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Focus: Research news

NIR diagnostic device wins at Photonics Europe


n EU-funded project developing an infrared system to diagnose

disease has won an innovation award at SPIE Photonics Europe conference, which took place in Brussels in April. The Photonics Innovation Village award for best innovation by a multilateral project, organisation or company was granted to Gooch and Housego and collaborators, including scientists from the University of Exeter in the UK, for the MINERVA (mid- to near-infrared spectroscopy for improved medical diagnostics) project. MINERVA is

made by analysing the entire biomolecular mid-IR spectral signature using automated algorithms. However, the lack of suitable sources, detectors and components has restricted the technology to one of academic interest, based on weak thermal sources, low power lasers or synchrotron research tools. The MINERVA platform aims to address this.

funded with €7.3 million under the European Commission’s Seventh Framework programme, and runs from November 2012 until October 2016. The project is developing a new mid-IR technology platform based on supercontinuum sources covering the wavelength range from 1.5 to 12μm. In recent years it has been demonstrated that mid-IR imaging spectroscopy offers an effective tool for early cancer diagnosis and improved survival rates. Rather than a search for cancer marker absorption peaks, great progress has been |

‘ Clinical trials of a MINERVA- based system will start within the next few months’

Clinical trials of a MINERVA- based system will start within the next few months although the goal of developing an in vivo scanning system to probe patients is still some way off. According to

Professor Nicholas

Stone, professor of biomedical imaging and biosensing at the University of Exeter’s School of Physics: ‘By developing bright IR sources and sensitive detector arrays we expect to be able to capture diagnostic images of unstained tissues and cells in a matter of seconds. In addition clever data analysis methods will allow the image to be superimposed on each other and standard histopathology images of the same sample. The potential for revolutionising the current methods of clinical diagnosis are huge.’


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