PURPOSE: To test the reproducibility of model-derived quantitative and semiquantitative pharmacokinetic parameters among various commercially available perfusion analysis solutions for dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging. MATERIALS AND METHODS: The study was institutional review board approved and HIPAA compliant, with waiver of informed consent granted. The study group consisted of 15 patients (mean age, 44 years; range, 28-60 years), with 15 consecutive 1.5-T DCE MR imaging studies performed between October 1, 2010, and December 27, 2010, prior to uterine fibroid embolization. Studies were conducted by using variable-flip-angle T1 mapping and four-dimensional, time-resolved MR angiography with interleaved stochastic trajectories. Images from all DCE MR imaging studies were postprocessed with four commercially available perfusion analysis solutions by using a Tofts and Kermode model paradigm. Five observers measured pharmacokinetic parameters (volume transfer constant [K(trans)], v(e) [extracellular extravascular volume fraction], k(ep)[K(trans)/v(e)], and initial area under the gadolinium curve [iAUGC]) three times for each imaging study with each perfusion analysis solution (between March 13, 2011, and September 8, 2011) by using two different region-of-interest methods, resulting in 1800 data points. RESULTS: After normalization of data output, significant differences in mean values were found for the majority of perfusion analysis solution combinations. The within-subject coefficient of variation among perfusion analysis solutions was 48.3%-68.8% for K(trans), 37.2%-60.3% for k(ep), 27.7%-74.1% for v(e), and 25.1%-61.2% for iAUGC. The intraclass correlation coefficient revealed only poor to moderate consistency among pairwise perfusion analysis solution comparisons (K(trans), 0.33-0.65; k(ep), 0.02-0.81; v(e), -0.03 to 0.72; and iAUGC, 0.47-0.78). CONCLUSION: A considerable variability for DCE MR imaging pharmacokinetic parameters (K(trans), k(ep), v(e), iAUGC) was found among commercially available perfusion analysis solutions. Therefore, clinical comparability across perfusion analysis solutions is currently not warranted. Agreement on a postprocessing standard is paramount prior to establishing DCE MR imaging as a widely incorporated biomarker.
RCT Entities:
PURPOSE: To test the reproducibility of model-derived quantitative and semiquantitative pharmacokinetic parameters among various commercially available perfusion analysis solutions for dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging. MATERIALS AND METHODS: The study was institutional review board approved and HIPAA compliant, with waiver of informed consent granted. The study group consisted of 15 patients (mean age, 44 years; range, 28-60 years), with 15 consecutive 1.5-T DCE MR imaging studies performed between October 1, 2010, and December 27, 2010, prior to uterine fibroid embolization. Studies were conducted by using variable-flip-angle T1 mapping and four-dimensional, time-resolved MR angiography with interleaved stochastic trajectories. Images from all DCE MR imaging studies were postprocessed with four commercially available perfusion analysis solutions by using a Tofts and Kermode model paradigm. Five observers measured pharmacokinetic parameters (volume transfer constant [K(trans)], v(e) [extracellular extravascular volume fraction], k(ep)[K(trans)/v(e)], and initial area under the gadolinium curve [iAUGC]) three times for each imaging study with each perfusion analysis solution (between March 13, 2011, and September 8, 2011) by using two different region-of-interest methods, resulting in 1800 data points. RESULTS: After normalization of data output, significant differences in mean values were found for the majority of perfusion analysis solution combinations. The within-subject coefficient of variation among perfusion analysis solutions was 48.3%-68.8% for K(trans), 37.2%-60.3% for k(ep), 27.7%-74.1% for v(e), and 25.1%-61.2% for iAUGC. The intraclass correlation coefficient revealed only poor to moderate consistency among pairwise perfusion analysis solution comparisons (K(trans), 0.33-0.65; k(ep), 0.02-0.81; v(e), -0.03 to 0.72; and iAUGC, 0.47-0.78). CONCLUSION: A considerable variability for DCE MR imaging pharmacokinetic parameters (K(trans), k(ep), v(e), iAUGC) was found among commercially available perfusion analysis solutions. Therefore, clinical comparability across perfusion analysis solutions is currently not warranted. Agreement on a postprocessing standard is paramount prior to establishing DCE MR imaging as a widely incorporated biomarker.
Authors: Wei Huang; Xin Li; Yiyi Chen; Xia Li; Ming-Ching Chang; Matthew J Oborski; Dariya I Malyarenko; Mark Muzi; Guido H Jajamovich; Andriy Fedorov; Alina Tudorica; Sandeep N Gupta; Charles M Laymon; Kenneth I Marro; Hadrien A Dyvorne; James V Miller; Daniel P Barbodiak; Thomas L Chenevert; Thomas E Yankeelov; James M Mountz; Paul E Kinahan; Ron Kikinis; Bachir Taouli; Fiona Fennessy; Jayashree Kalpathy-Cramer Journal: Transl Oncol Date: 2014-02-01 Impact factor: 4.243
Authors: Soudabeh Kargar; Eric A Borisch; Adam T Froemming; Akira Kawashima; Lance A Mynderse; Eric G Stinson; Joshua D Trzasko; Stephen J Riederer Journal: Magn Reson Imaging Date: 2017-12-24 Impact factor: 2.546
Authors: Alireza Mehrtash; Sandeep N Gupta; Dattesh Shanbhag; James V Miller; Tina Kapur; Fiona M Fennessy; Ron Kikinis; Andriy Fedorov Journal: J Med Imaging (Bellingham) Date: 2016-03-01
Authors: Fiona M Fennessy; Andriy Fedorov; Tobias Penzkofer; Kyung Won Kim; Michelle S Hirsch; Mark G Vangel; Paul Masry; Trevor A Flood; Ming-Ching Chang; Clare M Tempany; Robert V Mulkern; Sandeep N Gupta Journal: Magn Reson Imaging Date: 2015-02-14 Impact factor: 2.546