were: 0.78 cm Left-Right, 1.31 cm Anterior-Posterior and 1.38 cm for the Superior-Inferior directions. The proposed PTV margins, compared to those recommended by consensus guidelines, reduce the PTV by 38 % sparing both the sigmoid and bowel OARs. CONCLUSIONS:By utilizing daily onboard MRI guidance, the GTV becomes readily visualized, allowing for margin reduction and potentially excluding a portion of the uterine fundus from the PTV. The amount of interfractional motion demonstrated in this study is considerable and clinically significant with the goal of decreasing treatment toxicity while maintaining tumor control. SUMMARY:Daily pretreatment magnetic resonance images (MRIs) from patients with locally advanced cervix cancer (LACC) treated with on-board MR-guided radiation therapy (MRgRT) were analyzed to quantify the range of interfractional motion and develop target volume guidelines for adaptive MRgRT. MRI-guidance leads to better tumor visualization in comparison to cone beam computed tomography (CBCT), and online adaptive planning can account for the interfraction motion of the tumor and surrounding tissue. MRI's ability to better visualize the disease and pelvic anatomy along with adaptive on-board MRgRT could allow for a reduction in the required setup margins as well as potentially excluding non-diseased portions of the uterus from the target volumes. These changes will lead to reduced treatment volumes and may lead to decreased treatment toxicities and allow for dose escalation in certain circumstances.

Background/HypothesisMRI-guided online adaptive radiotherapy (MRI-g-OART) improves target coverage and organs-at-risk (OARs) sparing in radiation therapy (RT). For patients with locally advanced cervical cancer (LACC) undergoing RT, changes in bladder and rectal filling contribute to large inter-fraction target volume motion. We hypothesized that deep learning (DL) convolutional neural networks (CNN) can be trained to accurately segment gross tumor volume (GTV) and OARs both in planning and daily fractions’ MRI scans.Materials/MethodsWe utilized planning and daily treatment fraction setup (RT-Fr) MRIs from LACC patients, treated with stereotactic body RT to a dose of 45-54 Gy in 25 fractions. Nine structures were manually contoured. MASK R-CNN network was trained and tested under three scenarios: (i) Leave-one-out (LOO), using the planning images of N- 1 patients for training; (ii) the same network, tested on the RT-Fr MRIs of the “left-out” patient, (iii) including the planning MRI of the “left-out” patient as an additional training sample, and tested on RT-Fr MRIs. The network performance was evaluated using the Dice Similarity Coefficient (DSC) and Hausdorff distances. The association between the structures’ volume and corresponding DSCs was investigated using Pearson’s Correlation Coefficient, r.ResultsMRIs from fifteen LACC patients were analyzed. In the LOO scenario the DSC for Rectum, Femur, and Bladder was >0.8, followed by the GTV, Uterus, Mesorectum and Parametrium (0.6-0.7). The results for Vagina and Sigmoid were suboptimal. The performance of the network was similar for most organs when tested on RT-Fr MRI. Including the planning MRI in the training did not improve the segmentation of the RT-Fr MRI. There was a significant correlation between the average organ volume and the corresponding DSC (r = 0.759, p = 0.018).ConclusionWe have established a robust workflow for training MASK R-CNN to automatically segment GTV and OARs in MRI-g-OART of LACC. Albeit the small number of patients in this pilot project, the network was trained to successfully identify several structures while challenges remain, especially in relatively small organs. With the increase of the LACC cases, the performance of the network will improve. A robust auto-contouring tool would improve workflow efficiency and patient tolerance of the OART process.

Residency candidate selection in radiation oncology has traditionally consisted of formal in-person interviews, which occur in groups, each over 1 to 2 days. This format was largely adopted due to the efficiency it provided programs in interviewing the most applicants in a given day and reducing faculty time away from clinical responsibilities. However, because of the ongoing threat of severe acute respiratory syndrome coronavirus–2, or coronavirus disease 2019, and the associated social distancing measures, the Association of American Medical Colleges, the Accreditation Council for Graduate Medical Education, and the National Resident Matching Program have recommended virtual interviews for the 2020 to 2021 residency application cycle.

IMPORTANCE A large proportion of extremity soft-tissue sarcomas (ESS) occur among young adults, yet this group is underrepresented in clinical trials, resulting in limited data on this population. Younger patients present many complex challenges that affect clinical management. Objective To investigate variations in treatment management in young adults vs older adults with ESS. DESIGN, SETTING, AND PARTICIPANTS This multicenter retrospective cohort study used the National Cancer Data Base (NCDB) to identify patients 18 years and older with ESS who received definitive treatment (ie, limb-sparing surgery [LSS] or amputation) between 2004 and 2014. Data analysis was conducted in November 2019. EXPOSURES Treatment regimen received among young adults (aged 18-39 years) and older adults (>= 40 years) after diagnosis with ESS. MAIN OUTCOMES AND MEASURES To detect unique factors associated with treatment decisions in young adults with ESS, multivariable analyses used logistic regressions for patterns of treatment and their association with demographic factors and tumor characteristics. RESULTS Overall, 8953 patients were identified, and among these, 1280 (14.3%) were young adults. From the full cohort, 4796 patients (53.6%) identified as male and 6615 (73.9%) identified as non-Hispanic White. More young adults than older adults underwent amputation (age 18-39 years, 104 of 1280 [8.1%]; age 40-64 years, 217 of 3937 [5.5%]; aged >= 65 years, 199 of 3736 [5.3%]), but the association was not statistically significant (age >= 65 years, odds ratio [OR], 1.49; 95% CI, 1.00-2.23; P = .05). Young adults were more likely to receive chemotherapy than older patients (age 40-65 years, OR, 0.52; 95% CI, 0.45-0.60; P = .001; >= 65 years, OR, 0.16; 95% CI, 0.12-0.20; P = .001). Conversely, young adults were less likely to receive radiation therapy compared with older patients (age 40-65 years, OR, 1.40; 95% CI, 1.22-1.61; P = .001; >= 65 years, OR, 1.33; 95% CI, 1.10-1.61; P = .003). Unique to younger adults, clinical stage II disease vs stage I and positive surgical margins were not associated with use of radiation therapy (stage II disease: OR, 1.25; 95% CI, 0.81-1.91; P = .31; positive surgical margins: OR, 1.43; 95% CI, 0.93-2.22; P = .11). White Hispanic young adults were less likely than non-Hispanic White young adults to receive radiation therapy (OR, 0.53; 95% CI, 0.36-0.78; P = .002). CONCLUSIONS AND RELEVANCE In this study, young adults with ESS were more likely to receive chemotherapy and less likely to receive radiation therapy than older adults. Further study is warranted to identify the clinical outcomes of these practice disparities.

Most sarcomas occur in the adolescent and young adult (AYA) population, ages 15-39, but compared to both children and older adults, the AYA population is under enrolled on clinical trials. It was hypothesized that the National Cancer Database (NCDB) could detect factors influencing receipt of chemotherapy (CHT) and/or radiation therapy (RT) before or after limb-sparing surgery for extremity soft tissue sarcomas (ESS) that were unique to AYAs compared to other adults. To evaluate for unique disparities impacting AYAs who receive LSS for ESS and the receipt of CHT and/or RT. The NCDB was utilized to identify patients (pts) with ESS diagnosed between 2004-2014 and treated definitively with LSS +/- RT +/- CHT. Multivariate analyses used logistic regressions for patterns of treatment and their relationship with tumor characteristics (primary site, grade, size, clinical stage, depth of extension, and surgical margins) and patient factors (sex, race, ethnicity, insurance status, income, education, distance from hospital, and transitions in care). 8201 pts in total were identified having received LSS and among these, 1141 were AYA. There were no significant differences between the age groups in incidence of ESS of upper (UE) versus lower extremity (LE), overall with 24.7% UE and 75.3% LE. Compared to older adults, fewer AYAs received RT (64.4% of AYAs versus 73.1% of adults age 40-60 years old (yo), p<0.001) and more received CHT (39.1% versus 29.8% of adults age 40-60, p<0.001). 10.3% of AYAs received LSS and CHT only without any radiation. This compares to 5.6% of adults 40-60 yo and only 2.1% of adults >60 yo. Receipt of RT was associated with size and deep tumor extension (5.01-10.0 cm compared to 5.00 cm or less, OR 1.30 (1.12-1.51), p<0.001, and OR 1.37 (1.22-1.53), p<0.001). On multivariate analysis, patients with private insurance were more likely to receive pre-LSS RT and CHT compared to those uninsured (OR 2.30 (1.41-3.76, p<0.001)). For AYAs, receipt of RT was not associated with grade, surgical margin status, and clinical stage. Non-black Hispanic AYAs had greater odds of receiving LSS + CHT without radiation (OR 1.65 (1.08-2.50, p<0.019). 10.9% of AYAs received CHT and pre-LSS RT and 17.9% received CHT and post-LSS RT. There are unique circumstances among AYAs receiving LSS for ESS that may impact definitive management. AYAs are more likely to receive chemotherapy alone and more likely to have RT omitted than older adults. Further study is warranted to investigate these disparities in management and our group plans to investigate factors impacting referrals to radiation oncology among AYAs with ESS.

The novel coronavirus disease 2019 (COVID-19) is a rapidly spreading and potentially fatal viral disease that has been recognized as a pandemic-causing agent in 2020. Adapting patient care to the changing environment is critical to mitigating public health risks and often includes alterations to trainee-level curricula. The National Institutes of Health has released interim guidelines for health care institutions across the nation on strategies to cope with COVID-19 and minimize its risk to patients and clinicians.1Coronavirus (COVID-19). National Institutes of Health.https://www.nih.gov/health-information/coronavirusGoogle Scholar Within the field of radiation oncology, responses have largely been dictated by individual institutions, although the American Society of Radiation Oncology has released general guidelines.2Summary - COVID-19 Resources - American Society for Radiation Oncology (ASTRO) - American Society for Radiation Oncology (ASTRO). ASTRO.https://www.astro.org/Daily Practice/COVID-19-Recommendations-and-Information/SummaryGoogle Scholar With a focus on resident training, we report our first-hand experience of how 4 major academic radiation oncology programs in Florida have instituted changes to address the COVID-19 pandemic and safely care for their vulnerable patients with cancer. We also discuss the dilemma associated with residency training and evaluate the role of residents in the radiation oncology clinic setting. The radiation oncology departments of the H. Lee Moffitt Cancer Center and Research Institute, Mayo Clinic in Jacksonville, University of Florida, and University of Miami Miller School of Medicine have each implemented significant changes to adapt to the new patient environment. Although some details of each departmental change differ (Table 1), there have been several common measures taken.Table 1Detailed radiation oncology departmental changesPatient prioritizationClinical encountersPatients receiving treatmentRadiation staffing changesExposure riskH. Lee Moffitt Cancer Center and Research Institute-Following modified guidelines based on the Ontario Pandemic Protocols-Triage by disease risk per guidelines-Delay treatments for up to 3 mo-Telehealth as much as possible-PDX at CT sim-Limited NPL, only with PPE-Delay RT for up to 3 mo when appropriate-Delay RT with medical management when appropriate-Hypofractionation encouraged-SFU consisting of ~5 attendings covering several disease sites; 1 attending from each SFU is in clinic per day-One in-person dosimetrist; all others work remotely-Physics team split to on-site and off-site duties-Schedulers and all assistants work remotely-Therapists following consistent shift schedule without crossover-All meetings conducted virtually-Consolidated hospital entrances and hours-Screening of everyone entering the hospital-No visitors allowed-Not treating COVID+ patients-Treat COVID-suspected patients at end of day-All patients and staff required to wear surgical masksMayo Clinic-Triage by disease risk-Delay all low-risk visits for 1-2 mo-Telehealth as much as possible-OTVs in person-RT delivered 7 days a week-Delay RT for up to 1-2 mo when appropriate-Hypofractionation encouraged-Skeleton crew of 2 teams for all staff; teams switch daily-Physics and dosimetry split to on-site and off-site duties-Consolidated LINACs and transitioned to 12-h therapist shifts-All meetings conducted virtually-Screening of everyone entering the hospital-One visitor allowed-Treat COVID+ patients at end of dayUniversity of Florida-Triage by disease risk-Delay low-risk consults and follow-ups for 1-2 mo-Telehealth as much as possible-PDX at CT sim-OTVs by attending only-Delay RT with medical management when appropriate-If treating COVID+ patients, plan to use a dedicated LINAC at the end of day-Hypofractionation encouraged-Attending clinic days condensed to 2-3 d per week-All imaging review and inpatient consults covered by 1 attending per day-All meetings conducted virtually-Screening of everyone entering the hospital-No hospitalized COVID+ patients currently under treatment-One visitor allowed-No children allowed unless they are the patientUniversity of Miami-Triage by disease risk-Delay low-risk consults and follow-ups-Telehealth as much as possible-Most results reviewed over phone-Delay RT with medical management when appropriate-Hypofractionation encouraged-All staff encouraged to work remotely-All meetings conducted virtually-Screening of all patients outside the hospital entrance-No visitors except with pediatric patients-All patients and staff required to wear surgical masksAbbreviations: COVID = coronavirus disease 2019; CT = computed tomography; LINAC = linear accelerator; NPL = nasopharyngolaryngoscopic examination; OTV = on-treatment visit; PDX = physical examination; PPE = personal protective equipment; RT = radiation therapy; SFU = superfunctional unit. Open table in a new tab Abbreviations: COVID = coronavirus disease 2019; CT = computed tomography; LINAC = linear accelerator; NPL = nasopharyngolaryngoscopic examination; OTV = on-treatment visit; PDX = physical examination; PPE = personal protective equipment; RT = radiation therapy; SFU = superfunctional unit. All institutions have adopted a triaging system to categorize the risk associated with a patient's cancer and potentially delay either the start of radiation therapy (RT) or initial clinic consult. The risk associated with delaying RT is often mitigated using medical management with hormone therapy, chemotherapy, and so forth, when clinically appropriate. All institutions have encouraged hypofractionation, transitioned at least some aspect of patient care to a telehealth format, moved all clinical and administrative meetings to a virtual media, and screen anyone who enters the hospital to determine their COVID-19 infection risk. Remote work is also strongly encouraged but the specific changes to department staffing vary. Lastly, the number of patient visitors is limited at each institution, with some prohibiting any visitors. Residents training in radiation oncology at these institutions have experienced changes to their educational experience, often for the purpose of protecting the trainees and patients (Table 2). There are several common measures taken by the programs. Residents are now limited in their ability to have in-person patient contact and in their time spent within radiation oncology departments. Which in-person patient encounter residents are involved with varies by institution and sometimes the attending physician. Remote work is strongly encouraged for all residents unless patient care duties dictate their presence within the departments. The clinical radiation oncology, physics, and radiation biology didactics courses are continuing at all institutions but through a virtual format. Any attending-lead teaching is conducted virtually when applicable (radiation contour and plan reviews, for example). Where residents may take their call from differs by institution, but inpatient consults are generally seen by the attending physicians only. All institutions have altered the timeline, format, or entirely cancelled residency-related activities including residency graduation ceremonies. Several institutions have developed redeployment strategies if additional clinicians are needed to help manage patients with COVID-19, but no residents have experienced redeployment to date. Residents are also provided with a variety of wellness resources to help manage the stressors associated with these changing times.Table 2Detailed radiation oncology residency changesPatient careRemote work and didacticsCall and inpatient consultsEvents and redeploymentWellnessH. Lee Moffitt Cancer Center and Research Institute-Limit in-person patient contact-No change in attending coverage: covering 1-2 per rotation-Attending performs PDX-No resident NPL examinations-Remoting strongly encouraged-All didactics performed virtually-In department only when necessary for patient care-Call taken while in department and consists of triaging duties but may be asked to assist the SFU attending-Inpatient consults seen by disease site team-Mock orals and annual Moffitt research symposium postponed-Graduation ceremonies cancelled-No redeployment to date-Daily wellness emails-Frequent virtual meetings about managing COVID patients for residents in all specialtiesMayo Clinic-Limit in-person patient contact-Temporarily crossover attendings to share the workload-Flexibility allotted to share workload among residents-Remoting strongly encouraged-All didactics performed virtually-In department only when necessary for patient care-Call taken from home-Only see inpatient consults if necessary-All Mayo Clinic resident social events cancelled-Any examinations to be delivered virtually-Graduation ceremonies cancelled-Deployment priority would be given to those closer to intern year-No redeployment to date-Refresher courses on placing orders, general internal medicine, and ICU proceduresUniversity of Florida-Limit in-person patient contact-Single attending coverage with consolidated clinic to 2-3 days-Attending only in-person routine follow-ups and OTVs-Residents participate in telehealth visits and in-person consults-No resident NPL examinations-Remoting strongly encouraged-All didactics performed virtually-In department only when necessary for patient care-Call taken while close to the hospital in case of emergencies-Only see emergent inpatient consults-Mock orals to be performed virtually-Graduation ceremonies likely cancelled-2 residents per week on call and ready to be redeployed if a surge occurs-If residents are pulled from clinic and redeployed, they will not have clinical duties the following week-No redeployment to date-Weekly virtual meetings with the program director-Free access to Talkspace for online therapy-Frequent emails from the University's Director of Wellness Programs regarding wellness, virtual support, and other similar resourcesUniversity of Miami-Limit in-person patient contact-Single attending coverage-Remoting strongly encouraged-All didactics performed virtually-In department only when necessary for patient care-Call taken from home-Unchanged call duties-Attendings evaluate inpatient consults alone unless the attending is at-risk-Nonemergent consults rescheduled as virtual outpatient visits-Mock orals likely postponed-Graduation ceremony plans uncertain-3 residents per 2-week block on call and ready to be redeployed if a surge occurs-No redeployment to date-Free virtual yoga, meditation, and stress management resources by local programs-Counselors made available-Free local hotel lodging for providers with concerns for family safetyAbbreviations: COVID = coronavirus disease 2019; ICU = intensive care unit; NPL = nasopharyngolaryngoscopic examination; OTV = on-treatment visit; PDX = physical examination; SFU = superfunctional unit. Open table in a new tab Abbreviations: COVID = coronavirus disease 2019; ICU = intensive care unit; NPL = nasopharyngolaryngoscopic examination; OTV = on-treatment visit; PDX = physical examination; SFU = superfunctional unit. Radiation oncology residents are experiencing a period of uncertainty with unclear roles as providers and trainees during the COVID-19 pandemic. Although radiation oncology is not a frontline specialty managing patients with COVID-19, the field cares for a vulnerable and at-risk population. As trainees, our in-person interaction with patients who may harbor COVID-19 unnecessarily places them and ourselves at risk. The use of personal protective equipment (PPE) offsets this risk but during a time of PPE shortage, and because all residents require attending physician oversight, the educational value of each patient interaction should be thoughtfully evaluated. Nevertheless, a prolonged decrease in resident-patient interaction could adversely affect resident training and affect our ability to practice independently in the future. This dynamic creates a dilemma regarding the ideal approach to residency training in the current climate. The residency programs described herein have taken several common measures to address this dilemma, and we applaud their implementation. We advocate for continued resident involvement in all aspects of patient care when performed through a virtual format. If institutions or patient scenarios do not allow for this format, in-person resident involvement should be evaluated with respect to the educational value of the encounter. For example, in-person on-treatment visits and follow-ups that are "routine" and involve no toxicity management or re-evaluation should not necessitate in-person resident involvement. The highest educational priority should be placed on patients due to start RT, and we encourage discussions between residents and their attendings regarding the value of hypofractionation for each case. Even if such cases occur in person, the resident may be able to remotely prepare for the consult, formulate their treatment recommendation, and generate the treatment plan without unnecessarily placing themselves or the patient at risk. As such, the need for a resident to see an in-person consult should be limited to when the clinical encounter provides additional information that affects the treatment plan. Regardless of the inherent educational value of the case, all clinical encounters that occur through a telehealth format should involve residents, as the use of this new media itself provides valuable experience. We do not support resident-performed invasive procedures such as nasopharyngolaryngoscopic examinations during the current pandemic state. All other physical examinations should be performed with proper PPE and only if they add value to clinical decision making. If possible, these should be performed at the time of computed tomography simulation to consolidate the frequency of patient and provider exposure. This recommendation follows our general ideology of eliminating duplicate exposure and minimizing wasteful PPE use. The transition of structured didactics to a virtual format should be seamless using widely available videoconferencing software. The utilization of this virtual format allows for continued training of residents while protecting staff within the department. As such, we advocate for its use for all structured didactics, case reviews, mock examinations, and treatment plan reviews. With the announcement of board examination delays, we emphasize continuing all curricula related to preparing residents for these examinations without interruption. Additionally, to offset the anticipated reduction in patient volume and resident clinical encounters, we encourage more frequent virtual case sessions to hone our clinical acumen. Given the uncertainties associated with this pandemic (eg, the possibility for redeployment to the frontlines, the risks to ourselves and loved ones, and anxiety related to the changing job market), resident wellness should be a deliberate discussion within departments. These changing factors may precipitate underlying anxiety or depression within the residents and feigning ignorance over their presence is not a viable solution. Even changes such as prolonged remote work may introduce feelings of isolation in a distinctly lonely environment, particularly for residents who moved to new cities for their training. Coupled with the cancellation or postponement of residency-related wellness activities or examinations, the stresses for residents may accumulate when they don't have access to their typical healthy outlets. We strongly urge programs to perform routine check-ins on residents both on a one-to-one and group basis. We also encourage residents to reach out to their colleagues and loved ones for support. For residents experiencing redeployment, we have provided a list of resources to aid in the clinical care of patients with COVID-19 (Table 3). This table also provides resources regarding crowd-sourced hypofractionation regimens, residency program changes, and protocols used to guide departmental changes during this pandemic.Table 3Resources for clinical care during the COVID-19 pandemicResourceUtilityURLCOVID-19 USA Physician/Advances Practice Provider Facebook groupAnecdotal experiences and resource sharing with regards to caring for COVID-19 patientshttps://tinyurl.com/FBcovid19Hypofractionated radiation therapy regimens during COVID-19Crowdsourced document reviewing appropriate hypofractionated radiation therapy regimens.https://tinyurl.com/RTcovid19COVID-19 Critical Care E-BookFrequently updated Internet book for critical care. Depth of knowledge extends beyond COVID-19.https://emcrit.org/ibcc/COVID19/UW COVID-19University of Washington's public COVID-19 resource websitehttps://covid-19.uwmedicine.org/Radiopaedia's COVID-19 summaryBasic clinical and radiographic summary of COVID-19 presentationshttps://radiopaedia.org/articles/covid-19Residency changes during COVID-19Crowdsourced document recounting radiation oncology residency program changes during COVID-19https://tinyurl.com/REScovid19Ontario Pandemic ProtocolsOntario general pandemic planning protocols and clinical guide for patients with cancerhttps://tinyurl.com/OntarioCancerhttps://tinyurl.com/PandemicProtocolsAbbreviation: COVID = coronavirus disease 2019. Open table in a new tab Abbreviation: COVID = coronavirus disease 2019. Residency training and medicine itself often displace the importance of self by prioritizing the patient and providing team. Radiation oncology resident schedules are typically dictated by the attendings with whom they work, and the COVID-19 pandemic introduces uncertainties that amplify this lack of control. We promote open communication among teams and advocate for residents to express their comfort level regarding in-person patient encounters. However, it is important to recognize the hierarchal difference that exists in the structure of medicine and acknowledge that a top-down approach is more effective. We therefore ask for program directors and department chairs to consider the matters discussed in this article when implementing residency changes. These times are far from normal, but we must continue to work toward achieving normalcy where we can. We humbly thank our institutions for monitoring the unfolding events and implementing strategies to ensure the safety of their staff and our patients.

PURPOSE/OBJECTIVE:Online Adaptive Radiotherapy (ART) with daily MR-imaging has the potential to improve dosimetric accuracy by accounting for inter-fractional anatomical changes. This study provides an assessment for the feasibility and potential benefits of online adaptive MRI-Guided Stereotactic Body Radiotherapy (SBRT) for treatment of liver cancer. MATERIALS/METHODS:Ten patients with liver cancer treated with MR-Guided SBRT were included. Prescription doses ranged between 27 and 50 Gy in 3-5 fx. All SBRT fractions employed daily MR-guided setup while utilizing cine-MR gating. Organs-at-risk (OARs) included duodenum, bowel, stomach, kidneys and spinal cord. Daily MRIs and contours were utilized to create each adapted plan. Adapted plans used the beam-parameters and optimization-objectives from the initial plan. Planning target volume (PTV) coverage and OAR constraints were used to compare non-adaptive and adaptive plans. RESULTS:PTV coverage for non-adapted treatment plans was below the prescribed coverage for 32/47 fractions (68%), with 11 fractions failing by more than 10%. All 47 adapted fractions met prescribed coverage. OAR constraint violations were also compared for several organs. The duodenum exceeded tolerance for 5/23 non-adapted and 0/23 for adapted fractions. The bowel exceeded tolerance for 5/34 non-adaptive and 1/34 adaptive fractions. The stomach exceeded tolerance for 4/19 non-adapted and 1/19 for adaptive fractions. Accumulated dose volume histograms were also generated for each patient. CONCLUSION:Online adaptive MR-Guided SBRT of liver cancer using daily re-optimization resulted in better target conformality, coverage and OAR sparing compared with non-adaptive SBRT. Daily adaptive planning may allow for PTV dose escalation without compromising OAR sparing.

193 Background: Cancer patients in underserved populations are at high risk for patient attrition and treatment delay. We theorized that decreased appointment scheduling was contributing to a high no-show rate within an urban safety-net hospital. Clinic appointments were being scheduled in the department-specific record and verify system rather than the hospital-wide electronic health record (EHR). We sought to adopt EHR scheduling with the long-term goal of decreasing the no-show rate. Our aim was to utilize the Lean Six Sigma (LSS) methodologies to increase EHR scheduling of follow-up and rescheduling of no-show appointments to 50%. Methods: While involving the entire clinic staff, we utilized the Lean Six Sigma DMAIC model: define, measure, analyze, improve and control, to improve EHR appointment scheduling. Appointment data was collected for the 3 months prior to and during the intervention time period. We determined the root causes for delinquent scheduling, including lack of staff availability to schedule patients into two electronic systems and to call no-show patients. Interventions included implementation of an electronic order for follow-up scheduling and blocked time for personnel to contact no-show patients and verify scheduling. After the formation of a novel process map, control plan, and Failure Modes Effects Analysis (FMEA), the pilot study ran for 2 months. Results: Follow-up appointment scheduling into the EHR improved from 2% to 98% (p < 0.01). After the first intervention month, the no-show rescheduling rate improved from 0% to 43% (p < 0.01): below goal. The team revised the process map by substituting a no-show EHR order in place of the calendar intervention. This constituted the beginning of month 2 and no-show appointment rescheduling subsequently improved from 43% to 87% (p < 0.01). The patient no-show rate was 19% during the pre-intervention period, 17% for the first intervention cycle and 15% for the second intervention cycle (p = 0.3). Conclusions: Utilization of LSS allowed for successful adoption of EHR appointment scheduling within our department. While not yet significant, the no-show rate appears to be trending downward as a result of improved scheduling, and we expect the no-show rate to continue to decline as the study matures. These findings suggest that optimized appointment scheduling may decrease patient retention in an at-risk population. Future directions include evaluating cancer outcomes and decreased healthcare costs as a result of higher patient retention.

Breast cancer is the most common noncutaneous malignancy in women. The prevalence increases with age such that nearly 7% of women in the United States over age 70 will be diagnosed with breast cancer. Radiation therapy (RT) is a standard component of the treatment course for women of all ages with breast cancer. RT is commonly encountered in the adjuvant setting for women with nonmetastatic disease, but also works for disease palliation in women with metastatic or recurrent disease. Different techniques for delivering RT for breast cancer include whole breast irradiation (WBI), accelerated partial-breast irradiation (APBI), and chest wall irradiation. Although these techniques often employ external beam radiation therapy (EBRT) delivered with photons, proton beam radiation therapy (PBRT) may also be used for each of these methods. Dosimetric breast cancer studies demonstrate clinical benefits of PBRT compared to photon EBRT. PBRT reduces the radiation dose delivered to the heart, particularly in women with left-sided breast cancer. This may subsequently reduce cardiac toxicity and associated cardiovascular disease. PBRT minimizes radiation dose to the lung and secondary tissues resulting in reduced pulmonary toxicity and secondary malignancies, respectively. PBRT offers superior target homogeneity and lymphatic coverage possibly leading to a lower risk of disease recurrence. A phase 3 prospective randomized clinical trial is currently being conducted to evaluate the efficacy of PBRT compared to EBRT with photons in patients with stage II-III breast cancer. Patients over age 70 with favorable stage I breast cancer may omit adjuvant RT. Elderly patients who are candidates for WBI, APBI and chest wall irradiation can receive PBRT and enjoy the same aforementioned benefits with potentially less toxicities. PBRT also plays a role in disease palliation and definitive therapy in patients who are not surgical candidates. In the elderly population, screening tests, such as the Timed Up and Go and G-8, can help determine which patients are suitable candidates for PBRT.

Cancer patients in underserved populations are at high risk for patient attrition and treatment delay. Infrequent appointment recording often results in patients who are lost to follow-up. We hypothesized that the utilization of Lean Six Sigma methodologies would increase patient scheduling for radiation oncology appointments thereby increasing patient retention within a large urban safety-net health system. The entire clinic staff collaborated to improve electronic health record (EHR) appointment scheduling using the Lean Six Sigma DMAIC approach (Define, Measure, Analyze, Improve and Control). Appointment data was collected for three months prior to and during the pilot study period from the EHR and the radiation oncology record and verify system. We determined the root causes for delinquent scheduling, including lack of staff availability to schedule patients into two electronic systems and to call no-show patients to reschedule. Interventions included implementation of an electronic order for follow-up scheduling and blocked time for personnel to contact no-show patients and verify scheduling. After the formation of a novel process map, control plan, and Failure Modes Effects Analysis (FMEA), the pilot study commenced for a planned six-month period. We report on the first two months of our pilot study. Follow-up appointment scheduling into the EHR improved from baseline 2% to 98% (p<0.01). No-show appointment rescheduling into the EHR improved from baseline 0% to 64%(p<0.01). A novel electronic scheduling intervention was added after the first month when no-show rescheduling into the EMR was at 43% with subsequent no-show rescheduling after the second month at 87% (p = 0.01). The patient no-show rate declined from 19% for the pre-intervention period to 17% for the first pilot month and to 15% for the second pilot month (p = 0.3). Utilization of the Lean Six Sigma methodology resulted in a significant increase in appointment scheduling within the radiation oncology department. While not yet significant, the no-show rate appears to be trending downward as a result of this scheduling improvement, and we expect the no-show rate to continue to decline as the study matures. These findings suggest that optimized appointment scheduling may improve patient retention and continuity of care in an at-risk population. Future directions include evaluating cancer outcomes and healthcare cost savings as a result of higher patient retention.

Studies suggest that advanced NSCLC may respond better to radiotherapy (RT) combined with anti-PD-1 immunotherapy (IT) than to IT alone. Texture analysis evaluates diagnostic imaging for patterns of intensity and has been used to construct predictive models for cancers at multiple sites. We hypothesized that for patients with advanced NSCLC treated with Nivolumab monotherapy, texture features of pre-IT CT imaging can be associated with clinical outcomes and that those associations become more significant when RT history is included in a statistical model. From an IRB-approved database of patients with advanced NSCLC treated with Nivolumab, 21 patients with the longest overall survival (OS) and 20 with the shortest were selected for analysis. The last pre-immunotherapy PET CT was used for segmentation. All FDG-avid intrathoracic tumors were delineated on the CT scan per RTOG contouring guidelines. Ninety-two first-, second, and third-order texture features within the largest tumor for each patient were analyzed for association with OS. OS time was dichotomized to < 1 year vs. > 1 year. Univariate logistic regression was used to estimate odds ratio (OR), 95% confidence interval and p-value for each imaging feature. RT history prior to IT was incorporated into the model as a covariate and analyzed for impact on p-value and effect size (OR). Area-under-the-curve (AUC) was compared using RT history alone and RT history plus texture features to assess correlation with OS. Age, sex, ECOG status ≤ 2, pathology and TNM stage were non-significant on univariate analysis between cohorts. Eighteen of the 21 patients with long OS and 10 of 20 with short OS had an RT history prior to receiving IT. RT history alone had border-line p-value (0.08) but large effect (OR > 3.47). Sixteen of 92 texture features showed significant association with dichotomized OS time (p-values ranging from 0.008 to 0.035) and all exhibited large effect (OR < 0.5 or > 1.5). The addition of RT history as a covariate increased OR in 12 of 16 and decreased p-values in 10 of 16 texture features. Area-under-curve (AUC) analysis showed that considering RT history alone resulted in AUC of 0.63 (marginally significant), while the combination of RT history with texture features resulted in AUC of 0.86, a much stronger correlation with clinical outcome. The p-value for comparison of the two AUCs was 0.0017, indicating that the increase of AUC is statistically meaningful. This preliminary study suggests that texture features on pre-IT CT imaging can be associated with OS for patients with advanced NSCLC treated with Nivolumab, and that inclusion of pre-Nivolumab RT history improves model correlation with OS. Future directions include expansion of this study to the full database, correlation of texture features with molecular biomarkers, and assessment of RT timing and fractionation on treatment response.

We have demonstrated that the KBPs for multiple BMs was dosimetrically equivalent to the CLs with a single time of optimization, even if the number of BMs included in the model training group was different from that in the validation group.

Onboard adaptive radiation therapy (ART) is especially appealing for tumors such as cervical cancer (Cxca) that have a large inter-fraction motion, which dictates the use of a large planning treatment volume (PTV) to ensure adequate tumor coverage when a single plan is being used throughout the entire course of treatment. Treating with ART to reduce PTV margins could lead to better sparing of organs at risk (OAR). However, this approach requires potentially re-contouring the GTV and OAR at each fraction, which can be challenging and time consuming if it has to be performed on a daily basis. We hypothesize that deep learning via convolutional neural-networks (CNN) will generate accurate contours at each fraction of the treatment. The introduction of DL in ART will significantly increase workflow efficiency. For training and evaluation of the DL pipeline, we utilized on-board MRIs taken before each treatment fraction from five patients that have undergone RT for Cxca between 2017 and 2018. Nine structures (GTV+Cervix, Uterus, Parametrium, Sigmoid, Bladder, Vagina, Femur, Rectum and Mesorectum) were manually contoured on the planning MRI and 25th Fx MRI in commercially available deformable registration software for each patient. For DL, we adapted a flexible and generalizable network called MASK R-CNN, which utilizes ResNet10, to detect the candidate-object's class; the Region Proposal Network (RPN) to predict the object bounding box; and, an additional CNN to generate the mask for each object found in the image. The method includes parallel prediction of contours masks and class labels and outputs the object's contours with a confidence parameter. A total of 646 images, containing at least one contour, were used for DL (90% for training and 10% for validation). The network was evaluated using the DICE Similarity coefficient (DSC) between the manual and automatic contours (Table). There was a good agreement between the auto-contoured and manual delineations with 6/9 structures resulting in DSC > 0.8 and 2 of them DSC ≥ 0.9. The auto-contours for parametrium, vagina, and mesorectum were underperforming. The resultant network was then applied to classify 4000 images, randomly selected from MRIs acquired at Fraction 1 to 24 in the five patients. The automatic contours were generated in approximately 2.5 hours, indicating that a single dataset (n=144) can be segmented in < 5.5 min. These preliminary results demonstrate that MASK R-CNN can successfully segment GTV and OAR in the challenging case of Cxca in a short time. A larger set of patients' MRIs should be contoured to continue to build the knowledge bank for the DL software. A robust auto-contouring tool is key for the development and implementation of ART.Abstract 1187; Table 1Dice Similarity Coefficients for manual and DL automatic contoursGTV+CervixUterusSigmoidBladderRectumParametriumVaginaMesorectumFemurTraining0.880.910.880.90.910.70.690.760.81Validation0.840.920.890.90.890.660.710.680.81 Open table in a new tab

Lung cancer is the most common cause of cancer-related death in the world with a disproportionally high burden of disease in low- and middle-income countries (LMICs). Stereotactic ablative radiotherapy (SABR) is the standard of care treatment for inoperable patients with early-stage non-small cell lung cancer (ES-NSCLC) and is currently being evaluated in several randomized control trials in the operable patient setting. SABR for ES-NSCLC has been widely implemented throughout high-income countries (HICs), yet its implementation in LMICs, where the burden of disease is highest, has been limited. The purpose of this report is to provide a practical outline for practitioners to implement SABR for ES-NSCLC while addressing potential barriers that may arise in LMICs. We ultimately aim to describe the essential infrastructure, patient selection, human resources, technical requirements, radiation therapy (RT) planning, RT delivery, patient follow up, quality assurance (QA), and cost considerations required to effectively and safely deliver SABR for ES-NSCLC.

For early-stage glottic cancers, intensity-modulated radiation therapy (IMRT) has been shown to have comparable local control to 3D-conformal radiotherapy with the advantage of decreased dose to the carotid arteries. The planning target volume (PTV) for early glottic cancers typically includes the entire larynx, plus a 3 to 5 mm uniform margin. The air cavity within the larynx creates a challenge for the inverse optimization process as the software attempts to "build up" dose within the air. This unnecessary attempt at dose build-up in air can lead to hot spots within the rest of the PTV and surrounding soft tissue. We hypothesized that removal of the air from the PTV would decrease hot spots and allow for a more homogeneous plan while still maintaining adequate coverage of the PTV. We analyzed 20 consecutive patients with early-stage glottic cancer, T1-2N0, who received IMRT at our institution from April 2015 to December 2016. Each patient received 63 to 65.25 Gy in 2.25 Gy per fraction. Two plans were created for each case: one in which the PTV included the laryngeal air cavity and one in which the air cavity was subtracted from the PTV to create a new PTV-air structure. Dosimetric variables were collected for PTV-air structure from both IMRT plans, including V100%, D98% D2%, and D0.2%. Dosimetric variables for spinal cord and the carotid arteries were also recorded. Homogeneity index (HI) defined as D98/D2 was calculated. Two-sided t-tests were used to compare dosimetric variables. The median PTV volume was 69.9 cc (standard deviation [SD] +/- 28.7 cc) and the median air cavity volume removed was 11.0 cc (SD +/- 3.4 cc). A 2-sided t-test revealed a statistically significant decrease in max dose (112.7% vs 108.8%, p value = 0.0002) and improvement of HI (0.93 vs 0.91, p value = 0.0023) for the PTV air in the IMRT plan optimized for PTV air, which had air excluded, compared to the IMRT plan optimized for PTV with air included. There was no significant worsening of PTV-air coverage or significant increase in doses to the organs at risk (OARs). The removal of the air cavity from the PTV for early-stage glottic cancers does not compromise PTV coverage or sparing of OARs and can result in a more homogeneous IMRT plan. A more homogeneous plan has the potential to reduce treatment morbidity, although further study is warranted to investigate the clinical impact of air cavity removal from the PTV. (C) 2019 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Soft tissue sarcomas are a rare but diverse form of cancer. Due to the heterogeneity of sarcomas, patients often require personalized treatment plans involving radiation, chemotherapy, and surgery, but treatment is still often ineffective. Methods to evaluate and monitor soft tissue sarcomas are needed to improve management of the disease. We assessed imaging features including pharamacokinetic parameters from Dynamic Contrast Enhanced-MRI (DCE-MRI) and Apparent Diffusion Coefficient (ADC) values to classify tumor habitats. We then utilized location and volumetric data of tumor habitats in soft tissue sarcomas to predict treatment response. 8 patients (58.6 ± 10.2 y/o) with soft tissue sarcomas underwent pre-treatment DCE-MRI and Diffusion Weighted-MRI (DW-MRI) and post-treatment resection, allowing pathology determination of treatment response. Tumors were manually segmented from T1-weighted post-contrast images, and tumor habitats were determined from DCE-MRI data using a previously published pattern recognition technique. For each habitat, pharmacokinetic parameters, Kep and Ktrans, from DCE-MRI and ADC maps from co-registered DW-MRI produced features which were then used in a clustering analysis to separate responders and nonresponders. Responders and nonresponders from the 8 patients were accurately divided using features from DCE-MRI and DW-MRI data. Out of all determined features, kep (p = 0.04), Ktrans (p < 0.01), and percent volume (p = 0.02) for well-perfused habitats were significantly lower in nonresponders, whereas volume (p = 0.04) and percent volume (p < 0.01) for necrotic habitats were significantly higher in responders. Prediction of treatment response in soft tissue sarcoma patients yielded promising results when utilizing differences in DCE and DW-MRI features to identify tumor habitats. Pharmacokinetic and anatomical information extracted from unique tumor habitats provided features that could distinguish responders and nonresponders, the combination of which provided more discriminatory ability than a single feature. Further efforts to validate these results in a larger data set, and to evaluate changes in tumor habitats over the course of treatment are needed and ongoing.Abstract 3721; Table 1PatientResponseAgeGenderDiagnosis% Necrosis on PathTreatment1y56FExtraskeletal osteosarcoma99neoadjuvant chemo2y65FPleomorphic fibrosarcoma100unplanned excision then chemo/XRT3y67FMyxofibrosarcoma100neoadjuvant chemo/XRT4y56FPleomorphic Rhabdomyosarcoma30neoadjuvant chemo5n67MExtraskeletal osteosarcoma25unplanned excision then chemo6y67MPleomorphic fibroblastic sarcoma40neoadjuvant chemo/XRT7n53FSynovial sarcoma10neoadjuvant chemo8n38MFibrosarcoma10neoadjuvant chemo Open table in a new tab

A large proportion of extremity soft tissue sarcomas (ESS) occur in the adolescent and young adult (AYA) population, ages 18-39, yet this group is underrepresented in clinical trials. Rare tumors are difficult to study via randomized controlled trials, and the limited data is often extrapolated to AYAs. AYAs present many complex challenges, which affect clinical management. We hypothesized that the National Cancer Database (NCDB) could detect unique factors that influence treatment decisions in AYAs with ESS. The NCDB was utilized to identify patients (pts) 18 and older with ESS diagnosed between 2004-2014 and treated definitively with limb-sparing surgery (LSS) or amputation. Multivariable analyses used logistic regressions for patterns of treatment and their correlation with demographic factors (sex, race, ethnicity, insurance status, income, education, and distance from hospital) and tumor characteristics (primary site, grade, size, clinical stage, depth of extension, and surgical margins). 8953 pts in total were identified and among these, 1280 were AYA. There was no statistical difference in the likelihood of amputation vs. LSS for AYA pts compared to older adults. AYA pts were more likely to receive chemotherapy than older pts (ages 40-65, OR 0.52 (0.45-0.60), p=0.001 and ≥65 years old, OR 0.16 (0.12-0.20), p=0.001). Conversely, AYAs were less likely to receive RT compared to older pts (ages 40-65, OR 1.40 (1.22-1.61), p=0.001 and ≥65 years old, OR 1.33 (1.10-1.61), p=0.003). For all ages, deep tumor extension (OR 1.37 (1.22-1.53), p=0.001) and tumor size (5.01-10 cm, OR 1.30 (1.12-1.51) p=0.001) were associated with the use of RT. Unique to AYAs, clinical stage II disease (compared to stage I, OR 1.25 (0.81-1.91), p=0.313) and positive surgical margins (OR 1.43 (0.93-2.22), p=0.107) were not associated with use of RT. Distance of >10 miles from the hospital was associated with decreased likelihood of receiving RT for all age groups including AYAs. Non-black, Hispanic AYAs were less likely (OR 0.53 (0.36-0.78), p=0.002) compared to those of white race and non-Hispanic ethnicity to receive RT. In addition, AYAs with private insurance were more likely (OR 1.80 (1.19-2.72), p=0.006) than those uninsured to receive RT. Age groups were not significantly associated with the decision to use LSS. However, they do appear to correlate with the decision to use chemotherapy and RT. The AYA population was significantly less likely to receive RT and more likely to receive chemotherapy despite controlling for clinical and demographic factors. Sarcoma disproportionately affects AYAs and further study is warranted to identify the clinical impact of these practice disparities.