Decision support tools for proton therapy ePR: intelligent treatment planning navigator and radiation toxicity tool for evaluating of prostate cancer treatment

2010 ◽  
Author(s):  
Anh H. Le ◽  
Ruchi Deshpande ◽  
Brent J. Liu
Keyword(s):  
Prostate Cancer ◽  
Decision Support ◽  
Cancer Treatment ◽  
Treatment Planning ◽  
Proton Therapy ◽  
Radiation Toxicity ◽  
Decision Support Tools ◽  
Prostate Cancer Treatment ◽  
Support Tools

Positioning accuracy and daily dose assessment for prostate cancer treatment using in‐room CT image guidance at a proton therapy facility

2018 ◽  
Vol 45 (5) ◽  
pp. 1832-1843 ◽  
Author(s):  
Yoshikazu Maeda ◽  
Yoshitaka Sato ◽  
Hiroki Minami ◽  
Yutaka Yasukawa ◽  
Kazutaka Yamamoto ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Treatment ◽  
Proton Therapy ◽  
Image Guidance ◽  
Dose Assessment ◽  
Ct Image ◽  
Prostate Cancer Treatment ◽  
Positioning Accuracy ◽  
Daily Dose ◽  
Proton Therapy Facility

WE-AB-209-11: Prostate Cancer Treatment Planning: Sensitivity and Representative Objective Function Weights

2016 ◽  
Vol 43 (6Part39) ◽  
pp. 3803-3803
Author(s):  
A. Goli ◽  
J.J. Boutilier ◽  
T. Craig ◽  
M.B. Sharpe ◽  
T.C.Y. Chan
Keyword(s):  
Prostate Cancer ◽  
Cancer Treatment ◽  
Objective Function ◽  
Treatment Planning ◽  
Prostate Cancer Treatment

scholarly journals Coverage-based treatment planning to accommodate deformable organ variations in prostate cancer treatment

2014 ◽  
Vol 41 (10) ◽  
pp. 101705 ◽  
Author(s):  
Huijun Xu ◽  
Douglas J. Vile ◽  
Manju Sharma ◽  
J. James Gordon ◽  
Jeffrey V. Siebers
Keyword(s):  
Prostate Cancer ◽  
Cancer Treatment ◽  
Treatment Planning ◽  
Prostate Cancer Treatment

scholarly journals Coverage-based treatment planning to accommodate delineation uncertainties in prostate cancer treatment

2015 ◽  
Vol 42 (9) ◽  
pp. 5435-5443 ◽  
Author(s):  
Huijun Xu ◽  
J. James Gordon ◽  
Jeffrey V. Siebers
Keyword(s):  
Prostate Cancer ◽  
Cancer Treatment ◽  
Treatment Planning ◽  
Prostate Cancer Treatment

A Knowledge-Based Imaging Informatics Approach for Managing Proton Beam Therapy of Cancer Patients

2007 ◽  
Vol 6 (4_suppl) ◽  
pp. 77-84 ◽  
Author(s):  
Brent J. Liu
Keyword(s):  
Decision Making ◽  
Radiation Therapy ◽  
Decision Support ◽  
Treatment Planning ◽  
Imaging Informatics ◽  
Patient Treatment ◽  
Decision Support Tools ◽  
Knowledge Based ◽  
Support Tools ◽  
Dicom Rt

The need for a unified patient-oriented information system to handle complex proton therapy (PT) imaging and informatics data during the course of patient treatment is becoming steadily apparent due to the ever increasing demands for better diagnostic treatment planning and more accurate information. Currently, this information is scattered throughout each of the different treatment and information systems in the oncology department. Furthermore, the lack of organization with standardized methods makes it difficult and time-consuming to navigate through the maze of data, resulting in challenges during patient treatment planning. We present a methodology to develop this electronic patient record (ePR) system based on DICOM standards and perform knowledge-based medical imaging informatics research on specific clinical scenarios where patients are treated with PT. Treatment planning is similar in workflow to traditional radiation therapy (RT) methods such as intensity-modulated radiation therapy (IMRT), which utilizes a priori knowledge to drive the treatment plan in an inverse manner. In March 2006, two new RT objects were drafted in a DICOM-RT Supplement 102 specifically for ion therapy, which includes PT. The standardization of DICOM-RT-ION objects and the development of a knowledge base as well as decision-support tools that can be add-on features to the ePR DICOM-RT system were researched. This methodology can be used to extend to PT and the development of future clinical decision-making scenarios during the course of the patient's treatment that utilize “inverse treatment planning.” We present the initial steps of this imaging and informatics methodology for PT and lay the foundation for development of future decision-support tools tailored to cancer patients treated with PT. By integrating decision-support knowledge and tools designed to assist in the decision-making process, a new and improved “ knowledge-enhanced treatment planning” approach can be realized.

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