Literature DB >> 22760344

Spectral CT of carotid atherosclerotic plaque: comparison with histology.

R Zainon1, J P Ronaldson, T Janmale, N J Scott, T M Buckenham, A P H Butler, P H Butler, R M Doesburg, S P Gieseg, J A Roake, N G Anderson.   

Abstract

OBJECTIVE: To distinguish components of vulnerable atherosclerotic plaque by imaging their energy response using spectral CT and comparing images with histology.
METHODS: After spectroscopic calibration using phantoms of plaque surrogates, excised human carotid atherosclerotic plaques were imaged using MARS CT using a photon-processing detector with a silicon sensor layer and microfocus X-ray tube (50 kVp, 0.5 mA) at 38-μm voxel size. The plaques were imaged, sectioned and re-imaged using four threshold energies: 10, 16, 22 and 28 keV; then sequentially stained with modified Von Kossa, Perl's Prussian blue and Oil-Red O, and photographed. Relative Hounsfield units across the energies were entered into a linear algebraic material decomposition model to identify the unknown plaque components.
RESULTS: Lipid, calcium, iron and water-like components of plaque have distinguishable energy responses to X-ray, visible on spectral CT images. CT images of the plaque surface correlated very well with histological photographs. Calcium deposits (>1,000 μm) in plaque are larger than iron deposits (<100 μm), but could not be distinguished from each other within the same voxel using the energy range available.
CONCLUSIONS: Spectral CT displays energy information in image form at high spatial resolution, enhancing the intrinsic contrast of lipid, calcium and iron within atheroma. KEY POINTS: Spectral computed tomography offers new insights into tissue characterisation. Components of vulnerable atherosclerotic plaque are spectrally distinct with intrinsic contrast. Spectral CT of excised atherosclerotic plaques can display iron, calcium and lipid. Calcium deposits are larger than iron deposits in atheroma. Spectral CT may help in the non-invasive detection of vulnerable plaques.

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Year:  2012        PMID: 22760344     DOI: 10.1007/s00330-012-2538-7

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


  32 in total

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Journal:  Eur Radiol       Date:  2011-12-02       Impact factor: 5.315

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Journal:  J Comput Assist Tomogr       Date:  2006 Sep-Oct       Impact factor: 1.826

Review 3.  The vulnerable, or high-risk, atherosclerotic plaque: noninvasive MR imaging for characterization and assessment.

Authors:  Tobias Saam; Thomas S Hatsukami; Norihide Takaya; Baocheng Chu; Hunter Underhill; William S Kerwin; Jianming Cai; Marina S Ferguson; Chun Yuan
Journal:  Radiology       Date:  2007-07       Impact factor: 11.105

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Review 6.  Contrast-enhanced ultrasound for assessing carotid atherosclerotic plaque lesions.

Authors:  Sasan Partovi; Matthias Loebe; Markus Aschwanden; Thomas Baldi; Kurt A Jäger; Steven B Feinstein; Daniel Staub
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7.  Predictors of surface disruption with MR imaging in asymptomatic carotid artery stenosis.

Authors:  H R Underhill; C Yuan; V L Yarnykh; B Chu; M Oikawa; L Dong; N L Polissar; G A Garden; S C Cramer; T S Hatsukami
Journal:  AJNR Am J Neuroradiol       Date:  2009-10-15       Impact factor: 3.825

8.  High-resolution CT imaging of carotid artery atherosclerotic plaques.

Authors:  M Wintermark; S S Jawadi; J H Rapp; T Tihan; E Tong; D V Glidden; S Abedin; S Schaeffer; G Acevedo-Bolton; B Boudignon; B Orwoll; X Pan; D Saloner
Journal:  AJNR Am J Neuroradiol       Date:  2008-02-13       Impact factor: 3.825

9.  Role of computed tomography voxel size in detection and discrimination of calcium and iron deposits in atherosclerotic human coronary artery specimens.

Authors:  Alexander C Langheinrich; Marian Kampschulte; Christine Crössmann; Regina Moritz; Wigbert S Rau; Rainer M Bohle; Erik L Ritman
Journal:  J Comput Assist Tomogr       Date:  2009 Jul-Aug       Impact factor: 1.826

10.  Direct quantitative in vivo comparison of calcified atherosclerotic plaque on vascular MRI and CT by multimodality image registration.

Authors:  Damini Dey; Piotr Slomka; Daisy Chien; David Fieno; Aiden Abidov; Rola Saouaf; Louise Thomson; John D Friedman; Daniel S Berman
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Authors:  Shuai Leng; Michael Bruesewitz; Shengzhen Tao; Kishore Rajendran; Ahmed F Halaweish; Norbert G Campeau; Joel G Fletcher; Cynthia H McCollough
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3.  Numerical observer for atherosclerotic plaque classification in spectral computed tomography.

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

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8.  In Vivo Molecular K-Edge Imaging of Atherosclerotic Plaque Using Photon-counting CT.

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9.  Beam profile assessment in spectral CT scanners.

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Journal:  J Appl Clin Med Phys       Date:  2018-02-07       Impact factor: 2.102

10.  Virtual Monoenergetic CT Imaging via Deep Learning.

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  10 in total

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