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In current treatment plans of intensity-modulated proton therapy, high-energy beams are usually assigned larger weights than low-energy beams. Using this form of beam delivery strategy cannot effectively use the biological advantages of low-energy and high-linear energy transfer (LET) protons present within the Bragg peak. However, the planning optimizer can be adjusted to alter the intensity of each beamlet, thus maintaining an identical target dose while increasing the weights of low-energy beams to elevate the LET therein. The objective of this study was to experimentally validate the enhanced biological effects using a novel beam delivery strategy with elevated LET. We used Monte Carlo and optimization algorithms to generate two different intensity-modulation patterns, namely to form a downslope and a flat dose field in the target. We spatially mapped the biological effects using high-content automated assays by employing an upgraded biophysical system with improved accuracy and precision of collected data. In vitro results in cancer cells show that using two opposed downslope fields results in a more biologically effective dose, which may have the clinical potential to increase the therapeutic index of proton therapy. [ABSTRACT FROM AUTHOR]

Cerenkov luminescence imaging (CLI) is an emerging optical imaging technique, which has been widely investigated for biological imaging. In this study, we proposed to integrate the CLI technique with the radionuclide treatment as a "see-and-treat" approach, and evaluated the performance of the pinhole collimator-based CLI technique. The detection of Cerenkov luminescence during radionuclide therapy was simulated using the Monte Carlo technique for breast cancer treatment as an example. Our results show that with the pinhole collimator-based configuration, the location, size and shape of the tumors can be clearly visualized on the Cerenkov luminescence images of the breast phantom. In addition, the CLI of multiple tumors can reflect the relative density of radioactivity among tumors, indicating that the intensity of Cerenkov luminescence is independent of the size and shape of a tumor. The current study has demonstrated the high-quality performance of the pinhole collimator-based CLI in breast tumor imaging for the "see-and-treat" multi-modality treatment. [ABSTRACT FROM AUTHOR]

Speckle noise has long been known as a limiting factor for the quality of an ultrasound B-mode image. In this study, anisotropic diffusion filtering is proposed as an effective method for ultrasound speckle reduction. This article provides a brief description of anisotropic diffusion filtering proposed by Perona and Malik, and compares its speckle filtering effects with other filtering methods including median, moving average, and frequency domain Gaussian low-pass. In this study, multiple filters are implemented in Matlab. For each filter, three different types of noisy images with speckle noise are tested. The results show that anisotropic filter can reduce the noise more effectively and meanwhile preserve the boundaries of the objects. In addition, this filter has more controllable filtering parameters and is independent on the information of the noise. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The physical properties of particles used in radiation therapy, such as protons, have been well characterized, and their dose distributions are superior to photon-based treatments. However, proton therapy may also have inherent biologic advantages that have not been capitalized on. Unlike photon beams, the linear energy transfer (LET) and hence biologic effectiveness of particle beams varies along the beam path. Selective placement of areas of high effectiveness could enhance tumor cell kill and simultaneously spare normal tissues. However, previous methods for mapping spatial variations in biologic effectiveness are time-consuming and often yield inconsistent results with large uncertainties. Thus the data needed to accurately model relative biological effectiveness to guide novel treatment planning approaches are limited. We used Monte Carlo modeling and high-content automated clonogenic survival assays to spatially map the biologic effectiveness of scanned proton beams with high accuracy and throughput while minimizing biological uncertainties. We found that the relationship between cell kill, dose, and LET, is complex and non-unique. Measured biologic effects were substantially greater than in most previous reports, and non-linear surviving fraction response was observed even for the highest LET values. Extension of this approach could generate data needed to optimize proton therapy plans incorporating variable RBE. [ABSTRACT FROM AUTHOR]