Glaser, Kevin J.

PurposeTo provide a fully automated algorithm for obtaining stiffness measurements from hepatic magnetic resonance elastography (MRE) images that are consistent with measurements performed by expert readers.Materials and MethodsAn initial liver contour was found using an adaptive threshold and expanded using an active contour to select a homogeneous area of the liver. The confidence map generated during the stiffness calculation was used to select a region of reliable wave propagation. The average stiffness within the automatically generated region of interest (ROI) was compared to measurements by two trained readers in a set of 88 clinical test cases ranging from healthy to severely fibrotic.ResultsThe stiffness measurements reported by the readers differed by −6.76% ± 22.8% (95% confidence) and had an intraclass correlation coefficient (ICC) of 0.972 (P < 0.05). The algorithm and the more experienced reader differed by 4.32% ± 14.9 with an ICC of 0.987.ConclusionThe automated algorithm performed reliably, even though MRE acquisitions often have motion artifacts present. The correlation between the automated measurements and those from the trained readers was superior to the correlation between the readers. J. Magn. Reson. Imaging 2013;38:371–379. © 2013 Wiley Periodicals, Inc.

Object The object of this study was to determine the potential of magnetic resonance elastography (MRE) to preoperatively assess the stiffness of meningiomas. Methods Thirteen patients with meningiomas underwent 3D brain MRE examination to measure stiffness in the tumor as well as in surrounding brain tissue. Blinded to the MRE results, neurosurgeons made a qualitative assessment of tumor stiffness at the time of resection. The ability of MRE to predict the surgical assessment of stiffness was tested using a Spearman rank correlation. Results One case was excluded due to a small tumor size. In the remaining 12 cases, both tumor stiffness alone (p = 0.023) and the ratio of tumor stiffness to surrounding brain tissue stiffness (p = 0.0032) significantly correlated with the surgeons' qualitative assessment of tumor stiffness. Results of the MRE examination provided a stronger correlation with the surgical assessment of stiffness compared with traditional T1- and T2-weighted imaging (p = 0.089), particularly when considering meningiomas of intermediate stiffness. Conclusions In this cohort, preoperative MRE predicted tumor consistency at the time of surgery. Tumor stiffness as measured using MRE outperformed conventional MRI because tumor appearance on T1- and T2-weighted images could only accurately predict the softest and hardest meningiomas.

MRI guided focused ultrasound (FUS) has been shown to create thermal lesions where tissue stiffness changes significantly. To assess the correlation between tissue stiffness change and tissue ablation, a pilot animal based study was conducted to treat LNCaP tumors in vivo and Hep3B tumors immediately post mortem. MR elastography was used to analyze tissue stiffness before and after ablation. Treated tissue was excised immediately after each experiment and processed by routine histological analysis. Four prostate cancer tumors and four liver cancer tumors showed, on average, a threefold increase in stiffness due to FUS thermal treatment. Histology showed complete (100%) coagulation necrosis in these cases. These data suggest that MRE may be an effective means to assess tissue ablation.