28
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Diffusion MRI of cancer: From low to high b-values : High b-Value Diffusion MRI of Cancer

      1 , 2
      Journal of Magnetic Resonance Imaging
      Wiley

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advance in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties – cellularly, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: (a) cancer detection and diagnosis; (b) cancer grading, staging, and classification; and (c) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multi-center clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale.

          Related collections

          Most cited references78

          • Record: found
          • Abstract: found
          • Article: not found

          Early detection of regional cerebral ischemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy.

          Diffusion-weighted MR images were compared with T2-weighted MR images and correlated with 1H spin-echo and 31P MR spectroscopy for 6-8 h following a unilateral middle cerebral and bilateral carotid artery occlusion in eight cats. Diffusion-weighted images using strong gradient strengths (b values of 1413 s/mm2) displayed a significant relative hyperintensity in ischemic regions as early as 45 min after onset of ischemia whereas T2-weighted spin-echo images failed to clearly demonstrate brain injury up to 2-3 h postocclusion. Signal intensity ratios (SIR) of ischemic to normal tissues were greater in the diffusion-weighted images at all times than in either TE 80 or TE 160 ms T2-weighted MR images. Diffusion- and T2-weighted SIR did not correlate for the first 1-2 h postocclusion. Good correlation was found between diffusion-weighted SIR and ischemic disturbances of energy metabolism as detected by 31P and 1H MR spectroscopy. Diffusion-weighted hyperintensity in ischemic tissues may be temperature-related, due to rapid accumulation of diffusion-restricted water in the intracellular space (cytotoxic edema) resulting from the breakdown of the transmembrane pump and/or to microscopic brain pulsations.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response.

            Assessment of radiation and chemotherapy efficacy for brain cancer patients is traditionally accomplished by measuring changes in tumor size several months after therapy has been administered. The ability to use noninvasive imaging during the early stages of fractionated therapy to determine whether a particular treatment will be effective would provide an opportunity to optimize individual patient management and avoid unnecessary systemic toxicity, expense, and treatment delays. We investigated whether changes in the Brownian motion of water within tumor tissue as quantified by using diffusion MRI could be used as a biomarker for early prediction of treatment response in brain cancer patients. Twenty brain tumor patients were examined by standard and diffusion MRI before initiation of treatment. Additional images were acquired 3 weeks after initiation of chemo- and/or radiotherapy. Images were coregistered to pretreatment scans, and changes in tumor water diffusion values were calculated and displayed as a functional diffusion map (fDM) for correlation with clinical response. Of the 20 patients imaged during the course of therapy, 6 were classified as having a partial response, 6 as stable disease, and 8 as progressive disease. The fDMs were found to predict patient response at 3 weeks from the start of treatment, revealing that early changes in tumor diffusion values could be used as a prognostic indicator of subsequent volumetric tumor response. Overall, fDM analysis provided an early biomarker for predicting treatment response in brain tumor patients.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Gleason grading and prognostic factors in carcinoma of the prostate.

              Gleason grade of adenocarcinoma of the prostate is an established prognostic indicator that has stood the test of time. The Gleason grading method was devised in the 1960s and 1970s by Dr Donald F Gleason and members of the Veterans Administration Cooperative Urological Research Group. This grading system is based entirely on the histologic pattern of arrangement of carcinoma cells in H&E-stained sections. Five basic grade patterns are used to generate a histologic score, which can range from 2 to 10. These patterns are illustrated in a standard drawing that can be employed as a guide for recognition of the specific Gleason grades. Increasing Gleason grade is directly related to a number of histopathologic end points, including tumor size, margin status, and pathologic stage. Indeed, models have been developed that allow for pretreatment prediction of pathologic stage based upon needle biopsy Gleason grade, total serum prostate-specific antigen level, and clinical stage. Gleason grade has been linked to a number of clinical end points, including clinical stage, progression to metastatic disease, and survival. Gleason grade is often incorporated into nomograms used to predict response to a specific therapy, such as radiotherapy or surgery. Needle biopsy Gleason grade is routinely used to plan patient management and is also often one of the criteria for eligibility for clinical trials testing new therapies. Gleason grade should be routinely reported for adenocarcinoma of the prostate in all types of tissue samples. Experimental approaches that could be of importance in the future include determination of percentage of high-grade Gleason pattern 4 or 5, and utilization of markers discovered by gene expression profiling or by genetic testing for DNA abnormalities. Such markers would be of prognostic usefulness if they provided added value beyond the established indicators of Gleason grade, serum prostate-specific antigen, and stage. Currently, established prognostic factors for prostatic carcinoma recommended for routine reporting are TNM stage, surgical margin status, serum prostate-specific antigen, and Gleason grade.
                Bookmark

                Author and article information

                Journal
                Journal of Magnetic Resonance Imaging
                J. Magn. Reson. Imaging
                Wiley
                10531807
                January 2019
                January 2019
                October 12 2018
                : 49
                : 1
                : 23-40
                Affiliations
                [1 ]Department of Radiology; Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research; Beijing China
                [2 ]Center for MR Research and Departments of Radiology, Neurosurgery, and Bioengineering; University of Illinois at Chicago; Chicago Illinois USA
                Article
                10.1002/jmri.26293
                6298843
                30311988
                eb10bc02-4ddd-421b-9f15-37d2eedab133
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                History

                Comments

                Comment on this article