Non-invasive imaging of deep tissue

Tufts biomedical and electrical engineers receive funding from the National Institutes of Health to develop a novel technique for frequency-domain near-infrared spectroscopy.
Sergio Fantini, Valencia Koomson, Angelo Sassaroli headshots
Tufts engineering faculty Sergio Fantini, Valencia Koomson, and Angelo Sassaroli

In the Diffuse Optical Imaging of Tissue (DOIT) Lab, Professor Sergio Fantini, Research Assistant Professor Angelo Sassaroli, and other collaborators from the Department of Biomedical Engineering study biological tissue at a macroscopic scale. Over the last several years, the lab has been pursuing a new approach to frequency-domain near-infrared spectroscopy (FD-NIRS) that could allow more targeted study of deeper biological tissue with improved sensitivity.

In the Department of Electrical and Computer Engineering, Associate Professor Valencia Koomson and researchers in the Advanced Integrated Circuits and Systems Laboratory design and implement innovative high-performance, low-power microsystems, like a wearable FD-NIRS device that could measure cerebral and tissue oxygenation.

The two groups are now bringing together their expertise with a grant from the National Institutes of Health (NIH) to enhance the reliability and quality of FD-NIRS in both clinical and research applications. Their proposed technique builds on the concept of phase dual slopes, which are beneficial because they are less sensitive to confounding contributions and also allow researchers or clinicians to more tightly target a given area deeper in tissue.

With NIH funding, the Tufts team will continue to develop the dual slope FD-NIRS technique, with further innovations to come including the design of a cost-effective, wearable, compact FD-NIRS device that could be used for freely-moving subjects. The researchers seek to advance diffuse optical measurements of biological issue, and to ultimately achieve a stronger sensitivity to deeper tissue in non-invasive diffuse optical spectroscopy and imaging.

Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Number R01EB029414. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.