TH-AB-BRA-10: Clinical Implementation of a Grid-Based Boltzmann Solver with Adaptive Meshing for Nuclear Medicine Dosimetry

Authors

  • Mikell J,

    1. Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX
    2. University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX
    3. Christiana Care Hospital, Newark, DE
    4. Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston TX
    5. Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA
    6. Varian Medical Systems, Palo Alto, CA
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  • Mourtada F,

    1. Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX
    2. University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX
    3. Christiana Care Hospital, Newark, DE
    4. Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston TX
    5. Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA
    6. Varian Medical Systems, Palo Alto, CA
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  • Wareing T,

    1. Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX
    2. University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX
    3. Christiana Care Hospital, Newark, DE
    4. Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston TX
    5. Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA
    6. Varian Medical Systems, Palo Alto, CA
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  • Kappadath S

    1. Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX
    2. University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX
    3. Christiana Care Hospital, Newark, DE
    4. Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston TX
    5. Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA
    6. Varian Medical Systems, Palo Alto, CA
    Search for more papers by this author

Abstract

Purpose:

We previously compared the Grid-Based Boltzmann Solver (GBBS) with DOSXYZnrc Monte Carlo (MC) for beta and gamma sources in uniform materials and along material interfaces. The current standard in nuclear medicine is MIRD, which only calculates mean organ doses assuming uniform uptake in anthropomorphic phantoms. This work extends GBBS to clinical nuclear medicine for fast and accurate patient-specific voxel-level dosimetry.

Methods:

We compared the GBBS with MC using a patient's post-therapy quantitative 90Y microsphere bremsstrahlung SPECT/CT.The GBBS (Attila™ v8.0.0) requires a tetrahedral mesh as input instead of voxels. Adaptive tetrahedral meshes were generated with TetGen v1.5.0 by folding CT and SPECT images into a mesh sizing function; the function was defined at each node on a background mesh with nodes defined at each SPECT/CT voxel. Target tetrahedral edge lengths varied from 0.5 to 8 cm and were adapted on SPECT activity level, CT material, and material gradient.GBBS used 30 electron energy groups, 32 angles, and 67,000 tetrahedrons. GBBS reported point data aligned with the center of SPECT/CT voxels which match MC. We report: 1) run time of the GBBS, 2) average difference in non-zero absorbed dose voxels, and 3) percent difference in mean absorbed dose to tumor and normal liver. DVHs and isodose curves were visually compared, and the tetrahedral mesh was compared to SPECT/CT.

Results:

GBBS calculation required 2 minutes. The average difference over all non-zero absorbed dose voxels (N=318,000) was −0.2 Gy. GBBS mean doses agreed within 1% of MC for both normal liver (39.1 Gy vs 39.3 Gy) and tumor (317 Gy vs 320 Gy). Adaptive meshing allowed sufficient material assignment and yielded smaller tetrahedrons near high activity regions and bone. DVHs had excellent visual agreement.

Conclusions:

GBBS with adaptive meshing is practical for fast and accurate clinical nuclear medicine dosimetry.

Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA138986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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