Accuracy Of Iodine Quantification Research Articles

Accuracy of iodine quantification in dual energy CT: A phantom study across 3 different CT systems

IntroductionNo study has rigorously compared the performances of iodine quantification on recent CT systems employing different emission-based technologies, depending on the manufacturers and models. MethodsA specific bespoke phantom was used for this study, with 12 known concentrations of iodinated contrast agent: 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 10.0, 15.0, 20.0, 30.0 and 50.0 mg/mL. Three different dual-energy scanners were tested: one system using dual-source acquisition (CT#1) and two systems using Fast kilovolt-peak switching technology ± artificial intelligence (AI) reconstruction methods (CT#2 and #3) from two different manufacturers. For each system, helical scans were performed following recommended clinical protocols. Four acquisitions were performed per iodine concentration (mg/mL), and measurements were made on iodine-maps using ROIs. Mean measured values were compared to the known concentrations, and the absolute quantification error (AQE) and the relative percentage error (RPE) were used to compare the performances of each CT. ResultsThe accuracy of the obtained measurements varied depending on the studied model but not on the acquisition mode (dual-source vs kVp switch ± AI). The quantification was more precise at high concentrations. RPE values were below 10 % with CT#2 (kVp switch) and below 25 % with CT#1 (dual-source), but were significantly higher with CT#3 (kVp switch + AI), exceeding 50 % at low concentrations (<3 mg/mL). ConclusionsWith the help of a phantom, we identified variability in the results accuracy depending on the CT model, with sometimes significant deviation. Considering the performances of the different DECT technologies in iodine mapping, dual-source (CT#1) and kVp switch (CT#2) technologies appear more accurate than kVp switch technology combined with deep-learning-based reconstruction (CT#3) especially at low concentrations (<3 mg/mL). Implications for practiceAs the primary and daily user of medical imaging devices, the radiographer role is to be attentive to the performance of imaging systems, particularly when performing quantitative acquisitions like iodine-quantification. In CT quantitative imaging (iodine map), it's essential for radiographers to consider their CT systems as measuring tools, and to be aware of their accuracies and limits.

Quantitative performance of photon-counting CT at low dose: Virtual monochromatic imaging and iodine quantification.

Quantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon-counting detectors (PCD) has reached clinical status. This work aimed to investigate the performance of a new photon-counting CT (PC-CT) in low-dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy-integrating detector dual-energy CT (DE-CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso-center, and solvent (tissue background) composition wereexplored. Quantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi-energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual-energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC-CT both tube voltages were set to either 120 or 140 kVp with photon-counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient-related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient-specificparameters. The accuracy of IQ and VMI in the PC-CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC-CT scanner outperforms the DE-CT scanner in the IQ task in all cases. Iodine quantification bias in the PC-CT (-0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE-CT (range -2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE-CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC-CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obesepopulation. The statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC-CT. Although VMI performance was mostly comparable between the scanners, the DE-CT scanner quantitatively outperformed PC-CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X-ray tubepotentials.

Technical performance of a dual-energy CT system with a novel deep-learning based reconstruction process: Evaluation using an abdomen protocol.

A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning based reconstruction process has been introduced. Characterizing the performance of this DE approach can help demonstrate its benefits and potential drawbacks. To evaluate the technical performance of a novel DECT system and compare it to that of standard single-kV CT and a rotate/rotate DECT, for abdominal imaging. DE and single-kV images of four different phantoms were acquired on a kV-switching DECT system, and on a rotate/rotate DECT. The dose for the acquisitions of each phantom was set to that selected for the kV-switching DE mode by the automatic tube current modulation (ATCM) at manufacturer-recommended settings. The dose that the ATCM would have selected in single-kV mode was also recorded. Virtual monochromatic images (VMIs) from 40 to 130keV, as well as iodine maps, were reconstructed from the DE data. Single-kV images, acquired at 120kV, were reconstructed using body hybrid iterative reconstruction. All reconstructions were made at 0.5mm section thickness. Task transfer functions (TTFs) were determined for a Teflon and LDPE rod. Noise magnitude (SD), and noise power spectrum (NPS) were calculated using 240 and 320mm diameter water phantoms. Iodine quantification accuracy and contrast-to-noise ratios (CNRs) relative to water for 2, 5, 10, and 15mg I/ml were determined using a multi-energy CT (MECT) phantom. Low-contrast visibility was determined and the presence of beam-hardening artifacts and inhomogeneities were evaluated. The TTFs of the kV-switching DE VMIs were higher than that of the single-kV images for Teflon (20% TTF: 6.8 lp/cm at 40keV, 6.2 lp/cm for single-kV), while for LDPE the DE TTFs at 70keV and above were equivalent or higher than the single-kV TTF. All TTFs of the kV-switching DECT were higher than for the rotate/rotate DECT. The SD was lowest in the 70keV VMI (12.0 HU), which was lower than that of single-kV (18.3 HU). The average NPS frequency varied between 2.3 lp/cm and 4.2 lp/cm for the kV-switching VMIs and was 2.2 lp/cm for single-kV. The error in iodine quantification was at maximum 1mg I/ml (at 5mg I/ml). The highest CNR for all iodine concentrations was at 60keV, 2.5 times higher than the CNR for single-kV. At 70-90keV, the number of visible low contrast objects was comparable to that in single-kV, while other VMIs showed fewer objects. At manufacturer-recommended ATCM settings, the CTDIvol for the DE acquisitions of the water and MECT phantoms were 12.6 and 15.4 mGy, respectively, and higher than that for single-kV. The 70keV VMI had less severe beam hardening artifacts than single-kV images. Hyper- and hypo-dense blotches may appear in VMIs when object attenuation exceeds manufacturer recommended limits. At manufacturer-recommended ATCM settings for abdominal imaging, this DE implementation results in higher CTDIvol compared to single-kV acquisitions. However, it can create sharper, lower noise VMIs with up to 2.5 times higher iodine CNR compared to single-kV images acquired at the same dose.

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an abdominal clinical study. An elliptical phantom with five different iodine concentrations (1-12 mgI/mL) was imaged five times with fast-kilovoltage-switching DECT for three target volume CT dose indexes. All images were reconstructed using filtered back-projection, iterative reconstruction (two levels), and DLIR algorithms. Measured and nominal iodine concentrations were compared among the algorithms. Contrast-enhanced CT of the abdomen with the same scanner was acquired in clinical patients. In arterial and portal venous phase images, iodine concentration, image noise, and coefficients of variation for four locations were retrospectively compared among the algorithms. One-way repeated-measures analyses of variance were used to evaluate differences in the iodine concentrations, standard deviations, coefficients of variation, and percentages of error among the algorithms. In the phantom study, the measured iodine concentrations were equivalent among the algorithms: within ± 8% of the nominal values, with root-mean-square deviations of 0.08-0.36 mgI/mL, regardless of radiation dose. In the clinical study (50 patients; 35 men; mean age, 68 ± 11 years), iodine concentrations were equivalent among the algorithms for each location (all p > .99). Image noise and coefficients of variation were lower with DLIR than with the other algorithms (all p < .01). The DLIR algorithm reduced image noise and variability of iodine concentration values compared with other reconstruction algorithms in the fast-kilovoltage-switching dual-energy CT. • In the phantom study, standard deviations and coefficients of variation in iodine quantification were lower on images with the deep learning image reconstruction algorithm than on those with other algorithms. • In the clinical study, iodine concentrations of measurement location in the upper abdomen were consistent across four reconstruction algorithms, while image noise and variability of iodine concentrations were lower on images with the deep learning image reconstruction algorithm.

Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients

To compare the accuracy of iodine quantification in liver parenchyma and lesions between dual-source photon-counting detector CT (PCD-CT) and dual-source energy-integrating detector CT (EID-CT) in a phantom and to demonstrate the feasibility of iodine quantification with PCD-CT in liver parenchyma and lesions in patients. An anthropomorphic abdominal phantom with a liver insert containing parenchyma and lesions was imaged on a clinical PCD-CT at 120kV and in the dual-energy mode on an EID-CT with kV-combinations of 80/Sn150kV, 90/Sn150kV, and 100/Sn150kV. Three patient sizes were imaged at three different radiation doses (CTDIvol: 5, 10, 15mGy). Thirty patients with liver cysts, hemangiomas or metastases imaged with PCD-CT were retrospectively included. Iodine maps were reconstructed and iodine concentrations were measured in liver parenchyma and lesions. For the phantom, iodine error was quantified as the absolute difference to the vendor's specifications as reference. Overall iodine error was 0.33 ± 0.29, 0.34 ± 0.32, 0.39 ± 0.37, 0.35 ± 0.39 mgI/mL for 80/Sn150kV, 90/Sn150kV, 100/Sn150kV of EID-CT, and PCD-CT, respectively, without significant differences between PCD-CT and EID-CT (p > 0.05). Radiation dose did not significantly influence error of PCD-CT (p > 0.05) nor EID-CT (p > 0.05). For both scanners, smaller patient sizes were associated with lower errors (p < 0.05). Iodine concentration and base material attenuation significantly influenced quantification for EID-CT (p < 0.05) but not PCD-CT (p > 0.05). In patients, iodine quantification was feasible in liver parenchyma, cysts, hemangiomas, and metastases. Iodine quantification with PCD-CT is accurate in simulated liver parenchyma and lesions irrespective of radiation dose, iodine concentration, and base attenuation and is feasible in common liver lesions in patients.

Optimization of image quality and accuracy of low iodine concentration quantification as function of dose level and reconstruction algorithm for abdominal imaging using dual-source CT: A phantom study

PurposeThe purpose of this study was to assess the impact of advanced modeled iterative reconstruction (ADMIRE) algorithm and dose levels on the accuracy of Hounsfield unit (HU) measurement, image noise and contrast-to-noise ratio (CNR) in virtual monochromatic images (VMIs) with low iodine concentrations, and the accuracy of iodine quantification. Materials and methodsA CT phantom was scanned with dual-source CT using abdomen-pelvis examination parameters at four dose levels: 5, 8, 11 and 20 mGy. Images were reconstructed using filtered-back projection (FBP) and ADMIRE levels 3 and 5 (A3-A5). HU accuracy was assessed calculating the root-mean-square deviation (RMSDHU). Image noise and CNR were computed on VMIs at 40/50/60/70 keV for 4 iodine inserts with 0.5, 1, 2 and 5 mg/mL concentrations. Accuracy of iodine quantification was assessed by the RMSDiodine and iodine bias (IB). ResultsThe RMSDHU decreased significantly as the dose levels increased compared to 5 mGy, except for 8 mGy with A3 (P = 0.380) and with A5 level (P = 0.945). Noise increased by 63.0 ± 3.0 (standard deviation [SD])% from 20 mGy to 5 mGy. Noise decreased significantly by -53.8 ± 0.9 (SD) % with A5 compared to FBP. The CNR decreased by -43.1 ± 6.5 (SD)% from 20 mGy to 5 mGy. It increased using ADMIRE, and as the ADMIRE levels increased. The RMSDiodine and IB decreased as the dose level increased, and this was similar for all reconstruction types. ConclusionADMIRE strongly improves image quality in VMIs and slightly improves HU accuracy but does not affect the accuracy of iodine quantification.

Optimization of image quality and accuracy of low iodine concentration quantification as function of kVp pairs for abdominal imaging using dual-source CT: A phantom study.

To determine the suitable kVp pair for optimal image quality of the virtual monochromatic images (VMIs) and iodine quantification accuracy at low concentration, using a third generation dual-source CT (DSCT). Multi-energy CT phantoms with and without body rings were scanned with a DSCT using four kVp pairs (tube "A"/"B" voltage): 100/Sn150, 90/Sn150, 80/Sn150 and 70/Sn150 kVp. The reference mAs was adjusted to obtain a CTDIvol close to 11mGy. HU values accuracy (RMSDHU), noise (SD) and contrast-to-noise ratio (CNR) of iodine inserts of 0.5, 1, 2 and 5mg/mL concentrations were assessed on VMIs at 40/50/60/70keV. Iodine quantification accuracy was assessed using the RMSDiodine and iodine bias (IBiodine). The RMSDHU decreased when the tube "A" voltage increased. The mean noise value increased significantly with tube "A" voltage (p<0.001) but decreased between 80/Sn150 and 90/Sn150 kVp for the small phantom (1.1±0.1%; p=0.047). The CNR significantly decreased with tube "A" voltage (p<0.001), except between 80/Sn150 and 90/Sn150 kVp for all inserts and between 90/Sn150 kVp and 100/Sn150 kVp for the 1.0 and 0.5mg/mL inserts in the large phantom. In the small phantom, no significant difference was found between 80/Sn150 kVp and 90/Sn150 kVp for all inserts and between 80/Sn150, 90/Sn150 and 100/Sn150 kVp for the 1 and 0.5mg/mL inserts. The RMSDiodine and IBiodine decreased as the tube "A" voltage of the kVp pair increased. The kVp pair of 70/Sn150 led to better image quality in VMIs and sufficient iodine accuracy.

Impact of four kVp combinations available in a dual-source CT on the spectral performance of abdominal imaging: A task-based image quality assessment on phantom data.

PurposeTo compare the spectral performance of four combinations of kVp available in a third generation dual‐source CT (DSCT) on abdominal imaging.MethodsAn image‐quality phantom was scanned with a DSCT using four kVp pairs (tube “A” voltage/tube “B” voltage): 100/Sn150 kVp, 90/Sn150 kVp, 80/Sn150 kVp, and 70/Sn150 kVp, classic parameters and dose level for abdomen examination (CTDIvol: 11 mGy). The noise power spectrum (NPS) and the task‐based transfer function (TTF) of two inserts were computed on virtual monochromatic images (VMIs) at 40/50/60/70 keV and for mixed, low‐, and high‐kVp images. Detectability index (d’) was computed on VMIs and mixed images to model the detection task of liver metastasis (LM) and hepatocellular carcinoma (HCC). Iodine quantification accuracy was assessed using the Root Mean Square Deviation (RMSDiodine) and the iodine bias (IB).ResultsNoise magnitude decreased by −55%± 0% between 40 and 70 keV for all kVp pairs. Compared to 70/Sn150 kVp, noise magnitude was increased by 9% ± 0% with 80/Sn150 kVp, by 16% ± 1% with 90/Sn150 kVp and by 24%± 1% with 100/Sn150 kVp. The average NPS spatial frequency (fav) shifted toward higher frequencies as energy level increased for all kVp pairs. Lowest fav values were found for 70/Sn150 kVp and highest for 100/Sn150 kVp. The value of TTF at 50% (f50) shifted toward lower frequencies with increasing energy level. The highest f50 values occurred for 100/Sn150 kVp and the lowest for 80/Sn150 kVp. For both lesions, d’ was highest for 70/Sn150 kVp and lowest for 100/Sn150 kVp. Compared to 70/Sn150 kVp, d’ decreased by −6% ± 3% with 80/Sn150 kVp, by −11% ± 2% with 90/Sn150 kVp and by −13%± 2% with 100/Sn150 kVp. For all acquisitions, the RSMDiodine and IB were the lowest for 100/Sn150 kVp (0.29 ± 0.10 mg/ml and 0.88 ± 0.30 mg/ml, respectively) and increased when the tube “A” voltage decreased (2.34 ± 0.29 mg/ml for 70/Sn150 kVp and 7.42 ± 0.51 mg/ml respectively).Conclusion70/Sn150 kVp presented the lowest image noise and highest detectability in VMIs of two small focal liver lesions. 100/Sn150 kVp presented the lowest image noise on mixed images and highest accuracy of iodine quantification in iodine images.

Accuracy of iodine quantification using dual-energy computed tomography with focus on low concentrations.

Iodine quantification using dual-energy computed tomography (DECT) is helpful in characterizing, and follow-up after treatment of tumors. Some malignant masses, for instance papillary renal cell carcinomas (p-RCC), are hard to differentiate from benign lesions because of very low contrast enhancement. In these cases, iodine concentrations might be very low, and it is therefore important that iodine quantification is reliable even at low concentrations if this technique is used. To examine the accuracy of iodine quantification and to determine whether it is also accurate for low iodine concentrations. Twenty-six syringes with different iodine concentrations (0-30 mg I/mL) were scanned in a phantom model using a DECT scanner with two different kilovoltage and image reconstruction settings. Iodine concentrations were measured and compared to known concentration. Absolute and relative errors were calculated. For concentrations of 1 mg I/mL or higher, there was an excellent correlation between true and measured iodine concentrations for all settings (R = 0.999-1.000; P < 0.001). For concentrations <1.0 mg I/mL, the relative error was greater. Absolute and relative errors were smaller using tube voltages of 80/Sn140 kV than 100/Sn140 kV (P < 0.01). Reconstructions using a 3.0-mm slice thickness had less variance between repeated acquisitions versus 0.6 mm (P < 0.001). Iodine quantification using DECT was in general very accurate, but for concentrations < 1.0 mg I/mL the technique was less reliable. Using a tube voltage with larger spectral separation was more accurate and the result was more reproducible using thicker image reconstructions.

Metal artifact reduction and tumor detection using photon-counting multi-energy computed tomography.

Metal artifacts are considered a major challenge in computed tomography (CT) as these adversely affect the diagnosis and treatment of patients. Several approaches have been developed to address this problem. The present study explored the clinical potential of a novel photon-counting detector (PCD) CT system in reducing metal artifacts in head CT scans. In particular, we studied the recovery of an oral tumor region located under metal artifacts after correction. Three energy thresholds were used to group data into three bins (bin 1: low-energy, bin 2: middle-energy, and bin 3: high-energy) in the prototype PCD CT system. Three types of physical phantoms were scanned on the prototype PCD CT system. First, we assessed the accuracy of iodine quantification using iodine phantoms at varying concentrations. Second, we evaluated the performance of material decomposition (MD) and virtual monochromatic images (VMIs) using a multi-energy CT phantom. Third, we designed an ATOM phantom with metal insertions to verify the effect of the proposed metal artifact reduction. In particular, we placed an insertion-mimicking an iodine-enhanced oral tumor in the beam path of metallic objects. Normalized metal artifact reduction (NMAR) was performed for each energy bin image, followed by an image-based MD and VMI reconstruction. Image quality was analyzed quantitatively by contrast-to-noise ratio (CNR) measurements. The results of iodine quantification showed a good match between the true and measured iodine concentrations. Furthermore, as expected, the contrast between iodine and the surrounding material was higher in bin 1 image than in bin 3 image. On the other hand, the bin 3 image of the ATOM phantom showed fewer metal artifacts than the bin 1 image because of the higher photon energy. The result of quantitative assessment demonstrated that the 40-keV VMI (CNR: 20.6 ± 1.2) with NMAR and MD remarkably increased the contrast of the iodine-enhanced region compared with that of the conventional images (CNR: 10.4 ± 0.5) having 30 to 140 keV energy levels. The PCD-based multi-energy CT imaging has immense potential to maximize the contrast of the target tissue and reduce metal artifacts simultaneously. We believe that it would open the door to novel applications for the diagnosis and treatment of several diseases.

A novel fast kilovoltage switching dual-energy CT with deep learning: Accuracy of CT number on virtual monochromatic imaging and iodine quantification.

A novel fast kilovoltage switching dual-energy CT with deep learning [Deep learning based-spectral CT (DL-Spectral CT)], which generates a complete sinogram for each kilovolt using deep learning views that complement the measured views at each energy, was commercialized in 2020. The purpose of this study was to evaluate the accuracy of CT numbers in virtual monochromatic images (VMIs) and iodine quantifications at various radiation doses using DL-Spectral CT. Two multi-energy phantoms (large and small) using several rods representing different materials (iodine, calcium, blood, and adipose) were scanned by DL-Spectral CT at varying radiation doses. Images were reconstructed using three reconstruction parameters (body, lung, bone). The absolute percentage errors (APEs) for CT numbers on VMIs at 50, 70, and 100keV and iodine quantification were compared among different radiation dose protocols. The APEs of the CT numbers on VMIs were <15% in both the large and small phantoms, except at the minimum dose in the large phantom. There were no significant differences among radiation dose protocols in computed tomography dose index volumes of 12.3mGy or larger. The accuracy of iodine quantification provided by the body parameter was significantly better than those obtained with the lung and bone parameters. Increasing the radiation dose did not always improve the accuracy of iodine quantification, regardless of the reconstruction parameter and phantom size. The accuracy of iodine quantification and CT numbers on VMIs in DL-Spectral CT was not affected by the radiation dose, except for an extremely low radiation dose for body size.

Effects of Patient Size and Radiation Dose on Iodine Quantification in Dual-Source Dual-Energy CT

The purpose of this study was to investigate the potential effects of patient size and radiation dose on the accuracy of iodine quantification using dual-source dual-energy computed tomography (CT). Three phantoms representing different patient sizes were constructed, containing iodine inserts with concentrations from 0 to 20 mg/ml. Dual-energy CT scans were performed at six dose levels from 2 to 30 mGy. Iodine concentrations were measured using a three-material-decomposition algorithm and their accuracy was assessed. In a small phantom, iodine quantification was accurate and consistent at all dose levels. In a medium phantom, minor underestimations were observed, and the results were consistent except at low dose. In the large phantom, more significant underestimation of iodine concentration was observed at higher doses (≥15 mGy), which was attributed to the beam-hardening effect. At lower doses, increasing upward bias was observed in the CT number, leading to significant overestimations of both iodine concentration and fat fraction, which was attributed to the photon-starvation effect. The severity of the latter effect was determined by mA instead of mAs, suggesting that the electronic noise, rather than the quantum noise, was responsible for the bias. Using higher kVp for the low-energy tube was found to alleviate these effects. Reliable iodine quantification can be achieved using dual-source CT, but the result can be affected by patient size and dose rate. In large patients, biases may occur due to the beam-hardening and the photon-starvation effects, in which case higher dose rate and higher kVp are recommended to minimize these effects.

Spectral CT Imaging-Based Quantification of Iodized Oil Retention following Chemoembolization: Phantom and Animal Studies.

To evaluate accuracy of iodine quantification using spectral CT and the potential of quantitative iodized oil analysis as an imaging biomarker of chemoembolization. A phantom of an artificial liver with 6 artificial tumors containing different amounts of iodized oil (0-8 vol%) was scanned by spectral CT, and iodized oil density (mg/mL) and Hounsfield unit (HU) values were measured. In addition, VX2 hepatoma was induced in 23 rabbits. After chemoembolization using iodized oil chemoemulsion, the rabbits were scanned by spectral CT. The accumulation of iodized oil in the tumor was quantified in terms of iodized oil density and HUs, and the performances in predicting a pathologic complete response (CR) were evaluated by receiver operating characteristic curve analyses. The mean difference between true iodine densities and spectral image-based measurements was 0.5 mg/mL. Mean HU values were highly correlated with mean iodine density (r2= 1.000, P < .001). In the animal study, a pathologic CR was observed in 17 of 23 rabbits (73.9%). The range of area under the curve values of iodine and HU measurements was 0.863-0.882. A tumoral iodine density of 3.57 mg/mL, which corresponds to 0.7 vol% iodized oil in the tumor, predicted a pathologic CR with a sensitivity of 70.6% and a specificity of 100.0%. Spectral CT imaging has a potential to predict tumor responses after chemoembolization by quantitatively assessing iodized oil in targets.

Impact of Patient Size and Radiation Dose on Accuracy and Precision of Iodine Quantification and Virtual Noncontrast Values in Dual-layer Detector CT—A Phantom Study

Iodine quantification (IQ) and virtual noncontrast (VNC) images produced by dual-energy CT (DECT) can be used for various clinical applications. We investigate the performance of dual-layer DECT (DLDECT) in different phantom sizes and varying radiation doses and tube voltages, including a low-dose pediatric setting. Three phantom sizes (simulating a 10-year-old child, an average, and a large-sized adult) were scanned with iodine solution inserts with concentrations ranging 0-32 mg/ml, using the DLDECT. Each phantom size was scanned with CTDIvol 2-15 mGy at 120 and 140 kVp. The smallest phantom underwent additional scans with CTDIvol 0.9-1.8 mGy. All scans were repeated 3 times. Each iodine insert was analyzed using VNC and IQ images for accuracy and precision, by comparison to known values. For scans from 2 to 15 mGy mean VNC attenuation and IQ error in the iodine inserts in the small, medium, and large phantoms was 1.2 HU ± 3.2, -1.2 HU ± 14.9, 2.6 HU ± 23.6; and +0.1 mg/cc ± 0.4, -0.9 mg/cc ± 0.9, and -1.8 mg/cc ± 1.8, respectively. In this dose range, there were no significant differences (p ≥ 0.05) in mean VNC attenuation or IQ accuracy in each phantom size, while IQ was significantly less precise in the small phantom at 2 mGy and 10 mGy (p < 0.05). Scans with CTDIvol 0.9-1.8 mGy in the small phantom showed a limited, but statistically significantly lower VNC attenuation precision and IQ accuracy (-0.5 HU ± 5.3 and -0.3 mg/cc ± 0.5, respectively) compared to higher dose scans in the same phantom size. Performance of iodine quantification and subtraction by VNC images in DLDECT is largely dose independent, with the primary factor being patient size. Low-dose pediatric scan protocols have a significant, but limited impact on IQ and VNC attenuation values.

Effects of radiation dose levels and spectral iterative reconstruction levels on the accuracy of iodine quantification and virtual monochromatic CT numbers in dual-layer spectral detector CT: an iodine phantom study.

The purpose of this study is to investigate the accuracy of iodine quantification and virtual monochromatic CT numbers obtained with the dual-layer spectral CT (DLCT) using a phantom at different radiation dose levels and spectral iterative reconstruction (IR) levels. An abdomen phantom with seven iodine inserts (2.0, 2.5, 5.0, 7.5, 10.0, 15.0, 20.0 mg/mL) was imaged using a DLCT scanner. Five repeated scans were performed at computed tomography dose index volume (CTDIvol) levels of 5, 10, 15, 20, 25 mGy at tube voltages of 120 and 140 kVp, respectively. Spectral-based images were reconstructed using four spectral IR levels (spectral level of 0, 2, 4, 6). Iodine density images and virtual monochromatic images (VMI) at energy levels of 50, 70 and 120 keV were created. The absolute percentage bias (APB) of the measured iodine concentration and the true iodine concentration, and the measured VMI CT numbers and the theoretical VMI CT numbers were compared to determine the difference of radiation dose levels and different spectral IR levels. At CTDIvol levels of 25, 20, 15, 10 mGy, radiation dose levels had no effect on the accuracy of iodine quantitation; at CTDIvol level of 5 mGy, the accuracy of iodine quantification was the poorest, with the mean APBiodine of 4.33% (P<0.05). There was no significant difference in the accuracy of iodine quantitation between 120 and 140 kVp (P=0.648). At energy levels of 50, 70 and 120 keV, there was no significant difference in the accuracy of the VMI CT numbers among the CTDIvol levels of 25, 20 and 15 mGy. However, the accuracy of VMI CT numbers was significantly degraded at the CTDIvol levels of 10 and 5 mGy (P<0.05). At energy level of 50 keV, the accuracy of VMI CT numbers was not affected by tube voltages (kVps) used (P=0.125). At the energy levels of 70 and 120 keV, 140 kVp produced a smaller bias than 120 kVp, with the mean APBHU at 120 and 140 kVp being of 3.62% vs. 2.99% for 70 keV (P<0.01), and 11.65% vs. 9.28% for 120 keV (P<0.01), respectively. Spectral IR levels did not affect the accuracy of iodine quantification and VMI CT numbers (P=0.998, P=0.963). The accuracy of iodine quantification and VMI CT numbers was only affected by very low radiation dose levels. At the clinically applied radiation dose levels of >10 mGy, the accuracy of both iodine quantification and VMI CT numbers is relatively stable and high.

High-Pitch Wide-Coverage Fast-Kilovoltage-Switching Dual-Energy CT: Impact of Pitch on Noise, Spatial Resolution, and Iodine Quantification in a Phantom Study.

The purpose of this study was to assess the impact of high pitch values on image noise, spatial resolution, and iodine quantification in single-source wide-coverage fast-kilovoltage-switching dual-energy CT (DECT). Two phantom experiments were conducted. First, image noise and spatial resolution in the x-, y-, and z-directions were assessed. Second, the accuracy of iodine quantification was investigated with multiple-size phantoms with pure iodine and blood-iodine inserts. Both phantoms were scanned repeatedly with a third-generation fast-kilovoltage-switching DECT scanner with a collimation width of 80 mm at four different pitch values (0.5, 0.99, 1.375, 1.53) and three different gantry rotation times (0.6, 0.8, 1.0 second). Image noise, spatial resolution, and absolute error of iodine concentration (E) were measured. A linear mixed effects model was used to determine the effect of pitch, rotation time, and size on the error of iodine concentration. Image noise and xy spatial resolution were comparable among the four pitch values. Spatial resolution in the z-direction was inferior and had higher variance at a low pitch of 0.5 compared with pitches of 0.99, 1.375, and 1.53. Error of iodine concentration was significantly affected by pitch and rotation time (p < 0.001). E decreased with increasing pitch and decreasing rotation time. In detail, mean E was 0.91 ± 0.47 mg I/mL for a pitch of 0.5, 0.52 ± 0.29 mg I/mL for 0.99, 0.44 ± 0.25 mg I/mL for 1.375, and 0.40 ± 0.25 mg I/mL for 1.53. High-pitch wide-coverage fast-kilovoltage-switching DECT can be performed without impairing image quality or iodine quantification, and the results are superior to those of imaging at a low pitch of 0.5.

Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images.

Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.

Development of a dual-energy computed tomography quality control program: Characterization of scanner response and definition of relevant parameters for a fast-kVp switching dual-energy computed tomography system.

A prototype QC phantom system and analysis process were developed to characterize the spectral capabilities of a fast kV-switching dual-energy computed tomography (DECT) scanner. This work addresses the current lack of quantitative oversight for this technology, with the goal of identifying relevant scan parameters and test metrics instrumental to the development of a dual-energy quality control (DEQC). A prototype elliptical phantom (effective diameter: 35 cm) was designed with multiple material inserts for DECT imaging. Inserts included tissue equivalent and material rods (including iodine and calcium at varying concentrations). The phantom was scanned on a fast kV-switching DECT system using 16 dual-energy acquisitions (CTDIvol range: 10.3-62 mGy) with varying pitch, rotation time, and tube current. The circular head phantom (22 cm diameter) was scanned using a similar protocol (12 acquisitions; CTDIvol range: 36.7-132.6 mGy). All acquisitions were reconstructed at 50, 70, 110, and 140 keV and using a water-iodine material basis pair. The images were evaluated for iodine quantification accuracy, stability of monoenergetic reconstruction CT number, noise, and positional constancy. Variance component analysis was used to identify technique parameters that drove deviations in test metrics. Variances were compared to thresholds derived from manufacturer tolerances to determine technique parameters that had a nominally significant effect on test metrics. Iodine quantification error was largely unaffected by any of the technique parameters investigated. Monoenergetic HU stability was found to be affected by mAs, with a threshold under which spectral separation was unsuccessful, diminishing the utility of DECT imaging. Noise was found to be affected by CTDIvol in the DEQC body phantom, and CTDIvol and mA in the DEQC head phantom. Positional constancy was found to be affected by mAs in the DEQC body phantom and mA in the DEQC head phantom. A streamlined scan protocol was developed to further investigate the effects of CTDIvol and rotation time while limiting data collection to the DEQC body phantom. Further data collection will be pursued to determine baseline values and statistically based failure thresholds for the validation of long-term DECT scanner performance.

Accuracy of iodine quantification in dual-layer spectral CT: Influence of iterative reconstruction, patient habitus and tube parameters

PurposeEvaluation of the influence of iterative reconstruction, tube settings and patient habitus on the accuracy of iodine quantification with dual-layer spectral CT (DL-CT). Material and methodsA CT abdomen phantom with different extension rings and four iodine inserts (1, 2, 5 and 10 mg/ml) was scanned on a DL-CT. The phantom was scanned with tube-voltages of 120 and 140 kVp and CTDIvol of 2.5, 5, 10 and 20 mGy. Reconstructions were performed for eight levels of iterative reconstruction (i0-i7). Diagnostic dose levels are classified depending on patient-size and radiation dose. ResultsMeasurements of iodine concentration showed accurate and reliable results. Taking all CTDIvol-levels into account, the mean absolute percentage difference (MAPD) showed less accuracy for low CTDIvol-levels (2.5 mGy: 34.72%) than for high CTDIvol-levels (20 mGy: 5.89%). At diagnostic dose levels, accurate quantification of iodine was possible (MAPD 3.38%). Level of iterative reconstruction did not significantly influence iodine measurements. Iodine quantification worked more accurately at a tube voltage of 140 kVp. Phantom size had a considerable effect only at low-dose-levels; at diagnostic dose levels the effect of phantom size decreased (MAPD <5% for all phantom sizes). ConclusionWith DL-CT, even low iodine concentrations can be accurately quantified. Accuracies are higher when diagnostic radiation doses are employed.

Objective image characterization of a spectral CT scanner with dual-layer detector

This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm−1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.