Results for “Databases” — Page 80

DOE OSTI2019

Robustness of trait connections across environmental gradients and growth forms

Abstract Aim Plant trait databases often contain traits that are correlated, but for whom direct (undirected statistical dependency) and indirect (mediated by other traits) connections may be confounded. The confounding of correlation and connection hinders our understanding of plant strategies, and how these vary among growth forms and climate zones. We identified the direct and indirect connections across plant traits relevant to competition, resource acquisition and reproductive strategies using a global database and explored whether connections within and between traits from different tissue types vary across climates and growth forms. Location Global. Major taxa studied Plants. Time period Present. Methods We used probabilistic graphical models and a database of 10 plant traits (leaf area, specific leaf area, mass‐ and area‐based leaf nitrogen and phosphorous content, leaf life span, plant height, stem specific density and seed mass) with 16,281 records to describe direct and indirect connections across woody and non‐woody plants across tropical, temperate, arid, cold and polar regions. Results Trait networks based on direct connections are sparser than those based on correlations. Land plants had high connectivity across traits within and between tissue types; leaf life span and stem specific density shared direct connections with all other traits. For both growth forms, two groups of traits form modules of more highly connected traits; one related to resource acquisition, the other to plant architecture and reproduction. Woody species had higher trait network modularity in polar compared to temperate and tropical climates, while non‐woody species did not show significant differences in modularity across climate regions. Main conclusions Plant traits are highly connected both within and across tissue types, yet traits segregate into persistent modules of traits. Variation in the modularity of trait networks suggests that trait connectivity is shaped by prevailing environmental conditions and demonstrates that plants of different growth forms use alternative strategies to cope with local conditions.

Flores‐Moreno, Habacuc↗

DOE OSTI2020

Method for estimating the density of high-level nuclear waste glass

A database of over 1100 silicate glass compositions and densities was compiled and used to evaluate the efficacy of an algorithm for estimating the density of silicate glass compositions. We sought to develop a parsimonious algorithm based on the additivity of partial molar volumes of individual oxide components weighted by their mole fraction in a glass composition. Bound molar volumes were used for oxides in which the density of the oxide bound in a glass matrix was previously determined. The bound molar volumes were known for oxides covering 97.5 mole percent of the database compositional space. The measured glass densities were plotted against the estimated glass densities and a linear regression yielded an R 2 adj. = 0.95 and a slope and intercept of approximately one and zero, respectively. This regression suggests that glass densities estimated by the algorithm, within analysis uncertainty, are equal to the measured densities of the glasses. In addition to the development of the density estimation, we corroborated many of the referenced bound molar volume data used in the parameterization of the estimation algorithm via linear regression of the individual partial molar volumes versus the inverse measured densities (specific volumes) of the glasses in the database.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

SU-D-BRD-07: Automatic Patient Data Audit and Plan Quality Check to Support ARIA and Eclipse

Purpose: To ensure patient safety and treatment quality in RT departments that use Varian ARIA and Eclipse, we developed a computer software system and interface functions that allow previously developed electron chart checking (EcCk) methodologies to support these Varian systems. Methods: ARIA and Eclipse store most patient information in its MSSQL database. We studied the contents in the hundreds database tables and identified the data elements used for patient treatment management and treatment planning. Interface functions were developed in both c-sharp and MATLAB to support data access from ARIA and Eclipse servers using SQL queries. These functions and additional data processing functions allowed the existing rules and logics from EcCk to support ARIA and Eclipse. Dose and structure information are important for plan quality check, however they are not stored in the MSSQL database but as files in Varian private formats, and cannot be processed by external programs. We have therefore implemented a service program, which uses the DB Daemon and File Daemon services on ARIA server to automatically and seamlessly retrieve dose and structure data as DICOM files. This service was designed to 1) consistently monitor the data access requests from EcCk programs, 2) translate the requests for ARIA daemon services to obtain dose and structure DICOM files, and 3) monitor the process and return the obtained DICOM files back to EcCk programs for plan quality check purposes. Results: EcCk, which was previously designed to only support MOSAIQ TMS and Pinnacle TPS, can now support Varian ARIA and Eclipse. The new EcCk software has been tested and worked well in physics new start plan check, IMRT plan integrity and plan quality checks. Conclusion: Methods and computer programs have been implemented to allow EcCk to support Varian ARIA and Eclipse systems. This project was supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TU-F-BRD-01: Biomedical Informatics for Medical Physicists

Biomedical informatics encompasses a very large domain of knowledge and applications. This broad and loosely defined field can make it difficult to navigate. Physicists often are called upon to provide informatics services and/or to take part in projects involving principles of the field. The purpose of the presentations in this symposium is to help medical physicists gain some knowledge about the breadth of the field and how, in the current clinical and research environment, they can participate and contribute. Three talks have been designed to give an overview from the perspective of physicists and to provide a more in-depth discussion in two areas. One of the primary purposes, and the main subject of the first talk, is to help physicists achieve a perspective about the range of the topics and concepts that fall under the heading of 'informatics'. The approach is to de-mystify topics and jargon and to help physicists find resources in the field should they need them. The other talks explore two areas of biomedical informatics in more depth. The goal is to highlight two domains of intense current interest--databases and models--in enough depth into current approaches so that an adequate background for independent inquiry is achieved. These two areas will serve as good examples of how physicists, using informatics principles, can contribute to oncology practice and research. Learning Objectives: To understand how the principles of biomedical informatics are used by medical physicists. To put the relevant informatics concepts in perspective with regard to biomedicine in general. To use clinical database design as an example of biomedical informatics. To provide a solid background into the problems and issues of the design and use of data and databases in radiation oncology. To use modeling in the service of decision support systems as an example of modeling methods and data use. To provide a background into how uncertainty in our data and knowledge can be incorporated into modeling methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

WE-D-9A-06: Open Source Monitor Calibration and Quality Control Software for Enterprise Display Management

Purpose: Medical display monitor calibration and quality control present challenges to medical physicists. The purpose of this work is to demonstrate and share experiences with an open source package that allows for both initial monitor setup and routine performance evaluation. Methods: A software package, pacsDisplay, has been developed over the last decade to aid in the calibration of all monitors within the radiology group in our health system. The software is used to calibrate monitors to follow the DICOM Grayscale Standard Display Function (GSDF) via lookup tables installed on the workstation. Additional functionality facilitates periodic evaluations of both primary and secondary medical monitors to ensure satisfactory performance. This software is installed on all radiology workstations, and can also be run as a stand-alone tool from a USB disk. Recently, a database has been developed to store and centralize the monitor performance data and to provide long-term trends for compliance with internal standards and various accrediting organizations. Results: Implementation and utilization of pacsDisplay has resulted in improved monitor performance across the health system. Monitor testing is now performed at regular intervals and the software is being used across multiple imaging modalities. Monitor performance characteristics such as maximum and minimum luminance, ambient luminance and illuminance, color tracking, and GSDF conformity are loaded into a centralized database for system performance comparisons. Compliance reports for organizations such as MQSA, ACR, and TJC are generated automatically and stored in the same database. Conclusion: An open source software solution has simplified and improved the standardization of displays within our health system. This work serves as an example method for calibrating and testing monitors within an enterprise health system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-164: Estimation of DVH Variation for PTV Due to Interfraction Organ Motion in Prostate VMAT Using Gaussian Error Function

Purpose: We developed a method to predict the change of DVH for PTV due to interfraction organ motion in prostate VMAT without repeating the CT scan and treatment planning. The method is based on a pre-calculated patient database with DVH curves of PTV modelled by the Gaussian error function (GEF). Methods: For a group of 30 patients with different prostate sizes, their VMAT plans were recalculated by shifting their PTVs 1 cm with 10 increments in the anterior-posterior, left-right and superior-inferior directions. The DVH curve of PTV in each replan was then fitted by the GEF to determine parameters describing the shape of curve. Information of parameters, varying with the DVH change due to prostate motion for different prostate sizes, was analyzed and stored in a database of a program written by MATLAB. Results: To predict a new DVH for PTV due to prostate interfraction motion, prostate size and shift distance with direction were input to the program. Parameters modelling the DVH for PTV were determined based on the pre-calculated patient dataset. From the new parameters, DVH curves of PTVs with and without considering the prostate motion were plotted for comparison. The program was verified with different prostate cases involving interfraction prostate shifts and replans. Conclusion: Variation of DVH for PTV in prostate VMAT can be predicted using a pre-calculated patient database with DVH curve fitting. The computing time is fast because CT rescan and replan are not required. This quick DVH estimation can help radiation staff to determine if the changed PTV coverage due to prostate shift is tolerable in the treatment. However, it should be noted that the program can only consider prostate interfraction motions along three axes, and is restricted to prostate VMAT plan using the same plan script in the treatment planning system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-F-CAMPUS-I-05: Semi-Automated, Open Source MRI Quality Assurance and Quality Control Program for Multi-Unit Institution

Purpose: Phantom measurements allow for the performance of magnetic resonance (MR) systems to be evaluated. Association of Physicists in Medicine (AAPM) Report No. 100 Acceptance Testing and Quality Assurance Procedures for MR Imaging Facilities, American College of Radiology (ACR) MR Accreditation Program MR phantom testing, and ACR MRI quality control (QC) program documents help to outline specific tests for establishing system performance baselines as well as system stability over time. Analyzing and processing tests from multiple systems can be time-consuming for medical physicists. Besides determining whether tests are within predetermined limits or criteria, monitoring longitudinal trends can also help prevent costly downtime of systems during clinical operation. In this work, a semi-automated QC program was developed to analyze and record measurements in a database that allowed for easy access to historical data. Methods: Image analysis was performed on 27 different MR systems of 1.5T and 3.0T field strengths from GE and Siemens manufacturers. Recommended measurements involved the ACR MRI Accreditation Phantom, spherical homogenous phantoms, and a phantom with an uniform hole pattern. Measurements assessed geometric accuracy and linearity, position accuracy, image uniformity, signal, noise, ghosting, transmit gain, center frequency, and magnetic field drift. The program was designed with open source tools, employing Linux, Apache, MySQL database and Python programming language for the front and backend. Results: Processing time for each image is <2 seconds. Figures are produced to show regions of interests (ROIs) for analysis. Historical data can be reviewed to compare previous year data and to inspect for trends. Conclusion: A MRI quality assurance and QC program is necessary for maintaining high quality, ACR MRI Accredited MR programs. A reviewable database of phantom measurements assists medical physicists with processing and monitoring of large datasets. Longitudinal data can reveal trends that although are within passing criteria indicate underlying system issues.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-00: New Developments in Knowledge-Based Treatment Planning and Automation

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-02: Setting the Stage for Incorporation of Toxicity Measures in Treatment Plan Assessments

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their clinic have proven to be useful in error reduction in proton treatment planning, thus improving the effectiveness and safety of proton therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-241: Reduction in Planning Errors Via a Process Control Developed Using the Eclipse Scripting API

Purpose: Errors found during initial physics plan checks frequently require replanning and reprinting, resulting decreased departmental efficiency. Additionally, errors may be missed during physics checks, resulting in potential treatment errors or interruption. This work presents a process control created using the Eclipse Scripting API (ESAPI) enabling dosimetrists and physicists to detect potential errors in the Eclipse treatment planning system prior to performing any plan approvals or printing. Methods: Potential failure modes for five categories were generated based on available ESAPI (v11) patient object properties: Images, Contours, Plans, Beams, and Dose. An Eclipse script plugin (PlanCheck) was written in C# to check errors most frequently observed clinically in each of the categories. The PlanCheck algorithms were devised to check technical aspects of plans, such as deliverability (e.g. minimum EDW MUs), in addition to ensuring that policy and procedures relating to planning were being followed. The effect on clinical workflow efficiency was measured by tracking the plan document error rate and plan revision/retirement rates in the Aria database over monthly intervals. Results: The number of potential failure modes the PlanCheck script is currently capable of checking for in the following categories: Images (6), Contours (7), Plans (8), Beams (17), and Dose (4). Prior to implementation of the PlanCheck plugin, the observed error rates in errored plan documents and revised/retired plans in the Aria database was 20% and 22%, respectively. Error rates were seen to decrease gradually over time as adoption of the script improved. Conclusion: A process control created using the Eclipse scripting API enabled plan checks to occur within the planning system, resulting in reduction in error rates and improved efficiency. Future work includes: initiating full FMEA for planning workflow, extending categories to include additional checks outside of ESAPI via Aria database queries, and eventual automated plan checks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Catalog of topological phonon materials

Phonons play a crucial role in many properties of solid-state systems, and it is expected that topological phonons may lead to rich and unconventional physics. On the basis of the existing phonon materials databases, we have compiled a catalog of topological phonon bands for more than 10,000 three-dimensional crystalline materials. Using topological quantum chemistry, we calculated the band representations, compatibility relations, and band topologies of each isolated set of phonon bands for the materials in the phonon databases. Additionally, we calculated the real-space invariants for all the topologically trivial bands and classified them as atomic or obstructed atomic bands. We have selected more than 1000 “ideal” nontrivial phonon materials to motivate future experiments. The datasets were used to build the Topological Phonon Database.

Science & Technology - Other Topics↗

DOE OSTI2018

Nonpareil 3: Fast Estimation of Metagenomic Coverage and Sequence Diversity

Estimations of microbial community diversity based on metagenomic data sets are affected, often to an unknown degree, by biases derived from insufficient coverage and reference database-dependent estimations of diversity. For instance, the completeness of reference databases cannot be generally estimated since it depends on the extant diversity sampled to date, which, with the exception of a few habitats such as the human gut, remains severely undersampled. Further, estimation of the degree of coverage of a microbial community by a metagenomic data set is prohibitively time-consuming for large data sets, and coverage values may not be directly comparable between data sets obtained with different sequencing technologies. Here, we extend Nonpareil, a database-independent tool for the estimation of coverage in metagenomic data sets, to a high-performance computing implementation that scales up to hundreds of cores and includes, in addition, a k -mer-based estimation as sensitive as the original alignment-based version but about three hundred times as fast. Further, we propose a metric of sequence diversity ( N d ) derived directly from Nonpareil curves that correlates well with alpha diversity assessed by traditional metrics. We use this metric in different experiments demonstrating the correlation with the Shannon index estimated on 16S rRNA gene profiles and show that N d additionally reveals seasonal patterns in marine samples that are not captured by the Shannon index and more precise rankings of the magnitude of diversity of microbial communities in different habitats. Therefore, the new version of Nonpareil, called Nonpareil 3, advances the toolbox for metagenomic analyses of microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

DB Schema Export Tool

Exports Sql Server database objects as schema files. Exported objects include tables, views, stored procedures, and functions,plus also database properties including database roles and logins. The program can also export table data to create SQL files with an Insert Into statement for each row.

Monroe, Matthew↗

DOE OSTI2016

Environmental and Molecular Science Laboratory Arrow

Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.

Source record↗

DOE OSTI2022

Sequence ID Map (SeqIDMap) v1.0

This is a web service that allows users to request an identifier for a sequence in a specific database, given another identifier for the same sequence with respect to another given database. This process is called ID mapping. It's a minimalist service (fast, no database server) that will be significantly easier to use in a container environment.

Johnson, Jeffrey↗