Literature DB >> 20093564

Reproducibility of perfusion parameters in dynamic contrast-enhanced MRI of lung and liver tumors: effect on estimates of patient sample size in clinical trials and on individual patient responses.

Chaan S Ng1, David L Raunig, Edward F Jackson, Edward A Ashton, Frederick Kelcz, Kevin B Kim, Razelle Kurzrock, Teresa M McShane.   

Abstract

OBJECTIVE: Dynamic contrast-enhanced MRI (DCE-MRI) is a potentially useful noninvasive technique for assessing tissue perfusion, particularly in the context of solid tumors and targeted antiangiogenic and antivascular therapies. Our aim was to determine the reproducibility of perfusion parameters derived at DCE-MRI of tumors of the lung and liver, the most common sites of metastasis. SUBJECTS AND METHODS: Patients with lung and liver tumors underwent two sequential DCE-MRI examinations 2-7 days apart without any intervening therapy. The volume transfer constant between blood plasma and the extravascular extracellular space (K(trans)) and blood-normalized initial area under the signal intensity-time curve (initial AUC(BN)) were computed with a two-compartment pharmacokinetic model. Differences in parameters were assessed with within-patient coefficients of variation.
RESULTS: Twenty-three patients had evaluable tumors (12 lung, 11 liver). The within-patient coefficients of variation for K(trans) and initial AUC(BN) for liver lesions were 8.9% and 9.9% and for lung lesions were 17.9% and 18.2%. Sample sizes for reductions in these parameters from 10% to 50% were estimated to range from two to 102 subjects. Estimates of confidence that changes observed in a given patient were due to intervening therapy rather than variability of the technique were calculated to range from 71% to 87% if a 20% reduction in a parameter was observed.
CONCLUSION: The rate of reproducibility of DCE-MRI parameters is in the range of 10%-20% and is influenced by lesion location, parameters being significantly more reproducible in the liver than in the lung. These findings provide the foundation for interpretation of results and design of clinical trials in which DCE-MRI studies are used to assess objective responses.

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Year:  2010        PMID: 20093564     DOI: 10.2214/AJR.09.3116

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  27 in total

1.  Phase 1 dose-escalation study of the antiplacental growth factor monoclonal antibody RO5323441 combined with bevacizumab in patients with recurrent glioblastoma.

Authors:  Ulrik Lassen; Olivier L Chinot; Catherine McBain; Morten Mau-Sørensen; Vibeke Andrée Larsen; Maryline Barrie; Patrick Roth; Oliver Krieter; Ka Wang; Kai Habben; Jean Tessier; Angelika Lahr; Michael Weller
Journal:  Neuro Oncol       Date:  2015-02-09       Impact factor: 12.300

2.  Estimation of intra-operator variability in perfusion parameter measurements using DCE-US.

Authors:  Marianne Gauthier; Ingrid Leguerney; Jessie Thalmensi; Mohamed Chebil; Sarah Parisot; Pierre Peronneau; Alain Roche; Nathalie Lassau
Journal:  World J Radiol       Date:  2011-03-28

3.  Impact of the arterial input function on microvascularization parameter measurements using dynamic contrast-enhanced ultrasonography.

Authors:  Marianne Gauthier; Stéphanie Pitre-Champagnat; Farid Tabarout; Ingrid Leguerney; Mélanie Polrot; Nathalie Lassau
Journal:  World J Radiol       Date:  2012-07-28

Review 4.  Vessel caliber--a potential MRI biomarker of tumour response in clinical trials.

Authors:  Kyrre E Emblem; Christian T Farrar; Elizabeth R Gerstner; Tracy T Batchelor; Ronald J H Borra; Bruce R Rosen; A Gregory Sorensen; Rakesh K Jain
Journal:  Nat Rev Clin Oncol       Date:  2014-08-12       Impact factor: 66.675

5.  DCE-MRI of the liver: effect of linear and nonlinear conversions on hepatic perfusion quantification and reproducibility.

Authors:  Shimon Aronhime; Claudia Calcagno; Guido H Jajamovich; Hadrien Arezki Dyvorne; Philip Robson; Douglas Dieterich; M Isabel Fiel; Valérie Martel-Laferriere; Manjil Chatterji; Henry Rusinek; Bachir Taouli
Journal:  J Magn Reson Imaging       Date:  2013-11-04       Impact factor: 4.813

Review 6.  The role of magnetic resonance imaging biomarkers in clinical trials of treatment response in cancer.

Authors:  Thomas E Yankeelov; Lori R Arlinghaus; Xia Li; John C Gore
Journal:  Semin Oncol       Date:  2011-02       Impact factor: 4.929

Review 7.  Gastroenteropancreatic neuroendocrine tumors: new insights in the diagnosis and therapy.

Authors:  Krystallenia I Alexandraki; Gregory Kaltsas
Journal:  Endocrine       Date:  2011-11-29       Impact factor: 3.633

8.  Metabolic Heterogeneity in Human Lung Tumors.

Authors:  Christopher T Hensley; Brandon Faubert; Qing Yuan; Naama Lev-Cohain; Eunsook Jin; Jiyeon Kim; Lei Jiang; Bookyung Ko; Rachael Skelton; Laurin Loudat; Michelle Wodzak; Claire Klimko; Elizabeth McMillan; Yasmeen Butt; Min Ni; Dwight Oliver; Jose Torrealba; Craig R Malloy; Kemp Kernstine; Robert E Lenkinski; Ralph J DeBerardinis
Journal:  Cell       Date:  2016-02-04       Impact factor: 41.582

Review 9.  Imaging in clinical trials.

Authors:  P Murphy; D-M Koh
Journal:  Cancer Imaging       Date:  2010-10-04       Impact factor: 3.909

Review 10.  CT perfusion of the liver: principles and applications in oncology.

Authors:  Se Hyung Kim; Aya Kamaya; Jürgen K Willmann
Journal:  Radiology       Date:  2014-08       Impact factor: 11.105

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