Clinical impact of an adaptive statistical iterative reconstruction algorithm for detection of hypervascular liver tumou
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Clinical impact of an adaptive statistical iterative reconstruction algorithm for detection of hypervascular liver tumours using a low tube voltage, high tube current MDCT technique Daniele Marin & Kingshuk Roy Choudhury & Rajan T. Gupta & Lisa M. Ho & Brian C. Allen & Sebastian T. Schindera & James G. Colsher & Ehsan Samei & Rendon C. Nelson
Received: 8 May 2013 / Revised: 12 June 2013 / Accepted: 14 June 2013 # European Society of Radiology 2013
Abstract Objectives To investigate the impact of an adaptive statistical iterative reconstruction (ASiR) algorithm on diagnostic accuracy and confidence for the diagnosis of hypervascular liver tumours, as well as the reader’s perception of image quality, using a low tube voltage (80 kVp), high tube current computed tomography (CT) technique. Methods Forty patients (29 men, 11 women) with 65 hypervascular liver tumours underwent dual energy CT. The 80 kV set of the dual energy acquisition was reconstructed with standard filtered backprojection (FBP) and ASiR at different blending levels. Lesion contrast-to-noise ratio (CNR), reader’s confidence for lesion detection and characterisation, and reader’s evaluation of image quality were recorded. Results ASiR yielded significantly higher CNR values compared with FBP (P
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