Dataset Information

Evaluation of a metal artifact reduction algorithm in CT studies used for proton radiotherapy treatment planning.

ABSTRACT: Metal objects in the body such as hip prostheses cause artifacts in CT images. When CT images degraded by artifacts are used for treatment planning of radiotherapy, the artifacts can yield inaccurate dose calculations and, for particle beams, erroneous penetration depths. A metal artifact reduction software (O-MAR) installed on a Philips Brilliance Big Bore CT has been tested for applications in treatment planning of proton radiotherapy. Hip prostheses mounted in a water phantom were used as test objects. Images without metal objects were acquired and used as reference data for the analysis of artifact-affected regions outside of the metal objects in both the O-MAR corrected and the uncorrected images. Water equivalent thicknesses (WET) based on proton stopping power data were calculated to quantify differences in the calculated proton beam penetration for the different image sets. The WET to a selected point of interest between the hip prostheses was calculated for several beam directions of clinical relevance. The results show that the calculated differences in WET relative to the reference case were decreased when the O-MAR algorithm was applied. WET differences up to 2.0 cm were seen in the uncorrected case while, for the O-MAR corrected case, the maximum difference was decreased to 0.4 cm. The O-MAR algorithm can significantly improve the accuracy in proton range calculations. However, there are some residual effects, and the use of proton beam directions along artifact streaks should only be used with caution and appropriate margins.

SUBMITTER: Andersson KM

PROVIDER: S-EPMC5711074 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Evaluation of a metal artifact reduction algorithm in CT studies used for proton radiotherapy treatment planning.

Andersson Karin M KM Ahnesjö Anders A Vallhagen Dahlgren Christina C

Journal of applied clinical medical physics 20140908 5

Metal objects in the body such as hip prostheses cause artifacts in CT images. When CT images degraded by artifacts are used for treatment planning of radiotherapy, the artifacts can yield inaccurate dose calculations and, for particle beams, erroneous penetration depths. A metal artifact reduction software (O-MAR) installed on a Philips Brilliance Big Bore CT has been tested for applications in treatment planning of proton radiotherapy. Hip prostheses mounted in a water phantom were used as tes ...[more]

PMID: 25207572

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Project description:PurposeAs computed tomography (CT) imaging is the most commonly used modality for treatment planning in radiation therapy, metal artifacts in the planning CT images may complicate the target delineation and reduce the dose calculation accuracy. Although current CT scanners do provide certain correction steps, it is a common understanding that there is not a universal solution yet to the metal artifact reduction (MAR) in general. Particularly noting the importance of MAR for radiation treatment planning, we propose a novel MAR method in this work that recruits an additional tilted CT scan and synthesizes nearly metal-artifact-free CT images.MethodsThe proposed method is based on the facts that the most pronounced metal artifacts in CT images show up along the x-ray beam direction traversing multiple metallic objects and that a tilted CT scan can provide complementary information free of such metal artifacts in the earlier scan. Although the tilted CT scan would contain its own metal artifacts in the images, the artifacts may manifest in a different fashion leaving a chance to concatenate the two CT images with the metal artifacts much suppressed. We developed an image processing technique that uses the structural similarity (SSIM) for suppressing the metal artifacts. On top of the additional scan, we proposed to use an existing MAR method for each scan if necessary to further suppress the metal artifacts.ResultsThe proposed method was validated by a simulation study using the pelvic region of an XCAT numerical phantom and also by an experimental study using the head part of the Rando phantom. The proposed method was found to effectively reduce the metal artifacts. Quantitative analyses revealed that the proposed method reduced the mean absolute percentages of the error by up to 86% and 89% in the simulation and experimental studies, respectively.ConclusionsIt was confirmed that the proposed method, using complementary information acquired from an additional tilted CT scan, can provide nearly metal-artifact-free images for the treatment planning.

Project description:Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions.A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach.Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties.The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

Project description:Metal artifacts resulting from coiling or clipping of a brain aneurysm degrade image quality and reduce diagnostic usefulness of computed tomography perfusion CTP. Our aim was to assess the diagnostic value of the iterative metal artifact reduction algorithm (iMAR) in CTP studies after coiling or clipping of ruptured intracranial aneurysms. Fifty-eight CTP exams performed in 32 patients were analysed. iMAR was applied to the source images from the CT scanner. Perfusion maps were generated from datasets both with and without iMAR, and both datasets were compared qualitatively and quantitatively. Qualitative analysis included evaluation of intensity of artifacts, image quality, presence of new artifacts, and the reader's confidence in their diagnosis as well as diagnostic impression. Quantitative analysis included evaluation of tissue attenuation curves, evaluation of region of interest (ROI)-based measurement of perfusion values at levels that do and do not contain metal, compared to previously published reference ranges of perfusion values. Our results showed that application of iMAR reduced artifacts and significantly improved image quality. New artifacts were observed adjacent to metallic implants, but did not limit the evaluation of other regions. After correction for artifact readers' confidence in their diagnosis increased from 41.3% to 87.9%, and the diagnostic impression changed in 31% of the exams. No difference between tissue attenuation curves was found. For slices without metal, no difference was noted between values measured before and after iMAR, and the total number of ROIs in the reference range of perfusion values was unchanged. At the level of the metal implant, 89.85% of ROIs obtained before using iMAR showed calculation errors. After using iMAR, only 1.7% showed errors. Before iMAR 3.1% of values were in the reference range, whereas after iMAR this increased to 33.1%. In conclusion, our results show that iMAR is an excellent tool for reducing artifacts in CTP. It is therefore recommended for use in clinical practice, particularly when severe artifacts are present, or when hypoperfusion is suspected at the level of the coil or clip. After the application of iMAR, the perfusion values at the level of the metal can be better calculated, but may not lie within the reference range; therefore, quantitative analysis at the level of artifacts is not advisable.

Project description:Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning.Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared.Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The γ pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P = 0.0022); bladder (2.15 vs 3.7, P = 0.0023); prostate and seminal vesicles∕vagina (1.3 vs 3.275, P = 0.0020); rectum (2.8 vs 3.9, P = 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8∕10), the average CT Hounsfield numbers of the prostate∕vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High γ pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements.Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists' confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.

Dataset Information

Evaluation of a metal artifact reduction algorithm in CT studies used for proton radiotherapy treatment planning.

Publications

Evaluation of a metal artifact reduction algorithm in CT studies used for proton radiotherapy treatment planning.

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