Dual-Energy CT-Derived Electron Density for Diagnosing Metastatic Mediastinal Lymph Nodes in Non-Small Cell Lung Cancer: Comparison With Conventional CT and FDG PET/CT Findings

Potential of spectral imaging generated by contrast-enhanced dual-energy CT for lung cancer histopathological classification - A preliminary study

Purpose

The potential of spectral images, particularly electron density and effective Z-images, generated by dual-energy computed tomography (DECT), for the histopathologic classification of lung cancer remains unclear. This study aimed to explore which imaging factors could better reflect the histopathological status of lung cancer.

Method

The data of 31 patients who underwent rapid kV-switching DECT and subsequently underwent surgery for lung cancer were analyzed. Virtual monochromatic images (VMIs) of 35 keV and 70 keV, virtual non-contrast images (VNC), iodine content images, electron density images, and effective Z-images were reconstructed for the following analyses: 1) correlation with the ratio of the lepidic growth pattern in the whole tumor and 2) comparisons with the four histological groups: well-differentiated adenocarcinoma (WDA), moderately differentiated adenocarcinoma (MDA), and poorly differentiated adenocarcinoma (PDA) and squamous cell carcinoma (SCC).

Results

There were significant correlations between the ratio of lepidic growth pattern and 70 keV, 35 keV, VNC, and electron density images (r = -0.861, P < 0.001; r = -0.791, P < 0.001; r = -0.869, P < 0.001; r = -0.871, P < 0.001, respectively). There were significant differences in the 70 keV, 35 keV, VNC, and electron density images in the Kruskal-Wallis test (P = 0.001, P = 0.006, P < 0.001, P < 0.001, respectively). However, there were no significant differences in iodine content or effective Z-images.

Conclusions

Electron density images generated by spectral imaging may be better indicators of the histopathological classification of lung cancer.

Clinical relevance

Electron density images may have an added value in predicting the histopathological classification of lung cancer.

Key points

•The role of electron density and effective Z-images obtained using dual-energy CT in lung cancer classification remains unclear.•Electron density and virtual non-contrast images correlated better with the ratio of lepidic growth patterns in lung cancer.•Electron density imaging is a better indicator of the histopathological classification of lung cancer than effective Z-imaging.

A Clinical-Radiomic Combined Model based on Dual-Layer Spectral CT for Predicting Pathological T4 in Gastric Cancer

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a dual-layer spectral CT based clinical-radiomic model for pre-treatment prediction of pathological T4 (pT4) in gastric cancer (GC) patients.

MATERIALS AND METHODS

This retrospective study included 148 surgically confirmed GC patients who underwent dual-layer spectral CT scanning before surgery and were divided into a training (n=104) and test (n=44) cohorts. Subjective assessments were performed based on conventional 120-kV CT images by two readers. Clinical models were developed using patient demographics, serum tumor markers, and image features from CT scans. Radiomics model included features extracted from conventional 120-kV CT and dual-layer CT-derived spectral base image (SBI), such as virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density (ID), effective atomic number (Zeff), and electron density (ED) images for both the arterial phase (AP) and portal venous phase (PVP). A clinical-radiomic combined model was developed and visualized using a nomogram.

RESULTS

Tumor thickness on CT and serum level of CA19-9 levels were identified as independent predictors. The clinical-radiomic combined model demonstrated superior performance compared to subjective image interpretation and other models, with an AUC of 0.906 (95% CI, 0.848-0.963) in the training cohort and 0.873 in the test cohort. The nomogram was significantly associated with pT4 status, supporting its potential utility in clinical prediction.

CONCLUSION

The integration of clinical characteristics with radiomic features from conventional CT and dual-layer CT-derived SBI achieved a high diagnostic accuracy for predicting pT4 in GC patients. This combined approach could assist in treatment planning and patient management in GC.

Review of the application of dual-energy CT combined with radiomics in the diagnosis and analysis of lung cancer

Lung cancer is one of the most common malignant tumors in the world. Early detection and precise treatment are of great significance to clinical decision-making and patient prognosis. As an emerging imaging technology, dual-energy computed tomography (DECT) has increasingly prominent advantages in multi-parameter and quantitative analysis in assessing the benign and malignant, classification, and prognosis of lung cancer. Radiomics uses an automated high-throughput method to extract a large number of quantitative features from medical images, quantify tumor heterogeneity, monitor tumor development and prognosis, and provide new ideas for the diagnosis and identification of lung cancer. This article will review the application progress of DECT post-processing technology combined with radiomics in lung cancer diagnosis, identification, biomarker and gene prediction, and prognosis assessment.

Multiparametric gadoxetic acid-enhanced MR versus dual-layer spectral detector CT for differentiating hepatocellular carcinoma from hypervascular pseudolesions

BackgroundIt can be difficult to differentiate hypervascular hepatocellular carcinoma (HCC) from hypervascular pseudolesion (HPL) such as arteriovenous shunts.PurposeTo determine retrospectively whether double-layer detector computed tomography (DLCT) can differentiate HCC from HPL compared to gadoxetate-enhanced magnetic resonance imaging (EOB-MRI).Material and MethodsWe retrospectively analyzed 46 patients who underwent EOB-MRI and DLCT for suspected HCCs. Arterial/portal phase and hepatobiliary phase (HBP) on EOB-MRI, T2-weighted (T2W) imaging, diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), CT value, iodine-density (ID), atomic-number (Zeff), and electron-density (ED) of the lesion and liver were evaluated. The reduction rates of ID (R-ID) between each phase of the arterial/portal phase on EOB-MRI were calculated. ROC analysis was performed to determine the accuracy for differentiating HCC from HPL.ResultsThere were 55 HCCs and 14 HPLs. On DWI, 42, 11, and two HCCs showed high, slightly high, and iso intensity, respectively. However, all 14 HPLs showed iso intensity on DWI. Area under ROC curve (AUC) of DWI (0.982, 95% confidence interval [CI]=0.957-1) was significantly higher than that of HBP (AUC=0.714; 95% CI=0.580-0.849; P < 0.001), R-ID (AUC=0.742, 95% CI=0.580-0.903; P = 0.004), and ED of portal phase (AUC=0.786, 95% CI=0.640-0.891; P = 0.001) in differentiating HCC and HPL. ADC (<0.001), T2W imaging (<0.001), HBP (<0.001), ED-arterial-phase (<0.001), ED-portal-phase (=0.003), ED-equilibrium-phase (=0.001), R-ID-between-arterial/equilibrium-phase (=0.032), and R-ID-between-portal/equilibrium-phase (=0.042) showed significant differences between HPL and HCC.ConclusionDWI is most useful for differentiating HCC from HPL, although ADC, T2W, HBP, R-ID, and ED may also be relatively useful to differentiate between HPLs and HCCs.

Efficacy of dual-layer spectral detector computed tomography for detecting early ischemic changes in patients with acute ischemic stroke: A pilot study

Objectives

This study evaluated the efficacy of dual-layer spectral detector computed tomography (DLCT) for detecting early ischemic changes (EICs) in patients with acute ischemic stroke (AIS), focusing on electron density (ED) and effective atomic number (effective Z) imaging.

Material and Methods

This retrospective study included 15 patients (mean age: 76.5 ± 9.8 years) with AIS who underwent non-contrast computed tomography (CT) with DLCT and magnetic resonance imaging (MRI) on the same day. Quantitative analysis was performed to compare conventional CT, ED, and effective Z values between the infarcted and contralateral brain regions. Qualitative assessment was conducted by two radiologists using the modified Alberta Stroke Program Early CT Score methodology. Receiver operating characteristic curve analysis was performed to evaluate diagnostic performance, and kappa statistics were used to assess interobserver agreement.

Results

Significant differences were observed in the conventional CT and ED values (P < 0.01) but not in effective Z values (P = 0.46) between the infarcted and contralateral regions. ED imaging demonstrated superior diagnostic accuracy (area under curve [AUC] = 0.90) compared with conventional 120-kVp CT (AUC = 0.85) and effective Z imaging (AUC = 0.62). Furthermore, interobserver agreement (kappa = 0.71) was better for ED imaging than for conventional 120-kVp CT (kappa = 0.65). Qualitative analysis revealed that ED images showed better agreement with MRI findings and higher interobserver consistency than conventional 120-kVp images.

Conclusion

Compared with conventional CT, DLCT with ED imaging significantly enhanced detection of EICs in AIS.

Solid-type adenocarcinoma on thin-section CT: quantitative parameters from dual-energy CT associated with spread through air spaces

BackgroundSpread through air spaces (STAS) is a well-established factor associated with poor oncological outcomes in patients undergoing surgery for solid lung adenocarcinoma. There could potentially be a disparity in iodine uptake between patients with positive and negative airway spread of solid lung adenocarcinoma.PurposeTo explore the associations and find correlations of iodine uptake with STAS status in patients who underwent surgery for solid lung adenocarcinoma.Material and MethodsPatients who underwent solid lung adenocarcinoma resection between January and June 2022 were included in this retrospective study. Iodine concentration and CT features were assessed using contrast-enhanced dual-energy computed tomography (DECT) scans, and these were compared with the status of STAS.ResultsOf 52 patients included, 25 (48%) were STAS-positive and 27 (52%) were STAS-negative. There were no statistically significant differences in CT features between the two groups (P > 0.05). STAS-positive was significantly associated with low arterial phase iodine concentration (ICA), normalized arterial phase iodine concentration (NICA), and venous phase iodine concentration (ICV), with a cutoff established at 1.15 mg/mL, 0.11, and 1.35 mg/mL, respectively (P < 0.05). The AUCs for ICA, NICA, and ICV in predicting STAS in solid lung adenocarcinoma were 0.82, 0.83, and 0.73, respectively. ICA and NICA were identified as independent risk factors for STAS in solid lung adenocarcinoma, with a combined AUC of 0.89.ConclusionThis study suggests that solid lung adenocarcinoma patients with low ICA, NICA, and ICVA were associated with STAS-positive, as well as a worse survival outcomes.

Quantitative multi-energy CT in oncology: State of the art and future directions

Multi-energy computed tomography (CT) involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different X-ray energies, multi-energy CT allows distinction of tissues and materials. Multi-energy technology encompasses different types of CT systems, such as dual-energy CT and photon-counting CT, that can use information from the energy and type of material present in acquired images to create multiple datasets. These scanners have overcome many of the limitations of conventional CT, making it possible to improve the diagnostic performance of CT and expand its use to new applications through better tissue characterization and multiple quantitative parameters. Quantitative imaging biomarkers based on multi-energy CT have enormous potential in oncologic imaging, from the diagnosis and characterization of tumor phenotypes to the evaluation of the response to treatment. Nevertheless, implementing these techniques in clinical practice remains challenging. This article reviews the basic principles underlying multi-energy CT and the most recent technical developments in these systems together with their advantages and limitations to establish the value of quantitative imaging derived from multi-energy CT in the field of oncology.

Predicting lymph node metastasis of clinical T1 non-small cell lung cancer: a brief review of possible methodologies and controversies

Non-small cell lung cancer (NSCLC) is a major subtype of lung cancer and poses a serious threat to human health. Due to the advances in lung cancer screening, more and more clinical T1 NSCLC defined as a tumor with a maximum diameter of 3cm surrounded by lung tissue or visceral pleura have been detected and have achieved favorable treatment outcomes, greatly improving the prognosis of NSCLC patients. However, the preoperative lymph node staging and intraoperative lymph node dissection patterns of operable clinical T1 NSCLC are still subject to much disagreement, as well as the heterogeneity between primary tumors and metastatic lymph nodes poses a challenge in designing effective treatment strategies. This article comprehensively describes the clinical risk factors of clinical T1 NSCLC lymph node metastasis, and its invasive and non-invasive prediction, focusing on the genetic heterogeneity between the primary tumor and the metastatic lymph nodes, which is significant for a thoroughly understanding of the biological behavior of early-stage NSCLC.

Impact on Image Quality and Diagnostic Performance of Dual-Layer Detector Spectral CT for Pulmonary Subsolid Nodules: Comparison With Hybrid and Model-Based Iterative Reconstruction

OBJECTIVE

To evaluate the image quality and diagnostic performance of pulmonary subsolid nodules on conventional iterative algorithms, virtual monoenergetic images (VMIs), and electron density mapping (EDM) using a dual-layer detector spectral CT (DLSCT).

METHODS

This retrospective study recruited 270 patients who underwent DLSCT scan for lung nodule screening or follow-up. All CT examinations with subsolid nodules (pure ground-glass nodules [GGNs] or part-solid nodules) were reconstructed with hybrid and model-based iterative reconstruction, VMI at 40, 70, 100, and 130 keV levels, and EDM. The CT number, objective image noise, signal-to-noise ratio, contrast-to-noise ratio, diameter, and volume of subsolid nodules were measured for quantitative analysis. The overall image quality, image noise, visualization of nodules, artifact, and sharpness were subjectively rated by 2 thoracic radiologists on a 5-point scale (1 = unacceptable, 5 = excellent) in consensus. The objective image quality measurements, diameter, and volume were compared among the 7 groups with a repeated 1-way analysis of variance. The subjective scores were compared with Kruskal-Wallis test.

RESULTS

A total of 198 subsolid nodules, including 179 pure GGNs, and 19 part-solid nodules were identified. Based on the objective analysis, EDM had the highest signal-to-noise ratio (164.71 ± 133.60; P < 0.001) and contrast-to-noise ratio (227.97 ± 161.96; P < 0.001) among all image sets. Furthermore, EDM had a superior mean subjective rating score (4.80 ± 0.42) for visualization of GGNs compared to other reconstructed images (all P < 0.001), although the model-based iterative reconstruction had superior subjective scores of overall image quality. For pure GGNs, the measured diameter and volume did not significantly differ among different reconstructions (both P > 0.05).

CONCLUSIONS

EDM derived from DLSCT enabled improved image quality and lesion conspicuity for the evaluation of lung subsolid nodules compared to conventional iterative reconstruction algorithms and VMIs.

Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images

OBJECTIVES

To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD).

METHODS

A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series.

RESULTS

Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p =  0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044).

CONCLUSION

Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR.

CLINICAL RELEVANCE STATEMENT

To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI.

KEY POINTS

ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.

Dual-energy CT quantitative parameters to evaluate occult peritoneal metastasis in advanced gastric cancer preoperatively

PURPOSE

To explore whether dual-energy CT (DECT) quantitative parameters could provide analytic value for the diagnosis of patients with occult peritoneal metastasis (OPM) in advanced gastric cancer preoperatively.

MATERIALS AND METHODS

This retrospective study included 219 patients with advanced gastric cancer and DECT scans. The patient's clinical data and DECT related iodine concentration (IC) parameters and effective atomic number (Zeff) were collated and analyzed among noun-peritoneal metastasis (NPM), OPM and radiologically peritoneal metastasis (RPM) groups. The predictive performance of the DECT parameters was compared with that of the conventional CT features and clinical characteristics through evaluating area under curve of the precision-recall (AUC-PR), F1 score, balanced accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

RESULTS

Borrmann IV type diagnosed on CT and serum tumor indicator CA125 index were statistically different between the NPM and OPM groups. DECT parameters included IC, normalized IC (NIC), and Zeff of PM group were lower than the NPM group. The DECT predictive nomogram combined three independent DECT parameters produced a better diagnostic performance than the conventional CT feature Borrmann IV type and serum CA125 index in AUC-PR with 0.884 vs 0.368 vs 0.189, but similar to the combined indicator which was based on the DECT parameters, the conventional CT feature, and serum CA125 index in AUC-PR with 0.884 vs 0.918.

CONCLUSION

The lower quantitative NIC, IC ratio, and Zeff on DECT was associated with peritoneal metastasis in advanced gastric cancer and was promising to identify patients with OPM noninvasively.

Dual-Energy Computed Tomography in Urological Diseases: A Narrative Review

Dual-Energy computed tomography (DECT) with its various advanced techniques, including Virtual Non-Contrast (VNC), effective atomic number (Z-eff) calculation, Z-maps, Iodine Density Index (IDI), and so on, holds great promise in the diagnosis and management of urogenital tumours. In this narrative review, we analyze the current status of knowledge of this technology to provide better lesion characterization, improve the staging accuracy, and give more precise treatment response assessments in relation to urological tumours.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study

OBJECTIVES

To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma.

METHODS

A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models.

RESULTS

Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model.

CONCLUSIONS

DLCT has added value for STAS prediction in lung adenocarcinoma.

CLINICAL RELEVANCE STATEMENT

Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future.

KEY POINTS

• Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Dual-energy computed tomography for evaluating nodal staging in lung adenocarcinoma: correlation with surgical pathology

PURPOSE

To ascertain the performance of dual-energy CT (DECT) with iodine quantification in differentiating malignant mediastinal and hilar lymph nodes (LNs) from benign ones, focusing on patients with lung adenocarcinoma.

MATERIALS AND METHODS

In this study, patients with suspected lung cancer received a preoperative contrast-enhanced DECT scan from Jun 2018 to Dec 2020. Quantitative DECT parameters and the size were compared between metastatic and benign LNs. Their diagnostic performances were analyzed by the ROC curves and compared by using the two-sample t test.

RESULTS

72 patients (23 men, 49 women; mean age 62.5 ± 10.1 years) fulfilled the inclusion criteria. A total of 98 LNs (67 benign, 31 metastatic) were analyzed. The iodine concentration normalized by muscle (NICmuscle) was significantly higher (P < 0.001) in metastatic LNs (4.79 ± 1.70) than in benign ones (3.00 ± 1.45). The optimal threshold of NICmuscle was 3.44, which yielded AUC: 0.798, sensitivity: 83.9%, specificity: 73.1%, accuracy: 76.5%, respectively. Applying the established size parameters with 10 mm as the threshold yielded AUC: 0.600, sensitivity: 29.0%, specificity: 91.0%, accuracy: 71.4%, respectively. The diagnostic performance of NICmuscle was significantly better (P = 0.007) than the performance obtained using the established size parameters.

CONCLUSIONS

For lung adenocarcinoma, the quantitative measurement of NICmuscle derived from DECT is useful for differentiating benign and metastatic mediastinal and hilar LNs before surgical intervention.

Characterization of Normal Bone in the Equine Distal Limb with Effective Atomic Number and Electron Density Determined with Single-Source Dual Energy and Detector-Based Spectral Computed Tomography

Single-source dual energy (SSDECT) and detector-based spectral computed tomography (DBSCT) are emerging technologies allowing the interrogation of materials that have different attenuation properties at different energies. Both technologies enable the calculation of effective atomic number (EAN), an index to determine tissue composition, and electron density (ED), which is assumed to be associated with cellularity in tissues. In the present prospective observational study, EAN and ED values were determined for 16 zones in normal subchondral and trabecular bone of 37 equine cadaver limbs. Using both technologies, the following findings were obtained: 1. palmar/plantar EAN zone values in the fetlock increased significantly with increasing age of the horse; 2. all EAN and ED values were significantly lower in the trabecular bone than in the subchondral bone of all phalanges; 3. in the distal phalanx and navicular bone, most EAN and ED values were significantly lower compared to the proximal and middle phalanx; and 4. some EAN and ED values were significantly different between front and hind limbs. Several EAN and ED values significantly differed between SSDECT and DBSCT. The reported EAN and ED values in the subchondral and trabecular bone of the equine distal limb may serve as preliminary reference values and aid future evaluation and classification of diseases.

A risk-scoring model based on endobronchial ultrasound multimodal imaging for predicting metastatic lymph nodes in lung cancer patients

Background and Objectives

Endobronchial ultrasound (EBUS) imaging is a valuable tool for predicting lymph node (LN) metastasis in lung cancer patients. This study aimed to develop a risk-scoring model based on EBUS multimodal imaging (grayscale, Doppler mode, elastography) to predict LN metastasis in lung cancer patients.

Patients and Methods

This retrospective study analyzed 350 metastatic LNs in 314 patients with lung cancer and 124 reactive LNs in 96 patients with nonspecific inflammation. The sonographic findings were compared with the final pathology results and clinical follow-up. Univariate and multivariate logistic regression analyses were performed to evaluate the independent risk factors of metastatic LNs. According to the β coefficients of corresponding indicators in logistic regression analysis, a risk-scoring model was established. Receiver operating characteristic curve was applied to evaluate the predictive capability of model.

Results

Multivariate analysis showed that short axis >10 mm, distinct margin, absence of central hilar structure, presence of necrosis, nonhilar vascularity, and elastography score 4 to 5 were independent predictors of metastatic LNs. Both short axis and margin were scored 1 point, and the rest of independent predictors were scored 2 points. The combination of 3 EBUS modes had the highest area under the receiver operating characteristic and accuracy of 0.884 (95% confidence interval, 0.846-0.922) and 87.55%, respectively. The risk stratification was as follows: 0 to 2 points, malignancy rate of 11.11%, low suspicion; 3 to 10 points, malignancy rate of 86.77%, high suspicion.

Conclusions

The risk-scoring model based on EBUS multimodal imaging can effectively evaluate metastatic LNs in lung cancer patients to support clinical decision making.

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.

Preoperative diagnosis of metastatic lymph nodes by CT-histopathologic matching analysis in gastric adenocarcinoma using dual-layer spectral detector CT

OBJECTIVES

There still remain challenges to accurate diagnosis of lymph node (LN) involvement in gastric cancer (GC) on conventional CT. This study evaluated the quantitative data derived from dual-layer spectral detector CT (DLCT) for preoperative diagnosis of metastatic LNs compared to conventional CT images.

METHODS

Patients with adenocarcinoma scheduled for gastrectomy were enrolled in this prospective study from July, 2021, to February, 2022. Regional LNs were labeled on preoperative DLCT. The LNs were located and matched using carbon nanoparticle solution during surgery according to their locations and anatomic landmarks on preoperative images. The matched LNs were randomly split into training and validation cohorts in a ratio of 2:1. The DLCT quantitative parameters in the training cohort were investigated using logistic regression models to identify independent predictors of metastatic LNs, and these predictors were subsequently applied to the validation cohort. Receiver operating characteristic curves were compared between the DLCT parameters and conventional CT images.

RESULTS

Fifty-five patients were included in the study, with 267 successfully matched LNs (90 metastatic, 177 nonmetastatic). Independent predictors included arterial phase CT attenuation on 70-keV images, venous phase electron density, and clustered feature. These combination predictors had areas under the curve (AUC) of 0.855 and 0.907 in the training and validation cohorts, respectively. Compared to conventional CT criteria alone, the model had higher AUC and accuracy (0.741 vs. 0.907, 75.28% vs. 87.64%; p < 0.01) for LN diagnosis.

CONCLUSION

Incorporating DLCT parameters improved preoperative diagnosis of LN metastasis in GC, increasing the accuracy of clinical N stage.

CLINICAL RELEVANCE STATEMENT

Compared to conventional CT criteria, quantitative parameters from dual-layer spectral detector CT showed higher diagnostic efficacy for the preoperative diagnosis of lymph node metastases in gastric cancer, increasing the accuracy of clinical N stage.

KEY POINTS

• Quantitative parameters from dual-layer spectral detector CT are useful for the preoperative diagnosis of lymph node metastases in gastric adenocarcinoma, increasing the accuracy of clinical N stage. • The values for metastatic lymph nodes are higher than those of nonmetastatic ones. The arterial phase of CT attenuation on 70-keV images, venous phase of electron density, and clustered feature independently predicted lymph node metastases. • Prediction model had area under the curve of 0.907, sensitivity of 81.82%, specificity of 91.07%, and accuracy of 87.64% for the preoperative diagnosis of lymph node metastasis.

Dual-Energy Computed Tomography Applications in Lung Cancer

This article examines the intrathoracic applications for dual-energy computed tomography (DECT), focusing on lung cancer. The topics covered include the image data sets, methods for iodine quantification, and clinical applications. The applications of DECT are to differentiate benign and malignant lung nodules, determining the grade of lung cancer and expression of ki-67 expression. Iodine quantification has role in assessment of treatment response in both the primary tumor and nodal metastases.

Development and validation of 18F-FDG PET/CT radiomics-based nomogram to predict visceral pleural invasion in solid lung adenocarcinoma

OBJECTIVES

This study aimed to establish a radiomics model based on 18F-FDG PET/CT images to predict visceral pleural invasion (VPI) of solid lung adenocarcinoma preoperatively.

METHODS

We retrospectively enrolled 165 solid lung adenocarcinoma patients confirmed by histopathology with 18F-FDG PET/CT images. Patients were divided into training and validation at a ratio of 0.7. To find significant VPI predictors, we collected clinicopathological information and metabolic parameters measured from PET/CT images. Three-dimensional (3D) radiomics features were extracted from each PET and CT volume of interest (VOI). Receiver operating characteristic (ROC) curve was performed to determine the performance of the model. Accuracy, sensitivity, specificity and area under curve (AUC) were calculated. Finally, their performance was evaluated by concordance index (C-index) and decision curve analysis (DCA) in training and validation cohorts.

RESULTS

165 patients were divided into training cohort (n = 116) and validation cohort (n = 49). Multivariate analysis showed that histology grade, maximum standardized uptake value (SUVmax), distance from the lesion to the pleura (DLP) and the radiomics features had statistically significant differences between patients with and without VPI (P < 0.05). A nomogram was developed based on the logistic regression method. The accuracy of ROC curve analysis of this model was 75.86% in the training cohort (AUC: 0.867; C-index: 0.867; sensitivity: 0.694; specificity: 0.889) and the accuracy rate in validation cohort was 71.55% (AUC: 0.889; C-index: 0.819; sensitivity: 0.654; specificity: 0.739).

CONCLUSIONS

A PET/CT-based radiomics model was developed with SUVmax, histology grade, DLP, and radiomics features. It can be easily used for individualized VPI prediction.

Thoracic Diseases: Technique and Applications of Dual-Energy CT

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

Added value of spectral parameters in diagnosing metastatic lymph nodes of pT1-2 rectal cancer

PURPOSE

To investigate the added value of spectral parameters derived from dual-layer spectral detector CT (SDCT) in diagnosing metastatic lymph nodes (LNs) of pT1-2 (stage 1-2 determined by pathology) rectal cancer.

METHODS

A total of 80 LNs (57 non-metastatic LNs and 23 metastatic LNs) from 42 patients with pT1-T2 rectal cancer were retrospectively analyzed. The short-axis diameter of LNs was measured, then its border and enhancement homogeneity were evaluated. All spectral parameters, including iodine concentration (IC), effective atomic number (Z_eff), normalized IC (nIC), normalized Z_eff (nZ_eff), and slope of the attenuation curve (λ), were measured or calculated. The chi-square test, Fisher's exact test, independent-samples t-test, or Mann-Whitney U test was used to compare the differences of each parameter between the non-metastatic group and the metastatic group. Multivariable logistic regression analyses were used to determine the independent factors for predicting LN metastasis. Diagnostic performances were assessed by ROC curve analysis and compared with the DeLong test.

RESULTS

The short-axis diameter, border, enhancement homogeneity, and each spectral parameter of LNs showed significant differences between the two groups (P < 0.05). The nZ_eff and short-axis diameter were independent predictors of metastatic LNs (P < 0.05), with areas under the curve (AUC) of 0.870 and 0.772, sensitivity of 82.5% and 73.9%, and specificity of 82.6% and 78.9%. After combining nZ_eff and the short-axis diameter, the AUC (0.966) was the highest with sensitivity of 100% and specificity of 87.7%.

CONCLUSION

The spectral parameters derived from SDCT might help us to improve the diagnostic accuracy of metastatic LNs in patients with pT1-2 rectal cancer, the highest diagnostic performance can be achieved after combining nZ_eff with the short-axis diameter of LNs.

Can quantitative parameters of spectral computed tomography predict lymphatic metastasis in lung cancer? A systematic review and meta-analysis

BACKGROUND AND PURPOSE

This study evaluated the use of quantitative spectral computed tomography (CT) parameters to identify lymph node metastasis (LM) in lung cancer.

MATERIALS AND METHODS

Literature about LM in lung cancer diagnosed using spectral CT up to September 2022 was retrieved from the PubMed, EMBASE, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure, and Wanfang databases. The literature was strictly screened according to the inclusion and exclusion criteria. Data were extracted, quality assessment was performed, and heterogeneity was evaluated. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (+LR), -LR, and diagnostic odds ratio (DOR) for normalized iodine concentration (NIC) and spectral attenuation curve (λHU) were calculated. The subject receiver operating characteristic (SROC) curves were used, and the area under the curve (AUC) was calculated.

RESULTS

Eleven studies, including 1,290 cases, without obvious publication bias were enrolled. In eight articles, the pooled AUC of NIC in the arterial phase (AP) was 0.84 (SEN=0.85, SPE=0.74, +LR=3.3, -LR=0.20, DOR=16) while that of NIC in the venous phase (VP) was 0.82 (SEN=0.78, SPE=0.72). Additionally, the pooled AUC for λHU (AP) was 0.87 (SEN=0.74, SPE=0.84, +LR=4.5, -LR=0.31, DOR=15) and that for λHU (VP) was 0.81 (SEN=0.62, SPE=0.81). Lymph node (LN) short-axis diameter was ranked last, with a pooled AUC of 0.81 (SEN=0.69, SPE=0.79).

CONCLUSION

Spectral CT is a suitable noninvasive and cost-effective method for determining LM in lung cancer. Additionally, NIC and λHU in the AP have good discrimination ability than short-axis diameter, providing a valuable basis and reference for preoperative evaluation. (registration number INPLASY202290096).

Thorax radiotherapy using 18F-positron emission tomography/computed tomography-guided precision radiotherapy is a prognostic factor for survival in patients with extracranial oligometastatic non-small cell lung cancer:A two-center propensity score-matched analysis

Background

This retrospective study compared positron emission tomography (PET)/computed tomography (CT) and CT in the treatment of extracranial oligometastatic non-small-cell lung cancer (NSCLC) and explored the impact of thorax radiotherapy (TRT) on patient survival.

Methods

We reviewed the medical records of Chinese patients with stage IV extracranial oligometastatic NSCLC who underwent PET/CT or CT at two centers. Propensity score matching (PSM) was used to control differences in patient characteristics between the maintenance chemotherapy alone and TRT plus maintenance chemotherapy groups.

Results

We analyzed 192 eligible patients. The median survival time was better in patients who received PET/CT than in those who only received CT (n = 192, 16 months vs. 6 months, p<0.001). Subgroup analysis showed the median survival time was significantly longer in the TRT plus maintenance group than in the chemotherapy alone group in patients who underwent PET/CT examinations (n = 94, 25 months vs. 11 months, p<0.001). However, there was no statistical difference in survival between both groups in patients who underwent CT examinations (n = 98, 8 months vs. 5 months, p = 0.180). A multifactorial analysis revealed a more favorable prognosis in patients who underwent PET/CT evaluation (HR: 0.343, 95% CI: 0.250-0.471, p <0.001) and TRT (HR: 0.624, 95% CI: 0.464-0.840, p = 0.002), than in those who did not. PSM was consistent with these results.

Conclusions

PET/CT-guided TRT is associated with improved clinical outcomes in patients with stage IV extracranial oligometastatic NSCLC.

Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography

OBJECTIVES

To investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to explore the relationships between DECT and pathological features.

METHODS

Clinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (Z_eff) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (λ_HU), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student's t-test, Pearson's rank correlation, and receiver operating characteristic curves were performed.

RESULTS

The inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (n = 158) displayed significantly decreased ED, IC, normalized IC, λ_HU, and DEI values compared with non-metastatic nodes (n = 241) (all p < 0.01). Strong correlations were found between IC (r = 0.776), normalized IC (r = 0.779), λ_HU (r = 0.738), DEI (r = 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918.

CONCLUSION

DECT parameters IC, normalized IC, λ_HU, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC.

KEY POINTS

• Electron density, iodine concentration, normalized iodine concentration, λ_HU, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes. • Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density. • DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.

Mediastinal Nodal Staging Performance of Combined Endobronchial and Esophageal Endosonography in Lung Cancer Cases: A Systematic Review and Meta-Analysis

By searching lliteratures till January 5, 2022, we evaluated the role of the mediastinal nodal staging of endobronchial ultrasound-guided fine-needle aspiration (EBUS) and endoscopic ultrasound-guided fine-needle aspiration (EUS) in lung cancer. A total of 20 studies with 2,961 patients were included in this study. The pooled sensitivity, specificity, PLR, and NLR for EBUS were 0.79, 0.97, 27.29, and 0.25, respectively. EUS showed staging performance similar to EBUS. The staging performance was significantly improved when combining EBUS + EUS.