Fungal PET Radiotracers: Infection vs. Inflammation Imaging?

This proposal introduces a transformative, real-time, image-based, noninvasive diagnostic technology to address the unmet need for early detection and localisation of invasive fungal infections (IFIs). IFIs are a growing and serious global health concern, particularly for patients in intensive care or with weakened immune systems. These infections are often difficult to diagnose early, leading to delayed treatment, increased mortality, and the overuse of broad-spectrum antifungal drugs, which in turn contributes to antifungal resistance (AFR). Current image-based diagnostic approaches, including Computed Tomography (CT) and Positron Emission Tomography (PET) scans, can show areas of infection but cannot reliably distinguish between infection, inflammation, or cancer. There is a pressing clinical need for noninvasive, sensitive, and specific tools that can detect fungal infections early, pinpoint their location, and monitor treatment responses — all in real-time. At King’s College London (KCL), in collaboration with King’s Health Partners (KHP) and the UK Health Security Agency (UKHSA), we are developing a PET imaging radiotracer to address this unmet need. Our technology enables the visualisation of fungal pathogens inside the body, potentially allowing clinicians to distinguish true infection from inflammation and better guide antifungal treatment decisions. We have developed a gallium-68-labelled small molecule and confirmed its uptake by major fungal pathogens, including Aspergillus fumigatus, Candida albicans, and Candida auris — a novel result for Candida species, for which no similar radiotracers currently exist. This proposal aims to take the next critical step by evaluating our candidate tracer in small animal models of fungal infection and comparing its behaviour in infected vs. inflamed tissue. Our objectives are: (1) to assess the radiotracer’s pharmacokinetics (PK) in healthy animals, and (2) to evaluate its ability to detect fungal infection and differentiate it from inflammation in small animal models infected with key fungal species. This work will generate essential data to support further development under UKRI’s Developmental Pathway Funding Scheme. If successful, this tracer could transform how fungal infections are diagnosed and monitored, reduce unnecessary antifungal use, and improve outcomes for some of the most vulnerable patients. The long-term impact of this project lies in its potential to support faster diagnosis, better targeted treatment, reduced AFR, and improved survival for patients facing life-threatening fungal infections.