Impact of Realistic 3D Tumor Microarchitecture on Cellular Dosimetry and Radiobiological Response in Targeted Radionuclide Therapy
- 1School of Computing Technologies, RMIT University, Melbourne
Abstract
Background: Patient-specific dosimetry in targeted radionuclide therapy (TRT) is increasingly supported by quantitative imaging; however, voxel-scale dose estimates cannot resolve cellular and subcellular heterogeneity present within tumor tissue. Conventional cellular dosimetry models often represent cells as regularly packed spheres, which may not capture realistic tumor microarchitecture. This study investigated how histopathology-informed three-dimensional (3D) tumor microarchitecture influences cellular absorbed-dose distributions, predicted radiobiological response, and treatment-related conclusions in TRT. Methods: Realistic 3D cellular tumor models were constructed from thick-section 3D cyclic immunofluorescence (3D CyCIF) imaging data. Monte Carlo radiation-transport simulations were performed for Lu-177, Pd-103, Tb-161 and Y-90, with activity localized in cancer-cell subcellular compartments and in non-cancer targets. Absorbed dose per total cluster decay was calculated individually for each cell nucleus and compared with corresponding simplified spherical tumor models. Cell survival fractions were estimated using the linear-quadratic model, and tumor control probability (TCP) was calculated from the individual cancer-cell survival probabilities. Results: Simplified model overestimated mean cancer-cell nuclear absorbed dose by 9.54% to 14.51% for nuclear localization and by 33.23% to 44.88% for cytoplasmic and membrane localization. In larger tissue models, simplified and realistic geometries produced comparable mean absorbed doses in several cases; however, the realistic models consistently generated broader cellular dose distributions, including low-dose cancer-cell subpopulations not captured by the simplified models. These dose-distribution differences propagated into wider survival-fraction distributions and altered TCP predictions. In the spatially heterogeneous tumor region, the realistic model required 1.11- to 1.33-fold higher activity to reach TCP90 for nuclear localization, and 1.49- to 5.93-fold higher activity for cytoplasmic and membrane localization. For similar tumor control, the radionuclide and source-localization combination associated with the greatest preservation of surrounding non-cancer cells differed between the simplified and realistic models. The intra-voxel analysis further showed that homogeneous voxel-scale activity assumptions can obscure biologically relevant microscopic dose heterogeneity. Conclusion: Native 3D tumor microarchitecture substantially influences cellular absorbed-dose distributions, predicted biological response, and treatment-related conclusions. Histopathology-informed 3D cellular models can be used as a complementary framework for characterizing cellular dose heterogeneity and may improve the evaluation of radionuclides and subcellular targeting strategies in heterogeneous tumor tissue.
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BibTeX
@misc{peirispulle2026impact,
title = {{Impact of Realistic 3D Tumor Microarchitecture on Cellular Dosimetry and Radiobiological Response in Targeted Radionuclide Therapy}},
author = {T. A. Peirispulle and R. Ware and S. Korevaar and P. Hetti Mudiyanselage and J. Thangarajah and R. Tennakoon},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.23.753948},
url = {https://www.biorxiv.org/content/10.64898/2026.09.23.753948v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Impact of Realistic 3D Tumor Microarchitecture on Cellular Dosimetry and Radiobiological Response in Targeted Radionuclide Therapy
AU - T. A. Peirispulle
AU - R. Ware
AU - S. Korevaar
AU - P. Hetti Mudiyanselage
AU - J. Thangarajah
AU - R. Tennakoon
PY - 2026
DA - 2026/09/23
PB - bioRxiv
DO - 10.64898/2026.09.23.753948
UR - https://www.biorxiv.org/content/10.64898/2026.09.23.753948v1
AB - Background: Patient-specific dosimetry in targeted radionuclide therapy (TRT) is increasingly supported by quantitative imaging; however, voxel-scale dose estimates cannot resolve cellular and subcellular heterogeneity present within tumor tissue. Conventional cellular dosimetry models often represent cells as regularly packed spheres, which may not capture realistic tumor microarchitecture. This study investigated how histopathology-informed three-dimensional (3D) tumor microarchitecture influences cellular absorbed-dose distributions, predicted radiobiological response, and treatment-related conclusions in TRT. Methods: Realistic 3D cellular tumor models were constructed from thick-section 3D cyclic immunofluorescence (3D CyCIF) imaging data. Monte Carlo radiation-transport simulations were performed for Lu-177, Pd-103, Tb-161 and Y-90, with activity localized in cancer-cell subcellular compartments and in non-cancer targets. Absorbed dose per total cluster decay was calculated individually for each cell nucleus and compared with corresponding simplified spherical tumor models. Cell survival fractions were estimated using the linear-quadratic model, and tumor control probability (TCP) was calculated from the individual cancer-cell survival probabilities. Results: Simplified model overestimated mean cancer-cell nuclear absorbed dose by 9.54% to 14.51% for nuclear localization and by 33.23% to 44.88% for cytoplasmic and membrane localization. In larger tissue models, simplified and realistic geometries produced comparable mean absorbed doses in several cases; however, the realistic models consistently generated broader cellular dose distributions, including low-dose cancer-cell subpopulations not captured by the simplified models. These dose-distribution differences propagated into wider survival-fraction distributions and altered TCP predictions. In the spatially heterogeneous tumor region, the realistic model required 1.11- to 1.33-fold higher activity to reach TCP90 for nuclear localization, and 1.49- to 5.93-fold higher activity for cytoplasmic and membrane localization. For similar tumor control, the radionuclide and source-localization combination associated with the greatest preservation of surrounding non-cancer cells differed between the simplified and realistic models. The intra-voxel analysis further showed that homogeneous voxel-scale activity assumptions can obscure biologically relevant microscopic dose heterogeneity. Conclusion: Native 3D tumor microarchitecture substantially influences cellular absorbed-dose distributions, predicted biological response, and treatment-related conclusions. Histopathology-informed 3D cellular models can be used as a complementary framework for characterizing cellular dose heterogeneity and may improve the evaluation of radionuclides and subcellular targeting strategies in heterogeneous tumor tissue.
ER -