dvha 0.7.1rc2

Create a database of DVHs, GUI with wxPython, plots with Bokeh

  

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Welcome to the brand new DVH Analytics (DVHA), rewritten as a native OS application with wxPython. The previous web-based version can be found here but is no longer being developed.

DVHA Executables

Executable versions of DVHA can be found here. Please keep in mind this software is still in beta. If you have issues, compiling from source may be more informative.

Admin Rights No Longer Needed

As of v0.6.7, DVHA supports both SQLite and PostgreSQL.

SQLite:

• No admin rights needed on your computer
• No need to figure out how to make user logins and databases in SQL
• Easier to share your database - just zip (and encrypt), send to colleague

PostgreSQL:

• Supports multiple instances of DVHA accessing the same database at once
• Database may be housed remotely (just need the accessible IP address)
• Supports user login and password

Additional SQLite vs PostgreSQL information can be found here.

About

DVH Analytics is a software application to help radiation oncology departments build an in-house database of treatment planning data for the purpose of historical comparisons and statistical analysis.

The application builds a SQL database of DVHs and various planning parameters from DICOM files (i.e., Plan, Structure, Dose). Since the data is extracted directly from DICOM files, we intend to accommodate an array of treatment planning system vendors.

In addition to viewing DVH data, this software provides methods to:

• download queried data
• create time-series plots of various planning and dosimetric variables
• calculate correlations
• generate multi-variable linear and machine learning regressions.
• additional screenshots available here

The code is built upon these core libraries:

• wxPython Phoenix - Build a native GUI on Windows, Mac, or Unix systems
• Pydicom - Read, modify and write DICOM files with python code
• dicompyler-core - Extensible radiation therapy research platform and viewer for DICOM and DICOM RT
• Bokeh - Interactive Web Plotting for Python
• scikit-learn - Machine Learning in Python

Installation

To install via pip:

pip install dvha

If you've installed via pip or setup.py, launch from your terminal with:

dvha

If you've cloned the project, but did not run the setup.py installer, launch DVHA with:

python dvha_app.py

See our installation notes for potential Shapely install issues on MS Windows and help setting up a PostgreSQL database if it is preferred over SQLite3.

Dependencies

• Python >3.5
• wxPython Phoenix >= 4.0.4
• Pydicom >=1.0
• dicompyler-core 0.5.3
• Bokeh >= 1.2.0
• PostgreSQL (optional) and psycopg2
• SQLite3
• SciPy
• NumPy
• Shapely
• Statsmodels 0.8.0
• Scikit-learn
• regressors

Support

If 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 the issues page.

Cite

DOI: https://doi.org/10.1002/acm2.12401
Cutright 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.

DOI: https://doi.org/10.1016/j.adro.2019.11.006
Roy 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).