Using patient-specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy.

The quality of adaptive treatment planning depends on the accuracy of its underlying deformable image registration (DIR). The purpose of this study is to evaluate the performance of two DIR algorithms, B-spline-based deformable multipass (DMP) and deformable demons (Demons), implemented in a commercial software package. Evaluations were conducted using both computational and physical deformable phantoms. Based on a finite element method (FEM), a total of 11 computational models were developed from a set of CT images acquired from four lung and one prostate cancer patients. FEM generated displacement vector fields (DVF) were used to construct the lung and prostate image phantoms. Based on a fast-Fourier transform technique, image noise power spectrum was incorporated into the prostate image phantoms to create simulated CBCT images. The FEM-DVF served as a gold standard for verification of the two registration algorithms performed on these phantoms. The registration algorithms were also evaluated at the homologous points quantified in the CT images of a physical lung phantom. The results indicated that the mean errors of the DMP algorithm were in the range of 1.0 ~ 3.1 mm for the computational phantoms and 1.9 mm for the physical lung phantom. For the computational prostate phantoms, the corresponding mean error was 1.0-1.9 mm in the prostate, 1.9-2.4mm in the rectum, and 1.8-2.1 mm over the entire patient body. Sinusoidal errors induced by B-spline interpolations were observed in all the displacement profiles of the DMP registrations. Regions of large displacements were observed to have more registration errors. Patient-specific FEM models have been developed to evaluate the DIR algorithms implemented in the commercial software package. It has been found that the accuracy of these algorithms is patient dependent and related to various factors including tissue deformation magnitudes and image intensity gradients across the regions of interest. This may suggest that DIR algorithms need to be verified for each registration instance when implementing adaptive radiation therapy.

Recirculating air filtration significantly reduces exposure to airborne nanoparticles.

BACKGROUND: Airborne nanoparticles from vehicle emissions have been associated with adverse effects in people with pulmonary and cardiovascular disease, and toxicologic studies have shown that nanoparticles can be more hazardous than their larger-scale counterparts. Recirculating air filtration in automobiles and houses may provide a low-cost solution to reducing exposures in many cases, thus reducing possible health risks. OBJECTIVES: We investigated the effectiveness of recirculating air filtration on reducing exposure to incidental and intentionally produced airborne nanoparticles under two scenarios: while driving in traffic, and while generating nanomaterials using gas-phase synthesis. METHODS: We tested the recirculating air filtration in two commercial vehicles when driving in traffic, as well as in a nonventilation room with a nanoparticle generator, simulating a nanomaterial production facility. We also measured the time-resolved aerosol size distribution during the in-car recirculation to investigate how recirculating air filtration affects particles of different sizes. We developed a recirculation model to describe the aerosol concentration change during recirculation. RESULTS: The use of inexpensive, low-efficiency filters in recirculation systems is shown to reduce nanoparticle concentrations to below levels found in a typical office within 3 min while driving through heavy traffic, and within 20 min in a simulated nanomaterial production facility. CONCLUSIONS: Development and application of this technology could lead to significant reductions in airborne nanoparticle exposure, reducing possible risks to health and providing solutions for generating nanomaterials safely.

Laboratory and on-road evaluations of cabin air filters using number and surface area concentration monitors.

An automotive cabin air filter's effectiveness for removing airborne particles was determined both in a laboratory wind tunnel and in vehicle on-road tests. The most penetrating particle size for the test filter was approximately 350 nm, where the filtration efficiency was 22.9 and 17.4% at medium and high fan speeds, respectively. The filtration efficiency increased for smaller particles and was 43.9% for 100 nm and 72.0% for 20 nm particles at a medium fan speed. We determined the reduction in passenger exposure to particles while driving in freeway traffic caused by a vehicle ventilation system with a cabin air filter installed. Both particle number and surface area concentration measurements were made inside the cabin and in the surrounding air. At medium fan speed, the number and surface area concentration-based exposure reductions were 65.6 +/- 6.0% and 60.6 +/- 9.4%, respectively. To distinguish the exposure reduction contribution from the filter alone and the remainder of the ventilation system, we also performed tests with and without the filter in place using the surface area monitors. The ventilation system operating in the recirculation mode with the cabin air filter installed provided the maximum protection, reducing the cabin particle concentration exponentially over time and usually taking only 3 min to reach 10 microm2/cm3 (a typical office air condition) under medium fan speed.