Dual-Energy CT: New Horizon in Medical Imaging

CT-based synthetic iodine map generation using conditional denoising diffusion probabilistic model

BACKGROUND

Iodine maps, derived from image-processing of contrast-enhanced dual-energy computed tomography (DECT) scans, highlight the differences in tissue iodine intake. It finds multiple applications in radiology, including vascular imaging, pulmonary evaluation, kidney assessment, and cancer diagnosis. In radiation oncology, it can contribute to designing more accurate and personalized treatment plans. However, DECT scanners are not commonly available in radiation therapy centers. Additionally, the use of iodine contrast agents is not suitable for all patients, especially those allergic to iodine agents, posing further limitations to the accessibility of this technology.

PURPOSE

The purpose of this work is to generate synthetic iodine map images from non-contrast single-energy CT (SECT) images using conditional denoising diffusion probabilistic model (DDPM).

METHODS

One-hundered twenty-six head-and-neck patients' images were retrospectively investigated in this work. Each patient underwent non-contrast SECT and contrast DECT scans. Ground truth iodine maps were generated from contrast DECT scans using commercial software syngo.via installed in the clinic. A conditional DDPM was implemented in this work to synthesize iodine maps. Three-fold cross-validation was conducted, with each iteration selecting the data from 42 patients as the test dataset and the remainder as the training dataset. Pixel-to-pixel generative adversarial network (GAN) and CycleGAN served as reference methods for evaluating the proposed DDPM method.

RESULTS

The accuracy of the proposed DDPM was evaluated using three quantitative metrics: mean absolute error (MAE) (1.039 ± 0.345 mg/mL), structural similarity index measure (SSIM) (0.89 ± 0.10) and peak signal-to-noise ratio (PSNR) (25.4 ± 3.5 db) respectively. Compared to the reference methods, the proposed technique showcased superior performance across the evaluated metrics, further validated by the paired two-tailed t-tests.

CONCLUSION

The proposed conditional DDPM framework has demonstrated the feasibility of generating synthetic iodine map images from non-contrast SECT images. This method presents a potential clinical application, which is providing accurate iodine contrast map in instances where only non-contrast SECT is accessible.

What is the appropriate measure of radiology workload: Study or image numbers?

INTRODUCTION

Previous studies assessing the volume of radiological studies rarely considered the corresponding number of images. We aimed to quantify the increases in study and image numbers per radiologist in a tertiary healthcare network to better understand the demands on imaging services.

METHODS

Using the Picture Archiving and Communication System (PACS), the number of images per study was obtained for all diagnostic studies reported by in-house radiologists at a tertiary healthcare network in Melbourne, Australia, between January 2009 and December 2022. Payroll data was used to obtain the numbers of full-time equivalent radiologists.

RESULTS

Across all modalities, there were 4,462,702 diagnostic studies and 1,116,311,209 images. The number of monthly studies increased from 17,235 to 35,152 (104%) over the study period. The number of monthly images increased from 1,120,832 to 13,353,056 (1091%), with computed tomography (CT) showing the greatest absolute increase of 9,395,653 images per month (1476%). There was no increase in the monthly studies per full-time equivalent radiologist; however, the number of monthly image slices per radiologist increased 399%, from 48,781 to 243,518 (Kendall Tau correlation coefficient 0.830, P-value < 0.0001).

CONCLUSION

The number of monthly images per radiologist increased substantially from 2009 to 2022, despite a relatively constant number of monthly studies per radiologist. Our study suggests that using the number of studies as an isolated fundamental data set underestimates the true radiologist's workload. We propose that the increased volume of images examined by individual radiologists may more appropriately reflect true work demand and may add more weight to future workforce planning.

Low Dose Iodinated Contrast Material and Radiation for Virtual Monochromatic Imaging in Craniocervical Dual-Layer Spectral Detector Computed Tomography Angiography: A Prospective and Randomized Study

RATIONALE AND OBJECTIVES

To investigate the feasibility of virtual monochromatic imaging (VMI) of dual-layer spectral detector computed tomography (SDCT) to reduce iodinated contrast material (CM) and radiation dose in craniocervical computed tomography angiography (CTA).

MATERIALS AND METHODS

A total of 280 consecutively selected patients performed craniocervical CTA with SDCT were prospectively selected and randomly divided into four groups (A, DoseRight index (DRI) 31, iopromide 370mgI/mL, volume 0.8 mL/kg; B, DRI 26, iopromide 370mgI/mL, volume 0.4 mL/kg; C, DRI 26, ioversol 320mgI/mL, volume 0.4 mL/kg; D, DRI 26, iohexol 300mgI/mL, volume 0.4 mL/kg). 50-70 kiloelectron volts (keV) VMIs in group B were reconstructed and compared to group A to select the optimal keV. Then, the optimal keV in groups B, C and D was reconstructed and compared. Objective image quality, including vascular attenuation, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), was evaluated. Subjective image quality was assessed using a 5-point Likert scale. In addition, the effective dose (ED), iodine load and iodine delivery rate (IDR) were compared between groups A and D.

RESULTS

55 keV VMI was the optimal VMI in group B. The objective and subjective image quality of 55 keV VMI in group B were equal to or better than those of the CI in group A. The SNR, CNR and subjective image quality in group D were similar to those in group B (P > 0.05). The ED, iodine load and IDR of group D were reduced by 44%, 59% and 19%, respectively, when compared to those of group A.

CONCLUSION

Low dose iodinated CM and radiation for 55 keV VMI in craniocervical CTA using SDCT could still provide equivalent or better image quality than the conventional scanning protocol.

Conversion of single-energy CT to parametric maps of dual-energy CT using convolutional neural network

OBJECTIVES

We propose a deep learning (DL) multitask learning framework using convolutional neural network for a direct conversion of single-energy CT (SECT) to 3 different parametric maps of dual-energy CT (DECT): virtual-monochromatic image (VMI), effective atomic number (EAN), and relative electron density (RED).

METHODS

We propose VMI-Net for conversion of SECT to 70, 120, and 200 keV VMIs. In addition, EAN-Net and RED-Net were also developed to convert SECT to EAN and RED. We trained and validated our model using 67 patients collected between 2019 and 2020. Single-layer CT images with 120 kVp acquired by the DECT (IQon spectral CT; Philips Healthcare, Amsterdam, Netherlands) were used as input, while the VMIs, EAN, and RED acquired by the same device were used as target. The performance of the DL framework was evaluated by absolute difference (AD) and relative difference (RD).

RESULTS

The VMI-Net converted 120 kVp SECT to the VMIs with AD of 9.02 Hounsfield Unit, and RD of 0.41% compared to the ground truth VMIs. The ADs of the converted EAN and RED were 0.29 and 0.96, respectively, while the RDs were 1.99% and 0.50% for the converted EAN and RED, respectively.

CONCLUSIONS

SECT images were directly converted to the 3 parametric maps of DECT (ie, VMIs, EAN, and RED). By using this model, one can generate the parametric information from SECT images without DECT device. Our model can help investigate the parametric information from SECT retrospectively.

ADVANCES IN KNOWLEDGE

DL framework enables converting SECT to various high-quality parametric maps of DECT.

A clinical-radiomics nomogram based on spectral CT multi-parameter images for preoperative prediction of lymph node metastasis in colorectal cancer

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics features selected were used to generate a composed radiomics signature (Com-RS). A nomogram was developed using age, CEA, and the Com-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer.

Evaluation of Radiation Dose Effect on Lung Function Using Iodine Maps Derived From Dual-Energy Computed Tomography

PURPOSE

There is interest in using dual-energy computed tomography (DECT) to evaluate organ function before and after radiation therapy (RT). The purpose of this study (trial identifier: NCT04863027) is to assess longitudinal changes in lung perfusion using iodine maps derived from DECT in patients with lung cancer treated with conventional or stereotactic RT.

METHODS AND MATERIALS

For 48 prospectively enrolled patients with lung cancer, a contrast-enhanced DECT using a dual-source CT simulator was acquired pretreatment and at 6 and 12 months posttreatment. Pulmonary functions tests (PFT) were obtained at baseline and at 6 and 12 months posttreatment. Iodine maps were extracted from the DECT images using a previously described 2-material decomposition framework. Longitudinal iodine maps were normalized using a reference region defined as all voxels with perfusion in the top 10% outside of the 5 Gy isodose volume. Normalized functional responses (NFR) were calculated for 3 dose ranges: <5, 5 to 20, and >20 Gy. Mixed model analysis was used to assess the correlation between dose metrics and NFR. Pearson correlation was used to assess if NFRs were correlated with PFT changes.

RESULTS

Out of the 48 patients, 21 (44%) were treated with stereotactic body RT and 27 (56%) were treated with conventionally fractionated intensity-modulated RT. Thirty-one out of these 48 patients were ultimately included in data analysis. It was found that NFR is linearly correlated with dose (P < .001) for both groups. The number of months elapsed post-RT was also found to correlate with NFR (P = .029), although this correlation was not observed for the stereotactic body RT subgroup. The NFR was not found to correlate with PFT changes.

CONCLUSIONS

DECT-derived iodine maps are a promising method for detailed anatomic evaluation of radiation effect on lung function, including potentially subclinical changes.

Fractures in Thoroughbred racing and the potential for pre-race identification of horses at risk

Risk rates for and predisposing factors to fractures occurring in Thoroughbred racing that have been published in peer reviewed journals are documented. The potential for currently available techniques to identify horses at increased risk for fracture is discussed on the bases of principles, practicalities, advantages, disadvantages and current data. All are reviewed in light of justifiable decision making and importance of fractures to horseracing's social license.

Evaluation of Quantitative Dual-Energy Computed Tomography Parameters for Differentiation of Parotid Gland Tumors

RATIONALE AND OBJECTIVES

To assess the diagnostic performance of quantitative parameters from dual-energy CT (DECT) in differentiating parotid gland tumors (PGTs).

MATERIALS AND METHODS

101 patients with 108 pathologically proved PGTs were enrolled and classified into four groups: pleomorphic adenomas (PAs), warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). Conventional CT attenuation and DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), electron density (Rho), double energy index (DEI), and the slope of the spectral Hounsfield unit curve (λHU), were obtained and compared between benign tumors (BTs) and MTs, and further compared among the four subgroups. Logistic regression analysis was used to assess the independent parameters and the receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance.

RESULTS

Attenuation, Zeff, DEI, IC, NIC, and λHU in the arterial phase (AP) and venous phase (VP) were higher in MTs than in BTs (p < 0.001-0.047). λHU in VP and Zeff in AP were independent predictors with an area under the curve (AUC) of 0.84 after the combination. Furthermore, attenuation, Zeff, DEI, IC, NIC, and λHU in the AP and VP of MTs were higher than those of PAs (p < 0.001-0.047). Zeff and NIC in AP and λHU in VP were independent predictors with an AUC of 0.93 after the combination. Attenuation and Rho in the precontrast phase; attenuation, Rho, Zeff, DEI, IC, NIC, and λHU in AP; and the Rho in the VP of PAs were lower than those of WTs (p < 0.001-0.03). Rho in the precontrast phase and attenuation in AP were independent predictors with an AUC of 0.89 after the combination. MTs demonstrated higher Zeff, DEI, IC, NIC, and λHU in VP and lower Rho in the precontrast phase compared with WTs (p < 0.001-0.04); but no independent predictors were found.

CONCLUSION

DECT quantitative parameters can help to differentiate PGTs.

Vertebral and Femoral Bone Mineral Density (BMD) Assessment with Dual-Energy CT versus DXA Scan in Postmenopausal Females

This study aimed to demonstrate the potential role of dual-energy CT in assessing bone mineral density (BMD) using hydroxyapatite-fat material pairing in postmenopausal women. A retrospective study was conducted on 51 postmenopausal female patients who underwent DXA and DECT examinations for other clinical reasons. DECT images were acquired with spectral imaging using a 256-slice system. These images were processed and visualized using a HAP-fat material pair. Statistical analysis was performed using the Bland-Altman method to assess the agreement between DXA and DECT HAP-fat measurements. Mean BMD, vertebral, and femoral T-scores were obtained. For vertebral analysis, the Bland-Altman plot showed an inverse correlation (R2: -0.042; RMSE: 0.690) between T-scores and DECT HAP-fat values for measurements from L1 to L4, while a good linear correlation (R2: 0.341; RMSE: 0.589) was found for measurements at the femoral neck. In conclusion, we demonstrate the enhanced importance of BMD calculation through DECT, finding a statistically significant correlation only at the femoral neck where BMD results do not seem to be influenced by the overlap of the measurements on cortical and trabecular bone. This outcome could be beneficial in the future by reducing radiation exposure for patients already undergoing follow-up for chronic conditions.

Identification of a small thrombus in the left ventricle identified on iodine maps derived from dual-source photon-counting detector CT

Transthoracic echocardiography is the main imaging modality to diagnose left ventricular thrombus (LVT), but its efficacy in certain cases is suboptimal. We report a patient in whom an LVT, initially unidentified by transthoracic echocardiography, was successfully diagnosed with iodine maps derived from dual-source photon-counting detector CT (DS-PCD-CT). The 64-year-old male was admitted to our institution following myocardial infarction. Although TTE failed to detect this small LVT, iodine maps derived from CT angiography (which was conducted to evaluate the coronary artery stenosis) revealed its presence. Iodine maps derived from DS-PCD-CT collecting data with high temporal resolution are beneficial to diagnose LVTs.

Spectral performance evaluation of a second-generation spectral detector CT

PURPOSE

The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities.

METHODS

A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70 keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150 keV, and root mean square error (RMSE) for adipose and iron content was reported.

RESULTS

Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70 keV images demonstrated reduced dependence compared to conventional images for phantom size (1 vs. 27 HU) and acquisition parameters, particularly tube voltage (4 vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44 mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49 ± 1.76% and 1.67 ± 0.84 mg/mL for adipose and iron content, respectively.

CONCLUSION

The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Characterization of Normal Bone in the Equine Distal Limb with Effective Atomic Number and Electron Density Determined with Single-Source Dual Energy and Detector-Based Spectral Computed Tomography

Single-source dual energy (SSDECT) and detector-based spectral computed tomography (DBSCT) are emerging technologies allowing the interrogation of materials that have different attenuation properties at different energies. Both technologies enable the calculation of effective atomic number (EAN), an index to determine tissue composition, and electron density (ED), which is assumed to be associated with cellularity in tissues. In the present prospective observational study, EAN and ED values were determined for 16 zones in normal subchondral and trabecular bone of 37 equine cadaver limbs. Using both technologies, the following findings were obtained: 1. palmar/plantar EAN zone values in the fetlock increased significantly with increasing age of the horse; 2. all EAN and ED values were significantly lower in the trabecular bone than in the subchondral bone of all phalanges; 3. in the distal phalanx and navicular bone, most EAN and ED values were significantly lower compared to the proximal and middle phalanx; and 4. some EAN and ED values were significantly different between front and hind limbs. Several EAN and ED values significantly differed between SSDECT and DBSCT. The reported EAN and ED values in the subchondral and trabecular bone of the equine distal limb may serve as preliminary reference values and aid future evaluation and classification of diseases.

Potential of Dual-Energy CT-Based Collagen Maps for the Assessment of Disk Degeneration in the Lumbar Spine

RATIONALE AND OBJECTIVES

Lumbar disk degeneration is a common condition contributing significantly to back pain. The objective of the study was to evaluate the potential of dual-energy CT (DECT)-derived collagen maps for the assessment of lumbar disk degeneration.

PATIENTS AND METHODS

We conducted a retrospective analysis of 127 patients who underwent dual-source DECT and MRI of the lumbar spine between 07/2019 and 10/2022. The level of lumbar disk degeneration was categorized by three radiologists as follows: no/mild (Pfirrmann 1&2), moderate (Pfirrmann 3&4), and severe (Pfirrmann 5). Recall (sensitivity) and accuracy of DECT collagen maps were calculated. Intraclass correlation coefficient (ICC) was used to evaluate inter-reader reliability. Subjective evaluations were performed using 5-point Likert scales for diagnostic confidence and image quality.

RESULTS

We evaluated a total of 762 intervertebral disks from 127 patients (median age, 69.7 (range, 23.0-93.7), female, 56). MRI identified 230 non/mildly degenerated disks (30.2%), 484 moderately degenerated disks (63.5%), and 48 severely degenerated disks (6.3%). DECT collagen maps yielded an overall accuracy of 85.5% (1955/2286). Recall (sensitivity) was 79.3% (547/690) for the detection of no/mild lumbar disk degeneration, 88.7% (1288/1452) for the detection of moderate disk degeneration, and 83.3% (120/144) for the detection of severe disk degeneration (ICC=0.9). Subjective evaluations of DECT collagen maps showed high diagnostic confidence (median 4) and good image quality (median 4).

CONCLUSION

The use of DECT collagen maps to distinguish different stages of lumbar disk degeneration may have clinical significance in the early diagnosis of disk-related pathologies in patients with contraindications for MRI or in cases of unavailability of MRI.

Application of Dual-Layer Spectral-Detector Computed Tomography Angiography in Identifying Symptomatic Carotid Atherosclerosis: A Prospective Observational Study

BACKGROUND

Dual-layer spectral-detector dual-energy computed tomography angiography (DLCTA) can distinguish components of carotid plaques. Data on identifying symptomatic carotid plaques in patients using DLCTA are not available.

METHODS AND RESULTS

In this prospective observational study, patients with carotid plaques were enrolled and received DLCTA. The attenuation for both polyenergetic image and virtual monoenergetic images (40, 70, 100, and 140 keV), as well as Z-effective value, were recorded in the noncalcified regions of plaques. Logistic regression models were used to assess the association between attenuations of DLCTA and the presence of symptomatic carotid plaques. In total, 100 participants (mean±SD age, 64.37±8.31 years; 82.0% were men) were included, and 36% of the cases were identified with the symptomatic group. DLCTA parameters were different between 2 groups (symptomatic versus asymptomatic: computed tomography [CT] 40 keV, 152.63 [interquartile range (IQR), 70.22-259.78] versus 256.78 [IQR, 150.34-408.13]; CT 70 keV, 81.28 [IQR, 50.13-119.33] versus 108.87 [IQR, 77.01-165.88]; slope40-140 keV, 0.91 [IQR, 0.35-1.87] versus 1.92 [IQR, 0.96-3.00]; Z-effective value, 7.92 [IQR, 7.53-8.46] versus 8.41 [IQR, 7.94-8.92]), whereas no difference was found in conventional polyenergetic images. The risk of symptomatic plaque was lower in the highest tertiles of attenuations in CT 40 keV (adjusted odds ratio [OR], 0.243 [95% CI, 0.078-0.754]), CT 70 keV (adjusted OR, 0.313 [95% CI, 0.104-0.940]), Z-effective values (adjusted OR, 0.138 [95% CI, 0.039-0.490]), and slope40-140 keV (adjusted OR, 0.157 [95% CI, 0.046-0.539]), with all P values and P trends <0.05. The areas under the curve for CT 40 keV, CT 70 keV, slope 40 to 140 keV, and Z-effective values were 0.64, 0.61, 0.64, and 0.63, respectively.

CONCLUSIONS

Parameters of DLCTA might help assist in distinguishing symptomatic carotid plaques. Further studies with a larger sample size may address the overlap and improve the diagnostic accuracy.

[Visualization of Borderline Coronary Artery Lesions by CT Angiography and Coronary Artery Disease Reporting and Data System]

Coronary artery disease (CAD) narrows vessel lumens at the sites of atherosclerosis, increasing the risk of myocardial ischemia or infarction. Early and accurate diagnosis of CAD is crucial to significantly improve prognosis and management. CT angiography (CTA) is a noninvasive imaging technique that enables assessment of vascular structure and stenosis with high resolution and contrast. Coronary CTA is useful in the diagnosis of CAD. Recently, the CAD-reporting and data system (CAD-RADS), a diagnostic classification system based on coronary CTA, has been developed to improve intervention efficacy in patients suspected of CAD. While the CAD-RAD is based on CTA, it includes borderline categories where interpreting the coronary artery status solely based on CTA findings may be challenging. This review introduces CTA findings that fall within the CAD-RADS categories that necessitate additional tests to decide to perform invasive coronary angiography and discusses appropriate management strategies.

Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging

Objective.Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourqueet al(2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material.Approach.The method decomposes materials into their effective atomic number (Zeff) and electron density relative to water (ρe). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with knownρevalues and elemental compositions. TheoreticalZeffvalues were found for the appropriate energy ranges using the elemental composition of the materials.Zeffvaried slightly with energy but was considered a systematic error. Anex vivobovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent.Main results.The mean root mean squared percent errors on the extractedZeffandρefor PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in theex vivobovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from theex vivotissue sample with K-edge imaging.Significance.PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.

Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning

BACKGROUND

Lymphovascular invasion (LVI) and perineural invasion (PNI) are important prognostic factors for gastric cancer (GC) that indicate an increased risk of metastasis and poor outcomes. Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment decisions. However, prior models using conventional computed tomography (CT) images to predict LVI or PNI separately have had limited accuracy. Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion. We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients.

AIM

To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately.

METHODS

This study used a retrospective dataset involving 257 GC patients (training cohort, n = 172; validation cohort, n = 85). First, several clinical indicators, including serum tumor markers, CT-TN stages and CT-detected extramural vein invasion (CT-EMVI), were extracted, as were quantitative spectral CT parameters from the delineated tumor regions. Next, a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters. A logistic regression (LR)-based nomogram model was subsequently constructed to predict LVI/PNI status, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

In both the training and validation cohorts, CT T3-4 stage, CT-N positive status, and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant (P < 0.05). LR analysis of the training group showed preoperative CT-T stage, CT-EMVI, single-energy CT values of 70 keV of venous phase (VP-70 keV), and the ratio of standardized iodine concentration of equilibrium phase (EP-NIC) were independent influencing factors. The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824, respectively, which were slightly greater than those of CT-T and CT-EMVI (AUC = 0.793, 0.762). The nomogram combining CT-T stage, CT-EMVI, VP-70 keV and EP-NIC yielded AUCs of 0.918 (0.866-0.954) and 0.874 (0.784-0.936) in the training and validation cohorts, which are significantly higher than using each of single independent factors (P < 0.05).

CONCLUSION

The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC, with accuracy boosted by integrating clinical markers.

Differentiation of Hamartomas and Malignant Lung Tumors in Single-Phased Dual-Energy Computed Tomography

This study investigated the efficacy of single-phase dual-energy CT (DECT) in differentiating pulmonary hamartomas from malignant lung lesions using virtual non-contrast (VNC), iodine, and fat quantification. Forty-six patients with 47 pulmonary lesions (mean age: 65.2 ± 12.1 years; hamartomas-to-malignant lesions = 22:25; male: 67%) underwent portal venous DECT using histology, PET-CT and follow-up CTs as a reference. Quantitative parameters such as VNC, fat fraction, iodine density and CT mixed values were statistically analyzed. Significant differences were found in fat fractions (hamartomas: 48.9%; malignancies: 22.9%; p ≤ 0.0001) and VNC HU values (hamartomas: -20.5 HU; malignancies: 17.8 HU; p ≤ 0.0001), with hamartomas having higher fat content and lower VNC HU values than malignancies. CT mixed values also differed significantly (p ≤ 0.0001), but iodine density showed no significant differences. ROC analysis favored the fat fraction (AUC = 96.4%; sensitivity: 100%) over the VNC, CT mixed value and iodine density for differentiation. The study concludes that the DECT-based fat fraction is superior to the single-energy CT in differentiating between incidental pulmonary hamartomas and malignant lesions, while post-contrast iodine density is ineffective for differentiation.

Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review

The accurate and timely assessment of lymph node involvement is paramount in the management of patients with malignant tumors, owing to its direct correlation with cancer staging, therapeutic strategy formulation, and prognostication. Dual-energy computed tomography (DECT), as a burgeoning imaging modality, has shown promising results in the diagnosis and prediction of preoperative metastatic lymph nodes in recent years. This article aims to explore the application of DECT in identifying metastatic lymph nodes (LNs) across various cancer types, including but not limited to thyroid carcinoma (focusing on papillary thyroid carcinoma), lung cancer, and colorectal cancer. Through this narrative review, we aim to elucidate the clinical relevance and utility of DECT in the detection and predictive assessment of lymph node metastasis in malignant tumors, thereby contributing to the broader academic discourse in oncologic radiology and diagnostic precision.

Low-dose versus conventional CT urography using dual-source CT with different time-current product values and the same tube voltage: image quality and diagnostic performance in various diagnoses

OBJECTIVES

To compare the image quality and diagnostic performance of low-dose CT urography to that of concurrently acquired conventional CT using dual-source CT.

METHODS

This retrospective study included 357 consecutive CT urograms performed by third-generation dual-source CT in a single institution between April 2020 and August 2021. Two-phase CT images (unenhanced phase, excretory phase with split bolus) were obtained with two different tube current-time products (280 mAs for the conventional-dose protocol and 70 mAs for the low-dose protocol) and the same tube voltage (90 kVp) for the two X-ray tubes. Iterative reconstruction was applied for both protocols. Two radiologists independently performed quantitative and qualitative image quality analysis and made diagnoses. The correlation between the noise level or the effective radiation dose and the patients' body weight was evaluated.

RESULTS

Significantly higher noise levels resulting in a significantly lower liver signal-to-noise ratio and contrast-to-noise ratio were noted in low-dose images compared to conventional images (P < .001). Qualitative analysis by both radiologists showed significantly lower image quality in low-dose CT than in conventional CT images (P < .001). Patient's body weight was positively correlated with noise and effective radiation dose (P < .001). Diagnostic performance for various diseases, including urolithiasis, inflammation, and mass, was not different between the two protocols.

CONCLUSIONS

Despite inferior image quality, low-dose CT urography with 70 mAs and 90 kVp and iterative reconstruction demonstrated diagnostic performance equivalent to that of conventional CT for identifying various diseases of the urinary tract.

ADVANCES IN KNOWLEDGE

Low-dose CT (25% radiation dose) with low tube current demonstrated diagnostic performance comparable to that of conventional CT for a variety of urinary tract diseases.

Thoracic Applications of Spectral CT Scan

TOPIC IMPORTANCE

Thoracic imaging with CT scan has become an essential component in the evaluation of respiratory and thoracic diseases. Providers have historically used conventional single-energy CT; however, prevalence of dual-energy CT (DECT) is increasing, and as such, it is important for thoracic physicians to recognize the utility and limitations of this technology.

REVIEW FINDINGS

The technical aspects of DECT are presented, and practical approaches to using DECT are provided. Imaging at multiple energy spectra allows for postprocessing of the data and the possibility of creating multiple distinct image reconstructions based on the clinical question being asked. The data regarding utility of DECT in pulmonary vascular disorders, ventilatory defects, and thoracic oncology are presented. A pictorial essay is provided to give examples of the strengths associated with DECT.

SUMMARY

DECT has been most heavily studied in chronic thromboembolic pulmonary hypertension; however, it is increasingly being used across a wide spectrum of thoracic diseases. DECT combines morphologic and functional assessments in a single imaging acquisition, providing clinicians with a powerful diagnostic tool. Its role in the evaluation and treatment of thoracic diseases will likely continue to expand in the coming years as clinicians become more experienced with the technology.

Atherosclerotic plaque features relevant to rupture-risk detected by clinical photon-counting CT ex vivo: a proof-of-concept study

BACKGROUND

To identify subjects with rupture-prone atherosclerotic plaques before thrombotic events occur is an unmet clinical need. Thus, this proof-of-concept study aims to determine which rupture-prone plaque features can be detected using clinically available photon-counting computed tomography (PCCT).

METHODS

In this retrospective study, advanced atherosclerotic plaques (ex vivo, paraffin-embedded) from the Carotid Plaque Imaging Project were scanned by PCCT with reconstructed energy levels (45, 70, 120, 190 keV). Density in HU was measured in 97 regions of interest (ROIs) representing rupture-prone plaque features as demonstrated by histopathology (thrombus, lipid core, necrosis, fibrosis, intraplaque haemorrhage, calcium). The relationship between HU and energy was then assessed using a mixed-effects model for each plaque feature.

RESULTS

Plaques from five men (age 79 ± 8 [mean ± standard deviation]) were included in the study. Comparing differences in coefficients (b1diff) of matched ROIs on plaque images obtained by PCCT and histology confirmed that calcium was distinguishable from all other analysed features. Of greater novelty, additional rupture-prone plaque features proved discernible from each other, particularly when comparing haemorrhage with fibrous cap (p = 0.017), lipids (p = 0.003) and necrosis (p = 0.004) and thrombus compared to fibrosis (p = 0.048), fibrous cap (p = 0.028), lipids (p = 0.015) and necrosis (p = 0.017).

CONCLUSIONS

Clinically available PCCT detects not only calcification, but also other rupture-prone features of human carotid plaques ex vivo.

RELEVANCE STATEMENT

Improved atherosclerotic plaque characterisation by photon-counting CT provides the ability to distinguish not only calcium, but also rupture-prone plaque features such as haemorrhage and thrombus. This may potentially improve monitoring and risk stratification of atherosclerotic patients in order to prevent strokes.

KEY POINTS

• CT of atherosclerotic plaques mainly detects calcium. • Many components, such as intra-plaque haemorrhage and lipids, determine increased plaque rupture risk. • Ex vivo carotid plaque photon-counting CT distinguishes haemorrhage and thrombus. • Improved plaque photon-counting CT evaluation may refine risk stratification accuracy to prevent strokes.

Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography

Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality assessment, treatment response assessment and image enhancement. However, their integration into the clinical workflow has been slow due to the lack of a consensus on data quality, benchmarked robust implementation, and consensus-based guidelines to ensure standardization and generalization. Contrast-enhanced mammography (CEM) has improved sensitivity and specificity compared to current standards of breast cancer diagnostic imaging i.e., mammography (MG) and/or conventional ultrasound (US), with comparable accuracy to MRI (current diagnostic imaging benchmark), but at a much lower cost and higher throughput. This makes CEM an excellent tool for widespread breast lesion characterization for all women, including underserved and minority women. Underlining the critical need for early detection and accurate diagnosis of breast cancer, this review examines the limitations of conventional approaches and reveals how AI can help overcome them. The Methodical approaches, such as image processing, feature extraction, quantitative analysis, lesion classification, lesion segmentation, integration with clinical data, early detection, and screening support have been carefully analysed in recent studies addressing breast cancer detection and diagnosis. Recent guidelines described by Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to establish a robust framework for rigorous evaluation and surveying has inspired the current review criteria.

Thyroid nodule characterization using Spectral Detector Computed Tomography (SDCT) in comparison to ultrasound

OBJECTIVE

To characterize thyroid nodules seen on Spectral Detector computed tomography (SDCT) in respect to their Thyroid Imaging Reporting and Data System (TI-RADS) category on Ultrasound (US).

METHODS

We included patients that underwent US examination for the evaluation of thyroid nodules and contrast-enhanced SDCT examination of the neck/thorax, between the years 2018-2020. The SDCT and US were performed within 6 months of each other. Only patients with a visible thyroid nodule on SDCT were included. Attenuation measurements of the nodules in Hounsfield units (HU) were performed on the conventional CT images, virtual non-contrast (VNC) images and virtual monoenergetic images of 40 keV and 100 keV. The Iodine concentration, spectral slope and enhancement estimation results of the nodules were measured. We compared the spectral results between two groups of nodules, according to the US report: TI-RADS 2-3 and TI-RADS 4-5 groups.

RESULTS

Thirty-eight nodules were included in the study, 22 nodules in the TI-RADS 2-3 group and 16 in the TI-RADS 4-5 group. The nodules of the TI-RADS 4-5 group had significantly higher Iodine concentration measurement, 4.6 ± 1.8 mg/ml, compared to 2.3 ± 1.2 mg/ml in the TI-RADS 2-3 group; significantly higher estimated enhancement, 3.9 ± 1.5, compared to 2.2 ± 0.7; and significantly higher calculated spectral slope, 5.6 ± 2.2 compared to 2.9 ± 1.5 (p < 0.001).

CONCLUSION

Spectral results of SDCT may assist in differentiating intermediate-high risk (TI-RADS 4-5) from low risk (TI-RADS 2-3) thyroid nodules.

ADVANCES IN KNOWLEDGE

SDCT offers additional information for the characterization of thyroid nodules.

Clinical value of dual-energy CT for predicting occult metastasis in central neck lymph nodes of papillary thyroid carcinoma

OBJECTIVES

To predict the probability of occult lymph node metastasis (OLNM) in the central cervical by analyzing the dual-energy computed tomography (DECT) parameters derived from papillary thyroid carcinoma (PTC).

METHODS

Data were retrospectively collected from patients with pathologically confirmed PTC who underwent arterial and venous phases of enhanced DECT with concurrent central neck lymph node dissection (CLND). Three clinical features, three shape-related features, and twenty-six DECT-derived parameters were measured. The univariate and multivariate analyses were applied to select the relevant parameters and develop the nomogram.

RESULTS

A total 140 cases with negative diagnosis of cervical central lymph node metastases by preoperative evaluation were included, among which 88 patients with metastasis (OLNM +) and 52 patients without metastasis (OLNM -) were finally confirmed by pathology. (1) Anteroposterior/transverse diameter ratio (A/T) derived from the PTC focus had significant difference between the OLNM + and OLNM - groups (p < 0.05). (2) In the arterial phase, iodine concentration (ICarterial), normalized iodine concentration (NICarterial), effective atomic number (Zeff-arterial), electron density (EDarterial), and slope of energy curve (karterial) from PTC focus showed significant difference (all p < 0.05) between the two groups. In the venous phase, only the CT value under the 40 keV (HU40keVvenous) had differences (p < 0.05). (3) The nomogram was produced to predict the probability of OLNM, and the AUC, sensitivity, and specificity in the training and test cohort were 0.830, 75.0%, 76.9%, and 0.829, 65.9%, 84.6%, respectively.

CONCLUSIONS

DECT parameters combined with shape-related feature derived from PTC might be used as predictors of OLNM in the central neck.

CLINICAL RELEVANCE STATEMENT

Preoperative imaging evaluation combining shape-related features and dual-energy CT parameters could serve as a reference to discern occult lymph node metastasis in central neck during the surgically planning of papillary thyroid carcinoma.

KEY POINTS

• Papillary thyroid carcinoma (PTC) patients may have occult lymph node metastasis (OLNM) in the central neck, which is extremely difficult to find by preoperative imaging examination. • Dual-energy CT quantitative evaluation has higher accuracy than conventional CT and can predicting OLNM in the central neck of PTC. • Dual-energy CT quantitative parameters and morphology of PTC can serve as a useful tool in predicting OLNM in the central neck, and as a guide for personalized treatment.

Performance evaluation of quantitative material decomposition in slow kVp switching dual-energy CT

BACKGROUND

Slow kVp switching technique is an important approach to realize dual-energy CT (DECT) imaging, but its performance has not been thoroughly investigated yet.

OBJECTIVE

This study aims at comparing and evaluating the DECT imaging performance of different slow kVp switching protocols, and thus helps determining the optimal system settings.

METHODS

To investigate the impact of energy separation, two different beam filtration schemes are compared: the stationary beam filtration and dynamic beam filtration. Moreover, uniform tube voltage modulation and weighted tube voltage modulation are compared along with various modulation frequencies. A model-based direct decomposition algorithm is employed to generate the water and iodine material bases. Both numerical and physical experiments are conducted to verify the slow kVp switching DECT imaging performance.

RESULTS

Numerical and experimental results demonstrate that the material decomposition is less sensitive to beam filtration, voltage modulation type and modulation frequency. As a result, robust material-specific quantitative decomposition can be achieved in slow kVp switching DECT imaging.

CONCLUSIONS

Quantitative DECT imaging can be implemented with slow kVp switching under a variety of system settings.

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

INTRODUCTION

No study has rigorously compared the performances of iodine quantification on recent CT systems employing different emission-based technologies, depending on the manufacturers and models.

METHODS

A specific bespoke phantom was used for this study, with 12 known concentrations of iodinated contrast agent: 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 10.0, 15.0, 20.0, 30.0 and 50.0 mg/mL. Three different dual-energy scanners were tested: one system using dual-source acquisition (CT#1) and two systems using Fast kilovolt-peak switching technology ± artificial intelligence (AI) reconstruction methods (CT#2 and #3) from two different manufacturers. For each system, helical scans were performed following recommended clinical protocols. Four acquisitions were performed per iodine concentration (mg/mL), and measurements were made on iodine-maps using ROIs. Mean measured values were compared to the known concentrations, and the absolute quantification error (AQE) and the relative percentage error (RPE) were used to compare the performances of each CT.

RESULTS

The accuracy of the obtained measurements varied depending on the studied model but not on the acquisition mode (dual-source vs kVp switch ± AI). The quantification was more precise at high concentrations. RPE values were below 10 % with CT#2 (kVp switch) and below 25 % with CT#1 (dual-source), but were significantly higher with CT#3 (kVp switch + AI), exceeding 50 % at low concentrations (<3 mg/mL).

CONCLUSIONS

With the help of a phantom, we identified variability in the results accuracy depending on the CT model, with sometimes significant deviation. Considering the performances of the different DECT technologies in iodine mapping, dual-source (CT#1) and kVp switch (CT#2) technologies appear more accurate than kVp switch technology combined with deep-learning-based reconstruction (CT#3) especially at low concentrations (<3 mg/mL).

IMPLICATIONS FOR PRACTICE

As the primary and daily user of medical imaging devices, the radiographer role is to be attentive to the performance of imaging systems, particularly when performing quantitative acquisitions like iodine-quantification. In CT quantitative imaging (iodine map), it's essential for radiographers to consider their CT systems as measuring tools, and to be aware of their accuracies and limits.

Review of Clinical Applications of Dual-Energy CT in Patients after Endovascular Aortic Repair

Abdominal aortic aneurysms (AAAs) are a significant cause of mortality in developed countries. Endovascular aneurysm repair (EVAR) is currently the leading treatment method for AAAs. Due to the high sensitivity and specificity of post-EVAR complication detection, CT angiography (CTA) is the reference method for imaging surveillance in patients after EVAR. Many studies have shown the advantages of dual-energy CT (DECT) over standard polyenergetic CTA in vascular applications. In this article, the authors briefly discuss the technical principles and summarize the current body of literature regarding dual-energy computed tomography angiography (DECTA) in patients after EVAR. The authors point out the most useful applications of DECTA in this group of patients and its advantages over conventional CTA. To conduct this review, a search was performed using the PubMed, Google Scholar, and Web of Science databases.

Material decomposition using dual-energy CT with unsupervised learning

Material decomposition (MD) is an application of dual-energy computed tomography (DECT) that decomposes DECT images into specific material images. However, the direct inversion method used in MD often amplifies noise in the decomposed material images, resulting in lower image quality. To address this issue, we propose an image-domain MD method based on the concept of deep image prior (DIP). DIP is an unsupervised learning method that can perform different tasks without using a large training dataset with known targets (i.e., basis material images). We retrospectively recruited patients who underwent non-contrast brain DECT scans and investigated the feasibility of using the proposed DIP-based method to decompose DECT images into two (i.e., bone and soft tissue) and three (i.e., bone, soft tissue, and fat) basis materials. We evaluated the decomposed material images in terms of signal-to-noise ratio (SNR) and modulation transfer function (MTF). The proposed DIP-based method showed greater improvement in SNR in the decomposed soft-tissue images compared to the direct inversion method and the iterative method. Moreover, the proposed method produced similar MTF curves in both two- and three-material decompositions. Additionally, the proposed DIP-based method demonstrated better separation ability than the other two studied methods in the case of three-material decomposition. Our results suggest that the proposed DIP-based method is capable of unsupervisedly generating high-quality basis material images from DECT images.

Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses

RATIONALE AND OBJECTIVES

To investigate the diagnostic value of radiomics features and dual-source dual-energy CT (DECT) based material decomposition in differentiating low-risk thymomas, high-risk thymomas, and thymic carcinomas.

MATERIALS AND METHODS

This retrospective study included 32 patients (16 males, mean age 66 ± 14 years) with pathologically confirmed thymic masses who underwent contrast-enhanced DECT between 10/2014 and 01/2023. Two experienced readers evaluated all patients regarding conventional radiomics features, as well as DECT-based features, including attenuation (HU), iodine density (mg/mL), and fat fraction (%). Data comparisons were performed using analysis of variance and chi-square statistic tests. Receiver operating characteristic curve analysis and Cox-regression tests were used to discriminate between low-risk/high-risk thymomas and thymic carcinomas.

RESULTS

Of the 32 thymic tumors, 12 (38%) were low-risk thymomas, 11 (34%) were high-risk thymomas, and 9 (28%) were thymic carcinomas. Values differed significantly between low-risk thymoma, high-risk thymoma, and thymic carcinoma regarding DECT-based features (p ≤ 0.023) and 30 radiomics features (p ≤ 0.037). The area under the curve to differentiate between low-risk/high-risk thymomas and thymic cancer was 0.998 (95% CI, 0.915-1.000; p < 0.001) for the combination of DECT imaging parameters and radiomics features, yielding a sensitivity of 100% and specificity of 96%. During a follow-up of 60 months (IQR, 35-60 months), the multiparametric approach including radiomics features, DECT parameters, and clinical parameters showed an excellent prognostic power to predict all-cause mortality (c-index = 0.978 [95% CI, 0.958-0.998], p = 0.003).

CONCLUSION

A multiparametric approach including conventional radiomics features and DECT-based features facilitates accurate, non-invasive discrimination between low-risk/high-risk thymomas and thymic carcinomas.

Comparison of image quality, contrast administration, and radiation doses in pediatric abdominal dual-layer detector dual-energy CT using propensity score matching analysis

PURPOSE

To compare the image quality, contrast administration, and radiation dose between single-energy CT (SECT) and dual-energy CT (DECT) in pediatric patients.

METHODS

From March to December 2021, children who underwent abdominal SECT or DECT were retrospectively included in this study. The DECT group received 10-30 % less contrast than the routine dose. CT images were obtained at hepatic venous phase using a routine reconstruction method (iDose4). DECT scans were additionally reconstructed with a virtual monoenergetic image (VMI) at 40 and 65 keV. Quantitative image evaluations compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the liver, portal vein, and pancreas. Qualitative analysis assessed degree of contrast enhancement, lesion or organ conspicuity, image noise, artificiality, and overall image quality.

RESULTS

Among 318 patients, 112 (median age, 16 years; 56 in each group) were included after propensity score matching. Compared with the SECT group, DECT group with iDose4 demonstrated lower CNRs and SNRs, while VMI at 40 or 65 keV showed no significant difference. In qualitative analysis, iDose4 produced higher scores on artificiality, and VMI at 40 keV demonstrated superior contrast enhancement and lesion conspicuity in the DECT group. Overall image quality was higher with VMI 65 keV among the DECT patients, and there was no significant difference compared to SECT. The volume CT dose index (CTDIvol) did not differ significantly between the two groups (median, 2.8 mGy vs. 2.9 mGy; p = 0.802). The injected contrast volume was reduced by 10 % in the DECT group.

CONCLUSION

Pediatric abdominal DECT with reduced contrast administration showed no significant differences in image quality and radiation dose compared to SECT.

Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses

BACKGROUND

To investigate the potential of radiomic features and dual-source dual-energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes.

METHODS

In this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast-enhanced DECT. Attenuation, radiomic features and DECT-derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi-square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses.

RESULTS

Of the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT-derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast-enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893-1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow-up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all-cause mortality (c-index = .8 [95% CI, .702-.890], p < .001).

CONCLUSIONS

A multiparametric approach combining radiomic features and DECT-derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum.

Dual-Energy Computed Tomography to Photon Counting Computed Tomography: Emerging Technological Innovations

Computed tomography (CT) has seen remarkable developments in the past several decades, radically transforming the role of imaging in day-to-day clinical practice. Dual-energy CT (DECT), an exciting innovation introduced in the early part of this century, has widened the scope of CT, opening new opportunities due to its ability to provide superior tissue characterization. The introduction of photon-counting CT (PCCT) heralds a paradigm shift in CT scanner technology representing another significant milestone in CT innovation. PCCT offers several advantages over DECT, such as improved spectral resolution, enhanced tissue characterization, reduced image artifacts, and improved image quality.

Segmental analysis of liver cirrhosis with different etiologies: a study based on iodine mixed imaging in port-venous phase

BACKGROUND

Computed tomography (CT) in port-venous phase can display the intra-hepatic vessels, and may provide the possibility for segment function evaluation for cirrhosis.

PURPOSE

To assess the value of iodine mixed imaging of dual-source dual-energy CT in port-venous phase in segmental evaluation of liver cirrhosis with different etiologies.

MATERIAL AND METHODS

Patients diagnosed with liver cirrhosis were enrolled. Patients without cirrhosis were included as a control group. Each patient underwent iodine-contrast enhanced multi-phase dual-energy CT scanning. Parameters were analyzed by SPSS, version 22.0, and Medcalc.

RESULTS

In total, 256 patients were investigated, including 114 Child-Pugh A, 51 Child-Pugh B, 41 Child-Pugh C and 50 control patients. Total iodine content (ICt)/body surface area (BSA) in the cirrhosis group was significantly lower than the control group (P < 0.05) and the standardized-iodine parameter (SI) of each segment decreased with cirrhosis progression. In Child-Pugh A and B, SI increased more significantly in the caudal and lateral segment in A (alcholism) than in the V (virus-related) and N (non-alcoholic steatohepatitis) groups (P < 0.001). ICt/BSA showed the best diagnosis power of cirrhosis with an area under the curve of 0.765, sensitivity of 76.0% and specificity of 71.8%.

CONCLUSION

Blood flow compensated in the left lateral and caudal lobe in the early stage of liver cirrhosis. The compensation in alcoholism in the middle and early stages is significantly higher than that of V and N cirrhosis. Iodine mixed imaging in portal phase may provide the possibility of an incremental value in segmented blood flow perfusion and functional evaluation of liver cirrhosis on a morphological basis.

What do we see when we do not see the bladder? Review of the main urinary diversion techniques and their complications

OBJECTIVE

To review the different types of urinary diversion surgeries (UDS) in order to recognize the expected findings in a postoperative study, using different imaging techniques. To recognize the main postoperative complications, both early and late.

CONCLUSION

UDS are surgical procedures whose purpose is to redirect urine flow after cystectomy, generally in an oncologic context. The imaging evaluation of urological surgeries is often a radiological challenge, with CT being the most commonly used image modality. Therefore, it is essential to know the main surgical techniques, the expected postoperative findings and the optimization of imaging techniques for early diagnosis and correct evaluation of postoperative complications.

Optimal combination periprosthetic vasculature visualization and metal artifact reduction by spectral computed tomography using virtual monoenergetic images in total hip arthroplasty

OBJECTIVES

To investigate the optimal parameters of spectral CT for preferably visualizing the periprosthetic vasculature and metal artifact reduction (MAR) in total hip arthroplasty (THA).

METHODS

A total of 34 THA of 30 patients were retrospectively included. Image reconstructions included conventional image (CI), CI combined with MAR (CIMAR), and virtual monoenergetic images (VMI) combined with MAR (VMIMAR) at 50-120 keV. The attenuation and standard deviation of the vessel and artifact, and the width of artifact were measured. Qualitative scoring was evaluated including the vascular contour, the extent of artifact, and overall diagnostic evaluation.

RESULTS

The attenuation, noise of the vessel and artifact, and the width of artifact decreased as the energy level increased (p < 0.001). The downtrend was relatively flat at 80-120 keV, and the vascular attenuation dropped to 200 HU at 90 keV. The qualitative rating of vascular contour was significantly higher at CIMAR (3.47) and VMIMAR 60-80 keV (2.82-3.65) compared with CI (2.03) (p ≤ 0.029), and the highest score occurred at 70 and 80 keV (3.65 and 3.56). The score of the extent of artifact was higher at VMIMAR 80 keV than CIMAR (3.53 VS 3.12, p = 0.003). The score of the overall diagnostic evaluation was higher at VMIMAR 70 and 80 keV (3.32 and 3.53, respectively) than CIMAR (3.12) (p ≤ 0.035).

CONCLUSION

Eighty kiloelectron volts on VMIMAR, providing satisfactorily reduced metal artifacts and improved vascular visualization, can be an optimal recommended parameter of spectrum CT for the assessment of periprosthetic vasculature in THA patients.

CRITICAL RELEVANCE STATEMENT

The metal artifact is gradually reducing with increasing energy level; however, the vascular visualization is worsening. The vascular visualization is terrible above 100 keV, while the vessel is disturbed by artifacts below 70 keV. The best performance is found at 80 keV.

KEY POINTS

• VMIMAR can provide both reduced metal artifacts and improved vascular visualization. • Eighty kiloelectron volts on VMIMAR performs best in vascular visualization of total hip arthroplasty patients. • Energy spectrum CT is recommended for routine use in patients with total hip arthroplasty.

Establishment of diagnostic reference levels in computed tomography in two large hospitals in Oman

This study aimed to estimate diagnostic reference levels (DRLs) for the most frequent computed tomography (CT) imaging examinations to monitor and better control radiation doses delivered to patients. Seven CT imaging examinations: Head, Chest, Chest High Resolution (CHR), Abdomen Pelvis (AP), Chest Abdomen Pelvis (CAP), Kidneys Ureters Bladder (KUB) and Cardiac, were considered. CT dosimetric quantities and patient demographics were collected from data storage systems. Local typical values for DRLs were calculated for CTDIvol (mGy), dose length product (DLP) (mGy·cm) and effective doses (mSv) were estimated for each examination. The calculated DRLs were given as (median CTDIvol (mGy):median DLP (mGy·cm)): Head: 39:657; Chest: 13:451; CHR: 6:228; AP: 12:578; CAP: 20:807; KUB: 7:315, and Cardiac: 2:31. Estimated effective doses for Head, Chest, CHR, AP, CAP, KUB and Cardiac were 1.3, 12.7, 6.3, 12.5, 18.1, 5.8 and 0.8 mSv, respectively. The estimated DRLs will act as guidance doses to prevent systematic excess of patient doses.

Impact of tin filter on the image quality of ultra-low dose chest CT: A phantom study on three CT systems

PURPOSE

The purpose of this study was to assess the impact of a tin filter on the image quality of ultra-low dose (ULD) chest computed tomography (CT) on three different CT systems.

MATERIALS AND METHODS

An image quality phantom was scanned on three CT systems including two split-filter dual-energy CT (SFCT-1 and SFCT-2) scanners and one dual-source CT scanner (DSCT). Acquisitions were performed with a volume CT dose index (CTDIvol) of 0.4 mGy, first at 100 kVp without tin filter (Sn), and second, at Sn100/Sn140 kVp, Sn100/Sn110/Sn120/Sn130/Sn140/Sn150 kVp and Sn100/Sn150 kVp for SFCT-1, SFCT-2 and DSCT respectively. Noise-power-spectrum and task-based transfer function were computed. The detectability index (d') was computed to model the detection of two chest lesions.

RESULTS

For DSCT and SFCT-1, noise magnitude values were higher with 100kVp than with Sn100 kVp and with Sn140 kVp or Sn150 kVp than with Sn100 kVp. For SFCT-2, noise magnitude increased from Sn110 kVp to Sn150 kVp and was higher at Sn100 kVp than at Sn110 kVp. For most kVp with the tin filter, the noise amplitude values were lower than those obtained at 100 kVp. For each CT system, noise texture and spatial resolution values were similar with 100 kVp and with all kVp used with a tin filter. For all simulated chest lesions, the highest d' values were obtained at Sn100 kVp for SFCT-1 and DSCT and at Sn110 kVp for SFCT-2.

CONCLUSION

For ULD chest CT protocols, the lowest noise magnitude and highest detectability values for simulated chest lesions are obtained with Sn100 kVp for the SFCT-1 and DSCT CT systems and at Sn110 kVp for SFCT-2.

Dual-Energy CT for Pediatric Thoracic Imaging: A Review

Dual-energy CT has expanded the potential of thoracic imaging in both children and adults. Data processing allows material- and energy-specific reconstructions, which improve material differentiation and tissue characterization compared with single-energy CT. Material-specific reconstructions include iodine, virtual unenhanced, perfusion blood volume, and lung vessel images, which can improve assessment of vascular, mediastinal, and parenchymal abnormalities. The energy-specific reconstruction algorithm allows virtual monoenergetic reconstructions, including low-energy images to increase iodine conspicuity and high-energy images to reduce beam-hardening and metal artifacts. This review highlights dual-energy CT principles, hardware, and postprocessing algorithms; the clinical applications of dual-energy CT; and the potential benefits of photon counting (the most recently introduced iteration of spectral imaging) in pediatric thoracic imaging.

Virtual unenhanced images derived from dual-energy computed tomography for assessing bone mineral density and detecting osteoporosis

Background

The early detection and treatment of osteoporosis can help prevent osteoporosis-related fractures, especially in patients who undergo enhanced computed tomography (CT) scans for disease diagnosis or evaluation of treatment outcomes. Although Hounsfield unit (HU) measurement of the vertebral body has been shown to have a strong positive correlation with bone mineral density (BMD), the contrast media will impact the CT value of the vertebral body and decrease the accuracy. This study is aimed to examine the distinctions in vertebral body CT attenuation measurement on true unenhanced (TUE) and virtual unenhanced (VUE) images generated from triphasic enhanced dual-energy CT (DECT) scans and to determine the feasibility of assessing BMD and detecting osteoporosis on VUE images as compared to quantitative CT (QCT).

Methods

A total of 235 patients underwent abdominal CT examinations that included unenhanced (with 120 kVp and Smart mA) and triphasic enhanced DECT scans. The BMD and CT attenuation values of the L1-L2 vertebrae were measured on TUE and VUE images reconstructed from the triphasic enhanced CT. The differences and associations between TUE and VUE generated from triphasic enhanced CT were analyzed. The diagnostic performances of HU measurements obtained from TUE and VUE images were evaluated using receiver operating characteristic curve.

Results

The BMD and HU measurements of the vertebrae showed good interobserver repeatability on both TUE and VUE images (all intercorrelation coefficients >0.92). The CT attenuation values of L1 and L2 and their average value showed no statistically significant difference among the triphasic VUE images (F=0.121, F=0.061, F=0.090; all P values >0.05) but were significantly lower than those obtained from the TUE images. HU measurements in both the TUE and triphasic VUE images, along with the reference BMD derived from QCT, demonstrated a strong positive correlation (rTUE =0.981, rVUEa =0.966, rVUEv =0.962, rVUEd =0.964; all P values <0.05), with excellent diagnostic performance for the diagnoses of osteoporosis and osteopenia (all areas under curve >0.95). The Bland-Altman scatter plot exhibited good agreement, as the deviations between the reference BMD and the calculated BMD were evenly distributed around 0.

Conclusions

Although the attenuation values of the vertebrae on the VUE images were underestimated compared to those on the TUE images, the HU measurement on VUE image was effective in assessing BMD and detecting osteoporosis and osteopenia with good diagnostic performance.

Impact of Phantom Size on Low-Energy Virtual Monoenergetic Images of Three Dual-Energy CT Platforms

The purpose of this study was to compare the quality of low-energy virtual monoenergetic images (VMIs) obtained with three Dual-Energy CT (DECT) platforms according to the phantom diameter. Three sections of the Mercury Phantom 4.0 were scanned on two generations of split-filter CTs (SFCT-1st and SFCT-2nd) and on one Dual-source CT (DSCT). The noise power spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were assessed on VMIs from 40 to 70 keV. The highest noise magnitude values were found with SFCT-1st and noise magnitude was higher with DSCT than with SFCT-2nd for 26 cm (10.2% ± 1.3%) and 31 cm (7.0% ± 2.5%), and the opposite for 36 cm (-4.2% ± 2.5%). The highest average NPS spatial frequencies and TTF values at 50% (f50) values were found with DSCT. For all energy levels, the f50 values were higher with SFCT-2nd than SFCT-1st for 26 cm (3.2% ± 0.4%) and the opposite for 31 cm (-6.9% ± 0.5%) and 36 cm (-5.6% ± 0.7%). The lowest d' values were found with SFCT-1st. For all energy levels, the d' values were lower with DSCT than with SFCT-2nd for 26 cm (-6.2% ± 0.7%), similar for 31 cm (-0.3% ± 1.9%) and higher for 36 cm (5.4% ± 2.7%). In conclusion, compared to SFCT-1st, SFCT-2nd exhibited a lower noise magnitude and higher detectability values. Compared with DSCT, SFCT-2nd had a lower noise magnitude and higher detectability for the 26 cm, but the opposite was true for the 36 cm.

Noninvasive assessment of significant liver fibrosis in rabbits by spectral CT parameters and texture analysis

PURPOSE

Noninvasive assessment of significant liver fibrosis in rabbits by spectral CT parameters and texture analysis.

MATERIALS AND METHODS

Thirty-three rabbits were randomly divided into 27 carbon tetrachloride-induced liver fibrosis group and 6 control group. Spectral CT contrast-enhanced scan was performed in batches, and the liver fibrosis was staged according to the histopathological results. The portal venous phase spectral CT parameters [70 keV CT value, normalized iodine concentration (NIC), spectral HU curve slope (λHU)] were measured, and MaZda texture analysis was performed on 70 keV monochrome images. Three dimensionality reduction methods and four statistical methods in B11 module were used to perform discriminant analysis and calculate misclassified rate (MCR), and ten texture features under the lowest combination of MCR were statistically analyzed. Receiver operating characteristic curve (ROC) was used to calculate the diagnostic performance of spectral parameters and texture features for significant liver fibrosis. Finally, the binary logistic regression was used to further screen independent predictors and establish model.

RESULTS

A total of 23 experimental rabbits and 6 control rabbits were included, of which 16 had significant liver fibrosis. Three spectral CT parameters with significant liver fibrosis were significantly lower than those of non-significant liver fibrosis (p < 0.05), and the AUC ranged from 0.846 to 0.913. The combination analysis of mutual information (MI) and nonlinear discriminant analysis (NDA) had the lowest MCR, which with 0%. In the filtered texture features, four were statistically significant and AUC > 0.5, ranges from 0.764 to 0.875. The logistic regression model showed that Perc.90% and NIC could be used as independent predictors, the overall prediction accuracy of the model was 89.7% and the AUC was 0.976.

CONCLUSION

Spectral CT parameters and texture features have high diagnostic value for predicting significant liver fibrosis in rabbits, and the combination of the two can improve its diagnostic efficiency.

A quantitative analysis of spectral computed tomography characteristics of osseous metastases

INTRODUCTION

Spectral detector computed tomography (SDCT) is a recent advancement that enables elemental material decomposition which could improve the detection of osseous metastases in the oncologic patient.

METHODS

Sixteen patients who underwent oncologic staging SDCT as well as WBBS with Technetium-99 m hydroxydiphosphonate (Tc99m HDP) were included in this retrospective study. A total of 50 osseous metastases were identified and confirmed on bone scintigraphy. Quantitative ROI-based measurements of each lesion and a similar region of normal bone were performed, and the acquired spectral data were used for comparison. These parameters included effective atomic number (Zeff ), electron density (%EDW) and calcium suppression (HU). Receiver operating characteristic (ROC) analysis was performed.

RESULTS

In comparison to normal bone, osseous metastases showed statistically significantly elevated values in effective atomic number, electron density and calcium suppression. ROC analysis demonstrated outstanding discrimination with area under the curve (AUC) values of 0.934 and 0.915 for effective atomic number and electron density, and excellent discrimination with an AUC value of 0.884 for calcium suppression. Threshold values of effective atomic number (Zeff ) >9.7, electron density >115% EDW and calcium suppression values >0 HU were demonstrated to be able to differentiate an osseous lesion from normal bone with a sensitivity of 82%, 82% and 84% and a specificity of 86%, 92% and 88% respectively.

CONCLUSION

Spectral analysis of osseous metastases demonstrated significantly elevated values in effective atomic number, electron density and calcium suppression as compared to normal bone which would be useful adjunct quantitative parameters in CT imaging to increase diagnostic confidence.

Quality of virtual-non-contrast phases derived from arterial and delayed phases of fast-kVp switching dual-energy CT in patients after endovascular aortic repair

Objective of this study is: to analyze CT numbers in arteries and endoleaks in true non-contrast (TNC) and virtual non-contrast phases derived from arterial (VNCa) and delayed (VNCd) phases of dual-energy CT (DECT) in patients after endovascular aneurysm repair (EVAR); to assess the impact of image noise on subjective image quality parameters and the degree of subtraction of calcifications; to calculate effective dose (ED) reduction following replacement of TNC with VNC. The study included 97 patients after EVAR procedure. An initial single-energy TNC acquisition was followed by two DECT acquisitions. CT numbers of TNC, VNCa, VNCd were analyzed statistically. VNCd images were assessed qualitatively. The mean densities in endoleaks were 46.19 HU in TNC, 51.24 HU in VNCa, 42.24 HU in VNCd. The differences between them were statistically significant (p < 0.05). The mean signal-to-noise ratio (SNR) measured in the aorta and endoleaks was highest in VNCa, lowest in TNC images. No correlation between image noise, the results of qualitative analysis of VNCd, and the degree of subtraction of calcifications was found. Omitting TNC led to mean 6.54 ± 1.63 (SD) mSv (23.28% of total examination) ED reduction. VNC images have a higher SNR compared to TNC images with significant differences in the CT numbers between the TNC and VNC reconstructions. Image noise has no impact on the subjective image quality and the degree of subtraction of calcifications in VNCd images. The findings show a high diagnostic value of VNC images and suggest that VNCd images are optimal in the assessment of endoleaks with possible substantial ED reduction.

Feasibility of photon-counting CT for femoroacetabular impingement syndrome evaluation: lower radiation dose and improved diagnostic confidence

OBJECTIVE

The feasibility of low-dose photon-counting detector (PCD) CT to measure alpha and acetabular version angles of femoroacetabular impingement (FAI).

MATERIAL AND METHODS

FAI patients undergoing an energy-integrating detector (EID) CT underwent an IRB-approved prospective ultra-high-resolution (UHR) PCD-CT between 5/2021 and 12/2021. PCD-CT was dose-matched to the EID-CT or acquired at 50% dose. Simulated 50% dose EID-CT images were generated. Two radiologists evaluated randomized EID-CT and PCD-CT images and measured alpha and acetabular version angles on axial image slices. Image quality (noise, artifacts, and visualization of cortex) and confidence in non-FAI pathology were rated on a 4-point scale (3 = adequate). Preference tests of standard dose PCD-CT, 50% dose PCD-CT, and 50% dose EID-CT relative to standard dose EID-CT were performed using Wilcoxon Rank test.

RESULTS

20 patients underwent standard dose EID-CT (~ CTDIvol, 4.5 mGy); 10 patients, standard dose PCD-CT (4.0 mGy); 10 patients, 50% PCD-CT (2.6 mGy). Standard dose EID-CT images were scored as adequate for diagnostic task in all categories (range 2.8-3.0). Standard dose PCD-CT images scored higher than the reference in all categories (range 3.5-4, p < 0.0033). Half-dose PCD-CT images also scored higher for noise and cortex visualization (p < 0.0033) and equivalent for artifacts and visualization of non-FAI pathology. Finally, simulated 50% EID-CT images scored lower in all categories (range 1.8-2.4, p < 0.0033).

CONCLUSIONS

Dose-matched PCD-CT is superior to EID-CT for alpha angle and acetabular version measurement in the work up of FAI. UHR-PCD-CT enables 50% radiation dose reduction compared to EID while remaining adequate for the imaging task.

Dual-Energy Computed Tomography in Stroke Imaging : Value of a New Image Acquisition Technique for Ischemia Detection after Mechanical Thrombectomy

OBJECTIVE

To assess if a new dual-energy computed tomography (DECT) technique enables an improved visualization of ischemic brain tissue after mechanical thrombectomy in acute stroke patients.

MATERIAL AND METHODS

The DECT head scans with a new sequential technique (TwinSpiral DECT) were performed in 41 patients with ischemic stroke after endovascular thrombectomy and were retrospectively included. Standard mixed and virtual non-contrast (VNC) images were reconstructed. Infarct visibility and image noise were assessed qualitatively by two readers using a 4-point Likert scale. Quantitative Hounsfield units (HU) were used to assess density differences of ischemic brain tissue versus healthy tissue on the non-affected contralateral hemisphere.

RESULTS

Infarct visibility was significantly better in VNC compared to mixed images for both readers R1 (VNC: median 1 (range 1-3), mixed: median 2 (range 1-4), p < 0.05) and R2 (VNC: median 2 (range 1-3), mixed: 2 (range 1-4), p < 0.05). Qualitative image noise was significantly higher in VNC compared to mixed images for both readers R1 (VNC: median 3, mixed: 2) and R2 (VNC: median 2, mixed: 1, p < 0.05, each). Mean HU were significantly different between the infarcted tissue and the reference healthy brain tissue on the contralateral hemisphere in VNC (infarct 24 ± 3) and mixed images (infarct 33 ± 5, p < 0.05, each). The mean HU difference between ischemia and reference in VNC images (mean 8 ± 3) was significantly higher (p < 0.05) compared to the mean HU difference in mixed images (mean 5 ± 4).

CONCLUSION

TwinSpiral DECT allows an improved qualitative and quantitative visualization of ischemic brain tissue in ischemic stroke patients after endovascular treatment.

Dual-energy CT iodine overlay improves efficiency of oral contrast leak assessment

BACKGROUND

Evaluation for gastrointestinal leak is a frequent imaging indication, and dual-energy computed tomography (DECT) with oral or rectally administered contrast can be used to improve efficiency and diagnostic confidence.

PURPOSE

To assess the value of the DECT iodine overlay (IO) reconstruction as a stand-alone image set compared to routine CT in assessing oral or rectal contrast leak from the gastrointestinal system.

MATERIAL AND METHODS

A blinded, retrospective audit study was performed by three readers who each interpreted 50 studies performed for assessment of oral or rectal contrast leak that were acquired using DECT. Each reader independently assessed both the routine CT images and the images of the reconstructed IO for contrast leak in random order with a six-week "wash-out period" between readings. Clinical follow-up provided the reference standard. Readers recorded the presence/absence of a leak, diagnostic confidence, image quality score, and interpretation time for each image set.

RESULTS

Pooled data for overall accuracy in identification of a leak increased from 0.81 (95% confidence interval [CI]=0.74-0.87) for routine CT to 0.91 (95% CI=0.85-0.95) with IO, and the area under the curve (AUC) was significantly higher for IO than routine CT (P = 0.015). Readers required significantly less time to interpret IO than routine CT (median improvement of 12.5 s per image using pooled data; P < 0.001) while maintaining diagnostic confidence and perceived image quality.

CONCLUSION

Use of DECT IO reconstructions for identification of oral or rectal contrast leak requires less time to interpret than routine CT with improved accuracy and maintained diagnostic confidence and perceived image quality.

Quantification of airway wall contrast enhancement on virtual monoenergetic images from spectral computed tomography

OBJECTIVES

Quantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition.

METHODS

For this cross-sectional retrospective study, 234 lung-healthy patients who underwent spectral CT in four different contrast phases (non-enhanced, pulmonary arterial, systemic arterial, and venous phase) were recruited. Virtual monoenergetic images were reconstructed from 40-160 keV, on which attenuations of segmented lung parenchyma and airway walls combined for 5th-10th subsegmental generations were assessed in Hounsfield Units (HU) by an in-house software. The spectral attenuation curve slope between 40 and 100 keV (λHU) was calculated.

RESULTS

Mean lung density was higher at 40 keV compared to that at 100 keV in all groups (p < 0.001). λHU of lung attenuation was significantly higher in the systemic (1.7 HU/keV) and pulmonary arterial phase (1.3 HU/keV) compared to that in the venous phase (0.5 HU/keV) and non-enhanced (0.2 HU/keV) spectral CT (p < 0.001). Wall thickness and wall attenuation were higher at 40 keV compared to those at 100 keV for the pulmonary and systemic arterial phase (p ≤ 0.001). λHU for wall attenuation was significantly higher in the pulmonary arterial (1.8 HU/keV) and systemic arterial (2.0 HU/keV) compared to that in the venous (0.7 HU/keV) and non-enhanced (0.3 HU/keV) phase (p ≤ 0.002).

CONCLUSIONS

Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition, and may separate arterial and venous enhancement. Further studies are warranted to analyze spectral CT for inflammatory airway diseases.

KEY POINTS

• Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition. • Spectral CT may separate arterial and venous enhancement of lung parenchyma and airway wall. • The contrast enhancement can be quantified by calculating the spectral attenuation curve slope from virtual monoenergetic images.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques

OBJECTIVES

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF).

METHODS

A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison.

RESULTS

The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively.

CONCLUSION

The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations.

KEY POINTS

• This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.