Impact of CT reconstruction algorithm on auto-segmentation performance.

Model-based iterative reconstruction (MBIR) reduces CT imaging dose while maintaining image quality. However, MBIR reduces noise while preserving edges which may impact intensity-based tasks such as auto-segmentation. This work evaluates the sensitivity of an auto-contouring prostate atlas across multiple MBIR reconstruction protocols and benchmarks the results against filtered back projection (FBP). Images were created from raw projection data for 11 prostate cancer cases using FBP and nine different MBIR reconstructions (3 protocols/3 noise reduction levels) yielding 10 reconstructions/patient. Five bony structures, bladder, rectum, prostate, and seminal vesicles (SVs) were segmented using an auto-segmentation pipeline that renders 3D binary masks for analysis. Performance was evaluated for volume percent difference (VPD) and Dice similarity coefficient (DSC), using FBP as the gold standard. Nonparametric Friedman tests plus post hoc all pairwise comparisons were employed to test for significant differences (P < 0.05) for soft tissue organs and protocol/level combinations. A physician performed qualitative grading of 396 MBIR contours across the prostate, bladder, SVs, and rectum in comparison to FBP using a six-point scale. MBIR contours agreed with FBP for bony anatomy (DSC ≥ 0.98), bladder (DSC ≥ 0.94, VPD < 8.5%), and prostate (DSC = 0.94 ± 0.03, VPD = 4.50 ± 4.77% (range: 0.07-26.39%). Increased variability was observed for rectum (VPD = 7.50 ± 7.56% and DSC = 0.90 ± 0.08) and SVs (VPD and DSC of 8.23 ± 9.86% range (0.00-35.80%) and 0.87 ± 0.11, respectively). Over the all protocol/level comparisons, a significant difference was observed for the prostate VPD between BSPL1 and BSTL2 (adjusted P-value = 0.039). Nevertheless, 300 of 396 (75.8%) of the four soft tissue structures using MBIR were graded as equivalent or better than FBP, suggesting that MBIR offered potential improvements in auto-segmentation performance when compared to FBP. Future work may involve tuning organ-specific MBIR parameters to further improve auto-segmentation performance. Running title: Impact of CT Reconstruction Algorithm on Auto-segmentation Performance.

Improving Bone Mineral Density Assessment Using Spectral Detector CT.

INTRODUCTION: Bone mineral density (BMD) analysis by Dual-Energy x-ray Absorptiometry (DXA) can have some false negatives due to overlapping structures in the projections. Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance for BMD assessment and compared it to DXA and phantomless volumetric bone mineral density (PLvBMD), the latter known to systematically underestimate BMD. DXA is the current standard for BMD assessment, while PLvBMD is an established alternative for opportunistic BMD analysis using CT. Similarly to PLvBMD, spectral data could allow BMD screening opportunistically, without additional phantom calibration. METHODOLOGY: Ten concentrations of dipotassium phosphate (K2HPO4) ranging from 0 to 600 mg/ml, in an acrylic phantom were scanned using SDCT in four different, clinically-relevant scan conditions. Images were processed to estimate the K2HPO4 concentrations. A model representing a human lumbar spine (European Spine Phantom) was scanned and used for calibration via linear regression analysis. After calibration, our method was retrospectively applied to abdominal SDCT scans of 20 patients for BMD assessment, who also had PLvBMD and DXA. Performance of PLvBMD, DXA and our SDCT method were compared by sensitivity, specificity, negative predictive value and positive predictive value for decreased BMD. RESULTS: There was excellent correlation (R2 >0.99, p < 0.01) between true and measured K2HPO4 concentrations for all scan conditions. Overall mean measurement error ranged from -11.5 ± 4.7 mg/ml (-2.8 ± 6.0%) to -12.3 ± 6.3 mg/ml (-4.8 ± 3.0%) depending on scan conditions. Using DXA as a reference standard, sensitivity/specificity for detecting decreased BMD in the scanned patients were 100%/73% using SDCT, 100%/40% using PLvBMD provided T-scores, and 90-100%/40-53% using PLvBMD hydroxyapatite density classifications, respectively. CONCLUSIONS: Our results show excellent sensitivity and high specificity of SDCT for detecting decreased BMD, demonstrating clinical feasibility. Further validation in prospective clinical trials will be required.

Impact of a novel exponential weighted 4DCT reconstruction algorithm.

PURPOSE: This work characterizes a novel exponential 4DCT reconstruction algorithm (EXPO), in phantom and patient, to determine its impact on image quality as compared to the standard cosine-squared weighted 4DCT reconstruction. METHODS: A motion platform translated objects in the superior-inferior (S-I) direction at varied breathing rates (8-20 bpm) and couch pitches (0.06-0.1) to evaluate interplay between parameters. Ten-phase 4DCTs were acquired and data were reconstructed with cosine squared and EXPO weighting. To quantify the magnitude of image blur, objects were translated in the anterior-posterior (A-P) and S-I directions for full-width half maximum (FWHM) analysis between both 4DCT algorithms and a static case. 4DCT sinogram data for 10 patients were retrospectively reconstructed using both weighting factors. Image subtractions elucidated intensity and boundary differences. Subjective image quality grading (presence of image artifacts, noise, spatial resolution (i.e., lung/liver boundary sharpness), and overall image quality) was conducted yielding 200 evaluations. RESULTS: After taking static object size into account, the FWHM of EXPO reconstructions in the A-P direction was 3.3 ± 1.7 mm (range: 0-4.9) as compared to cosine squared 9.8 ± 4.0 mm (range: 2.6-14.4). The FWHM of objects translated in the S-I direction reconstructed with EXPO agreed better with the static FWHM than the cosine-squared reconstructions. Slower breathing periods, faster couch pitches, and intermediate 4DCT phases had the largest reductions of blurring with EXPO. 18 of 60 comparisons of artifacts were improved with EXPO reconstruction, whereas no appreciable changes were observed in image quality scores. In 18 of 20 cases, EXPO provided sharper images although the reduced projections also increased baseline noise. CONCLUSION: Exponential weighted 4DCT offers potential for reducing image blur (i.e., improving image sharpness) in 4DCT with a tendency to reduce artifacts. Future work will involve evaluating the impact on treatment planning including delineation ability and dose calculation.

Machine learning-based dual-energy CT parametric mapping.

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Zeff), relative electron density (ρ e), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

Accuracy of electron density, effective atomic number, and iodine concentration determination with a dual-layer dual-energy computed tomography system.

PURPOSE: This study aimed to quantitate the accuracy of the determination of electron density (ED), effective atomic number (Zeff ), and iodine concentration, directed for more accurate radiation therapy planning, with a new dual-layer dual-energy computed tomography (DL-DECT) system. The dependence of the accuracy of these values on the scan and reconstruction parameters, as well as on the phantom size, was also examined. METHODS: Measurements were performed on a commercial DECT system with a DL detector (IQon Spectral CT, Philips Healthcare), using phantoms with various tissue-equivalent inserts as well as iodine and calcium inserts of different concentrations. The expected values of ED and Zeff for the insert materials were derived from the chemical compositions provided by the vendors. The nominal scan condition for the accuracy measurements was 120 kVp, 20 mGy CTDIvol, 0.812 pitch, 16 × 0.625 mm collimation, and 0.33-second gantry rotation. RESULTS: The median deviation of ED ranged from -0.1% to 1.1% for all Gammex tissue inserts. The median deviation of Zeff ranged from -2.3% to 1.7% for soft tissue and bone inserts and was ≤7% for lung inserts. The absolute deviations for ED and Zeff in lung inserts were within 1% of the ED of water and 1 a.u., respectively. For two different phantom sizes, the ED values agreed to within 0.7% and the Zeff values agreed to within 2%, except for the lung inserts. When the scan parameters were changed from 120 kVp/20 mGy to 140 kVp/30 mGy, the ED differed within [-0.51%, 0.65%] and the Zeff differed within [-1.1%, 0.23%] for all materials except lungs, in which Zeff increased by 2.4%. The accuracy of ED and Zeff measurement at 120 kVp was no worse than that at 140 kVp. For iodine quantitation, the median absolute deviations from the nominal values were up to 0.3 mg/mL for iodine concentrations of 2-20 mg/mL, with an overall median deviation of -0.1 mg/mL. Iodine and calcium were well separated on the ED-Zeff scatter plot, even at the lowest concentrations (2 mg/mL for iodine and 50 mg/mL for calcium). CONCLUSIONS: The accuracy of ED measurement, Zeff determination, and iodine quantitation derived from DL-DECT was demonstrated with phantom measurements. The accuracies were not sensitive to scan and reconstruction parameters, namely tube potential, dose, rotation time, and spectral reconstruction level, especially in the case of electron density.

A comparison study of size-specific dose estimate calculation methods.

BACKGROUND: The size-specific dose estimate (SSDE) has emerged as an improved metric for use by medical physicists and radiologists for estimating individual patient dose. Several methods of calculating SSDE have been described, ranging from patient thickness or attenuation-based (automated and manual) measurements to weight-based techniques. OBJECTIVE: To compare the accuracy of thickness vs. weight measurement of body size to allow for the calculation of the size-specific dose estimate (SSDE) in pediatric body CT. MATERIALS AND METHODS: We retrospectively identified 109 pediatric body CT examinations for SSDE calculation. We examined two automated methods measuring a series of level-specific diameters of the patient's body: method A used the effective diameter and method B used the water-equivalent diameter. Two manual methods measured patient diameter at two predetermined levels: the superior endplate of L2, where body width is typically most thin, and the superior femoral head or iliac crest (for scans that did not include the pelvis), where body width is typically most thick; method C averaged lateral measurements at these two levels from the CT projection scan, and method D averaged lateral and anteroposterior measurements at the same two levels from the axial CT images. Finally, we used body weight to characterize patient size, method E, and compared this with the various other measurement methods. Methods were compared across the entire population as well as by subgroup based on body width. RESULTS: Concordance correlation (ρc) between each of the SSDE calculation methods (methods A-E) was greater than 0.92 across the entire population, although the range was wider when analyzed by subgroup (0.42-0.99). When we compared each SSDE measurement method with CTDIvol, there was poor correlation, ρc<0.77, with percentage differences between 20.8% and 51.0%. CONCLUSION: Automated computer algorithms are accurate and efficient in the calculation of SSDE. Manual methods based on patient thickness provide acceptable dose estimates for pediatric patients <30 cm in body width. Body weight provides a quick and practical method to identify conversion factors that can be used to estimate SSDE with reasonable accuracy in pediatric patients with body width ≥20 cm.

Individually optimized contrast-enhanced 4D-CT for radiotherapy simulation in pancreatic ductal adenocarcinoma.

PURPOSE: To develop an individually optimized contrast-enhanced (CE) 4D-computed tomography (CT) for radiotherapy simulation in pancreatic ductal adenocarcinomas (PDA). METHODS: Ten PDA patients were enrolled. Each underwent three CT scans: a 4D-CT immediately following a CE 3D-CT and an individually optimized CE 4D-CT using test injection. Three physicians contoured the tumor and pancreatic tissues. Image quality scores, tumor volume, motion, tumor-to-pancreas contrast, and contrast-to-noise ratio (CNR) were compared in the three CTs. Interobserver variations were also evaluated in contouring the tumor using simultaneous truth and performance level estimation. RESULTS: Average image quality scores for CE 3D-CT and CE 4D-CT were comparable (4.0 and 3.8, respectively; P = 0.082), and both were significantly better than that for 4D-CT (2.6, P < 0.001). Tumor-to-pancreas contrast results were comparable in CE 3D-CT and CE 4D-CT (15.5 and 16.7 Hounsfield units (HU), respectively; P = 0.21), and the latter was significantly higher than in 4D-CT (9.2 HU, P = 0.001). Image noise in CE 3D-CT (12.5 HU) was significantly lower than in CE 4D-CT (22.1 HU, P = 0.013) and 4D-CT (19.4 HU, P = 0.009). CNRs were comparable in CE 3D-CT and CE 4D-CT (1.4 and 0.8, respectively; P = 0.42), and both were significantly better in 4D-CT (0.6, P = 0.008 and 0.014). Mean tumor volumes were significantly smaller in CE 3D-CT (29.8 cm3, P = 0.03) and CE 4D-CT (22.8 cm3, P = 0.01) than in 4D-CT (42.0 cm3). Mean tumor motion was comparable in 4D-CT and CE 4D-CT (7.2 and 6.2 mm, P = 0.17). Interobserver variations were comparable in CE 3D-CT and CE 4D-CT (Jaccard index 66.0% and 61.9%, respectively) and were worse for 4D-CT (55.6%) than CE 3D-CT. CONCLUSIONS: CE 4D-CT demonstrated characteristics comparable to CE 3D-CT, with high potential for simultaneously delineating the tumor and quantifying tumor motion with a single scan.

How accurate is size-specific dose estimate in pediatric body CT examinations?

BACKGROUND: Size-specific dose estimate is gaining increased acceptance as the preferred index of CT dose in children. However it was developed based on non-clinical data. OBJECTIVE: To compare the accuracy of size-specific dose estimate (SSDE) based on geometric and body weight measures in pediatric chest and abdomen CT scans, versus the more accurate [Formula: see text] (mean SSDE based on water-equivalent diameter). MATERIALS AND METHODS: We retrospectively identified 50 consecutive children (age <18 years) who underwent chest CT examination and 50 children who underwent abdomen CT. We measured anteroposterior diameter (DAP) and lateral diameter (DLAT) at the central slice (of scan length) of each patient and calculated DAP+LAT (anteroposterior diameter plus lateral diameter) and DED (effective diameter) for each patient. We calculated the following in each child: (1) SSDEs based on DAP, DLAT, DAP+LAT, DED, and body weight, and (2) SSDE based on software calculation of mean water-equivalent diameter ([Formula: see text] adopted standard within our study). We used intraclass correlation coefficient (ICC) and Bland-Altman analysis to compare agreement between the SSDEs and [Formula: see text]. RESULTS: Gender and age distribution were similar between chest and abdomen CT groups; mean body weight was 37 kg for both groups, with ranges of 6-130 kg (chest) and 8-107 kg (abdomen). SSDEs had very strong agreement (ICC>0.9) with [Formula: see text]. SSDEs based on DLAT had 95% limits of agreement of up to 43% with [Formula: see text]. SSDEs based on other parameters (body weight, DAP, DAP+LAT, DED) had 95% limits of agreement of up to 25%. CONCLUSION: Differences between SSDEs calculated using various indications of patient size (geometric indices and patient weight) and the more accurate [Formula: see text] calculated using proprietary software were generally small, with the possible exception for lateral diameter, and provide acceptable dose estimates for body CT in children.

Dosimetric impact of orthopedic metal artifact reduction (O-MAR) on Spine SBRT patients.

The dosimetric impact of orthopedic metal artifact reduction (O-MAR) on spine SBRT patients has not been comprehensively studied, particularly with spinal prostheses in high-dose gradient regions. Using both phantom and patient datasets, we investigated dosimetric effects of O-MAR in combination of various metal locations and dose calculation algorithms. A physical phantom, with and without a titanium insert, was scanned. A clinical patient plan was applied to the artifact-free reference, non-O-MAR, and O-MAR phantom images with the titanium located either inside or outside of the tumor. Subsequently, five clinical patient plans were calculated with pencil beam and Monte Carlo (iPlan) on non-O-MAR and O-MAR patient images using an extended CT-density table. The dose differences for phantom plans and patient plans were analyzed using dose distributions, dose-volume histograms (DVHs), gamma index, and selected dosimetric endpoints. From both phantom plans and patient plans, O-MAR did not affect dose distributions and DVHs while minimizing metal artifacts. Among patient plans, we found that, when the same dose calculation method was used, the difference in the dosimetric endpoints between non-O-MAR and O-MAR datasets were small. In conclusion, for spine SBRT patients with spinal prostheses, O-MAR image reconstruction does not affect dose calculation accuracy while minimizing metal artifacts. Therefore, O-MAR images can be safely used for clinical spine SBRT treatment planning.

Effect of body size on dose reduction with longitudinal tube current modulation in pediatric patients.

OBJECTIVE: The purpose of the study was to evaluate whether dose reduction by tube current modulation in pediatric abdominal CT depends on patient body size. MATERIALS AND METHODS: A 12-month (February 2012 through January 2013) retrospective evaluation of consecutive abdominal 128-MDCT examinations was performed. All studies were performed with longitudinal (z-axis) tube current modulation. Dose reduction from tube current modulation in every CT acquisition was recorded and compared with body weight. In addition, 100 randomized CT abdominal scans were evaluated for average and SD of the water-equivalent diameter along the z-axis. RESULTS: The results include 466 abdominal CT scans of 369 children (172 girls, 197 boys; age range, 3 weeks-18 years; average, 9.2 years; body weight range, 3.5-130 kg; average, 31 kg). The average tube current-time reduction was 19%. Dose reduction was least effective (p<0.05; average, 11%) for body weight less than 20 kg. The least variability (SD/average) of water-equivalent diameter along the z-axis was found for body weights greater than 20 kg (5.0%) and 20-40 kg (5.9%) (p<0.05). Dose reduction was most effective (p<0.05; average, 30%) at the body weight range of 60-100 kg. CONCLUSION: Dose reduction with automated tube modulation depends on body weight and is less effective in children with a small body size. One of the reasons for this phenomenon could be a closer to uniform water-equivalent diameter along the z-axis in children with a small body size.

Evaluation of slice sensitivity profiles for helical and axial 4D-CT acquisitions on the Philips Brilliance CT Big Bore.

PURPOSE: 4D-CT can be performed using two acquisition modes. One employs a cine axial scan and the other acquires the data using a very low pitch helical acquisition. This study evaluates the longitudinal resolutions of each of these methods by creating slice sensitivity profiles (SSP). METHODS: An SSP phantom was scanned using both axial and helical scanning modes. The phantom was scanned at the center of the field of view (FOV) and at several points offset from the FOV center. For helical scans, the pitch was varied from 0.04 to 0.2. With the axial scans, the phantom position relative to the center of the detector ring was varied. All of these were performed using a 16 × 1.5 mm collimation. RESULTS: The SSP graphs were generated from these scanned datasets. The full width at half maximum (FWHM) of the graphs was used as the surrogate for longitudinal resolution. The results of these experiments demonstrated that axial scans have a slightly better resolution at CT isocenter (1.5 vs 1.8 mm). Helical mode scanning maintained this measurement for varying pitch factors and placement with the scan field. However, the resolution for axial scans degrades as the phantom is moved further from the center of the FOV and is positioned nearer to the edge of the detector rings. CONCLUSIONS: When it is imperative to maintain uniform longitudinal resolution throughout the FOV, it is suggested that helical acquisition be utilized or the axial mode data be reconstructed to account for beam divergence. For axial scans, this will require either limiting the longitudinal extent of each cine axial acquisition and/or using a smaller reconstructed FOV.

Individually optimized uniform contrast enhancement in CT angiography for the diagnosis of pulmonary thromboembolic disease--a simulation study.

PURPOSE: To improve the diagnostic quality of CT pulmonary angiography (CTPA) by individually optimizing a biphasic contrast injection function to achieve targeted uniform contrast enhancement. To compare the results against a previously reported discrete Fourier transform (DFT) approach. METHODS: This simulation study used the CTPA datasets of 27 consecutive patients with pulmonary thromboembolic disease (PE). An optimization approach was developed consisting of (1) computation of the impulse enhancement function (IEF) based on a test bolus scan, and (2) optimization of a biphasic contrast injection function using the IEF in order to achieve targeted uniform enhancement. The injection rates and durations of a biphasic contrast injection function are optimized by minimizing the difference between the resulting contrast enhancement curve and the targeted uniform enhancement curve, while conforming to the clinical constraints of injection rate and total contrast volume. The total contrast volume was limited first to the clinical standard of 65 ml, and then to the same amount used in the DFT approach for comparison. The optimization approach and the DFT approach were compared in terms of the root mean square error (RMSE) and total contrast volume used. RESULTS: When the total contrast volume was limited to 65 ml, the optimization approach produced significantly better contrast enhancement (closer to the targeted uniform contrast enhancement) than the DFT approach (RMSE 17 HU vs 56 HU, p < 0.00001). On average, the optimization approach used 63 ml contrast, while the DFT approach used 50 ml with four patients exceeding 65 ml. When equivalent total contrast volume was used for individual patient, the optimization approach still generated significantly better contrast enhancement (RMSE 44 HU vs 56 HU, p < 0.01). Constraints for the injection function could be easily accommodated into the optimization process when searching for the optimal biphasic injection function. CONCLUSIONS: The optimization approach generated individually optimized biphasic injection functions yielding significantly better contrast enhancement compared to the DFT approach. This new approach has the potential to improve the diagnostic quality of CTPA for PE.

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: comparison of analytic and polyenergetic statistical reconstruction algorithms.

PURPOSE: Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasive in vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. METHODS: Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. RESULTS: Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm(3) grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean. Reconstruction with the statistical AM algorithm led to standard deviations roughly 40% to 60% less than FBP reconstruction. Additional tin filtration of the high energy beam exhibits similar pDECT estimation accuracy as the unfiltered beam, even when scanning with only 25% of the dose. Using the law of propagated uncertainty, low Z materials are found to be more sensitive to image reconstruction errors than high Z materials. Furthermore, it is estimated that reconstructed CT image uncertainty must be limited to less than 0.25% to achieve a target linear-attenuation coefficient estimation uncertainty of 3% at 28 keV. CONCLUSIONS: That pDECT supports mean linear attenuation coefficient measurement accuracies of 1% of reference values for energies greater than 30 keV is encouraging. However, the sensitivity of the pDECT measurements to noise and systematic errors in reconstructed CT images warrants further investigation in more complex phantom geometries. The investigated statistical reconstruction algorithm, AM, reduced random measurement uncertainty relative to FBP owing to improved noise performance. These early results also support efforts to increase DE spectral separation, which can further reduce the pDECT sensitivity to measurement uncertainty.

Effect of tube voltage on CT noise levels in different phantom sizes.

OBJECTIVE: The purpose of this study was to determine the effect of lowering tube voltage on dose and noise in cylindric water phantoms to optimize quality and decrease the radiation dose for body CT. MATERIALS AND METHODS: We performed CT on cylindric water phantoms with diameters of 10, 20, 25, and 30 cm, simulating the abdomen of an infant, child, adolescent, and adult. We used tube voltages of 120, 100, and 80 kVp. The CT dose index (32-cm reference) ranged from 1 to 10 mGy in 10- and 20-cm phantoms and from 2 to 20 mGy in the 25- and 30-cm phantoms. The noise was measured at the center and periphery of the scans. Central and peripheral doses were measured in 16- and 32-cm CT dose index phantoms, and the ratio of central to peripheral doses was calculated. RESULTS: At the same noise levels, there was no significant increase in dose in 10-cm cylindric water phantoms when tube voltage was decreased to either 80 or 100 kVp. In 20-, 25-, and 30-cm phantoms, there was a 1-6% increase in dose when tube voltage was decreased to 100 kVp. Central-to-peripheral noise ratios increased 7-37% with increased phantom size. The measured peripheral dose increased as much as 5%. CONCLUSION: Our findings support the practice of lowering tube voltage to 80 kVp for imaging of infants and to 100 kVp for imaging of older children. The increase in peripheral dose with decreased tube voltage is minimal and is unlikely to cause substantial change in the effective dose.

Experimental implementation of a polyenergetic statistical reconstruction algorithm for a commercial fan-beam CT scanner.

PURPOSE: To present a framework for characterizing the data needed to implement a polyenergetic model-based statistical reconstruction algorithm, Alternating Minimization (AM), on a commercial fan-beam CT scanner and a novel method for assessing the accuracy of the commissioned data model. METHODS: The X-ray spectra for three tube potentials on the Philips Brilliance CT scanner were estimated by fitting a semi-empirical X-ray spectrum model to transmission measurements. Spectral variations due to the bowtie filter were computationally modeled. Eight homogeneous cylinders of PMMA, Teflon and water with varying diameters were scanned at each energy. Central-axis scatter was measured for each cylinder using a beam-stop technique. AM reconstruction with a single-basis object-model matched to the scanned cylinder's composition allows assessment of the accuracy of the AM algorithm's polyenergetic data model. Filtered-backprojection (FBP) was also performed to compare consistency metrics such as uniformity and object-size dependence. RESULTS: The spectrum model fit measured transmission curves with residual root-mean-square-error of 1.20%-1.34% for the three scanning energies. The estimated spectrum and scatter data supported polyenergetic AM reconstruction of the test cylinders to within 0.5% of expected in the matched object-model reconstruction test. In comparison to FBP, polyenergetic AM exhibited better uniformity and less object-size dependence. CONCLUSIONS: Reconstruction using a matched object-model illustrate that the polyenergetic AM algorithm's data model was commissioned to within 0.5% of an expected ground truth. These results support ongoing and future research with polyenergetic AM reconstruction of commercial fan-beam CT data for quantitative CT applications.

Clinical evaluation of a commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy.

PURPOSE: 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. METHODS: 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: 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. CONCLUSIONS: 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.

Effect of novel amplitude/phase binning algorithm on commercial four-dimensional computed tomography quality.

PURPOSE: Respiratory motion is a significant source of anatomic uncertainty in radiotherapy planning and can result in errors of portal size and the subsequent radiation dose. Although four-dimensional computed tomography allows for more accurate analysis of the respiratory cycle, breathing irregularities during data acquisition can cause considerable image distortions. The aim of this study was to examine the effect of respiratory irregularities on four-dimensional computed tomography, and to evaluate a novel image reconstruction algorithm using percentile-based tagging of the respiratory cycle. METHODS AND MATERIALS: Respiratory-correlated helical computed tomography scans were acquired for 11 consecutive patients. The inspiration and expiration data sets were reconstructed using the default phase-based method, as well as a novel respiration percentile-based method with patient-specific metrics to define the ranges of the reconstruction. The image output was analyzed in a blinded fashion for the phase- and percentile-based reconstructions to determine the prevalence and severity of the image artifacts. RESULTS: The percentile-based algorithm resulted in a significant reduction in artifact severity compared with the phase-based algorithm, although the overall artifact prevalence did not differ between the two algorithms. The magnitude of differences in respiratory tag placement between the phase- and percentile-based algorithms correlated with the presence of image artifacts. CONCLUSION: The results of our study have indicated that our novel four-dimensional computed tomography reconstruction method could be useful in detecting clinically relevant image distortions that might otherwise go unnoticed and to reduce the image distortion associated with some respiratory irregularities. Additional work is necessary to assess the clinical impact on areas of possible irregular breathing.

Displacement-based binning of time-dependent computed tomography image data sets.

Respiration can cause tumors in the thorax or abdomen to move by as much as 3 cm; this movement can adversely affect the planning and delivery of radiation treatment. Several techniques have been used to compensate for respiratory motion, but all have shortcomings. Manufacturers of computed tomography (CT) equipment have recently used a technique developed for cardiac CT imaging to track respiratory-induced anatomical motion and to sort images according to the phase of the respiratory cycle they represent. Here we propose a method of generating CT images that accounts for respiratory-induced anatomical motion on the basis of displacement, i.e., displacement-binned CT image sets. This technique has shown great promise, however, it is not fully supported by currently used CT image reconstruction software. As an interim solution, we have developed a method for extracting displacement-binned CT image data sets from data sets assembled on the basis of a prospectively determined breathing phase acquired on a multislice helical CT scanner. First, the projection data set acquired from the CT scanner was binned at small phase intervals before reconstruction. The manufacturer's software then generated image sets identified as belonging to particular phases of the respiratory cycle. All images were then individually correlated to the displacement of an external fiducial marker. Next, CT image data sets were resorted on the basis of the displacement and assigned an appropriate phase. Finally, displacement-binned image data sets were transferred to a treatment-planning system for analysis. Although the technique is currently limited by the phase intervals allowed by the CT software, some improvement in image reconstruction was seen, indicating that this technique is useful at least as an interim measure.

Gated CT imaging using a free-breathing respiration signal from flow-volume spirometry.

Respiration-induced tumor motion is known to cause artifacts on free-breathing spiral CT images used in treatment planning. This leads to inaccurate delineation of target volumes on planning CT images. Flow-volume spirometry has been used previously for breath-holds during CT scans and radiation treatments using the active breathing control (ABC) system. We have developed a prototype by extending the flow-volume spirometer device to obtain gated CT scans using a PQ 5000 single-slice CT scanner. To test our prototype, we designed motion phantoms to compare image quality obtained with and without gated CT scan acquisition. Spiral and axial (nongated and gated) CT scans were obtained of phantoms with motion periods of 3-5 s and amplitudes of 0.5-2 cm. Errors observed in the volume estimate of these structures were as much as 30% with moving phantoms during CT simulation. Application of motion-gated CT with active breathing control reduced these errors to within 5%. Motion-gated CT was then implemented in patients and the results are presented for two clinical cases: lung and abdomen. In each case, gated scans were acquired at end-inhalation, end-exhalation in addition to a conventional free-breathing (nongated) scan. The gated CT scans revealed reduced artifacts compared with the conventional free-breathing scan. Differences of up to 20% in the volume of the structures were observed between gated and free-breathing scans. A comparison of the overlap of structures between the gated and free-breathing scans revealed misalignment of the structures. These results demonstrate the ability of flow-volume spirometry to reduce errors in target volumes via gating during CT imaging.