New Photon-Counting CT Technique Diagnoses Osteoarthritis Before Symptoms Develop

X-ray imaging has evolved significantly since its introduction in 1895. This technique is known for capturing images quickly, making it ideal for emergency situations; however, it does not provide adequate soft tissue contrast and struggles to differentiate the imaging signal from the disease site from that of intrinsic structures like bones. In imaging, visualization is particularly critical for diseases such as osteoarthritis, a degenerative joint condition often referred to as wear-and-tear arthritis. Osteoarthritis can advance without noticeable symptoms until it reaches an advanced and irreversible stage. Early intervention could alleviate symptoms and enhance quality of life if tools for early diagnosis and continuous disease monitoring were available. Now, a new technological breakthrough brings back traditional black and white diagnostic images of X-rays and traditional computed tomography (CT) scans into technicolor.

Researchers at Penn State (University Park, PA, USA) have developed novel contrast agents that target two proteins associated with osteoarthritis. By marking these proteins with newly designed metal nanoprobes, the researchers can utilize advanced imaging techniques known as “K-edge” imaging or photon-counting CT to simultaneously track distinct biological processes in color, which together provide greater insight into the disease's progression than traditional imaging methods. This work, conducted in rats with potential implications for humans, enables researchers and clinicians to visualize previously hidden processes in color and detect signs of the disease long before the development of clinical symptoms.

Image: The novel contrast agents target two proteins implicated in osteoarthritis and can be imaged using a photon-counting CT scanner (Photo courtesy of Pan Lab)

The photon-counting CT scanner can detail the same bone, muscle, and fat structures that conventional CT scanners capture but offers a much broader capability to separate various components at a higher resolution and in specific colors. This scanner identifies materials with unique K-edge properties, which refers to how electrons in a material absorb energy. Electrons reside in a K-shell, which surrounds the nucleus of an atom. When energy is absorbed from photons—particles of light—the electrons can move to higher energy shells. If the atom reaches a specific energy absorption limit, it emits a flash of light. The researchers can program the scanner to detect that particular light emission, referred to as the K-edge. If a material with a distinct K-edge identity targets a specific protein, the scanner can then track that protein's activity.

The team designed two K-edge metal nanoprobes composed of praseodymium and hafnium. These probes are aimed at two proteins found in cartilage tissue: aggrecan and aggrecanase, respectively. Aggrecan, which contributes to the structure and weight-bearing capacity of cartilage, is abundant in healthy joints and in the early stages of osteoarthritis. In contrast, aggrecanase, which cleaves aggrecan and diminishes cartilage function, is prevalent in the later stages of osteoarthritis. As the disease progresses, the ratio of these proteins shifts, providing metrics to monitor disease status. The researchers employed the photon-counting CT scanner to observe how this ratio changed as the disease advanced in an animal model. They corroborated their findings with additional imaging and experimental validation, with their results published in Advanced Science.

“This high-resolution, K-edge-based imaging approach could potentially be used to image multiple biological targets, thus enabling disease progression tracking over time by measuring the ratio of protein expression,” said corresponding author Dipanjan Pan, the Dorothy Foehr Huck & J. Lloyd Huck Chair Professor in Nanomedicine and professor of materials science and engineering and of nuclear engineering at Penn State. “The approach can be particularly beneficial in skeletal disease diagnoses since the progression of cartilage degradation is highly variable among patients and the ratio information from the protein markers could provide crucial information about the stage of the disease.”