Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function

Unveiling the biological side of PET-derived biomarkers: a simulation-based approach applied to PDAC assessment

PURPOSE

Radiomics has revolutionized clinical research by enabling objective measurements of imaging-derived biomarkers. However, the true potential of radiomics necessitates a comprehensive understanding of the biological basis of extracted features to serve as a clinical decision support. In this work, we propose an end-to-end framework for the in silico simulation of [18F]FLT PET imaging process in Pancreatic Ductal Adenocarcinoma, accounting for the biological characterization of tissues (including perfusion and fibrosis) on tracer delivery. We thus establish a direct association between radiomics features and the underlying biological properties of tissues.

METHODS

We considered 4 immunohistochemically stained Whole Slide Images of pancreatic tissue of one healthy control and three patients with PDAC and/or precursor lesions. From marker-specific images, tissue-depending diffusivity properties were estimated and computational domains were built to simulate the [18F]FLT spatial-temporal uptake exploiting Partial Differential Equations and Finite Elements Method. Consequently, we simulated the imaging process obtaining surrogated PET images for the considered patients, and we performed image-derived features extraction from PET images to be mapped with biological properties via correlation estimation.

RESULTS

The framework captured the phenotypic differences and generated Time Activity Curves reflecting the underlying tissue composition. Image-derived biomarkers were ranked in view of their association with biological characteristics of the tissue, unveiling their molecular correlative. Moreover, we showed that the proposed pipeline could serve as a digital phantom to optimize the image acquisition for lesion detection.

CONCLUSIONS

This innovative framework holds the potential to enhance interpretability and reliability of radiomics, fostering the adoption in personalized nuclear medicine and patient care.

Mathematical modeling of18F-Fluoromisonidazole (18F-FMISO) radiopharmaceutical transport in vascularized solid tumors

18F-Fluoromisonidazole (18F-FMISO) is a highly promising positron emission tomography radiopharmaceutical for identifying hypoxic regions in solid tumors. This research employs spatiotemporal multi-scale mathematical modeling to explore how different levels of angiogenesis influence the transport of radiopharmaceuticals within tumors. In this study, two tumor geometries with heterogeneous and uniform distributions of capillary networks were employed to incorporate varying degrees of microvascular density. The synthetic image of the heterogeneous and vascularized tumor was generated by simulating the angiogenesis process. The proposed multi-scale spatiotemporal model accounts for intricate physiological and biochemical factors within the tumor microenvironment, such as the transvascular transport of the radiopharmaceutical agent, its movement into the interstitial space by diffusion and convection mechanisms, and ultimately its uptake by tumor cells. Results showed that both quantitative and semi-quantitative metrics of18F-FMISO uptake differ spatially and temporally at different stages during tumor growth. The presence of a high microvascular density in uniformly vascularized tumor increases cellular uptake, as it allows for more efficient release and rapid distribution of radiopharmaceutical molecules. This results in enhanced uptake compared to the heterogeneous vascularized tumor. In both heterogeneous and uniform distribution of microvessels in tumors, the diffusion transport mechanism has a more pronounced than convection. The findings of this study shed light on the transport phenomena behind18F-FMISO radiopharmaceutical distribution and its delivery in the tumor microenvironment, aiding oncologists in their routine decision-making processes.

Hypoxia boosts aerobic glycolysis of carcinoma：a complex process for tumor development

Hypoxia, a common feature in malignant tumors, is mainly caused by insufficient oxygen supply. Hypoxia is closely related to cancer development, affecting cancer invasion and metastasis, energy metabolism and other pathological processes, and is not conducive to cancer treatment and prognosis. Tumor cells exacerbate metabolic abnormalities to adapt to the hypoxic microenvironment, especially to enhance aerobic glycolysis. Glycolysis leads to an acidic microenvironment in cancer tissues, enhancing cancer metastasis, deterioration and drug resistance. Therefore, hypoxia is a therapeutic target that cannot be ignored in cancer treatment. The adaptation of tumor cells to hypoxia is mainly regulated by hypoxia inducible factors (HIFs), and the stability of HIFs is improved under hypoxic conditions. HIFs can promote the glycolysis of tumors by regulating glycolytic enzymes, transporters, and participates in regulating the TCA (tricarboxylic acid) cycle. In addition, HIFs indirectly affect glycolysis through its interaction with non-coding RNAs. Therefore, targeting hypoxia and HIFs are important tumor therapies.