Kinetic Modeling and Radiomics Analysis of the Heterogeneity of Tumor-Associated Macrophages and Metabolism in Head and Neck Cancer.
- 1Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri 63110, United States.
Abstract
Purpose: Tumor-associated macrophages (TAMs) play an important role in the initiation and progression of head and neck squamous cell carcinoma (HNSCC). Herein, we evaluated the tumor tissue heterogeneity uptake of a CD163+ PET tracer, [64Cu]-ICT-01, and compared it with [18F]-FDG using kinetic modeling and radiomics analysis in a mouse oral carcinoma 1 (MOC1) HNSCC mouse model. Methods: MOC1 cells were implanted on the flanks of four C57BL/6 mice. At 3 weeks post tumor implantation, these mice underwent a 60 min dynamic scan post-injection of [18F]-FDG and then another 60 min dynamic scan the next day post-injection of [64Cu]-ICT-01. Nine tumor volumes were delineated using a region-growing algorithm, which were further divided into tissue volumes based on tracer uptake using k-means clustering. Kinetic modeling was performed using compartmental models and graphical Logan/Patlak. Standardized uptake value (SUV) PET images were generated using time windows of 1-10 min and 45- 60 min. A total of 91 textural radiomic features were obtained using Pyradiomics, and key features were selected using the coefficient of variance (CV). Results:k-means clustering identified three distinct tissue uptakes for [64Cu]-ICT-01, and only two tissues with high and low uptakes for [18F]-FDG. The 2TC4K and Logan models were found to be suitable models for modeling the kinetics of [64Cu]-ICT-01. [18F]-FDG generally yielded greater variances in quantitative parameters across tissues within the tumors than those of [64Cu]-ICT-01, except for K1. However, greater variances in radiomic features were obtained for [64Cu]-ICT-01 than for [18F]-FDG. [64Cu]-ICT-01 also yielded six more features with CV > 0.7 compared to [18F]-FDG. Conclusion: [64Cu]-ICT-01 showed greater differences in uptake kinetics and textural information, while [18F]-FDG provided greater differences in quantitative values across the tissues within the tumor. [64Cu]-ICT-01 and [18F]-FDG showed the heterogeneous nature of the tumor microenvironment, and their combination would enable us to understand the tumor biology and hence improve tumor diagnosis.
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BibTeX
@article{nai2026kinetic,
title = {{Kinetic Modeling and Radiomics Analysis of the Heterogeneity of Tumor-Associated Macrophages and Metabolism in Head and Neck Cancer.}},
author = {Ying-Hwey Nai and Gyu Seong Heo and Priscella Madrid and Deborah Sultan and Richard Laforest and Robert Gropler and Yongjian Liu},
journal = {Chemical \& biomedical imaging},
year = {2026},
month = may,
doi = {10.1021/cbmi.6c00065},
url = {https://europepmc.org/article/MED/42953257},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Kinetic Modeling and Radiomics Analysis of the Heterogeneity of Tumor-Associated Macrophages and Metabolism in Head and Neck Cancer.
AU - Ying-Hwey Nai
AU - Gyu Seong Heo
AU - Priscella Madrid
AU - Deborah Sultan
AU - Richard Laforest
AU - Robert Gropler
AU - Yongjian Liu
PY - 2026
DA - 2026/05/30
JO - Chemical & biomedical imaging
DO - 10.1021/cbmi.6c00065
UR - https://europepmc.org/article/MED/42953257
AB - Purpose: Tumor-associated macrophages (TAMs) play an important role in the initiation and progression of head and neck squamous cell carcinoma (HNSCC). Herein, we evaluated the tumor tissue heterogeneity uptake of a CD163+ PET tracer, [64Cu]-ICT-01, and compared it with [18F]-FDG using kinetic modeling and radiomics analysis in a mouse oral carcinoma 1 (MOC1) HNSCC mouse model. Methods: MOC1 cells were implanted on the flanks of four C57BL/6 mice. At 3 weeks post tumor implantation, these mice underwent a 60 min dynamic scan post-injection of [18F]-FDG and then another 60 min dynamic scan the next day post-injection of [64Cu]-ICT-01. Nine tumor volumes were delineated using a region-growing algorithm, which were further divided into tissue volumes based on tracer uptake using k-means clustering. Kinetic modeling was performed using compartmental models and graphical Logan/Patlak. Standardized uptake value (SUV) PET images were generated using time windows of 1-10 min and 45- 60 min. A total of 91 textural radiomic features were obtained using Pyradiomics, and key features were selected using the coefficient of variance (CV). Results:k-means clustering identified three distinct tissue uptakes for [64Cu]-ICT-01, and only two tissues with high and low uptakes for [18F]-FDG. The 2TC4K and Logan models were found to be suitable models for modeling the kinetics of [64Cu]-ICT-01. [18F]-FDG generally yielded greater variances in quantitative parameters across tissues within the tumors than those of [64Cu]-ICT-01, except for K1. However, greater variances in radiomic features were obtained for [64Cu]-ICT-01 than for [18F]-FDG. [64Cu]-ICT-01 also yielded six more features with CV > 0.7 compared to [18F]-FDG. Conclusion: [64Cu]-ICT-01 showed greater differences in uptake kinetics and textural information, while [18F]-FDG provided greater differences in quantitative values across the tissues within the tumor. [64Cu]-ICT-01 and [18F]-FDG showed the heterogeneous nature of the tumor microenvironment, and their combination would enable us to understand the tumor biology and hence improve tumor diagnosis.
SN - 2832-3637
ER -