4.5 Article

Toward a noninvasive estimate of interstitial fluid pressure by dynamic contrast-enhanced MRI in a rat model of cerebral tumor

期刊

MAGNETIC RESONANCE IN MEDICINE
卷 80, 期 5, 页码 2040-2052

出版社

WILEY
DOI: 10.1002/mrm.27163

关键词

Darcy's law; DCE-MRI; dynamic contrast-enhanced MRI; glioma; tissue hydraulic conductivity; tumor interstitial fluid pressure

资金

  1. National Cancer Institute of the National Institutes of Health, MRI Biomarkers of Response in Cerebral Tumor [R01 CA135329]
  2. NATIONAL CANCER INSTITUTE [R01CA135329] Funding Source: NIH RePORTER

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Purpose: This study demonstrates a DCE-MRI estimate of tumor interstitial fluid pressure (TIFP) and hydraulic conductivity in a rat model of glioblastoma, with validation against an invasive wick-in-needle (WIN) technique. An elevated TIFP is considered a mark of aggressiveness, and a decreased TIFP a predictor of response to therapy. Methods: The DCE-MRI studies were conducted in 36 athymic rats (controls and posttreatment animals) with implanted U251 cerebral tumors, and with TIFP measured using a WIN method. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the MRI parameters required for estimating TIFP noninvasively were estimated. Two models, a fluid-mechanical model and a multivariate empirical model, were used for estimating TIFP, as verified against WIN-TIFP. Results: Using DCE-MRI, the mean estimated hydraulic conductivity (MRI-K) in U251 tumors was (2.3 +/- 3.1) x 10(-5) (mm(2)/mmHg-s) in control studies. Significant positive correlations were found between WIN-TIFP and MRI-TIFP in both mechanical and empirical models. For instance, in the control group of the fluid-mechanical model, MRI-TIFP was a strong predictor of WIN-TIFP (R-2 = 0.76, p < .0001). A similar result was found in the bevacizumab-treated group of the empirical model (R-2 = 0.93, p = .014). Conclusion: This research suggests that MRI dynamic studies contain enough information to noninvasively estimate TIFP in this, and possibly other, tumor models, and thus might be used to assess tumor aggressiveness and response to therapy.

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