Literature DB >> 30554271

Variation of degree of stenosis quantification using different energy level with dual energy CT scanner.

Luca Saba1, Giovanni Maria Argioas2, Pierleone Lucatelli3, Francesco Lavra4, Jasjit S Suri5,6, Max Wintermark7.   

Abstract

PURPOSE: To investigate the variation in the quantification of the carotid degree of stenosis (DoS) with a dual energy computed tomography (CT), using different energy levels during the image reconstruction.
METHODS: In this retrospective study, 53 subjects (37 males; mean age 67 ± 11 years; age range 47-83 years) studied with a multi-energy CT scanner were included. Datasets were reconstructed on a dedicated workstation and from the CT raw data multiple datasets were generated at the following monochromatic energy levels: 66, 70, 77, and 86 kilo-electronvolt (keV). Two radiologists independently performed all measurements for quantification of the degree of stenosis. Wilcoxon test was used to test the differences between the Hounsifield unit (HU) values in the plaques at different keV.
RESULTS: The Wilcoxon analysis showed a statistically significant difference (p = 0.001) in the DoS assessment among the different keVs selected. The Bland-Altman analysis showed that the DoS difference had a linear relation with the keV difference (the bigger is the difference in keV, the bigger is the variation in DoS) and that for different keVs, the difference in DoS is reduced with its increase.
CONCLUSION: A standardization in the use of the energy level during the image reconstruction should be considered.

Entities:  

Keywords:  CT; Carotid artery; Dual energy CT

Mesh:

Year:  2018        PMID: 30554271     DOI: 10.1007/s00234-018-2142-x

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  2 in total

Review 1.  Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.

Authors:  Luca Saba; Skandha S Sanagala; Suneet K Gupta; Vijaya K Koppula; Amer M Johri; Narendra N Khanna; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Durga P Misra; Vikas Agarwal; Aditya M Sharma; Vijay Viswanathan; Vijay S Rathore; Monika Turk; Raghu Kolluri; Klaudija Viskovic; Elisa Cuadrado-Godia; George D Kitas; Neeraj Sharma; Andrew Nicolaides; Jasjit S Suri
Journal:  Ann Transl Med       Date:  2021-07

2.  A Novel Block Imaging Technique Using Nine Artificial Intelligence Models for COVID-19 Disease Classification, Characterization and Severity Measurement in Lung Computed Tomography Scans on an Italian Cohort.

Authors:  Mohit Agarwal; Luca Saba; Suneet K Gupta; Alessandro Carriero; Zeno Falaschi; Alessio Paschè; Pietro Danna; Ayman El-Baz; Subbaram Naidu; Jasjit S Suri
Journal:  J Med Syst       Date:  2021-01-26       Impact factor: 4.460

  2 in total

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