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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Raster-scanning serial protein crystallography using micro- and nano-focused synchrotron beams

A raster scanning serial protein crystallography approach is presented, that consumes as low ∼200–700 nl of sedimented crystals. New serial data pre-analysis software, NanoPeakCell, is introduced. High-resolution structural information was obtained from lysozyme microcrystals (20 µm in the largest dimension) using raster-scanning serial protein crystallography on micro- and nano-focused beamlines at the ESRF. Data were collected at room temperature (RT) from crystals sandwiched between two silicon nitride wafers, thereby preventing their drying, while limiting background scattering and sample consumption. In order to identify crystal hits, new multi-processing and GUI-driven Python-based pre-analysis software was developed, named NanoPeakCell, that was able to read data from a variety of crystallographic image formats. Further data processing was carried out using CrystFEL, and the resultant structures were refined to 1.7 Å resolution. The data demonstrate the feasibility of RT raster-scanning serial micro- and nano-protein crystallography at synchrotrons and validate it as an alternative approach for the collection of high-resolution structural data from micro-sized crystals. Advantages of the proposed approach are its thriftiness, its handling-free nature, the reduced amount of sample required, the adjustable hit rate, the high indexing rate and the minimization of background scattering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

SU-F-P-32: A Phantom Study of Accuracy of Four-Dimensional Cone-Beam CT (4D-CBCT) Vs. Three-Dimensional Cone Beam CT (3D-CBCT) in Image Guided Radiotherapy

Purpose: SymmetryTM 4D IGRT system of Elekta has been installed at our institution, which offers the 4D CBCT registration option. This study is to evaluate the accuracy of 4D CBCT system by using the CIRS 4D motion phantom and to perform a feasibility study on the implementation of 4D-CBCT as image guidance for SBRT treatment. Methods: The 3D and 4D CT image data sets are acquired using the CIRS motion phantom on a Philips large bore CT simulator. The motion was set as 0.5 cm superior and inferior directions with 6 seconds recycle time. The 4D CT data were sorted as 10 phases. One identifiable part of the 4D CT QA insert from CIRS phantom was used as the target. The ITV MIP was drawn based on maximum intensity projection (MIP) and transferred as a planning structure into 4D CBCT system. Then the 3D CBCT and 4D CBCT images were taken and registered with the free breath (3D), MIP (4D) and average intensity projection (AIP)(4D) reference data sets. The couch shifts (X, Y, Z) are recorded and compared. Results: Table 1 listed the twelve couch shifts based on the registration of MIP, AIP and free breath CT data sets with 3D CBCT and 4D CBCT for both whole body and local registration. X, Y and Z represent couch shifts in the direction of the right-left, superior-inferior and anterior-posterior. The biggest differences of 0.73 cm and 0.57 cm are noted in the free breath CT data with 4D CBCT and 3D CBCT data registration. Fig. 1 and Fig. 2 are the shift analysis in diagram. Fig. 3 shows the registration. Conclusion: Significant differences exist in the shifts corresponding with the direction of target motion. Further investigations are ongoing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-199: Predictive Models for Cone Beam CT-Based Online Verification of Pencil Beam Scanning Proton Therapy

Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal and distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.

60 APPLIED LIFE SCIENCES↗