Understanding and Fighting Cancer: Phospholipid imaging to prevent ineffective chemotherapy


Published September 21, 2021
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Scientific application
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Euro-BioImaging is organizing an online User Forum on October 14, 2021 from 14:00-17:00 CEST. This event will highlight the importance of cutting-edge imaging technologies in support of cancer research and showcase the specific expertise available at our Nodes across Europe through case studies presented in tandem with the research community.

In this brief abstract, learn how the Dutch High Field Imaging Node uses non-invasive imaging (metabolic MRI) to detect phospholipidic markers to predict cancer treatment outcome. Hear this talk and others like it on October 14 at the Euro-BioImaging User Forum.

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Phospholipid imaging to prevent ineffective chemotherapy

Dennis Klomp
University Medical Center Utrecht
Dutch High Field Imaging Node

Leonard Seelen
University Medical Center, Utrecht

As a new EuroBioImaging Node, we are pleased to present a study where highfield MRI is used to detect phospholipid metabolites in patients treated for cancer. We have used 31P MRSI as a metabolic imaging tool to investigate its feasibility in detecting phospholipids and to explore effect sizes of this biomarker in relation to response to treatments

Methods: 50 patients with breast cancer were enrolled prior to obtaining treatment. A 31P breast setup was used on a 7T MRI system (Philips) to assess PME/PDE ratio of the primary tumor and verified to biopsy and histology of excised specimen after surgery to assess its predictive value in advising against chemotherapy. Next, the technology was ported to a body setup including integrated body coil, local receiver arrays and high-power amplifiers to explore detection of PME/PDE in lung, pancreas and liver cancer; for each site a single patient was enrolled.

Results: In breast cancer we have shown that sensitivity is sufficient to provide a 96% accuracy in predicting chemotherapy inefficacy. Next, after MDR processes, we managed to port the technology to the entire body and could indeed perform the metabolic imaging scan in pancreas, liver and lung cancer. Despite motion and field non-uniformities, we are able to detect the PME and PDE metabolites throughout the human body non-invasively. Moreover, we could detect energy metabolites like ATP, Phosphocreatine and inorganic phosphate as well as the acidity of the tissue with this technique.

Conclusion: metabolic MRI can be a tool to study cell proliferation throughout the body non-invasively, which may be a marker to predict treatment outcome.


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