Biomedical subjects

Xingen Wu

Publications and source records attributed to Xingen Wu.

3 recordsLinked to original sources

PubMed2006

An improved MLC segmentation algorithm and software for step-and-shoot IMRT delivery without tongue-and-groove error.

We present an improved multileaf collimator (MLC) segmentation algorithm, denoted by SLS(NOTG) (static leaf sequencing with no tongue-and-groove error), for step-and-shoot intensity-modulated radiation therapy (IMRT) delivery. SLS(NOTG) is an improvement over the MLC segmentation algorithm called SLS that was developed by Luan et al. [Med. Phys. 31(4), 695-707 (2004)], which did not consider tongue-and-groove error corrections. The aims of SLS(NOTG) are (1) shortening the treatment times of IMRT plans by minimizing their numbers of segments and (2) minimizing the tongue-and-groove errors of the computed IMRT plans. The input to SLS(NOTG) is intensity maps (IMs) produced by current planning systems, and its output is (modified) optimized leaf sequences without tongue-and-groove error. Like the previous SLS algorithm [Luan et al., Med. Phys. 31(4), 695-707 (2004)], SLS(NOTG) is also based on graph algorithmic techniques in computer science. It models the MLC segmentation problem as a weighted minimum-cost path problem, where the weight of the path is the number of segments and the cost of the path is the amount of tongue-and-groove error. Our comparisons of SLS(NOTG) with CORVUS indicated that for the same intensity maps, the numbers of segments computed by SLS(NOTG) are up to 50% less than those by CORVUS 5.0 on the Elekta LINAC system. Our clinical verifications have shown that the dose distributions of the SLS(NOTG) plans do not have tongue-and-groove error and match those of the corresponding CORVUS plans, thus confirming the correctness of SLS(NOTG). Comparing with existing segmentation methods, SLS(NOTG) also has two additional advantages: (1) SLS(NOTG) can compute leaf sequences whose tongue-and-groove error is minimized subject to a constraint on the maximum allowed number of segments, which may be desirable in clinical situations where a treatment with the complete correction of tongue-and-groove error takes too much time, and (2) SLS(NOTG) can be used to minimize a more general type of error called the tongue-or-groove error.

Algorithms↗

PubMed2004

Deformable image registration for the use of magnetic resonance spectroscopy in prostate treatment planning.

PURPOSE: There is now convincing evidence that prostate cancer cells lack the ability to produce and accumulate citrate. Using magnetic resonance spectroscopy imaging (MRSI), regions of absent or low citrate concentration in the prostate can be visualized at a resolution of a few mm. This new advancement provides not only a tool for early diagnosis and screening but also the opportunity for preferential targeting of radiation to regions of high tumor burden in the prostate. The differences in the shape and location of the prostate between MRSI imaging and treatment have been the major obstacle in integrating MRSI in radiation therapy treatment planning. The purpose of this study is to develop a reliable method for deforming the prostate and surrounding regions from the geometry of MRSI imaging to the geometry of treatment planning, so that the regions of high tumor burden identified by the MRSI study can be faithfully transferred to the images used for treatment planning. METHODS AND MATERIALS: Magnetic resonance spectroscopy imaging studies have been performed on 2 prostate cancer patients using a commercial MRSI system with an endorectal coil and coupling balloon. At the end of each study, we also acquired the MRI of the pelvic region at both the deformed state where the prostate is distorted by the endorectal balloon and the resting state with the endorectal balloon deflated and removed. The task is to find a three-dimensional matrix of transformation vectors for all volume elements that links the two image sets. We have implemented an optimization method to iteratively optimize the transformation vectors using a Newton-Ralphson algorithm. The objective function is based on the mutual information. The distorted images using the transformation vectors are compared with the images acquired at the resting conditions. RESULTS AND DISCUSSION: The algorithm is capable of performing the registration automatically without the need for intervention. It does not require manual contouring of the organs. By applying the algorithm to multiple image sets of different patients, we found a good agreement between the images transformed from those acquired at the deformed state and those acquired at resting conditions. The computation time required for achieving the registration is in the range of a half-hour (for image size: 256 pixels x 256 pixels x 25 slices). However, the space of registration can be restricted to speed up the process. CONCLUSION: In this article, we described a three-dimensional deformable image registration method to automatically transform images from the deformed imaging state to resting state. Our examples show that this method is feasible and useful to the treatment planning system.

Algorithms↗

PubMed2004

Radiation absorbed dose distribution in a patient treated with yttrium-90 microspheres for hepatocellular carcinoma.

We have implemented a three-dimensional dose calculation technique accounting for dose inhomogeneity within the liver and tumor of a patient treated with 90Y microspheres. Single-photon emission computed tomography (SPECT) images were used to derive the activity distribution within liver. A Monte Carlo calculation was performed to create a voxel dose kernel for the 90Y source. The activity distribution was convolved with the voxel dose kernel to obtain the three-dimensional (3D) radiation absorbed dose distribution. An automated technique was developed to accurately register the computed tomography (CT) and SPECT scans in order to display the 3D dose distribution on the CT scans. In addition, dose-volume histograms were generated to fully analyze the tumor and liver doses. The calculated dose-volume histogram indicated that although the patient was treated to the nominal whole liver dose of 110 Gy, only 16% of the liver and 83% of the tumor received a dose higher than 110 Gy. The mean tumor and liver doses were 163 and 58 Gy, respectively.

Body Burden↗