Package: dvha
DVH Analytics (DVHA) is a software application for building a local database of radiation oncology
treatment planning data. It imports data from DICOM-RT files (i.e., plan, dose, and structure), creates a SQL database,
provides customizable plots, and provides tools for generating linear, multi-variable, and machine learning
regressions.DocumentationBe sure to check out thelatest releasefor the user manual PDF, which is geared towards the user interface. For
power-users,dvha.readthedocs.iocontains detailed documentation for backend tools (e.g., if you want to
perform queries with python commands).ExecutablesExecutable versions of DVHA can be foundhere.
Please keep in mind this software is still in beta. If you have issues, compiling from source may be more informative.AboutIn addition to viewing DVH data, this software provides methods to:download queried datacreate time-series plots of various planning and dosimetric variablescalculate correlationsgenerate multi-variable linear and machine learning regressionsshare regression models with other DVHA usersadditional screenshots availablehereThe code is built with these core libraries:wxPython Phoenix- Build a native GUI on Windows, Mac, or Unix systemsPydicom- Read, modify and write DICOM files with python codedicompyler-core- A library of core radiation therapy modules for DICOM RTBokeh- Interactive Web Plotting for Pythonscikit-learn- Machine Learning in PythonInstallationTo install via pip:$pipinstalldvhaIf you’ve installed via pip or setup.py, launch from your terminal with:$dvhaIf you’ve cloned the project, but did not run the setup.py installer, launch DVHA with:$pythondvha_app.pySee ourinstallation notesfor potential
Shapely install issues on MS Windows and help setting up a PostgreSQL database if it is preferred over SQLite3.DependenciesPython>3.5wxPython Phoenix>= 4.0.4, < 4.1.0Pydicom>=1.4.0dicompyler-core>= 0.5.4Bokeh>= 1.2.0, < 2.0.0PostgreSQL(optional) andpsycopg2SQLite3SciPyNumPyShapely< 1.7.0Statsmodels>=0.8.0Scikit-imageScikit-learn>= 0.21.0regressorsRapidFuzzseleniumPhantomJSDVHA MLC AnalyzerSupportIf you like DVHA and would like to support our mission, all we ask is that you cite us if we helped your
publication, or help the DVHA community by submitting bugs, issues, feature requests, or solutions on theissues page.CiteDOI:https://doi.org/10.1002/acm2.12401Cutright D, Gopalakrishnan M, Roy A, Panchal A, and Mittal BB. “DVH Analytics: A DVH database for clinicians and researchers.” Journal of Applied Clinical Medical Physics 19.5 (2018): 413-427.The previous web-based version described in the above publication can be foundherebut is no longer being developed.Related PublicationsDOI:http://doi.org/10.1002/mp.14795Roy A, Widjaja R, Wang M, Cutright D, Gopalakrishnan M, Mittal BB. “Treatment plan quality control using multivariate control charts.” Medical Physics. (2021).DOI:https://doi.org/10.1016/j.adro.2019.11.006Roy A, Cutright D, Gopalakrishnan M, Yeh AB, and Mittal BB. “A Risk-Adjusted Control Chart to Evaluate IMRT Plan Quality.” Advances in Radiation Oncology (2019).Selected Studies Using DVHA5,000 PatientsNational Cancer Institute (5R01CA219013-03): Active 8/1/17 → 7/31/22Retrospective NCI Phantom-Monte Carlo Dosimetry for Late Effects in Wilms TumorBrannigan R (Co-Investigator), Kalapurakal J (PD/PI), Kazer R (Co-Investigator)265 PatientsDOI:https://doi.org/10.1016/j.ijrobp.2019.06.2509Gross J, et al. “Determining the organ at risk for lymphedema after regional nodal irradiation in
breast cancer.” International Journal of Radiation Oncology* Biology* Physics 105.3 (2019): 649-658.