Approximately 7% of the 30.2 million MR exams performed in 2006 were abdominal MRIs, and the liver is by far the most common abdominal organ imaged using MR [1]. When successful, lesion characterization by MR is exquisite and elegant, and the definitive nature of the information can aid treatment follow-up, stop unnecessary workups and prevent invasive biopsies. All too often, however, liver MR is unsuccessful because of patient difficulties with breath-holds, problems with timing or acquisition in the critical (and non-repeatable) timed post-contrast series of images, operator dependence, image artifacts, or differences in levels of certainty in interpretation between various radiologists arising from inherently qualitative interpretations. Weighted images are at best surrogates of the underlying parameter and often poorly reflect the parameters [2]. Moreover, when quantitative information is available, it can outperform even expert readers of clinical contrasts [3]. If the liver examination could be performed quickly during free-breathing, without relying on operator expertise, and could provide quantitative parameters which can be used to definitively diagnose disease, the impact on the diagnosis and treatment of liver diseases would be significant. We propose to leverage rapid imaging, parameter quantitation, and body MRI expertise in our group to provide a rapid, quantitative, high quality 3D exam in under 10 minutes. A standard liver MR exam consists of multiple scans highlighting different contrast mechanisms: T2 weighted scans without and with fat saturation, T1-weighted in- and opposed-phase gradient echo, diffusion images, and T1-weighted fat saturated 3D gradient echo scans pre- and at least 3 timed phases post-contrast). We will develop, optimize and validate methods to generate quantitative measurements of each mechanism, by developing quantitative 3D high resolution DCE perfusion, fat fraction, T1 and T2 mapping, and improved 3D diffusion mapping. The diagnostic value of the new protocol will then be extensively tested on patients with biopsy proven pathologies, and will be compared to the present clinical standard.

Public Health Relevance

Despite exquisite soft tissue contrast and a massive impact on diagnosis, follow-up and treatment of liver lesions and disorders, liver MRI still has significat limitations due to complexity of scanning, inefficient image acquisition, qualitative rather than quantitative imaging, and complicated image interpretation. We propose to completely change liver MRI by providing free-breathing 3D high resolution perfusion, fat fraction, T1 and T2 mapping, and markedly improved, short breath-hold high resolution 3D diffusion mapping in which we overcome these limitations using the novel rapid image acquisition, reconstruction, registration, and analysis tools being developed by our team. The total time needed for this new exam will be less than 10 minutes. This exam will be extensively tested on patients after development to determine the clinical utility in comparison to the present clinical standard.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
Project #
Application #
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Sherker, Averell H
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Case Western Reserve University
Schools of Medicine
United States
Zip Code
Pahwa, Shivani; Liu, Hao; Chen, Yong et al. (2018) Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study. Sci Rep 8:4990
Lu, Cheng; Romo-Bucheli, David; Wang, Xiangxue et al. (2018) Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers. Lab Invest 98:1438-1448
Beig, Niha; Patel, Jay; Prasanna, Prateek et al. (2018) Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma. Sci Rep 8:7
Coristine, Andrew J; Chaptinel, Jerome; Ginami, Giulia et al. (2018) Improved respiratory self-navigation for 3D radial acquisitions through the use of a pencil-beam 2D-T2 -prep for free-breathing, whole-heart coronary MRA. Magn Reson Med 79:1293-1303
Yang, Mingrui; Ma, Dan; Jiang, Yun et al. (2018) Low rank approximation methods for MR fingerprinting with large scale dictionaries. Magn Reson Med 79:2392-2400
Obmann, Verena C; Pahwa, Shivani; Tabayayong, William et al. (2018) Diagnostic Accuracy of a Rapid Biparametric MRI Protocol for Detection of Histologically Proven Prostate Cancer. Urology 122:133-138
Chen, Yong; Lo, Wei-Ching; Hamilton, Jesse I et al. (2018) Single breath-hold 3D cardiac T1 mapping using through-time spiral GRAPPA. NMR Biomed 31:e3923
Peyster, Eliot G; Madabhushi, Anant; Margulies, Kenneth B (2018) Advanced Morphologic Analysis for Diagnosing Allograft Rejection: The Case of Cardiac Transplant Rejection. Transplantation 102:1230-1239
Ma, Dan; Jiang, Yun; Chen, Yong et al. (2018) Fast 3D magnetic resonance fingerprinting for a whole-brain coverage. Magn Reson Med 79:2190-2197
Whitney, Jon; Corredor, German; Janowczyk, Andrew et al. (2018) Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer. BMC Cancer 18:610

Showing the most recent 10 out of 80 publications