======Project 14:====== 
=====Towards Correlation of Clinical Outcomes with Radiation Therapy Dose Distribution=====
**Last updated: 05/5/16 at 1:00PM**


======Summary======
Correlate clinical outcomes with refined dose distributions on critical structures

Goals:
  * To refine the datasets and infrastructure required for predicting clinical outcomes using past patient data. 
  * Make the first steps towards accurate toxicity and outcome predictions in a commercial, cloud computing platform.


**Students:** Alex Mathews, Pranav Lakshminarayanan

**Mentor(s):** Dr. Todd McNutt, Dr. Russell Taylor


======Background and Significance======
With cancer treatments, there is a tradeoff between clinical effectiveness and deleterious side effects. 

The ability to predict clinical outcomes for a particular patient (taking into account unique anatomy and condition) would allow oncologists to make more informed decisions regarding patient treatment plans.
======Deliverables======
 
  * **Minimum:** (Expected by March 27)
    * Set up a queryable infrastructure with anonymized patient data
    * Implementation and testing of deformable registration algorithm

  * **Expected:** (Expected by April 24)
    * Implementation and validation of deformable registration algorithm on the dataset
    * Design dose mapping algorithm

  * **Maximum:** (Expected by May 6)
    * Implementation of dose mapping algorithm



======Technical Approach======
The steps to achieve our goals are as follows:
1. Set up a development database within the Hopkins network
    * Store anonymized patient data, scans or binary masks, and clinical outcomes
    * Must be queryable and accessible by other devices
{{ :courses:446:2016:446-2016-14:techapproach1.png?500 |}}
      
2. Deformable registration of critical structures
    * Currently, we are looking at the head and neck region, specifically the parotid glands
    * The deformable registration would bring images into one reference frame
3. Dose distribution mapping
    * Based on how dose is applied, generate a 3D map of received dose over the critical structure
    * Partition the organ in a way to allow for insightful analytics

{{ :courses:446:2016:446-2016-14:techapproach2.png?700 |}}
======Dependencies======
Access to Oncospace database
  * Complete

Access to space on Hopkins network
  * Complete

Github repositories and access to Oncospace codebase
  * Complete
======Milestones and Status ======

**Projected Timeline:**
{{ :courses:446:2016:446-2016-14:ganttchart.png?750 |}}

**Milestones:**
  - Obtain and set up server
    * Planned Date: March 12
    * Status: In progress
  - Infrastructure and endpoint documentation
    * Planned Date: March 19
    * Status: In progress
  - Data transfer from Oncospace database
    * Planned Date: March 27
    * Status: Planned
  - Implement deformable registration algorithm on test data  
    * Planned Date: March 27
    * Status: In progress
  - Implement deformable registration on full dataset
    * Planned Date: April 17
    * Status: Planned
  - Implement dose mapping algorithm on full dataset
    * Planned Date: April 30
    * Status: Planned

======Reports and presentations======

  * Project Plan
    * {{:courses:446:2016:446-2016-14:oncospace-cis2-proposal-presentation.pdf| Project plan presentation}}
    * {{:courses:446:2016:446-2016-14:project_proposal.pdf|Project plan proposal}}
  * Project Background Reading 
    * See Bibliography below for links.
  * Project Checkpoint
    * {{:courses:446:2016:446-2016-14:checkpoint_presentation.pdf| Project checkpoint presentation}}
  * Paper Seminar Presentations
    * here provide links to all seminar presentations
  * Project Final Presentation
    * {{:courses:446:2016:446-2016-14:final_poster_pdf.pdf|PDF of Poster}}
  * Project Final Report
    * {{:courses:446:2016:446-2016-14:final_report.pdf|Final Report}}
    * links to any appendices or other material

======Project Bibliography=======

Bentzen, S. M., Constine, L. S., Deasy, J. O., Eisbrunch, A., Jackson, A., Marks, L. B., Haken, R. K. T., & Yorke, E. D. (2010). Quantitative analysis of normal tissue effects in the clinic (QUANTEC): An introduction to the scientific issues. International Journal of Radiation Oncology Biology Physics, 76(3), S3–S9. 

Bhide SA, Newbold KL, Harrington KJ, Nutting CM. Clinical evaluation of intensity-modulated radiotherapy for head and neck cancers. The British Journal of Radiology. 2012;85(1013):487-494. doi:10.1259/bjr/85942136.

Fumbeya Marungo, Hilary Paisley, John Rhee, Todd McNutt, Scott Robertson, Russell Taylor, “Big Data Meets Medical Physics Dosimetry” (2014)

Kutcher, G., Burman, C., Brewster, L., Goitein, M., & Mohan, R. (1991). Histogram re- duction method for calculating complication probabilities for three-dimensional treatment planning evaluations. International Journal of Radiation Oncology* Biology* Physics, 21(1), 137–146.

Michael Kazhdan, Patricio Simari, Todd McNutt, Binbin Wu, Robert Jacques, Ming Chuang, and Russell Taylor, “A Shape Relationship Descriptor for RadiationTherapy Planning” Medical Image Computing and Computer-Assisted Intervention 5762/2009(12), 100–108 (2009)

Steven F. Petit, Binbin Wu, Michael Kazhdan , André Dekker, Patricio Simari, Rachit Kumar, Russell Taylor, Joseph M. Herman, Todd McNutt,” Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma”, Radiotherapy and Oncology, 102 (2012) 38–44.


======Other Resources and Project Files======
Coming soon...