HEATING IN VASCULAR TISSUE AND FLOW-THROUGH TISSUE PHANTOMS INDUCED BY FOCUSED ULTRASOUND

High intensity focused ultrasound (HIFU) can be used to control bleeding, both from individual blood vessels as well as from gross damage to the capillary bed. This process, called acoustic hemostasis, is being studied in the hope that such a method would ultimately provide a lifesaving treatment during the so-called "golden hour", a brief grace period after a severe trauma in which prompt therapy can save the life of an injured person. Thermal effects play a major role in occlusion of small vessels and also appear to contribute to the sealing of punctures in major blood vessels. However, aggressive ultrasound-induced tissue heating can also impact healthy tissue and can lead to deleterious mechanical bioeffects. Moreover, the presence of vascularity can limit one’s ability to elevate the temperature of blood vessel walls owing to convective heat transport. In an effort to better understand the heating process in tissues with vascular structure we have developed a numerical simulation that couples models for ultrasound propagation, acoustic streaming, ultrasound heating and blood cooling in Newtonian viscous media. The 3-D simulation allows for the study of complicated biological structures and insonation geometries. We have also undertaken a series of in vitro experiments, in non-uniform flow-through tissue phantoms, designed to provide a ground truth verification of the model predictions. The calculated and measured results were compared over a range of values for insonation pressure, insonation time, and flow rate; we show good agreement between predictions and measurements. We then conducted a series of simulations that address two limiting problems of interest: hemostasis in small and large vessels. We employed realistic human tissue properties and considered more complex geometries. Results show that the heating pattern in and around a blood vessel is different for different vessel sizes, flow rates and for varying beam orientations relative to the flow axis. Complete occlusion and wall- puncture sealing are both possible depending on the exposure conditions. These results concur with prior clinical observations and may prove useful for planning of a more effective procedure in HIFU treatments.

On the Relationship Between File Sizes, Transport Protocols, and Self-Similar Network Traffic

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits variability at a wide range of scales self-similarity. In this paper, we examine a mechanism that gives rise to self-similar network traffic and present some of its performance implications. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. We examine its effects through detailed transport-level simulations of multiple TCP streams in an internetwork. First, we show that in a "realistic" client/server network environment i.e., one with bounded resources and coupling among traffic sources competing for resources the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. We show that this causal relationship is not significantly affected by changes in network resources (bottleneck bandwidth and buffer capacity), network topology, the influence of cross-traffic, or the distribution of interarrival times. Second, we show that properties of the transport layer play an important role in preserving and modulating this relationship. In particular, the reliable transmission and flow control mechanisms of TCP (Reno, Tahoe, or Vegas) serve to maintain the long-range dependency structure induced by heavy-tailed file size distributions. In contrast, if a non-flow-controlled and unreliable (UDP-based) transport protocol is used, the resulting traffic shows little self-similar characteristics: although still bursty at short time scales, it has little long-range dependence. If flow-controlled, unreliable transport is employed, the degree of traffic self-similarity is positively correlated with the degree of throttling at the source. Third, in exploring the relationship between file sizes, transport protocols, and self-similarity, we are also able to show some of the performance implications of self-similarity. We present data on the relationship between traffic self-similarity and network performance as captured by performance measures including packet loss rate, retransmission rate, and queueing delay. Increased self-similarity, as expected, results in degradation of performance. Queueing delay, in particular, exhibits a drastic increase with increasing self-similarity. Throughput-related measures such as packet loss and retransmission rate, however, increase only gradually with increasing traffic self-similarity as long as reliable, flow-controlled transport protocol is used.

Scheduling Flows with Unknown Sizes: Approximate Analysis

Previous studies have shown that giving preferential treatment to short jobs helps reduce the average system response time, especially when the job size distribution possesses the heavy-tailed property. Since it has been shown that the TCP flow length distribution also has the same property, it is natural to let short TCP flows enjoy better service inside the network. Analyzing such discriminatory system requires modification to traditional job scheduling models since usually network traffic managers do not have detailed knowledge about individual flows such as their lengths. The Multi-Level (ML) queue, proposed by Kleinrock, can b e used to characterize such system. In an ML queueing system, the priority of a flow is reduced as the flow stays longer. We present an approximate analysis of the ML queueing system to obtain a closed-form solution of the average system response time function for general flow size distributions. We show that the response time of short flows can be significantly reduced without penalizing long flows.