Dual-Phase Dual-Energy CT in Patients Treated with Erlotinib for Advanced Non-Small Cell Lung Cancer: Possible Benefits of Iodine Quantification in Response Assessment

Quantitative evaluation of axillary lymph nodes in breast cancer on dual-phase dual-energy CT by precise match with pathology

BackgroundIdentification of axillary lymph node (aLN) metastasis in breast cancer (BC) is important. Dual-energy computed tomography (DECT) is a promising innovation in the field of CT. However, its role in evaluating aLNs remains unclear.PurposeTo investigate the diagnostic performance of DECT in evaluating aLN metastasis in BC patients.Material and MethodsData were prospectively collected from treatment-naïve BC patients who underwent DECT for staging, ultrasound-guided biopsy for suspicious aLNs, and placement of tissue marker in the pathology-positive aLNs. Further cross-sectional imaging was performed preoperatively to locate the marker-labeled LN and help to identify the pathologically proven LN on DECT. Maximal short diameter (MSD) and 13 DECT parameters were measured on metastatic aLNs and contralateral normal aLNs. The univariate, least absolute shrinkage and selection operator and multivariable logistic regression were performed to find independent parameters for predicting metastasis. The diagnostic performance was assessed using receiver operating characteristics (ROC) analysis.ResultsA total of 76 axillary LNs (38 metastasized, 38 normal) from 38 patients were finally included. All DECT parameters showed significant difference between metastatic and normal LNs (all P < 0.001). Arterial enhancement fraction (AEF) and MSD were independent predictors of metastasis (P = 0.010 and 0.014, respectively). The area under the ROC curve (AUC) of AEF was the highest (0.967). The combined AUC of AEF and MSD was significantly higher than that of MSD alone (0.994 vs. 0.943; P = 0.025).ConclusionDECT is a promising tool for preoperative evaluation of aLNs in BC patients, with MSD and AEF having the best diagnostic performance.

Evaluation of induction chemotherapy response using multiphasic dual-energy CT in nasopharyngeal carcinoma

OBJECTIVES

To develop a nomogram that assists in selecting nasopharyngeal carcinoma (NPC) patients suitable for induction chemotherapy.

MATERIALS AND METHODS

This retrospective study included NPC patients who underwent multiphasic contrast‑enhanced DECT (comprising non-contrast, arterial, and venous phase scanning) between May 2019 and December 2023. The relationships between quantitative DECT-derived parameters and treatment response to induction chemotherapy were analyzed using logistic regression analysis. The predictive performance of a nomogram integrating key predictors was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 294 patients (median age, 53 years; interquartile range, 46-59 years; 224 men) were included. Among these, 215 were responders and 79 were non-responders. The normalized iodine concentration in the arterial phase (nICarterial) (odds ratio (OR), 0.71; 95% confidence interval (CI), 0.52-0.98; p = 0.036), arterial enhancement fraction (AEF) (OR, 1.45; 95% CI, 1.04-2.00; p = 0.026), and extracellular volume fraction (ECVf) (OR, 0.65; 95% CI, 0.15-0.87; p = 0.019) of tumors were identified as independent predictors of chemotherapy response. This nomogram demonstrated excellent performance (AUC = 0.803 [95% CI, 0.740-0.864]) across all participants, as well as in subgroup analyses of Epstein-Barr virus DNA (high and low) (AUC: 0.761, 0.799) and across five subgroups with different chemotherapy regimens (AUC, 0.773-0.833).

CONCLUSIONS

We developed a comprehensive nomogram to predict treatment response to induction chemotherapy by integrating nICarterial, AEF, and ECVf. This nomogram demonstrated superior predictive performance compared to the individual parameters when assessed separately.

KEY POINTS

Question To date, no reliable method has been established to predict the efficacy of induction chemotherapy for nasopharyngeal carcinoma prior to treatment. Findings nICarterial, AEF, and ECVf were the independent predictors of induction chemotherapy response, and the combined nomogram demonstrated strong performance to predict response. Clinical relevance The multiphasic contrast‑enhanced parameters derived from dual-energy CT offer a noninvasive approach to predict treatment response to induction chemotherapy and identify nasopharyngeal carcinoma patients who may benefit from induction chemotherapy.

Dual-energy CT quantitative parameters for prediction of prognosis in patients with resectable rectal cancer

OBJECTIVE

To determine whether quantitative parameters derived from dual-energy CT (DECT) could predict prognosis in patients with resectable rectal cancer (RC).

MATERIALS AND METHODS

One hundred and thirty-four patients (recurrence/distant metastasis group, n = 36; non-metastasis/non-recurrence group, n = 98) with RC who underwent radical resection and DECT were retrospectively included. DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), electron density (Rho), effective atomic number (Zeff), dual-energy index (DEI), the slope of the spectral Hounsfield unit curve (λHU) on arterial and venous phase images. Univariate and multivariate Cox proportional hazards models were employed to identify independent risk factors of prognosis. The area under the receiver operating characteristic curve (AUC) was used to assess the performance. Disease-free survival (DFS) curves were constructed using the Kaplan-Meier method.

RESULTS

Patients in the metastasis/recurrence group had higher Rho in arterial phase (A-Rho), NIC in venous phase (V-NIC), Rho in venous phase (V-Rho), Zeff in venous phase (V-Zeff), λHU in venous phase (V-λHU), pT stage, pN stage, serum carcinoembryonic antigen (CEA), carbohydrate antigen-199 levels and more frequent in extramural venous invasion than those in non-metastasis/non-recurrence group (all p < 0.05). V-NIC, V-λHU, and CEA were independent risk factors of recurrence/distant metastasis (all p < 0.05). The AUC of combined indicator integrating three independent risk factors achieved the best diagnostic performance (AUC = 0.900). In stratified survival analysis, patients with high V-NIC, V-λHU, and CEA had lower 3-year DFS than those with low V-NIC, V-λHU, and CEA.

CONCLUSION

Combining V-NIC, V-λHU, and CEA could be used to noninvasively predict prognosis in resectable RC.

KEY POINTS

Question TNM staging fails to accurately prognosticate; can quantitative parameters derived from dual-energy CT predict prognosis in patients with resectable rectal cancer? Findings Normalized iodine concentration (V-NIC) and the slope of the spectral Hounsfield unit curve in venous phase (V-λHU), and carcinoembryonic antigen (CEA) are independent risk factors for recurrence/metastasis. Clinical relevance The combined indicator integrating V-NIC, V-λHU, and CEA could predict 3-year disease-free survival in patients with resectable rectal cancer and could aid in postoperative survival risk stratification to guide personalized treatment.

Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas

PURPOSE

The purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA.

MATERIALS AND METHODS

Sixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29-78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models.

RESULTS

The 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73-0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66-0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74-0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74-0.93) (P = 0.60).

CONCLUSION

Both whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.

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

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

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

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.

Imaging of lung cancer

Lung cancer is the leading cause of cancer-related mortality globally. Imaging is essential in the screening, diagnosis, staging, response assessment, and surveillance of patients with lung cancer. Subtypes of lung cancer can have distinguishing imaging appearances. The most frequently used imaging modalities include chest radiography, computed tomography, magnetic resonance imaging, and positron emission tomography. Artificial intelligence algorithms and radiomics are emerging technologies with potential applications in lung cancer imaging.

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.

Lung dual energy CT: Impact of different technological solutions on quantitative analysis

PURPOSE

To evaluated the accuracy of spectral parameters quantification of four different CT scanners in dual energy examinations of the lung using a dedicated phantom.

METHOD

Measurements were made with different technologies of the same vendor: one dual source CT scanner (DSCT), one TwinBeam (i.e. split filter) and two sequential acquisition single source scanners (SSCT). Angular separation of Calcium and Iodine signals were calculated from scatter plots of low-kVp versus high-kVp HUs. Electron density (ρe), effective atomic number (Zeff) and Iodine concentration (Iconc) were measured using Syngo.via software. Accuracy (A) of ρe, Zeff and Iconc was evaluated as the absolute percentage difference (D%) between reference values and measured ones, while precision (P) was evaluated as the variability σ obtained by repeating the measurement with different acquisition/reconstruction settings.

RESULTS

Angular separation was significantly larger for DSCT (α = 9.7°) and for sequential SSCT (α = 9.9°) systems. TwinBeam was less performing in material separation (α = 5.0°). The lowest average A was observed for TwinBeam (A_ρe = [4.7 ± 1.0], A_Z = [9.1 ± 3.1], A_Iconc = [19.4 ± 4.4]), while the best average A was obtained for Flash (A_ρe = [1.8 ± 0.4], A_Z = [3.5 ± 0.7], A_Iconc = [7.3 ± 1.8]). TwinBeam presented inferior average P (P_ρe = [0.6 ± 0.1], P_Z = [1.1 ± 0.2], P_Iconc = [10.9 ± 4.9]), while other technologies demonstrate a comparable average.

CONCLUSIONS

Different technologies performed material separation and spectral parameter quantification with different degrees of accuracy and precision. DSCT performed better while TwinBeam demonstrated not excellent performance. Iodine concentration measurements exhibited high variability due to low Iodine absolute content in lung nodules, thus limiting its clinical usefulness in pulmonary applications.

Dual-energy CT iodine map in predicting the efficacy of neoadjuvant chemotherapy for hypopharyngeal carcinoma: a preliminary study

Neoadjuvant chemotherapy has become one of the important means for advanced hypopharyngeal carcinoma. So far, there is no effective index to predict the curative effect. To investigate the value of iodine map of dual-energy computed tomography (CT) in predicting the efficacy of neoadjuvant chemotherapy for hypopharyngeal carcinoma. A total of 54 hypopharyngeal carcinomapatients who underwent two courses of TPF neoadjuvant chemotherapy were recruited in this study. Three cases had a complete response (CR), thirty-six cases had a partial response (PR), eleven cases had stable disease (SD), and four cases had a progressive disease (PD) after the chemotherapy. All patients underwent a dual-source CT scan before chemotherapy and rescanned after chemotherapy. The normalized iodine-related attenuation (NIRA) of the mean of maximum slice and most enhanced region of lesion at arterial and parenchymal phase were measured: NIRA_mean-A, NIRA_max-A, NIRA_mean-P, and NIRA_max-P, respectively. Correlation analysis was conducted between different metrics of NIRA and the diameter change rate of lesions, and the curative effect was evaluated based on the receiver operating characteristic (ROC) curve. There were a significant correlation between NIRA_mean-A, NIRA_max-A, NIRA_mean-P, NIRA_max-P and the change rate of lesion's maximum diameter (ΔD%) (all P < 0.01). The NIRA_max-A, NIRA_mean-P, NIRA_max-P had significant differences between CR, PR, SD, PD groups, but NIRA_mean-A did not reach a significant difference. All NIRA_mean-A, NIRA_max-A, NIRA_mean-P, NIRA_max-P had significant differences between effective (CR + PR) and ineffective (SD + PD) groups. The ROC analysis revealed that NIRA_mean-P had the largest AUC and prediction efficacy (AUC = 0.809). Dual-energy CT iodine map could predict the efficacy of neoadjuvant chemotherapy and provides imaging evidence to assist in treatment decisions for hypopharyngeal carcinoma patients.

Dual-energy CT with virtual monoenergetic images and iodine maps improves tumor conspicuity in patients with pancreatic ductal adenocarcinoma

Objectives

To evaluate the value of monoenergetic images (MEI [+]) and iodine maps in dual-source dual-energy computed tomography (DECT) for assessing pancreatic ductal adenocarcinoma (PDAC), including the visually isoattenuating PDAC.

Materials and methods

This retrospective study included 75 PDAC patients, who underwent contrast-enhanced DECT examinations. Conventional polyenergetic image (PEI) and 40–80 keV MEI (+) (10-keV increments) were reconstructed. The tumor contrast, contrast-to-noise ratio (CNR) of the tumor and peripancreatic vessels, the signal-to-noise ratio (SNR) of the pancreas and tumor, and the tumor diameters were quantified. On iodine maps, the normalized iodine concentration (NIC) in the tumor and parenchyma was compared. For subjective analysis, two radiologists independently evaluated images on a 5-point scale.

Results

All the quantitative parameters were maximized at 40-keV MEI (+) and decreased gradually with increasing energy. The tumor contrast, SNR of pancreas and CNRs in 40–60 keV MEI (+) were significantly higher than those in PEI (p < 0.05). For visually isoattenuating PDAC, 40–50 keV MEI (+) provided significantly higher tumor CNR compared to PEI (p < 0.05). The reproducibility in tumor measurements was highest in 40-keV MEI (+) between the two radiologists. The tumor and parenchyma NIC were 1.28 ± 0.65 and 3.38 ± 0.72 mg/mL, respectively (p < 0.001). 40–50 keV MEI (+) provided the highest subjective scores, compared to PEI (p < 0.001).

Conclusions

Low-keV MEI (+) of DECT substantially improves the subjective and objective image quality and consistency of tumor measurements in patients with PDAC. Combining the low-keV MEI (+) and iodine maps may yield diagnostically adequate tumor conspicuity in visually isoattenuating PDAC.

Combined whole-lesion radiomic and iodine analysis for differentiation of pulmonary tumors

Quantitative radiomic and iodine imaging features have been explored for diagnosis and characterization of tumors. In this work, we invistigate combined whole-lesion radiomic and iodine analysis for the differentiation of pulmonary tumors on contrast-enhanced dual-energy CT (DECT) chest images. 100 biopsy-proven solid lung lesions on contrast-enhanced DECT chest exams within 3 months of histopathologic sampling were identified. Lesions were volumetrically segmented using open-source software. Lesion segmentations and iodine density volumes were loaded into a radiomics prototype for quantitative analysis. Univariate analysis was performed to determine differences in volumetric iodine concentration (mean, median, maximum, minimum, 10th percentile, 90th percentile) and first and higher order radiomic features (n = 1212) between pulmonary tumors. Analyses were performed using a 2-sample t test, and filtered for false discoveries using Benjamini–Hochberg method. 100 individuals (mean age 65 ± 13 years; 59 women) with 64 primary and 36 metastatic lung lesions were included. Only one iodine concentration parameter, absolute minimum iodine, significantly differed between primary and metastatic pulmonary tumors (FDR-adjusted p = 0.015, AUC 0.69). 310 (FDR-adjusted p = 0.0008 to p = 0.0491) radiomic features differed between primary and metastatic lung tumors. Of these, 21 features achieved AUC ≥ 0.75. In subset analyses of lesions imaged by non-CTPA protocol (n = 72), 191 features significantly differed between primary and metastatic tumors, 19 of which achieved AUC ≥ 0.75. In subset analysis of tumors without history of prior treatment (n = 59), 40 features significantly differed between primary and metastatic tumors, 11 of which achieved AUC ≥ 0.75. Volumetric radiomic analysis provides differentiating capability beyond iodine quantification. While a high number of radiomic features differentiated primary versus metastatic pulmonary tumors, fewer features demonstrated good individual discriminatory utility.

A spectral CT-based nomogram for predicting the response to induction chemotherapy in nasopharyngeal carcinoma

AIM

To establish a spectral computed tomography (CT)-based nomogram for predicting the response to induction chemotherapy (ICT) in nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

Fifty-four patients with NPC who underwent spectral CT examination before ICT were enrolled prospectively. Patients were assigned to response and non-response groups according to response evaluation. The predictive indicators were spectral CT parameters of venous phase, including iodine concentration (IC), normalised IC (NIC), slope of the spectral attenuation curve in Hounsfield units (λHU), effective atomic number (Eff-Z), and water concentration. Multivariate logistic regression was used to construct a predictive model. The receiver operating characteristic (ROC) and calibration curves were used to evaluate the robustness of model, while the bootstrap method was used for internal validation. The Hosmer-Lemeshow test was used to test the goodness of fit of the discriminant model.

RESULTS

Multivariate logistic regression analysis showed that NIC, λHU, and Eff-Z were the potential predictors, and the three indicators were further used to establish a predictive model. The nomogram was evaluated to have good predictive performance, the area under the ROC curve was 0.909 (95% confidence interval [CI]: 0.799-0.970), and the model was well calibrated (χ² = 8.149, p=0.419).

CONCLUSIONS

The spectral CT nomogram has potential clinical value in predicting response to ICT in NPC and may help guide individualised treatment decisions.

Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer: Combining iodine enhancement and glycolytic activity

Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.

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.

Quantitative contrast enhanced dual energy CT to predict avascular necrosis: a feasibility study of proximal humerus fractures

BACKGROUND

Avascular necrosis is a delayed complication of proximal humerus fractures that increases the likelihood of poor clinical outcomes. CT scans are routinely performed to guide proximal humerus fracture management. We hypothesized iodine concentration on post-contrast dual energy CT scans identifies subjects who develop avascular necrosis and ischemia due to compromised blood flow.

MATERIALS AND METHODS

55 patients with proximal humerus fractures enrolled between 2014 and 2017 underwent clinical, radiographic and contrast enhanced dual energy CT assessment. Iodine densities of the humeral head and the glenoid (control) were measured on CT. Subjects managed with open reduction internal fixation or conservatively (non-surgical) were followed for up to two years for radiographic evidence of avascular necrosis. Arthroplasty subjects underwent histopathologic evaluation for ischemia of the resected humeral head.

RESULTS

17 of 55 subjects (30.9%) were treated conservatively, 21 (38.2%) underwent open reduction internal fixation and 17 of 55 (30.9%) underwent arthroplasty. Of the 38 subjects treated conservatively or with ORIF, 20 (52.6%) completed 12 months of follow up and 14 (36.8%) 24 months of follow up. At 12 months follow up, two of 20 subjects (10%) and at 24 months 3 of 14 subjects (21.4%) developed avascular necrosis. At 12 months, the mean humerus/glenoid iodine ratio was 1.05 (standard deviation 0.24) in subjects with AVN compared to 0.91 (0.24) in those who did not. At 24 months, subjects with avascular necrosis had a mean humerus/glenoid iodine concentration ratio of 1.06 (0.17) compared to 0.924 (0.21) in those who did not. Of 17 arthroplasty subjects, 2 had severe ischemia and an iodine ratio of 1.08 (0.30); 5 had focal ischemia and a ratio of 1.00 (0.36); and 8 no ischemia and a ratio of 0.83 (0.08).

CONCLUSIONS

Quantifying iodine using dual energy CT in subjects with proximal humerus fractures is technically feasible. Preliminary data suggest higher humeral head iodine concentration may increase risk of avascular necrosis; however, future studies must enroll and follow enough subjects managed with open reduction internal fixation or conservatively for two or more years to provide statistically significant results. Trial Registrations NCT02170545 registered June 23, 2014, ClinicalTrials.gov.

Prospective Evaluation of the First Integrated Positron Emission Tomography/Dual-Energy Computed Tomography System in Patients With Lung Cancer

PURPOSE

The aim of this pilot study was to prospectively evaluate the first integrated positron emission tomography (PET)/dual-energy computed tomography (DECT) system performance in patients with non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

In this single-center, prospective trial, consecutive patients with NSCLC referred for a PET study between May 2017 and June 2018 were enrolled. All patients received contrast-enhanced imaging on a clinical PET/DECT system. Data analysis included PET-based standard uptake values (SUVmax) and DECT-based iodine densities of tumor masses, lymph nodes, and distant metastases. Results were analyzed using correlation tests and receiver operating characteristics curves.

RESULTS

The study population was composed of 21 patients (median age 62 y, 14 male patients). A moderate positive correlation was found between iodine density values (2.2 mg/mL) and SUVmax (10.5) in tumor masses (ρ=0.53, P<0.01). Iodine density values (2.3 mg/mL) and SUVmax (5.4) of lymph node metastases showed a weak positive correlation (ρ=0.23, P=0.14). In addition, iodine quantification analysis provided no added value in differentiating between pathologic and nonpathologic lymph nodes with an area under the curve (AUC) of 0.55 using PET-based SUVmax as the reference standard. A weak positive correlation was observed between iodine density (2.2 mg/mL) and SUVmax in distant metastases (14.9, ρ=0.23, P=0.52).

CONCLUSIONS

The application of an integrated PET/DECT system in lung cancer might provide additional insights in the assessment of tumor masses. However, the added value of iodine density quantification for the evaluation of lymph nodes and distant metastases seems limited.

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study

Objective

To build and assess a pre-treatment dual-energy CT-based clinical-radiomics nomogram for the individualized prediction of clinical response to systemic chemotherapy in advanced gastric cancer (AGC).

Methods

A total of 69 pathologically confirmed AGC patients who underwent dual-energy CT before systemic chemotherapy were enrolled from two centers in this retrospective study. Treatment response was determined with follow-up CT according to the RECIST standard. Quantitative radiomics metrics of the primary lesion were extracted from three sets of monochromatic images (40, 70, and 100 keV) at venous phase. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used to select the most relevant radiomics features. Multivariable logistic regression was performed to establish a clinical model, three monochromatic radiomics models, and a combined multi-energy model. ROC analysis and DeLong test were used to evaluate and compare the predictive performance among models. A clinical-radiomics nomogram was developed; moreover, its discrimination, calibration, and clinical usefulness were assessed.

Result

Among the included patients, 24 responded to the systemic chemotherapy. Clinical stage and the iodine concentration (IC) of the tumor were significant clinical predictors of chemotherapy response (all p < 0.05). The multi-energy radiomics model showed a higher predictive capability (AUC = 0.914) than two monochromatic radiomics models and the clinical model (AUC: 40 keV = 0.747, 70 keV = 0.793, clinical = 0.775); however, the predictive accuracy of the 100-keV model (AUC: 0.881) was not statistically different (p = 0.221). The clinical-radiomics nomogram integrating the multi-energy radiomics signature with IC value and clinical stage showed good calibration and discrimination with an AUC of 0.934. Decision curve analysis proved the clinical usefulness of the nomogram and multi-energy radiomics model.

Conclusion

The pre-treatment DECT-based clinical-radiomics nomogram showed good performance in predicting clinical response to systemic chemotherapy in AGC, which may contribute to clinical decision-making and improving patient survival.

Dual-Energy CT-Based Iodine Quantification in Liver Tumors - Impact of Scan-, Patient-, and Position-Related Factors

RATIONALE AND OBJECTIVES

To quantify the contribution of lesion location and patient positioning, dual-energy approach, patient size, and radiation dose to the error of dual-energy CT-based iodine quantification (DECT-IQ) in liver tumors.

MATERIALS AND METHODS

A phantom with four liver lesions (diameter 15 mm; iodine concentration 0-5 mgI/mL) and two sizes was used. One lesion emulated a subdiaphragmatic lesion. Both sizes were imaged in dual-energy mode on (1) a dual-source DECT (DS-DE) at 100/Sn150 kV and (2) a single-source split-filter DECT (SF-DE) at AuSn120 kV at two radiation doses (8 and 12 mGy). Scans were performed at seven different vertical table positions (from -6 to + 6 cm from the gantry isocenter). Iodine concentration was repeatedly measured and absolute errors (error_abs) were calculated. Errors were compared using robust repeated-measures ANOVAs with post-hoc comparisons. A linear mixed effect model was used to determine the factors influencing the error of DECT-IQ.

RESULTS

The linear mixed effect models showed that errors were significantly influenced by DECT approach, phantom size, and lesion location (all p < 0.001). The impact of lesion location on the error was stronger in SF-DE compared to DS-DE. Radiation dose did not significantly influence error (p = 0.22). When averaged across all setups, error_abs was significantly higher for SF-DE (2.08 ± 1.92 mgI/mL) compared to DS-DE (0.37 ± 0.29 mgI/mL) (all p < 0.001). Artefacts were found in the subdiaphragmatic lesion for SF-DE with significantly increased error_abs compared to DS-DE (p < 0.001). Error_abs was significantly higher in the large compared to the medium phantom for DS-DE (0.30 ± 0.23 mgI/mL vs. 0.43 ± 0.33 mgI/mL) and SF-DE (1.68 ± 1.99 vs. 2.36 ± 1.81 mgI/mL) (p < 0.001).

CONCLUSION

The dual-energy approach, patient size, and lesion location modified by patient position significantly impacted DECT-IQ in simulated liver tumors.

Added value of spectral parameters for the assessment of lymph node metastasis of lung cancer with dual-layer spectral detector computed tomography

BACKGROUND

Lymph node (LN) metastasis is an important factor affecting the treatment of lung cancer. The purpose of this article was to investigate the benefits of dual-layer spectral detector computed tomography (SDCT) for the evaluation of metastatic LNs in lung cancer.

METHODS

Data from 93 patients with lung cancer who underwent dual-phase enhanced scanning with SDCT were retrospectively analyzed. According to the pathological findings, 166 LNs were grouped as metastatic (n=80) or non-metastatic (n=86). LNs in station 4 (n=80) and station 7 (n=35) accounted for the majority of the LNs (approximately 69.23%). The short-axis diameter of the LN, arterial enhancement fraction (AEF), normalized iodine concentration (NIC), and the slope of the spectral Hounsfield unit curve (λHU) during the arterial phase (AP) and venous phase (VP) were measured. The Mann-Whitney U test was used to statistically compare these quantitative parameters. Receiver operating characteristic (ROC) curves were plotted to identify the cutoff values, and decision curve analysis (DCA) was performed to determine the net benefit of each parameter. The diagnostic performance, obtained by combining the short-axis diameter with each of the above parameters, was also studied.

RESULTS

The short-axis LN diameter, AEF, NIC, and λHU during the AP and VP all showed significant differences between the metastatic and non-metastatic groups (P<0.05). Of the parameters, the AEF had the greatest diagnostic efficiency for metastatic LNs [area under the ROC curve (AUC)AEF =0.885] with a threshold of 86.40%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and 95% confidence interval were 90.00%, 89.53%, 88.89%, 90.59%, and 0.830-0.944, respectively. When the quantitative parameters were combined with the short-axis diameter, the AUCs of the parameters, except the AEF, were significantly improved (P<0.05).

CONCLUSIONS

The iodine quantitative parameters from SDCT, such as the AEF, demonstrated high diagnostic performances in the differentiation of metastatic and non-metastatic LNs.

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation

Although artificial intelligence (AI) has been a focus of medical research for decades, in the last decade, the field of radiology has seen tremendous innovation and also public focus due to development and application of machine-learning techniques to develop new algorithms. Interestingly, this innovation is driven simultaneously by academia, existing global medical device vendors, and-fueled by venture capital-recently founded startups. Radiologists find themselves once again in the position to lead this innovation to improve clinical workflows and ultimately patient outcome. However, although the end of today's radiologists' profession has been proclaimed multiple times, routine clinical application of such AI algorithms in 2020 remains rare. The goal of this review article is to describe in detail the relevance of appropriate imaging data as a bottleneck for innovation, provide insights into the many obstacles for technical implementation, and give additional perspectives to radiologists who often view AI solely from their clinical role. As regulatory approval processes for such medical devices are currently under public discussion and the relevance of imaging data is transforming, radiologists need to establish themselves as the leading gatekeepers for evolution of their field and be aware of the many stakeholders and sometimes conflicting interests.

Dual-Energy CT Material Decomposition in Pediatric Thoracic Oncology

Technical advances in CT have enabled implementation of dual-energy CT into routine clinical practice. By acquiring images at two different energy spectra, dual-energy CT enables material decomposition, allowing generation of material- and energy-specific images. Material-specific images include virtual nonenhanced images and iodine-specific images (iodine maps). Energy-specific images include virtual monoenergetic images. The reconstructed images can provide unique qualitative and quantitative information about tissue composition and contrast media distribution. In thoracic oncologic imaging, dual-energy CT provides advantages in characterization of thoracic malignancies and lung nodules, determination of extent of disease, and assessment of response to therapy. An especially important feature in children is that dual-energy CT does not come at a higher radiation exposure. Keywords: CT, CT-Quantitative, Lung, Mediastinum, Neoplasms-Primary, Pediatrics, Thorax, Treatment Effects © RSNA, 2021.

Intraindividual Consistency of Iodine Concentration in Dual-Energy Computed Tomography of the Chest and Abdomen

OBJECTIVES

Dual-energy computed tomography (DECT)-derived quantification of iodine concentration (IC) is increasingly used in oncologic imaging to characterize lesions and evaluate treatment response. However, only limited data are available on intraindividual consistency of IC and its variation. This study investigates the longitudinal reproducibility of IC in organs, vessels, and lymph nodes in a large cohort of healthy patients who underwent repetitive DECT imaging.

MATERIALS AND METHODS

A total of 159 patients, who underwent a total of 469 repetitive (range, 2-4), clinically indicated portal-venous phase DECT examinations of the chest and abdomen, were retrospectively included. At time of imaging, macroscopic tumor burden was excluded by follow-up imaging (≥3 months). Iodine concentration was measured region of interest-based (N = 43) in parenchymatous organs, vessels, lymph nodes, and connective tissue. Normalization of IC to the aorta and to the trigger delay as obtained from bolus tracking was performed. For statistical analysis, intraclass correlation coefficient and modified variation coefficient (MVC) were used to assess intraindividual agreement of IC and its variation between different time points, respectively. Furthermore, t tests and analysis of variance with Tukey-Kramer post hoc test were used.

RESULTS

The mean intraclass correlation coefficient over all regions of interest was good to excellent (0.642-0.936), irrespective of application of normalization or the normalization technique. Overall, MVC ranged from 1.8% to 25.4%, with significantly lower MVC in data normalized to the aorta (5.8% [1.8%-15.8%]) in comparison with the MVC of not normalized data and data normalized to the trigger delay (P < 0.01 and P = 0.04, respectively).

CONCLUSIONS

Our study confirms intraindividual, longitudinal variation of DECT-derived IC, which varies among vessels, lymph nodes, organs, and connective tissue, following different perfusion characteristics; normalizing to the aorta seems to improve reproducibility when using a constant contrast media injection protocol.

A comparison study of dual-energy spectral CT and 18F-FDG PET/CT in primary tumors and lymph nodes of lung cancer

PURPOSE

We aimed to investigate whether there is a correlation between dual-energy spectral computed tomography (DESCT) and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) parameters in primary tumor and metastatic lymph nodes in patients with newly diagnosed lung cancer.

METHODS

Primary tumor and metastatic lymph nodes of 68 patients diagnosed with lung cancer were evaluated retrospectively with 18F-FDG PET/CT and DESCT imaging. The histologic subtypes were adenocarcinoma (n=29), squamous cell carcinoma (SCC) (n=26), small cell lung cancer (SCLC) (n=11), and large cell neuroendocrine cancer (LCNEC) (n=2). In terms of PET parameters, SUVmax, SUVmean, SULmax, SULmean, SULpeak, and normalized SUL values were obtained for primary tumors and metastatic lymph nodes. In terms of DESCT parameters, maximum and mean iodine content (IC), normalized IC values, iodine enhancement (IE) and normalized IE values were calculated.

RESULTS

We found no correlation between DESCT and 18F-FDG PET/CT parameters in primary tumors and metastatic lymph nodes. In addition, no correlation was found in the analysis performed in any of the histologic subgroups. In patients with a primary tumor <3 cm, there was a moderate negative correlation between the parameters SUVmax-ICmax (r= -0.456, p = 0.043), SUVmean-ICmax (r= -0.464, p = 0.039) SULmean-ICmax (r= -0.497, p = 0.026), SUVmax-ICmean (r= -0.527, p = 0.020), SULmean-ICmean (r= -0.499, p = 0.025), and SULpeak-ICmean (r= -0.488, p = 0.029).

CONCLUSION

We consider that DESCT and 18F-FDG PET/CT indicate different characteristics of the tumors and should not supersede each other.

The Performance of a Dual-Energy CT Derived Radiomics Model in Differentiating Serosal Invasion for Advanced Gastric Cancer Patients After Neoadjuvant Chemotherapy: Iodine Map Combined With 120-kV Equivalent Mixed Images

Objectives

The aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for the model based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC).

Methods

A total of 155 patients (110 in the training cohort and 45 in the testing cohort) with LAGC who had standard NAC before surgery were retrospectively enrolled. All CT images were analyzed by two radiologists for manual classification. Volumes of interests (VOIs) were delineated semi-automatically, and 1,226 radiomics features were extracted from every segmented lesion in both IM and 120 kVp images, respectively. Spearman's correlation analysis and the least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented for filtering unstable and redundant features and screening out vital features. Two predictive models (120 kVp and IM-120 kVp) based on 120 kVp selected features only and 120 kVp combined with IM selected features were established by multivariate logistic regression analysis. We then build a combination model (ComModel) developed with IM-120 kVp signature and ycT. The performance of these three models and manual classification were evaluated and compared.

Result

Three radiomics models showed great predictive accuracy and performance in both the training and testing cohorts (ComModel: AUC: training, 0.953, testing, 0.914; IM-120 kVp: AUC: training, 0.953, testing, 0.879; 120 kVp: AUC: training, 0.940, testing, 0.831). All these models showed higher diagnostic accuracy (ComModel: 88.9%, IM-120 kVp: 84.4%, 120 kVp: 80.0%) than manual classification (68.9%) in the testing group. ComModel and IM-120 kVp model had better performances than manual classification both in the training (both p<0.001) and testing cohorts (p<0.001 and p=0.034, respectively).

Conclusions

Dual-energy CT-based radiomics models demonstrated convincible diagnostic performance in differentiating serosal invasion in preoperative restaging for LAGC. The radiomics features derived from IM showed great potential for improving the diagnostic capability.

Comparison of virtual non-contrast dual-energy CT and a true non-contrast CT for contouring in radiotherapy of 3D printed lung tumour models in motion: a phantom study

OBJECTIVES

This work aims to investigate whether virtual non-contrast (VNC) dual-energy CT(DECT) of contrasted lung tumours can be used as an alternative for true non-contrast (TNC) images in radiotherapy. Two DECT techniques and a TNC CT were compared and influences on gross tumour volume (GTV) volume and CT number from motion artefacts in three-dimensional printed lung tumour models (LTM) in amotion phantom were examined.

METHODS

Two spherical LTMs (diameter 3.0 cm) with different inner shapes were created in a three-dimensional printer. The inner shapes contained water or iodine (concentration 5 mg ml^-1) and were scanned with a dual-source DECT (ds-DECT), single-source sequential DECT (ss-DECT) and TNC CT in a respiratory motion phantom (15 breaths/min, amplitude 1.5 cm). CT number and volume of LTMs were measured. Therefore, two GTVs were contoured.

RESULTS

Deviations in GTV volume (outer shape) of LTMs in motion for contrast-enhanced ss-DECT and ds-DECT VNC images compared to TNC images are not significant (p > 0.05). Relative GTV volume and CT number deviations (inner shapes) of LTMs in motion were 6.6 ± 0.6% and 104.4 ± 71.2 HU between ss-DECT and TNC CT and -8.4 ± 10.6% and 25.5 ± 58.5 HU between ds-DECT and TNC, respectively.

CONCLUSION

ss-DECT VNC images could not sufficiently subtract iodine from water in LTMs inmotion, whereas ds-DECT VNC images might be a valid alternative to a TNC CT.

ADVANCES IN KNOWLEDGE

ds-DECT provides a contrasted image for contouring and a non-contrasted image for radiotherapy treatment planning for LTM in motion.

Improved differentiation between primary lung cancer and pulmonary metastasis by combining dual-energy CT-derived biomarkers with conventional CT attenuation

OBJECTIVES

To assess the clinical utility of dual-energy CT (DE-CT)-derived iodine concentration (IC) and effective Z (Z^eff) in addition to conventional CT attenuation (HU) for the discrimination between primary lung cancer (LC) and pulmonary metastases (PM) from different primary malignancies.

METHODS

DE-CT scans of 79 patients with LC (3 histopathologic subgroups) and 89 patients with PM (5 histopathologic subgroups) were evaluated. Quantitative IC, Z^eff, and conventional HU values were extracted and normalized to the thoracic aorta. Differences between groups were assessed by pairwise Welch's t test. Correlation and linear regression analyses were used to examine the relationship of imaging parameters in LC and PM. Diagnostic accuracy was measured by the area under receiver operator characteristic curve (AUC) and validated based on resampling methods.

RESULTS

Significant differences between subgroups of LC and PMs were noted for all imaging parameters, with the highest number of significant pairs for IC. In univariate analysis, only IC was a significant diagnostic feature for discriminating LC from PM (p = 0.03). All quantitative imaging parameters correlated significantly (p < 0.0001, respectively), with the highest correlation between IC and Z^eff (r = 0.91), followed by IC and HU (r = 0.76) and Z^eff and HU (r = 0.73). Diagnostic models combining IC or Z^eff with HU (IC+HU: AUC = 0.73; Z^eff+HU: AUC = 0.69; IC+Z^eff+HU: AUC = 0.73) were not significantly different and outperformed individual parameters (IC: AUC = 0.57; Z^eff: AUC = 0.57; HU: AUC = 0.55) in diagnostic accuracy (p < 0.05, respectively).

CONCLUSION

DE-CT-derived IC or Z^eff and conventional HU represent complementary imaging parameters, which, if used in combination, may improve the differentiation between LC and PM.

KEY POINTS

• Individual quantitative imaging parameters derived from DE-CT (iodine concentration, effective Z) and conventional CT (HU) provide complementary diagnostic information for the differentiation of primary lung cancer and pulmonary metastases. • A combination of conventional HU and DE-CT parameters enhances the diagnostic utility of individual parameters.

Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography

Background

To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOI_O1, tumor plus outer layer 1; VOI_O2, tumor plus outer layers 1 and 2; VOI_I1, tumor minus inner layer 1; VOI_I2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis.

Results

A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOI_O1, and VOI_O2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P >  0.05).

Conclusions

Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.

Utility of Iodine Density Perfusion Maps From Dual-Energy Spectral Detector CT in Evaluating Cardiothoracic Conditions: A Primer for the Radiologist

OBJECTIVE. The purpose of this article is to outline the utility of iodine density maps for evaluating cardiothoracic disease and abnormalities. Multiple studies have shown that the variety of images generated from dual-energy spectral detector CT (SDCT) improve identification of cardiothoracic conditions. CONCLUSION. Understanding the technique of SDCT and being familiar with the features of different cardiothoracic conditions on iodine density map images help the radiologist make a better diagnosis.

Comparative study of dual energy CT iodine imaging and standardized concentrations before and after chemoradiotherapy for esophageal cancer

Background

To compare dual energy CT iodine imaging and standardized iodine concentration before and after chemoradiotherapy (CRT) for esophageal cancer and evaluate the efficacy of CRT for EC by examining DECT iodine maps and standard CT values.

Methods

The clinical data of 45 patients confirmed by pathology with newly diagnosed esophageal cancer who underwent concurrent CRT from February 2012 to January 2017 in our department of radiology were collected. All patients underwent dual-source dual-energy CT (DECT) before and after CRT. Normalized iodine concentration (NIC) and normalized CT (NCT) corresponding to the overall cancer lesion and its maximum cross-sectional area were observed and compared. Additionally, 30 healthy individuals were compared as control group. After treatment, the patients were divided into two groups according to RECIST1.1: treatment effective group and ineffective group.

Results

There were 33 patients (CR 9, PR 24) in the effective group and 12 patients (SD 12, PD 0) in the ineffective group. There was no significant difference in the NIC-A, NIC-V, NCT-A and NCT-A indexes between the effective group (B group) and the ineffective group (C group) before treatment (P > 0.05). After the treatment, the above-mentioned indexes in the effective group of patients were significantly lower than before treatment, and compared with the ineffective group, the NIC-A, NIC-V, NCT-A and NCT-V values of the effective group were significantly lower than those of ineffective group (P < 0.05). After treatment, the NIC-V and NCT-V in the ineffective group were lower than before treatment, and the difference was statistically significant (P < 0.05). However, their NIC-A and NCT-A were not statistically different from those before treatment (P > 0.05).

Conclusion

Using DECT iodine map, the changes of NIC and NIC before and after CRT in patients with esophageal cancer can evaluate the effect of CRT, and does not increase the radiation dose, so it is suitable for clinical use.

Assessing Chemotherapeutic Response in Pancreatic Ductal Adenocarcinoma: Histogram Analysis of Iodine Concentration and CT Number in Single-Source Dual-Energy CT

OBJECTIVE

The objective of this study was to evaluate the feasibility of histographic analysis of iodine concentration (IC) and CT number on single-source dual-energy CT (DECT) to assess response to first-line chemotherapy in patients with pancreatic ductal adenocarcinoma (PDAC) who received first-line chemotherapy but not radiation therapy.

SUBJECTS AND METHODS

This prospective study was approved by our institutional review board, and patients gave written informed consent. Sixty consecutive patients with PDAC undergoing first-line chemotherapy underwent DECT during the pancreatic parenchymatous phase (PPP) and the equilibrium phase (EP). The IC and CT number of PDAC were measured using PPP and EP iodine-based material decomposition and monochromatic images (65 keV), respectively. Histographic parameters for the IC and CT number of PDACs were obtained, and differences in mean IC (ΔIC) and CT number (ΔHU) between the PPP and the EP were calculated. These parameters were then compared between the response (partial response or stable disease) and nonresponse (progressive disease) groups.

RESULTS

Among the histographic parameters, the kurtosis of IC during the PPP (p = 0.018) and ΔIC (p = 0.0004) were identified as significant for differentiating between the two groups. IC diagnostic factor was calculated using the following coefficients of logistic regression analysis: 0.52 - (1.45 × kurtosis of IC during PPP) + (0.69 × ΔIC). The sensitivity, specificity, and area under the ROC curve for differentiating between the two groups were 97.7%, 70.6%, and 0.889, respectively.

CONCLUSION

The IC diagnostic factor is a potential biomarker for assessing chemotherapeutic response in patients with PDAC.

Effect of CT Acquisition Parameters on Iodine Density Measurement at Dual-Layer Spectral CT

OBJECTIVE

We aimed to evaluate the effect of tube voltage, tube current-time product, and iterative reconstruction on iodine quantification using a dual-layer spectral CT scanner.

MATERIALS AND METHODS

Two mediastinal iodine phantoms, each containing six tubes of different iodine concentrations (0, 1, 2.5, 5, 10, and 20 mg I/mL; the two phantoms had tubes with contrast media diluted in water and in 10% amino acid solution, respectively), were inserted into an anthropomorphic chest phantom and scanned with varying acquisition parameters (120 and 140 kVp; 20, 40, 60, 80, 100, 150, and 200 mAs; and spectral reconstruction levels 0 and 6). Thereafter, iodine density was measured (in milligrams of iodine per milliliter) using a dedicated software program, and the effect of acquisition parameters on iodine density and on its relative measurement error (RME) was analyzed using a linear mixed-effects model.

RESULTS

Tube voltages (all, p < 0.001) and tube current-time products (p < 0.05, depending on the interaction terms for iodine density; p = 0.023 for RME) had statistically significant effects on iodine density and RME. However, the magnitude of their effects was minimal. That is, estimated differences between tube voltage settings ranged from 0 to 0.8 mg I/mL for iodine density and from 1.0% to 4.2% for RME. For tube current-time product, alteration of 100 mAs caused changes in iodine density and RME of approximately 0.1 mg I/mL and 0.6%, respectively. Spectral level was not an affecting factor for iodine quantification (p = 0.647 for iodine density and 0.813 for RME).

CONCLUSION

Iodine quantification using dual-layer spectral CT was feasible irrespective of CT acquisition parameters because their effects on iodine density and RME were minimal.

The Role of Dual-Energy Computed Tomography in Assessment of Abdominal Oncology and Beyond

The added value and strength of dual energy computed tomography for the evaluation of oncologic patients revolve around the use of lower energy reconstructed images and iodine material density images. Lower keV simulated monoenergetic images optimize soft tissue tumor to nontumoral attenuation differences and increase contrast to noise ratios to improve lesion detection. Iodine material density images or maps are helpful from a qualitative standpoint for image interpretation because they result in improved detection and characterization of tumors and lymph node involvement, and from a quantitative assessment by enabling interrogation of specific properties of tissues to predict and assess therapeutic response.

Dual-energy CT-based iodine quantification to differentiate abdominal malignant lymphoma from lymph node metastasis

PURPOSE

To investigate the value of dual-energy computed tomography (DECT)-derived iodine and fat quantification in differentiating malignant abdominal lymphoma from lymph node metastasis.

MATERIALS AND METHODS

In this retrospective study, 59 patients (39 men; mean age, 62.7 years) with histopathologically-confirmed diagnosis of either malignant lymphoma or lymph node metastasis were included. For each lesion, contrast-enhanced attenuation, as well as DECT-derived iodine density and fat fraction measurements were recorded. Mean attenuation and material density values were compared between malignant lymphomas and lymph node metastases. The receiver operating characteristic (ROC) curve analysis was adopted to estimate the optimal threshold for discriminating between both entities. A control group (n = 60) was analyzed for comparison of attenuation and material density values of normal abdominal lymph nodes.

RESULTS

Assessment of DECT-derived iodine density and fat fraction values revealed significant differences between lymph node metastases (1.7 ± 0.4 mg/ml and 15.5 ± 7.3%) and malignant lymphomas (2.5 ± 0.5 mg/ml and 26.7 ± 12.2%) as well as normal lymph nodes (2.4 ± 0.8 mg/ml and 24.1 ± 10.8%) (P ≤ 0.013). An iodine concentration of 2.0 mg/ml represented the optimal threshold to discriminate between lymphoma and lymph node metastasis (sensitivity, 87%; specificity, 89%). Moreover, a significant correlation was found between iodine concentration and fat fraction for both lymphomas and lymph node metastases (P = 0.001).

CONCLUSION

DECT enables characterization of abdominal masses as derived iodine and fat fraction values differ significantly between malignant abdominal lymphomas and lymph node metastases.

Iodine quantification to distinguish hepatic neuroendocrine tumor metastasis from hepatocellular carcinoma at dual-source dual-energy liver CT

PURPOSE

To investigate the value of third-generation dual-source dual-energy computed tomography (DECT) iodine quantification to distinguish hepatic neuroendocrine tumor (NET) metastasis from hepatocellular carcinoma (HCC) in non-cirrhotic liver parenchyma.

MATERIAL AND METHODS

Forty-six patients (mean age, 64.9 ± 10.1 years; 28 male and 18 female) with either hepatic NET metastasis or HCC, who had undergone liver DECT, were included in this retrospective study. For each lesion, arterial-phase attenuation values and DECT quantitative parameters, including iodine uptake, fat fraction, normalized iodine uptake (NIU), and lesion-to-liver-parenchyma ratio (LPR) were evaluated. Available cumulative data from histopathology, MRI, PET/CT, or interval imaging follow-up served as the reference standard for all liver lesions. In addition, the diagnostic accuracy of contrast-enhanced and material decomposition analysis for the differentiation of hepatic NET metastasis and HCC was assessed using receiver operating characteristics (ROC) curve analysis.

RESULTS

Hepatic NET metastasis and HCC showed significant differences in arterial attenuation (P = 0.003), iodine uptake (P < 0.001), NIU (P < 0.001), and LPR (P = 0.003). No significant differences were found for unenhanced attenuation and fat fraction values (P = 0.686 and P = 0.892, respectively). NIU showed superior sensitivity (100%; iodine uptake, 71%), while both iodine uptake and NIU revealed superior specificity (100% and 90%, respectively) compared to LPR (sensitivity, 96%; specificity, 80%) and arterial attenuation analysis (sensitivity, 79%; specificity, 80%) (P ≤ 0.016).

CONCLUSION

Third-generation DECT with assessment of iodine uptake improves the differentiation of hepatic NET metastasis and HCC in non-cirrhotic liver, with NIU showing the strongest diagnostic performance.

Response assessment in pancreatic ductal adenocarcinoma: role of imaging

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal (GI) malignancy with poor 5-year survival rate. Advances in surgical techniques and introduction of novel combination chemotherapy and radiation therapy regimens have necessitated the need for biomarkers for assessment of treatment response. Conventional imaging methods such as RECIST have been used for response evaluation in clinical trials particularly in patients with metastatic PDAC. However, the role of these approaches for assessing response to loco-regional and systemic therapies is limited due to complex morphological and histological nature of PDAC. Determination of tumor resectability after neoadjuvant therapy remains a challenge. This review article provides an overview of the challenges and limitations of response assessment in PDAC and reviews the current evidence for the utility of novel morphological and functional imaging tools in this disease.

Assessment of iodine uptake by pancreatic cancer following chemotherapy using dual-energy CT

Pancreatic cancer remains a major health problem, and only less than 20% of patients have resectable disease at the time of initial diagnosis. Systemic chemotherapy is often used in the patients with borderline resectable, locally advanced unresectable disease and metastatic disease. CT is often used to assess for therapeutic response; however, conventional imaging including CT may not correctly reflect treatment response after chemotherapy. Dual-energy (DE) CT can acquire datasets at two different photon spectra in a single CT acquisition, and permits separating materials and extract iodine by applying a material decomposition algorithm. Quantitative iodine mapping may have an added value over conventional CT imaging for monitoring the treatment effects in patients with pancreatic cancer and potentially serve as a unique biomarker for treatment response. In this pictorial essay, we will review the technique for iodine quantification of pancreatic cancer by DECT and discuss our observations of iodine quantification at baseline and after systemic chemotherapy with conventional cytotoxic agents, and illustrate example cases.