Initial validation of equilibrium contrast imaging for extracellular volume quantification using a three‐dimensional engineered tissue model. Issue 5 (19th October 2015)

• Record Type: Journal Article
• Authors: Bandula, Steve; Magdeldin, Tarig; Stevens, Nicola; Yeung, Jason; Moon, James C.; Taylor, Stuart A.; Cheema, Umber; Punwani, Shonit
• Is Part Of: Journal of magnetic resonance imaging. Volume 43:Issue 5(2016)
• Page Start: 1224
• Page End: 1229
• Publication Date: 2015-10-19
• Subjects: magnetic resonance imaging -- contrast agents -- biological model -- fibrosis; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.25066
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: To test the principles underpinning equilibrium contrast imaging estimation of tissue extracellular volume (ECV) fraction, using a three‐dimensional (3D) engineered tissue model with known cellular and extracellular volumes. Methods: Six 3D tissue models (tumoroids) consisting of cell cultures within a collagen containing hydrogel were constructed after culture centrifugation and direct measurement of the cell component volume. Measured tumoroid ECV ranged from 0.89 to 1. ECV was calculated after measuring the T1 relaxation time at 3 Tesla using inversion recovery relaxometry (TI 100–1500 ms) within the tumoroids and surrounding medium before and 375 min after spiking the medium with Gadolinium (to achieve a concentration of 1.4 mM/L). Linear regression model prediction of directly measured ECV (ECVm ) by EQ‐MRI measured ECV (ECVeq ); and Bland‐Altman agreement between measures was assessed. Results: The fractional cellular volume measured by EQ‐MRI (ECVeq ) within the tumoroids ranged from 0.821 to 0.963. ECVeq was a good predictor of ECVm (R2 = 0.77, P = 0.02). The regression line Y‐axis intercept (when X = 0) was 0.045 ± 0.019 with a slope of 1.28 ± 0.35. Bland‐Altman comparison demonstrated 95% limits of agreement between ‐0.002 and 0.114 with a bias (SD) of 0.056 (0.03). Conclusion: This study supports the principles of ECV estimation using equilibrium contrast MRI, but future development of this model may allow validation over a wider, more physiological ECV range and a greater understanding of the effect of tissue extracellular protein burden on ECV. J. Magn. Reson. Imaging 2016;43:1224–1229.