Siyuan Dong, Annabella Shewarega, Julius Chapiro, Zhuotong Cai, Fahmeed Hyder, Daniel Coman, James S Duncan
{"title":"High-resolution extracellular pH imaging of liver cancer with multiparametric MR using Deep Image Prior.","authors":"Siyuan Dong, Annabella Shewarega, Julius Chapiro, Zhuotong Cai, Fahmeed Hyder, Daniel Coman, James S Duncan","doi":"10.1002/nbm.5145","DOIUrl":null,"url":null,"abstract":"<p><p>Noninvasive extracellular pH (pH<sub>e</sub>) mapping with Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) using MR spectroscopic imaging (MRSI) has been demonstrated on 3T clinical MR scanners at 8 <math><mo>×</mo> <mn>8</mn> <mo>×</mo> <mn>10</mn></math> mm<sup>3</sup> spatial resolution and applied to study various liver cancer treatments. Although pH<sub>e</sub> imaging at higher resolution can be achieved by extending the acquisition time, a postprocessing method to increase the resolution is preferable, to minimize the duration spent by the subject in the MR scanner. In this work, we propose to improve the spatial resolution of pH<sub>e</sub> mapping with BIRDS by incorporating anatomical information in the form of multiparametric MRI and using an unsupervised deep-learning technique, Deep Image Prior (DIP). Specifically, we used high-resolution <math><msub><mi>T</mi> <mn>1</mn></msub> </math> , <math><msub><mi>T</mi> <mn>2</mn></msub> </math> , and diffusion-weighted imaging (DWI) MR images of rabbits with VX2 liver tumors as inputs to a U-Net architecture to provide anatomical information. U-Net parameters were optimized to minimize the difference between the output super-resolution image and the experimentally acquired low-resolution pH<sub>e</sub> image using the mean-absolute error. In this way, the super-resolution pH<sub>e</sub> image would be consistent with both anatomical MR images and the low-resolution pH<sub>e</sub> measurement from the scanner. The method was developed based on data from 49 rabbits implanted with VX2 liver tumors. For evaluation, we also acquired high-resolution pH<sub>e</sub> images from two rabbits, which were used as ground truth. The results indicate a good match between the spatial characteristics of the super-resolution images and the high-resolution ground truth, supported by the low pixelwise absolute error.</p>","PeriodicalId":19309,"journal":{"name":"NMR in Biomedicine","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NMR in Biomedicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/nbm.5145","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/15 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Noninvasive extracellular pH (pHe) mapping with Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) using MR spectroscopic imaging (MRSI) has been demonstrated on 3T clinical MR scanners at 8 mm3 spatial resolution and applied to study various liver cancer treatments. Although pHe imaging at higher resolution can be achieved by extending the acquisition time, a postprocessing method to increase the resolution is preferable, to minimize the duration spent by the subject in the MR scanner. In this work, we propose to improve the spatial resolution of pHe mapping with BIRDS by incorporating anatomical information in the form of multiparametric MRI and using an unsupervised deep-learning technique, Deep Image Prior (DIP). Specifically, we used high-resolution , , and diffusion-weighted imaging (DWI) MR images of rabbits with VX2 liver tumors as inputs to a U-Net architecture to provide anatomical information. U-Net parameters were optimized to minimize the difference between the output super-resolution image and the experimentally acquired low-resolution pHe image using the mean-absolute error. In this way, the super-resolution pHe image would be consistent with both anatomical MR images and the low-resolution pHe measurement from the scanner. The method was developed based on data from 49 rabbits implanted with VX2 liver tumors. For evaluation, we also acquired high-resolution pHe images from two rabbits, which were used as ground truth. The results indicate a good match between the spatial characteristics of the super-resolution images and the high-resolution ground truth, supported by the low pixelwise absolute error.
期刊介绍:
NMR in Biomedicine is a journal devoted to the publication of original full-length papers, rapid communications and review articles describing the development of magnetic resonance spectroscopy or imaging methods or their use to investigate physiological, biochemical, biophysical or medical problems. Topics for submitted papers should be in one of the following general categories: (a) development of methods and instrumentation for MR of biological systems; (b) studies of normal or diseased organs, tissues or cells; (c) diagnosis or treatment of disease. Reports may cover work on patients or healthy human subjects, in vivo animal experiments, studies of isolated organs or cultured cells, analysis of tissue extracts, NMR theory, experimental techniques, or instrumentation.