User Interface for Refined Dose-Toxicity Analysis in Radiotherapy

Last updated: Tue May 1 13:30


The goal of this project is to develop a web-based user interface for radio dose toxicity analysis.

  • Students: Alaleh Azhir, Santiago Appiani, William Franceschi
  • Mentor(s): Dr. Todd McNutt, Pranav Lakshminarayanan

Completed UI with yellow representing the DVH and segmentation pipeline, and blue representing auxiliary features and download optionsaua:

Background, Specific Aims, and Significance

Physicians lack a simple method to quantitatively analyze dose distributions within organs before, during and after treatment. A user interface with 3D rendering would allow physicians to better analyze dose distributions before treatment, and make necessary adjustments to the treatment plan. Currently, there exist no simple tools for clinicians or researchers for extracting and analyzing dosage features of treatment plans.

Specific Aims:

  1. Compatible with existing online SQL database for obtaining the medically related data
  2. Create interactive 3D visualizations of objects using JavaScript libraries such as D3.js
  3. Allow physician to easily use segmenting tools on organs, run analysis on new regions
  4. Display the results using interactive DVH histograms on the website
  5. Allow new feature analysis scripts to be easily added to the existing user interface
  6. Enable the users to Download the results of the analyses from the web


  • Minimum: (completed)
    1. A UI for visualizing organs in 3D, calculating DVH curves, and running python analysis scripts from the javascript layer
    2. Documentation
  • Expected: (completed)
    1. A UI for segmenting and analyzing organs in 3D using a list of segmentation options.
    2. Dose-volume data analysis scripts are integrated and can be performed on segments of organs.
    3. Results of the analysis can be exported.
  • Maximum: (ongoing)
    1. An interactive UI for segmenting and analyzing organs in 3D with a flexible segmentation as indicated by the user in addition to the existing ones. (additional segmentation feature ongoing)
    2. Create and export DVH data for batch of patients (completed)
    3. Extract specific points on DVH given list of doses (completed)
    4. User friendly - help direct user step by step & notify user with loading screen for long processes (completed)

Technical Approach

1. Set up Python Web Framework on the back-end

2. Set up front-end visualizations:

  • Choose Library for data selection features
  • D3 Library for DBH curves and object 3D visualization
  • Include options, and later text boxes to help user segment data

3. Enabling communication between back and front end using XHR requests

4. Enabling user to download the results of the analysis as a .csv file


- Dependency : Access to Database

  • Resolution Date: 2/13

- Dependency : Access to DVH analysis Code

  • Resolution Date: 2/13

- Dependency : Access to Pranav's Segmentation Code

  • Resolution Date: 3/7

Milestones and Status

  1. Milestone name: Basic Website Framework
    • Planned Date: 2/27
    • Expected Date: 2/27
    • Status: Complete
  2. Milestone name: Choosing Js Libraries
    • Planned Date: 2/27
    • Expected Date: 2/27
    • Status: Complete
  3. Milestone name: Basic UI with DVH
    • Planned Date: 3/15
    • Expected Date: 3/15
    • Status: Complete
  4. Milestone name: Exporting Data
    • Planned Date: 3/27
    • Expected Date: 3/27
    • Status: Complete
  5. Milestone name: Interact with 3D Visual Representation of ROIs
    • Planned Date: 4/1
    • Expected Date: 4/1
    • Status: Complete
  6. Milestone name: Integrate segmentation tools
    • Planned Date: 4/10
    • Expected Date: 4/15
    • Status: Complete
  7. Milestone name: Finialize Documentation
    • Planned Date: 4/15
    • Expected Date: 4/15
    • Status: Complete
  8. Milestone name: Add customizable Segmentation Tools
    • Planned Date: 4/25
    • Expected Date: 4/25
    • Status: Ongoing

Reports and presentations

Project Bibliography

* Lakshminarayanan, P. (2017). Radio-morphology: Parametric Shape-Based Features in Radiotherapy (Unpublished master's thesis). Johns Hopkins University.

* McNutt, T., PhD., & Lakshminarayanan, P. (2018, February 6). User Interface to Extract radio-morphologic features for refined dose-toxicity analysis in radiotherapy. Lecture presented at CIS II Lecture in Hackerman B17, Baltimore, MD.

* Chen R, Gabriel P, Kavanagh B, McNutt T, “How will big data impact clinical decision making and precision medicine in radiation therapy?” Int’l J. of Radiation Oncology, Biology, Physics. Published online: November 27 2015

Other Resources and Project Files

courses/456/2018/456-2018-05/project-05.txt · Last modified: 2019/08/07 12:01 (external edit)