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Bacteria-Specific PET Scan Detects Lung Infections With Precision

Researchers have developed a bacteria-targeted PET tracer that lights up lung infections in real time, distinguishing pathogens from inflammation. This technology promises earlier, more accurate diagnoses for patients with hard-to-detect respiratory disease.

PET scan of human body.

Image Credit: springsky/Shutterstock.com

The bacteria-specific positron emission tomography (PET) imaging agent directly identifies and localizes pathogenic bacteria within lung tissue, rather than just imaging inflammatory changes.

The technology, described by the Society of Nuclear Medicine and Molecular Imaging, could improve diagnostic accuracy in conditions like cystic fibrosis and chronic obstructive pulmonary disease (COPD), where lung infections are common but difficult to pinpoint with existing imaging techniques.

Imaging Infection, Not Just Inflammation

Current imaging methods primarily detect tissue damage or inflammation caused by infection, which often leads to ambiguity in results. To solve this, the team designed a radiolabeled biosensor that recognizes metabolic activity unique to bacteria.

The tracer combines a bacterial enzyme substrate with fluorine-18, a positron-emitting isotope used in PET, and β-lactamase enzymes, widely expressed by pathogenic bacteria and absent in human cells, to generate a signal.

When the PET tracer encounters β-lactamase-expressing bacteria, the enzyme cleaves the molecule and tags the bacterial cells with radioactive 18F. This enables highly specific imaging of infectious foci while avoiding uninfected or inflamed tissue uptake.

Validated In Bacteria And Animals

The team validated the biosensor in vitro using cultures of Mycobacterium abscessus alongside mammalian cells. The uptake and retention of the radiotracer occurred exclusively in bacterial cultures, with negligible uptake in human cells. Control experiments using β-lactamase inhibitors confirmed the enzyme-dependent mechanism.

The tracer was administered in animal models with induced lung infections, and subsequent PET scans revealed distinct areas of radiotracer accumulation matching microbiologically confirmed bacterial sites. PET signals in infectious regions caused by bacteria without β-lactamase activity were absent or significantly reduced, as were those in non-infected lung regions, highlighting the tracer’s specificity.

Notably, the biosensor distinguished bacterial infection from non-specific inflammation, a longstanding limitation of conventional PET imaging.

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High Sensitivity And Rapid Results

Quantitative analysis showed the sensor could detect bacterial loads as low as 104 colony-forming units (CFUs), which is highly relevant in clinical applications. Imaging with this tracer was highly efficient, and the high-contrast imaging retrieved from the PET scans suggests the tracer's potential for clinical translation.

The tracer also showed favorable pharmacokinetics: it penetrated lung tissue effectively, cleared quickly from non-target tissues, and produced high-contrast images within an hour.

What’s Next?

Further optimization and human clinical trials will be needed before the technique can be adopted in practice. However, the findings illustrate the high specificity of this tracer and its molecular recognition and signal transduction capabilities. This diagnostic tool can produce real-time results and will be important in next-generation advanced imaging. 

Reference

Press Release. Society of Nuclear Medicine and Molecular Imaging. Novel Bacteria-Specific PET Imaging Approach Detects Hard-to-Diagnose Lung Infections. Accessed on 24th June 2025.

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    

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