Literature DB >> 27165137

Quantitative imaging of excised osteoarthritic cartilage using spectral CT.

Kishore Rajendran1, Caroline Löbker2,3, Benjamin S Schon2, Christopher J Bateman1, Raja Aamir Younis1, Niels J A de Ruiter1, Alex I Chernoglazov4, Mohsen Ramyar1, Gary J Hooper2, Anthony P H Butler1,5,6, Tim B F Woodfield2, Nigel G Anderson7.   

Abstract

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.

Entities:  

Keywords:  Articular cartilage; Glycosaminoglycan; Ionic contrast media; Osteoarthritis; Spectral CT

Mesh:

Substances:

Year:  2016        PMID: 27165137     DOI: 10.1007/s00330-016-4374-7

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  26 in total

1.  Noise reduction in spectral CT: reducing dose and breaking the trade-off between image noise and energy bin selection.

Authors:  Shuai Leng; Lifeng Yu; Jia Wang; Joel G Fletcher; Charles A Mistretta; Cynthia H McCollough
Journal:  Med Phys       Date:  2011-09       Impact factor: 4.071

Review 2.  Clinical applications of spectral molecular imaging: potential and challenges.

Authors:  Nigel G Anderson; Anthony P Butler
Journal:  Contrast Media Mol Imaging       Date:  2014 Jan-Feb       Impact factor: 3.161

Review 3.  Clinical and translational potential of MRI evaluation in knee osteoarthritis.

Authors:  Daichi Hayashi; Ali Guermazi; C Kent Kwoh
Journal:  Curr Rheumatol Rep       Date:  2014-01       Impact factor: 4.592

4.  Formalin fixation affects equilibrium partitioning of an ionic contrast agent-microcomputed tomography (EPIC-μCT) imaging of osteochondral samples.

Authors:  K E M Benders; J Malda; D B F Saris; W J A Dhert; R Steck; D W Hutmacher; T J Klein
Journal:  Osteoarthritis Cartilage       Date:  2010-10-13       Impact factor: 6.576

Review 5.  Cartilage in normal and osteoarthritis conditions.

Authors:  Johanne Martel-Pelletier; Christelle Boileau; Jean-Pierre Pelletier; Peter J Roughley
Journal:  Best Pract Res Clin Rheumatol       Date:  2008-04       Impact factor: 4.098

6.  Biomechanics of articular cartilage and determination of material properties.

Authors:  Xin L Lu; Van C Mow
Journal:  Med Sci Sports Exerc       Date:  2008-02       Impact factor: 5.411

Review 7.  Quantitative radiologic imaging techniques for articular cartilage composition: toward early diagnosis and development of disease-modifying therapeutics for osteoarthritis.

Authors:  Edwin H G Oei; Jasper van Tiel; William H Robinson; Garry E Gold
Journal:  Arthritis Care Res (Hoboken)       Date:  2014-08       Impact factor: 4.794

8.  Diffusion and near-equilibrium distribution of MRI and CT contrast agents in articular cartilage.

Authors:  Tuomo S Silvast; Harri T Kokkonen; Jukka S Jurvelin; Thomas M Quinn; Miika T Nieminen; Juha Töyräs
Journal:  Phys Med Biol       Date:  2009-10-28       Impact factor: 3.609

9.  Comparison of quantitative imaging of cartilage for osteoarthritis: T2, T1rho, dGEMRIC and contrast-enhanced computed tomography.

Authors:  Carmen Taylor; Julio Carballido-Gamio; Sharmila Majumdar; Xiaojuan Li
Journal:  Magn Reson Imaging       Date:  2009-03-09       Impact factor: 2.546

Review 10.  Imaging strategies for assessing cartilage composition in osteoarthritis.

Authors:  Stephen J Matzat; Feliks Kogan; Grant W Fong; Garry E Gold
Journal:  Curr Rheumatol Rep       Date:  2014-11       Impact factor: 4.592

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  9 in total

Review 1.  Photon-counting Detector CT: System Design and Clinical Applications of an Emerging Technology.

Authors:  Shuai Leng; Michael Bruesewitz; Shengzhen Tao; Kishore Rajendran; Ahmed F Halaweish; Norbert G Campeau; Joel G Fletcher; Cynthia H McCollough
Journal:  Radiographics       Date:  2019 May-Jun       Impact factor: 5.333

2.  A Hybrid 2D/3D User Interface for Radiological Diagnosis.

Authors:  Veera Bhadra Harish Mandalika; Alexander I Chernoglazov; Mark Billinghurst; Christoph Bartneck; Michael A Hurrell; Niels de Ruiter; Anthony P H Butler; Philip H Butler
Journal:  J Digit Imaging       Date:  2018-02       Impact factor: 4.056

3.  Photon Counting CT: Clinical Applications and Future Developments.

Authors:  Scott S Hsieh; Shuai Leng; Kishore Rajendran; Shengzhen Tao; Cynthia H McCollough
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-08-28

4.  Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment.

Authors:  Adam S Wang; Norbert J Pelc
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-07-07

5.  Quantitative Knee Arthrography in a Large Animal Model of Osteoarthritis Using Photon-Counting Detector CT.

Authors:  Kishore Rajendran; Naveen S Murthy; Matthew A Frick; Shengzhen Tao; Mark D Unger; Katherine T LaVallee; Nicholas B Larson; Shuai Leng; Timothy P Maus; Cynthia H McCollough
Journal:  Invest Radiol       Date:  2020-06       Impact factor: 10.065

6.  X-ray-based virtual slicing of TB-infected lungs.

Authors:  Ana Ortega-Gil; Juan José Vaquero; Mario Gonzalez-Arjona; Joaquín Rullas; Arrate Muñoz-Barrutia
Journal:  Sci Rep       Date:  2019-12-18       Impact factor: 4.379

7.  Multi-energy spectral photon-counting computed tomography (MARS) for detection of arthroplasty implant failure.

Authors:  Lawrence Chun Man Lau; Wayne Yuk Wai Lee; Anthony P H Butler; Alex I Chernoglazov; Kwong Yin Chung; Kevin Ki Wai Ho; James Griffith; Philip H Butler; Patrick Shu Hang Yung
Journal:  Sci Rep       Date:  2021-01-15       Impact factor: 4.379

8.  Beam profile assessment in spectral CT scanners.

Authors:  Marzieh Anjomrouz; Muhammad Shamshad; Raj K Panta; Lieza Vanden Broeke; Nanette Schleich; Ali Atharifard; Raja Aamir; Srinidhi Bheesette; Michael F Walsh; Brian P Goulter; Stephen T Bell; Christopher J Bateman; Anthony P H Butler; Philip H Butler
Journal:  J Appl Clin Med Phys       Date:  2018-02-07       Impact factor: 2.102

9.  Spectral Photon-Counting Molecular Imaging for Quantification of Monoclonal Antibody-Conjugated Gold Nanoparticles Targeted to Lymphoma and Breast Cancer: An In Vitro Study.

Authors:  Mahdieh Moghiseh; Chiara Lowe; John G Lewis; Dhiraj Kumar; Anthony Butler; Nigel Anderson; Aamir Raja
Journal:  Contrast Media Mol Imaging       Date:  2018-12-18       Impact factor: 3.161

  9 in total

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