The current standard for definitive diagnosis of COVID-19 is the real-time reverse transcriptase-polymerase chain reaction (RT-PCR).

Background

The current standard for definitive diagnosis of COVID-19 is the real-time reverse transcriptase-polymerase chain reaction (RT-PCR). While this is a highly sensitive and specific test for COVID-19, it does not measure the severity nor progress of the associated lung disease.

Significance of CERN Technology/MARS imaging could help COVID-19 treatment monitoring and drug development

Mars technology utilises the varying absorption of X-rays across the diagnostic energy range. This enables MARS to generate functional imaging by simultaneously identifying and quantifying various components of tissues as well as exogenously administered pharmaceutical agents such as nanoparticles. Hence there is the possibility of having a tagging agent for lung injury and fibrosis that can be visualised. This would enable both highly specific and quantitative imaging for either Covid-19 or the lungs response to the virus. Developing a technique would enable better diagnosis, drug development, and monitoring of therapy. This applies to both animal trials for drug research and human clinical trials.

Proposal

The MARS team in collaboration with its various partners have demonstrated that spectral photon-counting for molecular imaging is useful for detecting lung TB using iodine and silver contrast agents, bone micro-fractures using hafnium particles, and HER-2 positive cell lines using gold nanoparticles in breast cancer research^{1, 2, 3}. It is hoped that a similar quantitative marker can be found for assessing Covid-19 lung damage. They are seeking potential partners who have access to, or capable of, developing disease models like and/or Covid. Interested parties may contact Professor Anthony Butler at anthony.butler@marsbioimaging.com or www.marsbioimaging.com for further information.

Publications:

1. https://doi.org/10.1002/adfm.201904936

2. https://doi.org/10.1007/978-981-32-9816-3_17

3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4958312/

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