Extracting atomic numbers and electron densities from a dual source dual energy CT scanner: experiments and a simulation model

Impact on Image Quality and Diagnostic Performance of Dual-Layer Detector Spectral CT for Pulmonary Subsolid Nodules: Comparison With Hybrid and Model-Based Iterative Reconstruction

OBJECTIVE

To evaluate the image quality and diagnostic performance of pulmonary subsolid nodules on conventional iterative algorithms, virtual monoenergetic images (VMIs), and electron density mapping (EDM) using a dual-layer detector spectral CT (DLSCT).

METHODS

This retrospective study recruited 270 patients who underwent DLSCT scan for lung nodule screening or follow-up. All CT examinations with subsolid nodules (pure ground-glass nodules [GGNs] or part-solid nodules) were reconstructed with hybrid and model-based iterative reconstruction, VMI at 40, 70, 100, and 130 keV levels, and EDM. The CT number, objective image noise, signal-to-noise ratio, contrast-to-noise ratio, diameter, and volume of subsolid nodules were measured for quantitative analysis. The overall image quality, image noise, visualization of nodules, artifact, and sharpness were subjectively rated by 2 thoracic radiologists on a 5-point scale (1 = unacceptable, 5 = excellent) in consensus. The objective image quality measurements, diameter, and volume were compared among the 7 groups with a repeated 1-way analysis of variance. The subjective scores were compared with Kruskal-Wallis test.

RESULTS

A total of 198 subsolid nodules, including 179 pure GGNs, and 19 part-solid nodules were identified. Based on the objective analysis, EDM had the highest signal-to-noise ratio (164.71 ± 133.60; P < 0.001) and contrast-to-noise ratio (227.97 ± 161.96; P < 0.001) among all image sets. Furthermore, EDM had a superior mean subjective rating score (4.80 ± 0.42) for visualization of GGNs compared to other reconstructed images (all P < 0.001), although the model-based iterative reconstruction had superior subjective scores of overall image quality. For pure GGNs, the measured diameter and volume did not significantly differ among different reconstructions (both P > 0.05).

CONCLUSIONS

EDM derived from DLSCT enabled improved image quality and lesion conspicuity for the evaluation of lung subsolid nodules compared to conventional iterative reconstruction algorithms and VMIs.

In vitro blood sample assessment: investigating correlation of laboratory hemoglobin and spectral properties of dual-energy CT measurements (ρ/Z)

OBJECTIVES

Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection.

METHODS

DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured.

RESULTS

Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37-0.49) and attenuation (r-values 0.59-0.83) while no correlation was observed for Zeff (r-values -0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value < 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined.

CONCLUSION

In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection.

CLINICAL RELEVANCE STATEMENT

By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice.

KEY POINTS

Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection.

Prediction of proton stopping power ratios using dual-energy CT basis material decomposition

BACKGROUND

Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction.

PURPOSE

To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.

METHODS

A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups.

RESULTS

The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR.

CONCLUSIONS

The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.

Technical note: Error analysis of material-decomposition-based effective atomic number quantification method

BACKGROUND

The effective atomic number (Zeff ) is widely applied to the identification of unknown materials. One method to determine the Zeff is material-decomposition-based spectral X-ray imaging. The method relies on certain approximations of the X-ray interaction cross-sections such as empirical model coefficients. The impact of such approximations on the accuracy of Zeff quantification has not been fully investigated.

PURPOSE

To perform an error analysis of the material-decomposition-based Zeff quantification method and propose a coefficient calibration-in-groups method to improve the modeling accuracy and reduce the Zeff quantification error.

METHODS

The model of the material-decomposition-based Zeff quantification method relies on the dependence of the interaction cross-sections  (σPE ) on the atomic number Z and corresponding coefficient, that is,σ PE ∝ Z m $\sigma _\mathrm{PE}\propto Z^m$ . In this work, all the data is from the National Institute of Standards and Technology (NIST) website. First, the coefficient m is calibrated through a logarithmic fitting method to quickly determine the m values for any certain energy and Zeff ranges. Then materials including elements and common compounds with Zeff ranging from 6-20 are selected as the objects whose effective atomic numbers are to be quantified. Different combinations of basis materials are applied to decompose the object materials and their quantification errors are analyzed. With the help of error analysis, the object materials are divided into high-error and low-error groups based on the decomposition coefficient ratioa m i n / a m a x $a_{min}/a_{max}$ , which is found to have a strong correlation with error, and their coefficients are calibrated in groups. Finally, the average errors of three m selection strategies: (1) using an empirical m value of 3.94, which is also considered a standard method; (2) using a single m value, which is calibrated through the logarithmic fitting method; (3) using different m values calibrated in groups, are calculated to test the effectiveness of our method.

RESULTS

The approximation of the X-ray interaction cross-section leads to certain errors in Zeff quantification and the error distributions for different basis materials are different. The average errors for most basis material combinations (C(6)/Ca(20), C(6)/Al(13), Al(13)/Ca(20), C(6)/Ne(10), Na(11)/P(15)) are lower than 0.5, maintaining good average accuracy. While the average error for S(16)/Ca(20) is up to 0.8461, leading to more misjudgments on atomic number. Meanwhile, the error distribution regularity can be observed. The Pearson's correlation coefficients of absolute errors and decomposition coefficient ratios are 0.743, 0.8432 and 0.7126 for basis material combinations C(6)/Ca(20), C(6)/Al(13) and Al(13)/Ca(20), indicating a good correlation. The method using either empirical m value of 3.94 or single calibrated m value of 4.619 has relatively high average errors. The proposed method using different m values calibrated in groups has the lowest average errors 0.254, 0.203 and 0.169, which are reduced by 21.6%(0.07), 3.8%(0.008) and 62.9%(0.286) respectively compared with the standard method.

CONCLUSIONS

The error analysis demonstrates that the approximation of X-ray interaction cross-sections leads to inevitable errors, while also revealing certain error distribution regularity. The coefficient calibrated-in-groups method has better modeling accuracy and has effectively reduced the error compared with the standard method using a single empirical m value of 3.94.

Feasibility of dual-energy CBCT material decomposition in the human torso with 2D anti-scatter grids and grid-based scatter sampling

BACKGROUND

Dual-energy (DE) imaging techniques in cone-beam computed tomography (CBCT) have potential clinical applications, including material quantification and improved tissue visualization. However, the performance of DE CBCT is limited by the effects of scattered radiation, which restricts its use to small object imaging.

PURPOSE

This study investigates the feasibility of DE CBCT material decomposition by reducing scatter with a 2D anti-scatter grid and a measurement-based scatter correction method. Specifically, the investigation focuses on iodine quantification accuracy and virtual monoenergetic (VME) imaging in phantoms that mimic head, thorax, abdomen, and pelvis anatomies.

METHODS

A 2D anti-scatter grid prototype was utilized with a residual scatter correction method in a linac-mounted CBCT system to investigate the effects of robust scatter suppression in DE CBCT. Scans were acquired at 90 and 140 kVp using phantoms that mimic head, thorax, and abdomen/pelvis anatomies. Iodine vials with varying concentrations were placed in each phantom, and CBCT images were decomposed into iodine and water basis material images. The effect of a 2D anti-scatter grid with and without residual scatter correction on iodine concentration quantification and contrast visualization in VME images was evaluated. To benchmark iodine concentration quantification accuracy, a similar set of experiments and DE processing were also performed with a conventional multidetector CT scanner.

RESULTS

In CBCT images, a 2D grid with or without scatter correction can differentiate iodine and water after DE processing in human torso-sized phantom images. However, iodine quantification errors were up to 10 mg/mL in pelvis phantoms when only the 2D grid was used. Adding scatter correction to 2D-grid CBCT reduced iodine quantification errors below 1.5 mg/mL in pelvis phantoms, comparable to iodine quantification errors in multidetector CT. While a noticeable contrast-to-noise ratio improvement was not observed in VME CBCT images, contrast visualization was substantially better in 40 keV VME images in visual comparisons with 90 and 140 kVp CBCT images across all phantom sizes investigated.

CONCLUSIONS

This study indicates that accurate DE decomposition is potentially feasible in DE CBCT of the human torso if robust scatter suppression is achieved with 2D anti-scatter grids and residual scatter correction. This approach can potentially enable better contrast visualization and tissue and contrast agent quantification in various CBCT applications.

Split-filter dual energy computed tomography radiotherapy: From calibration to image guidance

Background and purpose

Dual-energy computed tomography (DECT) is an emerging technology in radiotherapy (RT). Here, we investigate split-filter DECT throughout the RT treatment chain as compared to single-energy CT (SECT).

Materials and methods

DECT scans were acquired with a tin-gold split-filter at 140 kV resulting in a low- and high-energy CT reconstruction (recon). Ten cancer patients (four head-and-neck (HN)​, three rectum​, two anal/pelvis and one abdomen) were DECT scanned without and with iodine administered. A cylindrical and an anthropomorphic HN phantom were scanned with DECT and 120 kV SECT. The DECT images generated were: 120 kV SECT-equivalent (CTmix), virtual monoenergetic images (VMIs), iodine map, virtual non-contrast (VNC), effective atomic number (Zeff), and relative electron density (ρe,w). The clinical utility of these recons was investigated for calibration, delineation, dose calculation and image-guided RT (IGRT).

Results

A calibration curve for 75 keV VMI had a root-mean-square-error (RMSE) of 34 HU in closest agreement with the RSME of SECT calibration. This correlated with a phantom-based dosimetric agreement to SECT of γ1%1mm > 98%. A 40 keV VMI recon was most promising to improve tumor delineation accuracy with an average evaluation score of 1.6 corresponding to "partial improvement". The dosimetric impact of iodine was in general < 2%. For this setup, VNC vs. non-contrast CTmix based dose calculations are considered equivalent. SECT- and DECT-based IGRT was in agreement within the setup uncertainty.

Conclusions

DECT-based RT could be a feasible alternative to SECT providing additional recons to support the different steps of the RT workflow.

The Value of Dual-Energy Computed Tomography Angiography-Derived Parameters in the Evaluation of Clot Composition

OBJECTIVES

We aimed to assess the value of dual-energy computed tomography angiography (DE-CTA) derived parameters as a quantitative biomarker of thrombus composition in acute ischemic stroke (AIS).

METHODS

AIS patients who underwent DE-CTA before thrombectomy between August 2016 and September 2022 were included in this study. We assessed the relative proportion of red blood cells (RBCs) and the fibrin/platelet ratio (F/P) of the retrieved clots and categorized the clots as RBC-dominant (RBCs > F/P) or F/P-dominant (F/P > RBCs). The thrombus based parameters were measured on polyenergetic images (PEI), virtual monoenergetic (VM), virtual non-contrast (VNC), iodine concentration (IC), and effective atomic number (Zeff) images respectively, and the slope of the spectral Hounsfield unit curve (λHU) was calculated. These parameters were compared in the DE-CTA images of RBC- and F/P-dominant thrombi. The diagnostic performance of the parameters was analyzed using the ROC curve. Correlations between thrombus composition and DE-CTA-derived parameters were assessed.

RESULTS

The retrieved clots in 54 of 88 patients (61.36%) were RBC-dominant. The RBC-dominant thrombi showed significantly higher VNC values and lower IC, λHU, and Zeff values than the F/P-dominant thrombi (p < 0.05). The CT density measured on IC images showed the largest AUC value (AUC, 0.94; sensitivity, 77.78%; specificity, 100.00%). The Spearman rank-order correlation coefficient values showed that CT density measured on IC images of the thrombus showed the strongest association with the proportion of RBCs (r = -0.64, p < 0.001) and F/P (r = 0.65, p < 0.001).

CONCLUSIONS

DE-CTA-derived parameters, especially the CT density measured on IC images, could be associated with thrombus composition and allow for personalized thrombectomy strategies.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using ex vivo animal tissues and tissue-mimicking phantoms

Objective. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (Im), electron density, and stopping power ratio (SPR). We aimed to develop a novel MR-based multimodal method to accurately determine SPR and molecular compositions. This method was evaluated in tissue-mimicking andex vivoporcine phantoms, and in a brain radiotherapy patient.Approach. Four tissue-mimicking phantoms with known compositions, two porcine tissue phantoms, and a brain cancer patient were imaged with kVCT and MRI. Three imaging-based values were determined: SPRCM(CT-based Multimodal), SPRMM(MR-based Multimodal), and SPRstoich(stoichiometric calibration). MRI was used to determine two tissue-specific quantities of the Bethe Bloch equation (Im, electron density) to compute SPRCMand SPRMM. Imaging-based SPRs were compared to measurements for phantoms in a proton beam using a multilayer ionization chamber (SPRMLIC).Main results. Root mean square errors relative to SPRMLICwere 0.0104(0.86%), 0.0046(0.45%), and 0.0142(1.31%) for SPRCM, SPRMM, and SPRstoich, respectively. The largest errors were in bony phantoms, while soft tissue and porcine tissue phantoms had <1% errors across all SPR values. Relative to known physical molecular compositions, imaging-determined compositions differed by approximately ≤10%. In the brain case, the largest differences between SPRstoichand SPRMMwere in bone and high lipids/fat tissue. The magnitudes and trends of these differences matched phantom results.Significance. Our MR-based multimodal method determined molecular compositions and SPR in various tissue-mimicking phantoms with high accuracy, as confirmed with proton beam measurements. This method also revealed significant SPR differences compared to stoichiometric kVCT-only calculation in a clinical case, with the largest differences in bone. These findings support that including MRI in proton therapy treatment planning can improve the accuracy of calculated SPR values and reduce range uncertainties.

Differentiation of malignant from benign orbital tumours using dual-energy CT

AIM

To investigate the diagnostic accuracy of dual-energy computed tomography (DECT)-derived iodine concentration (IC), effective atomic number (Z_eff), and spectral attenuation information for differentiating malignant and benign orbital tumours.

MATERIALS AND METHODS

Data from 41 patients with orbital tumours from November 2019 to March 2021 were analysed retrospectively. Each patient underwent contrast-enhanced DECT using a 128-section dual-source computed tomography (DSCT) system. Dual-energy information, including IC, normalised iodine concentration (NIC), Z_eff, virtual monoenergetic images (VMIs) reconstructed from 40 to 120 keV and slope (k) value were determined. Quantitative measurement of DECT parameters was undertaken by two independent radiologists blinded to clinical data. Differences in parameters were assessed using independent sample t-test. Diagnosis performance was calculated by the receiver operating characteristic (ROC) curve analysis. Radiation doses of conventional CT and DECT were compared by paired t-tests.

RESULTS

Forty-one patients with histopathologically confirmed tumours were enrolled, including 10 malignant cases and 21 benign cases. Malignant orbital tumours exhibited significantly greater IC, NIC, Z_eff, CT attenuation of VMIs at 40-105 keV, and k values compared to benign orbital tumours (p<0.05). In ROC analyses, 40 keV VMI demonstrated the highest diagnostic performance of single parameters (area under the ROC curve [AUC], 0.940), and combined parameters achieved the best performance (AUC, 0.971; sensitivity, 90%; specificity, 93.55%). Radiation doses were significantly reduced in DECT than conventional CT (p<0.001).

CONCLUSIONS

Quantitative DECT analysis can be a useful technique, which yields excellent diagnostic accuracy, in the differentiation of malignant and benign orbital tumours with low radiation dose.

Spectral Properties of Abdominal Tissues on Dual-energy Computed Tomography and the Effects of Contrast Agent

BACKGROUND/AIM

Multiparametric dual energy comptuted tomography (CT) imaging allows for multidimensional tissue characterization beyond the measurement of Hounsfield units. The purpose of this study was to evaluate multiple imaging parameters for different abdominal organs in dual energy CT (DECT) and analyze the effects of the contrast agent on these different parameters and provide normal values for characterization of parenchymatous organs.

PATIENTS AND METHODS

This retrospective analysis included a total of 484 standardized DECT scans of the abdomen. Hounsfield Units (HU), rho (electron density relative to water), Z_eff (effective atomic number) and FF (fat fraction) were evaluated for liver, spleen, kidney, muscle, fat-tissue. Independent generalized estimation equation models were fitted.

RESULTS

In DECT imaging there is only little difference in mean HU_mixed for parenchymatous abdominal organs. Analysis including Z_eff, rho and FF allows for better discrimination while a large overlap remains for liver, spleen and muscle. Including multidimensional analysis and the effects of contrast medium further enhances tissue characterization. Small differences remain for liver and spleen.

CONCLUSION

Organ characterization using multiparametric dual energy CT analysis is possible. An increased number of parameters obtained from DECT improves organ characterization. To our knowledge this is the first attempt to provide normal values for characterization of parenchymatous organs.

CT-guided bone biopsy using electron density maps from dual-energy CT

Computed tomography (CT) -guided bone biopsy is a diagnostic procedure performed on the musculoskeletal system with a high diagnostic yield and low complications. However, CT-guided bone biopsy has the disadvantage that it is difficult to confirm the presence of tumor cells during the biopsy procedure. Recently, the clinical benefits of dual-energy CT (DECT) over single-energy CT have been revealed. DECT can provide material decomposition images including calcium suppression images, and effective atomic number (Z_eff) and electron density (ED) maps. ED maps have been reported to indicate cellularity. A 61-year-old woman with a history of breast cancer surgery was admitted to our hospital and underwent a CT-guided bone biopsy of the right ilium using ED maps. As a result, she was diagnosed with breast cancer metastases of intertrabecular bone. A comparison of ED maps with a pathological specimen revealed that high ED values occurred exclusively in the tumor area with high cellularity. This study indicates that ED maps produced using DECT may have potential utility in the accurate identification of metastases with high cellularity in bone lesions.

A comparative study of effective atomic number calculations for dual-energy CT

PURPOSE

Several new formalisms of Effective Atomic Number ( Z eff ) have emerged recently, deviating from the widely accepted Mayneord's definition. This comparative study aims to reexamine their theories, reveal their connections, and apply them to material differentiation on dual-energy computed tomography (DECT).

METHODS

The first part of this paper is an in-depth review of several highly cited Z eff formalisms. This part includes (1) refuting the claim in Taylor's study that the classic Mayneord's formalism was inaccurate, (2) showing that Mayneord's, Rutherford's, and Bourque's formalisms were equivalent, and (3) explaining the fundamental difference between Taylor's and Bourque's formalisms. The second part of this paper explains how we translated the theories into software implementation and added an open-source Z eff calculation engine to our free research software 3D Quantitative Imaging (3DQI). The work includes developing an interpolation method based on radial basis function to make Taylor's formalism applicable to DECT, and devising a table lookup method to generate Z eff map with high efficiency for all appropriate formalisms.

RESULTS

Comparing Bourque's and Taylor's formalisms for six common materials over 40 ∼ 100 keV energy range, it was found that Bourque's Z eff values had a weak energy dependence by 0.18% ∼ 3.10%, but for Taylor's results this variation increased by a factor of 10. Further comparison showed that at 61 keV, different formalisms fall into two categories-Bourque, Mayneord, Van Abbema (a derivative of Rutherford) for the first category, and Taylor and Manohara for the second. Formalisms within each category produced similar Z eff values. For a material consisting of two elements, the two categories of formalisms tended to show a greater discrepancy if the constituent elements had larger difference in Z . The developed Z eff calculation engine was successfully applied to kidney stone classification and colon electronic cleansing.

CONCLUSIONS

We renewed the understanding of several popular Z eff formalisms: Contrary to the conclusion of Taylor's study, Mayneord's power-law formula is well grounded in theory; Bourque's formalism (based on the average electron microscopic cross-section) is considered numerically equivalent to Rutherford's, but with the advantage of being mathematically rigorous and physically meaningful; Taylor's formalism (based on the average atomic microscopic cross-section) is theoretically not suitable for DECT but a workaround still exists; Manohara's formalism should be used with caution due to a problem in its definition of electron cross-sections. The developed Z eff engine in the 3DQI software facilitated accurate and efficient Z eff estimate for various DECT applications.

Dual-Energy CT-Derived Electron Density for Diagnosing Metastatic Mediastinal Lymph Nodes in Non-Small Cell Lung Cancer: Comparison With Conventional CT and FDG PET/CT Findings

Background: Accurate nodal staging is essential to guide treatment selection in patients with non-small cell lung cancer (NSCLC). To our knowledge, measurement of electron density (ED) using dual-energy CT (DECT) is unexplored for this purpose. Objective: To assess the utility of ED from DECT in diagnosing metastatic mediastinal lymph nodes in patients with NSCLC, in comparison with conventional CT and FDG PET/CT. Methods: This retrospective study included 57 patients (36 men, 21 women; mean age 68.4±8.9 years) with NSCLC and surgically resected mediastinal lymph nodes who underwent preoperative DECT and FDG PET/CT. The patients had a total of 117 resected mediastinal lymph nodes (33 metastatic, 84 nonmetastatic). Two radiologists independently reviewed nodes' morphologic features on the 120 kVp images and also measured nodes' iodine concentration (IC) and ED using maps generated from DECT data; consensus was reached for discrepancies. Two separate radiologists assessed FDG PET/CT examinations in consensus for positive node uptake. Diagnostic performance was evaluated for individual and pairwise combinations of features. Results: The sensitivity, specificity, and accuracy for nodal metastasis were 15.2%, 98.8%, and 75.2% for presence of necrosis; 54.5%, 85.7%, and 76.9% for short-axis diameter >8.5 mm; 63.6%, 73.8%, and 70.9% for long-axis diameter >13.0 mm; 51.5%, 79.8%, and 71.8% for attenuation on 120 kVp images ≤95.8 HU; 87.9%, 58.3%, and 66.7% for ED ≤3.48×1023/cm3; and 66.7%, 75.0%, and 72.6% for positive FDG uptake, respectively. Among pairwise combinations of features, accuracy was highest for the combination of ED and short-axis diameter (accuracy 82.9%, sensitivity 54.5%, specificity 94.0%) and the combination of ED and positive FDG uptake (accuracy 82.1%, sensitivity 60.6%, specificity 90.5%); these accuracies were greater than for the individual features (p<.05). Remaining combinations exhibited accuracies ranging from 74.4% to 77.8%. Interobserver agreement analysis demonstrated intraclass correlation coefficient of 0.90 for ED. IC was not significantly different between metastatic and nonmetastatic nodes (p=.18) and was excluded from the diagnostic performance analysis. Conclusion: ED derived from DECT may help diagnose metastatic lymph nodes in NSCLC given decreased ED in metastatic nodes. Clinical Impact: ED may complement conventional CT findings and FDG uptake on PET/CT in diagnosing metastatic nodes.

Improving the Quality of Cerebral Perfusion Maps With Monoenergetic Dual-Energy Computed Tomography Reconstructions

OBJECTIVE

We compared 40- to 70-keV virtual monoenergetic to conventional computed tomography (CT) perfusion reconstructions with respect to quality of perfusion maps.

METHODS

Conventional CT perfusion (CTP) images were acquired at 80 kVp in 25 patients, and 40- to 70-keV images were acquired with a dual-layer CT at 120 kVp in 25 patients. First, time-attenuation-curve contrast-to-noise ratio was assessed. Second, the perfusion maps of both groups were qualitatively analyzed by observers. Last, the monoenergetic reconstruction with the highest quality was compared with the clinical standard 80-kVp CTP acquisitions.

RESULTS

Contrast-to-noise ratio was significantly better for 40 to 60 keV as compared with 70 keV and conventional images (P < 0.001). Visually, the difference between the blood volume maps among reconstructions was minimal. The 50-keV perfusion maps had the highest quality compared with the other monoenergetic and conventional maps (P < 0.002).

CONCLUSIONS

The quality of 50-keV CTP images is superior to the quality of conventional 80- and 120-kVp images.

On the molecular relationship between Hounsfield Unit (HU), mass density, and electron density in computed tomography (CT)

Accurate determination of physical/mass and electron densities are critical to accurate spatial and dosimetric delivery of radiotherapy for photon and charged particles. In this manuscript, the biology, chemistry, and physics that underly the relationship between computed tomography (CT) Hounsfield Unit (HU), mass density, and electron density was explored. In standard radiation physics practice, quantities such as mass and electron density are typically calculated based off a single kilovoltage CT (kVCT) scan assuming a one-to-one relationship between HU and density. It is shown that, in absence of mass density assumptions on tissues, the relationship between HU and density is not one-to-one with uncertainties as large as 7%. To mitigate this uncertainty, a novel multi-dimensional theoretical approach is defined between molecular (water, lipid, protein, and mineral) composition, HU, mass density, and electron density. Empirical parameters defining this relationship are x-ray beam energy/spectrum dependent and, in this study, two methods are proposed to solve for them including through a tissue mimicking phantom calibration process. As a proof of concept, this methodology was implemented in a separate in-house created tissue mimicking phantom and it is shown that sub 1% accuracy is possible for both mass and electron density. As molecular composition is not always known, the sensitivity of this model to uncertainties in molecular composition was investigated and it was found that, for soft tissue, sub 1% accuracy is achievable assuming nominal organ/tissue compositions. For boney tissues, the uncertainty in mineral content may lead to larger errors in mass and electron density compared with soft tissue. In this manuscript, a novel methodology to directly determine mass and electron density based off CT HU and knowledge of molecular compositions is presented. If used in conjunction with a methodology to determine molecular compositions, mass and electron density can be accurately calculated from CT HU.

Impact of computed tomography (CT) reconstruction kernels on radiotherapy dose calculation

PURPOSE

To quantitatively evaluate the effect of computed tomography (CT) reconstruction kernels on various dose calculation algorithms with heterogeneity correction.

METHODS

The gammex electron density (ED) Phantom was scanned with the Siemens PET/CT Biograph20 mCT and reconstructed with twelve different kernel options. Hounsfield unit (HU) vs electron density (ED) curves were generated to compare absolute differences. Scans were repeated under head and pelvis protocols and reconstructed per H40s (head) and B40s (pelvis) kernels. In addition, raw data from a full-body patient scan were also reconstructed using the four B kernels. Per reconstruction, photon (3D and VMAT), electron (18 and 20 MeV) and proton (single field) treatment plans were generated using Varian Eclipse dose calculation algorithms. Photon and electron plans were also simulated to pass through cortical bone vs liver plugs of the phantom for kernel comparison. Treatment field monitor units (MU) and isodose volumes were compared across all scenarios.

RESULTS

The twelve kernels resulted in minor differences in HU, except at the extreme ends of the density curve with a maximum absolute difference of 55.2 HU. The head and pelvis scans of the phantom resulted in absolute HU differences of up to 49.1 HU for cortical bone and 45.1 HU for lung 300, which is a relative difference of 4.1% and 6.2%, respectively. MU comparisons across photon and proton calculation algorithms for the patient and phantom scans were within 1-2 MU, with a maximum difference of 5.4 MU found for the 20 MeV electron plan. The 20MeV electron plan also displayed maximum differences in isodose volumes of 20.4 cc for V90%.

CONCLUSION

Clinically insignificant differences were found among the various kernel generated plans for photon and proton plans calculated on patient and phantom scan data. However, differences in isodose volumes found for higher energy electron plans amongst the kernels may have clinical implications for prescribing dose to an isodose level.

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

Dual-energy CT and coronary imaging

Dual-energy computed tomography has been proposed for enhancing the evaluation of coronary artery disease in many fronts. However, the clinical translation of such applications has followed a slower pace of clinical translation. This paper will review the evidence supporting the use of dual-energy computed tomography in coronary artery disease (CAD) and provide some practical illustrations, while underscoring the challenges and gaps in knowledge that have contributed to this phenomenon.

Status and innovations in pre-treatment CT imaging for proton therapy

Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements in the accuracy of stopping-power prediction are demanded to allow for a dose conformality that is not inferior to state-of-the-art image-guided photon therapy. Although range uncertainty has been kept practically constant over the last decades, recent technological and methodological developments, like the clinical application of dual-energy CT, have been introduced or arise at least on the horizon to improve the accuracy and precision of range prediction. This review gives an overview of the current status, summarizes the innovations in dual-energy CT and its potential impact on the field as well as potential alternative technologies for stopping-power prediction.

Intravenous contrast media in radiation therapy planning computed tomography scans - Current practice in Ireland

Introduction

While Computerised Tomography (CT) remains the gold standard in radiation therapy (RT) planning, inferior soft tissue definition remains a challenge. Intravenous contrast (IVC) use during CT planning can enhance soft tissue contrast optimising Target Volume (TV) and Organ at Risk visualisation and delineation. Despite this known benefit, there are no guidelines for when and how to use IVC in RT planning scans in Ireland.

Aim

The study aims to examine the patterns of practice in relation to the use of IVC in RT planning scans in Ireland and to determine the level of compliance with international guidelines. Radiation Therapists (RTT) IVC training will also be investigated.

Materials and methods

An anonymised online survey was designed based on previously-reported literature. This was distributed to all RT departments in Ireland. The survey contained open, closed and Likert scale questions that investigated IVC practices in each department.

Results

75% (n = 9/12) of Irish departments responded. All responding departments reported using IVC. RTTs cannulated patients in 67% (n = 6/9) of the departments and administration contrast in all departments. Variations from recommended guidelines were found in disease sites where IVC was routinely used and in the assessment of renal functioning prior to contrast administration. IVC training varied in duration and number of supervised procedures required to fulfill competencies.

Conclusion

IVC is used extensively in Irish RT departments. There are variations in IVC practice between departments and with international recommended guidelines.

Accuracy of Dual-Energy Virtual Monochromatic CT Numbers: Comparison between the Single-Source Projection-Based and Dual-Source Image-Based Methods

RATIONALE AND OBJECTIVES

To investigate the accuracy of dual-energy virtual monochromatic computed tomography (CT) numbers obtained by two typical hardware and software implementations: the single-source projection-based method and the dual-source image-based method.

MATERIALS AND METHODS

A phantom with different tissue equivalent inserts was scanned with both single-source and dual-source scanners. A fast kVp-switching feature was used on the single-source scanner, whereas a tin filter was used on the dual-source scanner. Virtual monochromatic CT images of the phantom at energy levels of 60, 100, and 140 keV were obtained by both projection-based (on the single-source scanner) and image-based (on the dual-source scanner) methods. The accuracy of virtual monochromatic CT numbers for all inserts was assessed by comparing measured values to their corresponding true values. Linear regression analysis was performed to evaluate the dependency of measured CT numbers on tissue attenuation, method, and their interaction.

RESULTS

Root mean square values of systematic error over all inserts at 60, 100, and 140 keV were approximately 53, 21, and 29 Hounsfield unit (HU) with the single-source projection-based method, and 46, 7, and 6 HU with the dual-source image-based method, respectively. Linear regression analysis revealed that the interaction between the attenuation and the method had a statistically significant effect on the measured CT numbers at 100 and 140 keV.

CONCLUSIONS

There were attenuation-, method-, and energy level-dependent systematic errors in the measured virtual monochromatic CT numbers. CT number reproducibility was comparable between the two scanners, and CT numbers had better accuracy with the dual-source image-based method at 100 and 140 keV.

The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT

OBJECTIVE:

To analyse the effect of different image reconstruction techniques on image quality and dual energy CT (DECT) imaging metrics.

METHODS:

A software platform for pre-clinical cone beam CT X-ray image reconstruction was built using the open-source reconstruction toolkit. Pre-processed projections were reconstructed with filtered back-projection and iterative algorithms, namely Feldkamp, Davis, and Kress (FDK), Iterative FDK, simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique and conjugate gradient. Imaging metrics were quantitatively assessed, using a quality assurance phantom, and DECT analysis was performed to determine the influence of each reconstruction technique on the relative electron density (ρ_e) and effective atomic number (Z_eff) values.

RESULTS:

Iterative reconstruction had favourable results for the DECT analysis: a significantly smaller spread for each material in the ρ_e-Z_eff space and lower Z_eff and ρ_e residuals (on average 24 and 25% lower, respectively). In terms of image quality assurance, the techniques FDK, Iterative FDK and SART provided acceptable results. The three reconstruction methods showed similar geometric accuracy, uniformity and CT number results. The technique SART had a contrast-to-noise ratio up to 76% higher for solid water and twice as high for Teflon, but resolution was up to 28% lower when compared to the other two techniques.

CONCLUSIONS:

Advanced image reconstruction can be beneficial, but the benefit is small, and calculation times may be unacceptable with current technology. The use of targeted and downscaled reconstruction grids, larger, yet practicable, pixel sizes and GPU are recommended.

ADVANCES IN KNOWLEDGE:

An iterative CBCT reconstruction platform was build using RTK.

Improved differentiation between high- and low-grade gliomas by combining dual-energy CT analysis and perfusion CT

The purpose of this study was to investigate the value of the cerebral blood volume (CBV) obtained with perfusion computed tomography (CT) and the electron density (ED) measured by dual-energy CT for differentiating high- from low-grade glioma (HGG, LGG).The CBV and ED were obtained in 9 LGG and 7 HGG patients. The CBV and ED of LGGs and HGGs were compared. Receiver operating characteristic (ROC) curves were generated for CBV, ED, and CBV plus ED. The correlation between CBV, ED, and the MIB-1 labeling index of the tumors was examined. All of these analyses were also performed using relative CBV (rCBV) and ED (rED) (the value of tumors/the value of contralateral white matter).The mean CBV, ED, rCBV, and rED values were significantly higher in HGG than LGG (P < .05). By ROC analysis, the combination of rCBV plus rED as well as CBV plus ED were more accurate than CBV, ED, rCBV, rED alone. There was a significant correlation between ED and MIB-1 (P = .04).ED improved diagnostic accuracy of perfusion CT for differentiating HGG from LGG.

Simultaneous characterization of electron density and effective atomic number for radiotherapy planning using stoichiometric calibration method and dual energy algorithms

Relative electron densities of body tissues (ρ_e) for radiotherapy treatment planning are normally obtained by CT scanning of tissue substitute materials (TSMs) and producing a Hounsfield Unit-ρ_e calibration curve. Aiming for more accurate, simultaneous characterization of ρ_e and effective atomic number (Z_eff) of real tissues, an in-house phantom (including 10 water solutions plus composite cork as TSMs) was constructed and scanned at 4 kVps. Dual-energy algorithms were applied to 80-140 and 100-140 kVp combination scans, for better differentiation of tissues with same attenuation coefficient at 120 kVp but different ρ_e and Z_eff. Stoichiometric calibration and closeness of the ρ_e of the 11 TSMs to real tissues (≤ 0.5%) resulted in smaller ρ_e calculation discrepancies, compared to studies with commercial phantoms (p < 0.024). Applying an energy subtraction algorithm further mitigated errors by spectral separation and reduction of beam hardening artifacts and noise, reducing the mean and standard deviation of the absolute difference of ρ_e at 80-140 kVp (p < 0.003) and 100-140 kVp (p < 0.0001) scans, compared to 120 kVp scan, respectively. Moreover, a parametrization algorithm decreased the Z_eff discrepancy from real tissues at 80-140 kVp scans; for thyroid, the residual error was ≤ 0.18 units of Z_eff (vs. 0.2 with the Gammex 467 phantom from a previous study). These results further suggest that a dual-energy algorithm in combination with stoichiometry can decrease errors in calculation of the ρ_e of real tissues to ameliorate inhomogeneity for dose calculation in radiotherapy treatment planning, especially when the energy spectrum of the X-ray tube of the CT machine is not available.

Therapy Effects of Advanced Hypopharyngeal and Laryngeal Squamous Cell Carcinoma: Evaluated using Dual-Energy CT Quantitative Parameters

The accurate evaluation of the therapeutic effects of advanced laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) remains challenging. In this study, we determined the value of quantitative parameters derived from dual-energy computed tomography (DECT) for predicting the therapeutic effects of advanced LHSCC and to provide valuable evidence for early judgement of the tumour's response to therapy in clinical practice. We prospectively analysed 41 patients with pathologically confirmed LHSCC. All patients received a DECT scan before therapy. Nineteen of 41 patients showed complete remission (CR), and 22 showed non-complete remission (NCR). The mean of the slope of spectral Hounsfield unit curve (λHU), standardized iodine concentration and effective atomic number in the CR group were significantly lower than the NCR group (P < 0.05). There were no significant differences for T stage, treatment modality and standardized water concentration between two groups (P > 0.05). The best predictor of CR effect was λHU. The 2-year cumulative recurrence rate of patients with higher λHU values was significantly higher than that of patients with lower λHU values (P < 0.05), while the 2-year survival rate of those patients was not significantly different (P > 0.05). DECT could easily identify CR patients and potentially help to choose the appropriate treatment regimen for advanced LHSCC.

VOXSI: A voxelized single- and dual-energy CT scenario generator for quantitative imaging

BACKGROUND AND PURPOSE

Dedicated CT simulation models have the potential to investigate several acquisition, reconstruction, or post-processing parameters without giving any radiation dose to patients. A software program was developed for the simulation and the analysis of single-energy and dual-energy CT images. Simulation and analysis functionalities of the software are described.

MATERIALS AND METHODS

In the software, named VOXSI (VOXelized CT SImulator), the X-ray source, user specified simulation geometry, CT setup and the detector energy response can be varied. CT image reconstructions can be performed with an implementation of the ASTRA toolbox. In the DECT post processing toolkit, GUI tools are provided to calculate effective atomic number, relative electron density, pseudo-monoenergetic images, and material map images. Quantitative CT number validation, based on a RMI 467 tissue characterization phantom model, was performed between experimental and simulated CT scans at three different X-ray tube potentials (80, 120, and 140 kVp) with a third generation CT scanner.

RESULTS

Overall, a good agreement was found for the mean CT numbers of the RMI 467 inserts. For all energies, the maximum difference in CT numbers between experimental and simulated data was below 17 HU for the soft tissues and below 48 HU for the osseous tissues.

CONCLUSION

The software's simulation algorithm showed a good agreement between the CT measurements and CT simulations of the RMI 467 phantom at different energies. The capabilities of the software are demonstrated by an elaborated dual-energy CT research example.

ESTRO ACROP: Technology for precision small animal radiotherapy research: Optimal use and challenges

Many radiotherapy research centers have recently installed novel research platforms enabling the investigation of the radiation response of tumors and normal tissues in small animal models, possibly in combination with other treatment modalities. Many more research institutes are expected to follow in the coming years. These novel platforms are capable of mimicking human radiotherapy more closely than older technology. To facilitate the optimal use of these novel integrated precision irradiators and various small animal imaging devices, and to maximize the impact of the associated research, the ESTRO committee on coordinating guidelines ACROP (Advisory Committee in Radiation Oncology Practice) has commissioned a report to review the state of the art of the technology used in this new field of research, and to issue recommendations. This report discusses the combination of precision irradiation systems, small animal imaging (CT, MRI, PET, SPECT, bioluminescence) systems, image registration, treatment planning, and data processing. It also provides guidelines for reporting on studies.

The influence of tissue composition uncertainty on dose distributions in brachytherapy

BACKGROUND AND PURPOSE

Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.

MATERIALS AND METHODS

Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D₉₀), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μ_en/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.

RESULTS

Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D₉₀ for target tissues and doses to OAR for brachytherapy with low energy sources and less for ¹⁹²Ir-based brachytherapy. Discrepancies in μ_en/ρ are also indicative of dose differences.

CONCLUSIONS

Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.

Revised inverse problem algorithm-based prediction of coronary artery stenosis readings from the clinical data of patients with coronary heart diseases

AIM

Coronary artery stenosis readings were predicted in this study on the basis of clinical data for patients with coronary heart diseases using the inverse problem algorithm.

METHOD

Five factors, including age, BSA (body surface area), MAP (mean artery pressure), sugar AC (ante cibum), and LDL-C (low-density Lipoprotein-Cholesterol) were incorporated into a nonlinear first-order regression fit analysis to develop a prediction equation with sixteen terms derived via a revised inverse problem algorithm implemented through the STATISTICA default regression fit. The clinical data acquired from ninety-three coronary heart disease patients were first normalized to the same domain range of [-1 to +1], and then processed by the above algorithm to find the compromised solution of predicted coronary artery stenosis reading. The actual reading was obtained by weighting the stenosis of three major cardiac artery branches, namely, the left anterior descending artery (LAD) (wi 0.3), left circumflex artery (LCA) (wi 0.3), and right coronary artery (RCA) (wi 0.4).

RESULT

The derived regression fit possessed the final loss function value Φ = 3.589 and correlation coefficient r2 = 0.892 with variance of 79.55%. Accordingly, forty-five patients with similar syndromes were analyzed to verify the prediction, which exhibited a high coincidence. The LDL-C factor was dominant for the prediction of the largest coefficient in the derived equation, whereas the age factor exhibited a minor contribution to the regression fit. The attempts to reduce the number of influence factors to 4, 3 or 2 for the model simplification yielded the results, whose low linearity and high loss function values reflected their inappropriate setting.

CONCLUSION

The algorithm proved to be an effective technique for prediction of the potential diagnosis in the medical field.

Taguchi dynamic analysis application to computer tomography number-mass density linear dependence optimization

The Taguchi dynamic analysis was applied to optimize the linear dependence between computer tomography (CT) number and mass density. The Taguchi unique L₁₈(2¹ × 3⁵) orthogonal array was utilized in the dynamic analysis of a commercial Catphan 600 phantom with CTP 404 module, in order to optimize eighteen combinations of six factors controlling the CT simulator operation, i.e. scan time, kVp, mA, field of view (FOV), slice thickness, and imaging processing algorithm. Each factor being assigned two or three different levels made it possible to organize the required number of combinations (18). The seven materials involved in the phantom possessed different mass densities, which were incorporated into the dynamic analysis. The revised signal-to-noise ratio (S/N) was utilized to describe the integrated performance of various factors' combinations in pursuing the optimal ρ_m-CT number (HU) calibration curve. The optimal option was found to be: 1 s scan time, 130 kVp, 200 mA, 40 cm² FOV, 3 cm of slice thickness, and soft type of algorithm for maintaining the ρ_m-HU calibration. Factors kVp and FOV dominated the performance either by providing a significant change in S/N value or strongly improving the reproducibility in daily quality assurance. The ρ_m-HU calibration (HU = 1016.9 × density + 1029.5, r² = 0.9954) was further verified by the treatment planning systematic default (TPS) (HU= 1242.1 × density+ 1054.8, r² = 0.9755). The well-calibrated ρ_m-HU curve was successfully applied to clinical examination of the simulated oral cancer from CT scanned slice via a Rando phantom. A significant disagreement between optimal and default isodose curves was observed for doses exceeding 7000 cGy, while a good fit was exhibited by doses below 5000 cGy.

Can CT scan protocols used for radiotherapy treatment planning be adjusted to optimize image quality and patient dose? A systematic review

This article reviews publications related to the use of CT scans for radiotherapy treatment planning, specifically the impact of scan protocol changes on CT number and treatment planning dosimetry and on CT image quality. A search on PubMed and EMBASE and a subsequent review of references yielded 53 relevant articles. CT scan parameters significantly affect image quality. Some will also affect Hounsfield unit (HU) values, though this is not comprehensively reported on. Changes in tube kilovoltage and, on some scanners, field of view and reconstruction algorithms have been found to produce notable HU changes. The degree of HU change which can be tolerated without changing planning dose by >1% depends on the body region and size, planning algorithms, treatment beam energy and type of plan. A change in soft-tissue HU value has a greater impact than changes in HU for bone and air. The use of anthropomorphic phantoms is recommended when assessing HU changes. There is limited published work on CT scan protocol optimization in radiotherapy. Publications suggest that HU tolerances of ±20 HU for soft tissue and of ±50 HU for the lung and bone would restrict dose changes in the treatment plan to <1%. Literature related to the use of CT images in radiotherapy planning has been reviewed to establish the acceptable level of HU change and the impact on image quality of scan protocol adjustment. Conclusions have been presented and further work identified.

The potential of dual-energy CT to reduce proton beam range uncertainties

PURPOSE

Dual-energy CT (DECT) promises improvements in estimating stopping power ratios (SPRs) for proton therapy treatment planning. Although several comparable mathematical formalisms have been proposed in literature, the optimal techniques to characterize human tissue SPRs with DECT in a clinical environment are not fully established. The aim of this work is to compare the most robust DECT methods against conventional single-energy CT (SECT) in conditions reproducing a clinical environment, where CT artifacts and noise play a major role on the accuracy of these techniques.

METHODS

Available DECT tissue characterization methods are investigated and their ability to predict SPRs is compared in three contexts: (a) a theoretical environment using the XCOM cross section database; (b) experimental data using a dual-source CT scanner on a calibration phantom; (c) simulations of a virtual humanoid phantom with the ImaSim software. The latter comparison accounts for uncertainties caused by CT artifacts and noise, but leaves aside other sources of uncertainties such as CT grid size and the I-values. To evaluate the clinical impact, a beam range calculation model is used to predict errors from the probability distribution functions determined with ImaSim simulations. Range errors caused by SPR errors in soft tissues and bones are investigated.

RESULTS

Range error estimations demonstrate that DECT has the potential of reducing proton beam range uncertainties by 0.4% in soft tissues using low noise levels of 12 and 8 HU in DECT, corresponding to 7 HU in SECT. For range uncertainties caused by the transport of protons through bones, the reduction in range uncertainties for the same levels of noise is found to be up to 0.6 to 1.1 mm for bone thicknesses ranging from 1 to 5 cm, respectively. We also show that for double the amount noise, i.e., 14 HU in SECT and 24 and 16 HU for DECT, the advantages of DECT in soft tissues are lost over SECT. In bones however, the reduction in range uncertainties is found to be between 0.5 and 0.9 mm for bone thicknesses ranging from 1 to 5 cm, respectively.

CONCLUSION

DECT has a clear potential to improve proton beam range predictions over SECT in proton therapy. However, in the current state high levels of noise remain problematic for DECT characterization methods and do not allow getting the full benefits of this technology. Future work should focus on adapting DECT methods to noise and investigate methods based on raw-data to reduce CT artifacts.

Methodological accuracy of image-based electron density assessment using dual-energy computed tomography

PURPOSE

Electron density is the most important tissue property influencing photon and ion dose distributions in radiotherapy patients. Dual-energy computed tomography (DECT) enables the determination of electron density by combining the information on photon attenuation obtained at two different effective x-ray energy spectra. Most algorithms suggested so far use the CT numbers provided after image reconstruction as input parameters, i.e., are imaged-based. To explore the accuracy that can be achieved with these approaches, we quantify the intrinsic methodological and calibration uncertainty of the seemingly simplest approach.

METHODS

In the studied approach, electron density is calculated with a one-parametric linear superposition ('alpha blending') of the two DECT images, which is shown to be equivalent to an affine relation between the photon attenuation cross sections of the two x-ray energy spectra. We propose to use the latter relation for empirical calibration of the spectrum-dependent blending parameter. For a conclusive assessment of the electron density uncertainty, we chose to isolate the purely methodological uncertainty component from CT-related effects such as noise and beam hardening.

RESULTS

Analyzing calculated spectrally weighted attenuation coefficients, we find universal applicability of the investigated approach to arbitrary mixtures of human tissue with an upper limit of the methodological uncertainty component of 0.2%, excluding high-Z elements such as iodine. The proposed calibration procedure is bias-free and straightforward to perform using standard equipment. Testing the calibration on five published data sets, we obtain very small differences in the calibration result in spite of different experimental setups and CT protocols used. Employing a general calibration per scanner type and voltage combination is thus conceivable.

CONCLUSION

Given the high suitability for clinical application of the alpha-blending approach in combination with a very small methodological uncertainty, we conclude that further refinement of image-based DECT-algorithms for electron density assessment is not advisable.

Dual-Energy CT in Head and Neck Imaging

PURPOSE OF REVIEW

To explain the technique of Dual-energy CT (DECT) and highlight its applications and advantages in head and neck radiology.

RECENT FINDINGS

Using DECT, additional datasets can be created next to conventional images. In head and neck radiology, three material decomposition algorithms can be used for improved lesion detection and delineation of the tumor. Iodine concentration measurements can aid in differentiating malignant from nonmalignant lymph nodes and benign posttreatment changes from tumor recurrence. Virtual non-calcium images can be used for detection of bone marrow edema. Virtual mono-energetic imaging can be useful for improved iodine conspicuity at lower keV and for reduction of metallic artifacts and increase in signal-to-noise ratio at higher keV.

SUMMARY

DECT and its additional reconstructions can play an important role in head and neck cancer patients, from initial diagnosis and staging, to therapy planning, evaluation of treatment response and follow-up. Moreover, it can be helpful in imaging of infections and inflammation and parathyroid imaging as supplementary reconstructions can be obtained at lower or equal radiation dose compared with conventional single energy scanning.

Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

OBJECTIVE

The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system.

METHODS

The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Z_eff) and relative electron densities (ρ_e) for phantom inserts with known elemental compositions and relative electron densities.

RESULTS

The optimal energy combination was determined to be 50 and 90 kVp. For this combination, Z_eff and ρ_e can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60 cGy.

CONCLUSION

Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Z_eff and ρ_e. When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Z_eff and ρ_e errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system.

A new method to measure electron density and effective atomic number using dual-energy CT images

The purpose of this work is to present a new method to extract the electron density ([Formula: see text]) and the effective atomic number (Z eff) from dual-energy CT images, based on a Karhunen-Loeve expansion (KLE) of the atomic cross section per electron. This method was used to calibrate a Siemens Definition CT using the CIRS phantom. The predicted electron density and effective atomic number using 80 kVp and 140 kVp were compared with a calibration phantom and an independent set of samples. The mean absolute deviations between the theoretical and calculated values for all the samples were 1.7 %  ±  0.1 % for [Formula: see text] and 4.1 %  ±  0.3 % for Z eff. Finally, these results were compared with other stoichiometric method. The application of the KLE to represent the atomic cross section per electron is a promising method for calculating [Formula: see text] and Z eff using dual-energy CT images.