bluuebunny/crossref_metadata_2025_split huggingface dataset:
MLTI-07. PREOPERATIVE VERSUS POSTOPERATIVE STEREOTACTIC RADIOSURGERY FOR LARGE BRAIN METASTASES: AN INTERNATIONAL META-ANALYSIS
Authors: Garcia Henry Ruiz , Lehrer Eric , Bhargav Adip , Peterson Jennifer , Chaichana Kaisorn , Quinones-Hinojosa Alfredo , Harrell Anna , Routman David , Burns Terry , Zaorsky Nicholas , Trifiletti Daniel 
Published: August 2019

Abstract
PURPOSE: Preoperative stereotactic radiosurgery (SRS) for symptomatic brain metastases has arisen as a therapeutic option for patients with brain lesions, potentially reducing radionecrosis risk, leptomeningeal disease risk, as well as delays in systemic therapy after craniotomy. The purpose of our work is to analyze the current evidence regarding 1-year local control (LC) and RN rates in the preoperative and postoperative settings. METHODS AND MATERIALS: Population, Intervention, Control, Outcomes, Study Design/Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology guidelines were used to select articles in which patients had “large” brain metastases (&gt;4 cm3 or &gt;2 cm in diameter) solely treated with preoperative or postoperative SRS and 1-year LC and/or rates of RN reported. Radiosurgery was stratified by timing: preoperatively or postoperatively. Random effects meta-analyses using timing of SRS relative to surgery as covariates were conducted. Meta-regression and Wald-type tests were used to determine the effect of increasing tumor size on the summary estimate, where the null hypothesis was rejected for p &lt; 0.05. RESULTS: Fifteen studies were included (of 314 screened), published between 2012 and 2018 with 854 brain metastases. Preoperative SRS was delivered in 229 lesions. The 1-year LC random effects estimate was 79.1% (95% confidence interval [CI]: 55.9–95.0%; I 2 = 80%) for preoperative SRS and 80.5% (95% CI: 66.3–91.5%; I 2 = 93%) for postoperative SRS (p=0.9). Radionecrosis incidence random effects estimate was 2.1% (95% CI: 0.1–8.6%; I 2 = 36%) for preoperative SRS and 6.3% (95% CI: 1.1–15.4%; I 2 = 90%) for postoperative SRS (p=0.52). CONCLUSIONS: Rates of 1-year LC and RN incidence are similar after preoperative SRS as compared to postoperative SRS for large brain metastases. Results from ongoing prospective clinical trials studying preoperative SRS are important to further investigate these two techniques.
MLTI-09. UNDERWEIGHT AND WEIGHT LOSS ARE PREDICTORS OF POOR OUTCOME IN PATIENTS WITH BRAIN METASTASIS
Authors: Weller Michael , Lareida Anna , Terziev Robert , Grossenbacher Bettina , Andratschke Nicolaus , Roth Patrick , Rohrmann Sabine , Stahel Rolf , Guckenberger Matthias , Le Rhun Emilie , Wolpert Fabian 
Published: August 2019

Abstract
BACKGROUND: Despite increased risk of comorbidities, overweight may be associated with improved outcome in patients with metastatic cancer. Conversely, tumor cachexia has been identified as a negative predictor of outcome in patients with brain metastasis (BM) from lung cancer. Here we evaluate the association of abnormal body mass index (BMI) and weight change with outcome in patients with BM from different primary tumors. METHODS: Patients with a diagnosis of BM diagnosed and treated at the University Hospital Zurich (n=703) were assessed for associations of BMI, weight change, comorbidities and survival. RESULTS: Compared with patients with normal BMI of 18.5–24.9 kg/m2 who experienced a median overall survival (OS) of 9 months (95% confidence interval (CI) 7.5–10.5), OS was inferior in patients with BMI&lt; 18.5 kg/m2 (OS 6 months, 95% CI 1.6–10.3, p=0.04), but superior in patients with BMI &gt;25 kg/m2 (OS 13 months, 95% CI 11.0–15.0; p=0.033). For patients with documented weight course (n=173 of 703), we report a median relative weight loss of 5% within the first 6 months of BM diagnosis (95% CI 3.3–6.5). Reduction above the median was associated with an unfavorable outcome in this subgroup (weight loss ≧5% 22.0 months, 95% CI 19.2–24.8; weight loss &lt; 5% 14.0 months, 95% CI 11.9–16.). CONCLUSIONS: Despite being associated with a worse cardiovascular risk profile, high BMI is associated with preferable and underweight with poor outcome in BM patients. Conversely, weight loss above median may be a predictor of poor outcome. Future studies need to address the question whether vigorous treatment of tumor cachexia, e.g. by specific nutrition management, might improve outcome of BM patients. In contrast, regimens that are associated with weight loss such as ketogenic diet may be detrimental.
MLTI-15. A CASE SERIES OF PRE-OPERATIVE GAMMA-KNIFE RADIOSURGERY FOR RESECTABLE BRAIN METASTASES
Authors: Takezaki Tatsuya , Yamamoto Haruaki , Shinojima Naoki , Kuroda Jun-ichiro , Yamashiro Shigeo , Mukasa Akitake 
Published: August 2019

Abstract
Recent advances in the systemic treatment of various cancers have resulted in longer survival and higher incidence of brain metastases. Phase 3 trials in north America and in Japan have demonstrated that stereotactic radiosurgery will be a standard adjuvant modality following surgery for resectable brain metastases. However, we don’t know the optimal sequence of this combination therapy. We hypothesized that pre-operative stereotactic radiosurgery for resectable brain metastases provides favorable rates of local control, overall survival, leptomeningeal dissemination and symptomatic radiation necrosis. We have experienced 4 cases of resected brain metastases within 1–7 days after Gamma-knife surgery (median margin dose:22Gy) and have been following their clinical course. We will show the repressive cases.
MLTI-19. VENOUS THROMBOEMBOLIC EVENTS IN PATIENTS WITH BRAIN METASTASES: THE PICOS SCORE
Authors: Wolpert Fabian , Grossenbacher Bettina , Lareida Anna , Roth Patrick , Neidert Marian , Andratschke Nicolaus , Le Rhun Emilie , Weller Michael 
Published: August 2019

Abstract
BACKGROUND: Venous thromboembolic events are significant complications in patients and possibly associated with an unfavorable outcome. Thrombosis risk is poorly defined for patients with brain metastasis, and available risk calculation scores are not validated for these patients. METHODS: We identified 811 patients with brain metastasis followed at our institution and screened electronic charts retrospectively for the occurrence of venous thromboembolic events, along with candidate risk factors. Risk factors were tested in uni- and multivariate analyses and finally integrated in a score model for risk prediction. RESULTS: Venous thromboembolic events were documented in 97 of 811 patients (12.0%). Primary tumors with high thrombogenicity (p=0.02, odds ratio 1.7, 95% CI 1.1–2.8), dexamethasone (p=0.011, odds ratio 2.27, 95% CI 1.5–4.5), chemotherapy (p=0.005, odds ratio 3.4, 95% CI 1.6–7.5), BMI &gt; 35 kg/m2 (p=0.002, odds ratio 3.4, 95% CI 1.6–7.5) and immobilization (p=0.003, odds ratio 2.4, 95% CI 1.3–4.3) were confirmed as independent predictors of VTE. We derived a score model for venous thromboembolic event prediction, the PICOS (thrombogenic Primary, Immobilization, Chemotherapy, Obesity, Steroids) score (0–7 points). Receiver Operating Characteristic Curve Analysis demonstrated its prognostic accuracy (AUC=0.71, 95% CI 0.64–0.77), and its predictive capability was superior to that of other scores proposed for the evaluation of venous thromboembolic event risk such as the Khorana (AUC=0.51) or CONKO (AUC=0.52) scores. CONCLUSIONS: We report a rate of venous thrombotic events of 12.0% in our cohort of 811 patients with brain metastasis. We define a risk model for prediction in of venous thrombotic events in patients with BM, the PICOS score. It may become a valuable tool for the identification of brain metastasis patients at high risk for venous thromboembolic events and be helpful for guidance of clinicians towards decision whether to start thrombosis prophylaxis. Further, the PICOS score might be used for stratification in controlled studies.
OTHR-07. ESTIMATING INCIDENCE PROPORTION OF BRAIN METASTASES AT DIAGNOSIS AND LIFETIME INCIDENCE AMONG CANCER PATIENTS DIAGNOSED FROM 2010–2015 IN CANADA
Authors: Paudel Yuba Raj , Walker Emily , Smith Trenton , Yuan Yan , Nichol Alan , Davis Faith 
Published: August 2019

Abstract
INTRODUCTION: The incidence of brain metastases (BM) among Canadian cancer patients is unknown. We aimed to estimate the incidence proportion (IP) of BM at the time of all cancer diagnoses and during follow-up of cancer patients with the top six primary tumours that are most likely to metastasize to the brain. METHODS: Data on BM at diagnosis from 2010–2015 was obtained from the Canadian Cancer Registry (CCR). Site-specific IPs of BM was estimated for patients from provincial registries that achieved ≥90% complete data. These estimates were applied to the total number of newly diagnosed primary cancers to estimate total number of BM at diagnosis from 2010–2015 in Canada. To estimate the number of lifetime BM that arise from six selected primary cancers including lung, breast, skin melanoma, colorectal, kidney/renal pelvis and esophagus, we applied IP estimates reported in the literature. RESULTS: We identified 1,105,905 cancer cases in the CCR from 2010–2015, of which 519,950 (47%) were from the six primaries. The annual average number of patients with BMs at diagnosis from all cancer sites was approximately 2,800 and was highest for lung cancer(2,400).The site-specific IPs of BM at diagnosis were: lung (9.6%;95% CI: 9.3–10.0%), esophageal (2%;95%CI:1.5–2.7%), kidney/renal pelvis (1.3%;95%CI:1.0–1.5%), skin melanoma (1.1%;95%CI:0.9–1.3%), colorectal (0.3%;95%CI:0.2–0.3%), and breast (0.2%;95%CI:0.2–0.3%).Using clinical and population data from the literature, we estimated that nearly 7,400 lifetime BM cases occur annually for these six primaries. CONCLUSIONS: Each year in Canada, approximately 2,800 BMs from all primary cancers are found at the time of diagnosis and approximately 7,400 lifetime BM occur annually from the six selected primary tumours.
OTHR-13. A DEEP LEARNING APPROACH TO DETECT CANCER METASTASES TO THE BRAIN IN MRI
Authors: Zhang Min , Young Geoffrey , Chen Huai , Qin Lei , Cao Xinhua , Wu Xian , Xu Xiaoyin 
Published: August 2019

Abstract
BACKGROUND AND OBJECTIVE: Brain metastases have been found to account for one-fourth of all cancer metastases seen in clinics. Magnetic resonance imaging (MRI) is widely used for detecting brain metastases. Accurate detection of the brain metastases is critical to design radiotherapy to treat the cancer and monitor their progression or response to the therapy and prognosis. However, finding metastases on brain MRI is very challenging as many metastases are small and manifest as objects of weak contrast on the images. In this work we present a deep learning approach integrated with a classification scheme to detect cancer metastases to the brain on MRI. MATERIALS AND METHODS: We retrospectively extracted 101 metastases patients, equal to 1535 metastases on 10192 slices of images in a total of 336 scans from our PACS and manually marked the lesions on T1-weighted contrast enhanced MRI as the ground-truth. We then randomly separated the cases into training, validation, and test sets for developing and optimizing the deep learning neural network. We designed a 2-step computer-aided detection (CAD) pipeline by first applying a fast region-based convolutional neural network method (R-CNN) to sequentially process each slice of an axial brain MRI to find abnormal hyper-intensity that may correspond to a brain metastasis and, second, applying a random under sampling boost (RUSBoost) classification method to reduce the false positive metastases. RESULTS: The computational pipeline was tested on real brain images. A sensitivity of 97.28% and false positive rate of 36.25 per scan over the images were achieved by using the proposed method. CONCLUSION: Our results demonstrated the deep learning-based method can detect metastases in very challenging cases and can serve as CAD tool to help radiologists interpret brain MRIs in a time-constrained environment.
RADI-01. PROGNOSTIC FACTORS OF SHORT SURVIVAL FOR BRAIN METASTASES TREATED WITH SRS WITHOUT WBRT.
Authors: Harat Maciej , Blok Maciej , Makarewicz Roman , Roszkowski Krzysztof 
Published: August 2019

Abstract
Nowadays multiple brain metastases (up to 10–15 tumors) are treated with SRS alone. The most common diagnosis-specific Graded Prognostic Assessment and Score for Radiosurgery indices are based on data regarding limited brain metastases (1–4). Moreover, many of patients included in that analyses were treated with WBRT or combination of WBRT and SRS and some relevant data were not included due to a retrospective analysis of large datasets. SRS may increase intracranial control of disease, however, treatment of patients with a prognosis of fewer than 3 months survival after SRS may not be clinically reliable. Therefore we conducted an analysis of prospective registry to find the factors that correlate with very short survival after SRS. Materials and methods, A consecutive cohort of 84 patients treated with SRS only for brain metastases between 04.2018-03.2019. Data prospectively collected and introduced into a registry of patients treated with SRS in our department were analyzed. The analyzed factors are age, primary site, histopathology, previous surgery, molecular results, systemic therapy, duration of SRS planning, the extent of extracerebral metastatic disease, number of brain metastases, mass effect and neurological symptoms/ We performed a univariate analysis and multivariate Cox regression model to find a correlation between clinical and molecular data and survival in brain metastases patients treated with SRS only. Factors predicted early death and correlated with survival will be presented at the conference
RADI-07. GAMMA KNIFE RADIOSURGERY FOR SMALL CELL LUNG CANCER: PROGNOSTIC FACTORS INCLUDING ADDITIONAL LESIONS IDENTIFIED ON THE DAY OF RADIOSURGERY
Authors: Chaung Kevin , Kharouta Michael , Shamp Stephen , Machtay Mitchell , Sloan Andrew , Bhatt Aashish , Mansur David , Hodges Tiffany , Zhang Yuxia , Choi Serah 
Published: August 2019

Abstract
OBJECTIVES: Prophylactic cranial irradiation (PCI) and whole brain radiation (WBRT) are standard of care for intracranial disease in small cell lung cancer (SCLC) patients. We sought to identify predictors of overall survival (OS) in SCLC patients treated with salvage Gamma Knife radiosurgery (GKRS) for brain metastases after prior WBRT or PCI. METHODS: Retrospective analyses were conducted on 26 SCLC patients treated with GKRS at one institution between May 2010 and June 2018. Factors predictive of OS were analyzed using Cox proportional hazards regression and Wilcoxon sum-rank testing. RESULTS: Median follow-up and median OS following GKRS was 6.6 mos (range 0.7–24.2 mos). Median OS was 21.4 mos from initial diagnosis (range 7.3–49.3 mos). Presence of extracranial metastases at the time of GKRS was not significantly associated with median OS after GKRS (5.8 mos for patients with extracranial metastases vs 7.2 mos for patients without, p=0.425). Mean number of lesions was 2.7 (range 1–10) on diagnostic brain MRIs and 4.1 (range 1–12) on GKRS planning MRIs. Eleven patients (42%) had the same number of lesions between diagnostic MRI and GKRS MRI, and 15 patients (58%) had additional lesions on the GKRS MRI. Number of lesions treated and total tumor volume were not associated with median OS. Patients who had additional lesions on GKRS MRI compared to diagnostic MRI had lower median OS from initial diagnosis of SCLC (29.9 mos vs 18.1 mos, p=0.0182) and a trend toward lower median OS from time of GKRS (7.3 mos vs 4.8 mos, p=0.0547) compared to patients who did not have additional lesions. CONCLUSIONS: Finding additional brain metastases on GKRS planning MRIs is associated with decreased OS in SCLC patients treated with salvage GKRS. Presence of extracranial metastases at the time of GKRS and number or total volume of brain metastases were not associated with OS.
RADI-12. LEPTOMENINGEAL FAILURE AFTER PREOPERATIVE VERSUS POSTOPERATIVE RADIOSURGERY
Authors: Fiveash John , Riley Kristen , Markert James , Guthrie Bart , Foreman Paul , Popple Richard , Marcrom Sam , Strickler Scott , Willey Christopher , McDonald Andrew , Thomas Evan , Stewart John , Bredel Markus 
Published: August 2019

Abstract
INTRODUCTION: Postoperative stereotactic radiosurgery (postop SRS) is potentially complicated by difficulty defining the target volume and the risk of leptomeningeal seeding at the time of surgery. It is hypothesized that preop SRS may render cells less viable to disseminate in the leptomeningeal space. This retrospective study compares the leptomeningeal dissemination (LMD) rate for preop versus postop radiosurgery METHODS: We identified 140 patients with brain metastases who underwent resection and radiosurgery at the University of Alabama at Birmingham including 91 postop patients (2005–2015) and 49 preop patients (2011–2018). The preop group included 19 patients enrolled in a phase I trial of preoperative radiosurgery (12–15 Gy) for tumors 2–6 cm in greatest diameter. In that study 15 Gy was found to be safe in the preop setting but further escalation was not attempted. An additional 30 patients received preop SRS off-study (median dose 15 Gy). The median postop dose was 16 Gy. LMD recurrence was defined as focal pachymeningeal or diffuse leptomeningeal enhancement of the brain, spinal cord, or cauda equina, dural enhancement beyond 5 mm from the index metastasis, subependymal enhancement, or enhancement of cranial nerves. This definition is not limited to carcinomatosis. All events were categorized and confirmed by at least two physicians. RESULTS: 40/140 (29%) patients developed new focal or diffuse LMD. Preop SRS was associated with a higher freedom from leptomeningeal recurrence (84% vs 60% at one year, p=0.021 Breslow, p=0.128 log-rank). Since later LMD may not be related to surgery, a second analysis censoring follow-up at one year was performed and confirmed this trend (p=0.008 Breslow, p=0.014 log-rank). CONCLUSIONS: Preoperative SRS is associated with a reduction in the risk of LMD compared to postop SRS. Focal pachymeningeal dissemination may not always be recognized as related to surgery. A randomized trial of preop vs postop SRS is warranted.
RADI-16. ECONOMIC IMPLICATIONS OF PREOPERATIVE VERSUS POSTOPERATIVE STEREOTACTIC RADIOSURGERY FOR BRAIN METASTASES
Authors: Ward Matthew , Prabhu Roshan , Asher Anthony , Wait Scott , Sumrall Ashley , Shah Chirag , Burri Stuart 
Published: August 2019

Abstract
OBJECTIVE: Retrospective data suggests preoperative stereotactic radiosurgery (preSRS) reduces radiation necrosis (RN) and leptomeningeal disease (LMD) failure after resection of brain metastases (BM) as compared to postoperative SRS (postSRS). We evaluated the potential financial impact of a reduction in symptomatic RN (SRN) and LMD, should preSRS become a national standard. METHODS: A decision tree was designed to evaluate the two strategies: preSRS vs. postSRS. We assumed no difference in survival and that a reduction in SRN and LMD exists on par with retrospective data. Effectiveness was not considered given unclear health utilities. Treatments for SRN considered were dexamethasone, bevacizumab, surgical resection, or hyperbaric oxygen (HBO). Treatments for LMD considered included conventional radiation, SRS, systemic therapy (lapatinib/capecitabine), or no therapy. Probabilities were extracted from the 2-year LMD/SRN rates and subsequent treatment patterns observed in retrospective data. Treatment costs were based on the 2019 Medicare physician fee schedule and published data in 2019 US dollars without discounting. National costs to the healthcare system were estimated by assuming 200,000 BM cases per year with a surgical utilization rate of 16%. Deterministic and probabilistic sensitivity analyses (PSA) were performed. RESULTS: The incorporated rate of LMD and SRN for postSRS was 22.4% and 16.4% and 4.3% and 4.9% for preSRS, respectively. The expected mean costs were $3,129 for postSRS and $810 for preSRS. Deterministic sensitivity analysis demonstrated that the model was sensitive to only LMD/SRN rates. PSA demonstrated that in 95% of simulations, the expected savings ranged from $770-$6,429/patient. Therefore, the national healthcare system stands to save approximately $74 million per year if preSRS was a national standard (range $25–206 million). CONCLUSIONS: A prospective randomized trial demonstrating the effectiveness of preSRS in the reduction of LMD and/or SRN would carry a significant return on investment through the reduction of subsequent treatment costs.
RADI-19. EVALUATION OF BRAIN METASTASIS LOCAL CONTROL POST RADIOSURGERY VIA MACHINE LEARNING AND RADIOMICS
Authors: Dise Joseph , Abraham Christopher , Caruthers Douglas , Mutic Sasa , Robinson Clifford 
Published: August 2019

Abstract
Stereotactic radiosurgery can be used to treat multiple, surgically inaccessible, metastatic brain lesions in a single, minimally invasive outpatient procedure. For brain metastasis, stereotactic radiosurgery can provide excellent local control depending on the robustness of the treatment plan. Previous studies have been performed correlating key radiation planning factors to higher local control probability such as tumor size and maximum dose. However, a separate non-inferiority study demonstrated that higher prescription isodose lines (in excess of 70% or higher) did not correlate to local failure. The previous works were limited to shallow feature levels regarding only the dicom plan information and lacked a predictive model. In order to address these conflicting conclusions and to support clinical decision making, we propose a radiosurgery informatics pipeline to support testing these hypotheses with observational data. First, a multidisciplinary team generated a mind-map of relevant information to inform database design. Portions of this mind-map were implemented in a relational database system (PorstgreSQL), and populated with information from 1024 patients treated for brain metastasis via stereotactic radiosurgery. Clinical information were derived from curated databases and the array of intervention variables were mined from the DICOM RT plans, structure sets, images and dose via MATLAB scripts. These factors include, but are not limited to, radiation dosimetry, prior whole brain radiation, radiomic imaging features, prior radiosurgery status, and physician determined local control status. From this pipeline, we plan to use a multi-level feature-based supervised machine learning approach that will be created via boosting to predict local control in patients using local failure timing, or lack thereof, provided by physician. To control for local failure observer bias, an unsupervised machine learning model via random trees will be created to predict clusters of patient parameters with similar local control rates.