Magnetic resonance imaging glossary of findings of pediatric pancreatitis and the revised Atlanta classification.

While still uncommon, the incidence of acute pancreatitis in children has been increasing over the last two decades. The Atlanta classification for acute pancreatitis, developed for adults, stratifies cases of acute pancreatitis based on imaging and clinical criteria. This classification scheme allows for standardized use of terminology to facilitate treatment and prognostication. Although US and CT should be used in critical or unstable patients, MRI is an ideal imaging modality in pediatric patients with acute pancreatitis because of its ability to characterize tissue without ionizing radiation. We review MRI examples specific to Atlanta classification terminology in pediatric patients. Chronic pancreatitis has also been increasingly diagnosed in children, and imaging plays a key role in the diagnosis and management of this insidious disease. MRI with magnetic resonance cholangiopancreatography is the optimal modality for assessing the pancreas in a child with known or suspected chronic pancreatitis because it provides tissue characterization and high-contrast imaging of the pancreatic duct without the use of invasive instrumentation or ionizing radiation. We also review and demonstrate accepted MRI findings of chronic pancreatitis.

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory.

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

Computational Framework to Evaluate the Hydrodynamics of Cell Scaffold Geometries.

The fluid dynamics of microporous materials are important to many biomedical processes such as cell deposition in scaffold materials, tissue engineering, and bioreactors. Microporous scaffolds are frequently composed of suspensions of beads that have varying topology which, in turn, informs their hydrodynamic properties. Previous work has shown that shear stress distributions can affect the response of cells in microporous environments. Using computational fluid dynamics, we characterize localized differences in fluid flow attributes such wall shear stress and velocity to better understand the fluid dynamics underpinning microporous device function. We evaluated whether bead packings with similar void fractions had different fluid dynamics as characterized by the distribution of velocity magnitudes and wall shear stress and found that there are differences despite the similarities in void fraction. We show that another metric, the average distance to the nearest wall, can provide an additional variable to measure the porosity and susceptibility of microporous materials to high shear stress. By increasing our understanding of the impact of bead size on cell scaffold fluid dynamics we aim to increase the ability to predict important attributes such as loading efficiency in these devices.

Multi-GPU Immersed Boundary Method Hemodynamics Simulations.

Large-scale simulations of blood flow that resolve the 3D deformation of each comprising cell are increasingly popular owing to algorithmic developments in conjunction with advances in compute capability. Among different approaches for modeling cell-resolved hemodynamics, fluid structure interaction (FSI) algorithms based on the immersed boundary method are frequently employed for coupling separate solvers for the background fluid and the cells within one framework. GPUs can accelerate these simulations; however, both current pre-exascale and future exascale CPU-GPU heterogeneous systems face communication challenges critical to performance and scalability. We describe, to our knowledge, the largest distributed GPU-accelerated FSI simulations of high hematocrit cell-resolved flows with over 17 million red blood cells. We compare scaling on a fat node system with six GPUs per node and on a system with a single GPU per node. Through comparison between the CPU- and GPU-based implementations, we identify the costs of data movement in multiscale multi-grid FSI simulations on heterogeneous systems and show it to be the greatest performance bottleneck on the GPU.

Extraosseous Multiple Myeloma: Case Report of Presentation in the Lower Extremity Soft Tissues with Literature Review.

A rare presentation of extramedullary multiple myeloma in the soft tissues of the bilateral thighs prompted a literature review of published cases of extramedullary multiple myeloma (EM-MM) and solitary plasmacytomas to determine the relative anatomic distribution of these lesions. All available published cases in English were included in the analysis, dating back to 1966 and including 2,538 extramedullary myeloma or solitary plasmacytoma lesions. Analysis of the anatomic location of EM-MM lesions demonstrates the majority being in the upper airway (33.8%), soft tissues including retroperitoneum and abdomen (14.1%), gastrointestinal tract (10.3%), central nervous system, head and neck (16.0%), and GU (2.4%). We were able to find only 44 documented cases of extremity soft tissue lesions, comprising 1.7% of all lesions.