Purpose Quantify the impact of respiratory motion on the treatment of lung tumors with spot scanning proton therapy. Methods and Materials 4D Monte Carlo simulations were used to assess the interplay effect, which results from relative motion of the tumor and the proton beam, on the dose distribution in the patient. Ten patients with varying tumor sizes (2.6-82.3cc) and motion amplitudes (3-30mm) were included in the study. We investigated the impact of the spot size, which varies between proton facilities, and studied single fractions and conventionally fractionated treatments. The following metrics were used in the analysis: minimum/maximum/mean dose, target dose homogeneity and 2-year local control rate (2y-LC). Results Respiratory motion reduces the target dose homogeneity, with the largest effects observed for the highest motion amplitudes. Smaller spot sizes (σ≈3mm) are inherently more sensitive to motion, decreasing target dose homogeneity on average by a factor ~2.8 compared to a larger spot size (σ≈13mm). Using a smaller spot size to treat a tumor with 30mm motion amplitude reduces the minimum dose to 44.7% of the prescribed dose, decreasing modeled 2y-LC from 87.0% to 2.7%, assuming a single fraction. Conventional fractionation partly mitigates this reduction, yielding a 2y-LC of 71.6%. For the large spot size, conventional fractionation increases target dose homogeneity and prevents a deterioration of 2y-LC for all patients. No correlation with tumor volume is observed. The effect on the normal lung dose distribution is minimal: observed changes in mean lung dose and lung V20 are <0.6Gy(RBE) and <1.7% respectively. Conclusions For the patients in this study, 2y-LC could be preserved in the presence of interplay using a large spot size and conventional fractionation. For treatments employing smaller spot sizes and/or in the delivery of single fractions, interplay effects can lead to significant deterioration of the dose distribution and lower 2y-LC.
Spline-based deformable registration methods are quite popular within the medical-imaging community due to their flexibility and robustness. However, they require a large amount of computing time to obtain adequate results. This paper makes two contributions towards accelerating B-spline-based registration. First, we propose a grid-alignment scheme and associated data structures that greatly reduce the complexity of the registration algorithm. Based on this grid-alignment scheme, we then develop highly data parallel designs for B-spline registration within the stream-processing model, suitable for implementation on multi-core processors such as graphics processing units (GPUs). Particular attention is focused on an optimal method for performing analytic gradient computations in a data parallel fashion. CPU and GPU versions are validated for execution time and registration quality. Performance results on large images show that our GPU algorithm achieves a speedup of 15 times over the single-threaded CPU implementation whereas our multi-core CPU algorithm achieves a speedup of 8 times over the single-threaded implementation. The CPU and GPU versions achieve near-identical registration quality in terms of RMS differences between the generated vector fields.
We present a fabricated metal-semiconductor-metal ͑MSM͒ photodetector exhibiting an enhanced photocurrent by integrating a nanoscale metallic grating into its contacts. This serves to increase the incident photon flux about the aperture of the device by guiding incident photons as surface plasmon polaritons. High speed time response data shows that the device responsivity may be increased without sacrificing speed. We demonstrate both a photocurrent enhancement and responsivity increase of about 90% at the design wavelength in comparison to otherwise identical MSM photodetectors without integrated nanoscale gratings. The device retains the MSM advantages of simplicity, planarity, and monolithic integrability.
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