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SU-E-J-253: The Radiomics Toolbox in the Computational Environment for Radiological Research (CERR)

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features and (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.

60 APPLIED LIFE SCIENCES↗

Multivariate Linear Models for In Situ Monitoring of Low-Activity Nuclear Waste Using Infrared and Raman Spectroscopy - 20218

This paper presents the use of in situ monitoring tools for molecular analysis of non-radioactive species found in the supernatant liquid and dissolvable salt cake of nuclear waste at Hanford. We have selected two in situ spectroscopic techniques that do not require any sample preparation or consumables: infrared (in the form of attenuated total reflectance Fourier transform infrared or ATR-FTIR) and Raman spectroscopy. This work aims to evaluate their performance for liquid waste simulants representative of the Hanford DFLAW (Direct Feed Low-Activity Waste) feed. In addition, we have evaluated the performance of four multivariate linear models that extract concentrations from spectral measurements for a data set that was designed to include key molecular species found in liquid low-activity waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predictors of Postoperative Complications After Trimodality Therapy for Esophageal Cancer

Purpose: While trimodality therapy for esophageal cancer has improved patient outcomes, surgical complication rates remain high. The goal of this study was to identify modifiable factors associated with postoperative complications after neoadjuvant chemoradiation. Methods and Materials: From 1998 to 2011, 444 patients were treated at our institution with surgical resection after chemoradiation. Postoperative (pulmonary, gastrointestinal [GI], cardiac, wound healing) complications were recorded up to 30 days postoperatively. Kruskal-Wallis tests and χ{sup 2} or Fisher exact tests were used to assess associations between continuous and categorical variables. Multivariate logistic regression tested the association between perioperative complications and patient or treatment factors that were significant on univariate analysis. Results: The most frequent postoperative complications after trimodality therapy were pulmonary (25%) and GI (23%). Lung capacity and the type of radiation modality used were independent predictors of pulmonary and GI complications. After adjusting for confounding factors, pulmonary and GI complications were increased in patients treated with 3-dimensional conformal radiation therapy (3D-CRT) versus intensity modulated radiation therapy (IMRT; odds ratio [OR], 2.018; 95% confidence interval [CI], 1.104-3.688; OR, 1.704; 95% CI, 1.03-2.82, respectively) and for patients treated with 3D-CRT versus proton beam therapy (PBT; OR, 3.154; 95% CI, 1.365-7.289; OR, 1.55; 95% CI, 0.78-3.08, respectively). Mean lung radiation dose (MLD) was strongly associated with pulmonary complications, and the differences in toxicities seen for the radiation modalities could be fully accounted for by the MLD delivered by each of the modalities. Conclusions: The radiation modality used can be a strong mitigating factor of postoperative complications after neoadjuvant chemoradiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Polytopic vector analysis in igneous petrology: Application to lunar petrogenesis

Lunar samples represent a heterogeneous assemblage of rocks with complex inter-relationships that are difficult to decipher using standard petrogenetic approaches. These inter-relationships reflect several distinct petrogenetic trends as well as thermomechanical mixing of distinct components. Additional complications arise from the unequal quality of chemical analyses and from the fact that many samples (e.g., breccia clasts) are too small to be representative of the system from which they derived. Polytopic vector analysis (PVA) is a multi-variate procedure used as a tool for exploratory data analysis. PVA allows the analyst to classify samples and clarifies relationships among heterogenous samples with complex petrogenetic histories. It differs from orthogonal factor analysis in that it uses non-orthogonal multivariate sample vectors to extract sample endmember compositions. The output from a Q-mode (sample based) factor analysis is the initial step in PVA. The Q-mode analysis, using criteria established by Miesch and Klovan and Miesch, is used to determine the number of endmembers in the data system. The second step involves determination of endmembers and mixing proportions with all output expressed in the same geochemical variable as the input. The composition of endmembers is derived by analysis of the variability of the data set. Endmembers need not be present in the data set, nor is it necessary for their composition to be known a priori. A set of any endmembers defines a 'polytope' or classification figure (triangle for a three component system, tetrahedron for a four component system, a 'five-tope' in four dimensions for five component system, et cetera).

Shervais, John W.↗

Survey on stochastic distribution systems: A full probability density function control theory with potential applications

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non-Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data-driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision-making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives.

42 ENGINEERING↗

Generalized Enhanced Multivariance Product Representation for Data Partitioning: Constancy Level

Enhanced Multivariance Product Representation (EMPR) method is used to represent multivariate functions in terms of less-variate structures. The EMPR method extends the HDMR expansion by inserting some additional support functions to increase the quality of the approximants obtained for dominantly or purely multiplicative analytical structures. This work aims to develop the generalized form of the EMPR method to be used in multivariate data partitioning approaches. For this purpose, the Generalized HDMR philosophy is taken into consideration to construct the details of the Generalized EMPR at constancy level as the introductory steps and encouraging results are obtained in data partitioning problems by using our new method. In addition, to examine this performance, a number of numerical implementations with concluding remarks are given at the end of this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inferring Atmospheric Release Characteristics in a Large Computer Experiment using Bayesian Adaptive Splines

An atmospheric release of hazardous material, whether accidental or intentional, can be catastrophic for those in the path of the plume. Predicting the path of a plume based on characteristics of the release (location, amount and duration) and meteorological conditions is an active research area highly relevant for emergency and long-term response to these releases. As a result, researchers have developed particle dispersion simulators to provide plume path predictions that incorporate release characteristics and meteorological conditions. However, since release characteristics and meteorological conditions are often unknown, the inverse problem is of great interest, that is, based on all the observations of the plume so far, what can be inferred about the release characteristics? This is the question we seek to answer using plume observations from a controlled release at the Diablo Canyon Nuclear Power Plant in Central California. With access to a large number of evaluations of a computationally expensive particle dispersion simulator that includes continuous and categorical inputs and spatio-temporal output, building a fast statistical surrogate model (or emulator) presents many statistical challenges, but is an essential tool for inverse modeling and sensitivity analysis. We achieve accurate emulation using Bayesian adaptive splines to model weights on empirical orthogonal functions. Here, we use this emulator as well as appropriately identifiable simulator discrepancy and observational error models to calibrate the simulator, thus finding a posterior distribution of characteristics of the release. Since the release was controlled, these characteristics are known, making it possible to compare our findings to the truth.

54 ENVIRONMENTAL SCIENCES↗

{sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy

Purpose: We sought to investigate the ability of mid-treatment {sup 18}F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer. Methods and Materials: This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized {sup 18}F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We used nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses. Results: Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67). Conclusions: Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Transcatheter Arterial Embolization for Primary Postpartum Hemorrhage: Predictive Factors of Need for Embolic Material Conversion of Gelatin Sponge Particles to N-Butyl Cyanoacrylate

PurposeTo identify predictive factors for embolic material conversion to N-butyl cyanoacrylate (NBCA) for the treatment of primary postpartum hemorrhage (PPH) after failed transcatheter arterial embolization (TAE) using gelatin sponge (GS).Materials and MethodsInstitutional review board approval was obtained. We retrospectively studied 62 consecutive women with primary PPH who underwent TAE between January 2006 and March 2015. Five of them were excluded for the following: cardiopulmonary arrest at arrival (n = 1), uterine inversion (n = 1), and hysterectomy after TAE (n = 3). Remaining 57 women (age range, 21–43 years; mean, 32.6 years) comprised study population. TAE was initially performed using GS in all cases and then converted to NBCA after two embolizations using GS with persistent hemodynamic instability or vaginal bleeding. The patients’ background, uterine height, vital signs, laboratory tests, disseminated intravascular coagulation score, and details of procedure were reviewed. Univariate and multivariate analyses were performed to determine factors related to embolic material conversion.ResultsTechnical success rate was 100%. Fourteen patients (25%) needed embolic material conversion to NBCA. Univariate analysis showed that uterine height, systolic blood pressure (sBP), and hemoglobin level were significantly related to embolic material conversion to NBCA (P = 0.029, 0.030, and 0.042). Logistic regression analysis showed that uterine height (odds ratio, 1.37; P = 0.025) and sBP (odds ratio, 0.96; P = 0.003) were associated with embolic material conversion to NBCA.ConclusionUterine height and sBP can be predictive factors for embolic material conversion to NBCA for the treatment of PPH.Level of EvidenceLevel 4, Case Control Study.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Primordial non-Gaussianity in the bispectrum of the halo density field

The bispectrum vanishes for linear Gaussian fields and is thus a sensitive probe of non-linearities and non-Gaussianities in the cosmic density field. Hence, a detection of the bispectrum in the halo density field would enable tight constraints on non-Gaussian processes in the early Universe and allow inference of the dynamics driving inflation. We present a tree level derivation of the halo bispectrum arising from non-linear clustering, non-linear biasing and primordial non-Gaussianity. A diagrammatic description is developed to provide an intuitive understanding of the contributing terms and their dependence on scale, shape and the non-Gaussianity parameter f{sub NL}. We compute the terms based on a multivariate bias expansion and the peak-background split method and show that non-Gaussian modifications to the bias parameters lead to amplifications of the tree level bispectrum that were ignored in previous studies. Our results are in a good agreement with published simulation measurements of the halo bispectrum. Finally, we estimate the expected signal to noise on f{sub NL} and show that the constraint obtainable from the bispectrum analysis significantly exceeds the one obtainable from the power spectrum analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

The Influence of Total Nodes Examined, Number of Positive Nodes, and Lymph Node Ratio on Survival After Surgical Resection and Adjuvant Chemoradiation for Pancreatic Cancer: A Secondary Analysis of RTOG 9704

Purpose: Lymph node status is an important predictor of survival in pancreatic cancer. We performed a secondary analysis of Radiation Therapy Oncology Group (RTOG) 9704, an adjuvant chemotherapy and chemoradiation trial, to determine the influence of lymph node factors-number of positive nodes (NPN), total nodes examined (TNE), and lymph node ratio (LNR ratio of NPN to TNE)-on OS and disease-free survival (DFS). Patient and Methods: Eligible patients from RTOG 9704 form the basis of this secondary analysis of lymph node parameters. Actuarial estimates for OS and DFS were calculated using Kaplan-Meier methods. Cox proportional hazards models were performed to evaluate associations of NPN, TNE, and LNR with OS and DFS. Multivariate Cox proportional hazards models were also performed. Results: There were 538 patients enrolled in the RTOG 9704 trial. Of these, 445 patients were eligible with lymph nodes removed. Overall median NPN was 1 (min-max, 0-18). Increased NPN was associated with worse OS (HR = 1.06, p = 0.001) and DFS (HR = 1.05, p = 0.01). In multivariate analyses, both NPN and TNE were associated with OS and DFS. TNE > 12, and >15 were associated with increased OS for all patients, but not for node-negative patients (n = 142). Increased LNR was associated with worse OS (HR = 1.01, p < 0.0001) and DFS (HR = 1.006, p = 0.002). Conclusion: In patients who undergo surgical resection followed by adjuvant chemoradiation, TNE, NPN, and LNR are associated with OS and DFS. This secondary analysis of a prospective, cooperative group trial supports the influence of these lymph node parameters on outcomes after surgery and adjuvant therapy using contemporary techniques.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accumulated Delivered Dose Response of Stereotactic Body Radiation Therapy for Liver Metastases

Purpose: To determine whether the accumulated dose using image guided radiation therapy is a stronger predictor of clinical outcomes than the planned dose in stereotactic body radiation therapy (SBRT) for liver metastases. Methods and Materials: From 2003 to 2009, 81 patients with 142 metastases were treated in institutional review board–approved SBRT studies (5-10 fractions). Patients were treated during free breathing (with or without abdominal compression) or with controlled exhale breath-holding. SBRT was planned on a static exhale computed tomography (CT) scan, and the minimum planning target volume dose to 0.5 cm{sup 3} (minPTV) was recorded. The accumulated minimum dose to the 0.5 cm{sup 3} gross tumor volume (accGTV) was calculated after performing dose accumulation from exported image guided radiation therapy data sets registered to the planning CT using rigid (2-dimensional MV/kV orthogonal) or deformable (3-dimensional/4-dimensional cone beam CT) image registration. Univariate and multivariate Cox regression models assessed the factors influencing the time to local progression (TTLP). Hazard ratios for accGTV and minPTV were compared using model goodness-of-fit and bootstrapping. Results: Overall, the accGTV dose exceeded the minPTV dose in 98% of the lesions. For 5 to 6 fractions, accGTV doses of >45 Gy were associated with 1-year local control of 86%. On univariate analysis, the cancer subtype (breast), smaller tumor volume, and increased dose were significant predictors for improved TTLP. The dose and volume were uncorrelated; the accGTV dose and minPTV dose were correlated and were tested separately on multivariate models. Breast cancer subtype, accGTV dose (P<.001), and minPTV dose (P=.02) retained significance in the multivariate models. The univariate hazard ratio for TTLP for 5-Gy increases in accGTV versus minPTV was 0.67 versus 0.74 (all patients; 95% confidence interval of difference 0.03-0.14). Goodness-of-fit testing confirmed the accGTV dose as a stronger dose–response predictor than the minPTV dose. Conclusions: The accGTV dose is a better predictor of TTLP than the minPTV dose for liver metastasis SBRT. The use of modern image guided radiation therapy in future analyses of dose–response outcomes should increase the concordance between the planned and delivered doses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Sensor failure and multivariable control for airbreathing propulsion systems

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Behbehani, K.↗

Impact of Body Mass Index on Outcomes After Conformal Radiotherapy in Patients With Prostate Cancer

Purpose: Several retrospective analyses have suggested that obese men with prostate cancer treated with external beam radiotherapy (EBRT) have outcomes inferior to those of normal-weight men. However, a recently presented analysis for the first time challenged this association between body mass index (BMI) and treatment failure. It is therefore important to provide further data on this issue. Methods and Materials: This was a retrospective analysis of 564 men treated with risk-adapted conformal EBRT at a single institution. Low-risk patients received EBRT alone, and the other patients received EBRT plus endocrine treatment. In addition, high-risk patients were treated to higher EBRT doses (74 Gy). A rectal balloon catheter for internal immobilization, which can be identified on portal images, was used in 261 patients (46%). Thus, localization did not rely on bony landmarks alone in these cases. Results: The median BMI was 26, and 15% of patients had BMI {>=}30. Neither univariate nor multivariate analyses detected any significant impact of BMI on biochemical relapse, prostate cancer-specific survival, or overall survival. The 5-year biochemical relapse rate was 21% and prostate cancerspecific survival 96%. Conclusions: The present analysis of a large cohort of consecutively treated patients suggests that efforts to reduce prostate movement and geographic miss might result in comparable outcomes in obese and normal-weight patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Weight change since age 20 and incident risk of obesity‐related cancer in Japan: a pooled analysis of the Miyagi Cohort Study and the Ohsaki Cohort Study

It is unclear whether weight change during adulthood affects the risk of obesity‐related cancers such as those of the esophagus, colorectum, pancreas, breast, endometrium, and kidney among Japanese, where obesity is less frequent and less severe. We examined the association between weight change during adulthood and the risk of obesity‐related cancer among Japanese by conducting a pooled analysis of two prospective studies of residents in Miyagi Prefecture, Japan. A total of 78,743 persons (40,422 women and 38,321 men) aged 40–79 years participated in the Miyagi Cohort Study in 1990 and in the Ohsaki Cohort Study in 1994. Weight change since age 20 was divided into four categories (weight loss; stable weight; moderate weight gain; high weight gain). Cox proportional hazards regression analysis was used to estimate the multivariate hazard ratios (HRs) and 95% confidence intervals (CIs) for obesity‐related cancer incidence. During 1,057,899 person‐years of follow up, 4,467 cases of obesity‐related cancer (women; 1,916 cases, men; 2,551cases) were identified. In women, compared to the stable weight, weight gain was associated with an increased risk of obesity‐related cancer (moderate weight gain; HRs = 1.10, 95%CIs: 0.97–1.26, high weight gain; HRs = 1.29, 95%CIs: 1.14–1.47). The results indicate that weight gain since age 20 was associated with a significantly increased risk of obesity‐related cancer among Japanese women. By contrast, in men, our study found that weight change is not associated with the incidence of obesity‐related cancer.

Wakamatsu, Mano↗

Subsets of Women With Close or Positive Margins After Breast-Conserving Surgery With High Local Recurrence Risk Despite Breast Plus Boost Radiotherapy

Purpose: (1) To examine the effect of surgical margin status on local recurrence (LR) and survival following breast-conserving therapy; (2) To identify subsets with close or positive margins with high LR risk despite whole breast radiotherapy (RT) plus boost. Methods and Materials: Subjects were 2,264 women with pT1-3, any N, M0 invasive breast cancer, treated with breast-conserving surgery and whole breast {+-} boost RT. Five-year Kaplan-Meier (KM) LR, breast cancer-specific and overall survival (BCSS and OS) were compared between cohorts with negative (n = 1,980), close (n = 222), and positive (n = 62) margins. LR rates were analyzed according to clinicopathologic characteristics. Multivariable Cox regression modeling and matched analysis of close/positive margin cases and negative margin controls were performed. Results: Median follow-up was 5.2 years. Boost RT was used in 92% of patients with close or positive margins. Five-year KM LR rates in the negative, close and positive margin cohorts were 1.3%, 4.0%, and 5.2%, respectively (p = 0.001). BCSS and OS were similar in the three margin subgroups. In the close/positive margin cohort, LR rates were 10.2% with age <45 years, 11.8% with Grade III, 11.3% with lymphovascular invasion (LVI), and 26.3% with {>=}4 positive nodes. Corresponding rates in the negative margin cohort were 2.3%, 2.4%, 1.0%, and 2.4%, respectively. On Cox regression analysis of the entire cohort, close or positive margin, Grade III histology, {>=}4 positive nodes, and lack of systemic therapy were significantly associated with higher LR risk. When close/positive margin cases were matched to negative margin controls, the difference in 5-year LR remained significant (4.25% vs. 0.7%, p < 0.001). Conclusions: On univariable analysis, subsets with close or positive margins, in combination with age <45 years, Grade III, LVI, and {>=}4 positive nodes, have 5-year LR >10% despite whole breast plus boost RT. These patients should be considered for more definitive surgery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Search for the Rare Decay $B_s^0 \to \mu^+\mu^-$ at D0

Results of the search for the rare decay B 0 s → μ + μ - using data collected by the D0 detector at the Fermilab Tevatron collider are presented. This analysis covers the full Run II data set, corresponding to approximately 10.4 fb -1 of integrated luminosity in p¯p collisions at a center of mass energy of 1.96 TeV. The analysis used new variables and a multivariate technique to improve the background reduction. After seeing fewer events than expected from background, a new Tevatron best observed limit was set on the branching fraction of the decay at B(B 0 s → μ + μ - ) < 15 x 10 -9 (12 x 10 -9 ) at the 95% (90%) C.L.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗