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Dual-Contrast Agent with Nanoparticle and Molecular Components in Photon-Counting Computed Tomography: Assessing Articular Cartilage Health.

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Title: Dual-Contrast Agent with Nanoparticle and Molecular Components in Photon-Counting Computed Tomography: Assessing Articular Cartilage Health.
Authors: Paakkari, Petri1,2 (AUTHOR) petri.paakkari@uef.fi, Inkinen, Satu I.3 (AUTHOR), Jäntti, Jiri1,2 (AUTHOR), Tuppurainen, Juuso1,2 (AUTHOR), Fugazzola, Maria C.4 (AUTHOR), Joenathan, Anisha5 (AUTHOR), Ylisiurua, Sampo6,7 (AUTHOR), Nieminen, Miika T.7 (AUTHOR), Kröger, Heikki8,9 (AUTHOR), Mikkonen, Santtu1,10 (AUTHOR), van Weeren, René4 (AUTHOR), Snyder, Brian D.11 (AUTHOR), Töyräs, Juha1,12,13 (AUTHOR), Honkanen, Miitu K. M.2 (AUTHOR), Matikka, Hanna2 (AUTHOR), Grinstaff, Mark W.5 (AUTHOR), Honkanen, Juuso T. J.14 (AUTHOR), Mäkelä, Janne T. A.1,2 (AUTHOR)
Source: Annals of Biomedical Engineering. Jun2025, Vol. 53 Issue 6, p1423-1438. 16p.
Subjects: Dual energy CT (Tomography), Articular cartilage, Contrast media, Biomedical engineering, Medical sciences
Abstract: Purpose: Photon-counting detectors (PCDs) are cutting-edge technology that enable spectral computed tomography (CT) imaging with a single scan. Spectral imaging is particularly effective in contrast-enhanced CT (CECT) imaging, especially when multiple contrast agents are utilized, as materials are distinguishable based on their unique X-ray absorption. One application of CECT is joint imaging, where it assesses the structure and composition of articular cartilage soft tissue. This evaluates articular cartilage and reveals compositional changes associated with early-stage osteoarthritis (OA) using a photon-counting detector CT (PCD-CT) technique combined with a dual-contrast agent method. Methods: A dual-contrast agent combination was used, consisting of proteoglycan-binding cationic tantalum oxide nanoparticles, developed in our lab, and a commercial non-ionic iodinated iodixanol agent. Ex vivo equine stifle joint cartilage samples (N = 30) were immersed in the contrast agent bath for 96 hours and imaged at multiple timepoints for analysis of proteoglycan, collagen, and water contents as well as collagen orientation, histological scoring, and biomechanical parameters. Results: By analyzing contrast agent concentrations, the technique provided a simultaneous assessment of the solid constituents and function of cartilage. Contrast agent diffusion depended on contrast agent composition and was significantly different between healthy and early-stage OA groups within 12 hours. Conclusion: The present study shows the promising utility of the dual-contrast PCD-CT technique for articular cartilage assessment and early-stage OA detection. [ABSTRACT FROM AUTHOR]
Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Dual-Contrast Agent with Nanoparticle and Molecular Components in Photon-Counting Computed Tomography: Assessing Articular Cartilage Health.
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+Biomedical+Engineering%22">Annals of Biomedical Engineering</searchLink>. Jun2025, Vol. 53 Issue 6, p1423-1438. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Dual+energy+CT+%28Tomography%29%22">Dual energy CT (Tomography)</searchLink><br /><searchLink fieldCode="DE" term="%22Articular+cartilage%22">Articular cartilage</searchLink><br /><searchLink fieldCode="DE" term="%22Contrast+media%22">Contrast media</searchLink><br /><searchLink fieldCode="DE" term="%22Biomedical+engineering%22">Biomedical engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+sciences%22">Medical sciences</searchLink>
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  Data: Purpose: Photon-counting detectors (PCDs) are cutting-edge technology that enable spectral computed tomography (CT) imaging with a single scan. Spectral imaging is particularly effective in contrast-enhanced CT (CECT) imaging, especially when multiple contrast agents are utilized, as materials are distinguishable based on their unique X-ray absorption. One application of CECT is joint imaging, where it assesses the structure and composition of articular cartilage soft tissue. This evaluates articular cartilage and reveals compositional changes associated with early-stage osteoarthritis (OA) using a photon-counting detector CT (PCD-CT) technique combined with a dual-contrast agent method. Methods: A dual-contrast agent combination was used, consisting of proteoglycan-binding cationic tantalum oxide nanoparticles, developed in our lab, and a commercial non-ionic iodinated iodixanol agent. Ex vivo equine stifle joint cartilage samples (N = 30) were immersed in the contrast agent bath for 96 hours and imaged at multiple timepoints for analysis of proteoglycan, collagen, and water contents as well as collagen orientation, histological scoring, and biomechanical parameters. Results: By analyzing contrast agent concentrations, the technique provided a simultaneous assessment of the solid constituents and function of cartilage. Contrast agent diffusion depended on contrast agent composition and was significantly different between healthy and early-stage OA groups within 12 hours. Conclusion: The present study shows the promising utility of the dual-contrast PCD-CT technique for articular cartilage assessment and early-stage OA detection. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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