Literature DB >> 15191763

The PLUNC 3D treatment planning system: a dynamic alternative to commercially available systems.

Marshall A Tewell1, Robert Adams.   

Abstract

Three-dimensional (3D) treatment planning is an integral step in the treatment of various cancers when radiation is prescribed as either the primary or adjunctive modality, especially when the gross tumor volume lies in a difficult to reach area or is proximal to critical bodily structures. Today, 3D systems have made it possible to more precisely localize tumors in order to treat a higher ratio of cancer cells to normal tissue. Over the past 15 years, these systems have evolved into complex tools that utilize powerful computational algorithms that offer diverse functional capabilities, while simultaneously attempting to maintain a user-friendly quality. A major disadvantage of commercial systems is that users do not have access to the programming source code, resulting in significantly limited clinical and technological flexibility. As an alternative, in-house systems such as Plan-UNC (PLUNC) offer optimal flexibility that is vital to research institutions and important to treatment facilities. Despite this weakness, commercially available systems have become the norm because their commissioning time is significantly less and because many facilities do not have computer experts on-site.

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Year:  2004        PMID: 15191763     DOI: 10.1016/j.meddos.2004.03.014

Source DB:  PubMed          Journal:  Med Dosim        ISSN: 1873-4022            Impact factor:   1.482


  5 in total

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Authors:  Kyle Wang; Michael J Eblan; Allison M Deal; Matthew Lipner; Timothy M Zagar; Yue Wang; Panayiotis Mavroidis; Carrie B Lee; Brian C Jensen; Julian G Rosenman; Mark A Socinski; Thomas E Stinchcombe; Lawrence B Marks
Journal:  J Clin Oncol       Date:  2017-01-23       Impact factor: 50.717

2.  Evaluation of PET/MRI for Tumor Volume Delineation for Head and Neck Cancer.

Authors:  Kyle Wang; Brandon T Mullins; Aaron D Falchook; Jun Lian; Kelei He; Dinggang Shen; Michael Dance; Weili Lin; Tiffany M Sills; Shiva K Das; Benjamin Y Huang; Bhishamjit S Chera
Journal:  Front Oncol       Date:  2017-01-23       Impact factor: 6.244

3.  Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning.

Authors:  Henry Wang; Lei Xing
Journal:  J Appl Clin Med Phys       Date:  2016-11-08       Impact factor: 2.102

4.  A Safe and Practical Cycle for Team-Based Development and Implementation of In-House Clinical Software.

Authors:  Jean M Moran; Kelly C Paradis; Scott W Hadley; Martha M Matuszak; Charles S Mayo; Katherine Woch Naheedy; Xiaoping Chen; Dale W Litzenberg; James Irrer; Maria G Ditman; Pam Burger; Marc L Kessler
Journal:  Adv Radiat Oncol       Date:  2021-09-15

5.  Teaching treatment planning for protons with educational open-source software: experience with FoCa and matRad.

Authors:  Daniel Sanchez-Parcerisa; Jose Udías
Journal:  J Appl Clin Med Phys       Date:  2018-05-12       Impact factor: 2.102

  5 in total

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