UCLA

Dynamic contrast enhanced (DCE) MRI plays a central role in the diagnosis, characterization, and treatment monitoring of various diseases. It can provide essential functional information of the tissues, including the perfusion and permeability properties. Besides, the changes in functional properties is recognized to precede the morphological alterations, which can potentially provide an avenue for early diagnosis and treatment evaluation.

However, current practice of DCE MRI continues to face demanding technical challenges. First, there is direct conflict in the requirements for adequate anatomical coverage and high spatial and temporal resolution for tissues characterization. Existing techniques usually compromise one or more aspects, leading to suboptimal protocol. Second, dynamic T1 mapping for the quantification of CA concentration is hard to realize. Approximation in this step can introduce error in the derivation of DCE parameters. Third, imaging of some organs, such as heart or abdominal organs, is subject to artifacts caused by physiological motion, which can significantly degrade image quality or increase the scan time. Forth, the growing concern towards Gd deposition within body parts makes it controversial to use contrast agent.

The primary goal of the work in the dissertation is to address the aforementioned limitations by developing a novel quantitative DCE MRI technique using MR Multitasking framework to achieve: 1) motion-resolved imaging with free-breathing acquisition and bulk-motion correction, 2) high spatial-temporal resolution with 3D anatomical coverage for simultaneous perfusion and permeability quantification, 3) dynamic T1 mapping for accurate quantification of CA concentration and potentials for reducing GBCA dose. All the technical advancements aims to improve the detection, staging, characterization, and treatment monitoring for multiple organs and diseases. There are three specific aims to achieve the ultimate goal.

First, the Multitasking DCE technique was developed and tested in the study of carotid atherosclerosis. It enables 3D coverage of entire carotid vasculature with high spatial resolution (0.7 mm isotropic), high temporal resolution (600 ms), and dynamic T1 mapping for direct quantification of CA concentration. Bulk motion detection and removal scheme were also implemented for the improvement of image quality. In vivo studies have shown that the proposed technique can achieve accurate T1 quantification and robustness to motion. The PK parameters were repeatable in vivo and showed significant difference between carotid atherosclerosis and normal carotid vessel wall.

Second, 6-dimensional (6D) Multitasking DCE technique was developed for the characterization of PDAC. It achieves respiratory-motion-resolved, high-temporal-resolution T1 quantification of the entire abdomen in a 10-min free-breathing scan. Sixteen healthy volunteers and 14 patients with pathologically confirmed PDAC were recruited for the in vivo study. The results demonstrated that the quantitative PK parameters using Multitasking DCE were repeatable in vivo and showed significant differences between normal pancreas, tumor and non-tumoral regions in PDAC patients. In addition, 8 patients with confirmed CP were recruited. The PK parameters representing blood flow and vascular properties showed significant difference between normal pancreas, PDAC, and CP.

Third, the Multitasking DCE technique using a low dose at 0.02 mmol/kg (LD-MT-DCE) was developed for breast imaging. It produced co-registered high-spatial-resolution (0.9 mm � 0.9 mm � 1.14 mm) dynamic T1 maps at 1.4-second temporal resolution with whole-breast coverage in the 10-min scan. The dose was chosen to be 0.02 mmol/kg, 20% of the standard dose, based on a numerical simulation conducted to evaluate the dose effect on the accuracy and precision of the PK parameters quantified using LD-MT-DCE. Twenty healthy volunteers and 7 patients with breast cancer were recruited for the in vivo study. The results demonstrated that LD-MT-DCE were repeatable, showed excellent image quality and equivalent diagnosis compared with standard-dose clinical DCE. The estimated PK parameters were capable of differentiating between normal breast tissue, and benign and malignant tumors.