Iodine Maps Research Articles

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

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

High-pitch, high temporal resolution, multi-energy cardiac imaging on a dual-source photon-counting-detector CT.

To measure the accuracy of material decomposition using a dual-source photon-counting-detector (DS-PCD) CT operated in the high-pitch helical scanning mode and compare the results against dual-source energy-integrating-detector (DS-EID) CT, which requires use of a low-pitch value in dual-energy mode. A DS-PCD CT and a DS-EID CT were used to scan a cardiac motion phantom consisting of a 3-mm diameter iodine cylinder. Iodine maps were reconstructed using DS-PCD in high-pitch mode and DS-EID in low-pitch mode. Image-based circularity, diameter, and iodine concentration of the iodine cylinder were calculated and compared between the two scanners. With institutional review board approval, in vivo exams were performed with the DS-PCD CT in high-pitch mode. Images were qualitatively compared against patients with similar heart rates that were scanned with DS-EID CT in low-pitch dual-energy mode. On iodine maps, the mean circularity was 0.97±0.02 with DS-PCD in high-pitch mode and 0.95±0.06 with DS-EID in low-pitch mode. The mean diameter was 2.9±0.2mm with DS-PCD and 3.1±0.2mm with DS-EID, both of which are close to the 3mm ground truth. For DS-PCD, the mean iodine concentration was 9.6±0.8mg/ml and this was consistent with the 9.4±0.6mg/ml value obtained with the cardiac motion disabled. For DS-EID, the concentration was 12.7±1.2mg/ml with motion enabled and 11.7±0.5mg/ml disabled. The background noise in the iodine maps was 15.1 HU with DS-PCD and 14.4 HU with DS-EID, whereas the volume CT dose index (CTDIvol ) was 3 mGy with DS-PCD and 11 mGy with DS-EID. On comparison of six patients (three on PCD, three on EID) with similar heart rates, DS-PCD provided iodine maps with well-defined coronaries even at a high heart rate of 86 beats per minute. Meanwhile, there were substantial motion artifacts in iodine maps obtained with DS-EID for patients with similar heart rates. In a cardiac motion phantom, DS-PCD CT can perform accurate material decomposition in high-pitch mode, providing iodine maps with excellent geometric accuracy and robustness to motion at approximately 38% of the dose for similar noise as DS-EID CT.

Dual-energy CT iodine map in predicting the efficacy of neoadjuvant chemotherapy for hypopharyngeal carcinoma: a preliminary study

Neoadjuvant chemotherapy has become one of the important means for advanced hypopharyngeal carcinoma. So far, there is no effective index to predict the curative effect. To investigate the value of iodine map of dual-energy computed tomography (CT) in predicting the efficacy of neoadjuvant chemotherapy for hypopharyngeal carcinoma. A total of 54 hypopharyngeal carcinomapatients who underwent two courses of TPF neoadjuvant chemotherapy were recruited in this study. Three cases had a complete response (CR), thirty-six cases had a partial response (PR), eleven cases had stable disease (SD), and four cases had a progressive disease (PD) after the chemotherapy. All patients underwent a dual-source CT scan before chemotherapy and rescanned after chemotherapy. The normalized iodine-related attenuation (NIRA) of the mean of maximum slice and most enhanced region of lesion at arterial and parenchymal phase were measured: NIRAmean-A, NIRAmax-A, NIRAmean-P, and NIRAmax-P, respectively. Correlation analysis was conducted between different metrics of NIRA and the diameter change rate of lesions, and the curative effect was evaluated based on the receiver operating characteristic (ROC) curve. There were a significant correlation between NIRAmean-A, NIRAmax-A, NIRAmean-P, NIRAmax-P and the change rate of lesion's maximum diameter (ΔD%) (all P < 0.01). The NIRAmax-A, NIRAmean-P, NIRAmax-P had significant differences between CR, PR, SD, PD groups, but NIRAmean-A did not reach a significant difference. All NIRAmean-A, NIRAmax-A, NIRAmean-P, NIRAmax-P had significant differences between effective (CR + PR) and ineffective (SD + PD) groups. The ROC analysis revealed that NIRAmean-P had the largest AUC and prediction efficacy (AUC = 0.809). Dual-energy CT iodine map could predict the efficacy of neoadjuvant chemotherapy and provides imaging evidence to assist in treatment decisions for hypopharyngeal carcinoma patients.

Iodine map histogram metrics in early-stage breast cancer: prediction of axillary lymph node metastasis status.

Variations in axillary lymph node (ALN) metastatic potential between different breast cancers lead to microscopical alterations in tumor perfusion heterogeneity. This study investigated the usefulness of histogram metrics from iodine maps in the preoperative diagnosis of metastatic ALNs in patients with early-stage breast cancer. Between October 2020 and November 2021 enhanced spectral computed tomography (CT) was performed in female patients with breast cancer. Quantitative spectral CT parameters and histogram parameters (mean, median, maximum, minimum, 10th percentiles, 90th percentiles, kurtosis, skewness, energy, range, and variance) from iodine maps were compared between patients with metastatic and nonmetastatic ALNs. Continuous variables were compared using Student's t-test or Mann-Whitney U test. Categorical variables were compared using Pearson's chi-square tests or Fisher's exact tests. Associations between ALN status and imaging features were evaluated using Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis. This study included 113 female patients (62 and 51 in the ALN-negative and ALN-positive groups, respectively). Tumor size, molecular subtypes, and location differed significantly between the ALN-negative and ALN-positive groups (P<0.05). None of the quantitative spectral CT parameters of mass between metastatic and nonmetastatic ALN groups were significantly different (P>0.05). Histogram parameters of iodine maps for breast cancers, including maximum, 10th percentile, range, and energy, were significantly higher in the metastatic ALNs group compared with the nonmetastatic ALNs group (P<0.05). Multivariable logistic regression analyses showed that tumor location and energy were independent predictors of metastatic ALNs in breast cancers. The combination of independent predictors yielded an area under the curve (AUC) of 0.824 (sensitivity 72.5%; specificity 74.2%). Whole-lesion histogram parameters derived from spectral CT iodine maps may be used as a complementary noninvasive means for the preoperative identification of ALN metastases in patients with early-stage breast cancer.

Evaluation of myocardial viability in patients with myocardial ischemia reperfusion injury using the dual-energy CT myocardial blood pool imaging.

To evaluate myocardial viability in patients with myocardial ischemia reperfusion injury (MIRI) via dual-energy computed tomography myocardial blood pool imaging (DECT MBPI). Between September 2017 and January 2019, we prospectively recruited 59 patients with acute myocardial infarction (AMI) who developed MIRI after revascularization during invasive coronary angiography (ICA). Then, they received DECT MBPI, SPECT, and PET sequentially within 1 week after the onset of MIRI. A total of 1003 myocardial segments of 59 patients were recruited for this study. The iodine reduction areas and delayed enhancement areas were calculated by cardiac iodine map with SPECT rest myocardial perfusion imaging (MPI) + PET myocardial metabolism imaging (MMI) as reference criteria. The paired sample t-test was used to measure the difference of the myocardial iodine value. Cohen's Kappa analysis was used to test the consistency among different observers. ROC analysis was used to calculate the myocardial viability of DECT MBPI. ROC showed the AUCs of DECT MBPI iodine value to identify a normal myocardium, an ischemic myocardium, and an infarcted myocardium were 0.957, 0.900, and 0.906 (p < 0.001). The sensitivity, specificity, and accuracy of DECT MBPI in identifying an ischemic myocardium were 87.6%, 89.3%, and 97.9% (p < 0.001). The sensitivity, specificity, and accuracy of DECT MBPI in identifying an infarcted myocardium were 88.9%, 92.2%, and 98.6% (p < 0.001). The cutoff value for DECT MBPI to differentiate between an ischemic and a normal myocardium was 0.84 mg I/mL. The cutoff value for DECT MBPI to differentiate between an infarct and a normal myocardium was 2.01 mg I/mL. DECT MBPI can be used to assess myocardial viability in patients with MIRI with high sensitivity and specificity. • Dual-energy computed tomography myocardial blood pool imaging (DECT MBPI) can evaluate myocardial viability of myocardial ischemia-reperfusion injury (MIRI). • DECT MBPI is a non-invasive and timesaving method for evaluation on myocardial ischemia-reperfusion injury in patients with acute myocardial infarction after coronary intervention.

Evaluation of radiomics feature stability in abdominal monoenergetic photon counting CT reconstructions

Feature stability and standardization remain challenges that impede the clinical implementation of radiomics. This study investigates the potential of spectral reconstructions from photon-counting computed tomography (PCCT) regarding organ-specific radiomics feature stability. Abdominal portal-venous phase PCCT scans of 10 patients in virtual monoenergetic (VM) (keV 40–120 in steps of 10), polyenergetic, virtual non-contrast (VNC), and iodine maps were acquired. Two 2D and 3D segmentations measuring 1 and 2 cm in diameter of the liver, lung, spleen, psoas muscle, subcutaneous fat, and air were obtained for spectral reconstructions. Radiomics features were extracted with pyradiomics. The calculation of feature-specific intraclass correlation coefficients (ICC) was performed by comparing all segmentation approaches and organs. Feature-wise and organ-wise correlations were evaluated. Segmentation-resegmentation stability was evaluated by concordance correlation coefficient (CCC). Compared to non-VM, VM-reconstruction features tended to be more stable. For VM reconstructions, 3D 2 cm segmentation showed the highest average ICC with 0.63. Based on a criterion of ≥ 3 stable organs and an ICC of ≥ 0.75, 12—mainly non-first-order features—are shown to be stable between the VM reconstructions. In a segmentation-resegmentation analysis in 3D 2 cm, three features were identified as stable based on a CCC of > 0.6 in ≥ 3 organs in ≥ 6 VM reconstructions. Certain radiomics features vary between monoenergetic reconstructions and depend on the ROI size. Feature stability was also shown to differ between different organs. Yet, glcm_JointEntropy, gldm_GrayLevelNonUniformity, and firstorder_Entropy could be identified as features that could be interpreted as energy-independent and segmentation-resegmentation stable in this PCCT collective. PCCT may support radiomics feature standardization and comparability between sites.

Dual-Energy CT for Accurate Discrimination of Intraperitoneal Hematoma and Intestinal Structures.

The purpose of this study was to evaluate the potential of dual-energy CT (DECT) with virtual unenhanced imaging (VNC) and iodine maps (IM) to differentiate between intraperitoneal hematomas (IH) and bowel structures (BS) compared to linearly blended DECT (DE-LB) images (equivalent to single-energy CT). This retrospective study included the DECT of 30 patients (mean age: 64.5 ± 15.1 years, 19 men) with intraperitoneal hematomas and 30 negative controls. VNC, IM, and DE-LB were calculated. Imaging follow-up and surgical reports were used as references. Three readers assessed diagnostic performance and confidence in distinguishing IH and BS for DE-LB, VNC, and IM. Diagnostic confidence was assessed on a five-point Likert scale. The mean values of VNC, IM, and DE-LB were compared with nonparametric tests. Diagnostic accuracy was assessed by calculating receiver operating characteristics (ROC). The results are reported as medians with interquartile ranges. Subjective image analysis showed higher diagnostic performance (sensitivity: 96.7–100% vs. 88.2–96.7%; specificity: 100% vs. 96.7–100%; p < 0.0001; ICC: 0.96–0.99) and confidence (Likert: 5; IRQ [5–5] vs. 4, IRQ [3–4; 4–5]; p < 0.0001; ICC: 0.80–0.96) for DECT compared to DE-LB. On objective image analysis, IM values for DECT showed significant differences between IH (3.9 HU; IQR [1.6, 8.0]) and BS (39.5 HU; IQR [29.2, 43.3]; p ≤ 0.0001). VNC analysis revealed a significantly higher attenuation of hematomas (50.5 HU; IQR [44.4, 59.4]) than BS (26.6 HU; IQR [22.8, 32.4]; p ≤ 0.0001). DE-LB revealed no significant differences between hematomas (60.5 HU, IQR [52.7, 63.9]) and BS (63.9 HU, IQR [58.0, 68.8]; p > 0.05). ROC analysis revealed the highest AUC values and sensitivity for IM (AUC = 100%; threshold by Youden-Index ≤ 19 HU) and VNC (0.93; ≥34.1 HU) compared to DE-LB (0.64; ≤63.8; p < 0.001). DECT is suitable for accurate discrimination between IH and BS by calculating iodine maps and VNC images.

Differentiation of Intracerebral Tumor Entities with Quantitative Contrast Attenuation and Iodine Mapping in Dual-Layer Computed Tomography.

Purpose: To investigate if quantitative contrast enhancement and iodine mapping of common brain tumor (BT) entities may correctly differentiate between tumor etiologies in standardized stereotactic CT protocols. Material and Methods: A retrospective monocentric study of 139 consecutive standardized dual-layer dual-energy CT (dlDECT) scans conducted prior to the stereotactic needle biopsy of untreated primary brain tumor lesions. Attenuation of contrast-enhancing BT was derived from polyenergetic images as well as spectral iodine density maps (IDM) and their contrast-to-noise-ratios (CNR) were determined using ROI measures in contrast-enhancing BT and healthy contralateral white matter. The measures were correlated to histopathology regarding tumor entity, isocitrate dehydrogenase (IDH) and MGMT mutation status. Results: The cohort included 52 female and 76 male patients, mean age of 59.4 (±17.1) years. Brain lymphomas showed the highest attenuation (IDM CNR 3.28 ± 1,23), significantly higher than glioblastoma (2.37 ± 1.55, p < 0.005) and metastases (1.95 ± 1.14, p < 0.02), while the differences between glioblastomas and metastases were not significant. These strongly enhancing lesions differed from oligodendroglioma and astrocytoma (Grade II and III) that showed IDM CNR in the range of 1.22–1.27 (±0.45–0.82). Conventional attenuation measurements in DLCT data performed equally or slightly superior to iodine density measurements. Conclusion: Quantitative attenuation and iodine density measurements of contrast-enhancing brain tumors are feasible imaging biomarkers for the discrimination of cerebral tumor lesions but not specifically for single tumor entities. CNR based on simple HU measurements performed equally or slightly superior to iodine quantification.

Impact of photon counting detector CT derived virtual monoenergetic images and iodine maps on the diagnosis of pleural empyema

PurposeThe purpose of this study was to evaluate the impact of virtual monoenergetic image (VMI) energies and iodine maps on the diagnosis of pleural empyema with photon counting detector computed tomography (PCD-CT). Materials and methodsIn this IRB-approved retrospective study, consecutive patients with non-infectious pleural effusion or histopathology-proven empyema were included. PCD-CT examinations were performed on a dual-source PCD-CT in the multi-energy (QuantumPlus) mode at 120 kV with weight-adjusted intravenous contrast-agent. VMIs from 40-70 keV obtained in 10 keV intervals and an iodine map was reconstructed for each scan. CT attenuation was measured in the aorta, the pleura and the peripleural fat (between autochthonous dorsal muscles and dorsal ribs). Contrast-to-noise (CNR) and signal-to-noise (SNR) ratios were calculated. Two blinded radiologists evaluated if empyema was present (yes/no), and rated diagnostic confidence (1 to 4; not confident to fully confident, respectively) with and without using the iodine map. Sensitivity, specificity and diagnostic confidence were estimated. Interobserver agreement was estimated using an unweighted Cohen kappa test. A one-way ANOVA was used to compare variables. Differences in sensitivity and specificity between the different levels of energy were searched using McNemar test. ResultsSixty patients (median age, 60 years; 26 women) were included. A strong negative correlation was found between image noise and VMI energies (r = -0.98; P = 0.001) and CNR increased with lower VMI energies (r = -0.98; P = 0.002). Diagnostic accuracy (96%; 95% CI: 82–100) as well as diagnostic confidence (3.4 ± 0.75 [SD]) were highest at 40 keV. Diagnostic accuracy and confidence at higher VMI energies improved with the addition of iodine maps (P ≤0.001). Overall, no difference in CT attenuation of peripleural fat between patients with empyema and those with pleural effusion was found (P = 0.07). ConclusionLow VMI energies lead to a higher diagnostic accuracy and diagnostic confidence in the diagnosis of pleural empyema. Iodine maps help in diagnosing empyema only at high VMI energies.

Dual-energy CT with virtual monoenergetic images and iodine maps improves tumor conspicuity in patients with pancreatic ductal adenocarcinoma

ObjectivesTo evaluate the value of monoenergetic images (MEI [+]) and iodine maps in dual-source dual-energy computed tomography (DECT) for assessing pancreatic ductal adenocarcinoma (PDAC), including the visually isoattenuating PDAC.Materials and methodsThis retrospective study included 75 PDAC patients, who underwent contrast-enhanced DECT examinations. Conventional polyenergetic image (PEI) and 40–80 keV MEI (+) (10-keV increments) were reconstructed. The tumor contrast, contrast-to-noise ratio (CNR) of the tumor and peripancreatic vessels, the signal-to-noise ratio (SNR) of the pancreas and tumor, and the tumor diameters were quantified. On iodine maps, the normalized iodine concentration (NIC) in the tumor and parenchyma was compared. For subjective analysis, two radiologists independently evaluated images on a 5-point scale.ResultsAll the quantitative parameters were maximized at 40-keV MEI (+) and decreased gradually with increasing energy. The tumor contrast, SNR of pancreas and CNRs in 40–60 keV MEI (+) were significantly higher than those in PEI (p < 0.05). For visually isoattenuating PDAC, 40–50 keV MEI (+) provided significantly higher tumor CNR compared to PEI (p < 0.05). The reproducibility in tumor measurements was highest in 40-keV MEI (+) between the two radiologists. The tumor and parenchyma NIC were 1.28 ± 0.65 and 3.38 ± 0.72 mg/mL, respectively (p < 0.001). 40–50 keV MEI (+) provided the highest subjective scores, compared to PEI (p < 0.001).ConclusionsLow-keV MEI (+) of DECT substantially improves the subjective and objective image quality and consistency of tumor measurements in patients with PDAC. Combining the low-keV MEI (+) and iodine maps may yield diagnostically adequate tumor conspicuity in visually isoattenuating PDAC.

Dual-energy CT: Technical considerations and clinical applications

Although dual-energy CT was initially described by Hounsfield in 1973, it remains underused in clinical practice. It is therefore important to emphasize the clinical benefits and limitations of this technique. Iodine mapping makes it possible to quantify the uptake of iodine, which is very important in characterizing tumors, lung perfusion, pulmonary nodules, and the tumor response to new treatments. Dual-energy CT also makes it possible to obtain virtual single-energy images and virtual images without iodinated contrast or without calcium, as well as to separate materials such as uric acid or fat and to elaborate hepatic iron overload maps. In this article, we review some of the clinical benefits and technical limitations to improve understanding of dual-energy CT and expand its use in clinical practice.

Dual-energy CT imaging of chronic subdural hematoma membranes: technical note.

This technical note describes a novel dual-energy CT (DECT) protocol with iodine map reconstruction that will enable visualization of chronic subdural hematoma (CSDH) membranes. We describe the technique and discuss the potential implications for surgical management. The cohort included 36 patients with 50 hematomas. Enhancing external membrane was demonstrated in all the 50 hematomas, incomplete internal membrane in 13, and complete internal membrane in 23 hematomas. A spandrel sign at the transition zone that indicates partial or complete formation of internal membrane was demonstrated in 36 hematomas. KEY POINTS: • Iodine maps from 5-min delayed post-contrast DECT provide spectral contrast difference and facilitate segregation of chronic subdural hematoma membranes. • The ability to image the membranes helps in assessing the degree of organization of the hematoma by providing the information about the membrane thickness, volume, complexity of the membranes, and the proportion of the liquefied component within the hematoma before surgical procedures are undertaken. • Membrane visualization helps in the localization of the transition zone and extension of the membranes over the cerebral lobes helping in the determination of craniotomy location and size, during membranectomy.

Multivendor Comparison of Quantification Accuracy of Iodine Concentration and Attenuation Measurements by Dual-Energy CT: A Phantom Study.

BACKGROUND. Studies comparing accuracy of quantification by dual-energy CT (DECT) scanners have been limited by small numbers of scanners evaluated and narrow ranges of scanning conditions. OBJECTIVE. The purpose of this study was to compare DECT scanners of varying vendors, technologies, and generations in terms of the accuracy of iodine concentration and attenuation measurements. METHODS. A DECT quality-control phantom was designed to contain seven inserts of varying iodine concentrations as well as soft-tissue and fat inserts. The phantom underwent DECT using 12 different scanner configurations based on seven different DECT scanners from three vendors, with additional variation in tube voltage settings. Technologies included rapid-switching, dual-source, and dual-layer detector DECT. Scans also used three radiation dose levels (10, 20, and 30 mGy) and multiple reconstruction algorithms (filtered back projection, medium and high iterative reconstruction, and deep learning image reconstruction [DLIR]). The mean absolute percentage error (MAPE, representing the absolute ratio of measured error to nominal values on average; lower values indicate better accuracy) was calculated for iodine concentration on iodine maps (MAPEiodine) and attenuation on virtual monochromatic images (VMIs) using 40, 70, 100, and 140 keV (MAPEHU). Linear mixed models were used to explore factors affecting quantification accuracy. RESULTS. MAPEiodine and MAPEHU ranged 4.62-28.55% and 10.21-26.33%, respectively, across scanner configurations. Accuracies of iodine concentration and attenuation measurements were higher for third-generation rapid-switching and dual-source scanners in comparison with respective earlier-generation scanners and the single evaluated dual-layer detector scanner. Among all configurations, the third-generation rapid-switching scanner using DLIR had the highest quantification accuracy for iodine concentration (MAPEiodine, 4.62% ± 3.87%) and attenuation (MAPEHU, 10.21% ± 11.43%). Overall, MAPEiodine was significantly affected by scanner configuration (F = 450.0, p < .001) and iodine concentration (F = 211.0, p < .001). Overall, MAPEHU was significantly affected by scanner configuration (F = 233.5, p < .001), radiation dose (F = 14.9, p < .001), VMI energy level (F = 1959.4, p < .001), and material density (F = 411.5, p < .001); radiation dose was significantly associated with MAPEHU for five of 12 individual configurations. CONCLUSION. Quantification accuracy varied among DECT configurations of varying vendors, platforms, and generations and was affected by acquisition and reconstruction parameters. DLIR may improve quantification accuracy. CLINICAL IMPACT. The interscanner differences in DECT-based measurements should be recognized when quantitative evaluation is performed by DECT in clinical practice.

Energía Dual en TC. Consideraciones técnicas y aplicaciones clínicas

Although dual-energy CT was initially described by Hounsfield in 1973, it remains underused in clinical practice. It is therefore important to emphasize the clinical benefits and limitations of this technique. Iodine mapping makes it possible to quantify the uptake of iodine, which is very important in characterizing tumors, lung perfusion, pulmonary nodules, and the tumor response to new treatments. Dual-energy CT also makes it possible to obtain virtual single-energy images and virtual images without iodinated contrast or without calcium, as well as to separate materials such as uric acid or fat and to elaborate hepatic iron overload maps. In this article, we review some of the clinical benefits and technical limitations to improve understanding of dual-energy CT and expand its use in clinical practice.

Contribution of analysis of perfusion iodine map’s to diagnostic of acute pulmonary thromboembolism

Purpose: to study the contribution of perfusion iodine maps to diagnosis of acute pulmonary embolism (PE) and compare pulmonary perfusion defects with the main imaging biomarkers of PE.Materials and methods. 130 patients with suspected acute pulmonary thromboembolism were studied using pulmonary computed tomographic angiography with perfusion iodine map`s analysis. Pulmonary embolism was revealed in 42 cases. There were evaluated: the number and level of vessel occlusion (Qanadli index), number and grades of lung perfusion defects on perfusion iodine maps (perfusion index), signs of right heart failure, changes of lung parenchyma.Results. Analysis of the data showed a strong correlation between the index Qanadli and perfusion index, rather than signs of right failure. In 3 cases, the segmental and subsegmential pulmonary embolism was revealed form the iodine map’s analysis only.Conclusion. Thus, perfusion iodine maps improve the diagnosis of acute pulmonary embolism due to characterizing the changes of pulmonary microcirculation. From our data, the iodine maps can be employed as a prognostic tool for further therapy.

Dual Energy Technique Adds Value to Solitary Pulmonary Nodule Analysis with Dynamic Contrast-Enhanced CT: A 100 Nodule Experience

A highly sensitive test for evaluation of solitary pulmonary nodules (SPN) involves a 5-phase, contrast enhanced CT evaluation which can be fraught with technical error. The goal of this study is to determine if qualitative evaluation of iodine maps with dual energy CT (DECT) can add value to SPN evaluation.100 patients had their SPN evaluated with traditional quantitative analysis and qualitative evaluation with iodine maps generated from DECT data acquired at 80 kVp and 140 kVp. Quantitative analysis served as the gold standard. Quantitative analysis was performed at 1, 2, 3, and 4 minutes. Qualitative Iodine maps analysis was performed at 1 and 2 minutes. Sensitivity and specificity were 63% and 95%, and 73% and 91%, respectively, at 1 and 2 minutes. Combined analysis resulted in sensitivity of 67% and specificity of 94%. Six of 7 false negatives on combined analysis were stable for 2 years and the seventh was lost to follow up after 1 year. Of 5 false positives on combined analysis; 2 were due to 'bleed-through of calcium' on iodine maps, 2 were positive on 3 and 4-minute quantitative analysis with one biopsy-proven adenocarcinoma. Qualitative analysis of Iodine maps generated using DECT data can be easily performed and may provide more effective evaluation of the solitary pulmonary nodule when combined with traditional analysis. This method warrants further investigation with larger patient populations, comparison with PET-CT, and evaluation of outcomes including long-term nodule stability and tissue diagnosis.

Imaging Advances in Chronic Thromboembolic Pulmonary Hypertension

Chronic thromboembolic pulmonary hypertension (CTEPH) is an under recognized complication of pulmonary embolism with significant morbidity and mortality when left untreated. There have been ongoing advances in the treatment of CTEPH with potentially excellent outcomes for patients when diagnosed and treated in a timely fashion. Although ventilation-perfusion scintigraphy remains critical in screening for CTEPH, the radiologic diagnosis involves multiple modalities from digital subtraction angiography to high quality computed tomography pulmonary angiography. State of the art imaging in CTEPH now also includes dual energy computed tomography, lung subtraction iodine mapping, and magnetic resonance imaging.

Material decomposition from photon-counting CT using a convolutional neural network and energy-integrating CT training labels

Objective. Photon-counting CT (PCCT) has better dose efficiency and spectral resolution than energy-integrating CT, which is advantageous for material decomposition. Unfortunately, the accuracy of PCCT-based material decomposition is limited due to spectral distortions in the photon-counting detector (PCD). Approach. In this work, we demonstrate a deep learning (DL) approach that compensates for spectral distortions in the PCD and improves accuracy in material decomposition by using decomposition maps provided by high-dose multi-energy-integrating detector (EID) data as training labels. We use a 3D U-net architecture and compare networks with PCD filtered back projection (FBP) reconstruction (FBP2Decomp), PCD iterative reconstruction (Iter2Decomp), and PCD decomposition (Decomp2Decomp) as the input. Main results. We found that our Iter2Decomp approach performs best, but DL outperforms matrix inversion decomposition regardless of the input. Compared to PCD matrix inversion decomposition, Iter2Decomp gives 27.50% lower root mean squared error (RMSE) in the iodine (I) map and 59.87% lower RMSE in the photoelectric effect (PE) map. In addition, it increases the structural similarity (SSIM) by 1.92%, 6.05%, and 9.33% in the I, Compton scattering (CS), and PE maps, respectively. When taking measurements from iodine and calcium vials, Iter2Decomp provides excellent agreement with multi-EID decomposition. One limitation is some blurring caused by our DL approach, with a decrease from 1.98 line pairs/mm at 50% modulation transfer function (MTF) with PCD matrix inversion decomposition to 1.75 line pairs/mm at 50% MTF when using Iter2Decomp. Significance. Overall, this work demonstrates that our DL approach with high-dose multi-EID derived decomposition labels is effective at generating more accurate material maps from PCD data. More accurate preclinical spectral PCCT imaging such as this could serve for developing nanoparticles that show promise in the field of theranostics (therapy and diagnostics).

Radiomic Analysis of Pulmonary Nodules for Distinguishing Malignancy From Benignancy: The Value of Using Iodine Maps From Dual-Energy Computed Tomography.

The aim of the study is to investigate the diagnostic accuracy of radiomics on iodine maps from dual-energy computed tomography (DECT) in distinguishing lung cancer from benign pulmonary nodules. This retrospective study was approved by the institutional review board, and written informed consent was waived. A total of 109 patients with 55 malignant nodules and 62 benign nodules underwent contrast-enhanced DECT. Eight iodine uptake parameters on iodine maps generated by DECT were calculated and established a predictive model. Eighty-seven radiomics features of entire tumor were extracted from iodine maps and established a radiomics model. The iodine uptake model and radiomics model were independently built based on the highly reproducible features using the least absolute shrinkage and selection operator method. The diagnostic accuracy of 2 models were assessed using receiver operating curve analysis. For external validation, 47 patients (25 benign and 22 malignant) from another hospital were assigned to testing data set. All iodine uptake features showed significant association with malignancy ( P < 0.01) and 2 selected features (mean value of virtual noncontrast images and mean value of vital part on contrast-enhanced image) constituted the iodine model. The radiomics model comprised 2 features (original shape sphericity and original glszm small area high gray level emphasis), which showed good discrimination both in the training cohort (area under the curve, 0.957) and validation cohort (area under the curve, 0.800). Radiomics model showed superior performance than iodine uptake model (accuracy, 89.7% vs 80.6%). Radiomics model extracted from iodine maps provided a robust diagnostic tool for discriminating pulmonary malignant nodules and had high potential in clinical application.

Assessment of Correlation between Dual-Energy Ct (De-Ct)-Derived Iodine Concentration and Local Flourodeoxyglucose (Fdg) Uptake in Patients with Primary Non-Small-Cell Lung Cancer.

(1) The current literature contains several studies investigating the correlation between dual-energy-derived iodine concentration (IC) and positron emission tomography (PET)-derived Flourodeoxyglucose (18F-FDG) uptake in patients with non-small-cell lung cancer (NSCLC). In previously published studies, either the entire tumor volume or a region of interest containing the maximum IC or 18F-FDG was assessed. However, the results have been inconsistent. The objective of this study was to correlate IC with FDG both within the entire volume and regional sub-volumes of primary tumors in patients with NSCLC. (2) In this retrospective study, a total of 22 patients with NSCLC who underwent both dual-energy CT (DE-CT) and 18F-FDG PET/CT were included. A region of interest (ROI) encircling the entire primary tumor was delineated, and a rigid registration of the DE-CT, iodine maps and FDG images was performed for the ROI. The correlation between tumor measurements and area-specific measurements of ICpeak and the peak standardized uptake value (SUVpeak) was found. Finally, a correlation between tumor volume and the distance between SUVpeak and ICpeak centroids was found. (3) For the entire tumor, moderate-to-strong correlations were found between SUVmax and ICmax (R = 0.62, p = 0.002), and metabolic tumor volume vs. total iodine content (R = 0.91, p < 0.001), respectively. For local tumor sub-volumes, a negative correlation was found between ICpeak and SUVpeak (R = −0.58, p = 0.0046). Furthermore, a strong correlation was found between the tumor volume and the distance in millimeters between SUVpeak and ICpeak centroids (R = 0.81, p < 0.0001). (4) In patients with NSCLC, high FDG uptakes and high DE-CT-derived iodine concentrations correlated on a whole-tumor level, but the peak areas were positioned at different locations within the tumor. 18F-FDG PET/CT and DE-CT provide complementary information and might represent different underlying patho-physiologies.