Literature DB >> 21437971

Comparison of dynamic contrast-enhanced MRI and dynamic contrast-enhanced CT biomarkers in bladder cancer.

J H Naish1, D M McGrath, L J Bains, K Passera, C Roberts, Y Watson, S Cheung, M B Taylor, J P Logue, D L Buckley, J Tessier, H Young, J C Waterton, G J M Parker.   

Abstract

Dynamic contrast-enhanced MRI (DCE-MRI) is frequently used to provide response biomarkers in clinical trials of novel cancer therapeutics but assessment of their physiological accuracy is difficult. DCE-CT provides an independent probe of similar pharmacokinetic processes and may be modeled in the same way as DCE-MRI to provide purportedly equivalent physiological parameters. In this study, DCE-MRI and DCE-CT were directly compared in subjects with primary bladder cancer to assess the degree to which the model parameters report modeled physiology rather than artefacts of the measurement technique and to determine the interchangeability of the techniques in a clinical trial setting. The biomarker K(trans) obtained by fitting an extended version of the Kety model voxelwise to both DCE-MRI and DCE-CT data was in excellent agreement (mean across subjects was 0.085 ± 0.030 min(-1) for DCE-MRI and 0.087 ± 0.033 min(-1) for DCE-CT, intermodality coefficient of variation 9%). The parameter v(p) derived from DCE-CT was significantly greater than that derived from DCE-MRI (0.018 ± 0.006 compared to 0.009 ± 0.008, P = 0.0007) and v(e) was in reasonable agreement only for low values. The study provides evidence that the biomarker K(trans) is a robust parameter indicative of the underlying physiology and relatively independent of the method of measurement.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21437971     DOI: 10.1002/mrm.22774

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  9 in total

1.  Comparison of arterial input functions measured from ultra-fast dynamic contrast enhanced MRI and dynamic contrast enhanced computed tomography in prostate cancer patients.

Authors:  Shiyang Wang; Zhengfeng Lu; Xiaobing Fan; Milica Medved; Xia Jiang; Steffen Sammet; Ambereen Yousuf; Federico Pineda; Aytekin Oto; Gregory S Karczmar
Journal:  Phys Med Biol       Date:  2018-01-30       Impact factor: 3.609

2.  An evaluation of morphological and functional multi-parametric MRI sequences in classifying non-muscle and muscle invasive bladder cancer.

Authors:  Valeria Panebianco; Ettore De Berardinis; Giovanni Barchetti; Giuseppe Simone; Constantino Leonardo; Marcello Domenico Grompone; Maurizio Del Monte; Davide Carano; Michele Gallucci; James Catto; Carlo Catalano
Journal:  Eur Radiol       Date:  2017-02-08       Impact factor: 5.315

Review 3.  Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer.

Authors:  Michael Ingrisch; Steven Sourbron
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-04-06       Impact factor: 2.745

Review 4.  [The role of the vesical imaging-reporting and data system (VI-RADS) for bladder cancer diagnostics-status quo].

Authors:  V Hechler; M Rink; D Beyersdorff; M Beer; A J Beer; V Panebianco; M Pecoraro; C Bolenz; G Salomon
Journal:  Urologe A       Date:  2019-12       Impact factor: 0.639

Review 5.  Imaging biomarker roadmap for cancer studies.

Authors:  James P B O'Connor; Eric O Aboagye; Judith E Adams; Hugo J W L Aerts; Sally F Barrington; Ambros J Beer; Ronald Boellaard; Sarah E Bohndiek; Michael Brady; Gina Brown; David L Buckley; Thomas L Chenevert; Laurence P Clarke; Sandra Collette; Gary J Cook; Nandita M deSouza; John C Dickson; Caroline Dive; Jeffrey L Evelhoch; Corinne Faivre-Finn; Ferdia A Gallagher; Fiona J Gilbert; Robert J Gillies; Vicky Goh; John R Griffiths; Ashley M Groves; Steve Halligan; Adrian L Harris; David J Hawkes; Otto S Hoekstra; Erich P Huang; Brian F Hutton; Edward F Jackson; Gordon C Jayson; Andrew Jones; Dow-Mu Koh; Denis Lacombe; Philippe Lambin; Nathalie Lassau; Martin O Leach; Ting-Yim Lee; Edward L Leen; Jason S Lewis; Yan Liu; Mark F Lythgoe; Prakash Manoharan; Ross J Maxwell; Kenneth A Miles; Bruno Morgan; Steve Morris; Tony Ng; Anwar R Padhani; Geoff J M Parker; Mike Partridge; Arvind P Pathak; Andrew C Peet; Shonit Punwani; Andrew R Reynolds; Simon P Robinson; Lalitha K Shankar; Ricky A Sharma; Dmitry Soloviev; Sigrid Stroobants; Daniel C Sullivan; Stuart A Taylor; Paul S Tofts; Gillian M Tozer; Marcel van Herk; Simon Walker-Samuel; James Wason; Kaye J Williams; Paul Workman; Thomas E Yankeelov; Kevin M Brindle; Lisa M McShane; Alan Jackson; John C Waterton
Journal:  Nat Rev Clin Oncol       Date:  2016-10-11       Impact factor: 66.675

Review 6.  Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics.

Authors:  Massimo E Maffei
Journal:  Int J Mol Sci       Date:  2022-01-25       Impact factor: 5.923

Review 7.  Multiparametric Magnetic Resonance Imaging for Bladder Cancer: Development of VI-RADS (Vesical Imaging-Reporting And Data System).

Authors:  Valeria Panebianco; Yoshifumi Narumi; Ersan Altun; Bernard H Bochner; Jason A Efstathiou; Shaista Hafeez; Robert Huddart; Steve Kennish; Seth Lerner; Rodolfo Montironi; Valdair F Muglia; Georg Salomon; Stephen Thomas; Hebert Alberto Vargas; J Alfred Witjes; Mitsuru Takeuchi; Jelle Barentsz; James W F Catto
Journal:  Eur Urol       Date:  2018-05-10       Impact factor: 20.096

8.  Practical dynamic contrast enhanced MRI in small animal models of cancer: data acquisition, data analysis, and interpretation.

Authors:  Stephanie L Barnes; Jennifer G Whisenant; Mary E Loveless; Thomas E Yankeelov
Journal:  Pharmaceutics       Date:  2012       Impact factor: 6.321

9.  Radiomics-guided therapy for bladder cancer: Using an optimal biomarker approach to determine extent of bladder cancer invasion from t2-weighted magnetic resonance images.

Authors:  Yubing Tong; Jayaram K Udupa; Chuang Wang; Jerry Chen; Sriram Venigalla; Thomas J Guzzo; Ronac Mamtani; Brian C Baumann; John P Christodouleas; Drew A Torigian
Journal:  Adv Radiat Oncol       Date:  2018-05-08
  9 in total

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