Literature DB >> 25300721

Quantitative assessment of effects of motion compensation for liver and lung tumors in CT perfusion.

Alessandro Bevilacqua1, Domenico Barone2, Silvia Malavasi3, Giampaolo Gavelli2.   

Abstract

RATIONALE AND
OBJECTIVES: To study the effects of four different rigid alignment approaches on both time-concentration curves (TCCs) and perfusion maps in computed tomography perfusion (CTp) studies of liver and lung tumors.
MATERIALS AND METHODS: Eleven data sets in patients who were subjected to axial CTp after contrast agent administration were assessed. Each data set consists of four different sequences, according to the different rigid alignment configurations considered to compute blood flow perfusion maps: no alignment, translational, craniocaudal, and three dimensional (3D). The color maps were built on TCCs according to the maximum slope method. The effects of motion correction procedures on the reliability of TCCs and perfusion maps were assessed both quantitatively and visually.
RESULTS: TCCs built after 3D alignments show the best indices as well as producing the most reliable maps. We show examinations in which the translational alignment only yields more accurate TCCs, but less reliable perfusion maps, than those achieved with no alignment. Furthermore, we show color maps with two different perfusion patterns, both considered reliable by radiologists, achieved with different motion correction approaches.
CONCLUSIONS: The quantitative index we conceived allows relating quality of 3D alignment and reliability of perfusion maps. A better alignment does not necessarily yield more reliable perfusion values: color maps resulting from either alignment procedure must be critically assessed by radiologists. This achievement will hopefully represent a step forward for the clinical use of CTp studies for staging, prognosis, and monitoring values of therapeutic regimens.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  TCC; image processing; liver; lung; motion compensation; perfusion imaging

Mesh:

Year:  2014        PMID: 25300721     DOI: 10.1016/j.acra.2014.06.005

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  7 in total

1.  Better understanding of acute gouty attack using CT perfusion in a rabbit model.

Authors:  Yabin Hu; Qing Yang; Yanyan Gao; Xuexin Guo; Yongjian Liu; Can Li; Yanmeng Du; Lei Gao; Dezheng Sun; Congcong Zhu; Mi Yan
Journal:  Eur Radiol       Date:  2018-12-05       Impact factor: 5.315

Review 2.  Advances in Imaging and Automated Quantification of Malignant Pulmonary Diseases: A State-of-the-Art Review.

Authors:  Bruno Hochhegger; Matheus Zanon; Stephan Altmayer; Gabriel S Pacini; Fernanda Balbinot; Martina Z Francisco; Ruhana Dalla Costa; Guilherme Watte; Marcel Koenigkam Santos; Marcelo C Barros; Diana Penha; Klaus Irion; Edson Marchiori
Journal:  Lung       Date:  2018-10-09       Impact factor: 2.584

3.  Liver CT perfusion: which is the relevant delay that reduces radiation dose and maintains diagnostic accuracy?

Authors:  Alessandro Bevilacqua; Silvia Malavasi; Valérie Vilgrain
Journal:  Eur Radiol       Date:  2019-05-21       Impact factor: 5.315

4.  Is liver perfusion CT reproducible? A study on intra- and interobserver agreement of normal hepatic haemodynamic parameters obtained with two different software packages.

Authors:  Elisa Almeida Sathler Bretas; Ulysses S Torres; Lucas Rios Torres; Daniel Bekhor; Celso Fernando Saito Filho; Douglas Jorge Racy; Lorenzo Faggioni; Giuseppe D'Ippolito
Journal:  Br J Radiol       Date:  2017-08-22       Impact factor: 3.039

5.  CT perfusion imaging of lung cancer: benefit of motion correction for blood flow estimates.

Authors:  Lisa L Chu; Robert J Knebel; Aryan D Shay; Jonathan Santos; Ramsey D Badawi; David R Gandara; Friedrich D Knollmann
Journal:  Eur Radiol       Date:  2018-06-04       Impact factor: 5.315

6.  Multislice Analysis of Blood Flow Values in CT Perfusion Studies of Lung Cancer.

Authors:  Silvia Malavasi; Domenico Barone; Giampaolo Gavelli; Alessandro Bevilacqua
Journal:  Biomed Res Int       Date:  2017-01-10       Impact factor: 3.411

7.  CT Perfusion in Patients with Lung Cancer: Squamous Cell Carcinoma and Adenocarcinoma Show a Different Blood Flow.

Authors:  Alessandro Bevilacqua; Giampaolo Gavelli; Serena Baiocco; Domenico Barone
Journal:  Biomed Res Int       Date:  2018-09-03       Impact factor: 3.411

  7 in total

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