AbstractLiver is commonly involved in metastatic disease in colorectal cancer (CRC) and knowledge aboutthe presence and location of these tumors affects treatment decisions. In patients with CRCsurgical or ablative treatment of liver metastases improves overall survival. Early diagnosis ofcolorectal metastases (i.e. while lesions are small) is expected to improve treatment outcomes byincreasing the number of subjects that can undergo surgical resection or by identifying subjectsearly on when non-surgical options are an alternative treatment. Magnetic Resonance Imaging(MRI) is regarded as the most effective imaging modality for the detection and characterization ofliver neoplasms; T2-weighted (T2w) and T1-weighted (T1w) images - combined withadministration of a gadolinium chelate agent and multi-phase dynamic contrast enhancement(DCE) - are the foundational acquisitions used for the detection and characterization of livertumors. However challenges remain for the detection and characterization of small lesions dueto factors including inadequate spatial resolution partial volume effects physiological motion andvariations in timing of contrast arrival in DCE imaging. In this academic-industrial partnership thescientific and engineering teams at the University of Arizona and Siemens Medical Solutions arecoming together to develop robust radial MRI techniques for T2w/T2 mapping and DCE imagingof the liver to improve detection and characterization of small tumors with the goal of bringingthese techniques to routine clinical practice. The proposed work is based on a radial turbo spin-echo technique pioneered by the team at the University of Arizona for abdominal imaging and aradial stack-of-stars technique with continuous acquisition for DCE imaging. The specific aims ofthe partnership are: Aim 1: To develop radial T2w acquisition and reconstruction techniques withefficient full coverage of the liver for small tumor detection and accurate T2 quantification for tumorcharacterization. Aim 2: To implement a self-navigated 3D radial stack-of-stars technique forcontinuous acquisition of DCE data and retrospective reconstruction of the dynamic phases. Aim3: To conduct a clinical evaluation of the techniques from Aims 1 and 2 against conventional T2wand DCE techniques. Aim 4: To streamline translation of the new radial methods to the clinic bydeveloping a computationally efficient reconstruction pipeline. The endpoints of our study includetechnical advances in MRI acquisitions that markedly overcome limitations of current liver MRI forthe diagnosis of early metastases. We expect our proposal to yield technology improvementsthat will increase precision of care and outcomes in patients with metastatic malignancies inparticular those with colorectal cancer.