Fast shading correction for cone-beam CT via partitioned tissue classification.

The quantitative use of cone beam computed tomography (CBCT) in radiation therapy is limited by severe shading artifacts, even with system embedded correction. We recently proposed effective shading correction methods, using planning CT (pCT) as prior information to estimate low-frequency errors in either the projection domain or image domain. In this work, we further improve the clinical practicality of our previous methods by removing the requirement of prior pCT images. Clinical CBCT images are typically composed of a limited number of tissues. By utilizing the low frequency characteristic of shading distribution, we first generate a 'shading-free' template image by enforcing uniformity on CBCT voxels of the same tissue type via a technique named partitioned tissue classification. Only a small subset of voxels in the template image are used in the correction process to generate sparse samples of shading artifacts. Local filtration, a Fourier transform based algorithm, is employed to efficiently process the sparse errors to compute a full-field distribution of shading artifacts for CBCT correction. We evaluate the method's performance using an anthropomorphic pelvis phantom and 6 pelvis patients. The proposed method improves the image quality of CBCT for both phantom and patients to a level matching that of pCT. On the pelvis phantom, the signal non-uniformity (SNU) is reduced from 12.11% to 3.11% and 8.40% to 2.21% on fat and muscle, respectively. The maximum CT number error is reduced from 70 to 10 HU and 73 to 11 HU on fat and muscle, respectively. On patients, the average SNU is reduced from 9.22% to 1.06% and 11.41% to 1.67% on fat and muscle, respectively. The maximum CT number error is reduced from 95 to 9 HU and 88 to 8 HU on fat and muscle, respectively. The typical processing time for one CBCT dataset is about 45 s on a standard PC.

Fast shading correction for cone beam CT in radiation therapy via sparse sampling on planning CT.

PURPOSE: The image quality of cone beam computed tomography (CBCT) is limited by severe shading artifacts, hindering its quantitative applications in radiation therapy. In this work, we propose an image-domain shading correction method using planning CT (pCT) as prior information which is highly adaptive to clinical environment. METHOD: We propose to perform shading correction via sparse sampling on pCT. The method starts with a coarse mapping between the first-pass CBCT images obtained from the Varian TrueBeam system and the pCT. The scatter correction method embedded in the Varian commercial software removes some image errors but the CBCT images still contain severe shading artifacts. The difference images between the mapped pCT and the CBCT are considered as shading errors, but only sparse shading samples are selected for correction using empirical constraints to avoid carrying over false information from pCT. A Fourier-Transform-based technique, referred to as local filtration, is proposed to efficiently process the sparse data for effective shading correction. The performance of the proposed method is evaluated on one anthropomorphic pelvis phantom and 17 patients, who were scheduled for radiation therapy. (The codes of the proposed method and sample data can be downloaded from https://sites.google.com/view/linxicbct) RESULTS: The proposed shading correction substantially improves the CBCT image quality on both the phantom and the patients to a level close to that of the pCT images. On the phantom, the spatial nonuniformity (SNU) difference between CBCT and pCT is reduced from 74 to 1 HU. The root of mean square difference of SNU between CBCT and pCT is reduced from 83 to 10 HU on the pelvis patients, and from 101 to 12 HU on the thorax patients. The robustness of the proposed shading correction is fully investigated with simulated registration errors between CBCT and pCT on the phantom and mis-registration on patients. The sparse sampling scheme of our method successfully avoids false structures in the corrected CBCT even when the maximum registration error is as high as 8 mm. CONCLUSION: We develop an effective shading correction algorithm for CBCT readily implementable on clinical data as a software plug-in without modifications of current imaging hardware and protocol. The algorithm is directly applied on the output images from a commercial CBCT scanner with high computational efficiency and negligible memory burden.

Fractionated Radiosurgery Alone for Thirty-seven Brain Metastases: Not Everything that can be Counted Counts.

There is an ongoing debate as to the maximum number of brain metastases that can safely and practically be treated with a single course of radiosurgery. Despite evidence of durable local control and favorable overall survival when treating 10 or more brain metastases with radiosurgery alone, some institutions and guidelines still limit radiosurgery to an arbitrary number of metastases. As demonstrated by this case report, the number of lesions is not so important when the patient's life expectancy is otherwise good and body tumors are controllable. In the current era of effective targeted therapies, multi-year survival with brain metastases is increasingly common. Treating 37 brain metastases simultaneously in a five-fraction stereotactic course is technically feasible and in this case, resulted in 100% local and distant control in the brain for 18 months ongoing without any additional brain radiation. We discuss patient selection factors when treating large numbers of brain metastases, and present a possible class solution when using five daily fractions of 6 Gray (Gy) with a single plan and isocenter.

Dosimetric impact of a CT metal artefact suppression algorithm for proton, electron and photon therapies.

Accurate dose calculation is essential to precision radiation treatment planning and this accuracy depends upon anatomic and tissue electron density information. Modern treatment planning inhomogeneity corrections use x-ray CT images and calibrated scales of tissue CT number to electron density to provide this information. The presence of metal in the volume scanned by an x-ray CT scanner causes metal induced image artefacts that influence CT numbers and thereby introduce errors in the radiation dose distribution calculated. This paper investigates the dosimetric improvement achieved by a previously proposed x-ray CT metal artefact suppression technique when the suppressed images of a patient with bilateral hip prostheses are used in commercial treatment planning systems for proton, electron or photon therapies. For all these beam types, this clinical image and treatment planning study reveals that the target may be severely underdosed if a metal artefact-contaminated image is used for dose calculations instead of the artefact suppressed one. Of the three beam types studied, the metal artefact suppression is most important for proton therapy dose calculations, intermediate for electron therapy and least important for x-ray therapy but still significant. The study of a water phantom having a metal rod simulating a hip prosthesis indicates that CT numbers generated after image processing for metal artefact suppression are accurate and thus dose calculations based on the metal artefact suppressed images will be of high fidelity.

Reconstruction of electron spectra from depth doses with adaptive regularization.

Electron spectral reconstruction of medical accelerators from measured depth doses is a practical method for providing the input initial phase space distribution at the patient surface that is required by Monte Carlo treatment planning systems. The posed inverse problem of spectral reconstruction is ill conditioned and this may lead to nonphysical oscillations in the reconstructed spectra. Use of a variational method of solution with a regularization technique removes the oscillations but tends to smooth the sharp (deltalike) energy peak that is a common feature in electron spectra generated by medical accelerators. Because the sharp peak contains a large percentage of the electrons in the spectrum, an accurate estimate of the peak width, height and position is critical to the success of the technique for spectrum reconstruction with regularization. We propose use of an adaptive regularization term as a special form of the general Tichonov regularization function. The variational method with the adaptive regularization term is applied to reconstruct electron spectra for the 6, 9, and 18 MeV electron beams of a Varian Clinac 2100C accelerator and proves to be a very simple, effective and accurate approach. Results using this variational method with adaptive regularization almost perfectly reconstruct electron spectra from depth dose distributions.

X-ray CT high-density artefact suppression in the presence of bones.

This paper presents a novel method of reducing x-ray CT high-density artefacts generated by metal objects when abundant bone structures are present in the region of interest. This method has an advantage over previously proposed methods since it heavily suppresses the metal artefacts without introducing extra bone artefacts. The method of suppression requires that bone pixels are isolated and segmented by thresholding. Then artificial CT numbers are assigned to the bone pixels so that their projection profiles are smooth and thus can be properly simulated by a polynomial interpolation. The projection profile of the metal object is then removed to fully suppress the artefacts. The resulting processed profile is fed to a reconstruction routine and the previously preserved bone pixels added back. The new method utilizes two important features of the CT image with metal artefacts: (a) metal and bone pixels are not severely affected by the high-density artefacts and (b) the high-density artefacts can be located in specific projection channels in the profile domain, although they are spread out in the image domain. This suppression method solves the problem of CT image artefacts arising from metal objects in the body. It has the potential to greatly improve diagnostic CT imaging in the presence of these objects and treatment planning that utilizes CT for patients with metal applicators (e.g., brachytherapy for cervix cancer and prostate cryotherapy).

X-ray CT high-density artefact suppression in cryosurgery.

Advantages of x-ray CT for imaging guidance of cryosurgery include 3D visualization of frozen and unfrozen tissue and calibration of temperature in the tissue water-ice interface (0-10 degrees C) to Hounsfield units. However, use of x-ray CT images and their thermal calibration can be compromised by the cryoprobes generating high-density streak artefacts. A new subtraction technique for artefact suppression is proposed and tested in prostate cryosurgery simulations. By subtracting the measured CT x-ray projection profile without cryoprobes from the profile with cryoprobes plus iceballs, one obtains the combined profile of the cryoprobes and a low value background. Polynomial interpolation to obtain the background profile allows its addition to the original profile without probes. The result may then be fed to a conventional filtered back-projection routine to reconstruct the probe-free image. Finally the cryoprobe pixels in the originally constructed image with probes and iceballs are added back to the probe-free image to get the final artefact-suppressed image. The major advantage of this subtraction technique is that it can successfully suppress the high-density artefacts in bone-abundant body regions such as the pelvis. X-ray CT images of cryoprobe arrays in a homogeneous gelatin phantom and the pelvic region of an anthropomorphic Rando phantom containing a human skeleton were generated. After suppression, cryoprobe metal artefact streaks are reduced and visualization of the positions and dimensions of the cryoprobes are well preserved.