Juan Carlos Ramirez-Giraldo

Dual-energy dual-source CT with additional spectral filtration can improve the differentiation of non-uric acid renal stones: An ex vivo phantom study

OBJECTIVE The purpose of this study was to determine the ex vivo ability of dual-energy dual-source CT (DSCT) with additional tin filtration to differentiate among five groups of human renal stone types. MATERIALS AND METHODS Forty-three renal stones of 10 types were categorized into five primary groups on the basis of effective atomic numbers, which were calculated as the weighted average of the atomic numbers of constituent atoms. Stones were embedded in porcine kidneys and placed in a 35-cm water phantom. Dual-energy DSCT scans were performed at 80 and 140 kV with and without tin filtration of the 140-kV beam. The CT number ratio, defined as the ratio of the CT number of a given material in the low-energy image to the CT number of the same material in the high-energy image, was calculated on a volumetric voxel-by-voxel basis for each stone. Statistical analysis was performed, and receiver operating characteristic (ROC) curves were plotted to compare the difference in CT number ratio with and without tin filtration, and to measure the discrimination among stone groups. RESULTS The CT number ratio of non-uric acid stones increased on average by 0.17 (range, 0.03-0.36) with tin filtration. The CT number ratios for non-uric acid stone groups were not significantly different (p > 0.05) between any of the two adjacent groups without tin filtration. Use of the additional tin filtration on the high-energy x-ray tube significantly improved the separation of non-uric acid stone types by CT number ratio (p < 0.05). The area under the ROC curve increased from 0.78 to 0.84 without fin filtration and to 0.89-0.95 with tin filtration. CONCLUSION Our results showed better separation among different stone types when additional tin filtration was used on dual-energy DSCT. The increased spectral separation allowed a five-group stone classification scheme. Some overlapping between particular stone types still exists, including brushite and calcium oxalate.

Nonconvex prior image constrained compressed sensing (NCPICCS): theory and simulations on perfusion CT.

PURPOSE To present and evaluate a new image reconstruction method for dynamic CT based on a nonconvex prior image constrained compressed sensing (NCPICCS) algorithm. The authors systematically compared the undersampling potential, functional information recovery, and solution convergence speed of four compressed sensing (CS) based image reconstruction methods using perfusion CT data: Standard l1-based CS, nonconvex CS (NCCS), and l1-based and nonconvex CS, including an additional constraint based on a prior image (PICCS and NCPICCS, respectively). METHODS The Shepp-Logan phantom was modified such that its uppermost ellipses changed attenuation through time, simulating both an arterial input function (AIF) and a homogeneous tissue perfusion region. Data were simulated with and without Poisson noise added to the projection data and subsequently reconstructed with all four CS-based methods at four levels of undersampling: 20, 12, 6, and 4 projections. Root mean squared (RMS) error of reconstructed images and recovered time attenuation curves (TACs) were assessed as well as convergence speed. The performance of both PICCS and NCPICCS methods were also evaluated using a kidney perfusion animal experiment data set. RESULTS All four CS-based methods were able to reconstruct the phantoms with 20 projections, with similar results on the RMS error of the recovered TACs. NCCS allowed accurate reconstructions with as few as 12 projections, PICCS with as few as six projections, and NCPICCS with as few as four projections. These results were consistent for noise-free and noisy data. NCPICCS required the fewest iterations to converge across all simulation conditions, followed by PICCS, NCCS, and then CS. On animal data, at the lowest level of undersampling tested (16 projections), the image quality of NCPICCS was better than PICCS with fewer streaking artifacts, while the TAC accuracy on the selected region of interest was comparable. CONCLUSIONS The authors have presented a novel method for image reconstruction using highly undersampled dynamic CT data. The NCPICCS method takes advantage of the information provided by a prior image, as in PICCS, but employs a more general nonconvex sparsity measure [such as the l(p)-norm (0 < p < or = 1)] rather than the conventional convex l1-norm. Despite the lack of guarantees of a globally optimal solution, the proposed nonconvex extension of PICCS consistently allowed for image reconstruction from fewer samples than the analogous l1-based PICCS method. Both nonconvex sparsity measures as well as prior image information (when available) significantly reduced the number of iterations required for convergence, potentially providing computational advantages for practical implementation of CS-based image reconstruction techniques.

Diagnostic Performance of an Advanced Modeled Iterative Reconstruction Algorithm for Low-Contrast Detectability with a Third-Generation Dual-Source Multidetector CT Scanner: Potential for Radiation Dose Reduction in a Multireader Study

PURPOSE To assess the effect of radiation dose reduction on low-contrast detectability by using an advanced modeled iterative reconstruction (ADMIRE; Siemens Healthcare, Forchheim, Germany) algorithm in a contrast-detail phantom with a third-generation dual-source multidetector computed tomography (CT) scanner. MATERIALS AND METHODS A proprietary phantom with a range of low-contrast cylindrical objects, representing five contrast levels (range, 5-20 HU) and three sizes (range, 2-6 mm) was fabricated with a three-dimensional printer and imaged with a third-generation dual-source CT scanner at various radiation dose index levels (range, 0.74-5.8 mGy). Image data sets were reconstructed by using different section thicknesses (range, 0.6-5.0 mm) and reconstruction algorithms (filtered back projection [FBP] and ADMIRE with a strength range of three to five). Eleven independent readers blinded to technique and reconstruction method assessed all data sets in two reading sessions by measuring detection accuracy with a two-alternative forced choice approach (first session) and by scoring the total number of visible object groups (second session). Dose reduction potentials based on both reading sessions were estimated. Results between FBP and ADMIRE were compared by using both paired t tests and analysis of variance tests at the 95% significance level. RESULTS During the first session, detection accuracy increased with increasing contrast, size, and dose index (diagnostic accuracy range, 50%-87%; interobserver variability, ±7%). When compared with FBP, ADMIRE improved detection accuracy by 5.2% on average across the investigated variables (P < .001). During the second session, a significantly increased number of visible objects was noted with increasing radiation dose index, section thickness, and ADMIRE strength over FBP (up to 80% more visible objects, P < .001). Radiation dose reduction potential ranged from 56% to 60% and from 4% to 80% during the two sessions, respectively. CONCLUSION Low-contrast detectability performance increased with increasing object size, object contrast, dose index, section thickness, and ADMIRE strength. Compared with FBP, ADMIRE allows a substantial radiation dose reduction while preserving low-contrast detectability. Online supplemental material is available for this article.

Iodine quantification to distinguish clear cell from papillary renal cell carcinoma at dual-energy multidetector CT: a multireader diagnostic performance study.

PURPOSE To investigate whether dual-energy multidetector row computed tomographic (CT) imaging with iodine quantification is able to distinguish between clear cell and papillary renal cell carcinoma ( RCC renal cell carcinoma ) subtypes. MATERIALS AND METHODS In this retrospective, HIPAA-compliant, institutional review board-approved study, 88 patients (57 men, 31 women) with diagnosis of either clear cell or papillary RCC renal cell carcinoma at pathologic analysis, who underwent contrast material-enhanced dual-energy nephrographic phase study between December 2007 and June 2013, were included. Five readers, blinded to pathologic diagnosis, independently evaluated all cases by determining the lesion iodine concentration on color-coded iodine maps. The receiving operating characteristic curve analysis was adopted to estimate the optimal threshold for discriminating between clear cell and papillary RCC renal cell carcinoma , and results were validated by using a leave-one-out cross-validation. Interobserver agreement was assessed by using an intraclass correlation coefficient. The correlation between tumor iodine concentration and tumor grade was investigated. RESULTS A tumor iodine concentration of 0.9 mg/mL represented the optimal threshold to discriminate between clear cell and papillary RCC renal cell carcinoma , and it yielded the following: sensitivity, 98.2% (987 of 1005 [95% confidence interval: 97.7%, 98.7%]); specificity, 86.3% (272 of 315 [95% confidence interval: 85.0%, 87.7%]); positive predictive value, 95.8% (987 of 1030 [95% confidence interval: 95.0%, 96.6%]); negative predictive value, 93.7% (272 of 290 [95% confidence interval: 92.8%, 94.7%]); overall accuracy of 95.3% (1259 of 1320 [95% confidence interval: 94.6%, 96.2%]), with an area under the curve of 0.923 (95% confidence interval: 0.913, 0.933). An excellent agreement was found among the five readers in measured tumor iodine concentration (intraclass correlation coefficient, 0.9990 [95% confidence interval: 0. 9987, 0.9993). A significant correlation was found between tumor iodine concentration and tumor grade for both clear cell (τ = 0.85; P < .001) and papillary RCC renal cell carcinoma (τ = 0.53; P < .001). CONCLUSION Dual-energy multidetector CT with iodine quantification can be used to distinguish between clear cell and papillary RCC renal cell carcinoma , and it provides insights regarding the tumor grade.

Accuracy of contrast-enhanced dual-energy MDCT for the assessment of iodine uptake in renal lesions.

OBJECTIVE The objective of our study was to assess the accuracy of iodine-related attenuation and iodine quantification as imaging biomarkers of iodine uptake in renal lesions on a single-phase nephrographic image with dual-energy MDCT. MATERIALS AND METHODS Fifty-nine patients (41 men, 18 women; age range, 28-84 years) with 80 renal lesions underwent contrast-enhanced dual-energy CT during the nephrographic phase of enhancement. Renal lesions were characterized as enhancing or nonenhancing on color-coded iodine overlay maps using iodine-related attenuation (in Hounsfield units) and iodine quantification (in milligrams per milliliter). For iodine-related attenuation the iodine uptake thresholds of 15 and 20 HU were tested; a threshold of 0.5 mg/mL was used for iodine quantification. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of iodine-related attenuation and iodine quantification were calculated from chi-square tests of contingency with histopathology or imaging follow-up as the reference standard. The 95% CIs were calculated from binomial expression. Differences in sensitivity and specificity were assessed by means of McNemar analysis. RESULTS A significant difference in sensitivity and specificity was found between iodine-related attenuation with the thresholds of 15 HU (sensitivity, 91.4%; specificity, 93.3%; PPV, 91.4%; NPV, 93.3%) and 20 HU (sensitivity, 77.1%; specificity, 100%; PPV, 100%; NPV, 84.9%) (p = 0.008) and between iodine quantification (sensitivity, 100%; specificity, 97.7%; PPV, 97.2%; NPV, 100%) and iodine-related attenuation with a threshold of 20 HU (p = 0.004). No significant difference in sensitivity and specificity was found between iodine quantification and iodine-related attenuation with a threshold of 15 HU. CONCLUSION Contrast-enhanced dual-energy MDCT with iodine-related attenuation and iodine quantification allows accurate evaluation of iodine uptake in renal lesions on a single-phase nephrographic image.

Automated low-kilovoltage selection in pediatric computed tomography angiography: phantom study evaluating effects on radiation dose and image quality.

PurposeThe purpose of this study was to compare the effects of combined automated tube voltage selection and automated tube current modulation on radiation dose and image quality in small-sized phantoms undergoing computed tomography angiography (CTA) with the use of automated current modulation alone. Materials and MethodsThree semianthropomorphic phantoms, corresponding to a neonate, a small child, and a small adult, underwent simulated abdominal CTA using an automated tube voltage selection technology, which simultaneously optimizes kilovoltage (in kilovolt [peak]) and tube-current/milliamperage (in milliampere-second) on the basis of the patient topogram and clinical task. The phantoms were scanned with 2 protocols: protocol A, using the combination of automated kilovoltage and milliamperage, and protocol B, using only automated milliamperage with the standard 120 kV(p). Radiation doses were measured for each phantom, and the measurements were then used to estimate volume computed tomography dose index. Image noise and iodine contrast, contrast-to-noise ratio, and the relative dose factor were assessed. Differences were tested using paired t tests, and percentage differences for various technical factors and the phantom sizes were calculated. ResultsThe computed tomography dose index was significantly lower in protocol A (mean, 3.3 mGy) compared with that in protocol B (mean, 7.7 mGy), representing a 56.0% dose reduction (P = 0.01). In protocol A, tube potential dropped from 120 to 70 kV(p) in the small and medium phantoms and to 80 kV(p) in the large phantom. For each phantom size, image noise and iodine contrast increased significantly in protocol A relative to those in protocol B (P = 0.03 and P < 0.01, respectively). Corresponding contrast-to-noise ratio values increased by 9.1% in protocol A relative to those in protocol B (P = 0.04). The relative dose factor values for protocol A relative to those for protocol B were 31%, 36%, and 44% for the small, medium, and large phantoms, respectively. ConclusionsCombined use of automated kilovoltage selection and automated tube current modulation is more effective for reducing radiation dose and maintaining image quality during simulated pediatric CTA than is automated tube current modulation in isolation.

Noise Reduction to Decrease Radiation Dose and Improve Conspicuity of Hepatic Lesions at Contrast-Enhanced 80-kV Hepatic CT Using Projection Space Denoising

OBJECTIVE The purpose of this study was to investigate the combined potential of 80-kV CT and noise reduction using a projection space denoising algorithm to reduce radiation dose reduction or to improve the image quality of hepatic CT. MATERIALS AND METHODS Twenty patients with 56 liver lesions underwent dual-energy (80 and 140 kV) contrast-enhanced hepatic CT. Low-dose 80-kV-only images (comprising 26-54% of the total radiation dose), low-dose 80-kV projection space denoising images (routine and sharper reconstruction kernel), and full-dose mixed-kilovoltage with projection space denoising images were evaluated by three radiologists for lesion conspicuity, image noise, and sharpness. Lesions were compared with full-dose images using 5-point scales (0 = no change, +2 = markedly better, and -2 = markedly worse). Quantitative conspicuity in the form of lesion-to-liver contrast-to-noise ratio (CNR), image noise, and image sharpness were measured. RESULTS For all readers, the mean conspicuity rating of low-dose 80-kV projection space denoising images was better than that for full-dose images (mean conspicuity, 0.36-0.57; p < 0.001), with only 1.2% of lesions less conspicuous on 80-kV projection space denoising images. Eighty-kilovolt projection space denoising images reconstructed with a sharper kernel were subjectively similar to full-dose mixed-kilovoltage images comparing image noise (-0.054 to 0.018; p < 0.001 to p = 0.058) and sharpness (-0.64 to -0.09; p < 0.001 to p = 0.057). For 80-kV projection space denoising images with a sharper kernel, lesion-to-liver CNR was slightly higher than that for full-dose mixed-kilovoltage images (p < 0.001), whereas image sharpness and noise were unchanged (p = 0.74 and p = 0.02). CONCLUSION Eighty-kilovolt imaging with noise reduction can simultaneously increase lesion conspicuity and facilitate radiation dose reduction and image quality improvement at contrast-enhanced hepatic CT.

Feasibility of Dose Reduction Using Novel Denoising Techniques for Low kV (80 kV) CT Enterography: Optimization and Validation

RATIONALE AND OBJECTIVES The aim of this study was to optimize and validate projection-space denoising (PSDN) strategies for application to 80-kV computed tomographic (CT) data to achieve 50% dose reduction. MATERIALS AND METHODS Image data obtained at 80 kV (mean CT dose index volume, 7.9 mGy) from dual-source, dual-energy CT enterographic (CTE) exams in 42 patients were used. For each exam, nine 80 kV image data sets were reconstructed using PSDN (three levels of intensity) with or without image-based denoising and compared to commercial reconstruction kernels. For optimization, qualitative analysis selected optimal denoising strategies, with quantitative analysis measuring image contrast, noise, and sharpness (full width at half maximum bowel wall thickness, maximum CT number gradient). For validation, two radiologists examined image quality, comparing low-dose 80-kV optimally denoised images to full-dose mixed-voltage images. RESULTS PSDN algorithms generated the best 80-kV image quality (41 of 42 patients), while the commercial kernels produced the worst (39 of 42) (P < .001). Overall, 80-kV PSDN approaches resulted in higher contrast (mean, 332 vs 290 Hounsfield units), slightly less noise (mean, 20 vs 26 Hounsfield units), but slightly decreased image sharpness (relative bowel wall thickness, 1.069 vs 1.000) compared to full-dose mixed-voltage images. Mean image quality scores for full-dose CTE images were 4.9 compared to 4.5 for optimally denoised half-dose 80-kV CTE images and 3.1 for nondenoised 80-kV CTE images (P < .001). CONCLUSION Optimized denoising strategies improve the quality of 80-kV CTE images such that CT data obtained at 50% of routine dose levels approaches the image quality of full-dose exams.

A strategy to decrease partial scan reconstruction artifacts in myocardial perfusion CT: Phantom and in vivo evaluation

PURPOSE Partial scan reconstruction (PSR) artifacts are present in myocardial perfusion imaging using dynamic multidetector computed tomography (MDCT). PSR artifacts appear as temporal CT number variations due to inconsistencies in the angular data range used to reconstruct images and compromise the quantitative value of myocardial perfusion when using MDCT. The purpose of this work is to present and evaluate a technique termed targeted spatial frequency filtration (TSFF) to reduce CT number variations due to PSR when applied to myocardial perfusion imaging using MDCT. METHODS The TSFF algorithm requires acquiring enough X-ray projections to reconstruct both partial (π + fan angle α) and full (2π) scans. Then, using spatial linear filters, the TSFF-corrected image data are created by superimposing the low spatial frequency content of the full scan reconstruction (containing no PSR artifacts, but having low spatial resolution and worse temporal resolution) with the high spatial frequency content of the partial scan reconstruction (containing high spatial frequencies and better temporal resolution). The TSFF method was evaluated both in a static anthropomorphic thoracic phantom and using an in vivo porcine model and compared with a previously validated reference standard technique that avoids PSR artifacts by pacing the animal heart in synchrony with the gantry rotation. CT number variations were quantified by measuring the range and standard deviation of CT numbers in selected regions of interest (ROIs) over time. Myocardial perfusion parameters such as blood volume (BV), mean transit time (MTT), and blood flow (BF) were quantified and compared in the in vivo study. RESULTS Phantom experiments demonstrated that TSFF reduced PSR artifacts by as much as tenfold, depending on the location of the ROI. For the in vivo experiments, the TSFF-corrected data showed two- to threefold decrease in CT number variations. Also, after TSFF, the perfusion parameters had an average difference of 13.1% (range 4.5%-25.6%) relative to the reference method, in contrast to an average difference of 31.8% (range 0.3%-54.0%) between the non-TSFF processed data with the reference method. CONCLUSIONS TSFF demonstrated consistent reduction in CT number variations due to PSR using controlled phantom and in vivo experiments. TSFF-corrected data provided quantitative measures of perfusion (BV, MTT, and BF) with better agreement to a reference method compared to noncorrected data. Practical implementation of TSFF is expected to incur in an additional radiation exposure of 14%, when tube current is modulated to 20% of its maximum, to complete the needed full scan reconstruction.

Effect of a Noise-Optimized Second-Generation Monoenergetic Algorithm on Image Noise and Conspicuity of Hypervascular Liver Tumors: An In Vitro and In Vivo Study

OBJECTIVE The purpose of this study is to investigate whether the reduction in noise using a second-generation monoenergetic algorithm can improve the conspicuity of hypervascular liver tumors on dual-energy CT (DECT) images of the liver. MATERIALS AND METHODS An anthropomorphic liver phantom in three body sizes and iodine-containing inserts simulating hypervascular lesions was imaged with DECT and single-energy CT at various energy levels (80-140 kV). In addition, a retrospective clinical study was performed in 31 patients with 66 hypervascular liver tumors who underwent DECT during the late hepatic arterial phase. Datasets at energy levels ranging from 40 to 80 keV were reconstructed using first- and second-generation monoenergetic algorithms. Noise, tumor-to-liver contrast-to-noise ratio (CNR), and CNR with a noise constraint (CNRNC) set with a maximum noise increase of 50% were calculated and compared among the different reconstructed datasets. RESULTS The maximum CNR for the second-generation monoenergetic algorithm, which was attained at 40 keV in both phantom and clinical datasets, was statistically significantly higher than the maximum CNR for the first-generation monoenergetic algorithm (p < 0.001) or single-energy CT acquisitions across a wide range of kilovoltage values. With the second-generation monoenergetic algorithm, the optimal CNRNC occurred at 55 keV, corresponding to lower energy levels compared with first-generation algorithm (predominantly at 70 keV). Patient body size did not substantially affect the selection of the optimal energy level to attain maximal CNR and CNRNC using the second-generation monoenergetic algorithm. CONCLUSION A noise-optimized second-generation monoenergetic algorithm significantly improves the conspicuity of hypervascular liver tumors.