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

Dual-energy CT for evaluating the tumor regression grade of gastric cancer after neoadjuvant chemotherapy

OBJECTIVES

To evaluate the clinical value of dual-energy CT (DECT) parameters in estimating tumor regression grade (TRG) of gastric cancer after neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

In this retrospective study, the patients with pathologically confirmed gastric cancer were classified into two groups based on TRG results: the effective group and the ineffective group. DECT parameters, including iodine concentration (IC), normalized iodine concentration (NIC), and slope of the energy spectrum curve (λ), were obtained. Quantitative parameters and their change rates were compared before and after chemotherapy. The receiver operating characteristic (ROC) curves were plotted.

RESULTS

A total of 54 patients were included and divided into the effective group (n = 21) and the ineffective group (n = 33). After NAC, the change rates of parameters in the venous phase (%ΔIC-v, %ΔNIC-v, and %Δλ-v) were notably higher in the effective group were higher than in the ineffective group (all p < 0.05). The consistency between the response evaluation criteria in solid tumors version 1.1 (RECIST 1.1) and TRG was fair, with a Kappa value of 0.299 (p < 0.05). The %ΔIC-v, %ΔIC-d, %ΔNIC-v, %ΔNIC-d, and %Δλ-v exhibited moderate or strong correlations with TRG, with correlation coefficients (r) of -0.624, -0.475, -0.766, -0.516, and -0.431, respectively (all p < 0.05). %ΔNIC-v achieved a significantly greater area under the curve (AUC) compared to RECIST 1.1 (AUC, 0.877; 95% CI: 0.772-0.957; vs AUC, 0.649; 95% CI: 0.496-0.803; p < 0.05) for estimating TRG in gastric cancer.

CONCLUSION

DECT parameters, particularly %ΔNIC-v, show promise in assessing the efficacy of NAC for gastric cancer.

KEY POINTS

Question Two-dimensional morphological change is insufficient for accurately assessing the pathological TRG following NAC in gastric cancer. Findings DECT parameters show higher preoperative predictive efficacy than RECIST 1.1 for TRG in gastric cancer. Clinical relevance DECT-derived quantitative parameters offer a reliable and noninvasive tool for the preoperative prediction of pathological response in gastric cancer patients undergoing NAC.

Nomogram based on dual-energy computed tomography to predict the response to induction chemotherapy in patients with nasopharyngeal carcinoma: a two-center study

BACKGROUND

Previous studies utilizing dual-energy CT (DECT) for evaluating treatment efficacy in nasopharyngeal cancinoma (NPC) are limited. This study aimed to investigate whether the parameters from DECT can predict the response to induction chemotherapy in NPC patients in two centers.

METHODS

This two-center retrospective study included patients diagnosed with NPC who underwent contrast-enhanced DECT between March 2019 and November 2023. The clinical and DECT-derived parameters of tumor lesions were calculated to predict the response. We employed univariate and multivariate analysis to identify significant factors. Subsequently, the clinical, DECT, and clinical-DECT nomogram models were developed using independent predictors in the training cohort and validated in the test cohort. Receiver operating characteristic analysis was performed to evaluate the models' performance.

RESULTS

A total of 321 patients were included in the study, predominantly male [247 (76.9%)] with an average age of 52.04 ± 10.87 years. The training cohort (Center 1) comprised 252 patients, while the test cohort (Center 2) comprised 69 patients. Of these, 233 out of 321 patients (72.6%) were responders to induction chemotherapy. The clinical-DECT nomogram showed an AUC of 0.805 (95% CI, 0.688-0.906), outperforming both the DECT model (Extracellular volume fraction [ECVf]) (AUC, 0.706 [95% CI, 0.571-0.825]) and the clinical model (Ki67) (AUC, 0.693 [95% CI, 0.580-0.806]) in the test cohort.

CONCLUSIONS

Ki67 and ECVf emerged as independent predictive factors for response to induction chemotherapy in NPC patients. The proposed nomogram, incorporating ECVf, demonstrated accurate prediction of treatment response.

Dual-energy CT iodine concentration as a biomarker for immunotherapy treatment response in metastatic melanoma and renal cell carcinoma patients

OBJECTIVE

To investigate the predictive value of tumor iodine concentration obtained with dual-energy CT (DECT) for treatment response in patients treated with immune checkpoint inhibitors (ICI).

MATERIALS AND METHODS

Retrospective single-center study of consecutive metastatic melanoma and renal cell carcinoma (RCC) patients undergoing first-line ICI treatment. The iodine concentration measurement time points include prior to initiation of therapy (baseline [BL]), after initiation (follow-up [FU1]), and either time point nearest to 12 months or at time of progression (final follow-up [FFU]). Target lesion DECT-based whole-volume tumor normalized iodine concentration average (NICave) and size measurements were obtained. Reference standard was individual lesion FFU status categorized as responders or nonresponders per RECIST 1.1. Logistic regression model assessed NICave change and FU1 lesion response as predictors of FFU lesion outcome. Model's performance was summarized with AUC. Intraclass correlation coefficient (ICC) summarized inter-rater agreement of NICave.

RESULTS

Forty-six patients were included (mean age 61 ± 11 years, 12 women; 16 melanoma). Sixty-four of 175 target lesions were confirmed nonresponders at FFU. In a multivariable model, lesion status at FU1 (odds ratio [OR]: 27.4, p < 0.001) and changes in NICave from BL to FU1 (OR: 2.42 per 1-SD increase, p = 0.019) were significant predictors of lesion status at FFU. The model's AUC was 0.86 (95% CI: 0.76-0.93). Inter-rater reliability of NICave was 0.98 (95% CI: 0.97-0.99).

CONCLUSIONS

Changes in iodine concentration from baseline to first follow-up improve identification of delayed responding metastatic melanoma and RCC lesions treated with immune checkpoint inhibitor, initially classified as nonresponders by size change.

KEY POINTS

Question How can pseudoprogression/delayed treatment response in metastatic renal cell carcinoma (RCC) and melanoma patients on first-line immune checkpoint inhibitors be accurately identified? Findings Combining iodine concentration change from Dual-energy CT (baseline to first follow-up) with RECIST-based lesion size change improved prediction of final lesion outcome. Clinical relevance DECT-based whole-volume tumor iodine concentration for target lesions is useful as a predictive imaging biomarker for distinguishing delayed response from true progression in patients with metastatic RCC and melanoma treated with first-line immune checkpoint inhibitors.

AAPM Task Group Report 299: Quality control in multi-energy computed tomography

Multi-energy computed tomography (MECT) offers the opportunity for advanced visualization, detection, and quantification of select elements (e.g., iodine) or materials (e.g., fat) beyond the capability of standard single-energy computed tomography (CT). However, the use of MECT requires careful consideration as substantially different hardware and software approaches have been used by manufacturers, including different sets of user-selected or hidden parameters that affect the performance and radiation dose of MECT. Another important consideration when designing MECT protocols is appreciation of the specific tasks being performed; for instance, differentiating between two different materials or quantifying a specific element. For a given task, it is imperative to consider both the radiation dose and task-specific image quality requirements. Development of a quality control (QC) program is essential to ensure the accuracy and reproducibility of these MECT applications. Although standard QC procedures have been well established for conventional single-energy CT, the substantial differences between single-energy CT and MECT in terms of system implementations, imaging protocols, and clinical tasks warrant QC tests specific to MECT. This task group was therefore charged with developing a systematic QC program designed to meet the needs of MECT applications. In this report, we review the various MECT approaches that are commercially available, including information about hardware implementation, MECT image types, image reconstruction, and postprocessing techniques that are unique to MECT. We address the requirements for MECT phantoms, review representative commercial MECT phantoms, and offer guidance regarding homemade MECT phantoms. We discuss the development of MECT protocols, which must be designed carefully with proper consideration of MECT technology, imaging task, and radiation dose. We then outline specific recommended QC tests in terms of general image quality, radiation dose, differentiation and quantification tasks, and diagnostic and therapeutic applications.

Predicting lymphovascular invasion in N0 stage non-small cell lung cancer: A nomogram based on Dual-energy CT imaging and clinical findings

PURPOSE

To construct a nomogram for predicting lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC) using dual-energy computed tomography (DECT) findings combined with clinical findings.

METHODS

We retrospectively recruited 135 patients with N0 stage NSCLC from two hospitals underwent DECT before surgery and were divided into development cohort (n = 107) and validation cohort (n = 28). The clinical findings (baseline characteristics, biochemical markers, serum tumor markers and Immunohistochemical markers), DECT-derived parameters (iodine concentration [IC], effective atomic number [Eff-Z] and normalized iodine concentration [NIC], iodine enhancement [IE] and NIC ratio [NICr]) and Fractal dimension (FD) were collected and measured. A nomogram was constructed using significant findings to predict LVI in N0 stage NSCLC and was externally validated.

RESULTS

Multivariable analysis revealed that lymphocyte count (LYMPH, odds ratio [OR]: 3.71, P=0.014), IC in arterial phase (ICa, OR: 1.25, P=0.021), NIC in venous phase (NICv, OR: 587.12, P=0.009) and FD (OR: 0.01, P=0.033) were independent significant factors for predicting LVI in N0 stage NSCLC, and were used to construct a nomogram. The nomogram exhibited robust predictive capabilities in both the development and validation cohort, with AUCs of 0.819 (95 % CI: 72.6-90.4) and 0.844 (95 % CI: 68.2-95.8), respectively. The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of positive LVI, on external validation.

CONCLUSIONS

Combination of clinical and DECT imaging findings could aid in predicting LVI in N0 stage NSCLC using significant findings of LYMPH, ICa, NICv and FD.

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.

Gold nanoparticles spectral CT imaging and limit of detectability in a new materials contrast-detail phantom

This study involves the synthesis, characterization, and spectral photon counting CT (SPCCT) imaging of gold nanoparticles tailored for enhancing the contrast of small cancer lesions. We used the modified Turkevich method to produce thiol-capped gold nanoparticles (AuNPs) at different concentrations (20, 15, 10, 5, 2.5, 1.25, 0.6 mg/ml). We thoroughly characterized the AuNPs using Transmission Electron Microscopy (TEM), X-ray diffraction spectroscopy (XRD), Dynamic Light Scattering (DLS), and UV-visible absorption spectroscopy. To assess the AuNPs contrast enhancing performance, we designed and built a new material contrast detail phantom for CT imaging and determined the minimum detectable concentrations of AuNPs in simulated lesions of small diameters (1, 2, 3, and 5 mm). The synthesized AuNPs are spherical with an average size of approximately 20 ± 4 nm, with maximum UV absorption occurring at 527 nm wavelength, and exhibit a face-centered cubic structure of gold according to XRD analysis. The synthesized gold nanoparticles demonstrated high contrast in SPCCT, suggesting their potential as contrast agents for imaging cancer tissues. The AuNPs image contrast was directly proportional to the AuNPs concentration. We are the first to determine that the lowest visually distinguishable contrast was achieved at a gold concentration of 5 mg/ml for a 2 mm simulated lesion. For 1 mm size lesion the smallest visible concentration was 10 mg/ml. This newly developed phantom can be used for determining the minimal concentration required for various high-Z nanoparticles to produce detectable contrast in X-ray imaging for small-size simulated lesions.

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.

The value of dual-energy spectral CT in differentiating solitary pulmonary tuberculosis and solitary lung adenocarcinoma

BACKGROUND

To explore the value of dual-energy spectral CT in distinguishing solitary pulmonary tuberculosis (SP-TB) from solitary lung adenocarcinoma (S-LUAD).

METHODS

A total of 246 patients confirmed SP-TB (n = 86) or S-LUAD (n = 160) were retrospectively included. Spectral CT parameters include CT40keV value, CT70keV value, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff), and spectral curve slope (λ70keV). Data were measured during the arterial phase (AP) and venous phase (VP). Chi-square test was used to compare categorical variables, Wilcoxon rank-sum test was used to compare continuous variables, and a two-sample t-test was used to compare spectral CT parameters. ROC curves were used to calculate diagnostic efficiency.

RESULTS

There were significant differences in spectral CT quantitative parameters (including CT40keV value [all P< 0.001] , CT70keV value [all P< 0.001], λ70keV [P< 0.001, and P = 0.027], Zeff [P =0.015, and P = 0.001], and IC [P =0.002, and P = 0.028]) between the two groups during the AP and VP. However, WC (P = 0.930, and P = 0.823) was not statistically different between the two groups. The ROC curve analysis showed that the AUC in the AP and VP was 90.9% (95% CI, 0.873-0.945) and 83.4% (95% CI, 0.780-0.887), respectively. The highest diagnostic performance (AUC, 97.6%; 95% CI, 0.961-0.991) was achieved when all spectral CT parameters were combined with clinical variables.

CONCLUSION

Dual-energy spectral CT has a significant value in distinguishing SP-TB from S-LUAD.

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.

An Unusual Presentation of Duodenal Metastasis of a Previously Undiagnosed Primary Lung Adenocarcinoma

A cancer diagnosis can be a frightening experience for both patients and their families. It is at this juncture that a prompt diagnosis of cancer becomes vital. Lung cancer is the leading cause of cancer-related deaths in men and women due to its aggressive nature and widespread metastasis. A metastatic lesion leading to the diagnosis of cancer followed by identifying the primary source is not unusual. Still, it is very uncommon for cancer to present with signs and symptoms of an infectious abscess. We report a case of metastatic adenocarcinoma of the lung that presented as an abdominal abscess. This article aims to bring more awareness among the medical community to include cancer in the differential for early diagnosis of potentially lethal cancer.

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.

Quantitative distribution of iodinated contrast media in body computed tomography: data from a large reference cohort

OBJECTIVES

Dual-energy computed tomography allows for an accurate and reliable quantification of iodine. However, data on physiological distribution of iodine concentration (IC) is still sparse. This study aims to establish guidance for IC in abdominal organs and important anatomical landmarks using a large cohort of individuals without radiological tumor burden.

METHODS

Five hundred seventy-one oncologic, portal venous phase dual-layer spectral detector CT studies of the chest and abdomen without tumor burden at time point of imaging confirmed by > 3-month follow-up were included. ROI were placed in parenchymatous organs (n = 25), lymph nodes (n = 6), and vessels (n = 3) with a minimum of two measurements per landmark. ROI were placed on conventional images and pasted to iodine maps to retrieve absolute IC. Normalization to the abdominal aorta was conducted to obtain iodine perfusion ratios. Bivariate regression analysis, t tests, and ANOVA with Tukey-Kramer post hoc test were used for statistical analysis.

RESULTS

Absolute IC showed a broad scatter and varied with body mass index, between different age groups and between the sexes in parenchymatous organs, lymph nodes, and vessels (range 0.0 ± 0.0 mg/ml-6.6 ± 1.3 mg/ml). Unlike absolute IC, iodine perfusion ratios did not show dependency on body mass index; however, significant differences between the sexes and age groups persisted, showing a tendency towards decreased perfusion ratios in elderly patients (e.g., liver 18-44 years/≥ 64 years: 0.50 ± 0.11/0.43 ± 0.10, p ≤ 0.05).

CONCLUSIONS

Distribution of IC obtained from a large-scale cohort is provided. As significant differences between sexes and age groups were found, this should be taken into account when obtaining quantitative iodine concentrations and applying iodine thresholds.

KEY POINTS

• Absolute iodine concentration showed a broad variation and differed between body mass index, age groups, and between the sexes in parenchymatous organs, lymph nodes, and vessels. • The iodine perfusion ratios did not show dependency on body mass index while significant differences between sexes and age groups persisted. • Provided guidance values may serve as reference when aiming to differentiate healthy and abnormal tissue based on iodine perfusion ratios.

Assessment of Solitary Pulmonary Nodules Based on Virtual Monochrome Images and Iodine-Dependent Images Using a Single-Source Dual-Energy CT with Fast kVp Switching

With lung cancer being the most common malignancy diagnosed worldwide, lung nodule assessment has proved to be one of big challenges of modern medicine. The aim of this study was to examine the usefulness of Dual Energy Computed Tomography (DECT) in solitary pulmonary nodule (SPN) assessment. Between January 2017 and June 2018; 65 patients (42 males and 23 females) underwent DECT scans in the late arterial phase (AP) and venous phase (VP). We concluded that imaging at an energy level of 65 keV was the most accurate in detecting malignancy in solitary pulmonary nodules (SPNs) measuring ≤30 mm in diameter on virtual monochromatic maps. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. As for iodine concentration maps, the analysis of venous phase images resulted in the highest clinical usefulness. To summarize, DECT may be a useful tool in the differentiation of benign and malignant SPNs. A single-phase DECT examination with scans acquired 90 s after contrast media injection is recommended.

A Single Enhanced Dual-Energy CT Scan May Distinguish Lung Squamous Cell Carcinoma From Adenocarcinoma During the Venous phase

RATIONALE AND OBJECTIVES

To investigate whether iodine quantification extracted from enhanced dual energy-computed tomography (DE-CT) is useful for distinguishing lung squamous cell carcinoma from adenocarcinoma and to evaluate whether a single scan evaluated during the venous phase (VP) can be substituted for scans evaluated during other phases.

MATERIALS AND METHODS

Sixty-two patients with lung cancer (32 squamous cell carcinomas; 30 adenocarcinomas) underwent enhanced dual-phase DE-CT scans, including an arterial phase and VP. The iodine concentration (IC), normalized iodine concentration (NIC), and slope of the curve (K) in lesions were measured during two scanning phases in two different pathological types of lung cancers. The differences in parameters (IC, NIC, and K) between these two types of lung cancers were statistically analyzed. In addition, the receiver operating characteristic curves of these parameters were performed to discriminate squamous cell carcinoma from adenocarcinoma.

RESULTS

The mean IC, NIC, and K in adenocarcinomas were all higher than those in squamous cell carcinomas during the two scanning phases. However, the differences in these parameters between the two types of cancers were significant only during the VP, not during the arterial phase. Receiver operating characteristic analysis demonstrated that the optimal thresholds of the IC, NIC, and K for discriminating squamous cell carcinoma from adenocarcinoma were 1.550, 0.227, and 1.608, respectively. In addition, the sensitivity, specificity, and area under the curve were 81.2%, 83.3%, and 0.871 for the IC; 56.2%, 93.3%, and 0.800 for the NIC; and 65.6%, 80%, and 0.720 for the K; 81.3%, 83.3%, and 0.874 for the IC + NIC; 68.8%, 93.3%, and 0.891 for the IC + NIC + K, respectively. The "IC + NIC + K" had the highest diagnostic efficiency for discriminating two types of lung cancers, but with low sensitivity. Whereas, "IC"and "IC + NIC" had the similar lower diagnostic efficiency, but with high sensitivity and specificity.

CONCLUSION

The iodine quantification parameters derived from enhanced DE-CT during the VP may be useful for distinguishing lung squamous cell carcinoma from adenocarcinoma.

Extra-abdominal dual-energy CT applications: a comprehensive overview

Unlike conventional computed tomography, dual-energy computed tomography is a relatively novel technique that exploits ionizing radiations at different energy levels. The separate radiation sets can be achieved through different technologies, such as dual source, dual layers or rapid switching voltage. Body tissue molecules vary for their specific atomic numbers and electron density, and the interaction with different sets of radiations results in different attenuations, allowing to their final distinction. In particular, iodine recognition and quantification have led to important information about intravenous contrast medium delivery within the body. Over the years, useful post-processing algorithms have also been validated for improving tissue characterization. For instance, contrast resolution improvement and metal artifact reduction can be obtained through virtual monoenergetic images, dose reduction by virtual non-contrast reconstructions and iodine distribution highlighting through iodine overlay maps. Beyond the evaluation of the abdominal organs, dual-energy computed tomography has also been successfully employed in other anatomical districts. Although lung perfusion is one of the most investigated, this evaluation has been extended to narrowly fields of application, such as musculoskeletal, head and neck, vascular and cardiac. The potential pool of information provided by dual-energy technology is already wide and not completely explored, yet. Therefore, its performance continues to raise increasing interest from both radiologists and clinicians.

Dual-Energy CT: Lower Limits of Iodine Detection and Quantification

Background Assessments of the quantitative limitations among the six commercially available dual-energy (DE) CT acquisition schemes used by major CT manufacturers could aid researchers looking to use iodine quantification as an imaging biomarker. Purpose To determine the limits of detection and quantification of DE CT in phantoms by comparing rapid peak kilovoltage switching, dual-source, split-filter, and dual-layer detector systems in six different scanners. Materials and Methods Seven 50-mL iohexol solutions were used, with concentrations of 0.03-2.0 mg iodine per milliliter. The solutions and water sample were scanned five times each in two phantoms (small, 20-cm diameter; large, 30 × 40-cm diameter) with six DE CT systems and a total of 10 peak kilovoltage settings or combinations. Iodine maps were created, and the mean iodine signal in each sample was recorded. The limit of blank (LOB) was defined as the upper limit of the 95% confidence interval of the water sample. The limit of detection (LOD) was defined as the concentration with a 95% chance of having a signal above the LOB. The limit of quantification (LOQ) was defined as the lowest concentration where the coefficient of variation was less than 20%. Results The LOD range was 0.021-0.26 mg/mL in the small phantom and 0.026-0.55 mg/mL in the large phantom. The LOQ range was 0.07-0.50 mg/mL in the small phantom and 0.20-1.0 mg/mL in the large phantom. The dual-source and rapid peak kilovoltage switching systems had the lowest LODs, and the dual-layer detector systems had the highest LODs. Conclusion The iodine limit of detection using dual-energy CT systems varied with scanner and phantom size, but all systems depicted iodine in the small and large phantoms at or below 0.3 and 0.5 mg/mL, respectively, and enabled quantification at concentrations of 0.5 and 1.0 mg/mL, respectively. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Hindman in this issue.