Improving Diagnostic Imaging
If you’ve ever tried to take a picture of a squirming baby, you know how tough it can be to get a quality image of something that’s always on the move.
A similar challenge can be found in the more advanced imaging tools used in healthcare diagnostics. To capture high-quality images using MRI or PET scanners, the machines must find ways to compensate for the motion that accompanies a patient’s beating heart or their patterns of breathing in and out.
Bruno Madore, PhD, Director of the BWH Advanced Lab for MRI and Acoustics and Associate Professor of Radiology at Harvard Medical School, received a Partners Innovation Discovery Grant (IDG) in 2018 to support the development of an organ configuration motion sensor (OCM) designed to improve the quality of diagnostic images by accounting for these movements in patients.
OCM sensors are small, 3D- printed devices equipped with ultrasound transducers. The sensors can be placed on the abdomen, chest or over the heart and are very sensitive to internal motion.
While the signal on its own is unfocused, the picture becomes a lot clearer when the information it provides is integrated with other imaging tools. “If you just got that signal, it would be hard to interpret, but we always get it at the same time as something else,” explains Madore.
“For example, we can put them on someone going into an MR scanner and collect those signals at the same time as MR images, then we have machine-learning algorithms that learn what the MR images look like when the OCM signals look a certain way.
“Once that is learned, even if we take a person out of the scanner, we can still generate images because we still have the sensors sending out the signals, and we have learned what the MR images look like when those signals look a certain way.”
Madore and colleagues have already demonstrated that the sensors can fill a critical gap in high-resolution MRI scans for cardiac patients. Electrocardiograms (ECGs) are typically used to monitor heart activity during low-field MRI scans, but they get swamped in high-field MRI machines. OCM sensors can act as a surrogate to ECG in high-field MRI scanners, enabling the capture of higher-quality images.
Shifting from diagnostics to treatment, the sensors could be placed on patients who are undergoing radiation therapy to provide real-time information about their breathing patterns that can be used to improve the targeting of the treatment.
Some high-end hospitals have optical sensors that measure a patient’s breathing during treatments, but they can be expensive to install and require a clear line of sight, Madore says. A similar approach could improve the precision of biopsies or ablation treatments for cancer.
The information provided by these sensors could also serve as a thread that ties together the results of different tests taken at different times by different machines. “More generally, there are all sorts of good things that might happen if you can link those different experiences that patients have on different days in different places.”
How the Innovation Discovery Grant Made a Difference
Madore says the grant he received in 2018 helped in fine-tuning the design and confirming the accuracy of the data collected.
“At first, we had a much lower hit-and-miss success ratio, so now in terms of reliability we are getting good signals. We also did more systemic validation of the signals we get to show that we’re able to replicate other existing ways of following the breathing motion.”
While the funding was helpful, what made the award special was the visibility it provided for his work, especially through the World Medical Innovation Forum, where he gave a presentation on the commercial potential of the technology.
He also appreciated the business-focused aspect of the process, from the application for the grant itself to the coaching he received for his presentation at the Forum. It was a different process than what he usually goes through in seeking grant funding from the NIH.
“It was a different flavor which was very educational, very useful. An important perspective that had not been present otherwise.”
2020 IDG Applications Now Open
In 2020, the IDG program is open to all areas of clinical expertise and technology types. Projects may request up to $100,000 total cost (inclusive of 15% indirect costs).
Project plans must demonstrate tangible outcomes toward commercialization opportunities that improve patient health or healthcare delivery. Pre-proposals are due no later than Sept. 25, 2019, and full proposals will be invited by Nov. 18, 2019. The awards will be announced at the World Medical Innovation Forum in May 2020. Visit the IDG webpage for complete details.
Printed from https://innovationblog.partners.org/improving-diagnostic-imaging · Published 11 Dec 2019
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