Dual energy spectral CT imaging of insulinoma-Value in preoperative diagnosis compared with conventional multi-detector CT

Quantitative evaluation of pancreatic neuroendocrine tumors utilizing dual-source CT perfusion imaging

OBJECTIVE

We aimed to quantitatively analyze the perfusion characteristics of pancreatic neuroendocrine tumors (pNETs) utilizing dual-source CT imaging.

METHODS

Dual-source CT perfusion scans were obtained from patients with pNETs confirmed by surgical or biopsy pathology. Perfusion parameters, including blood flow (BF), blood volume (BV), capillary permeability surface (PS), mean transit time (MTT), contrast transit time to the start (TTS), and contrast transit time to the peak (TTP), were statistically analyzed and compared with nearby healthy tissue. Time density curves (TDCs) were plotted to further understand the dynamic enhancement characteristics of the tumors. Additionally, receiver operating characteristic curves (ROCs) were generated to assess their diagnostic value.

RESULTS

Twenty patients with pNETs, containing 26 lesions, were enrolled in the study, including 6 males with 8 lesions and 14 females with 18 lesions. The average values of BF, BV, PS, MTT, TTP and TTS for the 26 lesions (336.61 ± 216.72 mL/100mL/min, 41.96 ± 16.99 mL/100mL, 32.90 ± 11.91 mL/100 mL/min, 9.44 ± 4.40 s, 19.14 ± 5.6 s, 2.57 ± 1.6 s) were different from those of the adjacent normal pancreatic tissue (44.32 ± 55.35 mL/100mL/min, 28.64 ± 7.95 mL/100mL, 26.69 ± 14.88 mL/100 mL/min, 12.89 ± 3.69 s, 20.33 ± 5.18 s, 2.69 ± 1.71 s). However, there were no statistical differences in PS and TTS between the lesions and the adjacent normal pancreatic tissue (P > 0.05). The areas under the ROC curve for BF, BV, and PS were all greater than 0.5, whereas the areas under the ROC curve for MTT, TTP, and TTS were all less than 0.5.

CONCLUSION

CT perfusion parameters such as BF, BV, MTT, and TTP can distinguish pNETs from healthy tissue. The area under the ROC curve for BF, BV, and PS demonstrates substantial differentiating power for diagnosing pNET lesions.

Impact of virtual monochromatic images of different low-energy levels in dual-energy CT on radiomics models for predicting muscle invasion in bladder cancer

OBJECTIVE

The purpose of this study was to investigate the impact of different low-energy virtual monochromatic images (VMIs) in dual-energy CT on the performance of radiomics models for predicting muscle invasive status in bladder cancer (BCa).

MATERIALS AND METHODS

A total of 127 patients with pathologically proven muscle-invasive BCa (n = 49) and non-muscle-invasive BCa (n = 78) were randomly allocated into the training and test cohorts at a ratio of 7:3. Feature extraction was performed on the venous phase images reconstructed at 40, 50, 60 and 70-keV (single-energy analysis) or in combination (multi-energy analysis). Recursive feature elimination (RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to select the most relevant features associated with BCa. Models were built using a support vector machine (SVM) classifier. Diagnostic performance was assessed through receiver operating characteristic curves, evaluating sensitivity, specificity, accuracy, precision, and the area-under-the curve (AUC) values.

RESULTS

In the test cohort, the multi-energy model achieved the best diagnostic performance with AUC, sensitivity, specificity, accuracy, and precision of 0.917, 0.800, 0.833, 0.821, and 0.750, respectively. Conversely, the single-energy model exhibited lower AUC and sensitivity in predicting the muscle invasion status.

CONCLUSIONS

By combining information from VMIs of various energies, the multi-energy model displays superior performance in preoperatively predicting the muscle invasion status of bladder cancer.

Innovative imaging approaches for neuroendocrine tumor characterization: Combined dual energy CT and perfusion protocol implementation

The article addresses the diagnostic value of the combined use of computed tomography (CT) perfusion and dual-energy CT (DECT) in patients with neuroendocrine tumors. It emphasizes the heterogeneity and complexity of these neoplasms, primarily affecting the gastrointestinal tract, bronchopulmonary system, and pancreas. While conventional CT is widely employed in their diagnosis, the combination of CT perfusion and dual-energy CT offers greater precision, particularly in detecting synchronous tumors and characterizing their vascularization. A clinical case of a patient with chronic abdominal symptoms, whose diagnosis was facilitated using both combined techniques, is presented. The discussion explores how CT perfusion assesses tumor vascularization and how dual-energy CT improves soft tissue differentiation, resulting in increased diagnostic accuracy. It is highlighted that this approach not only enhances detection rates but also positively impacts clinical management and healthcare costs. Therefore, the importance of considering these advanced tools in the diagnosis of neuroendocrine tumors to improve diagnostic precision and efficiency in patient care is underscored.

Assessing muscle invasion in bladder cancer via virtual biopsy: a study on quantitative parameters and classical radiomics features from dual-energy CT imaging

OBJECTIVE

To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa).

MATERIALS AND METHODS

A retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA).

RESULTS

The normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively.

CONCLUSION

The proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa.

[Imaging of pancreatic neuroendocrine tumors]

BACKGROUND

Neuroendocrine tumors of the pancreas have a broad biological spectrum. The treatment decision is based on an optimal diagnosis with regard to the local findings and possible locoregional and distant metastases. In addition to purely morphologic imaging procedures, functional parameters are playing an increasingly important role in imaging.

OBJECTIVES

Prerequisites for optimal imaging of the pancreas, technical principles are provided, and the advantages and disadvantages of common cross-sectional imaging techniques as well as clinical indications for these special imaging methods are discussed.

MATERIALS AND METHODS

Guidelines, basic and review papers will be analyzed.

RESULTS

Neuroendocrine tumors of the pancreas have a broad imaging spectrum. Therefore, there is a need for multimodality imaging in which morphologic and functional techniques support each other. While positron emission tomography/computed tomography (PET/CT) can determine the presence of one or more lesions and its/their functional status of the tumor, magnetic resonance imaging (MRI) efficiently identifies the location, relationship to the main duct and the presence of liver metastases. CT allows a better vascular evaluation, even in the presence of anatomical variants as well as sensitive detection of lung metastases.

CONCLUSIONS

Knowledge of the optimal combination of imaging modalities including clinical and histopathologic results and dedicated imaging techniques is essential to achieve an accurate diagnosis to optimize treatment decision-making and to assess therapy response.

Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses

ABSTRACT

Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.

Dual-Energy CT in Oncologic Imaging

Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas

PURPOSE

To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9).

METHODS

This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test.

RESULTS

The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076).

CONCLUSIONS

Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

Pretreatment dual-energy CT for predicting early response to induction chemotherapy and survival in nasopharyngeal carcinoma

OBJECTIVES

To evaluate the predictive performance of pretreatment dual-energy CT (DECT) for early response to induction chemotherapy and survival in nasopharyngeal carcinoma (NPC).

METHODS

In this retrospective study, 56 NPC patients who underwent pretreatment DECT scans with posttreatment follow-up were enrolled. The DECT-derived normalised iodine concentration (nIC), effective atomic number (Zeff), 40-180 keV (20 keV interval), and Mix-0.3 value of the tumour lesions were measured to predict the early response to induction chemotherapy and survival in nasopharyngeal carcinoma. The Mann‒Whitney U test, ROC analysis, Kaplan‒Meier method with log-rank test, and Cox proportional hazards model were performed to evaluate the predictive performance of DECT parameters, respectively.

RESULTS

Among all DECT-derived parameters, ROC analysis showed the predictive performances of nIC and Zeff values for early objective response to induction chemotherapy (AUCs of 0.803 and 0.826), locoregional failure-free survival (AUCs of 0.786 and 0.767), progression-free survival (AUCs of 0.856 and 0.731) and overall survival (AUCs of 0.765 and 0.799) in NPC patients, respectively (all p < 0.05). Moreover, multivariate analysis showed that a high nIC value was an independent predictor of poor survival in NPC. In addition, survival analysis indicated that NPC patients with higher nIC values in primary tumours tend to have lower 5-year locoregional failure-free survival, progression-free survival and overall survival rates than those with lower nIC values.

CONCLUSIONS

DECT-derived nIC and Zeff values can predict early response to induction chemotherapy and survival in NPC; in particular, a high nIC value is an independent predictive factor of poor survival in NPC.

CLINICAL RELEVANCE STATEMENT

Preoperative dual-energy computed tomography may provide predictive value for early response and survival outcomes in patients with nasopharyngeal carcinoma, and facilitate their clinical management.

KEY POINTS

• Pretreatment dual-energy computed tomography helps to predict early response to therapy and survival in NPC. • NIC and Zeff values derived from dual-energy computed tomography can predict early objective response to induction chemotherapy and survival in NPC. • A high nIC value is an independent predictive factor of poor survival in NPC.

Dual-Energy, Spectral and Photon Counting Computed Tomography for Evaluation of the Gastrointestinal Tract

The use of dual-energy computed tomography (CT) allows for reconstruction of energy- and material-specific image series. The combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can improve lesion detection and disease characterization in the gastrointestinal tract in comparison with single-energy CT.

Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging

Purpose

This study aimed to investigate the value of quantified extracellular volume fraction (fECV) derived from dual-energy CT (DECT) for predicting the survival outcomes of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE).

Materials and methods

A total of 63 patients with HCC who underwent DECT before treatment were retrospectively included. Virtual monochromatic images (VMI) (70 keV) and iodine density images (IDI) during the equilibrium phase (EP) were generated. The tumor VMI-fECV and IDI-fECV were measured and calculated on the whole tumor (Whole) and maximum enhancement of the tumor (Maximum), respectively. Univariate and multivariate Cox models were used to evaluate the effects of clinical and imaging predictors on overall survival (OS) and progression-free survival (PFS).

Results

The correlation between tumor VMI-fECV and IDI-fECV was strong (both p< 0.001). The Bland-Altman plot between VMI-fECV and IDI-fECV showed a bias of 5.16% for the Whole and 6.89% for the Maximum modalities, respectively. Increasing tumor VMI-fECV and IDI-fECV were positively related to the effects on OS and PFS (both p< 0.05). The tumor IDI-fECV-Maximum was the only congruent independent predictor in patients with HCC after TACE in the multivariate analysis on OS (p = 0.000) and PFS (p = 0.028). Patients with higher IDI-fECV-Maximum values had better survival rates above the optimal cutoff values, which were 35.42% for OS and 29.37% for PFS.

Conclusion

The quantified fECV determined by the equilibrium-phase contrast-enhanced DECT can potentially predict the survival outcomes of patients with HCC following TACE treatment.

New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function

The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to the new powerful tubes. Iterative reconstruction algorithms and artificial intelligence are helpful for the management of image noise during image reconstruction. Functional information is provided by spectral CT (dual-energy and photon counting CT) and perfusion CT.

The evaluation of portal hypertension in cirrhotic patients with spectral computed tomography

BACKGROUND

Iodine concentrations measured using dual-energy spectral CT (DESCT) have been recently proposed as providing good performance for examining tissues hemodynamics.

PURPOSE

To evaluate the diagnostic efficacy of DESCT-derived parameters in evaluating portal venous pressure in patients with liver cirrhosis.

MATERIAL AND METHODS

A total of 71 patients with liver cirrhosis who underwent percutaneous transhepatic portal vein puncture procedures were included in this study. All participants underwent DESCT and gastrointestinal endoscopy within one month before the operation. The direct portal venous pressure of each participant was measured preoperatively.

RESULTS

Stepwise multivariate linear regression analysis showed that the iodine concentrations in the portal vein and hepatic parenchyma during the portal venous phase and the platelet count were independently correlated with the direct portal venous pressure (P < 0.001, P < 0.001, and P = 0.030, respectively). Receiver operating characteristic analysis revealed that the normalized iodine concentration of the hepatic parenchyma had the best performance for identifying clinically significant portal hypertension (≥10 mmHg), esophageal varices, and high-risk esophageal varices (the area under the curve values were 0.951, 0.932, and 0.960, respectively).

CONCLUSION

The normalized iodine concentration of the hepatic parenchyma is a reliable parameter to non-invasively assess portal venous pressure in patients with liver cirrhosis.

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study

OBJECTIVES

To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an abdominal clinical study.

METHODS

An elliptical phantom with five different iodine concentrations (1-12 mgI/mL) was imaged five times with fast-kilovoltage-switching DECT for three target volume CT dose indexes. All images were reconstructed using filtered back-projection, iterative reconstruction (two levels), and DLIR algorithms. Measured and nominal iodine concentrations were compared among the algorithms. Contrast-enhanced CT of the abdomen with the same scanner was acquired in clinical patients. In arterial and portal venous phase images, iodine concentration, image noise, and coefficients of variation for four locations were retrospectively compared among the algorithms. One-way repeated-measures analyses of variance were used to evaluate differences in the iodine concentrations, standard deviations, coefficients of variation, and percentages of error among the algorithms.

RESULTS

In the phantom study, the measured iodine concentrations were equivalent among the algorithms: within ± 8% of the nominal values, with root-mean-square deviations of 0.08-0.36 mgI/mL, regardless of radiation dose. In the clinical study (50 patients; 35 men; mean age, 68 ± 11 years), iodine concentrations were equivalent among the algorithms for each location (all p > .99). Image noise and coefficients of variation were lower with DLIR than with the other algorithms (all p < .01).

CONCLUSIONS

The DLIR algorithm reduced image noise and variability of iodine concentration values compared with other reconstruction algorithms in the fast-kilovoltage-switching dual-energy CT.

KEY POINTS

• In the phantom study, standard deviations and coefficients of variation in iodine quantification were lower on images with the deep learning image reconstruction algorithm than on those with other algorithms. • In the clinical study, iodine concentrations of measurement location in the upper abdomen were consistent across four reconstruction algorithms, while image noise and variability of iodine concentrations were lower on images with the deep learning image reconstruction algorithm.

Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms

PURPOSE

To explore the optimal energy level of dual-layer spectral detector computed tomography (DLCT) images of pancreatic neuroendocrine neoplasms (pNENs) and investigate the value in their detection.

METHODS

This retrospective analysis included 134 pNEN patients with 136 lesions; they underwent contrast-enhanced DLCT scanning with histopathological confirmation of pNENs. Virtual monoenergetic images (VMI) of 40-100 keV, iodine concentration map (IC map), Z-effective atomic number map (Zeff map), and conventional images were analysed. The optimal energy level was obtained by comparing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The lesion detection rates of DLCT and conventional images were compared. Subjective image analysis was performed by two readers who assessed the image quality and lesion conspicuity on a 5-point scale.

RESULTS

The SNR of VMIs from 40 to 80 keV (arterial phase, P < 0.001; venous phase, P < 0.05) and CNR from 40 to 60 keV (arterial and venous phases, each P < 0.05) were higher than that of conventional images; VMI_40keV showed the highest SNR and CNR. There was a good inter-reader agreement between the two reviewers (Kappa values > 0.61); the scores of Zeff and IC maps were higher than those of conventional images and VMI_40keV (P < 0.05). The detection performance of DLCT images was better than conventional images.

CONCLUSIONS

The VMI_40keV demonstrated the best CNR and SNR of pNENs compared to other VMIs. Zeff and IC maps improve objective image quality and reader preference compared to conventional images. These findings could possess important clinical implications in formulating treatment strategies.

Diagnostic Management of Gastroenteropancreatic Neuroendocrine Neoplasms: Technique Optimization and Tips and Tricks for Radiologists

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) comprise a heterogeneous group of neoplasms, which derive from cells of the diffuse neuroendocrine system that specializes in producing hormones and neuropeptides and arise in most cases sporadically and, to a lesser extent, in the context of complex genetic syndromes. Furthermore, they are primarily nonfunctioning, while, in the case of insulinomas, gastrinomas, glucagonomas, vipomas, and somatostatinomas, they produce hormones responsible for clinical syndromes. The GEP-NEN tumor grade and cell differentiation may result in different clinical behaviors and prognoses, with grade one (G1) and grade two (G2) neuroendocrine tumors showing a more favorable outcome than grade three (G3) NET and neuroendocrine carcinoma. Two critical issues should be considered in the NEN diagnostic workup: first, the need to identify the presence of the tumor, and, second, to define the primary site and evaluate regional and distant metastases. Indeed, the primary site, stage, grade, and function are prognostic factors that the radiologist should evaluate to guide prognosis and management. The correct diagnostic management of the patient includes a combination of morphological and functional evaluations. Concerning morphological evaluations, according to the consensus guidelines of the European Neuroendocrine Tumor Society (ENETS), computed tomography (CT) with a contrast medium is recommended. Contrast-enhanced magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI), is usually indicated for use to evaluate the liver, pancreas, brain, and bones. Ultrasonography (US) is often helpful in the initial diagnosis of liver metastases, and contrast-enhanced ultrasound (CEUS) can solve problems in characterizing the liver, as this tool can guide the biopsy of liver lesions. In addition, intraoperative ultrasound is an effective tool during surgical procedures. Positron emission tomography (PET-CT) with FDG for nonfunctioning lesions and somatostatin analogs for functional lesions are very useful for identifying and evaluating metabolic receptors. The detection of heterogeneity in somatostatin receptor (SSTR) expression is also crucial for treatment decision making. In this narrative review, we have described the role of morphological and functional imaging tools in the assessment of GEP-NENs according to current major guidelines.

Neuroendocrine neoplasm imaging: protocols by site of origin

With the relatively low incidence of neuroendocrine neoplasms (NEN), most radiologists are not familiar with their optimal imaging techniques. The imaging protocols for NENs should be tailored to the site of origin to accurately define local extension of NEN at time of staging. Patterns of spread and recurrence should be taken into consideration when choosing protocols for detection of recurrence and metastases. This paper will present the recommended CT and MRI imaging protocols for gastro-enteric and pancreatic NENs based on site of origin or predominant pattern of metastatic disease, and explain the rationale for MRI contrast type, contrast timing, as well as specific sequences in MRI. We will also briefly comment on PET/CT and PET/MRI imaging protocols.

Pancreatic neuroendocrine neoplasms: a 2022 update for radiologists

Pancreatic neuroendocrine neoplasms (PaNENs) are a unique group of pancreatic neoplasms with a wide range of clinical presentations and behaviors. Given their heterogeneous appearance and increasing detection on cross-sectional imaging, it is essential that radiologists understand the variable presentation and distinctions PaNENs display compared to other pancreatic neoplasms. Additionally, some of these neoplasms may be hormonally functional, and it is imperative that radiologists be aware of the common clinical presentations of hormonally active PaNENs. Knowledge of PaNEN pathology and treatments may influence which imaging modality is optimal for each patient. Each imaging modality used for PaNENs has distinct advantages and disadvantages, particularly in different treatment settings. Thus, the focus of this manuscript is to provide an update for the radiologist on PaNEN pathology, imaging, and treatments.

Value of CT spectral imaging in the differential diagnosis of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node: A STARD compliant article

To investigate the imaging characteristics of sarcoidosis and Hodgkin's lymphoma based on mediastinal enlarged lymph node using spectral CT and evaluate whether the quantitative information can improve the differential diagnosis of these diseases. This retrospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Overall, 21 patients with sarcoidosis and 39 patients with Hodgkin's lymphoma were examined with CT spectral imaging during the arterial phase (AP) and venous phase (VP). The CT values on 40 to 140 keV monochromatic images and iodine (water) concentrations of enlarged lymph nodes were obtained in AP and VP. Iodine concentrations (ICs) were normalized to the iodine concentration in the aorta. The differences in normalized iodine concentrations (NICs) and hounsfield units (HU) curve slop (λHU) were calculated. Anatomical distribution of mediastinal lymph nodes and morphologic features were also compared. Receiver operating characteristic curves were generated to help establish threshold values for the parameters required for the significant differentiation of sarcoidosis from lymphomas. The CT values on 40 to 100 keV monochromatic images in AP and 40 to 50 keV in VP were higher in sarcoidosis than those in Hodgkin's lymphoma, the differences were statistically significant (P < .05); NICs during the AP and λHU during the AP (VP) in patients with sarcoidosis differed significantly from those in patients with Hodgkin's lymphoma. Receiver operating characteristic curves analysis showed that the monochromatic CT value on 40 keV in AP had the highest sensitivity (71.4%) and specificity (100%) in differentiating sarcoidosis from Hodgkin's lymphoma. The anatomic distribution, coalescence, calcification, compression, enhancement pattern and enhancement degree of the mediastinal enlarged lymph node differed significantly between the groups (P < .05). The combination of monochromatic CT value, NICs and λHU had higher sensitivity and specificity than did those of conventional qualitative CT image analysis during the combined phases. CT spectral imaging has promising potential for the diagnostic differentiation of Hodgkin's lymphomas and sarcoidosis. The monochromatic CT value, iodine content and λHU could be valuable parameters for differentiating Hodgkin's lymphomas and sarcoidosis based on mediastinal enlarged lymph node.

Dual energy CT applications in oncological imaging

Cancer is the second leading cause of death in the United States, killing more than 600.000 people each year.¹ Despite several screening programs available, cancer diagnosis is often made incidentally during imaging studies performed for other reasons. Once the diagnosis is made, treatment assessment and surveillance of these patients heavily rely on radiological tools. Computed tomography (CT) in particular is one of the most commonly ordered modalities due to wide availability even in the most remote locations, and fast results. However, conventional CT often cannot definitively characterize a neoplastic lesion unless it was tailored toward answering a specific question. Furthermore, characterizing small lesions can be difficult with CT. An innovative technique called dual-energy CT (DECT) offers solutions to some of the challenges of conventional CT in oncological imaging.

Advances in the imaging of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms comprise a heterogeneous group of tumors that differ in their pathogenesis, hormonal syndromes produced, biological behavior and consequently, in their requirement for and/or response to specific chemotherapeutic agents and molecular targeted therapies. Various imaging techniques are available for functional and morphological evaluation of these neoplasms and the selection of investigations performed in each patient should be customized to the clinical question. Also, with the increased availability of cross sectional imaging, these neoplasms are increasingly being detected incidentally in routine radiology practice. This article is a review of the various imaging modalities currently used in the evaluation of neuroendocrine neoplasms, along with a discussion of the role of advanced imaging techniques and a glimpse into the newer imaging horizons, mostly in the research stage.

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.

Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen

OBJECTIVES

To evaluate the usefulness of deep learning image reconstruction (DLIR) to improve the image quality of dual-energy computed tomography (DECT) of the abdomen, compared to hybrid iterative reconstruction (IR).

METHODS

This study included 40 patients who underwent contrast-enhanced DECT of the abdomen. Virtual monochromatic 40-, 50-, and 70-keV and iodine density images were reconstructed using three reconstruction algorithms, including hybrid IR (ASiR-V50%) and DLIR (TrueFidelity) at medium- and high-strength level (DLIR-M and DLIR-H, respectively). The standard deviation of attenuation in liver parenchyma was measured as image noise. The contrast-to-noise ratio (CNR) for the portal vein on portal venous phase CT was calculated. The vessel conspicuity and overall image quality were graded on a 5-point scale ranging from 1 (poor) to 5 (excellent). The comparative scale of lesion conspicuity in 47 abdominal solid lesions was evaluated on a 5-point scale ranging from 0 (best) to -4 (markedly inferior).

RESULTS

The image noise of virtual monochromatic 40-, 50 -, and 70-keV and iodine density images was significantly decreased by DLIR compared to hybrid IR (p < 0.0001). The CNR was significantly higher in DLIR-H and DLIR-M than in hybrid IR (p < 0.0001). The vessel conspicuity and overall image quality scores were also significantly greater in DLIR-H and DLIR-M than in hybrid IR (p < 0.05). The lesion conspicuity scores for DLIR-M and DLIR-H were significantly higher than those for hybrid IR in the virtual monochromatic image of all energy levels (p ≤ 0.001).

CONCLUSIONS

DLIR improves vessel conspicuity, CNR, and lesion conspicuity of virtual monochromatic and iodine density images in abdominal contrast-enhanced DECT, compared to hybrid IR.

KEY POINTS

• Deep learning image reconstruction (DLIR) is useful for reducing image noise and improving the CNR of visual monochromatic 40-, 50-, and 70-keV images in dual-energy CT. • DLIR can improve lesion conspicuity of abdominal solid lesions on virtual monochromatic images compared to hybrid iterative reconstruction. • DLIR can also be applied to iodine density maps and significantly improves their image quality.

Utility of Quantitative Metrics from Dual-Layer Spectral-Detector CT for Differentiation of Pancreatic Neuroendocrine Tumor and Neuroendocrine Carcinoma

Background: The 2019 WHO classification separates neuroendocrine neoplasms (NENs) into neuroendocrine tumors (NET) and neuroendocrine carcinomas (NEC), which are considered to represent pathologically distinct entities warranting different management approaches. Dual-layer spectral-detector CT (DLCT) may aid their differentiation through specific material decomposition. Objective: To assess the utility of quantitative metrics derived from DLCT for the differentiation of pancreatic NET and NEC. Methods: This retrospective study included 104 patients (mean age 51±13 years; 53 women, 51 men) with pathologically confirmed NEN [89 NET, including 22 grade 1, 48 grade 2, and 19 grade 3 (G3); 15 NEC], who underwent multiphase DLCT within 15 days before biopsy or resection. Two radiologists independently placed ROIs to record tumor attenuation, iodine concentration (IC), and effective atomic number (Zeff) across phases, and also assessed qualitative features (composition, homogeneity, margins, calcifications, main pancreatic duct dilation, vascular invasion, lymphadenopathy). Interreader agreement was assessed. Mean values between readers were obtained for quantitative measures; consensus was reached for qualitative features. NET and NEC were compared using multivariable regression analysis and ROC analysis. Results: Interobserver agreement, expressed as intraclass correlation coefficients, ranged from 0.879 to 0.992 for quantitative metrics, and, expressed as kappa coefficients, from 0.763 to 0.823 for qualitative features. In multivariable analysis of qualitative and quantitative features, significant independent predictors of NEC (P<.05) were IC in portal venous phase (1.3 mg/mL in NEC vs 2.7 mg/mL in NET), Zeff in portal venous phase (8.1 vs 8.6), and attenuation in portal venous phase (78.2 vs 113.5 HU). AUC for predicting NEC was 0.897 for IC, 0.884 for Zeff, 0.921 for combination of IC and Zeff, and 0.855 for attenuation. Predicted probability based on combination of IC and Zeff achieved sensitivity of 93.3% and specificity of 80.9% for NEC. Significant independent predictors (P<.05) for differentiating G3 NET and NEC were IC (1.3 vs 2.0 mg/mL; AUC=0.789) and attenuation (78.2 vs 90.3 HU; AUC=0.647), both measured in portal venous phase. Conclusion: Incorporation of DLCT-metrics improves differentiation of NET and NEC compared with conventional CT attenuation and qualitative features. Clinical Impact: DLCT may help select patients with pancreatic NENs for platinum-based chemotherapies.

A critical analysis of laparoscopic and open approaches to sporadic pancreatic insulinoma resection in the modern era

BACKGROUND

A single center experience with sporadic pancreatic insulinoma was analyzed to develop an algorithm for modern surgical management.

METHODS

Thirty-four patients undergoing surgery from 2001 to 2019 were reviewed.

RESULTS

The majority underwent enucleation (10 laparoscopic, 15 open). Laparoscopy was performed in 22 patients with conversion to open in 11, mostly related to the proximity of the tumor to the pancreatic duct (n = 4). Tumors on the anterior and posterior surface of the pancreas in all anatomic locations were completed with laparoscopic enucleation. Overall, the clinically-relevant postoperative pancreatic fistula (CR-POPF) rate was 21%, with no difference between laparoscopic versus open enucleation (10% vs 20%, p = 0.50) or enucleation versus resection (16% vs 33%, p = 0.27). Laparoscopic enucleation had shorter median hospital length of stay (LOS) compared with open (4 vs 7 days, p = 0.02).

CONCLUSIONS

Laparoscopic enucleation does not increase the CR-POPF risk and provides an advantage with a shorter hospital LOS in select patients. Tumor location and relationship to the pancreatic duct guide surgical decision-making. These findings highlight tumor-specific criteria that would benefit from a minimally invasive approach.

Virtual Monoenergetic Images of Dual-Energy CT-Impact on Repeatability, Reproducibility, and Classification in Radiomics

Simple Summary

Virtual monoenergetic images from dual-energy CT are incrementally used in routine clinical practice. Thus, radiomic analysis will be more often performed on these images in the future. This study characterized the test–retest repeatability and reproducibility of radiomic features from virtual monoenergetic images and their impact on machine-learning-based lesion classification. The results of this study provide a basis to improve radiomic analyses and identify the role of feature stability in classification tasks when using virtual monoenergetic imaging with different scan or reconstruction parameters in multicenter clinical studies.

Abstract

The purpose of this study was to (i) evaluate the test–retest repeatability and reproducibility of radiomic features in virtual monoenergetic images (VMI) from dual-energy CT (DECT) depending on VMI energy (40, 50, 75, 120, 190 keV), radiation dose (5 and 15 mGy), and DECT approach (dual-source and split-filter DECT) in a phantom (ex vivo), and (ii) to assess the impact of VMI energy and feature repeatability on machine-learning-based classification in vivo in 72 patients with 72 hypodense liver lesions. Feature repeatability and reproducibility were determined by concordance–correlation–coefficient (CCC) and dynamic range (DR) ≥0.9. Test–retest repeatability was high within the same VMI energies and scan conditions (percentage of repeatable features ranging from 74% for SFDE mode at 40 keV and 15 mGy to 86% for DSDE at 190 keV and 15 mGy), while reproducibility varied substantially across different VMI energies and DECTs (percentage of reproducible features ranging from 32.8% for SFDE at 5 mGy comparing 40 with 190 keV to 99.2% for DSDE at 15 mGy comparing 40 with 50 keV). No major differences were observed between the two radiation doses (<10%) in all pair-wise comparisons. In vivo, machine learning classification using penalized regression and random forests resulted in the best discrimination of hemangiomas and metastases at low-energy VMI (40 keV), and for cysts at high-energy VMI (120 keV). Feature selection based on feature repeatability did not improve classification performance. Our results demonstrate the high repeatability of radiomics features when keeping scan and reconstruction conditions constant. Reproducibility diminished when using different VMI energies or DECT approaches. The choice of optimal VMI energy improved lesion classification in vivo and should hence be adapted to the specific task.

Pancreatic Neuroendocrine Neoplasms: CT Spectral Imaging in Grading

RATIONALE AND OBJECTIVES

The purpose of this study was to define the CT spectral imaging characteristics of pancreatic neuroendocrine neoplasms (PNENs) and evaluate their potential for differential diagnosis of nonlow grade (non-LG) PNENs from low grade (LG) PNENs.

MATERIALS AND METHODS

CT spectral imaging data of 54 pathologically proven PNENs were retrospectively reviewed. Patients were divided into two groups: 40 cases with grade 1 in LG PNENs group and 14 cases with grade 2 and grade 3 in non-LG PNENs group.

RESULTS

Gender, calcification, inhomogeneity, invasiveness, PD dilatation, lymph node enlargement, size, normalized iodine (water) concentration in arterial phase (AP) (Iodine (ap)), normalized effective-Z (Z_ap), slope of normalized CT spectral curves in both AP, and portal venous phase were found to be significant variables for differentiating non-LG PNENs from LG PNENs (p < 0.05). Non-LG PNENs had larger size and lower Z_ap and Iodine (ap) than LG PNENs. The tumor size, Z_ap and Iodine (ap) had fair to good diagnostic performance with the area under receiver-operating-characteristic curve (AUC) 0.843, 0.733, and 0.728, respectively. Multivariate analysis with logistic regression had higher AUC (p<0.05) than all the single parameters except for size.

CONCLUSION

There were significant differences in CT spectral imaging parameters between non-LG and LG PNENs. Tumor size was the most promising independent parameter and the combination of quantitative parameters with qualitative parameters is the best predictor in differentiating of non-LG PNENs from LG PNENs. CT spectral imaging can help determine the malignancy of PNENs, which can better assist in surgical planning.

Clinical value of energy spectrum curves of dual-energy computer tomography may help to predict pathological grading of gastric adenocarcinoma

BACKGROUND

To explore the clinical value of energy spectrum curves of dual-energy computer tomography (CT) in quantitative evaluation of different pathological grades of gastric adenocarcinoma.

METHODS

A total of 62 patients with 36 poorly, 25 moderately and 1 well differentiated gastric adenocarcinomas confirmed pathologically were collected. Dual-energy CT plain and enhanced scanning were undergone before operation. Dual-Energy software was used to measure the slope of the energy spectrum curves (λ) in arterial and venous phases (VPs) after image reconstruction. Patients were divided into two groups according to the pathological results, including well and moderately differentiated gastric adenocarcinoma group and poorly differentiated gastric adenocarcinoma group. Data of each group were analyzed by independent sample t-test. Receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficiency of the corresponding parameters.

RESULTS

There were significant differences in λ values of 40-50, 40-60, 40-80, 40-90, 40-100, 40-120, 40-130, 40-140 and 40-150 keV energy ranges in VP between the well and moderately differentiated group and poorly differentiated group (P<0.05), but no significant differences in λ values of different energy ranges in arterial phase (AP) between the two groups (P>0.05). And the area under curve in 40-120 keV energy range was the largest in VP. λ_40-120keV=2.69 was selected as the diagnostic threshold with the maximum Youden index, the sensitivity and specificity were 61.1% and 76%, respectively.

CONCLUSIONS

The energy spectrum curve of dual-energy CT had certain diagnostic value in the quantitative evaluation of pathological grading of gastric adenocarcinoma.

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.

Dictionary learning based image-domain material decomposition for spectral CT

The potential huge advantage of spectral computed tomography (CT) is that it can provide accurate material identification and quantitative tissue information by material decomposition. However, material decomposition is a typical inverse problem, where the noise can be magnified. To address this issue, we develop a dictionary learning based image-domain material decomposition (DLIMD) method for spectral CT to achieve accurate material components with better image quality. Specifically, a set of image patches are extracted from the mode-1 unfolding of normalized material images decomposed by direct inversion to train a unified dictionary using the K-SVD technique. Then, the DLIMD model is established to explore the redundant similarities of the material images, where the split-Bregman is employed to optimize the model. Finally, more constraints (i.e. volume conservation and the bounds of each pixel within material maps) are integrated into the DLIMD model. Numerical phantom, physical phantom and preclinical experiments are performed to evaluate the performance of the proposed DLIMD in material decomposition accuracy, material image edge preservation and feature recovery.

Pancreatic neuroendocrine tumours: spectrum of imaging findings

Pancreatic neuroendocrine tumours (pNETs) are rare and heterogeneous group of neoplasms presenting with a wide variety of symptoms and biological behaviour, from indolent to aggressive ones. pNETs are stratified into functional or non-functional, because of their ability to produce metabolically active hormones. pNETs can be an isolate phenomenon or a part of a hereditary syndrome like von Hippel-Lindau syndrome or neurofibromatosis-1. The incidence has increased in the last years, also because of the improvement of cross-sectional imaging. Computed tomography (CT), magnetic resonance imaging (MRI) and functional imaging are the mainstay imaging modalities used for tumour detection and disease extension assessment, due to easy availability and better contrast/spatial resolution. Radiological imaging plays a fundamental role in detection, characterization and surveillance of pNETs and is involved in almost every stage of patients' management. Moreover, with specific indications and techniques, interventional radiology can also play a role in therapeutic management. Surgery is the treatment of choice, consisting of either partial pancreatectomy or enucleation of the primary tumour. This article reviews the radiologic features of different pNETs as well as imaging mimics, in order to help radiologists to avoid potential pitfalls, to reach the correct diagnosis and to support the multidisciplinary team in establishing the right treatment.

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.

Differential diagnosis of chromophobe renal cell carcinoma and papillary renal cell carcinoma with dual-energy spectral computed tomography

BACKGROUND

Computed tomography (CT) image features of chromophobe renal cell carcinoma (ChRCC) and papillary renal cell carcinoma (PRCC) are, occasionally, sometimes difficult to identify. However, spectral CT might provide quantitative parameters to differentiate them.

PURPOSE

To differentiate between ChRCC and PRCC with quantitative parameters using spectral CT.

MATERIAL AND METHODS

Forty cases of RCC confirmed with pathological tests were analyzed retrospectively (27 cases of PRCC and 13 cases of ChRCC). All patients underwent non-enhanced CT and dual-phase contrast-enhanced CT scans. For each lesion, the CT value of monochromatic images as well as iodine and water concentrations were measured, and the slope of spectrum curve was calculated. Data were analyzed using Student's t-test. Sensitivity and specificity of the quantitative parameters were analyzed using the receiver operating characteristic (ROC) curve.

RESULTS

During the cortex phase (CP) and parenchyma phase (PP), the CT value and slope of spectrum curve of ChRCC were higher than those of PRCC, and significant differences were observed at low energy levels (40-70 keV). Normalized iodine concentration of ChRCC and that of PRCC was significantly different during CP and PP (P < 0.05). The water (iodine) concentrations of ChRCC and PRCC in CP and PP were not statistically different (P > 0.05). All the ROCs for parameters were above the reference line.

CONCLUSION

Spectral CT may help increase the diagnostic accuracy of differentiating PRCC from ChRCC using a quantitative analysis.

[Gastroenteropancreatic neuroendocrine neoplasms-Heterogeneity, management and perspectives of treatment and research]

The term neuroendocrine neoplasms (NEN) encompasses a molecularly and biologically very heterogeneous group of tumors, which have in common their origin in neuroendocrine cells. The also very heterogeneous subgroup of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) is the best classified and investigated group. This article provides a systematic review of the current classification, diagnostics and treatment options of GEP-NEN. In order to achieve a better overview, it was consciously decided not to use an approach based on the primary localization. Instead, a thematic organization according to classification, clinical phenotype, diagnostics and treatment was chosen.

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.

Extracellular volume fraction determined by equilibrium contrast-enhanced dual-energy CT as a prognostic factor in patients with stage IV pancreatic ductal adenocarcinoma

OBJECTIVES

To evaluate the feasibility of equilibrium contrast-enhanced dual-energy CT (DECT), as compared with single-energy CT (SECT) and to calculate extracellular volume (ECV) fraction to predict the survival outcomes of pancreatic ductal adenocarcinoma (PDAC) patients with distant metastases (stage IV) treated with chemotherapy.

METHODS

The study cohort included a total of 66 patients with stage IV PDAC who underwent DECT before systemic chemotherapy between July 2014 and March 2017. Unenhanced and 120-kVp equivalent images during the equilibrium phase were used to calculate tumor SECT-derived ECV fractions, and iodine density images were obtained from equilibrium-phase DECT for DECT-derived ECV fractions. Correlations between SECT- and DECT-derived ECV fractions were identified using the Pearson correlation coefficient and Bland-Altman analysis. The effects of clinical prognostic factors and tumor SECT- and DECT-derived ECV fractions on progression-free survival (PFS) and overall survival (OS) were assessed by univariate and multivariate analyses using Cox proportional hazards models.

RESULTS

The correlation between SECT- and DECT-derived ECV fractions was strong (r = 0.965; p < 0.001). The Bland-Altman plot between SECT- and DECT-derived ECV fractions showed a small bias (- 3.4%). Increasing tumor SECT- and DECT-derived ECV fractions were associated with a positive effect on PFS (SECT, p = 0.002; DECT, p = 0.007) and OS (DECT, p = 0.014; DECT, p = 0.015). Only tumor DECT-derived ECV fraction was an independent predictor of PFS (p = 0.018) and OS (p = 0.022) in patients with stage IV PDAC treated with chemotherapy on multivariate analysis.

CONCLUSIONS

The ECV fraction determined by equilibrium contrast-enhanced DECT can potentially predict the survival of patients with stage IV PDAC treated with chemotherapy.

KEY POINTS

• Extracellular volume fraction of stage IV pancreatic ductal adenocarcinoma determined by dual-energy CT was strongly correlated to that with single-energy CT (r = 0.965, p < 0.001). • Tumor extracellular volume fraction was an independent predictor of progression-free survival (p = 0.018) and overall survival (p = 0.022). • Extracellular volume fraction determined by dual-energy CT could be a useful imaging biomarker to predict the survival of patients with stage IV pancreatic ductal adenocarcinoma treated with chemotherapy.

The multidisciplinary team for gastroenteropancreatic neuroendocrine tumours: the radiologist's challenge

Background

Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are a heterogeneous group of tumours. An effective diagnosis requires a multimodal approach that combines evaluation of clinical symptoms, hormonelevels, radiological and nuclear imaging, and histological confirmation. Imaging plays a critical role in NETs diagnosis, prognosis and management, so the radiologists are important members of the multidisciplinary team. During diagnostic work-up two critical issues are present: firstly the need to identify tumor presence and secondly to define the primary site and assess regional and distant metastases.

Conclusions

The most appropriate imaging technique depends on the type of neuroendocrine tumour and the availability of specialized imaging techniques and expertise. There is no general consensus on the most efficient imaging pathway, reflecting the challenge in reliably detection of these tumours.

Noninvasive Assessment of Portal Hypertension Using Spectral Computed Tomography

BACKGROUND

Early diagnosis of portal hypertension is imperative for timely treatment to reduce the mortality rate. However, there is still no adequate method to noninvasively and accurately assess the portal hypertension in routine clinical practice.

PURPOSE

We aimed to evaluate the accuracy of parameters measured using dual energy spectral computed tomography (LightSpeed CT750 HD) in assessing portal venous pressure in patients with liver cirrhosis.

STUDY

Forty-five patients with liver cirrhosis who underwent percutaneous transhepatic portal vein puncture as part of their treatment for liver disease were enrolled in this study. Measurement of direct portal venous pressure was performed preoperatively. All patients underwent dual energy spectral computed tomography within 3 days before their operations.

RESULTS

The iodine concentrations of portal vein and hepatic parenchyma during the portal venous phase and the alanine aminotransferase level were found to be independently correlated with the direct portal venous pressure according to stepwise multivariate linear regression analysis (P<0.001, 0.004, and 0.024, respectively). In a receiver operating characteristic analysis, the area under the receiver operating characteristic of iodine concentrations of the portal vein (ICPV) for identifying clinically significant portal hypertension (≥10 mm Hg) was significantly higher than that of iodine concentrations of hepatic parenchyma (ICliver) and the alanine aminotransferase level (0.944, 0.825, and 0.301, respectively). The threshold ICPV of 58.27 yielded a sensitivity of 93.8%, specificity of 69.2%, positive predictive value of 88.2%, and negative predictive value of 81.8%, respectively.

CONCLUSIONS

ICPV values may be a useful tool in noninvasively assessing the portal venous pressure and identifying clinically significant portal hypertension in liver cirrhosis.

Contribution of DECT in detecting serosal invasion of gastric cancer

Background/aim

This study aimed to investigate the relationship between the iodine concentration (IC) of perigastric fat tissue as assessed by dual-energy computed tomography (DECT) and serosal invasion of gastric cancer.

Materials and methods

A total of 41 patients underwent preoperative staging evaluation for gastric cancer using DECT between July 2015 and March 2018. Patients were divided into 2 groups based on pathology results: serosal invasion (stage T4a) and intact serosa (stages T1–T3). Cutoff values, the diagnostic efficacy of IC in the perigastric fat tissue, and the perigastric fat tissue/tumor (P/T) ratio were determined.

Results

Among the 41 patients, 22 had stage T4a gastric cancer and 19 patients had gastric cancer with a stage lower than T4a. The mean IC of perigastric fat tissue and the P/T ratio were significantly higher in patients with serosal invasion than in those with intact serosa (P < 0.001). During the arterial phase, the area under the curve (AUC) was 0.915 and 0.854 for the IC of perigastric fat tissue and the P/T ratio, respectively. During the venous phase, the AUC was 0.890 and 0.876 for the IC of perigastric fat tissue and the P/T ratio, respectively.

Conclusion

The IC in the perigastric fat tissue seems to be a reliable indicator for serosal invasion of gastric cancer.

Dual-Energy CT of the Pancreas

This article explores the technical background of dual-energy CT (DECT) imaging along with its basic principles, before turning to a review of the various DECT applications specific to pancreatic imaging. In light of the most recent literature, we will review the constellation of DECT applications available for pancreatic imaging in both oncologic and non-oncologic applications. We emphasize the increased lesion conspicuity and the improved tissue characterization available with DECT post-processing tools. Finally, future clinical applications and opportunities for research will be overviewed.

Weight-adapted ultra-low-dose pancreatic perfusion CT: radiation dose, image quality, and perfusion parameters

PURPOSE

We evaluate the reliability and feasibility of weight-adapted ultra-low-dose pancreatic perfusion CT.

METHODS

A total of 100 (47 men, 53 women) patients were enrolled prospectively and were assigned to five groups (A, B, C, D, and E) with different combination of tube voltage and tube current according to their body weight. Radiation dose parameters including volume CT dose index (CTDI) and dose-length product (DLP) were recorded. Image quality was evaluated both subjectively and objectively (noise, signal-to-noise ratio, contrast-to-noise ratio). Perfusion parameters including blood flow (BF), blood volume (BV), and permeability (PMB) were measured. The dose, image quality measurements, and perfusion parameters were compared between the five groups using one-way analysis of variance (ANOVA).

RESULTS

Radiation dose reached 8.7 mSv in patients under 50 kg and was 18.9 mSv in patients above 80 kg. The mean subjective image quality score was above 4.45 on a 5-point scale with good agreement between two radiologists. Groups A-D had equivalent performance on objective image quality (P > 0.05), while Group E performed even better (P < 0.05). No significant differences emerged in comparison with perfusion parameters (BF, BV, PMB) of normal pancreas parenchyma between the five groups.

CONCLUSION

Weight-adapted ultra-low-dose pancreatic perfusion CT can effectively reduce radiation dose without prejudice to image quality, and the perfusion parameters of normal parenchyma are accurate and reliable.

Role of dual energy CT to improve diagnosis of non-traumatic abdominal vascular emergencies

Computed tomography angiography (CTA) is the modality of choice to evaluate abdominal vascular emergencies (AVE). CTA protocols are often complex and require acquisition of multiple phases to enable a variety of diagnosis such as acute bleeding, pseudoaneurysms, bowel ischemia, and dissection. With single energy CT (SECT), differentiating between calcium, coagulated blood, and contrast agents can be challenging based on their attenuation, especially when in small quantity or present as a mixture. With dual-energy CT (DECT), virtual monoenergetic (VM) and material decomposition (MD) image reconstructions enable more robust tissue characterization, improve contrast-enhancement, and reduce beam hardening artifacts. This article will demonstrate how radiologists can utilize DECT for various clinical scenarios in assessment of non-traumatic AVE.

Value of CT spectral imaging in the differential diagnosis of thymoma and mediastinal lymphoma

Objective:

To investigate the imaging characteristics of thymoma and mediastinal lymphoma using spectral CT and evaluate whether the quantitative information can improve the differential diagnosis of these diseases.

Methods:

This retrospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Overall, 39 patients with mediastinal tumors (24 thymomas and 15 mediastinal lymphomas) were examined with CT spectral imaging during the arterial phase (AP) and venous phase (VP). Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in normalized iodine concentrations (NICs), HU curve slop(λ_HU), and the differences between AP and VP for CT values of lesions in 70 Kev were calculated. The two-sample t-test was performed to compare quantitative parameters, and non-quantitative parameters were compared with the Chi-square test (Fisher exact). Receiver operating characteristic (ROC) curves were generated to help establish threshold values for the parameters required for the significant differentiation of thymomas from mediastinal lymphomas. Two readers qualitatively assessed the lesion types according to the imaging features. The sensitivity and specificity of the qualitative and quantitative studies were compared.

Results:

NICs during the VP and λ_HU during the AP in patients with mediastinal lymphomas differed significantly from those in patients with thymomas. The mean NICs during the VP were 0.28 ± 0.08  mg ml⁻¹ (±standard deviation) vs 0.49 ± 0.15  mg ml⁻¹, respectively. The λ_HU during the AP was 0.69 ± 0.17 vs 1.26 ± 0.74, respectively. The NICs during the VP and λ_HU during the AP had high sensitivity and specificity in differentiating mediastinal lymphomas from thymomas. The tumor location, margin, necrosis, presence of swollen mediastinal lymph nodes, relationship with adjacent vessels, and enhancement pattern differed significantly between the groups (p < 0.05). The combination of NICs and λ_HU had higher sensitivity and specificity than did those of conventional qualitative CT image analysis during the combined phases.

Conclusion:

CT spectral imaging has promising potential for the diagnostic differentiation of mediastinal lymphomas and thymomas. The iodine content and λ_HU could be valuable parameters for differentiating thymomas and mediastinal lymphomas.

Advances in knowledge:

The iodine content and λ_HU, provided by spectral CT, could be used as new parameters to distinguish mediastinal lymphomas from thymomas.

The Concentration of Iodine in Perigastric Adipose Tissue: A Novel Index for the Assessment of Serosal Invasion in Patients with Gastric Cancer after Neoadjuvant Chemotherapy

OBJECTIVE

This study aims to explore the association between iodine concentration (IC) in perigastric adipose tissue (PAT), quantified by dual-energy computed tomography (DECT) and serosal invasion (SI) in patients with gastric cancer post-neoadjuvant chemotherapy (NAC).

METHODS

Forty-three patients with T4-staged gastric cancer were enrolled. IC and standardized IC in PAT (ICPAT and SICPAT) were quantified by DECT pre and post NAC. A postoperative pathologic examination was performed to stage gastric cancer.

RESULTS

After NAC, a total of 43 participants were assigned to group A with 13 patients and group B with 30 patients according to the results of the postoperative pathologic examination. The accuracy of conventional CT in identifying SI was 74.42%. Differences of variations between pre- and post- NAC ICPAT, SICPAT, ∆ICPAT, and ∆SICPAT were observed respectively (p < 0.05). Intragroup ICPAT and SICPAT also changed significantly after NAC (p < 0.05). The area under the ROC curve was 0.929, with the threshold of ∆SICPAT reaching 0.095. The sensitivity, specificity, and accuracy of SICPAT in identifying post-NAC SI were 92.30, 86.70, and 88.37% respectively. Moreover, the 2 measurements in the same patient maintain a high level of consistency.

CONCLUSION

These results showed that SICPAT is a reliable index for identifying post-NAC SI.