Computed Tomography Artifacts Research Articles

Dual-energy CT with virtual monochromatic images and metal artifact reduction software for reducing metallic dental artifacts.

Background Metallic dental prostheses may degrade image quality on head and neck computed tomography (CT). However, there is little information available on the use of dual-energy CT (DECT) and metal artifact reduction software (MARS) in the head and neck regions to reduce metallic dental artifacts. Purpose To assess the usefulness of DECT with virtual monochromatic imaging and MARS to reduce metallic dental artifacts. Material and Methods DECT was performed using fast kilovoltage (kV)-switching between 80-kV and 140-kV in 20 patients with metallic dental prostheses. CT data were reconstructed with and without MARS, and with synthesized monochromatic energy in the range of 40-140-kiloelectron volt (keV). For quantitative analysis, the artifact index of the tongue, buccal, and parotid areas was calculated for each scan. For qualitative analysis, two radiologists evaluated 70-keV and 100-keV images with and without MARS for tongue, buccal, parotid areas, and metallic denture. The locations and characteristics of the MARS-related artifacts, if any, were also recorded. Results DECT with MARS markedly reduced metallic dental artifacts and improved image quality in the buccal area ( P < 0.001) and the tongue ( P < 0.001), but not in the parotid area. The margin and internal architecture of the metallic dentures were more clearly delineated with MARS ( P < 0.001) and in the higher-energy images than in the lower-energy images ( P = 0.042). MARS-related artifacts most commonly occurred in the deep center of the neck. Conclusion DECT with MARS can reduce metallic dental artifacts and improve delineation of the metallic prosthesis and periprosthetic region.

Full and hybrid iterative reconstruction to reduce artifacts in abdominal CT for patients scanned without arm elevation.

Background Abdominal computed tomography (CT) without arm elevation is associated with degraded image quality due to streak artifacts. Purpose To compare the degree of streak artifacts in abdominal CT images without arm elevation between full iterative reconstruction (IR), hybrid IR, and filtered back projection (FBP) using two commercially available scanners. Material and Methods First, a phantom study simulating CT examination without arm elevation was performed. Second, unenhanced axial images of 33 patients (17 and 16 patients for each vendor) who underwent CT without arm elevation were reconstructed with full IR, hybrid IR and FBP. A radiologist placed 50 parallel lines with lengths of 50 pixels vertical to the streaks and quantitatively evaluated the images for streak artifacts in the phantom study. Two radiologists evaluated the images of patients for streak artifacts (on the liver and the kidney) and diagnostic acceptability using a four-point scale. Results The phantom study indicated that full IR algorithms were more effective than FBP in reducing streak artifacts. In the clinical patient study, streak artifacts were significantly more reduced with full IR compared with FBP in both the liver and kidney ( P < 0.012). Streak artifact reduction was limited with hybrid IR. Model-based iterative reconstruction (MBIR) (one of the full IR algorithms) provided diagnostically more acceptable image quality ( P < 0.016) compared with FBP. Conclusion In abdominal CT without arm elevation, full IR enabled a more efficient streak artifact reduction compared with FBP and MBIR was associated with diagnostically more acceptable images.

Experimental validation of a multi-energy x-ray adapted scatter separation method

Both in radiography and computed tomography (CT), recently emerged energy-resolved x-ray photon counting detectors enable the identification and quantification of individual materials comprising the inspected object. However, the approaches used for these operations require highly accurate x-ray images. The accuracy of the images is severely compromised by the presence of scattered radiation, which leads to a loss of spatial contrast and, more importantly, a bias in radiographic material imaging and artefacts in CT. The aim of the present study was to experimentally evaluate a recently introduced partial attenuation spectral scatter separation approach (PASSSA) adapted for multi-energy imaging. For this purpose, a prototype x-ray system was used. Several radiographic acquisitions of an anthropomorphic thorax phantom were performed. Reference primary images were obtained via the beam-stop (BS) approach. The attenuation images acquired from PASSSA-corrected data showed a substantial increase in local contrast and internal structure contour visibility when compared to uncorrected images. A substantial reduction of scatter induced bias was also achieved. Quantitatively, the developed method proved to be in relatively good agreement with the BS data. The application of the proposed scatter correction technique lowered the initial normalized root-mean-square error (NRMSE) of 45% between the uncorrected total and the reference primary spectral images by a factor of 9, thus reducing it to around 5%.

Approaches to reducing photon dose calculation errors near metal implants.

Dose calculation errors near metal implants are caused by limitations of the dose calculation algorithm in modeling tissue/metal interface effects as well as density assignment errors caused by imaging artifacts. The purpose of this study was to investigate two strategies for reducing dose calculation errors near metal implants: implementation of metal-based energy deposition kernels in the convolution/superposition (C/S) dose calculation method and use of metal artifact reduction methods for computed tomography (CT) imaging. Both error reduction strategies were investigated using a simple geometric slab phantom with a rectangular metal insert (composed of titanium or Cerrobend), as well as two anthropomorphic phantoms (one with spinal hardware and one with dental fillings), designed to mimic relevant clinical scenarios. To assess the dosimetric impact of metal kernels, the authors implemented titanium and silver kernels in a commercial collapsed cone C/S algorithm. To assess the impact of CT metal artifact reduction methods, the authors performed dose calculations using baseline imaging techniques (uncorrected 120 kVp imaging) and three commercial metal artifact reduction methods: Philips Healthcare's o-mar, GE Healthcare's monochromatic gemstone spectral imaging (gsi) using dual-energy CT, and gsi with metal artifact reduction software (mars) applied. For the simple geometric phantom, radiochromic film was used to measure dose upstream and downstream of metal inserts. For the anthropomorphic phantoms, ion chambers and radiochromic film were used to quantify the benefit of the error reduction strategies. Metal kernels did not universally improve accuracy but rather resulted in better accuracy upstream of metal implants and decreased accuracy directly downstream. For the clinical cases (spinal hardware and dental fillings), metal kernels had very little impact on the dose calculation accuracy (<1.0%). Of the commercial CT artifact reduction methods investigated, the authors found that o-mar was the most consistent method, resulting in either improved dose calculation accuracy (dental case) or little impact on calculation accuracy (spine case). gsi was unsuccessful at reducing the severe artifacts caused by dental fillings and had very little impact on calculation accuracy. gsi with mars on the other hand gave mixed results, sometimes introducing metal distortion and increasing calculation errors (titanium rectangular implant and titanium spinal hardware) but other times very successfully reducing artifacts (Cerrobend rectangular implant and dental fillings). Though successful at improving dose calculation accuracy upstream of metal implants, metal kernels were not found to substantially improve accuracy for clinical cases. Of the commercial artifact reduction methods investigated, o-mar was found to be the most consistent candidate for all-purpose CT simulation imaging. The mars algorithm for gsi should be used with caution for titanium implants, larger implants, and implants located near heterogeneities as it can distort the size and shape of implants and increase calculation errors.

Unusual Brain Computed Tomography Artifact in Cerebellum Mimicking Hemorrhage: A Case Report

Unusual Brain Computed Tomography Artifact in Cerebellum Mimicking Hemorrhage: A Case Report

External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma

ABSTRACTBackground. Oropharyngeal squamous cell carcinoma (OPSCC) is one of the fastest growing disease sites of head and neck cancers. A recently described radiomic signature, based exclusively on pre-treatment computed tomography (CT) imaging of the primary tumor volume, was found to be prognostic in independent cohorts of lung and head and neck cancer patients treated in the Netherlands. Here, we further validate this signature in a large and independent North American cohort of OPSCC patients, also considering CT artifacts.Methods. A total of 542 OPSCC patients were included for which we determined the prognostic index (PI) of the radiomic signature. We tested the signature model fit in a Cox regression and assessed model discrimination with Harrell's c-index. Kaplan-Meier survival curves between high and low signature predictions were compared with a log-rank test. Validation was performed in the complete cohort (PMH1) and in the subset of patients without (PMH2) and with (PMH3) visible CT artifacts within the delineated tumor region.Results. We identified 267 (49%) patients without and 275 (51%) with visible CT artifacts. The calibration slope (β) on the PI in a Cox proportional hazards model was 1.27 (H0: β = 1, p = 0.152) in the PMH1 (n = 542), 0.855 (H0: β = 1, p = 0.524) in the PMH2 (n = 267) and 1.99 (H0: β = 1, p = 0.002) in the PMH3 (n = 275) cohort. Harrell's c-index was 0.628 (p = 2.72e-9), 0.634 (p = 2.7e-6) and 0.647 (p = 5.35e-6) for the PMH1, PMH2 and PMH3 cohort, respectively. Kaplan-Meier survival curves were significantly different (p < 0.05) between high and low radiomic signature model predictions for all cohorts.Conclusion. Overall, the signature validated well using all CT images as-is, demonstrating a good model fit and preservation of discrimination. Even though CT artifacts were shown to be of influence, the signature had significant prognostic power regardless if patients with CT artifacts were included.

CT chest and gantry rotation time: does the rotation time influence image quality?

Computed tomography (CT) gantry rotation time is one factor influencing image quality. Until now, there has been no report investigating the influence of gantry rotation time on chest CT image quality. To investigate the influence of faster gantry rotation time on image quality and subjective and objective image parameters in chest CT imaging. Chest CT scans from 160 patients were examined in this study. All scans were performed using a single-source mode (collimation, 128 × 0.6 mm; pitch, 1.2) on a dual-source CT scanner. Only gantry rotation time was modified, while other CT parameters were kept stable for each scan (120 kV/110 reference mAs). Patients were divided into four groups based on rotation time: group 1, 1 s/ rotation (rot); group 2, 0.5 s/rot; group 3, 0.33 s/rot; group 4, 0.28 s/rot. Two blinded radiologists subjectively compared CT image quality, noise, and artifacts, as well as radiation exposure, from all groups. For objective comparison, all image datasets were analyzed by a radiologist with 5 years of experience concerning objective measurements as well as signal-to-noise ratio (SNR). We found that faster gantry rotation times (0.28 s/rot and 0.33 s/rot) resulted in more streak artifacts, image noise, and decreased image quality. However, there was no significant difference in radiation exposure between faster and slower rotation times (P > 0.7). Faster CT gantry rotation reduces scan time and motion artifacts. However, accelerating rotation time increases image noise and streak artifacts. Therefore, a slower CT gantry rotation speed is still recommended for higher image quality in some cases.

ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography

In medical and industrial applications of computed tomography (CT) imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP) algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM) can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ 0 gradient minimization for limited-angle CT in this paper. The ℓ 0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR) and normalized root mean square distance (NRMSD), it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001). From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed artifacts nearby edges simultaneously.

MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR. Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.

Cervical Spine Computed Tomography Imaging Artifact Affecting Clinical Decision-Making in the Traumatized Patient

CT scanning is an important tool in the evaluation of trauma patients. We review a case involving a trauma patient in which a cervical spine computed tomography (CT) artifact affected decision-making by physicians. The CT artifact mimicked bilateral dislocated facets (51-B1.1). On the basis of CT findings, the patient was transferred to a different hospital for evaluation. Discrepancy between the primary CT scan and patient physical exam prompted secondary CT scans and X-ray evaluation; neither of these studies showed osseous abnormalities. This case reinforces the necessity for physicians to formulate their diagnosis based upon multiple areas of information including physical examination, plain x-ray and subsequent advanced imaging, rather than relying solely on advanced imaging.

Characterization of indeterminate spleen lesions in primary CT after blunt abdominal trauma: potential role of MR imaging.

The purpose of this study was to determine the value of magnetic resonance imaging (MRI) for characterization of indeterminate spleen lesions in primary computed tomography (CT) of patients with blunt abdominal trauma. Twenty-five consecutive patients (8 female, 17 male, mean age 51.6 ± 22.4 years) with an indeterminate spleen lesion diagnosed at CT after blunt abdominal trauma underwent MRI with T2- and T1-weighted images pre- and post-contrast material administration. MRI studies were reviewed by two radiologists. Age, gender, injury mechanism, injury severity score (ISS), management of patients, time interval between CT and MRI, and length of hospital stay were included into the analysis. Patient history, clinical history, imaging, and 2-month clinical outcome including review of medical records and telephone interviews served as reference standard. From the 25 indeterminate spleen lesions in CT, 11 (44 %) were traumatic; nine (36 %) were non-traumatic (pseudocysts, n=5; hemangioma, n=4) and five proven to represent artifacts in CT. The ISS (P<0.001) and the length of hospital stay (P=0.03) were significantly higher in patients with spleen lesions as compared with those without. All other parameters were similar among groups (all, P>0.05). The MRI features ill-defined lesion borders, variable signal intensity on T1- and T2-weighted images depending on the age of the hematoma, focal contrast enhancement indicating traumatic pseudoaneurysm, perilesional contrast enhancement, and edema were most indicative for traumatic spleen lesions. As compared with CT (2/25), MRI (5/25) better depicted thin subcapsular hematomas as indicator of traumatic spleen injury. In conclusion, MRI shows value for characterizing indeterminate spleen lesions in primary CT after blunt abdominal trauma.

Implications of CT noise and artifacts for quantitative 99mTc SPECT/CT imaging

This paper evaluates the effects of computed tomography (CT) image noise and artifacts on quantitative single-photon emission computed-tomography (SPECT) imaging, with the aim of establishing an appropriate range of CT acquisition parameters for low-dose protocols with respect to accurate SPECT attenuation correction (AC). SPECT images of two geometric and one anthropomorphic phantom were reconstructed iteratively using CT scans acquired at a range of dose levels (CTDIvol = 0.4 to 46 mGy). Resultant SPECT image quality was evaluated by comparing mean signal, background noise, and artifacts to SPECT images reconstructed using the highest dose CT for AC. Noise injection was performed on linear-attenuation (μ) maps to determine the CT noise threshold for accurate AC. High levels of CT noise (σ ∼ 200-400 HU) resulted in low μ-maps noise (σ ∼ 1%-3%). Noise levels greater than ∼ 10% in 140 keV μ-maps were required to produce visibly perceptible increases of ∼ 15% in (99m)Tc SPECT images. These noise levels would be achieved at low CT dose levels (CTDIvol = 4 μGy) that are over 2 orders of magnitude lower than the minimum dose for diagnostic CT scanners. CT noise could also lower (bias) the expected μ values. The relative error in reconstructed SPECT signal trended linearly with the relative shift in μ. SPECT signal was, on average, underestimated in regions corresponding with beam-hardening artifacts in CT images. Any process that has the potential to change the CT number of a region by ∼ 100 HU (e.g., misregistration between CT images and SPECT images due to motion, the presence of contrast in CT images) could introduce errors in μ140 keV on the order of 10%, that in turn, could introduce errors on the order of ∼ 10% into the reconstructed (99m)Tc SPECT image. The impact of CT noise on SPECT noise was demonstrated to be negligible for clinically achievable CT parameters. Because CT dose levels that affect SPECT quantification is low (CTDIvol ∼ 4 μGy), the low dose limit for the CT exam as part of SPECT/CT will be guided by CT image quality requirements for anatomical localization and artifact reduction. A CT technique with higher kVp in combination with lower mAs is recommended when low-dose CT images are used for AC to minimize beam-hardening artifacts.

An optimized computed tomography protocol for metallic gunshot head trauma in a seal model.

Computed tomography (CT) is commonly used to assess animals with head trauma. However, strongly attenuating objects such as metallic gunshot cause artifacts that may make accurate localization of shrapnel pieces difficult. The purpose of this study was to develop an optimized CT protocol for minimizing metal artifacts in an animal model of gunshot head trauma. A cadaver head of a stranded Gray seal (Halichoerus grypus) was shot post-mortem with a 0.223-inch caliber rifle. The head was frozen, thawed, and scanned using a multislice CT scanner and protocols with varying acquisition and reconstruction parameters. Scans were acquired with and without use of the scanner's proprietary Extended CT Scale (ECTS) mode and beam hardening reduction (Posterior Fossa Optimization [PFO]) filter. Window/level display settings were also varied. For each protocol and each of five selected metallic shrapnel pieces, a single observer measured combined metal halo artifact and shrapnel area using a hand-traced region of interest. The number of hypo- and hyper-attenuating streak artifacts was also recorded. Measurements were repeated for three different reading sessions. Metal CT artifacts were minimized with a high-frequency image reconstruction algorithm and a wide window setting. Further artifact reduction was achieved with a proprietary ECTS raw data reconstruction technique and a very wide window. This enabled a more confident evaluation of surrounding bone. On the other hand, these techniques are unfortunately not effective under conditions of soft tissue evaluation. Increasing tube voltage and use of a proprietary PFO filter did not yield a significant reduction in metal artifacts.

Prior‐based artifact correction (PBAC) in computed tomography

Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.

Reduction of metal artifacts from alloy hip prostheses in computer tomography.

The objective of this study was to evaluate the feasibility of reducing artifacts from large metal implants with gemstone spectral imaging (GSI) and metal artifact reduction software (MARS). Twenty-three in-vivo cobalt-chromium-molybdenum alloy total hip prostheses were prospectively scanned by fast kV-switching GSI between 80 and 140 kVp. The computed tomography images were reconstructed with monochromatic energy and with/without MARS. Both subjective and objective measurements were performed to assess the severity of metal artifacts. Increasing photon energy was associated with reduced metal artifacts in GSI images (P < 0.001). Combination of GSI with MARS further diminished the metal artifacts (P < 0.001). Artifact reduction at 3 anatomical levels (femoral head, neck, and shaft) were evaluated, with data showing that GSI and MARS could reduce metal artifacts at all 3 levels (P = 0.011, P < 0.001, and P = 0.003, respectively). Nevertheless, in certain cases, GSI without MARS produced more realistic images for the clinical situation. Proper usage of GSI with/without MARS could reduce the computed tomography artifacts of large metal parts and improve the radiological evaluation of postarthroplasty patients.

Reduction of dental metallic artefacts in CT: Value of a newly developed algorithm for metal artefact reduction (O-MAR)

To evaluate the image quality of O-MAR (Metal Artifact Reduction for Orthopedic Implants) for dental metal artefact reduction. This prospective study received institutional review board approval and written informed consent was obtained. Thirty patients who had dental implants or dental fillings were included in this study. Computed tomography (CT) images were obtained through the oral cavity and neck during the portal venous phase. The system reconstructed the O-MAR-processed images in addition to the uncorrected images. CT attenuation and image noise of the soft tissue of the oral cavity were compared between the O-MAR and the uncorrected images. Qualitative analysis was undertaken between the two image groups. The image noise of the O-MAR images was significantly lower than that of the uncorrected images (p < 0.01). O-MAR offered plausible attenuations of soft tissue compared with non-O-MAR. Better qualitative scores were obtained in the streaking artefacts and the degree of depiction of the oral cavity with O-MAR compared with non-O-MAR. O-MAR enables the depiction of structures in areas in which this was not previously possible due to dental metallic artefacts in qualitative image analysis. O-MAR images may have a supplementary role in addition to uncorrected images in oral diagnosis.

4D CT lung ventilation images are affected by the 4D CT sorting method.

Four-dimensional (4D) computed tomography (CT) ventilation imaging is a novel promising technique for lung functional imaging. The current standard 4D CT technique using phase-based sorting frequently results in artifacts, which may deteriorate the accuracy of ventilation imaging. The purpose of this study was to quantify the variability of 4D CT ventilation imaging due to 4D CT sorting. 4D CT image sets from nine lung cancer patients were each sorted by the phase-based method and anatomic similarity-based method, designed to reduce artifacts, with corresponding ventilation images created for each method. Artifacts in the resulting 4D CT images were quantified with the artifact score which was defined based on the difference between the normalized cross correlation for CT slices within a CT data segment and that for CT slices bordering the interface between adjacent CT data segments. The ventilation variation was quantified using voxel-based Spearman rank correlation coefficients for all lung voxels, and Dice similarity coefficients (DSC) for the spatial overlap of low-functional lung volumes. Furthermore, the correlations with matching single-photon emission CT (SPECT) ventilation images (assumed ground truth) were evaluated for three patients to investigate which sorting method provides higher physiologic accuracy. Anatomic similarity-based sorting reduced 4D CT artifacts compared to phase-based sorting (artifact score, 0.45 ± 0.14 vs 0.58 ± 0.24, p = 0.10 at peak-exhale; 0.63 ± 0.19 vs 0.71 ± 0.31, p = 0.25 at peak-inhale). The voxel-based correlation between the two ventilation images was 0.69 ± 0.26 on average, ranging from 0.03 to 0.85. The DSC was 0.71 ± 0.13 on average. Anatomic similarity-based sorting yielded significantly fewer lung voxels with paradoxical negative ventilation values than phase-based sorting (5.0 ± 2.6% vs 9.7 ± 8.4%, p = 0.05), and improved the correlation with SPECT ventilation regionally. The variability of 4D CT ventilation imaging due to 4D CT sorting was moderate overall and substantial in some cases, suggesting that 4D CT artifacts are an important source of variations in 4D CT ventilation imaging. Reduction of 4D CT artifacts provided more physiologically convincing and accurate ventilation estimates. Further studies are needed to confirm this result.

Dosimetric accuracy of proton therapy for chordoma patients with titanium implants

To investigate dosimetric errors in proton therapy treatment planning due to titanium implants, and to determine how these affect postoperative passively scattered proton therapy for chordoma patients with orthopedic hardware. The presence of titanium hardware near the tumor may affect the dosimetric accuracy of proton therapy. Artifacts in the computed tomography (CT) scan can cause errors in the proton stopping powers used for dose calculation, which are derived from CT numbers. Also, clinical dose calculation algorithms may not accurately simulate proton beam transport through the implants, which have very different properties as compared to human tissue. The authors first evaluated the impact of these two main issues. Dose errors introduced by metal artifacts were studied using phantoms with and without titanium inserts, and patient scans on which a metal artifact reduction method was applied. Pencil-beam dose calculations were compared to models of nuclear interactions in titanium and Monte Carlo simulations. Then, to assess the overall impact on treatment plans for chordoma, the authors compared the original clinical treatment plans to recalculated dose distributions employing both metal artifact reduction and Monte Carlo methods. Dose recalculations of clinical proton fields showed that metal artifacts cause range errors up to 6 mm distal to regions affected by CT artifacts. Monte Carlo simulations revealed dose differences >10% in the high-dose area, and range differences up to 10 mm. Since these errors are mostly local in nature, the large number of fields limits the impact on target coverage in the chordoma treatment plans to a small decrease of dose homogeneity. In the presence of titanium implants, CT metal artifacts and the approximations of pencil-beam dose calculations cause considerable errors in proton dose calculation. The spatial distribution of the errors however limits the overall impact on passively scattered proton therapy for chordoma.

Changes realized from extended bit‐depth and metal artifact reduction in CT

High-Z material in computed tomography (CT) yields metal artifacts that degrade image quality and may cause substantial errors in dose calculation. This study couples a metal artifact reduction (MAR) algorithm with enhanced 16-bit depth (vs standard 12-bit) to quantify potential gains in image quality and dosimetry. Extended CT to electron density (CT-ED) curves were derived from a tissue characterization phantom with titanium and stainless steel inserts scanned at 90-140 kVp for 12- and 16-bit reconstructions. MAR was applied to sinogram data (Brilliance BigBore CT scanner, Philips Healthcare, v.3.5). Monte Carlo simulation (MC-SIM) was performed on a simulated double hip prostheses case (Cerrobend rods embedded in a pelvic phantom) using BEAMnrc∕Dosxyz (400,000,0000 histories, 6X, 10 × 10 cm(2) beam traversing Cerrobend rod). A phantom study was also conducted using a stainless steel rod embedded in solid water, and dosimetric verification was performed with Gafchromic film analysis (absolute difference and gamma analysis, 2% dose and 2 mm distance to agreement) for plans calculated with Anisotropic Analytic Algorithm (AAA, Eclipse v11.0) to elucidate changes between 12- and 16-bit data. Three patients (bony metastases to the femur and humerus, and a prostate cancer case) with metal implants were reconstructed using both bit depths, with dose calculated using AAA and derived CT-ED curves. Planar dose distributions were assessed via matrix analyses and using gamma criteria of 2%∕2 mm. For 12-bit images, CT numbers for titanium and stainless steel saturated at 3071 Hounsfield units (HU), whereas for 16-bit depth, mean CT numbers were much larger (e.g., titanium and stainless steel yielded HU of 8066.5 ± 56.6 and 13,588.5 ± 198.8 for 16-bit uncorrected scans at 120 kVp, respectively). MC-SIM was well-matched between 12- and 16-bit images except downstream of the Cerrobend rod, where 16-bit dose was ∼6.4% greater than 12-bit. Absolute film dosimetry in a region downstream of a stainless steel rod revealed that 16-bit calculated dose, with and without MAR, agreed more closely with film results (1%-2% less than film) as compared to 12-bit reconstructions (5.6%-6.5% less than film measurements). Gamma analysis revealed that 16-bit dose calculations were better matched to film results than 12-bit (∼10% higher pass rates for 16-bit). Similar results were observed in two patient cases; the largest discrepancy was observed for a femur case where 12-bit doses, both with and without MAR correction, were 6-7 Gy lower (∼17%-20% of the prescription dose) as compared to 16-bit dose calculations. However, when beams are not directly traversing metal, such as a prostate cancer case with bilateral hip prostheses; the impact of 16-bit reconstruction was diminished. These results suggest that it may be desirable to implement 16-bit MAR-corrected images for treatment planning purposes, which can provide a more accurate dosimetric approach coupled with improved visualization by suppression of CT artifacts.

CT, MR, and ultrasound image artifacts from prostate brachytherapy seed implants: The impact of seed size

To investigate the effects of brachytherapy seed size on the quality of x-ray computed tomography (CT), ultrasound (US), and magnetic resonance (MR) images and seed localization through comparison of the 6711 and 9011 (125)I sources. For CT images, an acrylic phantom mimicking a clinical implantation plan and embedded with low contrast regions of interest (ROIs) was designed for both the 0.774 mm diameter 6711 (standard) and the 0.508 mm diameter 9011 (thin) seed models (Oncura, Inc., and GE Healthcare, Arlington Heights, IL). Image quality metrics were assessed using the standard deviation of ROIs between the seeds and the contrast to noise ratio (CNR) within the low contrast ROIs. For US images, water phantoms with both single and multiseed arrangements were constructed for both seed sizes. For MR images, both seeds were implanted into a porcine gel and imaged with pelvic imaging protocols. The standard deviation of ROIs and CNR values were used as metrics of artifact quantification. Seed localization within the CT images was assessed using the automated seed finder in a commercial brachytherapy treatment planning system. The number of erroneous seed placements and the average and maximum error in seed placements were recorded as metrics of the localization accuracy. With the thin seeds, CT image noise was reduced from 48.5 ± 0.2 to 32.0 ± 0.2 HU and CNR improved by a median value of 74% when compared with the standard seeds. Ultrasound image noise was measured at 50.3 ± 17.1 dB for the thin seed images and 50.0 ± 19.8 dB for the standard seed images, and artifacts directly behind the seeds were smaller and less prominent with the thin seed model. For MR images, CNR of the standard seeds reduced on average 17% when using the thin seeds for all different imaging sequences and seed orientations, but these differences are not appreciable. Automated seed localization required an average (±SD) of 7.0 ± 3.5 manual corrections in seed positions for the thin seed scans and 3.0 ± 1.2 manual corrections in seed positions for the standard seed scans. The average error in seed placement was 1.2 mm for both seed types and the maximum error in seed placement was 2.1 mm for the thin seed scans and 1.8 mm for the standard seed scans. The 9011 thin seeds yielded significantly improved image quality for CT and US images but no significant differences in MR image quality.