Sreenath Narayan

Body composition analysis of obesity and hepatic steatosis in mice by relaxation compensated fat fraction (RCFF) MRI.

To develop and validate a quantitative magnetic resonance imaging (MRI) methodology for phenotyping animal models of obesity and fatty liver disease on 7T small animal MRI scanners.

Improved fat–water reconstruction algorithm with graphics hardware acceleration

To develop a fast and robust Iterative Decomposition of water and fat with Echo Asymmetry and Least‐squares (IDEAL) reconstruction algorithm using graphics processor unit (GPU) computation.

Fast Lipid And Water Levels by Extraction with Spatial Smoothing (FLAWLESS): Three-dimensional volume fat/water separation at 7 Tesla

To quickly and robustly separate fat/water components of 7T MR images in the presence of field inhomogeneity for the study of metabolic disorders in small animals.

A Fast Iterated Conditional Modes Algorithm for Water–Fat Decomposition in MRI

Decomposition of water and fat in magnetic resonance imaging (MRI) is important for biomedical research and clinical applications. In this paper, we propose a two-phased approach for the three-point water-fat decomposition problem. Our contribution consists of two components: 1) a background-masked Markov random field (MRF) energy model to formulate the local smoothness of field inhomogeneity; 2) a new iterated conditional modes (ICM) algorithm accounting for high-performance optimization of the MRF energy model. The MRF energy model is integrated with background masking to prevent error propagation of background estimates as well as improve efficiency. The central component of our new ICM algorithm is the stability tracking (ST) mechanism intended to dynamically track iterative stability on pixels so that computation per iteration is performed only on instable pixels. The ST mechanism significantly improves the efficiency of ICM. We also develop a median-based initialization algorithm to provide good initial guesses for ICM iterations, and an adaptive gradient-based scheme for parametric configuration of the MRF model. We evaluate the robust of our approach with high-resolution mouse datasets acquired from 7T MRI.

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): Fat/Water separation at 7 tesla

To reduce swaps in fat–water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map.

Hepatic fat during fasting and refeeding by MRI fat quantification

To explore the sensitivity of high‐field small animal magnetic resonance imaging to dynamic changes in fat content in the liver and to characterize the effect of prandial state on imaging studies of hepatic fat.

Functional Imaging of Chemically Active Surfaces with Optical Reporter Microbeads.

We have developed a novel approach to allow for continuous imaging of concentration fields that evolve at surfaces due to release, uptake, and mass transport of molecules, without significant interference of the concentration fields by the chemical imaging itself. The technique utilizes optical “reporter” microbeads immobilized in a thin layer of transparent and inert hydrogel on top of the surface. The hydrogel has minimal density and therefore diffusion in and across it is like in water. Imaging the immobilized microbeads over time provides quantitative concentration measurements at each location where an optical reporter resides. Using image analysis in post-processing these spatially discrete measurements can be transformed into contiguous maps of the dynamic concentration field across the entire surface. If the microbeads are small enough relative to the dimensions of the region of interest and sparsely applied then chemical imaging will not noticeably affect the evolution of concentration fields. In this work colorimetric optode microbeads a few micrometers in diameter were used to image surface concentration distributions on the millimeter scale.

Inflammatory Pseudotumor of the Liver with Escherichia coli in the Sputum.

Inflammatory pseudotumor is a nonmalignant lesion that mimics malignant lesions and has been reported to occur at various sites throughout the body. Though it has been reported as a reaction to infection, the true etiology of the lesion is unknown. In this report, we present the case of a patient with a liver lesion of unknown origin. Through a series of imaging studies, we were able to observe the locally aggressive nature of this lesion as it rapidly eroded into the lung. Sputum cultures showed growth of E. coli, indicating E. coli infection as a possible etiology of this lesion. Pathology was consistent with inflammatory pseudotumor.