Cell phone technology set to deliver diagnostic imaging

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A multinational team of researchers has delivered proof-of-concept data demonstrating the potential for cellular phone technology to deliver diagnostic imaging data from remote locations. A data acquisition device at a remote site could be connected via a cell phone with image reconstruction software and hardware at a central site, according to the study published online April 30 in Public Library of Science ONE (PLoS ONE).

Researchers from Jerusalem’s Hebrew University Research Center in bioengineering at the Benin School of Computer Science and Engineering and the biophysics graduate group at the University of California, Berkeley, reported that their methodology allows for the transfer of raw data from the patient site to a central facility that has the software and hardware required for image reconstruction. The processed data is then returned from the central facility to the cellular phone as an image.

The team chose electrical impedance tomography (EIT) as a method to demonstrate cell phone feasibility in medical imaging.

EIT uses low-frequency electrical current to probe a body; the method is sensitive to changes in electrical conductivity. By injecting known amounts of current and measuring the resulting electrical potential field at points on the boundary of the body, it is possible to invert the data to determine the conductivity or resistivity of the region of the body.

Using their technology, the researchers were able to successfully acquire, transmit, process and return to the cell phone image data from a gel-filled phantom model that simulated breast tissue with a tumor.

The scientists are seeking to expand the technology to work with other imaging modalities such as x-ray and ultrasound. Their hope is that it could be deployed to the 75 percent of the world’s population that does not yet have access to medical imaging.

“The concept could be developed with various medical imaging modalities, such as ultrasound or even x-ray,” the authors wrote. “It would be most economical with medical imaging systems in which the data acquisition hardware is relatively inexpensive and which requires substantial computation for image reconstruction.”