[en] A time delay in a respiratory gating system could cause an unexpected phase mismatch for synchronized gating radiotherapy. This study presents a method of identifying and measuring the time delay in a gating system. Various port films were taken for a motion phantom at different gating window levels with a very narrow window size. The time delay for the gating system was determined by comparing the motion curve (the position of a moving object versus the gating time) measured in the port films to the motion curve determined by the video cameras. The measured time delay for a linac-based gating system was 0.17±0.03 s. This time delay could induce target missing if it was not properly taken into account for the synchronized gating radiotherapy. Measurement/verification of the time delay should be considered as an important part of the accepting/commissioning test before the clinical use of the gating system

[en] We studied a recently proposed aggregated CT reconstruction technique which combines the complementary advantages of kilovoltage (kV) and megavoltage (MV) x-ray imaging. Various phantoms were imaged to study the effects of beam orientations and geometry of the imaging object on image quality of reconstructed CT. It was shown that the quality of aggregated CT was correlated with both kV and MV beam orientations and the degree of this correlation depended upon the geometry of the imaging object. The results indicated that the optimal orientations were those when kV beams pass through the thinner portion and MV beams pass through the thicker portion of the imaging object. A special preprocessing procedure was also developed to perform contrast conversions between kV and MV information prior to image reconstruction. The performance of two reconstruction methods, one filtered backprojection method and one iterative method, were compared. The effects of projection number, beam truncation, and contrast conversion on the CT image quality were investigated

[en] The technologies with kilovoltage (kV) and megavoltage (MV) imaging in the treatment room are now available for image-guided radiation therapy to improve patient setup and target localization accuracy. However, development of strategies to efficiently and effectively implement these technologies for patient treatment remains challenging. This study proposed an aggregated technique for on-board CT reconstruction using combination of kV and MV beam projections to improve the data acquisition efficiency and image quality. These projections were acquired in the treatment room at the patient treatment position with a new kV imaging device installed on the accelerator gantry, orthogonal to the existing MV portal imaging device. The projection images for a head phantom and a contrast phantom were acquired using both the On-Board Imager^TM kV imaging device and the MV portal imager mounted orthogonally on the gantry of a Varian Clinac^TM 21EX linear accelerator. MV projections were converted into kV information prior to the aggregated CT reconstruction. The multilevel scheme algebraic-reconstruction technique was used to reconstruct CT images involving either full, truncated, or a combination of both full and truncated projections. An adaptive reconstruction method was also applied, based on the limited numbers of kV projections and truncated MV projections, to enhance the anatomical information around the treatment volume and to minimize the radiation dose. The effects of the total number of projections, the combination of kV and MV projections, and the beam truncation of MV projections on the details of reconstructed kV/MV CT images were also investigated

[en] A phantom study was conducted to investigate inherent positioning accuracy of an image-guided patient positioning system--the Novalis Body system for three-dimensional (3-D) conformal radiotherapy. This positioning system consists of two infrared (IR) cameras and one video camera and two kV x-ray imaging devices. The initial patient setup was guided by the IR camera system and the target localization was accomplished using the kV x-ray imaging system. In this study, the IR marker shift and phantom rotation were simulated and their effects on the positioning accuracy were examined by a Rando phantom. The effects of CT slice thickness and treatment sites on the positioning accuracy were tested. In addition, the internal target shift was simulated and its effect on the positioning accuracy was examined by a water tank. With the application of the Novalis Body system, the positioning error of the planned isocenter was significantly reduced. The experimental results with the simulated IR marker shifts indicated that the positioning errors of the planned isocenter were 0.6±0.3, 0.5±0.2, and 0.7±0.2 mm along the lateral, longitudinal, and vertical axes, respectively. The experimental results with the simulated phantom rotations indicated that the positioning errors of the planned isocenter were 0.6±0.3, 0.7±0.2, and 0.5±0.2 mm along the three axes, respectively. The experimental results with the simulated target shifts indicated that the positioning errors of the planned isocenter were 0.6±0.3, 0.7±0.2, and 0.5±0.2 mm along the three axes, respectively. On average, the positioning accuracy of 1 mm for the planned isocenter was achieved using the Novalis Body system

[en] This work proposes to use the radiation from brachytherapy sources to track their dwell positions in three-dimensional (3D) space. The prototype device uses a single flat panel detector and a BB tray. The BBs are arranged in a defined pattern. The shadow of the BBs on the flat panel is analyzed to derive the 3D coordinates of the illumination source, i.e., the dwell position of the brachytherapy source. A kilovoltage x-ray source located 3.3 m away was used to align the center BB with the center pixel on the flat panel detector. For a test plan of 11 dwell positions, with an Ir-192 high dose rate unit, one projection was taken for each dwell point, and locations of the BB shadows were manually identified on the projection images. The 3D coordinates for the 11 dwell positions were reconstructed based on two BBs. The distances between dwell points were compared with the expected values. The average difference was 0.07 cm with a standard deviation of 0.15 cm. With automated BB shadow recognition in the future, this technique possesses the potential of tracking the 3D trajectory and the dwell times of a brachytherapy source in real time, enabling real time source position verification.

[en] A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved

[en] Purpose: To investigate a method for the generation of digitally reconstructed radiographs directly from MR images (DRR-MRI) to guide a computerized portal verification procedure. Methods and Materials: Several major steps were developed to perform an MR image-guided portal verification procedure. Initially, a wavelet-based multiresolution adaptive thresholding method was used to segment the skin slice-by-slice in MR brain axial images. Some selected anatomical structures, such as target volume and critical organs, were then manually identified and were reassigned to relatively higher intensities. Interslice information was interpolated with a directional method to achieve comparable display resolution in three dimensions. Next, a ray-tracing method was used to generate a DRR-MRI image at the planned treatment position, and the ray tracing was simply performed on summation of voxels along the ray. The skin and its relative positions were also projected to the DRR-MRI and were used to guide the search of similar features in the portal image. A Canny edge detector was used to enhance the brain contour in both portal and simulation images. The skin in the brain portal image was then extracted using a knowledge-based searching technique. Finally, a Chamfer matching technique was used to correlate features between DRR-MRI and portal image. Results: The MR image-guided portal verification method was evaluated using a brain phantom case and a clinical patient case. Both DRR-CT and DRR-MRI were generated using CT and MR phantom images with the same beam orientation and then compared. The matching result indicated that the maximum deviation of internal structures was less than 1 mm. The segmented results for brain MR slice images indicated that a wavelet-based image segmentation technique provided a reasonable estimation for the brain skin. For the clinical patient case with a given portal field, the MR image-guided verification method provided an excellent match between features in both DRR-MRI and portal image. Moreover, target volume could be accurately visualized in the DRR-MRI and mapped over to the corresponding portal image for treatment verification. The accuracy of DRR-MRI was also examined by comparing it to the corresponding simulation image. The matching results indicated that the maximum deviation of anatomical features was less than 2.5 mm. Conclusion: A method for MR image-guided portal verification of brain treatment field was developed. Although the radiographic appearance in the DRR-MRI is different from that in the portal image, DRR-MRI provides essential anatomical features (landmarks and target volume) as well as their relative locations to be used as references for computerized portal verification

[en] Two novel carbazole-based Schiff-bases L1 and L2 have been synthesized and characterized by ¹H NMR, ¹³C NMR, FT-IR spectroscopy and elemental analysis. L1 can selectively detect Fe³⁺ by UV–vis spectroscopy and Fe³⁺/Cr³⁺ by fluorescent spectroscopy in CH₃CN among various metal ions. The addition of Fe³⁺ ions to a L1 solution results in a significant blue-shift from 410 nm to 378 nm accompanied with color change from yellowish green to colorless. Upon excitation at 380 nm, the addition of Fe³⁺ or Cr³⁺ causes a 13-fold or 11-fold fluorescence enhancement. The binding stoichiometry ratio of L1–Fe³⁺ and L1–Cr³⁺ is recognized as 2:1 by the method of Job's plot, and the possible binding mode of the system also proposes. The results indicate that L1 is an ideal chemosensor for Fe³⁺ and Cr³⁺ recognition. However, L2 without hydroxyl in ortho imino group cannot selectively recognize the tasted metal ions, indicating that the introduction of the appropriate coordination binding site to receptor can improve efficiently the selectivity of chemosensor. - Highlights: • We designed and synthesized two new carbazole-based Schiff bases L1 and L2. • L1 could selectively recognize Fe³⁺ but L2 could not, which suggested that increase recognition site helped to improve the selectivity of probe. • L1 not only could serve as a highly selective visual chemosensor for Fe³⁺ ion without the aid of any instruments, but also could be used as a fluorescent chemosensor for Fe³⁺ and Cr³⁺

[en] An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

[en] Digital tomosynthesis (DTS) is a method to reconstruct pseudo three-dimensional (3D) volume images from two-dimensional x-ray projections acquired over limited scan angles. Compared with cone-beam computed tomography, which is frequently used for 3D image guided radiation therapy, DTS requires less imaging time and dose. Successful implementation of DTS for fast target localization requires the reconstruction process to be accomplished within tight clinical time constraints (usually within 2 min). To achieve this goal, substantial improvement of reconstruction efficiency is necessary. In this study, a reconstruction process based upon the algorithm proposed by Feldkamp, Davis, and Kress was implemented on graphics hardware for the purpose of acceleration. The performance of the novel reconstruction implementation was tested for phantom and real patient cases. The efficiency of DTS reconstruction was improved by a factor of 13 on average, without compromising image quality. With acceleration of the reconstruction algorithm, the whole DTS generation process including data preprocessing, reconstruction, and DICOM conversion is accomplished within 1.5 min, which ultimately meets clinical requirement for on-line target localization