M Chao

Four‐dimensional cone‐beam computed tomography using an on‐board imager

On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patients respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.

Auto-propagation of contours for adaptive prostate radiation therapy

The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.

Feature-based rectal contour propagation from planning CT to cone beam CT.

The purpose of this work is to develop a novel feature-based registration strategy to automatically map the rectal contours from planning computed tomography (CT) (pCT) to cone beam CT (CBCT). The rectal contours were manually outlined on the pCT. A narrow band with the outlined contour as its interior surface was then constructed, so that we can exclude the volume inside the rectum in the registration process. The corresponding contour in the CBCT was found by using a feature-based registration algorithm, which consists of two steps: (1) automatically searching for control points in the pCT and CBCT based on the features of the surrounding tissue and matching the homologous control points using the scale invariance feature transformation; and (2) using the control points for a thin plate spline transformation to warp the narrow band and mapping the corresponding contours from pCT to CBCT. The proposed contour propagation technique is applied to digital phantoms and clinical cases and, in all cases, the contour mapping results are found to be clinically acceptable. For clinical cases, the method yielded satisfactory results even when there were significant rectal content changes between the pCT and CBCT scans. As a consequence, the accordance between the rectal volumes after deformable registration and the manually segmented rectum was found to be more than 90%. The proposed technique provides a powerful tool for adaptive radiotherapy of prostate, rectal, and gynecological cancers in the future.

Automated Contour Mapping With a Regional Deformable Model

PURPOSE To develop a regional narrow-band algorithm to auto-propagate the contour surface of a region of interest (ROI) from one phase to other phases of four-dimensional computed tomography (4D-CT). METHODS AND MATERIALS The ROI contours were manually delineated on a selected phase of 4D-CT. A narrow band encompassing the ROI boundary was created on the image and used as a compact representation of the ROI surface. A BSpline deformable registration was performed to map the band to other phases. A Mattes mutual information was used as the metric function, and the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm was used to optimize the function. After registration the deformation field was extracted and used to transform the manual contours to other phases. Bidirectional contour mapping was introduced to evaluate the proposed technique. The new algorithm was tested on synthetic images and applied to 4D-CT images of 4 thoracic patients and a head-and-neck Cone-beam CT case. RESULTS Application of the algorithm to synthetic images and Cone-beam CT images indicates that an accuracy of 1.0 mm is achievable and that 4D-CT images show a spatial accuracy better than 1.5 mm for ROI mappings between adjacent phases, and 3 mm in opposite-phase mapping. Compared with whole image-based calculations, the computation was an order of magnitude more efficient, in addition to the much-reduced computer memory consumption. CONCLUSIONS A narrow-band model is an efficient way for contour mapping and should find widespread application in future 4D treatment planning.

Individualized gating windows based on four-dimensional CT information for respiration-gated radiotherapy

The purpose of this work is to relate the gating window and displacement of a moving tumor target and develop a systematic method to individualize the gating window for respiration-gated radiation therapy (RT). As the relationship between patient anatomy and respiration phase is contained in 4D images, we aim to quantify this information and utilize the data to guide gated treatment planning. After 4D image acquisition, the target and organs at risk were delineated manually on the selected gating phase. The contours were propagated automatically onto every phase-specific image set using a control volume-based contour mapping technique. The mean and maximum distances between the contours in the gating phase and each of other phases were evaluated in three dimensions. The gating window was determined in such a way that the residual movement of the target within the window is smaller or equal to the patients setup error. The proposed method was applied to plan the gated treatments of 12 lung cancer patients. As a result of this work, a method to calculate patient-specific gating windows has been developed. The general reference drawn from this study is that, with the aide of 4D images and automated 4D contour propagation, it is feasible to individualize the gating widow selection. As compared with the current practice, the proposed technique has a potential to eliminate the guesswork involved in choosing a gating window and avoid dosimetric error in planning gated RT. In conclusion, individualization of gating windows reduces the subjectivity in respiration-gated RT and improves the treatment of moving targets.

Clinical feasibility of TBI with helical tomotherapy.

Our purpose was to present the clinical feasibility of TBI with helical tomotherapy (HT) in four patients with AML. Treatment planning, delivery, dose verification and summation, toxicity and patient outcomes for each patient are presented. TBI prescription was set in such a manner that 80% of the clinical target volume received 12 Gy in six fractions, at two fractions per day. Dose reconstruction was carried out by recontouring the regions of interest in the daily pretreatment megavoltage computed tomography of each individual fraction and calculating its corresponding dose. A deformable registration model was used for dose summation of all individual fractions. Differences between planned and delivered doses were calculated. Average planned and delivered doses to the regions of interest differed by up to 2.7%. TBI toxicity was limited to radiotherapy oncology group grade 1 dermatitis in all patients and grade 1 headache in one patient. Two patients are alive with no evidence of disease and no GVHD. Two patients died of GVHD, but there was no evidence of disease at the time of death. We conclude that HT simplifies the process of TBI. Dose verification is possible with HT showing small differences between plan and delivered doses.

MRI-based treatment planning with electron density information mapped from CT images: a preliminary study.

Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patients readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3–5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patients treatment with only simulation MRI and any available diagnostic/staging CT data.

Automated contour mapping using sparse volume sampling for 4D radiation therapy

The purpose of this work is to develop a novel strategy to automatically map organ contours from one phase of respiration to all other phases on a four-dimensional computed tomography (4D CT). A region of interest (ROI) was manually delineated by a physician on one phase specific image set of a 4D CT. A number of cubic control volumes of the size of approximately 1 cm were automatically placed along the contours. The control volumes were then collectively mapped to the next phase using a rigid transformation. To accommodate organ deformation, a model-based adaptation of the control volume positions was followed after the rigid mapping procedure. This further adjustment of control volume positions was performed by minimizing an energy function which balances the tendency for the control volumes to move to their correspondences with the desire to maintain similar image features and shape integrity of the contour. The mapped ROI surface was then constructed based on the central positions of the control volumes using a triangulated surface construction technique. The proposed technique was assessed using a digital phantom and 4D CT images of three lung patients. Our digital phantom study data indicated that a spatial accuracy better than 2.5 mm is achievable using the proposed technique. The patient study showed a similar level of accuracy. In addition, the computational speed of our algorithm was significantly improved as compared with a conventional deformable registration-based contour mapping technique. The robustness and accuracy of this approach make it a valuable tool for the efficient use of the available spatial-tempo information for 4D simulation and treatment.

Voxel-based dose reconstruction for total body irradiation with helical tomotherapy

PURPOSE We have developed a megavoltage CT (MVCT)-based dose reconstruction strategy for total body irradiation (TBI) with helical TomoTherapy (HT) using a deformable registration model to account for the patients interfraction changes. The proposed technique serves as an efficient tool for delivered dose verification and, potentially, plan adaptation. METHODS AND MATERIALS Four patients with acute myelogenous leukemia treated with TBI using HT were selected for this study. The prescription was 12 Gy, 2 Gy/fraction, twice per day, given at least 6 h apart. The original plan achieved coverage of 80% of the clinical target volume (CTV) by the 12 Gy isodose surface. MVCTs were acquired prior to each treatment. Regions of interest were contoured on each MVCT. The dose for each fraction was calculated based on the MVCT using the HT planned adaptive station. B-spline deformable registration was conducted to establish voxel-to-voxel correspondence between the MVCT and the planning CT. The resultant deformation vector was employed to map the reconstructed dose from each fraction to the same point as the plan dose, and a voxel-to-voxel summed dose from all six fractions was obtained. The reconstructed dose distribution and its dosimetric parameters were compared with those of the original treatment plan. RESULTS While changes in CTV contours occurred in all patients, the reconstructed dose distribution showed that the dose-volume histogram for CTV coverage was close (<1.5%) to that of the original plan. For sensitive structures, the differences between the reconstructed and the planned doses were less than 3.0%. CONCLUSION Voxel-based dose reconstruction strategy that takes into account interfraction anatomical changes using MVCTs is a powerful tool for treatment verification of the delivered doses. This proposed technique can also be applied to adaptive TBI therapy using HT.

MO‐E‐330A‐07: Knowledge‐Based Auto‐Contouring in 4D Radiation Therapy

Purpose: In this work we develop a strategy of automatic contouring to relieve the effort of organ segmentation in 4D radiation therapy. The method adopts a novel technique of control volumes to achieve robust contour mapping among a series of 4D CTimages. Methods and Materials: For a given patient, segmentation of tumor and sensitive structures was manually performed for one of the breathing phases by a physician. Along the segmented contours a number of small control volumes (∼ 1cm) were selected. To obtain contours on another CT phase we mapped the control volumes collectively to this phase using rigid transformation, which served as a good starting contour for further adjustment. The final positions of mapped control volumes were determined by minimizing the energy function consisting of two terms: intensity similarity between the mapped volumes and the original volumes in the selected phase; elastic potential energy preventing control volumes from movement. The approach was tested with the 4D CTimages of 5 lungcancer patients. Results: For the patients the knowledge‐based approach of automatic contouring worked well even for CTimages with significant deformations. In the lung case the contours have the average error of less than 2mm and a maximum error of 5mm for noisy anatomical structures. A significant reduction of time compared with manual contouring was achieved. Conclusions: The auto‐mapping of contours in 4D radiation therapy was implemented with control volumes. The method provides an efficient way for 4D segmentation with high accuracy.