Literature DB >> 19293470

Optimizing functional parameter accuracy for breath-hold DCE-MRI of liver tumours.

Matthew R Orton1, Keiko Miyazaki, Dow-Mu Koh, David J Collins, David J Hawkes, David Atkinson, Martin O Leach.   

Abstract

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a valuable tool for assessing treatment response to novel cancer therapeutics. With appropriate data acquisition, quantitative functional parameter estimates can be obtained by fitting a model to the data. This research focuses on applying a dual-input single-compartment pharmacokinetic model to breath-hold DCE-MRI imaging of the liver. In this paper, the use of two breath-holds, providing greater temporal information, is compared with a single breath-hold approach. Computer simulations are used to assess the accuracy, precision and sensitivity to input function errors obtained for parameters estimated from the two imaging protocols. Data from ten patients were analysed to assess the noise statistics obtained from the two breath-hold protocols. The noise statistics were used with a pharmacokinetic liver model to simulate data, from which the estimation accuracy, precision and sensitivity for the two protocols were assessed. Data from the ten patients were also analysed, and the estimates were compared with literature values. This work demonstrates the feasibility of obtaining functional liver perfusion estimates over a 3D volume using a sequential breath-hold protocol. The simulation results show that the protocol consisting of two images per breath-hold is to be preferred as it requires identical patient co-operation, but provides parameter estimates that have superior accuracy and precision.

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Year:  2009        PMID: 19293470     DOI: 10.1088/0031-9155/54/7/023

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  10 in total

1.  Free-breathing dynamic contrast-enhanced MRI of the abdomen and chest using a radial gradient echo sequence with K-space weighted image contrast (KWIC).

Authors:  Kyung Won Kim; Jeong Min Lee; Yong Sik Jeon; Sung Eun Kang; Jee Hyun Baek; Joon Koo Han; Byung Ihn Choi; Yung-Jue Bang; Berthold Kiefer; Kai Tobias Block; Hyunjun Ji; Simon Bauer; Chin Kim
Journal:  Eur Radiol       Date:  2012-11-28       Impact factor: 5.315

Review 2.  Perfusion magnetic resonance imaging of the liver.

Authors:  Choon Hua Thng; Tong San Koh; David J Collins; Dow Mu Koh
Journal:  World J Gastroenterol       Date:  2010-04-07       Impact factor: 5.742

3.  Measurement of Tissue interstitial volume in healthy patients and those with amyloidosis with equilibrium contrast-enhanced MR imaging.

Authors:  Steve Bandula; Sanjay M Banypersad; Daniel Sado; Andrew S Flett; Shonit Punwani; Stuart A Taylor; Philip N Hawkins; James C Moon
Journal:  Radiology       Date:  2013-05-14       Impact factor: 11.105

4.  Optimization of saturation-recovery dynamic contrast-enhanced MRI acquisition protocol: monte carlo simulation approach demonstrated with gadolinium MR renography.

Authors:  Jeff L Zhang; Chris C Conlin; Kristi Carlston; Luke Xie; Daniel Kim; Glen Morrell; Kathryn Morton; Vivian S Lee
Journal:  NMR Biomed       Date:  2016-05-20       Impact factor: 4.044

5.  DCE-MRI of hepatocellular carcinoma: perfusion quantification with Tofts model versus shutter-speed model--initial experience.

Authors:  Guido H Jajamovich; Wei Huang; Cecilia Besa; Xin Li; Aneela Afzal; Hadrien A Dyvorne; Bachir Taouli
Journal:  MAGMA       Date:  2015-12-08       Impact factor: 2.310

6.  Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging.

Authors:  M O Leach; B Morgan; P S Tofts; D L Buckley; W Huang; M A Horsfield; T L Chenevert; D J Collins; A Jackson; D Lomas; B Whitcher; L Clarke; R Plummer; I Judson; R Jones; R Alonzi; T Brunner; D M Koh; P Murphy; J C Waterton; G Parker; M J Graves; T W J Scheenen; T W Redpath; M Orton; G Karczmar; H Huisman; J Barentsz; A Padhani
Journal:  Eur Radiol       Date:  2012-05-07       Impact factor: 5.315

7.  DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6.

Authors:  J P B O'Connor; C J Rose; A Jackson; Y Watson; S Cheung; F Maders; B J Whitcher; C Roberts; G A Buonaccorsi; G Thompson; A R Clamp; G C Jayson; G J M Parker
Journal:  Br J Cancer       Date:  2011-06-14       Impact factor: 7.640

8.  DCE-MRI is more sensitive than IVIM-DWI for assessing anti-angiogenic treatment-induced changes in colorectal liver metastases.

Authors:  Mihaela Rata; Khurum Khan; David J Collins; Dow-Mu Koh; Nina Tunariu; Maria Antonietta Bali; James d'Arcy; Jessica M Winfield; Simona Picchia; Nicola Valeri; Ian Chau; David Cunningham; Matteo Fassan; Martin O Leach; Matthew R Orton
Journal:  Cancer Imaging       Date:  2021-12-19       Impact factor: 3.909

9.  Reproducibility of Dynamic Contrast-Enhanced MRI in Renal Cell Carcinoma: A Prospective Analysis on Intra- and Interobserver and Scan-Rescan Performance of Pharmacokinetic Parameters.

Authors:  Haiyi Wang; Zihua Su; Huiyi Ye; Xiao Xu; Zhipeng Sun; Lu Li; Feixue Duan; Yuanyuan Song; Tryphon Lambrou; Lin Ma
Journal:  Medicine (Baltimore)       Date:  2015-09       Impact factor: 1.817

10.  Assessment of repeatability and treatment response in early phase clinical trials using DCE-MRI: comparison of parametric analysis using MR- and CT-derived arterial input functions.

Authors:  Mihaela Rata; David J Collins; James Darcy; Christina Messiou; Nina Tunariu; Nandita Desouza; Helen Young; Martin O Leach; Matthew R Orton
Journal:  Eur Radiol       Date:  2015-09-18       Impact factor: 5.315

  10 in total

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