Contrast-enhanced dual-energy CT of gastrointestinal stromal tumors: is iodine-related attenuation a potential indicator of tumor response?

Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy

Effective neoadjuvant chemotherapy (NAC) can improve the survival of patients with locally progressive gastric cancer, but chemotherapeutics do not always exhibit good efficacy in all patients. Therefore, accurate preoperative evaluation of the effect of neoadjuvant therapy and the appropriate selection of surgery time to minimize toxicity and complications while prolonging patient survival are key issues that need to be addressed. This paper reviews the role of three imaging methods, morphological, functional, radiomics, and artificial intelligence (AI)-based imaging, in evaluating NAC pathological reactions for gastric cancer. In addition, the advantages and disadvantages of each method and the future application prospects are discussed.

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.

Thoracic Diseases: Technique and Applications of Dual-Energy CT

Dual-energy computed tomography (DECT) is one of the most promising technological innovations made in the field of imaging in recent years. Thanks to its ability to provide quantitative and reproducible data, and to improve radiologists' confidence, especially in the less experienced, its applications are increasing in number and variety. In thoracic diseases, DECT is able to provide well-known benefits, although many recent articles have sought to investigate new perspectives. This narrative review aims to provide the reader with an overview of the applications and advantages of DECT in thoracic diseases, focusing on the most recent innovations. The research process was conducted on the databases of Pubmed and Cochrane. The article is organized according to the anatomical district: the review will focus on pleural, lung parenchymal, breast, mediastinal, lymph nodes, vascular and skeletal applications of DECT. In conclusion, considering the new potential applications and the evidence reported in the latest papers, DECT is progressively entering the daily practice of radiologists, and by reading this simple narrative review, every radiologist will know the state of the art of DECT in thoracic diseases.

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign

OBJECTIVES

To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs).

MATERIALS AND METHODS

A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application.

RESULTS

The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC_65keV-AP = 0.92, AUC_65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability.

CONCLUSIONS

Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Z_eff-AP was significantly superior to conventional model in the discrimination of SPSNs.

The Role of Dual-Energy CT for the Assessment of Liver Metastasis Response to Treatment: Above the RECIST 1.1 Criteria

Imaging assessment of liver lesions is fundamental to predict therapeutic response and improve patient survival rates. Dual-Energy Computed Tomography (DECT) is an increasingly used technique in the oncologic field with many emerging applications. The assessment of iodine concentration within a liver lesion reflects the biological properties of the tumor and provides additional information to radiologists that is normally invisible to the human eye. The possibility to predict tumor aggressiveness and therapeutic response based on quantitative and reproducible parameters obtainable from DECT images could improve clinical decisions and drive oncologists to choose the best therapy according to metastasis biological features. Moreover, in comparison with standard dimensional criteria, DECT provides further data on the cancer microenvironment, especially for patients treated with antiangiogenic-based drugs, in which tumor shrinkage is a late parameter of response. We investigated the predictive role of DECT in the early assessment of liver metastasis response to treatment in comparison with standard dimensional criteria during antiangiogenetic-based therapy.

Spectral CT in Oncology

BACKGROUND

Spectral CT is gaining increasing clinical importance with multiple potential applications, including oncological imaging. Spectral CT-specific image data offers multiple advantages over conventional CT image data through various post-processing algorithms, which will be highlighted in the following review.

METHODOLOGY

The purpose of this review article is to provide an overview of potential useful oncologic applications of spectral CT and to highlight specific spectral CT pitfalls. The technical background, clinical advantages of primary and follow-up spectral CT exams in oncology, and the application of appropriate spectral tools will be highlighted.

RESULTS/CONCLUSIONS

Spectral CT imaging offers multiple advantages over conventional CT imaging, particularly in the field of oncology. The combination of virtual native and low monoenergetic images leads to improved detection and characterization of oncologic lesions. Iodine-map images may provide a potential imaging biomarker for assessing treatment response.

KEY POINTS

· The most important spectral CT reconstructions for oncology imaging are virtual unenhanced, iodine map, and virtual monochromatic reconstructions.. · The combination of virtual unenhanced and low monoenergetic reconstructions leads to better detection and characterization of the vascularization of solid tumors.. · Iodine maps can be a surrogate parameter for tumor perfusion and potentially used as a therapy monitoring parameter.. · For radiotherapy planning, the relative electron density and the effective atomic number of a tissue can be calculated..

CITATION FORMAT

· Sauerbeck J, Adam G, Meyer M. Onkologische Bildgebung mittels Spektral-CT. Fortschr Röntgenstr 2023; 195: 21 - 29.

Quantitative dual-energy CT techniques in the abdomen

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

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.

Predicting axillary lymph node metastasis in breast cancer using the similarity of quantitative dual-energy CT parameters between the primary lesion and axillary lymph node

PURPOSE

To evaluate the similarity of quantitative dual-energy computed tomography (DECT) parameters between the primary breast cancer lesion and axillary lymph node (LN) for predicting LN metastasis.

MATERIALS AND METHODS

This retrospective study included patients with breast cancer who underwent contrast-enhanced DECT between July 2019 and April 2021. Relationships between LN metastasis and simple DECT parameters, similarity of DECT parameters, and pathological and morphological features were analyzed. ROC curve analysis was used to evaluate diagnostic ability.

RESULTS

Overall, 137 LNs (39 metastases and 98 non-metastases) were evaluated. Significant differences were observed in some pathological (nuclear grade, estrogen receptor status, and Ki67 index) and morphological characteristics (shortest and longest diameters of the LN, longest-to-shortest diameter ratio, and hilum), most simple DECT parameters, and all DECT similarity parameters between the LN metastasis and non-metastasis groups (all, P < 0.001-0.004). The shortest diameter of the LN (odds ratio 2.22; 95% confidence interval 1.47, 3.35; P < 0.001) and the similarity parameter of 40-keV attenuation (odds ratio, 2.00; 95% confidence interval 1.13, 3.53; P = 0.017) were independently associated with LN metastasis compared to simple DECT parameters of 40-keV attenuation (odds ratio 1.01; 95% confidence interval 0.99, 1.03; P =0.35). The AUC value of the similarity parameters for predicting metastatic LN was 0.78-0.81, even in cohorts with small LNs (shortest diameter < 5 mm) (AUC value 0.73-0.78).

CONCLUSION

The similarity of the delayed-phase DECT parameters could be a more useful tool for predicting LN metastasis than simple DECT parameters in breast cancer, regardless of LN size.

Dual-Layer Spectral Detector CT in Comparison with FDG-PET/CT for the Assessment of Lymphoma Activity

PURPOSE

 In patients with malignant lymphoma, disease activity is recommended to be assessed by FDG-PET/CT and the Deauville five-point scale (5-PS). The purpose of this study was to explore the potential of iodine concentration measured in contrast-enhanced dual-layer spectral detector CT (SDCT) as an alternative surrogate parameter for lymphoma disease activity by investigating its correlation with maximum standardized uptake values (SUV_max) and 5-PS.

MATERIALS AND METHODS

 25 patients were retrospectively analyzed. Contrast-enhanced SDCT and FDG-PET/CT were performed in the same treatment interval within at most 3 months. CT attenuation values (AV), absolute iodine concentrations (aIC), and normalized iodine concentrations (nIC) of lymphoma lesions were correlated with SUV_max using Spearman's rank correlation coefficient. The performance of aIC and nIC to detect lymphoma activity (defined as 5-PS > 3) was determined using ROC curves.

RESULTS

 60 lesions were analyzed, and 31 lesions were considered active. AV, aIC, and nIC all correlated significantly with SUV_max. The strongest correlation (Spearman ρ = 0.71; p < 0.001) and highest area under the ROC curve (AUROC) for detecting lymphoma activity were observed for nIC normalized to inferior vena cava enhancement (AUROC = 0.866). The latter provided sensitivity, specificity, and diagnostic accuracy of 87 %, 75 %, and 80 %, respectively, at a threshold of 0.20. ROC analysis for AV (AUROC = 0.834) and aIC (AUROC = 0.853) yielded similar results.

CONCLUSION

 In malignant lymphomas, there is a significant correlation between metabolic activity as assessed by FDG-PET/CT and iodine concentration as assessed by SDCT. Iodine concentration shows promising diagnostic performance for detecting lymphoma activity and may represent a potential imaging biomarker.

KEY POINTS

  · Iodine concentration correlates significantly with SUVmax in lymphoma patients. · Iodine concentration may represent a potential imaging biomarker for detecting lymphoma activity. · Normalization of iodine concentration improves diagnostic performance of iodine concentration.

CITATION FORMAT

· Gehling K, Mokry T, Do TD et al. Dual-Layer Spectral Detector CT in Comparison with FDG-PET/CT for the Assessment of Lymphoma Activity. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1735-3477.

Application of machine learning with multiparametric dual-energy computed tomography of the breast to differentiate between benign and malignant lesions

BACKGROUND

Multiparametric dual-energy computed tomography (mpDECT) is widely used to differentiate various kinds of tumors; however, the data regarding its diagnostic performance with machine learning to diagnose breast tumors is limited. We evaluated univariate analysis and machine learning performance with mpDECT to distinguish between benign and malignant breast lesions.

METHODS

In total, 172 patients with 214 breast lesions (55 benign and 159 malignant) who underwent preoperative dual-phase contrast-enhanced DECT were included in this retrospective study. Twelve quantitative features were extracted for each lesion, including CT attenuation (precontrast, arterial, and venous phases), the arterial-venous phase difference in normalized effective atomic number (nZ_eff), normalized iodine concentration (NIC), and slope of the spectral Hounsfield unit (HU) curve (λ_Hu). Predictive models were developed using univariate analysis and eight machine learning methods [logistic regression, extreme gradient boosting (XGBoost), stochastic gradient descent (SGD), linear discriminant analysis (LDA), adaptive boosting (AdaBoost), random forest (RF), decision tree, and linear support vector machine (SVM)]. Classification performances were assessed based on the area under the receiver operating characteristic curve (AUROC). The best performances of the conventional univariate analysis and machine learning methods were compared using the Delong test.

RESULTS

The univariate analysis showed that the venous phase λ_Hu had the highest AUROC (0.88). Machine learning with mpDECT achieved an excellent and stable diagnostic performance, as shown by the mean classification performances in the training dataset (AUROC, 0.88-0.99) and testing (AUROC, 0.83-0.96) datasets. The performance of the AdaBoost model based on mpDECT was more stable than the other machine learning models and superior to the univariate analysis (AUROC, 0.96 vs. 0.88; P<0.001).

CONCLUSIONS

The performance of the AdaBoost classifier based on mpDECT data achieved the highest mean accuracy compared to the other machine learning models and univariate analysis in differentiating between benign and malignant breast lesions.

Dual-Energy CT Vital Iodine Tumor Burden for Response Assessment in Patients With Metastatic GIST Undergoing TKI Therapy: Comparison to Standard CT and FDG PET/CT Criteria

Background: CT-based criteria for assessing gastroinstestinal stromal tumor (GIST) response to tyroskine kinase inhibitor (TKI) therapy are limited partly because tumor attenuation is influenced by treatment-related changes including hemorrhage and calcification. Iodine concentration may be less impacted by such changes. Objective: To determine whether DECT vital iodine tumor burden (TB) provides improved differentiation between responders and non-responders in patients with metastatic GIST undergoing TKI therapy compared to established CT and PET/CT criteria. Methods: An anthropomorphic phantom with spherical inserts mimicking GIST lesions of varying iodine concentrations and having non-enhancing central necrotic cores underwent DECT to determine a threshold iodine concentration. Forty patients (median age 57 years; 25 women, 15 men) treated with TKI for metaststic GIST were retrospectively evaluated. Patients underwent baseline and follow-up DECT and FDG PET/CT. Response assessment was performed using RECIST 1.1, modified Choi (mChoi), vascular tumor burden (VTB), DECT vital iodine TB, and European Organization for Research and Treatment of Cancer (EORTC PET) criteria. DECT vital iodine TB used the same percentage changes as RECIST 1.1 response categories. Progression-free survival (PFS) was compared between responders and non-responders for each response criteria using Cox proportional hazard ratios and Harrell's c-indices. Results: The phantom experiment identified a 0.5 mg/mL threshold to differentiate vital from non-vital tissue. Using DECT vital iodine TB, median PFS was significantly different between non-responders and responders (587 vs 167 days, respectively; p=.02). Hazard ratio for progression for DECT vital iodine TB non-responders versus responders was 6.9, versus 7.6 for EORTC PET, 3.3 for VTB, 2.3 for RECIST 1.1, and 2.1 for mChoi. C-index was 0.74 for EORTC PET, 0.73 for DECT vital iodine TB, 0.67 for VTB, 0.61 for RECIST 1.1, and 0.58 for mChoi. C-index was significantly greater for DECT vital iodine TB than RECIST 1.1 (p=.02) and mChoi (p=.002), but not different than VTB and EORTC PET (p>.05). Conclusion: DECT vital iodine TB criteria showed comparable performance as EORTC PET and outperformed RECIST 1.1 and mChoi for response assessment of metastatic GIST under TKI therapy. Clinical Impact: DECT vital iodine TB could help guide early management decisions in patients on TKI therapy.

Use quantitative parameters in spectral computed tomography for the differential diagnosis of metastatic mediastinal lymph nodes in lung cancer patients

Background

Accurate diagnosis of mediastinal lymph node (LN) metastases is very important for the treatment and prognosis in lung cancer patients. Spectral computed tomography (CT), as a non-invasive approach, has good prospects for detecting mediastinal nodal metastasis. However, the diagnostic criteria of differentiating metastatic and nonmetastatic LNs have not been determined.

Methods

Clinical and imaging data of 64 lung cancer patients (mean age 61.3±10.3 years, 41 men) from April to December 2019 were retrospectively analyzed. The unenhanced scan and contrast enhanced arterial phase (AP) and venous phase (VP) spectral CT scans were performed. The 70 keV monochromatic image and iodine-based image in all phases were analyzed to measure the parameters of LNs. LNs were divided into the metastatic and non-metastatic groups based on confirmative pathological results, and their differences were statistically analyzed. The receiver operating characteristics curve (ROC) was used to evaluate the efficacy of the differential diagnosis.

Results

Seventy-four metastatic LNs and 152 non-metastatic LNs were obtained. Compared with non-metastatic LNs, metastatic LNs often had a larger size (P<0.001). In the unenhanced scans, the density of metastatic LNs was lower than that of non-metastatic LNs (P<0.001); however, there was no difference in CT value in AP and VP between metastatic and non-metastatic LNs (P=0.07, P=0.08, respectively). A statistically significant difference was found in iodine concentration (IC), normalized iodine concentration (NIC) and slope of the spectral curve (λHU) in unenhanced scan, IC and λHU in AP, as well as IC, NIC and λHU in VP between metastatic and non-metastatic LNs. There was no difference in NIC in AP between them.

Conclusions

Combined with morphology, spectral CT quantitative parameters demonstrate certain diagnostic efficiency for differential diagnosis between metastatic and non-metastatic LNs in lung cancer patients.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Background

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.

Methods

Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ_HU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT_40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.

Results

Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ_HU, and CT_40keV performed better in the VP (NIC_VP, λ_VPHU, and CT_VP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC_VP, λ_VPHU, and CT_VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC_AP (AUC =0.89) were greater than other parameters. NIC_AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.

Conclusions

Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Inter-scan and inter-scanner variation of quantitative dual-energy CT: evaluation with three different scanner types

OBJECTIVES

To investigate inter-scan and inter-scanner variation of iodine concentration (IC) and attenuation in virtual monoenergetic images at 65 keV (HU_65keV) in patients with repeated abdominal examinations on dual-source (dsDECT), rapid kV switching (rsDECT), and dual-layer detector DECT (dlDECT).

METHODS

We retrospectively included 131 patients who underwent two abdominal DECT examinations on the same scanner (dsDECT: n = 46, rsDECT: n = 45, dlDECT: n = 40). IC and HU_65keV were measured by placing regions of interest in the liver, spleen, kidneys, aorta, portal vein, and inferior vena cava. Overall IC and HU_65keV for each scanner, their inter-scan differences and proportional variation were calculated and compared between scanner types.

RESULTS

The three scanner-specific cohorts showed similar weight, body diameter, age, sex, and contrast media injection parameters as well as inter-scan differences hereof (p range: 0.23-0.99). Absolute inter-scan differences of HU_65keV and IC were comparable between scanners (p range: 0.08-1.0). Overall inter-scan variation was significantly higher in IC than HU_65keV (p < 0.05). For the liver, rsDECT showed significantly lower inter-scan variation of IC compared to dsDECT/dlDECT (p = 0.005/0.01), while for the spleen, this difference was only significant compared to dsDECT (p = 0.015). Normalizing IC of the liver to the portal vein and of the spleen to the aorta did not significantly reduce inter-scan variation (p = 0.97 and 0.50).

CONCLUSIONS

Iodine measurements across different DECT scanners show inter-scan variation which is higher compared to variation of attenuation values. Inter-scanner differences in longitudinal variation and overall iodine concentration depend on the scanner pairs and organs assessed and should be acknowledged in clinical and scientific DECT applications.

KEY POINTS

• All scanner types showed comparable inter-scan variation of attenuation, while for iodine, the rapid kV switching DECT showed lower variability in the liver and spleen. • Iodine concentration showed higher inter-scan variation than attenuation measurements; normalization to vessels did not significantly improve inter-scan reproducibility of iodine concentration in parenchymal organs. • Differences between the three scanner types regarding overall iodine concentration and attenuation obtained from both timepoints were within the range of average intra-patient, inter-scan differences for most assessed organs and vessels.

Quantitative accuracy of virtual non-contrast images derived from spectral detector computed tomography: an abdominal phantom study

Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNC_error was − 1.4 ± 6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNC_error significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: − 1.2 ± 4.9 HU vs. − 2.1 ± 6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: − 4.0 ± 3.5 HU vs. 5.1 ± 5.0 HU and 35-HU-base vs. 54-HU-base: − 3.5 ± 4.4 HU vs. 0.7 ± 6.5; all p ≤ 0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation.

Gastrointestinal stromal tumors (GIST): a proposal of a "CT-based predictive model of Miettinen index" in predicting the risk of malignancy

PURPOSE

To identify the predictors of malignancy on CT for the evaluation of gastrointestinal stromal tumors (GIST) by correlating CT findings with the mitotic index in order to propose a "CT-based predictive model of Miettinen index."

METHODS

One radiologist and one resident in radiology with 14- and 4-year experience in oncological field reviewed the CT findings of 42 patients by consensus, with respect to lesion site, size, contour, tumor growth pattern, enhancing pattern, degree of enhancement of tumor, percentage of tumor necrosis, mesenteric fat infiltration, ulceration, calcification, regional lymphadenopathy, direct invasion to adjacent organs, and distant metastasis. All parameters were correlated with the mitotic index evaluated at histopathological analysis following surgery. Normality of variables was evaluated using Shapiro-Wilk test. Pearson's correlation test was used to assess the interaction between variables. The diagnostic accuracy percentage of tumor necrosis was measured by receiver operating characteristic (ROC) analysis for detecting whether the number of mitosis per 50 high-power fields was > 5.

RESULTS

A significant statistical correlation was found between percentage of tumor necrosis and the mitotic index (p < 0.005), dimension, and location of the tumor.

CONCLUSION

CT could be an accurate technique in the prediction of malignancy of GIST in a CT risk assessment system, based on the location of the tumor, its size, and the percentage of tumor necrosis.

Dual-energy CT parameters in correlation to MRI-based apparent diffusion coefficient: evaluation in rectal cancer after radiochemotherapy

Background

Rectal cancer (RC) is a frequent malignancy for which magnetic resonance imaging (MRI) is the most common and accurate imaging. Iodine concentration (IC) can be quantified with spectral dual-layer computed tomography CT (DL-CT), which could improve imaging of RC, especially for evaluation of response to radiochemotherapy (RCT).

Purpose

To compare a DL-CT system to MRI as the non-invasive imaging gold standard for imaging of RC to evaluate the possibility of a response evaluation with DL-CT.

Material and Methods

Eleven patients who received DL-CT as well as MRI before and after RCT of RC were retrospectively included into this study. For each examination, a region of interest (ROI) was placed within the tumor. For MRI, the mean apparent diffusion coefficient (ADC) was assessed. For DL-CT, IC, z-effective, and Hounsfield Units (HU) were measured. IC, z-effective, and HU were normalized to the aorta. ADC was correlated to absolute and relative normalized IC, z-effective, and HU with Spearman’s ρ. Differences before and after treatment were tested with Wilcoxon signed-rank test.

Results

HU, IC, and Z-effective values in DL-CT images decreased significantly after RCT (P<0.01 for each comparison). The mean ADC increased significantly after RCT. Spearman’s ρ of the absolute IC difference and the absolute ADC (both before and after RCT) is high and significant (ρ = 0.73; P = 0.01), whereas the ρ-value for z-effective (ρ = 0.56) or HU (ρ = 0.45) to ADC was lower and non-significant.

Conclusion

Response evaluation of RC after RCT could be possible with DL-CT via the measurement of IC.

New boundaries of liver imaging: from morphology to function

From an invisible organ to one of the most explored non-invasively, the liver is, today, one of the cornerstones for current cross-sectional imaging techniques and minimally invasive procedures. After the achievements of US, CT and, most recently, MRI in providing highly accurate morphological and structural information about the organ, a significant scientific development has gained momentum for the last decades, coupling morphology to liver function and contributing far most to what we know today as precision medicine. In fact, dedicated tailor-made investigations are now possible in order to detect and, most of all, quantify physiopathological processes with unprecedented certitude. It is the intention of this review to provide a better insight to the reader of several functional imaging techniques applied to liver imaging. Contrast enhanced imaging, diffusion weighted imaging, elastography, spectral computed tomography and fat and iron assessment techniques are commonly performed clinically. Diffusion kurtosis imaging, magnetic resonance spectroscopy, T1 relaxometry and radiomics remain largely limited to advanced clinical research. Each of them has its own value and place on the diagnostic armamentarium and provide unique qualitative and quantitative information regarding the pathophysiology of diseases, contributing at a large scale to model therapeutic decisions and patient follow-up. Therefore, state-of-the-art liver imaging acts today as a non-invasive surrogate biomarker of many focal and diffuse liver diseases.

New advances in radiomics of gastrointestinal stromal tumors

Gastrointestinal stromal tumors (GISTs) are uncommon neoplasms of the gastrointestinal tract with peculiar clinical, genetic, and imaging characteristics. Preoperative knowledge of risk stratification and mutational status is crucial to guide the appropriate patients’ treatment. Predicting the clinical behavior and biological aggressiveness of GISTs based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) evaluation is challenging, unless the lesions have already metastasized at the time of diagnosis. Radiomics is emerging as a promising tool for the quantification of lesion heterogeneity on radiological images, extracting additional data that cannot be assessed by visual analysis. Radiomics applications have been explored for the differential diagnosis of GISTs from other gastrointestinal neoplasms, risk stratification and prediction of prognosis after surgical resection, and evaluation of mutational status in GISTs. The published researches on GISTs radiomics have obtained excellent performance of derived radiomics models on CT and MRI. However, lack of standardization and differences in study methodology challenge the application of radiomics in clinical practice. The purpose of this review is to describe the new advances of radiomics applied to CT and MRI for the evaluation of gastrointestinal stromal tumors, discuss the potential clinical applications that may impact patients’ management, report limitations of current radiomics studies, and future directions.

Measuring Dynamic CT Perfusion Based on Time-Resolved Quantitative DECT Iodine Maps: Comparison to Conventional Perfusion at 80 kVp for Pancreatic Carcinoma

OBJECTIVES

Using dual-energy computed tomography (DECT) for quantifying iodine content after injection of contrast agent could provide a quantitative basis for dynamic computed tomography (CT) perfusion measurements by means of established mathematical models of contrast agent kinetics, thus improving results by combining the strength of both techniques, which was investigated in this study.

MATERIALS AND METHODS

A dynamic DECT acquisition over 51 seconds performed at 80/Sn140 kVp in 17 patients with pancreatic carcinoma was used to calculate iodine-enhancement images for each time point by means of 3-material decomposition. After motion correction, perfusion maps of blood flow were calculated using the maximum-slope model from both 80 kVp image data and iodine-enhancement images. Blood flow was measured in regions of interest placed in healthy pancreatic tissue and carcinoma for both of the derived perfusion maps. To assess image quality of input data, an adjusted contrast-to-noise ratio was calculated for 80 kVp images and iodine-enhancement images. Susceptibility of perfusion results to residual patient breathing motion during acquisition was investigated by measuring blood flow in fatty tissue surrounding the pancreas, where blood flow should be negligible compared with the pancreas.

RESULTS

For both 80 kVp and iodine-enhancement images, blood flow was significantly higher in healthy tissue (114.2 ± 37.4 mL/100 mL/min or 115.1 ± 36.2 mL/100 mL/min, respectively) than in carcinoma (46.5 ± 26.6 mL/100 mL/min or 49.7 ± 24.7 mL/100 mL/min, respectively). Differences in blood flow between 80 kVp image data and iodine-enhancement images were statistically significant in healthy tissue, but not in carcinoma. For 80 kVp images, adjusted contrast-to-noise ratio was significantly higher (1.3 ± 1.1) than for iodine-enhancement images (1.1 ± 0.9). When evaluating fatty tissue surrounding the pancreas for estimating influence of patient motion, measured blood flow was significantly lower for iodine-enhancement images (30.7 ± 12.0 mL/100 mL/min) than for 80 kVp images (39.0 ± 19.1 mL/100 mL/min). Average patient radiation exposure was 8.01 mSv for dynamic DECT acquisition, compared with 4.60 mSv for dynamic 80 kVp acquisition.

DISCUSSION

Iodine enhancement images can be used to calculate CT perfusion maps of blood flow, and compared with 80 kVp images, results showed only a small difference of 1 mL/100 mL/min in blood flow in healthy tissue, whereas patient radiation exposure was increased for dynamic DECT. Perfusion maps calculated based on iodine-enhancement images showed lower blood flow in fatty tissues surrounding the pancreas, indicating reduced susceptibility to residual patient breathing motion during the acquisition.

Determination of iodine detectability in different types of multiple-energy images for a photon-counting detector computed tomography system

In addition to low-energy-threshold images (TLIs), photon-counting detector (PCD) computed tomography (CT) can generate virtual monoenergetic images (VMIs) and iodine maps. Our study sought to determine the image type that maximizes iodine detectability. Adult abdominal phantoms with iodine inserts of various concentrations and lesion sizes were scanned on a PCD-CT system. TLIs, VMIs at 50 keV, and iodine maps were generated, and iodine contrast-to-noise ratio (CNR) was measured. A channelized Hotelling observer was used to determine the area under the receiver-operating-characteristic curve (AUC) for iodine detectability. Iodine map CNR ( 0.57 ± 0.42 ) was significantly higher ( P < 0.05 ) than for TLIs ( 0.46 ± 0.26 ) and lower ( P < 0.001 ) than for VMIs at 50 keV ( 0.74 ± 0.33 ) for 0.5 mgI/cc and a 35-cm phantom. For the same condition and an 8-mm lesion, iodine detectability from iodine maps ( AUC = 0.95 ± 0.01 ) was significantly lower ( P < 0.001 ) than both TLIs ( AUC = 0.99 ± 0.00 ) and VMIs ( AUC = 0.99 ± 0.01 ). VMIs at 50 keV had similar detectability to TLIs and both outperformed iodine maps. The lowest detectable iodine concentration was 0.5 mgI/cc for an 8-mm lesion and 1.0 mgI/cc for a 4-mm lesion.

Imaging surveillance of gastrointestinal stromal tumour: current recommendation by National Comprehensive Cancer Network and European Society of Medical Oncology-European Reference Network for rare adult solid cancers

Imaging plays an active role in the surveillance of gastrointestinal stromal tumours (GISTs). Risk stratification schemes, based on size, mitotic count, and anatomical site of origin of the GIST, help in planning preoperative and postoperative imaging strategies especially in determining the frequency and duration of surveillance; however, there is no clear consensus on the optimal imaging strategies in patients with GISTs who are completely cured by surgery and patients who are at risk of recurrence. In addition, current surveillance protocols depend on the resectability of the primary tumour and presence of metastatic disease. The objective of this article is to provide a comprehensive review of the role of the different imaging methods for surveillance of GISTs, focusing on the guidelines recommended by National Comprehensive Cancer Network and European Society of Medical Oncology - European Network for Rare adult solid Cancers, and to propose practical guidelines for surveillance of GISTs for various risk categories.

Correlation Between Dual-Energy Computed Tomography Single Scan and Computed Tomography Perfusion for Pancreatic Cancer Patients: Initial Experience

OBJECTIVE

The objective of this study was to evaluate the role and limit of iodine maps by dual-energy computed tomography (CT) single scan for pancreatic cancer.

METHODS

Thirty patients with suspected solitary pancreatic cancer were enrolled in this study and underwent CT perfusion and iodine maps. The parameters of pancreatic cancer and normal pancreatic tissue were calculated. Pearson correlation and paired t test were used for evaluating 2 techniques.

RESULTS

Iodine concentration had a moderate positive correlation with blood flow or blood volume (P < 0.05 for both). All values of iodine concentration and blood flow, iodine concentration, and blood volume had significant positive correlations (P < 0.001 for both). The mean effective dose for CT perfusion and iodine maps had significant difference (8.61 ± 0.00 mSv vs 1.13 ± 0.14 mSv, P < 0.001).

CONCLUSIONS

Iodine maps had the potential to replace routine CT perfusion for pancreatic cancer with low radiation dose.

The value of single-source dual-energy CT imaging for discriminating microsatellite instability from microsatellite stability human colorectal cancer

OBJECTIVES

To demonstrate the value of single-source dual-energy computed tomography (ssDECT) imaging for discriminating microsatellite instability (MSI) from microsatellite stability (MSS) colorectal cancer (CRC).

METHODS

Thirty-eight and seventy-six patients with pathologically proven MSI and MSS CRC, respectively, were retrospectively selected and compared. These patients underwent contrast-enhanced abdominal ssDECT scans before any anti-cancer treatment. Effective atomic number (Eff-Z) in precontrast phase, slope k of spectral HU curve in precontrast (k-P), arterial (k-A), venous (k-V), and delayed phase (k-D), normalized iodine concentration in arterial (NIC-A), venous (NIC-V), and delayed phase (NIC-D), of tumors in two groups were measured by two reviewers. Consistency of measurements was tested by intra-class correlation coefficients (ICC). Mann-Whitney U test or Student's t test was used to compare above values between MSI and MSS. Multivariate logistic regression was used to analyze multiple parameters. Receiver operating characteristic curves were calculated to assess diagnostic efficacies.

RESULTS

Interobserver agreement was excellent (ICC > 0.80). MSI CRC had significantly lower values in all measurements (NIC-A, V, D; k-P, A, V, D; Eff-Z) than MSS CRC. For discriminating MSI from MSS CRC, the area under curve (AUC) using k-A was the highest (AUC, 0.803; sensitivity, 72.4%; specificity, 76.3%). The multivariate logistic regression (selection method, Enter) with combined ssDECT parameters (NIC-A, NIC-V, NIC-D, Eff-Z, k-P, k-A, k-V, k-D) significantly improved diagnostic capability with AUC of 0.886 (sensitivity, 81.6%; specificity, 81.6%).

CONCLUSIONS

The combination of multiple parameters in ssDECT imaging by multivariate logistic regression provides relatively high diagnostic accuracy for discriminating MSI from MSS CRC.

KEY POINTS

• ssDECT generates multiple parameters for discriminating CRC with MSI from MSS. • ssDECT measurements for MSI CRC were significantly lower than MSS CRC. • Combination of ssDECT parameters further improves diagnostic capability for differentiation.

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.

Locally advanced gastric cancer: total iodine uptake to predict the response of primary lesion to neoadjuvant chemotherapy

PURPOSE

Pathologic response to neoadjuvant chemotherapy is a prognostic factor in many cancer types. However, the existing evaluative criteria are deficient. We sought to prospectively evaluate the total iodine uptake derived from dual-energy computed tomography (DECT) in predicting treatment efficacy and progression-free survival (PFS) time in gastric cancer after neoadjuvant chemotherapy.

METHODS

From October 2012 to December 2015, 44 patients with locally advanced gastric cancer were examined with DECT 1 week before and three cycles after neoadjuvant chemotherapy. The percentage changes in tumor area (%ΔS), diameter (%ΔD), and density (%ΔHU) were calculated to evaluate the WHO, RESCIST, and Choi criteria. The percentage changes in tumor volume (%ΔV) and total iodine uptake of portal phase (%ΔTIU-p) were also calculated to determine cut-off values by ROC curves. The correlation between the different criteria and histopathologic tumor regression grade (Becker score) or PFS were statistically analyzed.

RESULTS

Forty-four patients were divided into responders and non-responders according to 43.34% volume reduction (P = 0.002) and 63.87% (P = 0.002) TIU-p reduction, respectively. The %ΔTIU-p showed strong (r = 0.602, P = 0.000) and %ΔV showed moderate (r = 0.416, P = 0.005), while the WHO (r = 0.075, P = 0.627), RECIST (r = 0.270, P = 0.077) and Choi criteria (r = 0.238, P = 0.120) showed no correlation with the Becker score. The differences in PFS time between the responder and non-responder groups were significant according to %ΔTIU-p and Choi criteria (P = 0.001 and P = 0.013, respectively).

CONCLUSIONS

The TIU-p can help predict pathological regression in advanced gastric cancer patients after neoadjuvant chemotherapy. In addition, the %ΔTIU-p could be one of the potentially valuable predictive parameters of the PFS time.

Practical Applications of Dual-Energy Computed Tomography in the Acute Abdomen

With new developments in workflow automation, as well as technological advances enabling faster imaging with improved image quality and dose profile, dual-energy computed tomography is being used more often in the imaging of the acutely ill and injured patient. Its ability to identify iodine, differentiate it from hematoma or calcification, and improve contrast resolution has proven invaluable in the assessment of organ perfusion, organ injury, and inflammation.

Hepatocellular Carcinoma: Diagnosis, Treatment Algorithms, and Imaging Appearance after Transarterial Chemoembolization

Hepatocellular carcinoma (HCC) is a common cause of cancer-related death, with incidence increasing worldwide. Unfortunately, the overall prognosis for patients with HCC is poor and many patients present with advanced stages of disease that preclude curative therapies. Diagnostic and interventional radiologists play a key role in the management of patients with HCC. Diagnostic radiologists can use contrast-enhanced computed tomography (CT), magnetic resonance imaging, and ultrasound to diagnose and stage HCC, without the need for pathologic confirmation, by following established criteria. Once staged, the interventional radiologist can treat the appropriate patients with percutaneous ablation, transarterial chemoembolization, or radioembolization. Follow-up imaging after these liver-directed therapies for HCC can be characterized according to various radiologic response criteria; although, enhancement-based criteria, such as European Association for the Study of the Liver and modified Response Evaluation Criteria in Solid Tumors, are more reflective of treatment effect in HCC. Newer imaging technologies like volumetric analysis, dual-energy CT, cone beam CT and perfusion CT may provide additional benefits for patients with HCC.

Dual-energy CT iodine maps as an alternative quantitative imaging biomarker to abdominal CT perfusion: determination of appropriate trigger delays for acquisition using bolus tracking

OBJECTIVE

Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion.

METHODS

Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kV_p with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kV_p image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time.

RESULTS

Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min^-1, respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (r_max = 0.89; p < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05).

CONCLUSION

An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

Quantification of Iodine Concentration Using Single-Source Dual-Energy Computed Tomography in a Calf Liver

OBJECTIVE

To evaluate the accuracy of single-source dual-energy computed tomography (ssDECT) in iodine quantification using various segmentation methods in an ex vivo model.

METHODS

Ten sausages, injected with variable quantities of iodinated contrast, were inserted into 2 livers and scanned with ssDECT. Material density iodine images were reconstructed. Three radiologists segmented each sausage. Iodine concentration, volume, and absolute quantity were measured. Agreement between the measured and injected iodine was assessed with the concordance correlation coefficient (CCC). Intrareader agreement was assessed using the intraclass correlation coefficient (ICC).

RESULTS

Air bubbles were observed in sausage (IX). Sausage (X) was within the same view as hyper-attenuating markers used for localization. With IX and X excluded, CCC and ICC were greater than 0.98 and greater than 0.88. When included, CCC and ICC were greater than 0.94 and greater than 0.79.

CONCLUSIONS

Iodine quantification was reproducible and precise. However, accuracy reduced in sausages consisting of air filled cavities and within the same view as hyperattenuating markers.

Predictive factors for treatment response using dual-energy computed tomography in patients with advanced lung adenocarcinoma

PURPOSE

This study aimed to investigate whether the quantitative parameters of dual-energy computed tomography (DECT) can predict the effects of chemotherapy in advanced adenocarcinoma based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines.

MATERIALS AND METHODS

A total of 90 patients (59 males, 31 females, age 61.4 ± 12.3 (23-85)) with unresectable lung adenocarcinoma (TNM stage IIIB or IV) who underwent DECT before chemotherapy were prospectively included in this study. By comparing baseline studies with the best response achieved during 1 st line chemotherapy, patients were divided into two groups according to RECIST (version 1.1) guidelines as follows; responders (CR or PR) and non-responders (SD or PD). Quantitative measurements were performed on baseline DECT, and a logistic regression model was used to evaluate predictive factors for a response to chemotherapy.

RESULTS

Among 90 patients, 38 were categorized as responders, while 52 patients were non-responders. The mean iodine concentration measurements were significantly higher in responders compared with non-responders (1.81 ± 0.51 vs 1.33 ± 0.76 mg/ml, p < 0.001). On multivariate analysis, EGFR mutation (odds ratio (OR): 3.116, 95% confidential interval (CI):1.182-8.213, p = .019) and iodine concentration (OR: 1.112, 95% CI:1.034-1.196, p = .006) were found to be significant for predicting a treatment response.

CONCLUSIONS

Dual-energy CT using a quantitative analytic method based on iodine concentration measurements can be used to predict the effects of chemotherapy in patients with advanced adenocarcinoma.

Correlations between the iodine concentrations from dual energy computed tomography and molecular markers Ki-67 and HIF-1α in rectal cancer: A preliminary study

PURPOSE

To investigate whether dual energy computed tomography (CT) with iodine quantification is correlated with molecular markers Ki-67and hypoxia-inducible factor 1α (HIF-1α)in rectal cancer (RC).

MATERIALS AND METHODS

Eighty patients (43 males and 37 females) diagnosed with rectal cancer got pelvic contrast-enhanced CT scan with dual energy computed tomography before any anticancer treatment. Analyse the normalized iodine concentration (NIC) values and CT values at each energy level (40-140 keV) from the virtual monochromatic image of the primary lesions. The postoperative specimens of all 80 patients underwent Ki-67 and HIF-1α immunohistochemistry staining. By SPSS17.0 software package, we analyzed the correlations of NIC values and CT values at each energy level (40-140 keV) with Ki-67 and HIF-1α expression. The receiver operating characteristic (ROC) curves of these dual energy computed tomography parameters were calculated and the diagnostic value were assessed.

RESULTS

There was a weak positive correlation between NIC values and carcinoembryonic antigen level (r=0.246, P=0.028) in RC. Both the value and the level of Ki-67 expression were correlated positively with the NIC values (r=0.344, P=0.002 and r=0.248, P=0.026). HIF-1α expression was correlated positively with the NIC values of the RC (r=0.598, P<0.001). The best threshold values of NIC values in diagnosing the expression of HIF-1α was 0.5839. The sensitivity, 78%; specificity, 87%; PPV, 86%; NPV,79%;accuracy, 83%.

CONCLUSION

The NIC values on dual energy computed tomography may be used as a measurement of hypoxia in RC and determining the ability of tumor invasion noninvasively.

Abdominal Applications of a Novel Detector-Based Spectral CT

Detector-based spectral computed tomography (SDCT) is a recently introduced technology that uses a single x-ray tube and 2 layers of detectors to simultaneously collect low- and high-energy data. In this article, we provide an overview of this novel SDCT technology in abdominal imaging. Several applications of SDCT in abdominal imaging are discussed and illustrated, along with a brief description of current literature on the status of dual-energy computed tomography in these applications. This includes urinary calculus composition, characterization of masses (renal, adrenal, hepatic, and others), tumor perfusion, improving vascular contrast, improving lesion conspicuity, decreasing artifacts, and reducing radiation dose.

Imaging therapy response of gastrointestinal stromal tumors (GIST) with FDG PET, CT and MRI: a systematic review

Purpose

Improvement of the therapeutic approaches in gastrointestinal stromal tumors (GIST) by the introduction of targeted therapies requires appropriate diagnostic tools, which allow sufficient assessment of therapeutic response, including differentiation of true progression from pseudoprogression due to myxoid degeneration or intratumoral hemorrhage. In this literature review the impact and limitations of different imaging modalities used in GIST therapy monitoring are discussed.

Methods

PubMed and Cochrane library search were performed using appropriate keywords. Overall, 39 original papers fulfilled the defined criteria and were included in this systematic review.

Results

Morphological imaging modalities like computed tomography (CT) are primarily used for both diagnosis and therapy monitoring. However, therapy with tyrosine kinase inhibitors and other targeted therapies in GIST may lead only to a minor tumor volume reduction even in cases of response. Therefore, the use of Response Evaluation Criteria in Solid Tumors (RECIST) has limitations. To overcome those limitations, modified response criteria have been introduced for the CT-based therapy assessment, like the Choi criteria as well as criteria based on dual energy CT studies. Functional imaging techniques, mostly based on FDG PET-CT are in use, in particular for the assessment of early treatment response.

Conclusions

The impact and the limitations of PET-based therapy monitoring, as well as its comparison with CT, MRI and survival data are discussed in this review. CT is still the standard method for the evaluation of therapy response despite its several limitations. FDG PET-CT is helpful for the assessment of early therapy response; however, more prospective data are needed to define its role as well as the appropriate time intervals for therapy monitoring. A multiparametric evaluation based on changes in both morphological and functional data has to be assessed in further prospective studies.

Material Separation Using Dual-Energy CT: Current and Emerging Applications

Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.

Noise-optimized virtual monoenergetic dual-energy computed tomography: optimization of kiloelectron volt settings in patients with gastrointestinal stromal tumors

PURPOSE

The aim of this study was to evaluate the impact of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique on quantitative and qualitative image analysis in patients with gastrointestinal stromal tumors (GISTs) at dual-energy computed tomography (DECT) of the abdomen.

METHODS

Forty-five DECT datasets of 21 patients (14 men; 63.7 ± 9.2 years) with GISTs were reconstructed with the standard linearly blended (M_0.6) and VMI+ and traditional virtual monoenergetic (VMI) algorithm in 10-keV increments from 40 to 100 keV. Attenuation measurements were performed in GIST lesions and abdominal metastases to calculate objective signal-to-noise (SNR) and contrast-to-noise ratios (CNR). Five-point scales were used to evaluate overall image quality, lesion delineation, image sharpness, and image noise.

RESULTS

Quantitative image parameters peaked at 40-keV VMI+ series (SNR 27.8 ± 13.0; CNR 26.3 ± 12.7), significantly superior to linearly blended (SNR 16.8 ± 7.3; CNR 13.6 ± 6.9) and all VMI series (all P < 0.001). Qualitative image parameters were highest for 60-keV VMI+ reconstructions regarding overall image quality and image sharpness (median 5, respectively; P ≤ 0.023). Qualitative assessment of lesion delineation peaked in 40 and 50-keV VMI+ series (median 5, respectively). Image noise was superior in 90 and 100-keV VMI and VMI+ reconstructions (all medians 5).

CONCLUSIONS

Low-keV VMI+ reconstructions significantly increase SNR and CNR of GISTs and improve quantitative and qualitative image quality of abdominal DECT datasets compared to traditional VMI and standard linearly blended image series.