Literature DB >> 16549620

Informatics in Radiology (infoRAD): Magnetic Resonance Imaging Workbench: analysis and visualization of dynamic contrast-enhanced MR imaging data.

James A d'Arcy1, David J Collins, Anwar R Padhani, Simon Walker-Samuel, John Suckling, Martin O Leach.   

Abstract

Magnetic Resonance Imaging Workbench (MRIW) allows analysis of T1- and T2*-weighted dynamic contrast-enhanced magnetic resonance imaging data sets to extract tissue permeability and perfusion characteristics by using standard pharmacokinetic models. Parametric maps are calculated from individual pixel enhancement curves in regions of interest (ROIs) and displayed as color overlays on the anatomic images. User-defined ROIs can be saved to ensure consistency of later reanalysis. Individual parametric maps are visualized together with user-selected parameter time-series plots. The following selections are available: overall ROI enhancement curve and fit, histogram, and individual pixel enhancement curve and fit. Summary data (transfer constant, leakage space, rate constant, integrated area under the gadolinium curve after 60 seconds, relative blood volume, relative blood flow, and mean transit time) may be exported to permanent storage along with per-pixel results for statistical analysis. Numerical values for parameters are displayed below the plot for easy reference. The dynamic range of plots and parametric map overlays is interactively adjustable. Viewing individual enhancement curves and parametric maps allows radiologists to investigate the heterogeneity of contrast agent kinetics for lesion characterization and to scrutinize serial changes in response to therapy. MRIW is written in IDL, enabling it to be used on a variety of computer systems. (c) RSNA, 2006

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Year:  2006        PMID: 16549620     DOI: 10.1148/rg.262045187

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  30 in total

Review 1.  Multicentre imaging measurements for oncology and in the brain.

Authors:  P S Tofts; D J Collins
Journal:  Br J Radiol       Date:  2011-12       Impact factor: 3.039

Review 2.  Review of treatment assessment using DCE-MRI in breast cancer radiation therapy.

Authors:  Chun-Hao Wang; Fang-Fang Yin; Janet Horton; Zheng Chang
Journal:  World J Methodol       Date:  2014-06-26

3.  Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study.

Authors:  Chunhao Wang; Fang-Fang Yin; John P Kirkpatrick; Zheng Chang
Journal:  Technol Cancer Res Treat       Date:  2016-05-23

4.  Intravoxel incoherent motion and dynamic contrast-enhanced MRI for differentiation between hepatocellular adenoma and focal nodular hyperplasia.

Authors:  Naim Jerjir; Luk Bruyneel; Marc Haspeslagh; Sarah Quenet; Kenneth Coenegrachts
Journal:  Br J Radiol       Date:  2017-06-07       Impact factor: 3.039

5.  Assessment of Treatment Response With Diffusion-Weighted MRI and Dynamic Contrast-Enhanced MRI in Patients With Early-Stage Breast Cancer Treated With Single-Dose Preoperative Radiotherapy: Initial Results.

Authors:  Chunhao Wang; Janet K Horton; Fang-Fang Yin; Zheng Chang
Journal:  Technol Cancer Res Treat       Date:  2015-07-01

6.  Vascular characterisation of triple negative breast carcinomas using dynamic MRI.

Authors:  Sonia P Li; Anwar R Padhani; N Jane Taylor; Mark J Beresford; Mei-Lin W Ah-See; J James Stirling; James A d'Arcy; David J Collins; Andreas Makris
Journal:  Eur Radiol       Date:  2011-01-22       Impact factor: 5.315

7.  Arterial input functions in dynamic contrast-enhanced magnetic resonance imaging: which model performs best when assessing breast cancer response?

Authors:  David K Woolf; N Jane Taylor; Andreas Makris; Nina Tunariu; David J Collins; Sonia P Li; Mei-Lin Ah-See; Mark Beresford; Anwar R Padhani
Journal:  Br J Radiol       Date:  2016-05-17       Impact factor: 3.039

8.  Noninvasive Imaging of Cycling Hypoxia in Head and Neck Cancer Using Intrinsic Susceptibility MRI.

Authors:  Rafal Panek; Liam Welsh; Lauren C J Baker; Maria A Schmidt; Kee H Wong; Angela M Riddell; Dow-Mu Koh; Alex Dunlop; Dualta Mcquaid; James A d'Arcy; Shreerang A Bhide; Kevin J Harrington; Christopher M Nutting; Georgina Hopkinson; Cheryl Richardson; Carol Box; Suzanne A Eccles; Martin O Leach; Simon P Robinson; Kate L Newbold
Journal:  Clin Cancer Res       Date:  2017-03-17       Impact factor: 12.531

9.  Multivariate modelling of prostate cancer combining magnetic resonance derived T2, diffusion, dynamic contrast-enhanced and spectroscopic parameters.

Authors:  S F Riches; G S Payne; V A Morgan; D Dearnaley; S Morgan; M Partridge; N Livni; C Ogden; N M deSouza
Journal:  Eur Radiol       Date:  2015-03-07       Impact factor: 5.315

10.  Radiotherapy planning using MRI.

Authors:  Maria A Schmidt; Geoffrey S Payne
Journal:  Phys Med Biol       Date:  2015-10-28       Impact factor: 3.609

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