MONTE CARLO MODELING OF DIFFUSE LIGHT TRANSPORT

点击翻译按钮获取中文摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Novel Monte Carlo techniques are being developed to quantitatively determine the tissue volume sampled by non-invasive diffuse imaging modalities. Recent research activity has culminated with the development of a new transport-theoretic method for imaging and analyzing the conditional response of a detector, conditioned by passage through any designated tissue subvolume targeted for investigation. The new procedure relies on a generalized reciprocity theory for radiative transport that enables the computation to be performed efficiently using a pair of Monte Carlo simulations: one tracking photons from the source, and the second tracking backward-moving photons initiated at the detector. This "midway method" then pairs the forward and backward -moving photons in matched spatial-angular bins at the surface of the targeted volume. An integration over the target bounding surfaces produces the desired joint probability of both visiting the targeted volume and being detected. The method has been tested on a two-layer epithelial tissue model and the data derived from the simulations is used to compare the relative merits and efficiencies of competing probe designs. These preferences are then confirmed through the solution of inverse problems that indicate best probe designs for a given source-detector-target volume configuration. Future work will include the addition of variance reduction strategies and additional testing and model validation studies. The use of this conditional detector response information should aid greatly in the design of novel probes customized for a particular application.