Blind Deblurring Reconstruction Technique with Applications in PET Imaging

We developed an empirical PET model taking into account system blurring and a blind iterative reconstruction scheme that estimates both the actual image and the point spread function of the system. Reconstruction images of high quality can be acquired by using the proposed reconstruction technique for both synthetic and experimental data. In the synthetic data study, the algorithm reduces image blurring and preserves the edges without introducing extra artifacts. The localized measurement shows that the performance of the reconstruction image improved by up to 100%. In experimental data studies, the contrast and quality of reconstruction is substantially improved. The proposed method shows promise in tumor localization and quantification

Investigation of dose perturbations and the radiographic visibility of potential fiducials for proton radiation therapy of the prostate

Image guidance using implanted fiducial markers is commonly used to ensure accurate and reproducible target positioning in radiation therapy for prostate cancer. The ideal fiducial marker is clearly visible in kV imaging, does not perturb the therapeutic dose in the target volume and does not cause any artifacts on the CT images used for treatment planning. As yet, ideal markers that fully meet all three of these criteria have not been reported. In this study, 12 fiducial markers were evaluated for their potential clinical utility in proton radiation therapy for prostate cancer. In order to identify the good candidates, each fiducial was imaged using a CT scanner as well as a kV imaging system. Additionally, the dose perturbation caused by each fiducial was quantified using radiochromic film and a clinical proton beam. Based on the results, three fiducials were identified as good candidates for use in proton radiotherapy of prostate cancer. © 2011 Institute of Physics and Engineering in Medicine

Clinical commissioning of intensity-modulated proton therapy systems: Report of AAPM Task Group 185

Proton therapy is an expanding radiotherapy modality in the United States and worldwide. With the number of proton therapy centers treating patients increasing, so does the need for consistent, high-quality clinical commissioning practices. Clinical commissioning encompasses the entire proton therapy system\u27s multiple components, including the treatment delivery system, the patient positioning system, and the image-guided radiotherapy components. Also included in the commissioning process are the x-ray computed tomography scanner calibration for proton stopping power, the radiotherapy treatment planning system, and corresponding portions of the treatment management system. This commissioning report focuses exclusively on intensity-modulated scanning systems, presenting details of how to perform the commissioning of the proton therapy and ancillary systems, including the required proton beam measurements, treatment planning system dose modeling, and the equipment needed

Evaluation of the systematic error in using 3D dose calculation in scanning beam proton therapy for lung cancer

The objective of this study was to evaluate and understand the systematic error between the planned three-dimensional (3D) dose and the delivered dose to patient in scanning beam proton therapy for lung tumors. Single-field and multi-field optimized scanning beam proton therapy plans were generated for 10 patients with stage II–III lung cancer with a mix of tumor motion and size. 3D doses in CT data sets for different respiratory phases and the time weighted average CT, as well as the four-dimensional (4D) doses were computed for both plans. The 3D and 4D dose differences for the targets and different organs at risk were compared using dose volume histogram (DVH) and voxel-based techniques and correlated with the extent of tumor motion. The gross tumor volume (GTV) dose was maintained in all 3D and 4D doses using the internal GTV override technique. The DVH and voxel-based techniques are highly correlated. The mean dose error and the standard deviation of dose error for all target volumes were both less than 1.5% for all but one patient. However, the point dose difference between the 3D and 4D doses was up to 6% for the GTV and greater than 10% for the clinical and planning target volumes. Changes in the 4D and 3D doses were not correlated with tumor motion. The planning technique (single-field or multi-field optimized) did not affect the observed systematic error

A prospective pilot clinical trial evaluating the utility of a dynamic near-infrared imaging device for characterizing suspicious breast lesions

Introduction: Characterizing and differentiating between malignant tumors, benign tumors, and normal breast tissue is increasingly important in the patient presenting with breast problems. Near-infrared diffuse optical imaging and spectroscopy is capable of measuring multiple physiologic parameters of biological tissue systems and may have clinical applications for assessing the development and progression of neoplastic processes, including breast cancer. The currently available application of near-infrared imaging technology for the breast, however, is compromised by low spatial resolution, tissue heterogeneity, and interpatient variation. Materials and methods: We tested a dynamic near-infrared imaging schema for the characterization of suspicious breast lesions identified on diagnostic clinical ultrasound. A portable handheld near-infrared tissue imaging device (P-Scan; ViOptix Inc., Fremont, CA, USA) was utilized. An external mechanical compression force was applied to breast tissue. The tissue oxygen saturation and hemoglobin concentration were recorded simultaneously by the handheld near-infrared imaging device. Twelve categories of dynamic tissue parameters were derived based on real-time measurements of the tissue hemoglobin concentration and the oxygen saturation. Results: Fifty suspicious breast lesions were evaluated in 48 patients. Statistical analyses were carried out on 36 out of 50 datasets that satisfied our inclusion criteria. Suspicious breast lesions identified on diagnostic clinical ultrasound had lower oxygenation and higher hemoglobin concentration than the surrounding normal breast tissue. Furthermore, histopathologic-proven malignant breast tumors had a lower differential hemoglobin contrast (that is, the difference of hemoglobin concentration variability between the suspicious breast lesion and the normal breast parenchyma located remotely elsewhere within the ipsilateral breast) as compared with histopathologic-proven benign breast lesions. Conclusion: The proposed dynamic near-infrared imaging schema has the potential to differentiate benign processes from those of malignant breast tumors. Further development and refinement of the dynamic imaging device and additional subsequent clinical testing are necessary for optimizing the accuracy of detection

Spatial mapping of the biologic effectiveness of scanned particle beams: towards biologically optimized particle therapy

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

Protein-Protein Interactions of Tandem Affinity Purified Protein Kinases from Rice

Eighty-eight rice (Oryza sativa) cDNAs encoding rice leaf expressed protein kinases (PKs) were fused to a Tandem Affinity Purification tag (TAP-tag) and expressed in transgenic rice plants. The TAP-tagged PKs and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by tandem mass spectrometry. Forty-five TAP-tagged PKs were recovered in this study and thirteen of these were found to interact with other rice proteins with a high probability score. In vivo phosphorylated sites were found for three of the PKs. A comparison of the TAP-tagged data from a combined analysis of 129 TAP-tagged rice protein kinases with a concurrent screen using yeast two hybrid methods identified an evolutionarily new rice protein that interacts with the well conserved cell division cycle 2 (CDC2) protein complex

Comparison of Strategies to Detect Epistasis from eQTL Data

Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects

Towards Establishment of a Rice Stress Response Interactome

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance