BIGDOSE: software for 3D personalized targeted radionuclide therapy dosimetry

Tiantian Li; Licheng Zhu; Zhonglin Lu; Na Song; Ko-Han Lin; Greta S P Mok

doi:10.21037/qims.2019.10.09

BIGDOSE: software for 3D personalized targeted radionuclide therapy dosimetry

Quant Imaging Med Surg. 2020 Jan;10(1):160-170. doi: 10.21037/qims.2019.10.09.

Authors

Tiantian Li¹, Licheng Zhu², Zhonglin Lu¹, Na Song³, Ko-Han Lin⁴, Greta S P Mok^{1

5

6}

Affiliations

¹ Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, University of Macau, Macau SAR, China.
² Department of Computer Science, Faculty of Science and Technology, University of Macau, Macau SAR, China.
³ Department of Nuclear Medicine, Albert Einstein College of Medicine, Yeshiva University, Bronx, New York, USA.
⁴ Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
⁵ Faculty of Health Sciences, Institute of Collaborative Innovation, University of Macau, Macau SAR, China.
⁶ Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau SAR, China.

Abstract

Background: Advance 3D quantitative radionuclide imaging techniques boost the accuracy of targeted radionuclide therapy (TRT) dosimetry to voxel level. The goal of this work is to develop a comprehensive 3D dosimetric software, BIGDOSE, with new features of image registration and virtual CT for patient-specific dosimetry.

Methods: BIGDOSE includes a portable graphical user interface written in Python, integrating (I) input of sequential ECT/CT images; (II) segmentation; (III) non-rigid image registration; (IV) curve fitting and voxel-based integration; (V) dose conversion and (VI) 3D dose analysis. The accuracy of the software was evaluated using a simulation study with 9 XCAT phantoms. We simulated SPECT/CT acquisitions at 1, 12, 24, 72 and 144-hrs post In-111 Zevalin injection with inter-scans misalignments using an analytical projector for medium energy general purpose (MEGP) collimator, modeling attenuation, scatter and collimator-detector response. The SPECT data were reconstructed using quantitative OS-EM method. A CT organ-based registration was performed before the dose calculation. Organ absorbed doses for the corresponding Y-90 therapeutic agent were calculated on target organs and compared with those obtained from OLINDA/EXM, using dose measured from GATE as the gold standard. One patient with In-111 DTPAOC injection as well as two patients with Y-90 microsphere embolization were used to demonstrate the clinical effectiveness of our software.

Results: In the simulation, the organ dose errors of BIGDOSE were -9.59%±9.06%, -8.36±5.82%, -23.41%±6.67%, -6.05%±2.06% for liver, spleen, kidneys and lungs, while they were -25.72%±12.52%, -14.93%±10.91%, -28.63%±12.97% and -45.30%±5.84% for OLINDA/EXM. Cumulative dose volume histograms, dose maps and iso-dose contours provided 3D dose distribution information on the simulated and patient data.

Conclusions: BIGDOSE provides a one-stop platform for voxel-based dose estimation with enhanced functions. It is a promising tool to streamline the current clinical TRT dosimetric practice with high accuracy, incorporating 3D personalized imaging information for improved treatment outcome.

Keywords: Targeted radionuclide therapy (TRT); dosimetric software; image registration; patient-specific internal dosimetry.