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BACKGROUND AND AIMS: Atherosclerotic plaques are characterized as being vulnerable to rupture based on a series of histologically defined features, including a lipid-rich necrotic core, spotty calcification and ulceration. Existing imaging modalities have limitations in their ability to distinguish between different materials and structural features. We examined whether X-ray spectral photon-counting computer tomography (SPCCT) images were able to distinguish key plaque features in a surgically excised specimen from the carotid artery with comparison to histological images. METHODS: An excised carotid plaque was imaged in the diagnostic X-ray energy range of 30-120 keV using a small-bore SPCCT scanner equipped with a Medipix3RX photon-counting spectral X-ray detector with a cadmium telluride (CdTe) sensor. Material identification and quantification (MIQ) images of the carotid plaque were generated using proprietary MIQ software at 0.09 mm volumetric pixels (voxels). The plaque was sectioned, stained and photographed at high resolution for comparison. RESULTS: A lipid-rich core with spotty calcification was identified in the MIQ images and confirmed by histology. MIQ showed a core region containing lipid, with a mean concentration of 260 mg lipid/ml corresponding to a mean value of -22HU. MIQ showed calcified regions with mean concentration of 41 mg Ca/ml corresponded to a mean value of 123HU. An ulceration of the carotid wall at the bifurcation was identified to be lipid-lined, with a small calcification identified near the breach of the artery wall. CONCLUSIONS: SPCCT derived material identification and quantification images showed hallmarks of vulnerable plaque including a lipid-rich necrotic core, spotty calcifications and ulcerations.

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To determine whether state-of-the-art multi-energy spectral photon-counting computed tomography (MARS) can detect knee arthroplasty implant failure not detected by standard pre-operative imaging techniques. A total knee arthroplasty (TKA) removed from a patient was reviewed. The extracted prosthesis [NexGen Legacy Posterior Stabilized (LPS) TKA] was analyzed as were pre-operative imaging examination and compared with a MARS-CT examination obtained of the extracted TKA prosthesis. Radiographs, fluoroscopy, ultrasound and MRI preoperatively did not reveal the cause of the implant failure. MARS CT images of the extracted prosthesis clearly showed the presence of posteromedial polyethylene and tibial tray wear which is compatible with the clinical appearance of the extracted TKA. MARS can identify polyethylene insert and metallic tibial tray wear as a cause of TKA failure, that could not be identified with on standard pre-operative imaging. Although clinical MARS CT system is still under development, this case does illustrate its potential clinical usefulness. This is the first study to document how MARS CT imaging can detect orthopedic implant failure not detected by standard current imaging techniques. This system has a potential clinical application in orthopedic patients.

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OBJECTIVES: To quantify iodine uptake in articular cartilage as a marker of glycosaminoglycan (GAG) content using multi-energy spectral CT. METHODS: We incubated a 25-mm strip of excised osteoarthritic human tibial plateau in 50 % ionic iodine contrast and imaged it using a small-animal spectral scanner with a cadmium telluride photon-processing detector to quantify the iodine through the thickness of the articular cartilage. We imaged both spectroscopic phantoms and osteoarthritic tibial plateau samples. The iodine distribution as an inverse marker of GAG content was presented in the form of 2D and 3D images after applying a basis material decomposition technique to separate iodine in cartilage from bone. We compared this result with a histological section stained for GAG. RESULTS: The iodine in cartilage could be distinguished from subchondral bone and quantified using multi-energy CT. The articular cartilage showed variation in iodine concentration throughout its thickness which appeared to be inversely related to GAG distribution observed in histological sections. CONCLUSIONS: Multi-energy CT can quantify ionic iodine contrast (as a marker of GAG content) within articular cartilage and distinguish it from bone by exploiting the energy-specific attenuation profiles of the associated materials. KEY POINTS: • Contrast-enhanced articular cartilage and subchondral bone can be distinguished using multi-energy CT. • Iodine as a marker of glycosaminoglycan content is quantifiable with multi-energy CT. • Multi-energy CT could track alterations in GAG content occurring in osteoarthritis.

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