The Science Behind Technicolor Imaging: The Role of Advanced imaging in managing Degenerative joint Disease

As a Penn State team leads the way by bringing traditional black and white diagnostic images of X-rays and traditional CT scans into technicolor, medical imaging no longer resides in Kansas, Toto.

Using advanced imaging called ‘K-edge’ or photon-counting Computed Tomography (CT), the researchers can mark the proteins with newly designed metal nanoprobes that contain contrast agents and track separate biological processes in colour, which, when combined, reveal more about the disease’s progression than a traditional scan.

Its findings were published in Advanced Science. The work, done in rats but having implications for humans, enables researchers and clinicians to see previously invisible processes in colour and see evidence of the disease well before clinical symptoms develop.

First author Nivetha Gunaseelan, doctoral student in biomedical engineering at Penn State, said, “If we develop a metal nanoprobe as a contrast agent tailored to identify and quantify target particles, very few things we cannot see with the photon counting CT scanner.”

With osteoarthritis, for instance, that visualization is critical, because these diseases can progress without any symptoms until they present clinically, which is often at a late, usually irreversible stage.

If we can diagnose early and have tools for longitudinal disease tracking, that early intervention could reduce symptoms and improve lifestyle.” Imaging techniques can be boosted to detect early cartilage change at the molecular level and this could aid in diagnosis and monitoring.”

The work relies on a relatively new technique, the photon-counting computed tomography (CT) scanner, which is able to see the same bone, muscle and fat in the exact same form conventional CT scanners can view, but with orders of magnitude broader ability to distinguish between components and reveal them in designated colours at a higher resolution.

“By using this high resolution, K-edge based imaging approach, we could potentially image multiple biological targets, allowing disease progression tracking over time by measuring the ratio of protein expression,” said corresponding author Dipanjan Pan, Dorothy Foehr Huck and J. Lloyd Huck Chair Professor of Nanomedicine, materials science and engineering and nuclear engineering, Penn State.

And since the rate of cartilage degradation varies greatly between patients, the ratio information from the protein markers may be pivotal in providing information about where the disease is at.

The researchers created K-edge metal nanoprobes made of praseodymium and hafnium. The probes target two proteins in cartilage tissue: These include aggrecan and aggrecanase, respectively. In healthy, early osteoarthritis joints, aggrecan is plentiful, helping the cartilage bear weight and provide structure.

However, Pan said, advancements in detector technologies like photon counting, CT scanning, and k-edge imaging (used by his lab for more than a decade), have allowed for highly precise and detailed imaging.

Now, we can count individual photons, and because of this we can create ‘hotspot ‘-like images centered on an element’s K-edge energy, said Pan. “Our results show for the first time that a cooperative biological process can be tracked in multicolor with a clinically relevant modality.”

According to Pan, photon counting CT scanning offers immunity to electronic noise and high-resolution imaging without sacrificing quantum efficiency, which enables at least several clinical applications.

Pan said that we showed the potential of K-edge nanoprobes and photon-counting CT scanning to detect critical stages of osteoarthritis before the development of symptoms and clinical presentation with the advanced stages. “The success of this field will depend on the synergistic development of these tools.”

Reference: Nivetha Gunaseelan, Parikshit Moitra, Saha P, Aditya T, Mahdieh Moghiseh, Jonker K, et al. Targeted K‐Edge Nanoprobes from Praseodymium and Hafnium for Ratiometric Tracking of Dual Biomarkers using Spectral Photon Counting CT. 

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