Researchers in the states may have found a way to detect potential prostate tumours using Magnetic resonance spectroscopy, and this should lead to fewer false negatives, better precision when locating tumours and a better idea of how aggressive they are.
Magnetic resonance spectroscopy analyses the biochemistry, unlike things like MRI, which look at the structure of tissues. This means it can be used to look for the distinct chemical, rather than structural, signatures of a tumour.
Leo Cheng and colleagues at Massachusetts General Hospital published a study in the journal Science Translational Medicine that builds on some earlier work published in 2005. This earlier work looked at the biochemistry of a tumour and identified a metabolic spectrum for prostate cancers - a series of chemicals produced by the tissue that identifies it as a tumour. Studying the entire suite of metabolites left behind by a cell is known as metabolomics.
With this ensemble of metabolites in mind, they set about scanning 5 cancerous prostate glands that had been removed from patients. Their scans measured the proportion of these signature metabolites to give an indication of whereabouts in the prostate had a higher ‘Malignancy index’ – i.e. a higher likelihood of being cancerous tissue.
When the results were compared, 5 out of seven tumours coincided with areas of high malignancy index – the remaining two it is thought were compromised by being close to the edge of the prostate, where interactions with air could have altered the metabolomic profile. Overall, its accuracy was over 90%.
Interestingly, there was also a correlation between the size of the tumour and the magnitude of the malignancy index – suggesting that this technique could not only identify malignant tissue, but also give you an indication of how aggressive it is.
As they say in the discussion of the paper: “Metabolomic imaging has the potential to detect lesions, guide biopsy, and eventually identify other conditions of malignancy, such as tumour aggressiveness”. They also add that it could be adapted to identify other types of cancer.