Single-source dual-energy spectral multidetector CT of pancreatic adenocarcinoma: optimization of energy level viewing significantly increases lesion contrast

Comparing two deep learning spectral reconstruction levels for abdominal evaluation using a rapid-kVp-switching dual-energy CT scanner

PURPOSE

Deep Learning Spectral Reconstruction (DLSR) potentially improves dual-energy CT (DECT) image quality, but there is a paucity of research involving human abdominal DECT scans. The purpose of this study was to comprehensively evaluate image quality by quantitatively and qualitatively comparing strong and standard levels of a DLSR algorithm. Optimal virtual monochromatic image (VMI) energy levels were also evaluated.

METHODS

DECT scans of the abdomen/pelvis from 51 patients were retrospectively evaluated. VMIs were reconstructed at energy levels ranging from 35 to 200 keV using both standard and strong DLSR levels. For quantitative analysis, various abdominal structures were assessed using regions of interest, and mean signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values were calculated. This was supplemented with a qualitative evaluation of VMIs reconstructed at 35, 45, 55, and 65 keV.

RESULTS

The strong-level DLSR demonstrated significantly better SNR and CNR values (p < 0.0001) compared to standard-level DLSR across all structures. The optimal SNR was observed at 70 keV (p < 0.0001), while the optimal CNR was found at 65 keV (p < 0.0001). The average qualitative scores between standard and strong DLSR were significantly different at 45, 55, and 65 keV (p < 0.0001). There was a moderate level of agreement between observers (ICC = 0.427, p < 0.0001).

CONCLUSION

A DLSR set to a strong level significantly improves image quality compared to standard-level DLSR, potentially enhancing the diagnostic evaluation of abdominal DECT scans. In addition to achieving a very high SNR, 65 keV VMIs had the highest CNR, which differs from what is typically observed with traditional DECT using non-deep learning reconstruction approaches.

Non-contrast spectral CT vs chemical-shift MRI in discriminating lipid-poor adrenal lesions

OBJECTIVES

To compare the diagnostic performance of conventional non-contrast CT, dual-energy spectral CT, and chemical-shift MRI (CS-MRI) in discriminating lipid-poor adenomas (> 10-HU on non-contrast CT) from non-adenomas.

METHODS

A total of 110 patients (69 men; 41 women; mean age 66.5 ± 13.4 years) with 80 lipid-poor adenomas and 30 non-adenomas who underwent non-contrast dual-layer spectral CT and CS-MRI were retrospectively identified. For each lesion, non-contrast attenuation on conventional 120-kVp images, ΔHU-index ([attenuation difference between virtual monoenergetic 140-keV and 40-keV images]/conventional attenuation × 100), and signal intensity index (SI-index) were quantified. Each parameter was compared between adenomas and non-adenomas using the Mann-Whitney U-test. The area under the receiver operating characteristic curve (AUC) and sensitivity to achieve > 95% specificity for adenoma diagnosis were determined.

RESULTS

Conventional non-contrast attenuation was lower in adenomas than in non-adenomas (22.4 ± 8.6 HU vs 32.8 ± 48.5 HU), whereas ΔHU-index (148.0 ± 103.2 vs 19.4 ± 25.8) and SI-index (41.6 ± 19.6 vs 4.2 ± 10.2) were higher in adenomas (all, p < 0.001). ΔHU-index showed superior performance to conventional non-contrast attenuation (AUC: 0.919 [95% CI: 0.852-0.963] vs 0.791 [95% CI: 0.703-0.863]; sensitivity: 75.0% [60/80] vs 27.5% [22/80], both p < 0.001), and near equivalent to SI-index (AUC: 0.952 [95% CI: 0.894-0.984], sensitivity 85.0% [68/80], both p > 0.05). Both the ΔHU-index and SI-index provided a sensitivity of 96.0% (48/50) for hypoattenuating adenomas (≤ 25 HU). For hyperattenuating (> 25 HU) adenomas, SI-index showed higher sensitivity than ΔHU-index (66.7% [20/30] vs 40.0% [12/30], p = 0.022).

CONCLUSIONS

Non-contrast spectral CT and CS-MRI outperformed conventional non-contrast CT in distinguishing lipid-poor adenomas from non-adenomas. While CS-MRI demonstrated superior sensitivity for adenomas measuring > 25 HU, non-contrast spectral CT provided high discriminative values for adenomas measuring ≤ 25 HU.

CLINICAL RELEVANCE STATEMENT

Spectral attenuation analysis improves the diagnostic performance of non-contrast CT in discriminating lipid-poor adrenal adenomas, potentially serving as an alternative to CS-MRI and obviating the necessity for additional diagnostic workup in indeterminate adrenal incidentalomas, particularly for lesions measuring ≤ 25 HU.

KEY POINTS

Incidental adrenal lesion detection has increased as abdominal CT use has become more frequent. Non-contrast spectral CT and CS-MRI differentiated lipid-poor adenomas from non-adenomas better than conventional non-contrast CT. For lesions measuring ≤ 25 HU, spectral CT may obviate the need for additional evaluation.

Imaging the pancreas with photon-counting CT - A review of normal pancreatic anatomy

PURPOSE

Compared to conventional energy integrating detector CT, Photon-Counting CT (PCCT) has the advantage of increased spatial resolution. The pancreas is a highly complex organ anatomically. The increased spatial resolution of PCCT challenges radiologists' knowledge of pancreatic anatomy. The purpose of this review was to review detailed macroscopic and microscopic anatomy of the pancreas in the context of current and future PCCT.

METHOD

This review is based on a literature review of all parts of pancreatic anatomy and a retrospective imaging review of PCCT scans from 20 consecutively included patients without pancreatic pathology (mean age 61.8 years, 11 female), scanned in the workup of pancreatic cancer with a contrast enhanced multiphase protocol. Two radiologists assessed the visibility of the main and accessory pancreatic ducts, side ducts, ampulla, major papilla, minor papilla, pancreatic arteries and veins, regional lymph nodes, coeliac ganglia, and coeliac plexus.

RESULTS

The macroscopic anatomy of the pancreas was consistently visualized with PCCT. Visualization of detailed anatomy of the ductal system (including side ducts), papillae, arteries, vein, lymph nodes, and innervation was possible in 90% or more of patients with moderate to good interreader agreement.

CONCLUSION

PCCT scans of the pancreas visualizes previously unseen or inconsistently seen small anatomical structures consistently. Increased knowledge of pancreatic anatomy could have importance in imaging of pancreatic cancer and other pancreatic diseases.

Assessment of solitary pulmonary nodules using dual-layer spectral detector computed tomography

We aim to quantitatively investigate the difference between benign and malignant solid pulmonary nodules that appeared on dual-energy spectral computed tomography, and assess the diagnostic accuracy of several parameters derived from computed tomography in differentiating malignant from benign pulmonary nodules. Between September 2021 and December 2022, spectral images of 71 patients (male:female = 44:27, mean age = 71.0 years) confirmed by pathology were retrospectively analyzed in the venous phase. Patients were classified into the malignant group and the benign group. The iodine concentration values of the nodules, normalized iodine concentration of the nodules to the neighboring vessels, virtual monochromatic images of 40 and 80 keV, and slope of the spectral curve were calculated and compared between the benign and malignant groups. Receiver operating characteristic curves and the area under the curve were performed to assess the diagnostic performance of the above parameters. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. The malignant pulmonary nodules have higher iodine density and slope of the spectral curve than the benign lesions. The combined model of iodine density and curve slope with an optimal cutoff of 0.39 (area under the curve = 0.82) yielded a sensitivity of 95% and a specificity of 63%. Contrast-enhanced dual-energy spectral computed tomography allows promising capability of distinguishing malignant from benign lesions, potential for avoiding unnecessary invasive procedure or surgery.

Diagnostic Value of Contrast-Enhanced Dual-Energy Computed Tomography in the Pancreatic Parenchymal and Delayed Phases for Pancreatic Cancer

Background/Objectives: The usefulness of dual-energy computed tomography (DECT) for low absorption in the parenchymal phase and contrast effects in the delayed phase for pancreatic cancer is not clear. Therefore, the diagnostic capability of low-KeV images obtained using DECT for pancreatic cancer in the pancreatic parenchymal and delayed phases was evaluated quantitatively and qualitatively. Methods: Twenty-five patients with pancreatic cancer who underwent contrast-enhanced DECT were included. A total of 50 and 70 KeV CT images, classified as low-keV and conventional CT-equivalent images, were produced, respectively. The tumor-to-pancreas contrast (Hounsfield units [HU]) in the pancreatic parenchymal and delayed phases was calculated by subtracting the CT value of the pancreatic tumor from that of normal parenchyma. Results: The median tumor-to-pancreas contrast on 50 KeV CT in the pancreatic parenchymal phase (133 HU) was higher than that on conventional CT (68 HU) (p < 0.001). The median tumor-to-pancreas contrast in the delayed phase was -28 HU for 50 KeV CT and -9 HU for conventional CT (p = 0.545). For tumors < 20 mm, the tumor-to-pancreas contrast of 50 KeV CT (-39 HU) had a significantly clearer contrast effect than that of conventional CT (-16.5 HU), even in the delayed phase (p = 0.034). Conclusions: These 50 KeV CT images may clarify the low-absorption areas of pancreatic cancer in the pancreatic parenchymal phase. A good contrast effect was observed in small pancreatic cancers on 50 KeV delayed-phase images, suggesting that DECT is useful for the visualization of early pancreatic cancer with a small tumor diameter.

Synthetic Low-Energy Monochromatic Image Generation in Single-Energy Computed Tomography System Using a Transformer-Based Deep Learning Model

While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel method to generate synthetic low-energy virtual monochromatic images at 50 keV (sVMI50keV) from SECT images using a transformer-based deep learning model, SwinUNETR. Data were obtained from 85 patients who underwent head and neck radiotherapy. Among these, the model was built using data from 70 patients for whom only DECT images were available. The remaining 15 patients, for whom both DECT and SECT images were available, were used to predict from the actual SECT images. We used the SwinUNETR model to generate sVMI50keV. The image quality was evaluated, and the results were compared with those of the convolutional neural network-based model, Unet. The mean absolute errors from the true VMI50keV were 36.5 ± 4.9 and 33.0 ± 4.4 Hounsfield units for Unet and SwinUNETR, respectively. SwinUNETR yielded smaller errors in tissue attenuation values compared with those of Unet. The contrast changes in sVMI50keV generated by SwinUNETR from SECT were closer to those of DECT-derived VMI50keV than the contrast changes in Unet-generated sVMI50keV. This study demonstrated the potential of transformer-based models for generating synthetic low-energy VMIs from SECT images, thereby improving the image quality of head and neck cancer imaging. It provides a practical and feasible solution to obtain low-energy VMIs from SECT data that can benefit a large number of facilities and patients without access to DECT technology.

Variation in Hounsfield unit calculated using dual-energy computed tomography: comparison of dual-layer, dual-source, and fast kilovoltage switching technique

The purpose of the study is to investigate the variation in Hounsfield unit (HU) values calculated using dual-energy computed tomography (DECT) scanners. A tissue characterization phantom inserting 16 reference materials were scanned three times using DECT scanners [dual-layer CT (DLCT), dual-source CT (DSCT), and fast kilovoltage switching CT (FKSCT)] changing scanning conditions. The single-energy CT images (120 or 140 kVp), and virtual monochromatic images at 70 keV (VMI70) and 140 keV (VMI140) were reconstructed, and the HU values of each reference material were measured. The difference in HU values was larger when the phantom was scanned using the half dose with wrapping with rubber (strong beam-hardening effect) compared with the full dose without the rubber (reference condition), and the difference was larger as the electron density increased. For SECT, the difference in HU values against the reference condition measured by the DSCT (3.2 ± 5.0 HU) was significantly smaller (p < 0.05) than that using DLCT with 120 kVp (22.4 ± 23.8 HU), DLCT with 140 kVp (11.4 ± 12.8 HU), and FKSCT (13.4 ± 14.3 HU). The respective difference in HU values in the VMI70 and VMI140 measured using the DSCT (10.8 ± 17.1 and 3.5 ± 4.1 HU) and FKSCT (11.5 ± 21.8 and 5.5 ± 10.4 HU) were significantly smaller than those measured using the DLCT120 (23.1 ± 27.5 and 12.4 ± 9.4 HU) and DLCT140 (22.3 ± 28.6 and 13.1 ± 11.4 HU). The HU values and the susceptibility to beam-hardening effects varied widely depending on the DECT scanners.

Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images

PURPOSE

To compare the diagnostic performance of 40 keV and 70 keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer.

METHODS

This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11 years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70 keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40 keV and 70 keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations.

RESULTS

Overall, 137 patients (median age, 71 years; interquartile range, 63-78 years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40 keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70 keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs.

CONCLUSIONS

The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70 keV VMIs, along with higher reader confidence.

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.

Pancreatic cancer in photon-counting CT: Low keV virtual monoenergetic images improve tumor conspicuity

PURPOSE OF THE STUDY

The aim of the study was to identify differences in the tumor conspicuity of pancreatic adenocarcinomas in different monoenergetic or polyenergetic reconstructions and contrast phases in photon-counting CT (PCCT).

MATERIAL AND METHODS

34 patients were retrospectively enrolled in this study. Quantitative image analysis was performed with region of interest (ROI) measurements in different monoenergetic levels ranging from 40 up to 70 keV (5-point steps) and polyenergetic series. Tumor-parenchyma attenuation differences and contrast-to-noise-ratio (CNR) were calculated. A qualitative image analysis was accomplished by 4 radiologists using a 5-point Likert scale (1 = "not recognizable" up to 5 = "easy recognizable"). Differences between groups were evaluated for statistical significance using the Friedman test and in case of significant differences pair-wise post-hoc testing with Bonferroni correction was applied.

RESULTS

Tumor-parenchyma attenuation difference was significantly different between the different image reconstructions for both arterial- and portal-venous-phase-images (p < 0.001). Tumor-parenchyma attenuation difference was significantly higher on arterial-phase-images at mono40keV compared to polyenergetic images (p < 0.001) and mono55keV images or higher (p < 0.001). For portal-venous-phase-images tumor-parenchyma attenuation difference was significantly higher on mono40keV images compared to polyenergetic images (p < 0.001) and mono50keV images (p = 0.03) or higher (p < 0.001). The same trend was seen for CNR. Tumor conspicuity was rated best on mono40keV images with 4.3 ± 0.9 for arterial-phase-images and 4.3 ± 1.1 for portal-venous-phase-images. In contrast, overall image quality was rated best on polyenergetic-images with 4.8 ± 0.5 for arterial-phase-images and 4.7 ± 0.6 for portal-venous-phase-images.

CONCLUSION

Low keV virtual monoenergetic images significantly improve the tumor conspicuity of pancreatic adenocarcinomas in PCCT based on quantitative and qualitative results. On the other hand, readers prefer polyenergetic images for overall image quality.

Artificial intelligence-based image-domain material decomposition in single-energy computed tomography for head and neck cancer

PURPOSE

While dual-energy computed tomography (DECT) images provide clinically useful information than single-energy CT (SECT), SECT remains the most widely used CT system globally, and only a few institutions can use DECT. This study aimed to establish an artificial intelligence (AI)-based image-domain material decomposition technique using multiple keV-output learning of virtual monochromatic images (VMIs) to create DECT-equivalent images from SECT images.

METHODS

This study involved 82 patients with head and neck cancer. Of these, the AI model was built with data from the 67 patients with only DECT scans, while 15 patients with both SECT and DECT scans were used for SECT testing. Our AI model generated VMI50keV and VMI100keV from VMI70keV equivalent to 120-kVp SECT images. We introduced a loss function for material density images (MDIs) in addition to the loss for VMIs. For comparison, we trained the same model with the loss for VMIs only. DECT-equivalent images were generated from SECT images and compared with the true DECT images.

RESULTS

The prediction time was 5.4 s per patient. The proposed method with the MDI loss function quantitatively provided more accurate DECT-equivalent images than the model trained with the loss for VMIs only. Using real 120-kVp SECT images, the trained model produced precise DECT images of excellent quality.

CONCLUSION

In this study, we developed an AI-based material decomposition approach for head and neck cancer patients by introducing the loss function for MDIs via multiple keV-output learning. Our results suggest the feasibility of AI-based image-domain material decomposition in a conventional SECT system without a DECT scanner.

Characterization of single- and multi-energy CT performance of an oral dark borosilicate contrast media using a clinical photon-counting-detector CT platform

BACKGROUND

The feasibility of oral dark contrast media is under exploration in abdominal computed tomography (CT) applications. One of the experimental contrast media in this class is dark borosilicate contrast media (DBCM), which has a CT attenuation lower than that of intra-abdominal fat.

PURPOSE

To evaluate the performances of DBCM using single- and multi-energy CT imaging on a clinical photon-counting-detector CT (PCD-CT).

METHODS

Five vials, three with iodinated contrast agent (5, 10, and 20 mg/mL; Omnipaque 350) and two with DBCM (6% and 12%; Nextrast, Inc.), and one solid-water rod (neutral contrast agent) were inserted into two multi-energy CT phantoms, and scanned on a clinical PCD-CT system (NAEOTOM Alpha) at 90, 120, 140, Sn100, and Sn140 kV (Sn: tin filter) in multi-energy mode. CARE keV IQ level was 180 (CTDIvol: 3.0 and 12.0 mGy for the small and large phantoms, respectively). Low-energy threshold images were reconstructed with a quantitative kernel (Qr40, iterative reconstruction strength 2) and slice thickness/increment of 2.0/2.0 mm. Virtual monoenergetic images (VMIs) were reconstructed from 40 to 140 keV at 10 keV increments. On all images, average CT numbers for each vial/rod were measured using circular region-of-interests and averaged over eight slices. The contrast-to-noise ratio (CNR) of iodine (5 mg/mL) against DBCM was calculated and plotted against tube potential and VMI energy level, and compared to the CNR of iodine against water. Similar analyses were performed on iodine maps and VNC images derived from the multi-energy scan at 120 kV.

RESULTS

With increasing kV or VMI keV, the negative HU of DBCM decreased only slightly, whereas the positive HU of iodine decreased across all contrast concentrations and phantom sizes. CT numbers for DBCM decreased from -178.5 ± 9.6 to -194.4 ± 6.3 HU (small phantom) and from -181.7 ± 15.7 to -192.1 ± 11.9 HU (large phantom) for DBCM-12% from 90 to Sn140 kV; on VMIs, the CT numbers for DBCM decreased minimally from -147.1 ± 15.7 to -185.1 ± 9.2 HU (small phantom) and -158.8 ± 28.6 to -188.9 ± 14.7 HU (large phantom) from 40 to 70 keV, but remained stable from 80 to 140 keV. The highest iodine CNR against DBCM in low-energy threshold images was seen at 90 or Sn140 kV for the small phantom, whereas all CNR values from low-energy threshold images for the large phantom were comparable. The CNR values of iodine against DBCM computed on VMIs were highest at 40 or 70 keV depending on iodine and DBCM concentrations. The CNR values of iodine against DBCM were consistently higher than iodine to water (up to 460% higher dependent on energy level). Further, the CNR of iodine compared to DBCM is less affected by VMI energy level than the identical comparison between iodine and water: CNR values at 140 keV were reduced by 46.6% (small phantom) or 42.6% (large phantom) compared to 40 keV; CNR values for iodine compared to water were reduced by 86.3% and 83.8% for similar phantom sizes, respectively. Compared to 70 keV VMI, the iodine CNR against DBCM was 13%-79% lower on iodine maps and VNC.

CONCLUSIONS

When evaluated at different tube potentials and VMI energy levels using a clinical PCD-CT system, DBCM showed consistently higher CNR compared to iodine versus water (a neutral contrast).

Benefits of Dual-Layer Spectral CT Imaging in Staging and Preoperative Evaluation of Pancreatic Ductal Adenocarcinoma

Imaging of pancreatic malignancies is challenging but has a major impact on the patients therapeutic approach and outcome. In particular with pancreatic ductal adenocarcinoma (PDAC), usually a hypovascularized tumor, conventional CT imaging can be prone to errors in determining tumor extent and presence of metastatic disease. Dual-layer spectral detector CT (SDCT) is an emerging technique for acquiring spectral information without the need for prospective patient selection or specific protocols, with a detector capable of differentiating high- and low-energy photons to acquire full spectral images. In this review, we present the diagnostic benefits and capabilities of modern SDCT imaging with a focus on PDAC. We highlight the most useful virtual reconstructions in oncologic imaging and their benefits in staging and assessment of resectability in PDAC, including the assessment of tumor extent, vascular infiltration, and metastatic disease. We present imaging examples on a latest-generation SDCT scanner.

Feasibility of using software-aided selection of virtual monoenergetic level for optimal image quality of acute necrotising pancreatitis based on dual-energy computed tomography: a preliminary study

OBJECTIVE

This study aimed to assess the feasibility of software-aided selection of monoenergetic level for acute necrotising pancreatitis (ANP) depiction compared to other automatic image series generated using dual-energy computed tomography (CT).

METHODS

The contrast-enhanced dual-source dual-energy CT images in the portal venous phase of 48 patients with ANP were retrospectively analysed. Contrast-to-noise ratio (CNR) of pancreatic parenchyma-to-necrosis, signal-to-noise ratio (SNR) of the pancreas, image noise, and score of subjective diagnosis were measured, calculated, and compared among the CT images of 100 kV, Sn140 kV, weighted-average 120 kV, and optimal single-energy level for CNR.

RESULTS

CNR of pancreatic parenchyma-to-necrosis in the images of 100 kV, Sn140 kV, weighted-average 120 kV, and the optimal single-energy level for CNR was 5.18 ± 2.39, 3.13 ± 1.35, 5.69 ± 2.35, and 9.99 ± 5.86, respectively; SNR of the pancreas in each group was 6.31 ± 2.77, 4.27 ± 1.56, 7.21 ± 2.69, and 11.83 ± 6.30, respectively; image noise in each group was 18.78 ± 5.20, 17.79 ± 4.63, 13.28 ± 3.13, and 9.31 ± 2.96, respectively; and score of subjective diagnosis in each group was 3.56 ± 0.50, 3.00 ± 0.55, 3.48 ± 0.55, and 3.88 ± 0.33, respectively. The four measurements of the optimal single-energy level for CNR images were significantly different from those of images in the other three groups (P < 0.05). CNR of pancreatic parenchyma-to-necrosis, SNR of the pancreas, and score of subjective diagnosis in the images of the optimal single-energy level for CNR were significantly higher, while the image noise was lower than those in the other three groups (all P = 0.000).

CONCLUSION

Optimal single-energy level imaging for CNR of dual-source CT could improve quality of CT images in patients with ANP, enhancing the display of necrosis in the pancreas.

Dual Energy CT in Oncology: Benefits for Both Patients and Radiologists From an Emerging Quantitative and Functional Diagnostic Technique

Dual-energy CT (DECT) imaging makes it possible to identify the characteristics of materials that cannot be recognized with conventional single-energy CT (SECT). In the postprocessing study phase, virtual monochromatic images and virtual-non-contrast (VNC) images, also permits reduction of dose exposure by eliminating the precontrast acquisition scan. Moreover, in virtual monochromatic images, the iodine contrast increases when the energy level decreases resulting in better visualization of hypervascular lesions and in a better tissue contrast between hypovascular lesions and the surrounding parenchyma; thus, allowing for reduction of required iodinate contrast material, especially important in patients with renal impairment. All these advantages are particularly important in oncology, providing the possibility of overcoming many SECT imaging limits and making CT examinations safer and more feasible in critical patients. This review explores the basis of DECT imaging and its utility in routine oncologic clinical practice, with particular attention to the benefits of this technique for both the patients and the radiologists.

Improving the Accuracy of the Effective Atomic Number (EAN) and Relative Electron Density (RED) with Stoichiometric Calibration on PCD-CT Images

The photon counting detector (PCD) in computed tomography (CT) can count the number of incoming photons in order to obtain energy information for photons corresponding to user-defined thresholds. Research on the extraction of effective atomic number (EAN) and relative electron density (RED) using dual-energy CT (DECT) is currently underway. This study proposes a method for improving EAN and RED accuracy of tissue-equivalent materials by using PCD-CT-based stoichiometric calibration. After obtaining DECT images in energy bin (EB) and full spectrum (FS) modes for eight tissue-equivalent materials, the EAN was calculated with stoichiometric calibration. Using the EAN image, the RED image was acquired to evaluate the accuracy. The errors of both EAN and RED obtained with EB were within 4%. In particular, the accuracy of RED was higher than that of the FS method. Study results indicate that PCD-CT contributes to improving EAN and RED accuracy. Further studies will be aimed at reducing ring artifacts by pixel-correcting PCD images and improving stopping power ratio (SPR) measurements for dose calculation in particle therapy.

Value of Dual-Energy Computed Tomography for Detecting Small Pancreatic Ductal Adenocarcinoma

OBJECTIVE

The aim of the study is to evaluate the usefulness of virtual monoenergetic imaging (VMI) generated from dual-energy computed tomography (DECT) in detecting small pancreatic ductal adenocarcinomas (PDACs).

METHODS

This study included 82 patients pathologically diagnosed with small PDAC (≤30 mm) and 20 without pancreatic tumors who underwent triple-phase contrast-enhanced DECT. To assess diagnostic performance for small PDAC detection via a receiver operating characteristic analysis, 3 observers reviewed 2 image sets (conventional computed tomography [CT] set and combined image set [conventional CT + 40-keV VMI from DECT]). The tumor-to-pancreas contrast-to-noise ratio was compared between conventional CT and 40-keV VMI from DECT.

RESULTS

The area under the receiver operating characteristic curve of the 3 observers were 0.97, 0.96, and 0.97 in conventional CT set and 0.99, 0.99, and 0.99 in combined image set (P = 0.017-0.028), respectively. The combined image set yielded a better sensitivity than the conventional CT set (P = 0.001-0.023), without a loss of specificity (all P > 0.999). The tumor-to-pancreas contrast-to-noise ratios of 40-keV VMI from DECT were approximately threefold higher than those of conventional CT at all phases.

CONCLUSIONS

The addition of 40-keV VMI from DECT to conventional CT had better sensitivity for detecting small PDACs without compromising specificity.

Application of spectral CT combined with perfusion scan in diagnosis of pancreatic neuroendocrine tumors

Background

Pancreatic neuroendocrine tumors (pNETs) are heterogeneous tumors from the pancreatic neuroendocrine system, and early diagnosis is important for tumor prognosis and treatment. In this study, we aimed to explore the diagnostic value of spectral CT combined with perfusion scanning in improving the detection rate of pNETs.

Methods

From December 2018 to December 2020, 58 patients with clinically suspected pNETs were prospectively enrolled in the study for one-stop spectral CT combined with perfusion scanning, 36 patients were confirmed with pNETs by histopathology. An independent cohort of 30 patients with pNETs who underwent routine pancreatic perfusion scanning in our hospital during the same period were retrospectively collected. The image characters of pNETs versus tumor-free pancreatic parenchymal were examined.

Results

The detection rate of spectral CT combined with perfusion was 83.1–96.2%. CT values of the pNETs lesions under each single energy in the arterial phase were statistically higher than those of the adjacent normal pancreatic parenchyma. IC, WC and NIC, in the arterial phase of pNETs lesion were all statistically higher than those of the adjacent normal pancreatic parenchyma. The perfusion parameters of pNETs including BF, BV and MSI were significantly higher than those in normal parenchyma. The average effective radiation dose during the perfusion combined energy spectrum enhanced scanning process was 17.51 ± 2.18 mSv.

Conclusion

The one-stop spectral CT combined with perfusion scan improves the detection of pNETs according to morphological features, perfusion parameters and energy spectrum characters with a relatively small radiation dose.

Virtual Monochromatic Images from Dual-Energy Computed Tomography Do Not Improve the Detection of Synovitis in Hand Arthritis

The objective of this study was to investigate subtraction images from different polychromatic and virtual monochromatic reconstructions of dual-energy computed tomography (CT) for the detection of inflammation (synovitis/tenosynovitis or peritendonitis) in patients with hand arthritis. In this IRB-approved prospective study, 35 patients with acute hand arthritis underwent contrast-enhanced dual-energy CT and musculoskeletal ultrasound (MSUS) of the clinically dominant hand. CT subtractions (CT-S) were calculated from 80 and 135 kVp source data and monochromatic 50 and 70 keV images. CT-S and MSUS were scored for synovitis and tenosynovitis/peritendonitis. Specificity, sensitivity and diagnostic accuracy were assessed by using MSUS as a reference. Parameters of objective image quality were measured. Thirty-three patients were analyzed. MSUS was positive for synovitis and/or tenosynovitis/peritendonitis in 28 patients. The 70 keV images had the highest diagnostic accuracy, with 88% (vs. 50 keV, 82%; 80 kVp, 85%; and 135 kVp, 82%), and superior sensitivity, with 96% (vs. 50 keV: 86%, 80 kVp: 93% and 135 kVp: 79%). The 80 kVp images showed the highest signal- and contrast-to-noise ratio, while the 50 keV images provided the lowest image quality. While all subtraction methods of contrast-enhanced dual-energy CT proved to be able to detect inflammation with sufficient diagnostic accuracy, virtual monochromatic images with low keV showed no significant improvement over conventional subtraction techniques and lead to a loss of image quality.

Dual-Energy CT in the Pancreas

Dual-energy computed tomography (DECT) is an evolving imaging technology that is gaining popularity, particularly in different abdominopelvic applications. Essentially, DECT uses two energy spectra simultaneously to acquire CT attenuation data which is used to distinguish among structures with different tissue composition. The wide variety of reconstructed image data sets makes DECT especially attractive in pancreatic imaging. This article reviews the current literature on DECT as it applies to imaging the pancreas, focusing on pancreatitis, trauma, pancreatic ductal adenocarcinoma, and other solid and cystic neoplasms. The advantages of DECT over conventional CT are highlighted, including improved lesion detection, radiation dose reduction, and enhanced image contrast. Additionally, data exploring the ideal protocol for pancreatic imaging using DECT is reviewed. Finally, limitations of DECT in pancreatic imaging as well as recommendations for future research are provided.

Parameters of dual-energy CT for the differential diagnosis of thyroid nodules and the indirect prediction of lymph node metastasis in thyroid carcinoma: a retrospective diagnostic study

BACKGROUND

To further investigate the differential diagnosis of thyroid nodules using dual-energy computed tomography (DECT) and explore the relationship between DECT parameters and lymph node metastasis in thyroid carcinoma for clinical practice, especially difficult diagnosis by routine imaging examination.

METHODS

A total of 150 patients with thyroid nodules who underwent preoperative DECT and Thyroid Imaging Report and Data System (TIRADS) classification were enrolled in this study, including 96 patients with malignant tumors and 54 with benign tumors. The DECT parameters were got form regions of interest (ROI) by an experienced radiologist team and thyroid nodules and lymph node status of all patients were identified by cytology and histopathology. Statistical analyses were performed using Student's t-test, Chi-squared test, and receiver operating characteristic (ROC) curves.

RESULTS

In the differential diagnosis of benign and malignant thyroid nodules, the optimal iodine concentration (IC) and normalized iodine concentration (NIC) cut-off values were ICa (2.835 mg/mL), NIC1a (0.690), and their corresponding area under the curve (AUC) were 0.940, 0.954 respectively; meantime, the optimal computed tomography (CT) value and slope of the spectral Hounsfield unit curve (λHU) cut-off values were 70 keVa (125.05 HU) and λHU2a (1.405), and their corresponding AUC were 0.955, 0.941 respectively. For lymph node status (with or without lymph node metastasis), the optimal IC and NIC thresholds were ICa (1.715 mg/mL) and NIC2a (0.155), and their corresponding AUC were 0.717, 0.720 respectively; meanwhile, the optimal CT value and λHU thresholds were 70 keVv (89.635 HU) and λHU2v (1.185), and their corresponding AUC were 0.729, 0.641 respectively.

CONCLUSIONS

Base on our study, we think DECT is useful in differentiating malignant from benign thyroid nodules, which has potential value in the indirect prediction of lymph node metastasis in thyroid carcinoma.

Imaging Assessment of Pancreatic Cancer Resectability After Neoadjuvant Therapy: AJR Expert Panel Narrative Review

Despite important innovations in the treatment of pancreatic ductal adenocarcinoma (PDAC), PDAC remains a disease with poor prognosis and high mortality. A key area for potential improvement in the management of PDAC, aside from earlier detection in patients with treatable disease, is the improved ability of imaging techniques to differentiate treatment response after neoadjuvant therapy (NAT) from worsening disease. It is well established that current imaging techniques cannot reliably make this distinction. This narrative review provides an update on the imaging assessment of pancreatic cancer resectability after NAT. Current definitions of borderline resectable PDAC, as well as implications for determining likely patient benefit from NAT, are described. Challenges associated with PDAC pathologic evaluation and surgical decision making that are of relevance to radiologists are discussed. Also explored are the specific limitations of imaging in differentiating the response after NAT from stable or worsening disease, including issues relating to protocol optimization, tumor size assessment, vascular assessment, and liver metastasis detection. The roles of MRI as well as PET and/or hybrid imaging are considered. Finally, a short PDAC reporting template is provided for use after NAT. The highlighted methods seek to improve radiologists' assessment of PDAC treatment response after NAT.

Can activated titanium interbody cages accelerate or enhance spinal fusion? a review of the literature and a design for clinical trials

While spinal interbody cage options have proliferated in the past decade, relatively little work has been done to explore the comparative potential of biomaterial technologies in promoting stable fusion. Innovations such as micro-etching and nano-architectural designs have shown purported benefits in in vitro studies, but lack clinical data describing their optimal implementation. Here, we critically assess the pre-clinical data supportive of various commercially available interbody cage biomaterial, topographical, and structural designs. We describe in detail the osteointegrative and osteoconductive benefits conferred by these modifications with a focus on polyetheretherketone (PEEK) and titanium (Ti) interbody implants. Further, we describe the rationale and design for two randomized controlled trials, which aim to address the paucity of clinical data available by comparing interbody fusion outcomes between either PEEK or activated Ti lumbar interbody cages. Utilizing dual-energy computed tomography (DECT), these studies will evaluate the relative implant-bone integration and fusion rates achieved by either micro-etched Ti or standard PEEK interbody devices. Taken together, greater understanding of the relative osseointegration profile at the implant-bone interface of cages with distinct topographies will be crucial in guiding the rational design of further studies and innovations.

Resectable and Borderline Resectable Pancreatic Ductal Adenocarcinoma: Role of the Radiologist and Oncologist in the Era of Precision Medicine

The incidence and mortality of pancreatic ductal adenocarcinoma are growing over time. The management of patients with pancreatic ductal adenocarcinoma involves a multidisciplinary team, ideally involving experts from surgery, diagnostic imaging, interventional endoscopy, medical oncology, radiation oncology, pathology, geriatric medicine, and palliative care. An adequate staging of pancreatic ductal adenocarcinoma and re-assessment of the tumor after neoadjuvant therapy allows the multidisciplinary team to choose the most appropriate treatment for the patient. This review article discusses advancement in the molecular basis of pancreatic ductal adenocarcinoma, diagnostic tools available for staging and tumor response assessment, and management of resectable or borderline resectable pancreatic cancer.

Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT

OBJECTIVES

To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements.

METHODS

We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions.

RESULTS

A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

CONCLUSION

A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

KEY POINTS

• A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93). • When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions. • Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography

PURPOSE

To construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.

MATERIALS AND METHODS

Fifty patients with pancreatic cancer underwent a dual-energy CT simulation and VMIs at 77 and 60 keV were reconstructed. A 2D deep densely connected convolutional neural network was modeled to learn the relationship between the VMIs at 77 (input) and 60 keV (ground-truth). Subsequently, VMIs were generated for 20 patients from SECT images using the trained deep learning model.

RESULTS

The contrast-to-noise ratio was significantly improved (p < 0.001) in the generated VMIs (4.1 ± 1.8) compared to the SECT images (2.8 ± 1.1). The mean overall image quality (4.1 ± 0.6) and tumor enhancement (3.6 ± 0.6) in the generated VMIs assessed on a five-point scale were significantly higher (p < 0.001) than that in the SECT images (3.2 ± 0.4 and 2.8 ± 0.4 for overall image quality and tumor enhancement, respectively).

CONCLUSIONS

The quality of the SECT image was significantly improved both objectively and subjectively using the proposed deep learning model for pancreatic tumors in radiotherapy.

Clinical Applications of Dual-Energy CT

Dual-energy CT (DECT) provides insights into the material properties of tissues and can differentiate between tissues with similar attenuation on conventional single-energy imaging. In the conventional CT scanner, differences in the X-ray attenuation between adjacent structures are dependent on the atomic number of the materials involved, whereas in DECT, the difference in the attenuation is dependent on both the atomic number and electron density. The basic principle of DECT is to obtain two datasets with different X-ray energy levels from the same anatomic region and material decomposition based on attenuation differences at different energy levels. In this article, we discuss the clinical applications of DECT and its potential robust improvements in performance and postprocessing capabilities.

Evaluation of equivocal small cystic pancreatic lesions with spectral-detector computed tomography

BACKGROUND

Evaluation of small cystic lesions of the pancreas remains a challenging task, as due to their size appearance can be rather hypodense than clearly fluid-filled.

PURPOSE

To evaluate whether additional information provided by novel dual-layer spectral-detector computed tomography (SDCT) imaging can improve assessment of these lesions.

MATERIAL AND METHODS

For this retrospective study, we reviewed reports of 1192 contrast-enhanced portal-venous phase SDCT scans of the abdomen conducted between May 2017 and January 2019. On basis of the radiological report 25 small (≤1.5 cm) cystic pancreatic lesions in 22 patients were identified, in which additional short-term follow-up imaging was recommended to confirm/clarify cystic nature. Conventional images (CI) and spectral images (SI) including virtual-monoenergetic images at 40 keV (VMI), iodine-density and iodine-overlay images were reconstructed. Two readers indicated lesion conspicuity and confidence for presence of cystic nature on three-point scales. First, solely CI were evaluated, while in a second reading after a four-week interval, the combination of CI and corresponding SI were reviewed. Quantitatively, ROI-based mean attenuation was measured in CI and VMI.

RESULTS

In the subjective reading, SI significantly improved lesion conspicuity (CI 2 [1-2], SI 3 [2-3], P < 0.001) and confidence regarding presence of cystic nature (CI 2 [1-2], SI 3 [3-3], P < 0.001). Inter-observer agreement depicted by intraclass correlation coefficient improved considerably from 0.51 with only CI to 0.85 when the combination with SI was used. Further, VMI displayed significantly higher signal-to-noise (CI 1.2 ± 0.8, VMI 3.2 ± 1.8, P < 0.001) and contrast-to-noise ratios (CI 2.6 ± 0.8, VMI 4.7 ± 1.9).

CONCLUSION

Compared to CI alone, combination with SI significantly improves visualization and confidence in evaluation of small equivocal cystic pancreatic lesions.

CT severity indices derived from low monoenergetic images at dual-energy CT may improve prediction of outcome in acute pancreatitis

OBJECTIVES

To determine whether imaging features and severity indices using low monoenergetic DECT images improve diagnostic conspicuity and outcome prediction in acute pancreatitis compared to conventional images.

METHODS

A retrospective study of patients with clinical and radiographic signs of acute pancreatitis who underwent 50 contrast-enhanced CT exams conducted on a single-source DECT was performed. Representative conventional and 50 keV-monoenergetic images were randomized and presented to four abdominal radiologists to determine preferred imaging for detecting fat stranding and parenchymal inflammation. Contrast and signal-to-noise ratios were constructed for necrotic, hypoattenuated, inflamed, and healthy parenchyma. These parameters and the CT severity index (CTSI) were compared between conventional and low monoenergetic images using paired t tests and correlated to clinical outcome.

RESULTS

Although preference for conventional images was noted for subtle peri-pancreatic fat stranding (169/200 (85%) reads), there was clear preference for low monoenergetic images among all readers for pancreatic inflammation evaluation (188/200 (94%) reads). Moreover, identification of small, hypoattenuating inflammatory foci on monoenergetic images alone in 13/50 (26%) cases resulted in upstaged CTSI from mild to moderate in 7/50 (14%), associated with longer hospitalization (16 ± 17 days vs. 5 ± 2 days; p < 0.05), ICU admission, and drainage. Quantitatively, a twofold difference between normal and inflamed parenchyma attenuation was identified for monoenergetic (44.8 ± 27.6) vs. conventional (25.1 ± 14.7) images (p < 0.05). Significant increases were seen in the monoenergetic SNR and CNR compared to the conventional images (p < 0.05).

CONCLUSIONS

DECT low monoenergetic images afford better tissue assessment and demarcation of inflamed pancreatic parenchyma. Additionally, they provide improved characterization of the extent parenchymal necrosis, enabling better classification that may better predict severe clinical outcomes.

KEY POINTS

• DECT low monoenergetic images afford better tissue assessment and demarcation of inflamed pancreatic parenchyma and provide improved characterization of the extent parenchymal necrosis. • Qualitatively, low monoenergetic images were preferred over conventional DECT images for the evaluation of pancreatic inflammation; and quantitatively, there is a twofold difference between normal and inflamed parenchyma attenuation, SNR, and CNR between monoenergetic vs. conventional images. • Monoenergetic imaging identified additional small, hypoattenuating inflammatory foci in 26% resulting in an upstaged CT severity index in 14% associated with longer hospitalization, ICU admission, and drainage, thereby enabling better classification and better prediction of severe clinical outcomes.

Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging

Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.

New advances in CT imaging of pancreas diseases: a narrative review

Computed tomography (CT) plays a pivotal role as a diagnostic tool in many diagnostic and diffuse pancreatic diseases. One of the major limits of CT is related to the radiation exposure of young patients undergoing repeated examinations. Besides the standard CT protocol, the most recent technological advances, such as low-voltage acquisitions with high performance X-ray tubes and iterative reconstructions, allow for significant optimization of the protocol with dose reduction. The variety of CT tools are further expanded by the introduction of dual energy: the production of energy-selective images (i.e., virtual monochromatic images) improves the image contrast and lesion detection while the material-selective images (e.g., iodine maps or virtual unenhanced images) are valuable for lesion detection and dose reduction. The perfusion techniques provide diagnostic and prognostic information lesion and parenchymal vascularization and interstitium. Both dual energy and perfusion CT have the potential for pushing the limits of conventional CT from morphological evaluation to quantitative imaging applied to inflammatory and oncological diseases. Advances in post-processing of CT images, such as pancreatic volumetry, texture analysis and radiomics provide relevant information for pancreatic function but also for the diagnosis, management and prognosis of pancreatic neoplasms. Artificial intelligence is promising for optimization of the workflow in qualitative and quantitative analyses. Finally, basic concepts on the role of imaging on screening of pancreatic diseases will be provided.

Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis

Dual energy CT (DECT)with image acquisition at two different photon X-ray levels allows the characterization of a specific tissue or material/elements, the extrapolation of virtual unenhanced and monoenergetic images, and the quantification of iodine uptake; such special capabilities make the DECT the perfect technique to support oncological imaging for tumor detection and characterization and treatment monitoring, while concurrently reducing the dose of radiation and iodine and improving the metal artifact reduction. Even though its potential in the field of oncology has not been fully explored yet, DECT is already widely used today thanks to the availability of different CT technologies, such as dual-source, single-source rapid-switching, single-source sequential, single-source twin-beam and dual-layer technologies. Moreover DECT technology represents the future of the imaging innovation and it is subject to ongoing development that increase according its clinical potentiality, in particular in the field of oncology. This review points out recent state-of-the-art in DECT applications in gland tumors, with special focus on its potential uses in the field of oncological imaging of endocrine and exocrine glands.

Therapeutic response assessment in pancreatic ductal adenocarcinoma: society of abdominal radiology review paper on the role of morphological and functional imaging techniques

Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related death in the United States and is projected to be the second by 2030. Systemic combination chemotherapy is considered an essential first-line treatment for the majority of patients with PDA, in both the neoadjuvant and palliative settings. In addition, a number of novel therapies are being tested in clinical trials for patients with advanced PDA. In all cases, accurate and timely assessment of treatment response is critical to guide therapy, reduce drug toxicities and cost from a failing therapy, and aid adaptive clinical trials. Conventional morphological imaging has significant limitations, especially in the context of determining primary tumor response and resectability following neoadjuvant therapies. In this article, we provide an overview of current therapy options for PDA, highlight several morphological imaging findings that may be helpful to reduce over-staging following neoadjuvant therapy, and discuss a number of emerging imaging, and non-imaging, tools that have shown promise in providing a more precise quantification of disease burden and treatment response in PDA.

Improved detectability of hypoattenuating focal pancreatic lesions by dual-layer computed tomography using virtual monoenergetic images

Background

Multidetector CT is the mainstay for radiologic evaluation of pancreatic pathology. Still, imaging of focal pancreatic lesions using MDCT is faced by a number of challenges that are related to the limited contrast between the lesion and surrounding parenchyma, such as detecting early-stage pancreatic cancer and subtle features of cystic lesions that point to malignancy. Dual-layer CT is the first dual-energy CT machine based on separation of high- and low-energy photons at the detector level. If improved contrast between the lesions and normal pancreatic parenchyma could be achieved on CT images, we may expect enhanced CT detection of pancreatic lesions. The purpose of this study was to evaluate whether virtual monoenergetic reconstructions generated using contrast-enhanced dual-layer CT could improve detectability of hypoattenuating focal pancreatic lesions compared to conventional polyenergetic reconstructions.

Results

Fifty-four lesions were identified and verified by histopathology or follow-up CT, MRCP, and/or EUS along with clinical data. Across the virtual monoenergetic spectrum, 40 KeV images had the highest contrast-to-noise and signal-to-noise ratios (p < 0.001, p < 0.001) and were significantly higher than conventional images (p < 0.001). Subjective scores for lesion visibility at low kiloelectron volt monoenergetic (40 and 50 KeV) images greatly exceeded conventional images (p < 0.001).

Conclusion

Low kiloelectron volt monoenergetic reconstructions of contrast-enhanced dual-layer CT significantly improve detectability of hypoattenuating focal pancreatic lesions compared to conventional polyenergetic reconstructions.

Benefit of dual-layer spectral CT in emergency imaging of different organ systems

Computed tomography (CT) has been the first choice of imaging technique in the emergency department and has a crucial role in many acute conditions. Since its implementation, spectral CT has gained widespread application with the potential to improve diagnostic performance and impact patient care. In spectral CT, images are acquired at two different energy levels allowing this technique to differentiate tissues by exploiting their energy-dependent attenuation properties. Dual-layer spectral CT provides additional information with its material decomposition applications that include virtual non-contrast imaging, iodine density, and effective atomic number (Zeff) maps along with virtual monoenergetic images without the need for preselection of a protocol. This review aims to demonstrate its added value in the emergency department in different organ systems enabling better evaluation of inflammatory and ischaemic conditions, assessment of organ perfusion, tissue/lesion characterisation and mass detection, iodine quantification, and the use of lower volumes of contrast medium. With improved diagnostic performance, spectral CT could also aid in rapid decision-making to determine the treatment method in many acute conditions without increased radiation dose to the patient.

Pancreatic Ductal Adenocarcinoma: Interface Enhancement Gradient Measured on Dual-Energy CT Images Improves Prognostic Evaluation

Purpose

To investigate the prognostic value of differential enhancement on baseline dual-energy CT images in patients with treatment-naive pancreatic ductal adenocarcinoma (PDAC), with a focus on tumor-host interface characterization.

Materials and Methods

This was a retrospective, institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study of 158 consecutive adult patients (mean age, 68 years; age range, 40.9-88.9 years; 50% women) with histopathologically proven, treatment-naive PDAC, who had undergone multiphasic pancreatic dual-energy CT from December 2011 to March 2017. Regions of interest in tumor core, tumor border, pancreas border with tumor, nontumoral pancreas, and aorta were recorded on pancreatic parenchymal phase (PPP) dual-energy CT 70-keV, 52-keV, and iodine material density (MD) images, plus portal venous phase (PVP) conventional CT images. Enhancement gradient (delta) across the tumor-pancreas interface was calculated. Delta was evaluated combining the dual-energy CT values with the PVP values and as individual predictors. Receiver operating characteristic analysis with logistic regression was used to determine the optimal cut point for each dual-energy CT delta to predict disease outcome based on highest Youden index. Survival curves were generated using Kaplan-Meier method, and comparison between two independent groups (high and low delta) was evaluated with log-rank test. Clinical outcomes included overall survival and distant metastasis-free survival. Three independent blinded radiologists visually scored tumor conspicuity (subjective delta score) on a 1-5 scale, and agreement was evaluated with κ statistic.

Results

Ninety-three patients had advanced stage (50 locally advanced and 43 metastatic) and 65 had lower stage (48 resectable and 17 borderline resectable) tumors. Patients with high delta tumors (≥ 40 HU) on either 70-keV PPP images or conventional PVP images had significantly shorter overall survival compared with those with low delta tumors (< 40 HU) in both early stage PDAC (13.5 months vs 23.3 months; hazard ratio [HR], 1.87; 95% confidence interval [CI]: 1.01, 3.5; P = .04) and advanced stage PDAC (10.8 months vs 18.0 months; HR, 2.1; 95% CI: 1.28, 3.6; P = .003). Qualitative visual scoring of tumor conspicuity also showed shorter overall survival in patients with more conspicuous tumors. Highest interreader agreement for subjective delta score was 0.73 and 0.60 using iodine MD and 52-keV images, respectively.

Conclusion

Increased quantitative and qualitative border conspicuity (high delta) is associated with shorter survival in patients with PDAC. Agreement on the subjective qualitative characterization of PDAC borders is best achieved using iodine MD and lower-energy simulated monoenergetic images at pancreatic protocol dual-energy CT.Keywords: Abdomen/GI, CT, CT-Dual Energy, CT-Quantitative, PancreasSupplemental material is available for this article.© RSNA, 2020.

CTPA with a conventional CT at 100 kVp vs. a spectral-detector CT at 120 kVp: Comparison of radiation exposure, diagnostic performance and image quality

•

With SD-CT, increased radiation exposure is not present.

•

In the current study, CTDI_vol was lower with SD-CT than with C-CT, even when 100 kVp was used for the latter.

•

With SD-CT, higher levels of diagnostic performance and image quality can be achieved.

•

SD-CT may be the system of choice due to the availability of spectral data and thus additional image information.

Purpose

To compare CT pulmonary angiographies (CTPAs) as well as phantom scans obtained at 100 kVp with a conventional CT (C-CT) to virtual monochromatic images (VMI) obtained with a spectral detector CT (SD-CT) at equivalent dose levels as well as to compare the radiation exposure of both systems.

Material and Methods

In total, 2110 patients with suspected pulmonary embolism (PE) were examined with both systems. For each system (C-CT and SD-CT), imaging data of 30 patients with the same mean CT dose index (4.85 mGy) was used for the reader study. C-CT was performed with 100 kVp and SD-CT was performed with 120 kVp; for SD-CT, virtual monochromatic images (VMI) with 40, 60 and 70 keV were calculated. All datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence and diagnostic performance (sensitivity, specificity). Contrast-to-noise ratio (CNR) for different iodine concentrations was evaluated in a phantom study.

Results

CNR was significantly higher with VMI at 40 keV compared to all other datasets. Subjective image quality as well as sensitivity and specificity showed the highest values with VMI at 60 keV and 70 keV. Hereby, a significant difference to 100 kVp (C-CT) was found for image quality. The highest sensitivity was found using VMI at 60 keV with a sensitivity of more than 97 % for all localizations of PE. For diagnostic confidence and subjective contrast, highest values were found with VMI at 40 keV.

Conclusion

Higher levels of diagnostic performance and image quality were achieved for CPTAs with SD-CT compared to C-CT given similar dose levels. In the clinical setting SD-CT may be the modality of choice as additional spectral information can be obtained.

Impact of spectral body imaging in patients suspected for occult cancer: a prospective study of 503 patients

Objectives

To investigate the diagnostic impact and performance of spectral dual-layer detector CT in the detection and characterization of cancer compared to conventional CE-CT.

Methods

In a national workup program for occult cancer, 503 patients (286 females and 217 males) were prospectively enrolled for a contrast-enhanced spectral CT scan. The readings were performed with and without spectral data available. A minimum of 3 months between interpretations was implemented to minimize recall bias. The sequence of reads for the individual patient was randomized. Readers were blinded for patient identifiers and clinical outcome. Two radiologists with 9 and 33 years of experience performed the readings in consensus. If disagreement, a third radiologist with 11 years of experience determined the outcome of the reading

Results

Significantly more cancer findings were identified on the spectral reading. In 73 cases of proven cancer, we found a sensitivity of 89% vs 77% and a specificity of 77% vs 83% on spectral CT compared to conventional CT. A slight increase in reading time in spectral images of 82 s was found (382 vs 300, p < 0.001). For all cystic lesions, the perceived diagnostic certainty increased from 30% being completely certain to 96% most pronounced in the kidney, liver, thyroid, and ovaries. And adding the spectral information to the reading gave a decrease in follow-up examination for diagnostic certainty (0.25 vs 0.81 per reading, p < 0.001).

Conclusion

The use of contrast-enhanced spectral CT increases the confidence of the radiologists in correct characterization of various lesions and minimizes the need for supplementary examinations.

Key Points

• Spectral CT is associated with a higher sensitivity, but a slightly lower specificity compared to conventional CT.

• Spectral CT increases the confidence of the radiologists.

• The need for supplementary examinations is decreased, with only a slight increase in reading times.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-06878-7) contains supplementary material, which is available to authorized users.

Advanced imaging techniques for chronic pancreatitis

MRI and MRCP play an important role in the diagnosis of chronic pancreatitis (CP) by imaging pancreatic parenchyma and ducts. MRI/MRCP is more widely used than computed tomography (CT) for mild to moderate CP due to its increased sensitivity for pancreatic ductal and gland changes; however, it does not detect the calcifications seen in advanced CP. Quantitative MR imaging offers potential advantages over conventional qualitative imaging, including simplicity of analysis, quantitative and population-based comparisons, and more direct interpretation of detected changes. These techniques may provide quantitative metrics for determining the presence and severity of acinar cell loss and aid in the diagnosis of chronic pancreatitis. Given the fact that the parenchymal changes of CP precede the ductal involvement, there would be a significant benefit from developing MRI/MRCP-based, more robust diagnostic criteria combining ductal and parenchymal findings. Among cross-sectional imaging modalities, multi-detector CT (MDCT) has been a cornerstone for evaluating chronic pancreatitis (CP) since it is ubiquitous, assesses primary disease process, identifies complications like pseudocyst or vascular thrombosis with high sensitivity and specificity, guides therapeutic management decisions, and provides images with isotropic resolution within seconds. Conventional MDCT has certain limitations and is reserved to provide predominantly morphological (e.g., calcifications, organ size) rather than functional information. The emerging applications of radiomics and artificial intelligence are poised to extend the current capabilities of MDCT. In this review article, we will review advanced imaging techniques by MRI, MRCP, CT, and ultrasound.

Dual-Energy CT: A Paradigm Shift in Acute Traumatic Abdomen

Abdominal trauma, one of the leading causes of death under the age of 45, can be broadly classified into blunt and penetrating trauma, based on the mechanism of injury. Blunt abdominal trauma usually results from motor vehicle collisions, fall from heights, assaults, and sports and is more common than penetrating abdominal trauma, which is usually seen in firearm injuries and stab wounds. In both blunt and penetrating abdominal trauma, an optimized imaging approach is mandatory to exclude life-threatening injuries. Easy availability of the portable ultrasound in the emergency department and trauma bay makes it one of the most commonly used screening imaging modalities in the abdominal trauma, especially to exclude hemoperitoneum. Evaluation of the visceral and vascular injuries in a hemodynamically stable patient, however, warrants intravenous contrast-enhanced multidetector computed tomography scan. Dual-energy computed tomography with its postprocessing applications such as iodine selective imaging and virtual monoenergetic imaging can reliably depict the conspicuity of traumatic solid and hollow visceral and vascular injuries.

White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

The role of low keV virtual monochromatic imaging in increasing the conspicuity of primary breast cancer in dual-energy spectral thoracic CT examination for staging purposes

Background

The additive value of dual-energy spectral computerized tomography (DESCT) in breast cancer imaging is still unknown.

Purpose

To investigate the role of DESCT in improving the conspicuity of primary breast cancer.

Material and Methods

Twenty-nine patients who were histopathologically diagnosed with breast cancer and underwent DESCT for staging of lung metastasis were evaluated retrospectively. The visual conspicuity of breast cancer was scored by two readers separately in reconstructed virtual monochromatic images obtained at 40, 60, 80, and 100 keV. A circular region of interest slightly smaller than the maximum contrasted portion of the primary breast cancer was manually placed. Iodine enhancement (HU) and iodine content (mg/mL) values of tumor, normal breast tissue and pectoral muscle, and contrast-to-noise values of images at four different energy levels were calculated.

Results

The lesion conspicuity score peaked at 40-keV series for both readers and was significantly higher than those at other energy levels (all P < 0.001). Lesion iodine enhancement was highest at 40-keV virtual monochromatic image reconstructions ( P < 0.001). The iodine content was significantly higher in tumor than normal breast tissue, and pectoral muscle ( P < 0.001). The highest contrast-to-noise value was obtained at 60 keV (4.0 ± 2.5), followed by 40 keV (3.9 ± 2.2), without a significant difference ( P = 0.33).

Conclusion

The conspicuity of primary breast cancer was significantly higher in low keV virtual monochromatic images obtained by DESCT. This gives us hope that DESCT may play an effective role in detecting incidental breast lesions. It also raises the question of whether quantitative values obtained by DESCT can be used for characterization of primary breast lesion.

Diagnostic value of spectral reconstructions in detecting incidental skeletal muscle metastases in CT staging examinations

Background

To investigate if iodine density overlay maps (IDO) and virtual monoenergetic images at 40 keV (VMI_40keV) acquired from spectral detector computed tomography (SDCT) can improve detection of incidental skeletal muscle metastases in whole-body CT staging examinations compared to conventional images.

Methods

In total, 40 consecutive cancer patients who underwent clinically-indicated, contrast-enhanced, oncologic staging SDCT were included at this retrospective study: 16 patients with n = 108 skeletal muscle metastases confirmed by prior or follow-up CT, ¹⁸F-FDG-PET, MRI or histopathology, and a control group of 24 patients without metastases. Four independent readers performed blinded, randomized visual detection of skeletal muscle metastases in conventional images, IDO and VMI_40keV, indicating diagnostic certainty for each lesion on a 5-point Likert scale. Quantitatively, ROI-based measurements of attenuation (HU) in conventional images and VMI_40keV and iodine concentration in IDO were conducted. CNR was calculated and receiver operating characteristics (ROC) analysis of quantitative parameters was performed.

Results

Regarding subjective assessment, IDO (63.2 (58.5–67.8) %) and VMI_40keV (54.4 (49.6–59.2) %) showed an increased sensitivity for skeletal muscle metastases compared to conventional images (39.8 (35.2–44.6) %). Specificity was comparable in VMI_40keV (69.8 (63.2–75.8) %) and conventional images (69.2 (60.6–76.9) %), while in IDO, it was moderately increased to 74.2 (65.3–78.4) %. Quantitative image analysis revealed that CNR of skeletal muscle metastases to circumjacent muscle was more than doubled in VMI_40keV (25.8 ± 11.1) compared to conventional images (10.0 ± 5.3, p ≤ 0.001). Iodine concentration obtained from IDO and HU acquired from VMI_40kev (AUC = 0.98 each) were superior to HU attenuation in conventional images (AUC = 0.94) regarding differentiation between healthy and metastatic muscular tissue (p ≤ 0.05).

Conclusions

IDO and VMI_40keV provided by SDCT improve diagnostic accuracy in the assessment of incidental skeletal muscle metastases compared to conventional CT.