Our research group has an interest in interrogating the microenvironment of tumor and tissue.
In doing so, we also study the delivery of tracer and drugs by PET or MRI.
Our group has invented a distributed parameter (DP) model for tracer kinetic modeling of DCE MRI  
This model allows separate determination of blood flow and capillary permeability-surface area product.
Flow calculated by the DP model has been validated by water PET. 
The DP model was able to predict patient outcome in a cohort of colorectal primary but not the Generalized Kinetic model (ktrans, ve) nor the adiabetic tissue homogeneity model (St Lawrence and Lee). 
The DP model is also able to predict patient outcome in a Phase II trial of Pazopanib (multiple tyrosine kinase inhibitor, antiangiogenic) and Nasopharyngeal carcinoma. 
Our group used the DP model together with a dual arterial input function (hepatic artery and portal vein) to better study focal liver lesions. 
Studying human neuroendocrine liver metastases, we found that a wash-in wash-out pattern is explained by high intravascular space and low interstitial space;
whereas a progressively enhancing pattern is explained by low intravascular space and high interstitial space. 
We are able to separately calculate the % contribution of splenic flow and splanchnic flow to total portal blood flow by deconvolution. 
Studying SCID mice with human tumor xenografts, we found tracer kinetics in the “non-enhancing” center has no convective transport described by traditional DCE MRI modeling.
The transport process is predominantly related to diffusion. We describe this by measuring the diffusivity of gadolinium in DCE MRI studies. 
We postulate that this is related to high interstitial fluid pressure in the tumor core and show a relationship between low gadolinium diffusion and the presence of necrosis. 
We have publications in Independent Component Analysis, IVIM, and are interested in studying the relationship of the liver interstitial space with liver fibrosis and cirrhosis.
We are currently working on using tracer kinetic modeling to study renal fibrosis and to estimate GFR in animals.
We are currently working on modeling dynamic PET to yield binding affinity and volume of distribution.
We have worked with Roche Translational Medicine Hub and were supported by NMRC Industry Alignment Fund Category 1.
Group Members :
A/Prof Choon Hua Thng
A/Prof Tong San Koh
Dr Quan Sing Ng
Puor Sherng Lee
Selected Publications :
 IEEE Trans Biomed Eng. 2003 Feb;50(2):159-67
 Neuroimage. 2006 Apr 1;30(2):426-35
 Radiology 2013;267(1):145–154.
 Clin Cancer Res. 2011 Aug 15;17(16):5481-9
 J Cereb Blood Flow Metab. 2008 Feb;28(2):402-11
 Radiology. 2008 Oct;249(1):307-20
 Magn Reson Med. 2011 Jan;65(1):250-60
 Magn Reson Med. 2013 Jan;69(1):269-76
 NMR Biomed. 2014 Apr;27(4):486-94
 Med Phys. 2011 May;38(5):2768-82
Automatic region-of-interest segmentation and registration of dynamic contrast-enhanced images of colorectal tumors.
Phys Med Biol (2014) 59(23) 7361-7381
Correlative assessment of tumor microcirculation using contrast-enhanced perfusion MRI and intravoxel incoherent motion diffusion-weighted MRI: Is there a link between them?
NMR in Biomedicine (2014) 27(10) 1184-1191
Optimum slicing of radical prostatectomy specimens for correlation between histopathology and medical images
International Journal of Computer Assisted Radiology and Surgery (2010) 5(5) 471-487
Dynamic contrast-enhanced CT imaging of hepatocellular carcinoma in cirrhosis: Feasibility of a prolonged dual-phase imaging protocol with tracer kinetics modeling
European Radiology (2009) 19(5) 1184-1196
Tracer kinetics analysis of dynamic contrast-enhanced CT and MR data in patients with squamous cell carcinoma of the upper aerodigestive tract: Comparison of the results
Clinical Physiology and Functional Imaging (2009) 29(5) 339-346