Fractional labelmaps for computing accurate dose volume histograms

Kyle Sunderland, Csaba Pinter, Andras Lasso, Gabor Fichtinger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

PURPOSE: In radiation therapy treatment planning systems, structures are represented as parallel 2D contours. For treatment planning algorithms, structures must be converted into labelmap (i.e. 3D image denoting structure inside/outside) representations. This is often done by triangulated a surface from contours, which is converted into a binary labelmap. This surface to binary labelmap conversion can cause large errors in small structures. Binary labelmaps are often represented using one byte per voxel, meaning a large amount of memory is unused. Our goal is to develop a fractional labelmap representation containing non-binary values, allowing more information to be stored in the same amount of memory. METHODS: We implemented an algorithm in 3D Slicer, which converts surfaces to fractional labelmaps by creating 216 binary labelmaps, changing the labelmap origin on each iteration. The binary labelmap values are summed to create the fractional labelmap. In addition, an algorithm is implemented in the SlicerRT toolkit that calculates dose volume histograms (DVH) using fractional labelmaps. RESULTS: We found that with manually segmented RANDO® head and neck structures, fractional labelmaps represented structure volume up to 19.07% (average 6.81%) more accurately than binary labelmaps, while occupying the same amount of memory. When compared to baseline DVH from treatment planning software, DVH from fractional labelmaps had agreement acceptance percent (1% ?D, 1% ?V) up to 57.46% higher (average 4.33%) than DVH from binary labelmaps. CONCLUSION: Fractional labelmaps promise to be an effective method for structure representation, allowing considerably more information to be stored in the same amount of memory.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2017
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
PublisherSPIE
Volume10135
ISBN (Electronic)9781510607156
DOIs
StatePublished - 2017
Externally publishedYes
EventMedical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling - Orlando, United States
Duration: Feb 14 2017Feb 16 2017

Other

OtherMedical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling
CountryUnited States
CityOrlando
Period2/14/172/16/17

Keywords

  • Dose volume histogram
  • Fractional labelmap
  • Radiation therapy
  • Treatment planning

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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