Speaker
Description
Human cancers are biologically and morphologically heterogeneous, exhibiting complex spatiotemporal dynamics during tumor growth. Imaging with positron emission tomography (PET) enables visualization of metabolic activity and its intratumor heterogeneity.
Using continuous and discrete mathematical models of tumor growth, we showed that the location of the metabolic activity hotspot drifts from the tumor center toward the periphery. This observation led to the definition of NHOC, the normalized distance from the PET hotspot to the tumor centroid.
We applied this metric to cohorts of patients with breast cancer and non–small-cell lung cancer (NSCLC). In these datasets NHOC was shown to be a strong predictor of survival \cite{jim21}.
NHOC is therefore a biomarker inspired by mechanistic modeling that enables personalized forecasting in patients.
Since the publication of the original study, this concept has gained significant traction in the medical community. NHOC has been applied and extended by nuclear medicine groups and validated in independent cohorts \cite{hov24,chen25}.
Moreover, we have recently extended its application to a cohort of high-grade gliomas, where it continues to demonstrate prognostic value \cite{bos26}. These results highlight the generalizability of the biomarker across tumor types.
In this talk, I will review the mathematical foundations of this metric, its application as an imaging biomarker, and its impact on enabling personalized forecasting.
Bibliography
@article{jim21,
title={Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers},
author={Jim{\'e}nez-S{\'a}nchez, Juan and Bosque, Jes{\'u}s J and Jim{\'e}nez Londo{\~n}o, Germ{\'a}n A and Molina-Garc{\'\i}a, David and Mart{\'\i}nez, {\'A}lvaro and P{\'e}rez-Beteta, Juli{\'a}n and Ortega-Sabater, Carmen and Honguero Mart{\'\i}nez, Antonio F and Garc{\'\i}a Vicente, Ana M and Calvo, Gabriel F and others},
journal={Proceedings of the National Academy of Sciences},
volume={118},
number={6},
pages={e2018110118},
year={2021},
publisher={National Academy of Sciences}}
@article{hov24,
title={Promising Candidate Prognostic Biomarkers in [18F] FDG PET Images: Evaluation in Independent Cohorts of Non--Small Cell Lung Cancer Patients},
author={Hovhannisyan-Baghdasarian, Narin{\'e}e and Luporsi, Marie and Captier, Nicolas and Nioche, Christophe and Cuplov, Vesna and Woff, Erwin and Hegarat, Nadia and Livartowski, Alain and Girard, Nicolas and Buvat, Ir{`e}ne and others},
journal={Journal of Nuclear Medicine},
volume={65},
number={4},
pages={635--642},
year={2024},
publisher={Society of Nuclear Medicine}}
@article{chen25,
title={An explainable imaging-clinical biomarker for non-small cell lung cancer prognostication based on normalised hotspot to centroid distance and [18F] FDG PET/CT radiomics},
author={Chen, Mitchell and Copley, Susan J and Han, Yidong and Arshad, Mubarik A and Viola, Patrizia and Linton-Reid, Kristofer and Stoycheva, Tina and Cook, Gary JR and Landau, David and Chua, Sue and others},
journal={European Journal of Nuclear Medicine and Molecular Imaging},
pages={1--18},
year={2025},
publisher={Springer}}
@article{bos26,
title={Complementary prognostic value of hotspot-to-centroid distance (NHOCpeak) to SUVpeak in high-grade glioma},
author={Bosque, Jes{\'u}s J and Molina-Garc{\'\i}a, David and P{\'e}rez-Beteta, Juli{\'a}n and Vicente, Ana M Garc{\'\i}a and P{\'e}rez-Garc{\'\i}a, V{\'\i}ctor M},
journal={Annals of Nuclear Medicine},
pages={1--11},
year={2026},
publisher={Springer}}
