Brian Joseph Soher

My research focuses on the development and clinical translation of quantitative, multi-parametric MRI and MR spectroscopy (MRS) data acquisition and analysis techniques. These methods are applicable to the characterization of both chronic and focal pathologies, originally in the brain, but more recently in other organs such as liver and muscle. The overarching goals of these investigations are 1) to improve acquired data quality, 2) to obtain the maximum amount of useful information and/or to exclude confounding signals, and 3) to acquire additional a priori information that can make a given analysis more robust. My practical goals are to develop flexible, reusable and user-friendly tools and techniques, primarily through open source software packages, that can be applied in a robust manner for clinical investigative and diagnostic use.

My early research aimed at developing robust quantitation methods for spectroscopic imaging (SI) data analysis in the brain. As part of a multi-disciplinary team I helped develop a cross-platform GUI-driven suite of spectral processing/analysis tools to simplify the use of SI in clinical research. Throughout my career, I have continued work to expand spatial coverage, to create simulations of metabolic data acquisition to extend the accuracy of the models used to fit the SI data, and to develop acquisition and post-processing algorithms to remove unwanted water and lipid signals. This work led up to the idea for which I received my first R01. It has also resulted in two open-source software packages, MIDAS and Vespa (http://mrir.med.miami.edu:8000/midas and https://vespa-mrs.github.io/vespa.io/) that have received wide acceptance by many researchers and groups.

The latest versions of these tools are in active use in CAMRD studies investigating 1) volumetric changes in physiologic biomarkers of cellular breakdown in the brain due to high grade glioma progression, 2) changes in liver energy homeostasis due to a challenge using injected fructose, 3) spectral analysis and quantitation of edited single-voxel MRS method such as MEGA-PRESS and MEGA-sLASER to isolate small metabolite signals like GABA and 2HG. I also work actively to educate my colleagues as to the existence and applicability of these and other tools that I have access to due to my contacts in the MR research community.

More recently, I have developed a number of research projects in the rapidly changing area of body MR. Initial projects were to characterize the use of high-speed 3D MR imaging sequences to characterize the presence of water and fat in various organs. Standard in- and opposed-phase techniques were compared with newer fat-water separated imaging techniques. Fat-water separation imaging methods create individual water and fat images that maintain useful anatomic references while allowing both fat and water signals to be viewed separately. In parallel with our technique development for water-far imaging techniques, I developed and patented a novel technique for utilizing the heat insensitive nature of fat to non-invasively map temperature changes during the application of hyperthermia treatments for sarcomas.

Currently, I am investigating the use of tissue modelling to estimate absolute tissue fat fractions to provide a normalization technique for comparing in- and opposed-phase measures across platforms, sequences and field strengths. I am also working on an R01 that measures dynamic liver energy metabolism to help detect and stage NASH patients.