We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Near Infrared-2 Imaging Technology Developed for Visualizing Blood Flow

By MedImaging International staff writers
Posted on 26 Dec 2012
Print article
Image: These images of a mouse's blood vessels show the difference in resolution between traditional near-infrared fluorescence imaging (top) and Stanford's new NIR-2 technique (bottom) (Photo courtesy of Stanford University).
Image: These images of a mouse's blood vessels show the difference in resolution between traditional near-infrared fluorescence imaging (top) and Stanford's new NIR-2 technique (bottom) (Photo courtesy of Stanford University).
Investigators have developed a fluorescence imaging technique that provides a view of the pulsing blood vessels of living animals with never-before-seen clarity. Compared with traditional imaging technologies, the sharpness enhancement is similar to cleaning fog off eyeglasses.

The technique, called near infrared-2 imaging (NIR-2), involves first injecting water-soluble carbon nanotubes into the live subject’s bloodstream. The researchers then shine a laser (its light is in the near-infrared range, a wavelength of about 0.8 micrometers) over the subject—in this instance, a mouse. The light causes the specially engineered nanotubes to fluoresce at a longer wavelength of 1-1.4 micrometers, which is then detected to determine the blood vessels’ structure.

That the nanotubes fluoresce at considerably longer wavelengths than conventional imaging techniques is vital in achieving the amazingly sharp images of the tiny blood vessels: longer wavelength light scatters less, and thereby generates clearer images of the vessels. Another advantage of detecting such long wavelength light is that the detector registers less background noise since the body does not produce autofluorescence in this wavelength range.

In addition to providing fine details, the technique, developed by Stanford University (Stanford, CA, USA) scientists Hongjie Dai, PhD, professor of chemistry; John Cooke, MD, PhD, professor of cardiovascular medicine; and Ngan Huang, PhD, acting assistant professor of cardiothoracic surgery—has a fast image acquisition rate, allowing researchers to measure blood flow in near real time.

The research was published online November 18, 2012, in the journal Nature Medicine. The ability to obtain both blood flow data and blood vessel clarity was not earlier possible, and will be especially useful in studying animal models of arterial disease, such as how blood flow is affected by the arterial blockages and constrictions that cause, among other things, heart attacks and stroke. “For medical research, it’s a very nice tool for looking at features in small animals,” Prof. Dai said. “It will help us better understand some vasculature diseases and how they respond to therapy, and how we might devise better treatments.”

Because NIR-2 can only penetrate 1 cm, at most, into the body, it will not replace other imaging techniques for humans, but it will be a powerful method for studying animal models by replacing or complementing computed tomography (CT), X-ray, magnetic resonance imaging (MRI), and laser Doppler techniques.

The next phase of the research, and one that will make the technology more easily accepted for use in humans, is to study alternative fluorescent molecules, according to Prof. Dai. “We’d like to find something smaller than the carbon nanotubes but that emit light at the same long wavelength, so that they can be easily excreted from the body and we can eliminate any toxicity concerns.”

Related Links:

Stanford University


Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Remote Controlled Digital Radiography and Fluoroscopy System
Eco Track-DRF - MARS 50/MARS50+/MARS 65/MARS 80
New
X-Ray QA Meter
Piranha CT
Ultrasound System
Acclarix AX9

Print article

Channels

Ultrasound

view channel
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)

Largest Model Trained On Echocardiography Images Assesses Heart Structure and Function

Foundation models represent an exciting frontier in generative artificial intelligence (AI), yet many lack the specialized medical data needed to make them applicable in healthcare settings.... Read more

Nuclear Medicine

view channel
Image: The multi-spectral optoacoustic tomography (MSOT) machine generates images of biological tissues (Photo courtesy of University of Missouri)

New Imaging Technique Monitors Inflammation Disorders without Radiation Exposure

Imaging inflammation using traditional radiological techniques presents significant challenges, including radiation exposure, poor image quality, high costs, and invasive procedures. Now, new contrast... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.