A spatially encoded dose difference maximal intensity projection map for patient dose evaluation: a new first line
Weigang Hu1, Pierre Graff, Thomas Boettger
1Department of Radiation Oncology, University of California, San Francisco, San Francisco, California 94143, USA.
Purpose:
To develop a spatially encoded dose difference maximal intensity projection (DD-MIP) as an online patient dose evaluation tool for visualizing the dose differences between the planning dose and dose on the treatment day.
Methods:
Megavoltage cone-beam CT (MVCBCT) images acquired on the treatment day are used for generating the dose difference index. Each index is represented by different colors for underdose, acceptable, and overdose regions. A maximal intensity projection (MIP) algorithm is developed to compress all the information of an arbitrary 3D dose difference index into a 2D DD-MIP image. In such an algorithm, a distance transformation is generated based on the planning CT. Then, two new volumes representing the overdose and underdose regions of the dose difference index are encoded with the distance transformation map. The distance-encoded indices of each volume are normalized using the skin distance obtained on the planning CT. After that, two MIPs are generated based on the underdose and overdose volumes with green-to-blue and green-to-red lookup tables, respectively. Finally, the two MIPs are merged with an appropriate transparency level and rendered in planning CT images.
Results:
The spatially encoded DD-MIP was implemented in a dose-guided radiotherapy prototype and tested on 33 MVCBCT images from six patients. The user can easily establish the threshold for the overdose and underdose. A 3% difference between the treatment and planning dose was used as the threshold in the study; hence, the DD-MIP shows red or blue color for the dose difference > 3% or < or = 3%, respectively. With such a method, the overdose and underdose regions can be visualized and distinguished without being overshadowed by superficial dose differences.
Conclusions:
A DD-MIP algorithm was developed that compresses information from 3D into a single or two orthogonal projections while hinting the user whether the dose difference is on the skin surface or deeper.
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