OPTIMISATION OF CHEMICAL SHIFT IMAGING METHODS FOR ASSESSING LIPID METABOLISM IN LIVER CANCER

Chileka Chiyanika (chilekac@yahoo.co.uk)
Science, The University of Queensland
June, 2015
 

Abstract

Cancer is a leading cause of death worldwide accounting for 8.2 million deaths in 2012. Liver cancer is the second leading cause of cancer-related death per annum worldwide. The liver is a major organ involved in energy metabolism; it plays a critical role in the metabolism of lipids and lipoproteins by regulating their synthesis and degradation. The integrity of cellular function in the liver is crucial for the liver to perform its function properly. Under normal physiological conditions the liver ensures homeostasis of lipid metabolism. The presence of cancer cells in the liver leads to changes in different aspects of lipid metabolism. These changes affect numerous cellular processes including cell growth, proliferation, differentiation, and motility. The study of lipid metabolism can give insightful information about processes occurring at the cellular level. Chemical shift imaging (CSI) is a technique that can be used to study lipid metabolism, but is not without many challenges. The aim of this study was to optimize CSI methods in order to assess lipid metabolism in liver cancer. The use of CSI could significantly impact patient management by improving:
i. Tumour staging.
ii. Treatment planning.
iii. Monitoring non-invasively targeted therapies that inhibit specific oncogenes.
iv. Monitoring of tumour response to treatment.
We used phantoms to develop a CSI protocol; this protocol was then used for an in vivo assessment of lipid metabolism in liver cancer using Fischer 344 rats on CDAA diet. Chemical shift imaging was performed in vivo using Fischer 344 male rats aged 41 weeks. Two rats served as control and three rats were exposed to a choline l-amino acid deficiency diet (CDAA) delivered for 34 weeks. Optimization via shimming was conducted using a combination of MAPSHIM, ITERATIVE and VOXEL SPECIFIC shimming methods. Dixon method through the use of FLASH was used to obtain images. Liver fat fractions and fat only images were also obtained using MIPAV version 2.0 and ParaVision 5.1 software. Independent t-test was calculated for statistical significance of liver fat fractions and relative lipid peak intensities. Water line width measured at full width half maximum of 63.4Hz was achieved. CSI images and spectra showed increased lipid peak intensities in the treated group, P= 0.05, while fat fraction showed significant difference P< .01. These results show that optimization of CSI methods is practical and achievable in studying the liver. Thus, optimized CSI methods can be used to assess lipid metabolism in liver cancer and help diagnose cancer at an early stage before any gross damage has occurred. This would enable intervention methods to be initiated as early as possible.