Department of Radiology and Biomedical Imaging, University of California in San Francisco, San Francisco, USA.
Department of Mathematics and Statistics, University of San Francisco, San Francisco, USA.
MAGMA. 2021 Feb;34(1):57-72. doi: 10.1007/s10334-020-00903-y. Epub 2021 Jan 27.
Magnetic resonance imaging with hyperpolarized contrast agents can provide unprecedented in vivo measurements of metabolism, but yields images that are lower resolution than that achieved with proton anatomical imaging. In order to spatially localize the metabolic activity, the metabolic image must be interpolated to the size of the proton image. The most common methods for choosing the unknown values rely exclusively on values of the original uninterpolated image.
In this work, we present an alternative method that uses the higher-resolution proton image to provide additional spatial structure. The interpolated image is the result of a convex optimization algorithm which is solved with the fast iterative shrinkage threshold algorithm (FISTA).
Results are shown with images of hyperpolarized pyruvate, lactate, and bicarbonate using data of the heart and brain from healthy human volunteers, a healthy porcine heart, and a human with prostate cancer.
利用超极化对比剂进行磁共振成像是提供代谢物的体内测量的一种前所未有的方法，但所得到的代谢物图像的分辨率低于质子解剖成像。为了对代谢活性进行空间定位，代谢物图像必须内插到质子图像的大小。选择未知值的最常见方法完全依赖于原始未内插图像的值。
在这项工作中，我们提出了一种替代方法，该方法使用更高分辨率的质子图像提供附加的空间结构。内插图像是凸优化算法的结果，该算法使用快速迭代收缩阈值算法（FISTA）求解。
使用健康人类志愿者、健康猪心和前列腺癌患者的心脏和大脑的数据，展示了超极化丙酮酸、乳酸盐和碳酸氢盐的图像结果。
