Poroelastic mechanical properties of brain tumors using intrinsic actuation MR elastography
Ligin Solamen1, Matthew McGarry1, Elijah Van Houten2, Jennifer Hong3, John Weaver1,4, and Keith Paulsen1,5

1Thayer School of Engineering, Dartmouth College, Hanover, NH, United States, 2Department of Mechanical Engineering, University of Sherbrooke, Sherbrooke, QC, Canada, 3Department of Neurosurgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States, 4Department of Radioogy, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States, 5Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States


Intrinsically actuated poroelastic MR elastography (IA-pMRE) is a technique which estimates tissue mechanical and hydrodynamic properties using measurements of displacement during the cardiac cycle, and does not require external vibration as in traditional MRE. Compared to conventional MRE, which obtains displacements in the range of 25-100Hz, IA-pMRE uses intrinsically generated low frequency (1-2Hz) displacements for elastography reconstruction. IA-pMRE was applied to 7 brain tumor patients and showed a significant difference in both the shear modulus and hydraulic conductivity of brain tissue compared to healthy tissue.


Non-invasive differentiation of brain tumors is not always definitive, and more accurate imaging assessments could inform patient management decisions. Externally actuated MRE has shown promise in biomechanical characterization of intracranial tumors.[1] Here, we present initial data on mechanical and hydrodynamical signatures of 7 patients (2 metastatic tumors, 1 meningioma, 4 glioblastoma) using low frequency IA-pMRE.


Intrinsic actuation MRE generates brain tissue displacement maps from the natural cerebrovascular pulsations arising from pressure variations during the cardiac cycle. [2] A retrospectively gated phase contrast angiography sequence is used to acquire 8 displacement images across one cardiac cycle followed by a Fourier transform to extract motion at the cardiac frequency. Harmonic equations of motion and a nonlinear inversion algorithm, which assumes a poroelastic mechanical model, is used to recover the shear modulus (stiffness) and hydraulic conductivity (ease of fluid flow) of brain tissue.[3] Seven patients diagnosed with various types of brain tumors were enrolled and compared to healthy controls with no known neurological conditions. Tumor regions were segmented and compared to the background brain tissue.

Results and Conclusions

Regions identified as tumor consistently had higher shear modulus values than the surrounding healthy tissue. IA-pMRE is a promising technique that enables study of neurological diseases without requiring externally applied vibration traditionally used during MRE exams and can be introduced as part of standard MRI protocols. Contrast between tumor and healthy brain tissue exists, however, stiffness does not appear to differentiate tumor types (similarly to findings from externally actuated MRE studies). [1] Future work will increase the number of patients enrolled in the study and analyze other properties, for example, the hydraulic conductivity, to provide more information on the mechanical environment. [4]


I would like to thank my mentors as well as our collaborators at Dartmouth-Hitchcock Medical Center and at the University of Sherbrooke.


[1] Simon M., et al. "Non-invasive characterization of intracranial tumors by magnetic resonance elastography" New Journal of Physics. 15 (2013). [2] Weaver, John B., et al. "Brain mechanical property measurement using MRE with intrinsic activation." Physics in Medicine and Biology 57.22 (2012): 7275. [3] Perriñez, P., et al. “Contrast detection in fluid-saturated media with magnetic resonance poroelastography.” Medical Physics 37 (2010). [4] Pattison, A. et al. “Spatially-Resolved Hydraulic Conductivity Estimation Via Poroelastic Magnetic Resonance Elastography” IEEE Transcations on Medical Imaging 33 (2014).


Figure 1: Cross sectional slices of patient with metastatic cancer originating from the lung. Clinical MRI T2 weighted image (left) and poroelastic shear modulus map (right).

Figure 2: Stiffness of segmented tumor (red) compared to the rest of the healthy tissue (blue) for the various types of tumors. Black horizontal line is the average poroelastic shear modulus of 7 healthy individuals.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)