Iodine quantification using dual-energy multidetector computed tomography imaging: phantom study assessing the impact of iterative reconstruction schemes and patient habitus on accuracy

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

BACKGROUND

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.

PURPOSE

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 were explored.

METHODS

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-specific parameters.

RESULTS

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 obese population.

CONCLUSIONS

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 tube potentials.

Dual-energy index variation when evaluating the potential ferromagnetism of ex vivo bullets

Background

An MRI is potentially hazardous for patients with retained ferromagnetic bullets. Recent studies have aimed to develop dual-energy computed tomography (DECT) as a screening tool for recognising highly ferromagnetic bullets. Inconsistent findings have been ascribed to inherent CT technology differences. Previous research demonstrated significant Hounsfield unit (HU) measurement variation among single-source CT machines.

Objectives

This study investigated the theoretical dual-energy index (DEI) variation between DECT machines when evaluating the potential ferromagnetic properties within the same sample of ex vivo bullets and metal phantoms.

Method

An experimental ex vivo study was conducted on eight metal phantoms and 10 unused bullets individually positioned in the same Perspex head phantom and scanned on two DECT machines. Two senior radiology registrars independently recorded the HU readings, and DEI values were calculated. Statistical analysis was performed using non-parametric methods for paired data, namely the Signed Rank Test. The DEI values based on mean HU readings between the DECT machines were compared.

Results

Inter- and intra-reader agreement was not statistically significant. The metal phantoms had poor interscanner agreement, with an overlap of the ferromagnetic and non-ferromagnetic ranges. The bullets had good interscanner agreement, with a similar ferromagnetic to non-ferromagnetic relationship.

Conclusion

The use of DEI values negates the previous assumption that significant interscanner variability exists among different DECT technologies while assessing highly attenuative ex vivo bullets.

Contribution

This investigation demonstrated that even though HU readings may be variable, the implementation of the DEI equation translates this into comparable values with good interscanner agreement.

Contrast thresholds for detection of various iodine concentrations in subtraction CT and dual-energy CT systems

OBJECTIVE

To estimate the minimum iodine concentrations detectable in simulated vessels of various diameters for both subtraction computed tomography (CT) and dual-energy CT systems.

METHODS

Fillable tubes (diameters: 1, 3, and 5 mm) were filled with a variety of iodine concentrations (range: 0-20 mg/ml), placed in the center of 28-mm cylindrical rods and surrounded with water. Rods with and without fillable tubes were placed in a 20-cm cylindrical solid-water phantom to simulate administration of iodine in blood vessels. The phantom was scanned with clinical subtraction CT (SCT) and dual-energy CT (DECT) head protocols to assess the detection of minimum iodine concentrations in both systems. The SCT and DECT images were evaluated quantitatively with a MATLAB script to extract regions of interest (ROIs) of each simulated vessel. ROI measurements were used to calculate the limit of detectability (LOD) and signal-to-noise ratio of Rose criteria for the assessment of the contrast thresholds.

RESULTS

Both SNR_Rose and LOD methods agreed and determined the minimum detectable iodine concentration to be 0.4 mg/ml in the 5-mm diameter vessel for SCT. However, the minimum detectable concentration in the 5-mm vessel with DECT was 1 mg/ml. The 3-mm vessel had a minimum detectable concentration of 0.8 mg/ml for SCT and 2 mg/ml for DECT. Lastly, the minimum detectable iodine concentration for the 1-mm vessel was 10 mg/ml for SCT and 10 mg/ml for DECT.

CONCLUSION

In this phantom study, SCT showed the capability to detect lower iodine concentrations compared to DECT. Contrast thresholds varied for vessels of different diameters and the smaller vessels required a higher iodine concentration for detection. Based on this knowledge, radiologists can modify their protocols to increase contrast enhancement.

Detection of axillary lymph node metastasis in breast cancer using dual-layer spectral computed tomography

PURPOSE

To investigate the value of contrast-enhanced dual-layer spectral computed tomography (DLCT) in the detection of axillary lymph node (ALN) metastasis in breast cancer.

MATERIALS AND METHODS

In this prospective study, 31 females with breast cancer underwent contrast-enhanced DLCT from August 2019 to June 2020. All ALNs were confirmed by postoperative histology. Spectral quantitative parameters, including λ _HU (in Hounsfield units per kiloelectron-volt), nIC (normalized iodine concentration), and Z_eff (Z-effective value) in both arterial and delay phases, were calculated and contrasted between metastatic and nonmetastatic ALNs using the McNemar test. Discriminating performance from metastatic and nonmetastatic ALNs was analyzed using receiver operating characteristic curves.

RESULTS

In total, 132 ALNs (52 metastatic and 80 nonmetastatic) were successfully matched between surgical labels and preoperative labels on DLCT images. All spectral quantitative parameters (λ_Hu , nIC, and Z_eff) derived from both arterial and delayed phases were greater in metastatic ALNs than in nonmetastatic SLNs (all p < 0.001). Logistic regression analyses showed that λ_Hu in the delayed phase was the best single parameter for the detection of metastatic ALNs on a per-lymph node basis, with an area under the curve of 0.93, accuracy of 86.4% (114/132), sensitivity of 92.3% (48/52), and specificity of 87.5% (70/80).

CONCLUSION

The spectral quantitative parameters derived from contrast-enhanced DLCT, such as λ_Hu , can be applied for the preoperative detection of ALN metastasis in breast cancer.

Quantitative dual-energy CT techniques in the abdomen

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

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

BACKGROUND

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.

PURPOSE

To examine the accuracy of iodine quantification and to determine whether it is also accurate for low iodine concentrations.

MATERIAL AND METHODS

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.

RESULTS

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).

CONCLUSION

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.

Characterization of size-specific effects during dual-energy CT material decomposition of non-iodine materials

PURPOSE

The dual-energy CT (DECT) LiverVNC application class in the Siemens Syngo.via software has been used to perform non-iodine material decompositions. However, the LiverVNC application is designed with an optional size-specific calibration based on iodine measurements. This work investigates the effects of this iodine-based size-specific calibration on non-iodine material decomposition and benchmarks alternative methods for size-specific calibrations.

METHODS

Calcium quantification was performed with split-filter and sequential-scanning DECT techniques on the Siemens SOMATOM Definition Edge CT scanner. Images were acquired of the Gammex MECT abdomen and head phantom containing calcium inserts with concentrations ranging from 50-300 mgCa/ml. Several workflows were explored investigating the effects of size-specific dual-energy ratios (DERs) and the beam hardening correction (BHC) function in the LiverVNC application. Effects of image noise were also investigated by varying CTDIvol and using iterative reconstruction (ADMIRE).

RESULTS

With the default BHC activated, Syngo.via underestimated the calcium concentrations in the abdomen for sequential-scanning acquisitions, leaving residual calcium in the virtual non-contrast images and underestimating calcium in the enhancement images for all DERs. Activation of the BHC with split-filter images resulted in a calcium over- or underestimation depending on the DER. With the BHC inactivated, the use of a single DER led to an under- or overestimate of calcium concentration depending on phantom size and DECT modality. Optimal results were found with BHC inactivated using size-specific DERs. CTDIvol levels and ADMIRE had no significant effect on results.

CONCLUSION

When performing non-iodine material decomposition in the LiverVNC application class, it is important to understand the implications of the BHC function and to account for patient size appropriately. The BHC in the LiverVNC application is specific to iodine and leads to inaccurate quantification of other materials. The inaccuracies can be overcome by deactivating the BHC function and using size-specific DERs, which provided the most accurate calcium quantification.

Dual-Energy CT-Based Iodine Quantification in Liver Tumors - Impact of Scan-, Patient-, and Position-Related Factors

RATIONALE AND OBJECTIVES

To quantify the contribution of lesion location and patient positioning, dual-energy approach, patient size, and radiation dose to the error of dual-energy CT-based iodine quantification (DECT-IQ) in liver tumors.

MATERIALS AND METHODS

A phantom with four liver lesions (diameter 15 mm; iodine concentration 0-5 mgI/mL) and two sizes was used. One lesion emulated a subdiaphragmatic lesion. Both sizes were imaged in dual-energy mode on (1) a dual-source DECT (DS-DE) at 100/Sn150 kV and (2) a single-source split-filter DECT (SF-DE) at AuSn120 kV at two radiation doses (8 and 12 mGy). Scans were performed at seven different vertical table positions (from -6 to + 6 cm from the gantry isocenter). Iodine concentration was repeatedly measured and absolute errors (error_abs) were calculated. Errors were compared using robust repeated-measures ANOVAs with post-hoc comparisons. A linear mixed effect model was used to determine the factors influencing the error of DECT-IQ.

RESULTS

The linear mixed effect models showed that errors were significantly influenced by DECT approach, phantom size, and lesion location (all p < 0.001). The impact of lesion location on the error was stronger in SF-DE compared to DS-DE. Radiation dose did not significantly influence error (p = 0.22). When averaged across all setups, error_abs was significantly higher for SF-DE (2.08 ± 1.92 mgI/mL) compared to DS-DE (0.37 ± 0.29 mgI/mL) (all p < 0.001). Artefacts were found in the subdiaphragmatic lesion for SF-DE with significantly increased error_abs compared to DS-DE (p < 0.001). Error_abs was significantly higher in the large compared to the medium phantom for DS-DE (0.30 ± 0.23 mgI/mL vs. 0.43 ± 0.33 mgI/mL) and SF-DE (1.68 ± 1.99 vs. 2.36 ± 1.81 mgI/mL) (p < 0.001).

CONCLUSION

The dual-energy approach, patient size, and lesion location modified by patient position significantly impacted DECT-IQ in simulated liver tumors.

Single-source dual energy CT to assess myocardial extracellular volume fraction in aortic stenosis before transcatheter aortic valve implantation (TAVI)

PURPOSE

To assess myocardial extracellular volume fraction (ECV) measurement provided by a single-source dual-energy computed tomography (SSDE-CT) acquisition added at the end of a routine CT examination before transcatether aortic valve implantation (TAVI) compared to cardiac magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Twenty-one patients (10 men, 11 women; mean age, 86±4.9 years [SD]; age range: 71-92 years) with severe aortic stenosis underwent standard pre-TAVI CT with additional cardiac SSDE-CT acquisition 7minutes after intravenous administration of iodinated contrast material and myocardial MRI including pre- and post-contrast T1-maps. Myocardial ECV and standard deviation (σECV) were calculated in the 16-segments model. ECV provided by SSDE-CT was compared to ECV provided by MRI, which served as the reference. Analyses were performed on a per-segment basis and on a per-patient involving the mean value of the 16-segments.

RESULTS

ECV was slightly overestimated by SSDE-CT (29.9±4.6 [SD] %; range: 20.9%-48.3%) compared to MRI (29.1±3.9 [SD] %; range: 22.0%-50.7%) (P<0.0001) with a bias and limits of agreement of +2.3% (95%CI: -16.1%-+20.6%) and +2.5% (95%CI: -2.1%-+7.1%) for per-segment and per-patient-analyses, respectively. Good (r=0.81 for per-segment-analysis) to excellent (r=0.97 for per-patient-analysis) linear relationships (both P<0.0001) were obtained. The σECV was significantly higher at SSDE-CT (P<0.0001). Additional radiation dose from CT was 1.89±0.38 (SD) mSv (range: 1.48-2.47 mSv).

CONCLUSION

A single additional SSDE-CT acquisition added at the end of a standard pre-TAVI CT protocol can provide ECV measurement with good to excellent linear relationship with MRI.

Accuracy of spectral curves at different phantom sizes and iodine concentrations using dual-source dual-energy computed tomography

To validate the accuracy of spectral curves obtained by an image-data-based algorithm and clarify the error factors that reduce accuracy. Iodine rods of known composition and different concentrations were inserted into a cylinder or elliptic-cylinder phantom and scanned according to the dual-energy protocol. Spectral curves were obtained by (i) theoretical calculation, (ii) image-data-based 2-material decomposition, and (iii) using a dedicated workstation. Accuracy was verified by comparing the spectral curve obtained by theoretical calculations with those obtained by the image-data-based algorithms or the dedicated workstations. For a quantitative evaluation, the error and relative error (RE) were calculated. In the image-data-based calculation, the errors with respect to the theoretical CT number ranged from - 8.3 to 71.1 HU. For all 192 combinations, 80.7% of the errors were under ± 15 HU, and 97.9% of the REs were under 10%. In the dedicated workstation, the errors ranged from - 94.7 to 26.8 HU. For all combinations, 68.8% of the errors were under ± 15 HU, and 68.2% of the REs were under 10%. By appropriately setting the effective energy corresponding to the CT number of the basis materials, an accurate spectral curve can be obtained. The beam-hardening effect is canceled by the 2-material decomposition process even without beam-hardening correction. Accuracy is primarily reduced by scattered radiation rather than the beam-hardening effect.

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

RATIONALE AND OBJECTIVES

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).

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSION

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.

Dual-energy computed tomography for non-invasive staging of liver fibrosis: Accuracy of iodine density measurements from contrast-enhanced data

AIM

To investigate whether iodine density measurements from contrast-enhanced dual-energy computed tomography (CT) data can non-invasively stage liver fibrosis.

METHODS

This single-center, prospective study was approved by our IRB with written informed consent. Forty-seven consecutive patients (26 men and 21 women; mean age, 63.1 years) with chronic liver disease underwent contrast-enhanced dual-energy CT of the liver (non-contrast, arterial, portal venous, and equilibrium phase images), followed by liver biopsy. Iodine density of liver and aorta were obtained by two independent observers. Iodine uptake of the liver (Δ Liver), representing the difference in iodine density between equilibrium phase and non-contrast images, was calculated and normalized by aorta (Δ Liver/Aorta). We accounted for contrast agent distribution volume by using hematocrit level. Accuracy of iodine density measurements for staging liver fibrosis was assessed by using receiver operating characteristic (ROC) curves. Multivariate linear regression analysis was used to assess the impact of independent variables (liver fibrosis stage and patient-related confounders) on iodine uptake.

RESULTS

The Δ Liver/Aorta significantly increased and moderately correlated with METAVIR liver fibrosis stage (ρ = 0.645, P < 0.001). Areas under the ROC curve ranged from 0.795 to 0.855 for discriminating each liver fibrosis score (≥F1-F4). METAVIR fibrosis stage was the most significant independent factor associated with Δ Liver (P = 0.005) and Δ Liver/Aorta (P < 0.001).

CONCLUSION

Hepatic extracellular volume fraction with contrast-enhanced dual-energy CT can non-invasively stage liver fibrosis in chronic liver diseases. This technique could prove useful for monitoring disease progression and treatment response, potentially reducing the need for liver biopsy.

Axillary Sentinel Lymph Nodes in Breast Cancer: Quantitative Evaluation at Dual-Energy CT

Purpose To evaluate the diagnostic performance of quantitative parameters derived from dual-energy CT for the preoperative diagnosis of metastatic sentinel lymph nodes (SLNs) in participants with breast cancer. Materials and Methods For this prospective study, dual-phase contrast agent-enhanced CT was performed in female participants with breast cancer from June 2015 to December 2017. Quantitative dual-energy CT parameters and morphologic parameters were compared between metastatic and nonmetastatic SLNs. The quantitative parameters were fitted to univariable and multivariable logistic regression models. The diagnostic role of morphologic and quantitative parameters was analyzed by receiver operating characteristic curves and compared by using the McNemar test. Results This study included 193 female participants (mean age, 47.6 years ± 10.1; age range, 22-79 years). Quantitative dual-energy CT parameters including slope of the spectral Hounsfield unit curve (λ_Hu) measured at both arterial and venous phases, normalized iodine concentration at both arterial and venous phase, and normalized effective atomic number at the venous phase were higher in metastatic than in nonmetastatic SLNs (P value range, ≤.001 to .031). Univariable and multivariable logistic regression analyses showed that venous phase λ_Hu (in Hounsfield units per kiloelectron-volt) was the best single parameter for the detection of metastatic SLNs. The accuracy of the venous phase λ_Hu for detecting metastatic SLNs was 90.5% on a per-lymph node basis and 87.0% on a per-patient basis. The accuracy and specificity at venous phase λ_Hu was higher than their counterparts in the morphologic parameters (P < .001). Conclusion Dual-energy CT is a complementary means for the preoperative identification of sentinel lymph nodes metastases in participants with breast cancer. © RSNA, 2018 Online supplemental material is available for this article.

Imaging of suspected pulmonary embolism and deep venous thrombosis in obese patients

Obesity is a growing problem around the world, and radiology departments frequently encounter difficulties related to large patient size. Diagnosis and management of suspected venous thromboembolism, in particular deep venous thrombosis (DVT) and pulmonary embolism (PE), are challenging even in some lean patients, and can become even more complicated in the setting of obesity. Many obstacles must be overcome to obtain imaging examinations in obese patients with suspected PE and/or DVT, and to ensure that these examinations are of sufficient quality to diagnose or exclude thromboembolic disease, or to establish an alternative diagnosis. Equipment limitations and technical issues both need to be acknowledged and addressed. Table weight limits and scanner sizes that readily accommodate obese and even morbidly obese patients are not in place at many clinical sites. There are also issues with image quality, which can be substantially compromised. We discuss current understanding of the effects of patient size on imaging in general and, more specifically, on the imaging modalities used for the diagnosis and treatment of DVT and PE. Emphasis will be placed on the technical parameters and protocol nuances, including contrast dosing, which are necessary to refine and optimize images for the diagnosis of DVT and PE in obese patients, while remaining cognizant of radiation exposure. More research is necessary to develop consistent high-level evidence regarding protocols to guide radiologists, and to help them effectively utilize emerging technology.

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

PURPOSE

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).

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Quantification of Iodine Concentration Using Single-Source Dual-Energy Computed Tomography in a Calf Liver

OBJECTIVE

To evaluate the accuracy of single-source dual-energy computed tomography (ssDECT) in iodine quantification using various segmentation methods in an ex vivo model.

METHODS

Ten sausages, injected with variable quantities of iodinated contrast, were inserted into 2 livers and scanned with ssDECT. Material density iodine images were reconstructed. Three radiologists segmented each sausage. Iodine concentration, volume, and absolute quantity were measured. Agreement between the measured and injected iodine was assessed with the concordance correlation coefficient (CCC). Intrareader agreement was assessed using the intraclass correlation coefficient (ICC).

RESULTS

Air bubbles were observed in sausage (IX). Sausage (X) was within the same view as hyper-attenuating markers used for localization. With IX and X excluded, CCC and ICC were greater than 0.98 and greater than 0.88. When included, CCC and ICC were greater than 0.94 and greater than 0.79.

CONCLUSIONS

Iodine quantification was reproducible and precise. However, accuracy reduced in sausages consisting of air filled cavities and within the same view as hyperattenuating markers.

Dual-energy CT: a phantom comparison of different platforms for abdominal imaging

OBJECTIVES

Evaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT).

METHODS

A semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated.

RESULTS

For all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT).

CONCLUSION

Noticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT.

KEY POINTS

• Current dual-energy CT platforms provide accurate, reliable quantitative information. • Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems. • Dual-layer CT offers constant noise levels over the complete energy range.

An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography

OBJECTIVES

Conventional material decomposition techniques for dual-energy computed tomography (CT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact.

MATERIALS AND METHODS

Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (eg, iodine, calcium) are assigned a multiplier of 1, whereas ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at dual-source CT and rapid kVp-switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium, and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the 3 contrast materials.

RESULTS

All 5 material combinations-tungsten, iodine, and calcium, and mixtures of tungsten-calcium and iodine-calcium-showed distinct dual-energy ratios, largely independent of material concentration at both dual-source CT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL, and 0.4 mg/mL for iodine, calcium, and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the 3 extracted material phases, vascular iodine, oral tungsten, and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image; however, this did not impede the depiction of the vasculature.

CONCLUSIONS

The CMEP is a straightforward, image-domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors.

Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT

PURPOSE

Determine iodine content threshold discriminating papillary renal cell carcinomas (pRCC) from complex cysts (CCs) using rapid kV-switching dual-energy CT (rsDECT).

MATERIALS AND METHODS

IRB-approved retrospective study of 72 consecutive patients with pathologic diagnosis of renal cell carcinoma, who underwent rsDECT from 2011 to 2015. Controls included consecutive patients with CC during same period. Iodine content of each pRCC (n = 27) was measured on rsDECT workstation for arterial (n = 15) or nephrographic phase (n = 12), and compared to iodine content for clear cell renal cell carcinomas (ccRCC, n = 46) and complex cysts (n = 54). An optimal iodine content threshold was estimated using logistic regressions and Youden's J based on maximum specificity and sensitivity.

RESULTS

Iodine threshold of 1.28 mg/cc was optimal to discriminate between pRCCs and CCs for nephrographic phase (sens 1.0, spec 0.96, PPV 0.92, and NPV 1.0, AUC 0.997, acc 0.97, p < 0.0001). Iodine threshold of 1.22 mg/cc was the optimal cutoff value to discriminate between pRCCs and CCs in the arterial phase (sens 0.67, spec 0.97, PPV 0.91, NPV 0.85, AUC 0.76, and acc 0.84, p = 0.006). The optimal threshold to discriminate between ccRCCs and pRCCs was 1.85 mg/cc in the arterial phase (sens 0.87, spec 0.92, PPV 0.87, NPV 0.92, p < 0001) and 2.71 mg/cc in the nephrographic phase (sens 1.0, spec 1.0, PPV 1.0, NPV 1.0, p < 0.0001).

CONCLUSIONS

Quantitative iodine values on rsDECT discriminate between papillary RCC and complex cysts, and between papillary RCC and clear cell RCC, the former addressing an important clinical challenge particularly when an unenhanced series has not been performed. These rsDECT thresholds differ from values derived from dual-source DECT technology.

Osteitis: a retrospective feasibility study comparing single-source dual-energy CT to MRI in selected patients with suspected acute gout

OBJECTIVE

Dual-energy computed tomography detects tophi in patients with chronic gout. However, other information that can be obtained from the same scan is not the focus of the current research, e.g., the detection of bone marrow edema (BME) using virtual bone marrow imaging (VBMI). The aim of this study was to evaluate if BME in patients with acute arthritis can be detected with VBMI using magnetic resonance imaging (MRI) as the standard of reference.

MATERIALS AND METHODS

This retrospective study included 11 patients who underwent both MRI and dual-energy computed tomography (mean interval of 40 days). BME in MRI (standard of reference) and VBMI was judged independently by two different blinded readers. φ-correlation coefficient and Cohen's κ were performed for statistical analysis. Approval was waived by the IRB.

RESULTS

Two patients with a final diagnosis of RA and one with septic arthritis showed osteitis on MRI and VBMI. However, in each case, there were individual bones identified with osteitis on MRI but not VBMI. Three additional patients with the final diagnosis of RA were identified correctly as negative for BME. There was a good correlation between both modalities (φ = 0.8; κ = 0.8). Inter-rater reliability was excellent for both modalities (κ = 0.9).

CONCLUSIONS

We have shown that detecting osteitis using VBMI is feasible in patients with inflammatory arthritis. Further studies are needed on larger, more-targeted populations to better define the indications, accuracy, and added value of this technique.

CT spectral imaging for monitoring the therapeutic efficacy of VEGF receptor kinase inhibitor AG-013736 in rabbit VX2 liver tumours

PURPOSE

The aim of this study was to evaluate the value of computed tomography (CT) spectral imaging in assessing the therapeutic efficacy of a vascular endothelial growth factor (VEGF) receptor inhibitor AG-013736 in rabbit VX2 liver tumours.

METHODS

Twenty-three VX2 liver tumour-bearing rabbits were scanned with CT in spectral imaging mode during the arterial phase (AP) and portal phase (PP). The iodine concentrations(ICs)of tumours normalized to aorta (nICs) at different time points (baseline, 2, 4, 7, 10, and 14 days after treatment) were compared within the treated group (n = 17) as well as between the control (n = 6) and treated groups. Correlations between the tumour size, necrotic fraction (NF), microvessel density (MVD), and nICs were analysed.

RESULTS

The change of nICs relative to baseline in the treated group was lower compared to the control group. A greater decrease in the nIC of a tumour at 2 days was positively correlated with a smaller increase in tumour size at 14 days (P < 0.05 for both). The tumour nIC values in AP and PP had correlations with MVD (r = 0.71 and 0.52) and NF (r = -0.54 and -0.51) (P < 0.05 for all).

CONCLUSIONS

CT spectral imaging allows for the evaluation and early prediction of tumour response to AG-013736.

KEY POINTS

• AG-013736 treatment response was evaluated by CT in a rabbit tumour model. • CT spectral imaging allows for the early treatment monitoring of targeted anti-tumour therapies. • Spectral CT findings correlated with vascular changes after anti-tumour therapies. • Spectral CT is a promising method for assessing clinical treatment response.

Accuracy of dual-energy computed tomography for the quantification of iodine in a soft tissue-mimicking phantom

The objective of this study was to evaluate the accuracy of dual-energy CT (DECT) for quantifying iodine using a soft tissue-mimicking phantom across various DECT acquisition parameters and dual-source CT (DSCT) scanners. A phantom was constructed with plastic tubes containing soft tissue-mimicking materials with known iodine concentrations (0-20 mg/mL). Experiments were performed on two DSCT scanners, one equipped with an integrated detector and the other with a conventional detector. DECT data were acquired using two DE modes (80 kV/Sn140 kV and 100 kV/Sn140 kV) with four pitch values (0.6, 0.8, 1.0, and 1.2). Images were reconstructed using a soft tissue kernel with and without beam hardening correction (BHC) for iodine. Using the dedicated DE software, iodine concentrations were measured and compared to true concentrations. We also investigated the effect of reducing gantry rotation time on the DECT-based iodine measurement. At iodine concentrations higher than 10 mg/mL, the relative error in measured iodine concentration increased slightly. This error can be decreased by using the kernel with BHC, compared with the kernel without BHC. Both 80 kV/Sn140 kV and 100 kV/Sn140 kV modes could provide accurate quantification of iodine content. Increasing pitch value or reducing gantry rotation time had only a minor impact on the DECT-based iodine measurement. The DSCT scanner, equipped with the new integrated detector, showed more accurate iodine quantification for all iodine concentrations higher than 10 mg/mL. An accurate quantification of iodine can be obtained using the second-generation DSCT scanner in various DE modes with pitch values up to 1.2 and gantry rotation time down to 0.28 s. For iodine concentrations ≥ 10 mg/mL, using the new integrated detector and the kernel with BHC can improve the accuracy of DECT-based iodine measurements.

Interdependencies of acquisition, detection, and reconstruction techniques on the accuracy of iodine quantification in varying patient sizes employing dual-energy CT

PURPOSE

To assess the impact of patient habitus, acquisition parameters, detector efficiencies, and reconstruction techniques on the accuracy of iodine quantification using dual-source dual-energy CT (DECT).

MATERIALS AND METHODS

Two phantoms simulating small and large patients contained 20 iodine solutions mimicking vascular and parenchymal enhancement from saline isodensity to 400 HU and 30 iodine solutions simulating enhancement of the urinary collecting system from 400 to 2,000 HU. DECT acquisition (80/140 kVp and 100/140 kVp) was performed using two DECT systems equipped with standard and integrated electronics detector technologies. DECT raw datasets were reconstructed using filtered backprojection (FBP), and iterative reconstruction (SAFIRE I/V).

RESULTS

Accuracy for iodine quantification was significantly higher for the small compared to the large phantoms (9.2 % ± 7.5 vs. 24.3 % ± 26.1, P = 0.0001), the integrated compared to the conventional detectors (14.8 % ± 20.6 vs. 18.8 % ± 20.4, respectively; P = 0.006), and SAFIRE V compared to SAFIRE I and FBP reconstructions (15.2 % ± 18.1 vs. 16.1 % ± 17.6 and 18.9 % ± 20.4, respectively; P ≤ 0.003). A significant synergism was observed when the most effective detector and reconstruction techniques were combined with habitus-adapted dual-energy pairs.

CONCLUSION

In a second-generation dual-source DECT system, the accuracy of iodine quantification can be substantially improved by an optimal choice and combination of acquisition parameters, detector, and reconstruction techniques.

Spectral CT evaluation of interstitial brachytherapy in pancreatic carcinoma xenografts: preliminary animal experience

OBJECTIVES

We sought to evaluate the capability of spectral CT to detect the therapeutic response to (125)I interstitial brachytherapy in a pancreatic carcinoma xenograft nude mouse model.

METHODS

Twenty mice bearing SWl990 human pancreatic cancer cell xenografts were randomly separated into two groups: experimental (n = 10; 1.0 mCi) and control (n = 10; 0 mCi). After a two-week treatment, spectral CT was performed. Contrast-to-noise ratio (CNR) and iodine concentration (IC) in the lesions were measured and normalized to the muscle tissue, and nIC CD31 immunohistochemistry was used to measure microvessel density (MVD). The relationships between the nIC and MVD of the tumours were analysed.

RESULTS

The nIC of the experimental group was significantly lower than that of the control group during the multiphase examination. A significant difference in the MVD was observed between the two groups (P <0.001). The nIC values of the three-phase scans have a certain positive correlation with MVD (r = 0.57, p < 0.0001; r = 0.48, p = 0.002; r = 0.63, p = 0.0017 in the 10, 25, and 60 s phase, respectively).

CONCLUSIONS

Spectral CT can be a useful non-invasive imaging modality in evaluating the therapeutic effect of (125)I interstitial brachytherapy to a pancreatic carcinoma.

KEY POINTS

Spectral CT offers opportunities to assess therapeutic response in pancreatic cancer cases. Spectral CT findings correlated with vascular changes associated with (125)I seed implantation. Spectral CT with monochromatic imaging removed most (125)I seed artefacts.

State of the art: dual-energy CT of the abdomen

Recent technologic advances in computed tomography (CT)--enabling the nearly simultaneous acquisition of clinical images using two different x-ray energy spectra--have sparked renewed interest in dual-energy CT. By interrogating the unique characteristics of different materials at different x-ray energies, dual-energy CT can be used to provide quantitative information about tissue composition, overcoming the limitations of attenuation-based conventional single-energy CT imaging. In the past few years, intensive research efforts have been devoted to exploiting the unique and powerful opportunities of dual-energy CT for a variety of clinical applications. This has led to CT protocol modifications for radiation dose reduction, improved diagnostic performance for detection and characterization of diseases, as well as image quality optimization. In this review, the authors discuss the basic principles, instrumentation and design, examples of current clinical applications in the abdomen and pelvis, and future opportunities of dual-energy CT.

Diagnostic accuracy of late iodine-enhancement dual-energy computed tomography for the detection of chronic myocardial infarction compared with late gadolinium-enhancement 3-T magnetic resonance imaging

OBJECTIVES

The purpose of the study was to compare the performance of late iodine-enhancement (LIE) dual-energy computed tomography (DECT) linear blending and selective myocardial iodine mapping for the detection of chronic myocardial infarction (CMI) with late gadolinium-enhancement (LGE) 3-T magnetic resonance imaging.

MATERIALS AND METHODS

This study was approved by the institutional review board, and the patients gave informed consent. A total of 20 patients with a history of CMI underwent cardiac LIE-DECT and LGE-MRI. Images of the LIE-DECT were reconstructed as 100 kilovolt (peak) (kV[p]), 140 kV(p), and weighted-average (WA; linear blending) images from low- and high-kilovoltage peak data using 3 different weighting factors (0.8, 0.6, 0.3). Additional color-coded myocardial iodine distribution maps were calculated. The images were reviewed for the presence of late enhancement, transmural extent, signal characteristics, infarct volume, and subjective image quality.

RESULTS

Segmental analysis of LIE-DECT data from 100 kV(p), WA of 0.8, and WA of 0.6 showed identical results for the identification of CMI (89% sensitivity, 98% specificity, 96% accuracy) and correctly identified all segments with transmural scarring detected through LGE-MRI. Weighted average of 0.6 received the best subjective image quality rating (15/20 votes) and average measured infarct size correlated best with LGE-MRI (5.7% difference). In comparison with LGE-MRI, iodine distribution maps were susceptible to false-positive and false-negative findings (52% sensitivity, 88% specificity, 81% accuracy), overestimating quantity of transmural scars by 78% while underestimating infarct volume by 55%.

CONCLUSIONS

Late iodine enhancement cardiac dual-energy computed tomography correlates well with LGE-MRI for detecting CMI, whereas iodine distribution analysis provides inferior accuracy. Linear blending further improves image quality and enables more precise estimation of scar volume.

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.