Quantitative distribution of iodinated contrast media in body computed tomography: data from a large reference cohort

What to Expect (and What Not) from Dual-Energy CT Imaging Now and in the Future?

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.

Virtual non-contrast images of detector-based spectral computed tomography in dogs: a promising alternative to true non-contrast images in veterinary medicine

Introduction

In veterinary medicine, abdominal computer tomographic (CT) examinations regularly require a minimum of two scans, with a native scan (true unenhanced, TUE) as a reference for the subsequent contrast-enhanced CT scan (CECT). Spectral detector CT (SDCT) offers the possibility to calculate virtual non-contrast (VNC) images from the post-contrast scan, but this has not yet been investigated in veterinary medicine. The purpose of this study was to assess the reliability of VNC images for abdominal organs in 44 dogs without abdominal pathologies by evaluating their quantitative and qualitative parameters compared to TUE images. We hypothesized that the subtraction of iodine is sufficient in the VNC series compared to the TUE series and that the image quality of the SDCT series is superior to conventional CT images.

Methods

Corresponding attenuation values in the VNC and TUE series regarding the regions of interest (ROI) in different parenchymal organs and major vessels of the abdominal cavity were assessed by means of a two one-sided t-test (TOST) and Bland-Altman plots. Additionally, the signal-to-noise ratio (SNR) was calculated for each ROI in the different series. In the second step, two board-certified veterinary radiologists made a qualitative assessment of VNC images vs. TUE images in consensus by rating the iodine subtraction, image noise, and image quality of VNC images based on a specific 5-point Likert scale.

Results

The difference in corresponding Hounsfield units (HUs) between TUE and VNC images was less than 10 HU in 78.67% of all ROIs. Regarding the limit of less than 10 HU, in the performed TOST, significant p-values of < 0.05 were reached for the liver, spleen, pancreas, and musculature, implying equivalence of both modalities. The quality of spectral base image (SBI) data was rated equivalent to calculated conventional images in the subjective assessment by reaching an average Likert scale score of 3.2 points.

Discussion

VNC images calculated from SDCT data prove a valid alternative to conventional TUE images in the abdominal organs of canine patients without abdominal pathology. VNC offers the possibility to reduce time under general anesthesia and minimize radiation exposure. Future studies are needed to prove the application of this method in clinically diseased patients.

Dual-energy CT in the differentiation between adrenal adenomas and metastases: Usefulness of material density maps and monochromatic images

OBJECTIVE

To evaluate the behavior of adrenal adenomas and metastases with dual-energy CT, analyzing the attenuation coefficient in monochromatic images at three different levels of energy (45, 70, and 140 keV) and the tissue concentrations of fat, water, and iodine in material density maps, with the aim of establishing optimal cutoffs for differentiating between these lesions and comparing our results against published evidence.

MATERIALS AND METHODS

This retrospective case-control study included oncologic patients diagnosed with adrenal metastases in the 6-12 months prior to the study who were followed up in our hospital between January and June 2020. For each case (patient with metastases) included in the study, we selected a control (patient with an adrenal adenoma) with a nodule of similar size. All patients were studied with a rapid-kilovoltage-switching dual-energy CT scanner, using a biphasic acquisition protocol. We analyzed the concentration of iodine in paired water-iodine images, the concentration of fat in the paired water-fat images, and the concentration of water in the paired iodine-water and fat-water images, in both the arterial and portal phases. We also analyzed the attenuation coefficient in monochromatic images (at 55, 70, and 140 keV) in the arterial and portal phases.

RESULTS

In the monochromatic images, in both the arterial and portal phases, the attenuation coefficient at all energy levels was significantly higher in the group of patients with metastases than in the group of patients with adenomas. This enabled us to calculate the optimal cutoffs for classifying lesions as adenomas or metastases, except for the arterial phase at 55 KeV, where the area under the receiver operating characteristic curve (AUC) for the estimated threshold (0.68) was not considered accurate enough to classify the lesions. For the arterial phase at 70 keV, the AUC was 0.76 (95% CI: 0.663‒0.899); the optimal cutoff (42.4 HU) yielded 92% sensitivity and 60% specificity. For the arterial phase at 140 keV, the AUC was 0.94 (95% CI: 0.894‒0.999); the optimal cutoff (18.9 HU) yielded 88% sensitivity and 94% specificity). For the portal phase at 55 keV, the AUC was 0.76 (95% CI: 0.663‒0.899); the optimal cutoff (95.4 HU) yielded 68% sensitivity and 84% specificity. For the portal phase at 70 keV, the AUC was 0.82 (95% CI: 0.757‒0.955); the optimal cutoff (58.4 HU) yielded 80% sensitivity and 84% specificity. For the portal phase at 140 keV, the AUC was 0.9 (95% CI: 0.834‒0.987); the optimal cutoff (16.35 HU) yielded 96% sensitivity and 84% specificity. In the material density maps, in the arterial phase, significant differences were found only for the iodine-water pair, where the concentration of water was higher in the group with metastases (1018.8 ± 7.6 mg/cm3 vs. 998.6 ± 8.0 mg/cm3 for the group with adenomas, p < 0.001). The AUC was 0.97 (95% CI: 0.893‒0.999); the optimal cutoff (1012.5 mg/cm3) yielded 88% sensitivity and 96% specificity. The iodine-water pair was also significantly higher in metastases (1019.7 ± 12.1 mg/cm3 vs. 998.5 ± 9.1 mg/cm3 in adenomas, p < 0.001). The AUC was 0.926 (95% CI: 0.807‒0.977); the optimal cutoff (1009.5 mg/cm3) yielded 92% sensitivity and 92% specificity. Although significant results were also observed for the fat-water pair in the portal phase, the AUC was insufficient to enable a sufficiently accurate cutoff for classifying the lesions. No significant differences were found in the fat-water maps or iodine-water maps in the arterial or portal phase or in the water-fat map in the arterial phase.

CONCLUSIONS

Monochromatic images show differences between the behavior of adrenal adenomas and metastases in oncologic patients studied with intravenous-contrast-enhanced CT, where the group of metastases had higher attenuation than the group of adenomas in both the arterial and portal phases; this pattern is in line with the evidence published for adenomas. Nevertheless, to our knowledge, no other publications report cutoffs for this kind of differentiation in contrast-enhanced monochromatic images obtained in rapid-kilovoltage-switching dual-energy CT scanners, and this is the first new contribution of our study. Regarding the material density maps, our results suggest that the water-iodine pair is a good tool for differentiating between adrenal adenomas and metastases, in both the arterial and portal phases. We propose cutoffs for differentiating these lesions, although to our knowledge no cutoffs have been proposed for portal-phase contrast-enhanced images obtained with rapid-kilovoltage-switching dual-energy CT scanners.

Comparison of the Medical Uses and Cellular Effects of High and Low Linear Energy Transfer Radiation

Exposure to ionizing radiation can occur during medical treatments, from naturally occurring sources in the environment, or as the result of a nuclear accident or thermonuclear war. The severity of cellular damage from ionizing radiation exposure is dependent upon a number of factors including the absorbed radiation dose of the exposure (energy absorbed per unit mass of the exposure), dose rate, area and volume of tissue exposed, type of radiation (e.g., X-rays, high-energy gamma rays, protons, or neutrons) and linear energy transfer. While the dose, the dose rate, and dose distribution in tissue are aspects of a radiation exposure that can be varied experimentally or in medical treatments, the LET and eV are inherent characteristics of the type of radiation. High-LET radiation deposits a higher concentration of energy in a shorter distance when traversing tissue compared with low-LET radiation. The different biological effects of high and low LET with similar energies have been documented in vivo in animal models and in cultured cells. High-LET results in intense macromolecular damage and more cell death. Findings indicate that while both low- and high-LET radiation activate non-homologous end-joining DNA repair activity, efficient repair of high-LET radiation requires the homologous recombination repair pathway. Low- and high-LET radiation activate p53 transcription factor activity in most cells, but high LET activates NF-kB transcription factor at lower radiation doses than low-LET radiation. Here we review the development, uses, and current understanding of the cellular effects of low- and high-LET radiation exposure.

Utility of dual-layer spectral-detector CT imaging for predicting pathological tumor stages and histologic grades of colorectal adenocarcinoma

Objectives

To assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC).

Methods

A total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy.

Results

Intra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NIC_AP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NIC_VP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHU_AP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHU_VP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NIC_AP[0.20 (0.10) vs 0.13 (0.08)], NIC_VP[0.35 (0.07) vs 0.31 (0.11)], and λHU_AP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, λHU_AP, and λHU_VP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NIC_AP, NIC_VP, and λHU_AP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05).

Conclusions

The quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections

PURPOSE

To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen.

METHOD

This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI_40keV, IO.

RESULTS

Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI_70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI_40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement.

CONCLUSION

Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.

Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters

OBJECTIVES

To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer.

METHODS

In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters.

RESULTS

Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NIC_PA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Z_eff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NIC_PA, and Z_eff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001).

CONCLUSIONS

DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer.

KEY POINTS

• DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NIC_PA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.

Value of spectral detector computed tomography for the early assessment of technique efficacy after microwave ablation of hepatocellular carcinoma

OBJECTIVES

To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis.

METHODS

This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40-100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy.

RESULTS

Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p<0.05). Iodine concentration and perfusion ratio differed significantly between HR and RT (all p<0.05; e.g. iodine concentration, 1.6±0.5 vs. 2.7±1.3 mg/ml). VMI50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p<0.05). Diagnostic accuracy for detection of incomplete ablation was slightly higher in VMI50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI50keV (p<0.05).

CONCLUSIONS

Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.

Consolidated lung on contrast-enhanced chest CT: the use of spectral-detector computed tomography parameters in differentiating atelectasis and pneumonia

Objectives

To investigate the value of spectral-detector computed tomography (SDCT) parameters for the quantitative differentiation between atelectasis and pneumonia on contrast-enhanced chest CT.

Material and methods

Sixty-three patients, 22 clinically diagnosed with pneumonia and 41 with atelectasis, underwent contrast-enhanced SDCT scans during the venous phase. CT numbers (Hounsfield Units [HU]) were measured on conventional reconstructions (CON_120kVp) and the iodine concentration (C_iodine, [mg/ml]), and effective atomic number (Z_eff) on spectral reconstructions, using region-of-interest (ROI) analysis. Receiver operating characteristics (ROC) and contrast-to-noise ratios (CNRs) were calculated to assess each reconstruction's potential to differentiate between atelectasis and pneumonia.

Results

On contrast-enhanced SDCT, the difference between atelectasis and pneumonia was significant on CON_120kVp, C_iodine, and Z_eff images (p < 0.001). On CON_120kVp images, a threshold of 81 HU achieved a sensitivity of 93 % and a specificity of 95 % for identifying pneumonia, while C_iodine and Z_eff images reached the same sensitivity but lower specificities of 85 % and 83 %. CON_120kVp images showed significantly higher CNRs between normal lung and atelectasis or pneumonia with 30.63 and 27.69 compared to C_iodine images with 3.54 and 1.27 and Z_eff images with 4.22 and 7.63 (p < 0.001). None of the parameters could differentiate atelectasis and pneumonia without contrast media.

Conclusions

Contrast-enhanced SDCT can differentiate atelectasis and pneumonia based on the spectral parameters C_iodine, and Z_eff. However, they had no added value compared to CT number measurement on CON_120kVp images. Furthermore, contrast media is still needed for a differentiation based on quantitative SDCT parameters.