Phantom validation of quantitative susceptibility and dynamic contrast‐enhanced permeability MR sequences across instruments and sites. Issue 4 (12th September 2019)

• Record Type: Journal Article
• Authors: Hobson, Nicholas; Polster, Sean P.; Cao, Ying; Flemming, Kelly; Shu, Yunhong; Huston, John; Gerrard, Chandra Y.; Selwyn, Reed; Mabray, Marc; Zafar, Atif; Girard, Romuald; Carrión‐Penagos, Julián; Chen, Yu Fen; Parrish, Todd; Zhou, Xiaohong Joe; Koenig, James I.; Shenkar, Robert; Stadnik, Agnieszka; Koskimäki, Janne; Dimov, Alexey; Turley, Dallas; Carroll, Timothy; Awad, Issam A.
• Is Part Of: Journal of magnetic resonance imaging. Volume 51:Issue 4(2020)
• Page Start: 1192
• Page End: 1199
• Publication Date: 2019-09-12
• Subjects: cavernous angioma -- cavernous malformation -- cavernoma -- MRI -- clinical trial -- dynamic contrast‐enhanced quantitative permeability (DCEQP) -- quantitative susceptibility mapping (QSM) -- phantom validation; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.26927
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: Quantitative susceptibility mapping (QSM) and dynamic contrast‐enhanced quantitative permeability (DCEQP) on magnetic resonance (MR) have been shown to correlate with neurovascular disease progression as markers of vascular leakage and hemosiderin deposition. Applying these techniques as monitoring biomarkers in clinical trials will be necessary; however, their validation across multiple MR platforms and institutions has not been rigorously verified. Purpose: To validate quantitative measurement of MR biomarkers on multiple instruments at different institutions. Study Type: Phantom validation between platforms and institutions. Phantom Model: T1 /susceptibility phantom, two‐compartment dynamic flow phantom. Field Strength/Sequence: 3T/QSM, T1 mapping, dynamic 2D SPGR. Assessment: Philips Ingenia, Siemens Prisma, and Siemens Skyra at three different institutions were assessed. A QSM phantom with concentrations of gadolinium, corresponding to magnetic susceptibilities of 0, 0.1, 0.2, 0.4, and 0.8 ppm was assayed. DCEQP was assessed by measuring a MultiHance bolus as the consistency of the width ratio of the curves at the input and outputs over a range of flow ratios between outputs. Statistical Tests: Each biomarker was assessed by measures of accuracy (Pearson correlation), precision (paired t ‐test between repeated measurements), and reproducibility (analysis of covariance [ANCOVA] between instruments). Results: QSM accuracy of r 2 > 0.997 on all three platforms was measured. Precision ( P = 0.66 Achieva, P = 0.76 Prisma, P = 0.69 Skyra) and reproducibility ( P = 0.89) were good. T1 mapping of accuracy was r 2 > 0.98. No significant difference between width ratio regression slopes at site 2 ( P = 0.669) or site 3 ( P = 0.305), and no significant difference between width ratio regression slopes between sites was detected by ANCOVA ( P = 0.48). Data Conclusion: The phantom performed as expected and determined that MR measures of QSM and DCEQP are accurate and consistent across repeated measurements and between platforms. Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1192–1199.