The incidence of hepatocellular carcinoma (HCC) has recently increased in the United States. HCC is/will be the source of enormous health care costs and morbidity/mortality, and generally develops in patients with advanced liver damage (advanced fibrosis and cirrhosis). Although imaging plays a major role in HCC screening and staging, the possibility of predicting HCC tumor grade, aggressiveness, angiogenesis and hypoxia with imaging are unmet needs. In addition, new antiangiogenic drugs now available to treat advanced HCC necessitate the use of new imaging criteria beyond size. In this proposal, we would like to test and validate non invasive magnet resonance imaging (MRI) methods based on advanced diffusion-weighted imaging (intravoxel incoherent motion diffusion MRI: IVIM DWI), BOLD (blood oxygen level dependent) MRI and perfusion-weighted imaging (PWI, using gadolinium contrast) to be used as non invasive markers of major histopathologic features of HCC (grade, aggressiveness, angiogenesis and hypoxia), and to predict and assess early response of HCC to systemic therapy with sorafenib (systemic drug approved for use in advanced HCC). We also would like to develop quality control tools to improve the quality and decrease variability of these quantitative MRI metrics. Based on our recent preliminary data, we believe that DWI has potential for predicting HCC tumor grade, and HCC response to locoregional therapy;and that BOLD MRI and PWI can be used to quantify degree of vascularity and lack of oxygen supply (hypoxia) in HCC, which are important tumor markers, and could be used as early markers of response to sorafenib. Ultimately, we are hoping to validate a novel non invasive algorithm based on multiparametric MRI to predict response of HCC to sorafenib, and to predict prognosis. These methods could become useful tools for testing new antiangiogenic drugs and experimental therapies in HCC, will enable individualized therapy, and provide prognosis in patients with HCC. This will be a highly significant progress in HCC and liver diseases given the increased burden of HCC in this country, and would benefit a large number of Americans over the next decade.
The incidence of hepatocellular carcinoma (HCC) has recently increased in the United States. In this proposal, we would like to develop and validate quantitative MRI methods as markers of histopathologic features of HCC, and to predict and assess early response of HCC to systemic therapy with sorafenib. These techniques combined could represent non-invasive markers of histologic findings in HCC, could enable individualized therapy, and provide prognosis in patients with HCC.
|Kennedy, Paul; Wagner, Mathilde; Castéra, Laurent et al. (2018) Quantitative Elastography Methods in Liver Disease: Current Evidence and Future Directions. Radiology 286:738-763|
|Hectors, Stefanie J; Wagner, Mathilde; Besa, Cecilia et al. (2018) Multiparametric FDG-PET/MRI of Hepatocellular Carcinoma: Initial Experience. Contrast Media Mol Imaging 2018:5638283|
|Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura et al. (2018) Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies. J Med Imaging (Bellingham) 5:011006|
|Bane, Octavia; Hectors, Stefanie J; Wagner, Mathilde et al. (2018) Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study. Magn Reson Med 79:2564-2575|
|Newitt, David C; Malyarenko, Dariya; Chenevert, Thomas L et al. (2018) Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network. J Med Imaging (Bellingham) 5:011003|
|Hectors, Stefanie J; Wagner, Mathilde; Bane, Octavia et al. (2017) Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging. Sci Rep 7:2452|
|Taouli, Bachir; Hoshida, Yujin; Kakite, Suguru et al. (2017) Imaging-based surrogate markers of transcriptome subclasses and signatures in hepatocellular carcinoma: preliminary results. Eur Radiol 27:4472-4481|
|Malyarenko, Dariya I; Newitt, David; J Wilmes, Lisa et al. (2016) Demonstration of nonlinearity bias in the measurement of the apparent diffusion coefficient in multicenter trials. Magn Reson Med 75:1312-23|
|Malyarenko, Dariya I; Wilmes, Lisa J; Arlinghaus, Lori R et al. (2016) QIN DAWG Validation of Gradient Nonlinearity Bias Correction Workflow for Quantitative Diffusion-Weighted Imaging in Multicenter Trials. Tomography 2:396-405|
|Jajamovich, Guido H; Huang, Wei; Besa, Cecilia et al. (2016) DCE-MRI of hepatocellular carcinoma: perfusion quantification with Tofts model versus shutter-speed model--initial experience. MAGMA 29:49-58|
Showing the most recent 10 out of 16 publications