Gastric cancer staging with dual energy spectral CT imaging

A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantitative indicator for distinguishing metastatic and nonmetastatic regional lymph nodes in pancreatic ductal adenocarcinoma

Background

There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC.

Methods

A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA).

Results

The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75.

Conclusions

As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating differentiation grade and lymphovascular and perineural invasion in colorectal adenocarcinoma

PURPOSE

To explore the predictive value of dual-layer spectral detector CT (SDCT) quantitative parameters for determining differentiation grade, lymphovascular invasion (LVI) and perineural invasion (PNI) in colorectal adenocarcinoma (CRAC) patients.

METHODS

A total of 106 eligible patients with CRAC were included in this study. Spectral parameters, including CT values at 40 and 100 keV, the effective atomic number (Zeff), the iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and the normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP), were compared according to the differentiation grade and the status of LVI and PNI. The diagnostic accuracies of the quantitative parameters with statistical significance were determined via receiver operating characteristic (ROC) curves, and the area under the curve (AUC) was calculated.

RESULTS

There were 57 males and 49 females aged 43-86 (69 ± 10) years. The measured values of the spectral quantitative parameters of the CRAC were consistent within the observer (ICC range: 0.800-0.926). The 40 keV-AP, IC-AP, NIC-AP, 40 keV-VP, and IC-VP were significantly different among the different differentiation grades in the CRAC (P = 0.040, AUC = 0.673; P = 0.035, AUC = 0.684; P = 0.031, AUC = 0.639; P = 0.044, AUC = 0.663 and P = 0.035, AUC = 0.666, respectively). A statistically significant difference was observed in 40 keV-VP, 100 keV-VP, Zeff-VP, IC-VP, and λHU-VP between LVI-positive and LVI-negative patients (P = 0.003, AUC = 0.688; P = 0.015, AUC = 0.644; P = 0.001, AUC = 0.688; P = 0.001, AUC = 0.703 and P = 0.003, AUC = 0.677, respectively). There were no statistically significant differences in the values of the spectral parameters of the PNI state of patients with CRAC (P > 0.05).

CONCLUSION

The quantitative parameters of SDCT had good diagnostic efficacy in differentiating between different grades and statuses of LVI in patients with CRAC; however, SDCT did not have value for identifying the state of PNI.

Nomogram based on dual-energy CT-derived extracellular volume fraction for the prediction of microsatellite instability status in gastric cancer

Purpose

To develop and validate a nomogram based on extracellular volume (ECV) fraction derived from dual-energy CT (DECT) for preoperatively predicting microsatellite instability (MSI) status in gastric cancer (GC).

Materials and methods

A total of 123 patients with GCs who underwent contrast-enhanced abdominal DECT scans were retrospectively enrolled. Patients were divided into MSI (n=41) and microsatellite stability (MSS, n=82) groups according to postoperative immunohistochemistry staining, then randomly assigned to the training (n=86) and validation cohorts (n=37). We extracted clinicopathological characteristics, CT imaging features, iodine concentrations (ICs), and normalized IC values against the aorta (nICs) in three enhanced phases. The ECV fraction derived from the iodine density map at the equilibrium phase was calculated. Univariate and multivariable logistic regression analyses were used to identify independent risk predictors for MSI status. Then, a nomogram was established, and its performance was evaluated by ROC analysis and Delong test. Its calibration performance and clinical utility were assessed by calibration curve and decision curve analysis, respectively.

Results

The ECV fraction, tumor location, and Borrmann type were independent predictors of MSI status (all P < 0.05) and were used to establish the nomogram. The nomogram yielded higher AUCs of 0.826 (0.729-0.899) and 0.833 (0.675-0.935) in training and validation cohorts than single variables (P<0.05), with good calibration and clinical utility.

Conclusions

The nomogram based on DECT-derived ECV fraction has the potential as a noninvasive biomarker to predict MSI status in GC patients.

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

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

Preoperative prediction of Lauren classification in gastric cancer: a radiomics model based on dual-energy CT iodine map

OBJECTIVE

To investigate the value of a radiomics model based on dual-energy computed tomography (DECT) venous-phase iodine map (IM) and 120 kVp equivalent mixed images (MIX) in predicting the Lauren classification of gastric cancer.

METHODS

A retrospective analysis of 240 patients undergoing preoperative DECT and postoperative pathologically confirmed gastric cancer was done. Training sets (n = 168) and testing sets (n = 72) were randomly assigned with a ratio of 7:3. Patients are divided into intestinal and non-intestinal groups. Traditional features were analyzed by two radiologists, using logistic regression to determine independent predictors for building clinical models. Using the Radiomics software, radiomics features were extracted from the IM and MIX images. ICC and Boruta algorithm were used for dimensionality reduction, and a random forest algorithm was applied to construct the radiomics model. ROC and DCA were used to evaluate the model performance.

RESULTS

Gender and maximum tumor thickness were independent predictors of Lauren classification and were used to build a clinical model. Separately establish IM-radiomics (R-IM), mixed radiomics (R-MIX), and combined IM + MIX image radiomics (R-COMB) models. In the training set, each radiomics model performed better than the clinical model, and the R-COMB model showed the best prediction performance (AUC: 0.855). In the testing set also, the R-COMB model had better prediction performance than the clinical model (AUC: 0.802).

CONCLUSION

The R-COMB radiomics model based on DECT-IM and 120 kVp equivalent MIX images can effectively be used for preoperative noninvasive prediction of the Lauren classification of gastric cancer.

CRITICAL RELEVANCE STATEMENT

The radiomics model based on dual-energy CT can be used for Lauren classification prediction of preoperative gastric cancer and help clinicians formulate individualized treatment plans and assess prognosis.

Early stage gastric adenocarcinoma: clinical and molecular landscapes

Gastric adenocarcinoma, even when diagnosed at an early (localized) disease stage, poses a major health-care burden with cure rates that remain unsatisfactorily low, particularly in Western countries. This lack of progress reflects, among other aspects, the impracticality of early diagnosis, considerable variations in therapeutic approaches that is partly based on regional preferences, and the ingrained heterogeneity of gastric adenocarcinoma cells and their associated tumour microenvironment (TME). Clinical trials have long applied empirical interventions with the assumption that all early stage gastric adenocarcinomas are alike. Despite certain successes, the shortcomings of these approaches can potentially be overcome by targeting the specific molecular subsets of gastric adenocarcinomas identified by genomic and/or multi-omics analyses, including microsatellite instability-high, Epstein-Barr virus-induced, DNA damage repair-deficient, HER2-positive and PD-L1-high subtypes. Future approaches, including the availability of sophisticated vaccines, novel antibody technologies, agents targeting TME components (including fibroblasts, macrophages, cytokines or chemokines, and T cells) and novel immune checkpoint inhibitors, supported by improved tissue-based and blood-based diagnostic assays, seem promising. In this Review, we highlight current knowledge of the molecular and cellular biology of gastric adenocarcinomas, summarize the current approaches to clinical management of the disease, and consider the role of novel management and/or treatment strategies.

Spectral CT-based nomogram for preoperative prediction of perineural invasion in locally advanced gastric cancer: a prospective study

OBJECTIVES

This work focused on developing and validating the spectral CT-based nomogram to preoperatively predict perineural invasion (PNI) for locally advanced gastric cancer (LAGC).

METHODS

This work prospectively included 196 surgically resected LAGC patients (139 males, 57 females, 59.55 ± 11.97 years) undergoing triple enhanced spectral CT scans. Patients were labeled as perineural invasion (PNI) positive and negative according to pathologic reports, then further split into primary (n = 130) and validation cohort (n = 66). We extracted clinicopathological information, follow-up data, iodine concentration (IC), and normalized IC values against to aorta (nICs) at arterial/venous/delayed phases (AP/VP/DP). Clinicopathological features and IC values between PNI positive and negative groups were compared. Multivariable logistic regression was performed to screen independent risk factors of PNI. Then, a nomogram was established, and its capability was determined by ROC curves. Its clinical use was evaluated by decision curve analysis. The correlations of PNI and the nomogram with patients' survival were explored by log-rank survival analysis.

RESULTS

Borrmann classification, tumor thickness, and nICDP were independent predictors of PNI and used to build the nomogram. The nomogram yielded higher AUCs of 0.853 (0.744-0.928) and 0.782 (0.701-0.850) in primary and validation cohorts than any other parameters (p < 0.05). Both PNI and the nomogram were related to post-surgical treatment planning. Only PNI was associated with disease-free survival in the primary cohort (p < 0.05).

CONCLUSION

This work prospectively established a spectral CT-based nomogram, which can effectively predict PNI preoperatively and potentially guide post-surgical treatment strategy in LAGC.

KEY POINTS

• The present prospective study established a spectral CT-based nomogram for preoperative prediction of perineural invasion in LAGC. • The proposed nomogram, including morphological features and the quantitative iodine concentration values from spectral CT, had the potential to predict PNI for LAGC before surgery, along with guide post-surgical treatment planning. • Normalized iodine concentration at the delayed phase was the most valuable quantitative parameter, suggesting the importance of delayed enhancement in gastric CT.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

DECT Numbers in Upper Abdominal Organs for Differential Diagnosis: A Feasibility Study

Evaluating the similarity between two entities such as primary and suspected metastatic lesions using quantitative dual-energy computed tomography (DECT) numbers may be useful. However, the criteria for the similarity between two entities based on DECT numbers remain unclear. We therefore considered the possibility that a similarity in DECT numbers within the same organ could provide suitable standards. Thus, we assumed that the variation in DECT numbers within a single organ is sufficiently minimal to be considered clinically equivalent. Therefore, the purpose of this preliminary study is to investigate the differences in DECT numbers within upper abdominal organs. This retrospective study included 30 patients with data from hepatic protocol DECT scans. DECT numbers of the following parameters were collected: (a, b) 70 and 40 keV CT values, (c) slope, (d) effective Z, and (e, f) iodine and water concentration. The agreement of DECT numbers obtained from two regions of interest in the same organ (liver, spleen, and kidney) were assessed using Bland-Altman analysis. The diagnostic ability of each DECT parameter to distinguish between the same or different organs was also assessed using receiver operating characteristic analysis. The 95% limits of agreement within the same organ exhibited the narrowest value range on delayed phase (DP) CT [(c) -11.2-8.3%, (d) -2.0-1.5%, (e) -11.3-8.4%, and (f) -0.59-0.62%]. The diagnostic ability was notably high when using differences in DECT numbers on portal venous (PVP) and DP images (the area under the curve of DP: 0.987-0.999 in (c)-(f)). Using the variability in DECT numbers in the same organ as a criterion for defining similarity may be helpful in making a differential diagnosis by comparing the DECT numbers of two entities.

Spectral CT for preoperative prediction of lymphovascular invasion in resectable gastric cancer: With external prospective validation

Objectives

To develop and externally validate a spectral CT based nomogram for the preoperative prediction of LVI in patients with resectable GC.

Methods

The two centered study contained a retrospective primary dataset of 224 pathologically confirmed gastric adenocarcinomas (161 males, 63 females; mean age: 60.57 ± 10.81 years, range: 20-86 years) and an external prospective validation dataset from the second hospital (77 males and 35 females; mean age, 61.05 ± 10.51 years, range, 31 to 86 years). Triple-phase enhanced CT scans with gemstone spectral imaging mode were performed within one week before surgery. The clinicopathological characteristics were collected, the iodine concentration (IC) of the primary tumours at arterial phase (AP), venous phase (VP), and delayed phase (DP) were measured and then normalized to aorta (nICs). Univariable analysis was used to compare the differences of clinicopathological and IC values between LVI positive and negative groups. Independent predictors for LVI were screened by multivariable logistic regression analysis in primary dataset and used to develop a nomogram, and its performance was evaluated by using ROC analysis and tested in validation dataset. Its clinical use was evaluated by decision curve analysis (DCA).

Results

Tumor thickness, Borrmann classification, CT reported lymph node (LN) status and nICDP were independent predictors for LVI, and the nomogram based on these indicators was significantly associated with LVI (P<0.001). It yielded an AUC of 0.825 (95% confidence interval [95% CI], 0.769-0.872) and 0.802 (95% CI, 0.716-0.871) in primary and validation datasets (all P<0.05), with promising clinical utility by DCA.

Conclusion

This study presented a dual energy CT quantification based nomogram, which enables preferable preoperative individualized prediction of LVI in patients with GC.

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.

A prospective study of dual-energy computed tomography for differentiating metastatic and non-metastatic lymph nodes of colorectal cancer

Background

Colorectal cancer (CRC) is the third most common malignancy worldwide, and lymph node metastasis is considered to be a risk factor for local recurrence and a poor prognosis in colorectal cancer. However, there remains a lack of reliable and non-invasive biomarkers to identify the lymph node status of CRC patients preoperatively. The purpose of this study was to explore the ability of dual-energy computed tomography (DECT) to differentiate metastatic from non-metastatic lymph nodes in colorectal cancer.

Methods

Seventy-one patients with primary colorectal cancer underwent contrast-enhanced dual-energy computed tomography imaging preoperatively. The colorectal specimen was scanned postoperatively, and lymph nodes were matched to the pathology report. The following dual-energy computed tomography quantitative parameters were analyzed: dual-energy curve slope value (λ_HU), standardized iodine concentration (n△HU), iodine water ratio (nIWR), electron density value (nρ_eff), and effective atom-number (nZ), based on metastatic and non-metastatic lymph node differentiation. Also, sensitivity and specificity analyses were performed using receiver operating characteristic curves.

Results

In all patients, one hundred and fifty lymph nodes, including 66 non-metastatic and 84 metastatic lymph nodes, were matched using the radiological-pathological correlation. Metastatic nodes had significantly greater λ_HU, n△HU, and nIWR values than non-metastatic nodes in both the arterial and venous phases (P<0.01). The area under curve (AUC), sensitivity, and specificity were 0.80, 80%, and 66% for λ_HU; 0.86, 70%, and 95% for n△HU; and 0.88, 71%, and 95% for nIWR in the arterial phase. There was no significant difference in electron density and effective Z values between metastatic and non-metastatic lymph nodes.

Conclusions

DECT quantitative parameters may help differentiate between metastatic and normal lymph nodes in patients with CRC.

Prediction of epithelial-to-mesenchymal transition molecular subtype using CT in gastric cancer

OBJECTIVES

To develop a prediction model with computed tomography (CT) images and to build a nomogram incorporating known clinicopathologic variables for individualized estimation of epithelial-to-mesenchymal transition (EMT) subtype gastric cancer.

METHODS

Patients who underwent primary resection of gastric cancer (GC) and molecular subgroup analysis (n = 451) were reviewed. Multivariable analysis using a stepwise variable selection method was performed to build a predictive model for EMT subtype GC. A nomogram using the results of the multivariable analysis was constructed. An optimal cutoff value of total prognostic points of the nomogram for the prediction of EMT subtype was determined. The predictive model for the EMT subtype was internally validated by bootstrap resampling method.

RESULTS

There were 88 patients with EMT subtype and 363 patients with non-EMT subtype based on transcriptome analysis. The patient's age, Lauren classification, and mural stratification on CT were variables selected for the predictive model. The area under the curve (AUC) of the model was 0.865, and the validated AUC of the bootstrap sample was 0.860. The optimal cutoff value of total prognostic points for the prediction of EMT subtype was 94.622, with 90.9% sensitivity, 67.2% specificity, and 71.8% accuracy.

CONCLUSION

A predictive model using patient's age, Lauren classification, and mural stratification on CT for EMT molecular subtype GC was made. A nomogram was built which would serve as a useful screening tool for an individualized estimate of EMT subtype.

KEY POINTS

• A predictive model for epithelial-to-mesenchymal transition (EMT) subtype incorporating patient's age, Lauren classification, and mural stratification on CT was built. • The predictive model had high diagnostic accuracy (area under the curve (AUC) = 0.865) and was validated (bootstrap AUC = 0.860). • Adding CT findings to clinicopathologic variables increases the accuracy of the predictive model than using only.

CT features predictive of nodal positivity at surgery in pancreatic cancer patients following neoadjuvant therapy in the setting of dual energy CT

PURPOSE

Evaluate utility of dual energy CT iodine material density images to identify preoperatively nodal positivity in pancreatic cancer patients who underwent neoadjuvant therapy.

METHODS

This IRB approved retrospective study evaluated 62 patients between 2012 and 2016 with proven pancreatic ductal adenocarcinoma, who underwent neoadjuvant therapy, tumor resection and both baseline and preoperative assessment with pancreatic multiphasic rapid switching dual energy CT. Three radiologists in consensus identified on imaging nodes > 0.5 cm in short axis, evaluated nodal morphology, size and on each phase density in HU, and concentrations on iodine material density images normalized to the aorta.

RESULTS

Of 62 patients, 33 were N0, 20 N1, and 9 N2. Total of 145 lymph nodes were evaluated, with average number of nodes per anatomic site ranging from 1.3 (body tumors) to 5 (uncinate) versus average of 24 and 30 nodes recovered respectively at surgery. Most (N = 44) were pancreatic head tumors. For all patients, regardless of site of primary tumor, the minimum measured iodine value of all of a patient's measured nodes taken as a group on preoperative studies, as normalized to the aorta, was significant at P = 0.041 value in differentiating N0 from N1/2 and ROC analysis showed an AUC of 0.67. With a cutoff of 0.2857, sensitivity was 0.78 and specificity was 0.58, with values < 0.2857 indicative of N1/2. Node morphology and changes in nodal size weren't statistically significant.

CONCLUSION

The dual energy based minimum normalized iodine value of all nodes in the surgical field on preoperative studies has modest utility in differentiating N0 from N1/2, and generally outperformed conventional features for identifying nodal metastases.

The Role of Dual-Energy Computed Tomography in Locating Gastrointestinal Tract Perforations

Objective With each passing day, dual-energy computed tomography (DECT) is being used more frequently in the evaluation of abdominal pathologies. In this article, we aimed to assess the role of dual-energy CT in locating gastrointestinal perforations, which are among the causes of acute abdomen. Materials and methods All patients who underwent DECT due to acute abdomen in a COVID-19 designated hospital between June 1st, 2020 and December 31st, 2020, who were found to have gastrointestinal tract (GIT) perforation and underwent surgery were included in the study. DECT results and intraoperative findings of the patients were compared. Results Thirteen patients (nine males and four females) who underwent DECT for acute abdomen and were diagnosed with perforation in the gastrointestinal system were included in the study. The mean age of the patients was 57.6 years (range: 11-85 years). Two patients had gastric perforation, three had duodenal perforations, and one patient had a perforation in the gallbladder wall. Two patients were diagnosed with jejunal perforations, one patient with Meckel's diverticulum, and three patients with colorectal perforation. Although free air was detected in the abdomen of one patient, perforation could not be located. In patients with GIT perforation who were operated on following DECT imaging, the perforation location shown on DECT correlated 100% with the perforation locations detected during surgery. Conclusion DECT is significantly effective in planning surgical treatment and determining the foci of perforation in GIT perforations.

Human Gut Microbiota-associated Gastrointestinal Malignancies: A Comprehensive Review

The human gastrointestinal tract houses trillions of microbes. The gut and various types of microorganisms, including bacteria, viruses, fungi, and archaea, form a complex ecosystem known as the gut microbiota, and the whole genome of the gut microbiota is referred to as the gut microbiome. The gut microbiota is essential for homeostasis and the overall well-being of a person and is increasingly considered an adjunct "virtual organ," with a complexity level comparable to that of the other organ systems. The gut microbiota plays an essential role in nutrition, local mucosal homeostasis, inflammation, and the mucosal immune system. An imbalanced state of the gut microbiota, known as dysbiosis, can predispose to development of various gastrointestinal malignancies through three speculated pathogenic mechanisms: (a) direct cytotoxic effects with damage to the host DNA, (b) disproportionate proinflammatory signaling inducing inflammation, and (c) activation of tumorigenic pathways or suppression of tumor-suppressing pathways. Several microorganisms, including Helicobacter pylori, Epstein-Barr virus, human papillomavirus, Mycoplasma species, Escherichia coli, and Streptococcus bovis, are associated with gastrointestinal malignancies such as esophageal adenocarcinoma, gastric adenocarcinoma, gastric mucosa-associated lymphoid tissue lymphoma, colorectal adenocarcinoma, and anal squamous cell carcinoma. Imaging plays a pivotal role in diagnosis and management of microbiota-associated gastrointestinal malignancies. Appropriate use of probiotics, fecal microbiota transplantation, and overall promotion of the healthy gut are ongoing areas of research for prevention and treatment of malignancies. Online supplemental material is available for this article. ^©RSNA, 2021.

Dual-Energy Computed Tomography-Based Radiomics to Predict Peritoneal Metastasis in Gastric Cancer

Objective

To develop and validate a dual-energy computed tomography (DECT) derived radiomics model to predict peritoneal metastasis (PM) in patients with gastric cancer (GC).

Methods

This retrospective study recruited 239 GC (non-PM = 174, PM = 65) patients with histopathological confirmation for peritoneal status from January 2015 to December 2019. All patients were randomly divided into a training cohort (n = 160) and a testing cohort (n = 79). Standardized iodine-uptake (IU) images and 120-kV-equivalent mixed images (simulating conventional CT images) from portal-venous and delayed phases were used for analysis. Two regions of interest (ROIs) including the peritoneal area and the primary tumor were independently delineated. Subsequently, 1691 and 1226 radiomics features were extracted from the peritoneal area and the primary tumor from IU and mixed images on each phase. Boruta and Spearman correlation analysis were used for feature selection. Three radiomics models were established, including the R_IU model for IU images, the R_MIX model for mixed images and the combined radiomics model (the R_comb model). Random forest was used to tune the optimal radiomics model. The performance of the clinical model and human experts to assess PM was also recorded.

Results

Fourteen and three radiomics features with low redundancy and high importance were extracted from the IU and mixed images, respectively. The R_IU model showed significantly better performance to predict PM than the R_MIX model in the training cohort (AUC, 0.981 vs. 0.917, p = 0.034). No improvement was observed in the R_comb model (AUC = 0.967). The R_IU model was the optimal radiomics model which showed no overfitting in the testing cohort (AUC = 0.967, p = 0.528). The R_IU model demonstrated significantly higher predictive value on peritoneal status than the clinical model and human experts in the testing cohort (AUC, 0.785, p = 0.005; AUC, 0.732, p <0.001, respectively).

Conclusion

DECT derived radiomics could serve as a non-invasive and easy-to-use biomarker to preoperatively predict PM for GC, providing opportunity for those patients to tailor appropriate treatment.

Pancreatic Neuroendocrine Neoplasms: CT Spectral Imaging in Grading

RATIONALE AND OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Accuracy of 18F-FDG PET/CT and CECT for primary staging and diagnosis of recurrent gastric cancer: A meta-analysis

Contrast-enhanced computed tomography (CECT) is commonly used for staging and diagnosing recurrent gastric cancer. Recently, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)/CT gained popularity as a diagnostic tool owing to advantages including dual functional and anatomical imaging, which may facilitate early diagnosis. The diagnostic performance of 18F-FDG PET/CT and CECT has been assessed in several studies but with variable results. Therefore, the present meta-analysis aimed to evaluate the accuracy of 18F-FDG PET/CT and CECT for primary TNM staging and the diagnosis of recurrent gastric cancers. A systematic search of the PubMed Central, Medline, Scopus, Cochrane and Embase databases from inception until January 2020 was performed. The Quality Assessment of Diagnostic Accuracy Study-2 tool was used to determine the quality of the selected studies. Pooled estimates of sensitivity and specificity were calculated. A total of 58 studies comprising 9,997 patients were included. Most studies had a low risk of bias. The sensitivity and specificity for nodal staging of gastric cancer were 49% (95% CI, 37-61%) and 92% (95% CI, 86-96%) for 18F-FDG PET/CT, respectively, and 67% (95% CI, 57-76%) and 86% (95% CI, 81-89%) for CECT, respectively. For metastasis staging, the sensitivity and specificity were 56% (95% CI, 40-71%) and 97% (95% CI, 87-99%) for 18F-FDG PET/CT, respectively, and 59% (95% CI, 41-75%) and 96% (95% CI, 83-99%) for CECT, respectively. For diagnosing cancer recurrence, the pooled sensitivity and specificity were 81% (95% CI, 72-88%) and 83% (95% CI, 74-89%) for 18F-FDG PET/CT, respectively, and 59% (95% CI, 41-75%) and 96% (95% CI, 83-99%) for CECT, respectively. Both 18F-FDG PET/CT and CECT were deemed highly useful for diagnosing recurrent gastric cancer due to their high sensitivities and specificities. However, these techniques cannot be used to exclude or confirm the presence of lymph node metastases or recurrent gastric cancer tumors, but can be used for the confirmation of distal metastasis.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review

Dual-energy computed tomography (DECT) can estimate tissue vascularity and perfusion via iodine quantification. The aim of this systematic review was to outline current and emerging clinical applications of iodine quantification within the gastrointestinal tract using DECT. The search was conducted with three databases: EMBASE, Pubmed and The Cochrane Library. This identified 449 studies after duplicate removal. From a total of 570 selected studies, 30 studies were enrolled for the systematic review. The studies were categorized into four main topics: gastric tumors (12 studies), colorectal tumors (8 studies), Crohn’s disease (4 studies) and miscellaneous applications (6 studies). Findings included a significant difference in iodine concentration (IC) measurements in perigastric fat between T1–3 vs. T4 stage gastric cancer, poorly and well differentiated gastric and colorectal cancer, responders vs. non-responders following chemo- or chemoradiotherapy treatment among cancer patients, and a positive correlation between IC and Crohn’s disease activity. In conclusion, iodine quantification with DECT may be used preoperatively in cancer imaging as well as for monitoring treatment response. Future studies are warranted to evaluate the capabilities and limitations of DECT in splanchnic flow.

[Comparative imaging study of mediastinal lymph node from pre-surgery dual energy CT versus post-surgeron verifications in non-small cell lung cancer patients]

OBJECTIVE

To validate the value of dual energy CT (DECT) in the differentiation of mediastinal metastatic lymph nodes from non-metastatic lymph nodes in non-small cell lung cancer (NSCLC).

METHODS

In the study, 57 surgically confirmed NSCLC patients who underwent enhanced DECT scan within 2 weeks before operation were enrolled. Two radiologists analyzed the CT images before operation. All mediastinal lymph nodes with short diameter≥5 mm on axial images were included in this study. The morphological parameters [long-axis diameter (L), short-axis diameter (S) and S/L of lymph nodes] and the DECT parameters [iodine concentration (IC), normalized iodine concentration (NIC), slope of spectral hounsfield unit curve (λHU) and effective atomic number (Zeff) in arterial and venous phase] were measured. The differences of morphological parameters and DECT parameters between metastatic and non-metastatic lymph nodes were compared. The parameters with significant difference were analyzed by the Logistic regression model, then a new predictive variable was established. Receiver operator characteristic (ROC) analyses were performed for S, NIC in venous phase and the new predictive variable.

RESULTS

In 57 patients, 49 metastatic lymph nodes and 938 non-metastatic lymph nodes were confirmed by surgical pathology. A total of 163 mediastinal lymph nodes (49 metastatic, 114 non-metastatic) with S≥5 mm were detected on axial CT images. The S, L and S/L of metastatic lymph nodes were significantly higher than those of non-metastatic lymph nodes (P < 0.05). The DECT parameters of metastatic lymph nodes were significantly lower than those of non-metastatic lymph nodes (P < 0.05). The best single morphological parameter for differentiation between metastatic and nonmetastatic lymph nodes was S (AUC, 0.752; threshold, 8.5 mm; sensitivity, 67.4%; specificity, 73.7%; accuracy, 71.8%). The best single DECT parameter for differentiation between metastatic and nonmetastatic lymph nodes was NIC in venous phase (AUC, 0.861; threshold, 0.53; sensitivity, 95.9%; specificity, 70.2%; accuracy, 77.9%). Multivariate analysis showed that S and NIC were independent predictors of lymph node metastasis. The AUC of combined S and NIC in the venous phase was 0.895(sensitivity, 79.6%; specificity, 87.7%; accuracy, 85.3%), which were significantly higher than that of S (P < 0.001) and NIC (P=0.037).

CONCLUSIONS

The ability of quantitative DECT parameters to distinguish mediastinal lymph node metastasis in NSCLC patients is better than that of morphological parameters. Combined S and NIC in venous phase can be used to improve preoperative diagnostic accuracy of metastatic lymph nodes.

The value of multidetector-row computed tomography in lymph node staging of gastric cancer: a preliminary Vietnamese study

Introduction

Gastric cancer (GC) is the fourth most common malignant disease in the world, following breast cancer, colorectal cancer, and lung cancer. This study aimed to evaluate the usefulness of multidetector-row computed tomography (MDCT) in identifying the metastatic lymph node of GC.

Material and methods

A cross-sectional study was performed after receiving approval by the institutional review board. A total of 88 patients with GC, who underwent radical gastrectomy, were examined by MDCT. Categorical variables were compared using Fisher’s exact test. The discriminating ability of lymph node size was determined according to an area under the receiver operating curve(AUROC) analysis, and the optimal cut-off point was determined.

Results

The proportion of metastatic lymph node patients in the proximal group (32.3%) was significantly higher than that in the distal group (18.4%). T categorisation and lymph node sizes were significantly different between the non-metastatic lymph node and metastatic lymph node groups. The AUROC for lymph node size was 0.738, with an optimal cut-off point of 7.5 mm,producing a sensitivity of 71.5% and a specificity of 70.5%.

Conclusions

MDCT displayed medium accuracy for the determination of metastatic lymph nodes and N categorisation. Based on our findings, although MDCT is generally the first choice for preoperative assessments in GC patients, other diagnostic modalities should supplement MDCT in order to achieve more precise N staging.

Stepwise analysis of potential accuracy-influencing factors of iodine quantification on a fast kVp-switching second-generation dual-energy CT: from 3D-printed phantom to a simple solution in clinical routine use

Background

Measurement of iodine concentration from dual-energy or spectral computed tomography (CT) provides useful diagnostic information especially in patients suffering from malignant tumors of various origins.

Purpose

The purpose of this study was to systematically investigate the accuracy of the measurement of iodine concentration, focusing on potential influencing factors and assessing its suitability for routine clinical use.

Material and Methods

First, a 3D-printed cylindrical phantom was used to assess reliability of dual-energy CT-based iodine concentration measurement. Second, a semi-anthropomorphic phantom was used to evaluate the potential impact of positional variation of the target volume as typically seen in clinical scans. Finally, a reference vial was placed on the body surface of 38 patients undergoing abdominal dual-energy CT to analyze correlations between applied doses and patient diameters.

Results

The position of the target volume within the cylindrical phantom and the applied dose level significantly influenced the magnitude of measured iodine concentrations ( P < 0.001). We also found a significant difference in accuracy depending on target volume position in the semi-anthropomorphic phantom ( P = 0.028). In patient scans, we observed an error of 19.6 ± 5.6% in iodine concentration measurements of a reference and significant, moderate to strong, negative correlations between measured iodine concentration, maximum patient diameter, and applied dose (maximum sagittal diameter: r = −0.455, P = 0.004; maximum coronal diameter: r=−0.517, P = 0.001; CTDIvol: r = −0.385, P = 0.017)

Conclusion

Dual-energy CT-based iodine concentration measurement should be interpreted with caution. In clinical examinations, placement of a reference vial could be a potential solution to relativize errors.

Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

OBJECTIVES

To build a dual-energy CT (DECT)-based deep learning radiomics nomogram for lymph node metastasis (LNM) prediction in gastric cancer.

MATERIALS AND METHODS

Preoperative DECT images were retrospectively collected from 204 pathologically confirmed cases of gastric adenocarcinoma (mean age, 58 years; range, 28-81 years; 157 men [mean age, 60 years; range, 28-81 years] and 47 women [mean age, 54 years; range, 28-79 years]) between November 2011 and October 2018, They were divided into training (n = 136) and test (n = 68) sets. Radiomics features were extracted from monochromatic images at arterial phase (AP) and venous phase (VP). Clinical information, CT parameters, and follow-up data were collected. A radiomics nomogram for LNM prediction was built using deep learning approach and evaluated in test set using ROC analysis. Its prognostic performance was determined with Harrell's concordance index (C-index) based on patients' outcomes.

RESULTS

The dual-energy CT radiomics signature was associated with LNM in two sets (Mann-Whitney U test, p < 0.001) and an achieved area under the ROC curve (AUC) of 0.71 for AP and 0.76 for VP in test set. The nomogram incorporated the two radiomics signatures and CT-reported lymph node status exhibited AUCs of 0.84 in the training set and 0.82 in the test set. The C-indices of the nomogram for progression-free survival and overall survival prediction were 0.64 (p = 0.004) and 0.67 (p = 0.002).

CONCLUSION

The DECT-based deep learning radiomics nomogram showed good performance in predicting LNM in gastric cancer. Furthermore, it was significantly associated with patients' prognosis.

KEY POINTS

• This study investigated the value of deep learning dual-energy CT-based radiomics in predicting lymph node metastasis in gastric cancer. • The dual-energy CT-based radiomics nomogram outweighed the single-energy model and the clinical model. • The nomogram also exhibited a significant prognostic ability for patient survival and enriched radiomics studies.

Increased Progastrin-Releasing Peptide Expression is Associated with Progression in Gastric Cancer Patients

PURPOSE

The purpose of this study was to assess the diagnostic and prognostic value of serum progastrin-releasing peptide (ProGRP) in patients with gastric cancer (GC).

MATERIALS AND METHODS

A total of 150 patients with GC (89 males and 61 females) were recruited, including those with stage I (n=28), stage II (n=33), stage III (n=50), and stage IV (n=39) disease; 50 healthy controls and 66 patients with benign gastric diseases were also enrolled. Levels of serum ProGRP, carcinoembryonic antigen (CEA), and carbohydrate antigen 72-4 (CA72-4) were measured in all subjects.

RESULTS

Serum ProGRP levels were significantly higher in GC patients than in controls (p<0.001), and ProGRP was significantly correlated with tumor size, tumor node metastasis stage, differentiation, invasion depth, and lymph node metastasis (p< 0.005). ProGRP levels were significantly decreased after chemotherapy (p<0.001). Receiver operating characteristic curves revealed a sensitivity and specificity for serum ProGRP in GC of 85.9% and 81.2%, respectively. ProGRP levels were positively correlated with CA72-4 and CEA (r=0.792 and 0.688, p<0.05, respectively). Combined detection of ProGRP, CEA, and CA72-4 showed the best diagnostic power for GC.

CONCLUSION

ProGRP may be useful as a potential biomarker for GC diagnosis and therapy.

Energy enhanced tissue texture in spectral computed tomography for lesion classification

Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels, i.e., the tissue heterogeneity, and has been recognized as important biomarkers in various clinical tasks. Spectral computed tomography (CT) is believed to be able to enrich tissue texture by providing different voxel contrast images using different X-ray energies. Therefore, this paper aims to address two related issues for clinical usage of spectral CT, especially the photon counting CT (PCCT): (1) texture enhancement by spectral CT image reconstruction, and (2) spectral energy enriched tissue texture for improved lesion classification. For issue (1), we recently proposed a tissue-specific texture prior in addition to low rank prior for the individual energy-channel low-count image reconstruction problems in PCCT under the Bayesian theory. Reconstruction results showed the proposed method outperforms existing methods of total variation (TV), low-rank TV and tensor dictionary learning in terms of not only preserving texture features but also suppressing image noise. For issue (2), this paper will investigate three models to incorporate the enriched texture by PCCT in accordance with three types of inputs: one is the spectral images, another is the co-occurrence matrices (CMs) extracted from the spectral images, and the third one is the Haralick features (HF) extracted from the CMs. Studies were performed on simulated photon counting data by introducing attenuation-energy response curve to the traditional CT images from energy integration detectors. Classification results showed the spectral CT enriched texture model can improve the area under the receiver operating characteristic curve (AUC) score by 7.3%, 0.42% and 3.0% for the spectral images, CMs and HFs respectively on the five-energy spectral data over the original single energy data only. The CM- and HF-inputs can achieve the best AUC of 0.934 and 0.927. This texture themed study shows the insight that incorporating clinical important prior information, e.g., tissue texture in this paper, into the medical imaging, such as the upstream image reconstruction, the downstream diagnosis, and so on, can benefit the clinical tasks.

Gastrointestinal stromal tumor risk classification: spectral CT quantitative parameters

PURPOSE

To examine the value of spectral CT quantitative parameters in gastrointestinal stromal tumor (GIST) risk classification.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board. The requirement for informed consent was signed. The authors evaluated 86 patients (30 high risk, 22 medium risk, 28 low risk, and 6 very low risk; mean age: 59 years [range 19-83 years]) with pathologically confirmed GIST who underwent plain and triple-phase contrast-enhanced CT with spectral CT imaging mode from March 2015 through September 2017, with manual follow-up. Quantitative parameters including the CT value of 70 keV monochromatic images, the slope of spectral curves, and the normalized iodine concentration (NIC) and water (iodine) concentrations were measured and calculated, and conducted a power analysis of the above data.

RESULTS

(1) The CT values at 70 keV of the high-risk group were higher than the intermediate and low groups in each of the enhanced phases (P ≤ 0.001), no significant differences in the intermediate-risk and low-risk groups were noted (P = 0.874, 0.871, 0.831, respectively). (2) The slope of the spectral curve of the high-risk group was higher than those of the intermediate and low groups in each of the enhanced phases (P ≤ 0.001), and there were no significant differences between the intermediate- and low-risk groups (P = 0.069, 0.466, 0.840, respectively). (3) The NIC of the high-risk group significantly differed from the lower risk groups (P ≤ 0.001). There was also no significant difference observed between the intermediate- and low-risk groups (P = 0.671, 0.457, 0.833, respectively). (4) The power analysis results show that only the low-risk group with delay period is 0.530, the rest groups are all greater than 0.999.

CONCLUSION

Dual-energy spectral CT with quantitative analysis may help to increase the accuracy in differentiating the pathological risk classification of GIST between high risk and non-high risk, preoperatively. There were limitations for distinguishing the intermediate- and low-risk groups.

Imaging biomarkers in upper gastrointestinal cancers

In parallel with the increasingly widespread availability of high performance imaging platforms and recent progresses in pathobiological characterisation and treatment of gastrointestinal malignancies, imaging biomarkers have become a major research topic due to their potential to provide additional quantitative information to conventional imaging modalities that can improve accuracy at staging and follow-up, predict outcome, and guide treatment planning in an individualised manner. The aim of this review is to briefly examine the status of current knowledge about imaging biomarkers in the field of upper gastrointestinal cancers, highlighting their potential applications and future perspectives in patient management from diagnosis onwards.

Application of spectral CT imaging in evaluating lymph node metastasis in patients with gastric cancers: initial findings

BACKGROUND

Traditional computed tomography (CT) can predict the lymph node metastasis of gastric cancers with moderate accuracy; however, investigation of spectral CT imaging in this field is still limited.

PURPOSE

To explore the application of spectral CT imaging in evaluating lymph node metastasis in patients with gastric cancers.

MATERIAL AND METHODS

Twenty-four patients with gastric cancers prospectively underwent spectral CT imaging in the arterial phase. The short and long diameters, material concentrations, and CT values were measured and compared between lymph nodes with and without metastasis. The diagnostic performance of the CT index in identifying metastatic lymph nodes was analyzed with receiver operating characteristic (ROC) analysis.

RESULTS

A total of 102 lymph nodes (77 metastatic, 25 non-metastatic) were detected on spectral CT imaging with the reference of postoperative pathologic exanimation. The short and long diameters, water/fat concentrations, CT value, and ratio between lymph nodes vs. tumors of metastatic lymph nodes were significantly higher than those of non-metastatic ones (all P < 0.05). With a cut-off of 0.785, the CT ratio of lymph node/tumor on 70-keV monochromatic images yielded an accuracy of 81.4% in differentiating lymph nodes with and without metastasis.

CONCLUSION

Spectral CT imaging detects lymph nodes more clearly, and the CT ratio of lymph node/tumor on 70-keV monochromatic images holds great potential in differentiating lymph nodes with and without metastasis, which is more accurate than size measurement.

T and N Staging of Gastric Cancer Using Dual-Source Computed Tomography

Aim

This study is aimed at comparing gastric cancer T and N staging between virtual monochromatic energy images and fusion images generated by dual-source computed tomography (DSCT) dual-energy mode data acquisition prospectively while measuring the iodine concentration of gastric cancer and lymph nodes at different T and N stages from iodine map retrospectively.

Methods

A total of 71 patients (50 males and 21 females; mean age: 59 ± 11 years) confirmed with gastric cancer by endoscopic biopsy with no neoadjuvant chemotherapy were enrolled for the CT examination before surgeries. The preoperative T and N staging results were compared between groups with pathological results as the gold standard. The iodine concentrations of the gastric lesions and LNs were measured on the iodine-based material decomposition images. All iodine concentration values were normalized against those in the abdominal aorta and defined as normalized iodine concentration (nIC) values. The short axis length of LNs and nIC values were statistically analyzed.

Results

Group A was better than group B for T3 and T4 staging. No statistically significant difference in the overall accuracies for N staging was found between groups. For the late arterial and delayed phases, T3 and T4 nIC values of the extraserosal adipose tissue showed statistically significant differences. The nIC values between N0 and Nm (N1-N3) showed statistically significant differences in the portal phase only.

Conclusions

T3 and T4 nIC values of the extraserosal adipose tissue showed statistically significant differences. Hence, dual-source CT may be helpful in the differential diagnosis between T3 and T4.

Dual Energy Spectral CT Imaging in the assessment of Gastric Cancer and cell proliferation: A Preliminary Study

Gastric cancer is one of the main diseases leading to cancer-related death. The recently introduced dual-energy spectral CT (DEsCT), allows to obtain many quantitative measurements from iodine-based material decomposition (MD) images, which contribute to improve the accuracy of staging of GC comparing to multidetector spiral CT. And Ki-67 is a well-recognized nuclear antigen-specific biomarker reflecting cellular proliferation for estimating growth fractions of various tumor types. In the present study we analyzed the features of quantitative measurements (the curve slope (λ_HU), IC, normalized iodine concentrations (NIC)) obtained from DEsCT and levels of Ki-67 protein expression. We demonstrated that the values between advanced gastric cancer (AGC) and early gastric cancer (EGC) were significantly different both in venous phase (VP) and delayed phase (DP). The values of different level of Ki-67 expression grade were significantly different both in VP and DP. The rank correlation analysis between Ki-67 grade and IC, NIC and λ_HU values showed significantly positive correlation in VP and DP. These results suggested that quantitative parameters (IC, NIC and λ_HU) in dual-energy CT imaging can be used to differentiate EGC from AGC, and have significantly positive correlation with Ki-67 antigen expression levels in gastric cancer for indicating tumor cellular proliferation.

Detection of gastric cancer and its histological type based on iodine concentration in spectral CT

Background

Computed tomography (CT) imaging is the most common imaging modality for the diagnosis and staging of gastric cancer. The aim of this study is was to prospectively explore the ability of quantitative spectral CT parameters in the detection of gastric cancer and its histologic types.

Methods

A total of 87 gastric adenocarcinoma (43 poorly and 44 well-differentiated) patients and 36 patients with benign gastric wall lesions (25 inflammation and 11 normal), who underwent dual-phase enhanced spectral CT examination, were retrospectively enrolled in this study. Iodine concentration (IC) and normalized iodine concentration (nIC) during arterial phase (AP) and portal venous phase (PP) were measured thrice in each patient by two blinded radiologists. Moreover, intraclass correlation coefficient (ICC) was used to assess the interobserver reproducibility. Differences of IC and nIC values between gastric cancer and benign lesion groups were compared using Mann-Whitney U test. Furthermore, the gender, age, location, thickness and histological types of gastric adenocarcinoma were analyzed by Mann-Whitney U test or Kruskal-Wallis H test. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of IC and nIC values, and the optimal cut-off value was calculated with Youden J.

Results

An excellent interobserver agreement (ICC >  0.6) was achieved for IC. Notably, the values of ICAP, ICPP, nICAP and nICPP were significantly higher in gastric cancer group (Z = 5.870, 3.894, 2.009 and 10.137, respectively; P < 0.05) than those in benign lesion group. Additionally, the values of ICAP, ICPP, nICAP and nICPP were significantly higher in poorly differentiated gastric adenocarcinoma group (Z = 4.118, 5.637, 6.729 and 2.950, respectively; P < 0.005) than those in well-differentiated gastric adenocarcinoma group. There were no statistically significant differences in the values of ICAP, ICPP, nICAP and nICPP between age, gender, tumor thickness and tumor location. Furthermore, the area under the curve (AUC) values of ICAP, nICAP, ICPP and nICPP were 0.745, 0.584, 0.662, and 0.932, respectively, for gastric cancer detection; while 0.756, 0.919, 0.851 and 0.684, respectively, in discriminating poorly differentiated gastric adenocarcinoma.

Conclusion

IC values exhibited great potential in the preoperative and non-invasive diagnosis of gastric cancer and its histological types. In particular, nICPP is more effective for the identification of gastric cancer, whereas nICAP is more effective in discriminating poorly differentiated gastric adenocarcinoma.

Diagnostic role of carbohydrate antigen 72-4 for gastrointestinal malignancy screening in Chinese patients: A prospective study

OBJECTIVE

Over the past decades, carbohydrate antigen 72-4 (CA72-4) was thought to be a tumor marker that was elevated in healthy individuals and patients with malignancies, including gastrointestinal (GI), ovarian, endometrial and lung malignancies. Furthermore, studies found that elevated serum CA72-4 might predict digestive tumors, especially gastric tumors, although there was still neither a sensitive nor specific tumor biomarker for gastric cancer (GC). This study aimed to evaluate the diagnostic accuracy of CA72-4 in predicting malignancies, especially GC.

METHODS

Altogether 403 patients underwent a CA72-4 test after admission to the Department of Gastroenterology in Changhai Hospital, the Second Military Medical University, from 1 June 2015 to 31 October 2015. Their age and sex, main symptoms, and final diagnoses were summarized.

RESULTS

The positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of CA72-4 for diagnosing GC were 31.58%, 79.17%, 1.70, and 0.97, respectively. In the receiver operating characteristic (ROC) curve analysis, the area under the ROC curve for discriminating between patients with GC and those without was 0.62.

CONCLUSION

Performing a CA72-4 test on its own is of little use for predicting malignances, especially GC, in patients with GI diseases.

Dual Energy Computed Tomography Scans of the Bowel: Benefits, Pitfalls, and Future Directions

Current computed tomography bowel imaging is challenging given the variable distension, content, and location of the bowel, the different appearance of tumors within and adjacent to bowel, and peristaltic artifacts. Published data remain sparse. Derangements in enhancement may be highlighted, image artifacts reduced, and radiation dose from multiphase scans minimized. This modality is suited for imaging bowel tumor detection and characterization, gastrointestinal bleeding, and bowel inflammation, and ischemia. Experimental results on computed tomography colonography and novel bowel contrast material offer hope for major improvements in bowel interrogation. It is likely to become increasingly valuable for bowel-related disease diagnosis and monitoring.

Axillary Sentinel Lymph Nodes in Breast Cancer: Quantitative Evaluation at Dual-Energy CT

Purpose To evaluate the diagnostic performance of quantitative parameters derived from dual-energy CT for the preoperative diagnosis of metastatic sentinel lymph nodes (SLNs) in participants with breast cancer. Materials and Methods For this prospective study, dual-phase contrast agent-enhanced CT was performed in female participants with breast cancer from June 2015 to December 2017. Quantitative dual-energy CT parameters and morphologic parameters were compared between metastatic and nonmetastatic SLNs. The quantitative parameters were fitted to univariable and multivariable logistic regression models. The diagnostic role of morphologic and quantitative parameters was analyzed by receiver operating characteristic curves and compared by using the McNemar test. Results This study included 193 female participants (mean age, 47.6 years ± 10.1; age range, 22-79 years). Quantitative dual-energy CT parameters including slope of the spectral Hounsfield unit curve (λ_Hu) measured at both arterial and venous phases, normalized iodine concentration at both arterial and venous phase, and normalized effective atomic number at the venous phase were higher in metastatic than in nonmetastatic SLNs (P value range, ≤.001 to .031). Univariable and multivariable logistic regression analyses showed that venous phase λ_Hu (in Hounsfield units per kiloelectron-volt) was the best single parameter for the detection of metastatic SLNs. The accuracy of the venous phase λ_Hu for detecting metastatic SLNs was 90.5% on a per-lymph node basis and 87.0% on a per-patient basis. The accuracy and specificity at venous phase λ_Hu was higher than their counterparts in the morphologic parameters (P < .001). Conclusion Dual-energy CT is a complementary means for the preoperative identification of sentinel lymph nodes metastases in participants with breast cancer. © RSNA, 2018 Online supplemental material is available for this article.

Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT

Gastric cancer remains fourth in cancer incidence worldwide with a five-year survival of only 20%-30%. Peritoneal metastasis is the most frequent type of metastasis that accompanies unresectable gastric cancer and is a definitive determinant of prognosis. Preventing and controlling the development of peritoneal metastasis could play a role in helping to prolong the survival of gastric cancer patients. A non-invasive and efficient imaging technique will help us to identify the invasion and metastasis process of peritoneal metastasis and to monitor the changes in tumor nodules in response to treatments. This will enable us to obtain an accurate description of the development process and molecular mechanisms of gastric cancer. We have recently described experiment using dual energy CT (DECT) and positron emission tomography/computed tomography (PET/CT) platforms for the detection and monitoring of gastric tumor metastasis in nude mice models. We have shown that weekly continuous monitoring with DECT and PET/CT can identify dynamic changes in peritoneal metastasis. The sFRP1-overexpression in gastric cancer mice models showed positive radiological performance, a higher FDG uptake and increasing enhancement, and the SUVmax (standardized uptake value) of nodules demonstrated an obvious alteration trend in response to targeted therapy of TGF-β1 inhibitor. In this article, we described the detailed non-invasive imaging procedures to conduct more complex research on gastric cancer peritoneal metastasis using animal models and provided representative imaging results. The use of non-invasive imaging techniques should enable us to better understand the mechanisms of tumorigenesis, monitor tumor growth, and evaluate the effect of therapeutic interventions for gastric cancer.

Association between spectral computed tomography images and clinicopathological features in advanced gastric adenocarcinoma

To investigate the role of spectral computed tomography (CT)-generated iodine concentration (IC) in the evaluation of clinicopathological features of advanced gastric adenocarcinoma (AGC), 42 patients who underwent abdominal enhanced CT with spectral imaging mode were selected for the present study. The IC of the primary lesion in the arterial phase (IC_AP) and portal venous phase (IC_VP) was measured and the IC of the aorta was used for a normalized iodine concentration (nIC). Micro-vessel density (MVD) and lymphatic vessel density (LVD) were detected using immunohistochemical assays against cluster of differentiation 34 and D2-40, respectively. Other clinicopathological characteristics were also documented. The IC parameters were revealed to be significantly increased in the high-MVD group, particularly for the nIC_VP (P=0.002). Additionally, the nIC_AP revealed a significant difference (P=0.041) between the high- and low-LVD group. The nIC_AP and nIC_VP were increased in the poorly differentiated group compared with the moderately differentiated group (P=0.040 and P=0.011, respectively). The ICs and MVD demonstrated a statistically significant positive linear correlation. nIC_VP was able to be used to discriminate between the moderately and poorly differentiated carcinomas, with an area under the receiver operating characteristic curve of 0.759. However, IC demonstrated no correlation with serosal involvement, lymph node metastasis, LVD, and nodular or metastatic tumors. The results of the present study suggest that the nIC_VP value may serve as a non-invasive marker for the angiogenesis of, and the differentiations between, patients with AGC.

Iodine Concentration in Spectral CT: Assessment of Prognostic Determinants in Patients With Gastric Adenocarcinoma

OBJECTIVE

The purpose of this study was to use virtual monochromatic spectral CT to investigate the usefulness of iodine concentration (IC) and its correlation with clinicopathologically determined prognostic factors in gastric adenocarcinoma.

SUBJECTS AND METHODS

From June 2012 to March 2015, 34 patients with gastric adenocarcinoma underwent arterial and portal venous phase spectral CT. The ICs in the arterial and portal venous phases were calculated and then normalized with the aorta as normalized IC (NIC). The surgical specimen was evaluated with CD34 staining to determine microvessel density (MVD). The correlation between imaging results and clinicopathologic findings was investigated for histologic grading, lymph node metastasis, serosal involvement, distant metastasis, pathologic TNM stage, and MVD.

RESULTS

The mean arterial phase NIC value of tumors was 0.12 ± 0.03, portal venous phase NIC value was 0.39 ± 0.06, and MVD was 26.94 ± 7.87 vessels per high-power field (×400). Both arterial phase and portal venous phase NIC values were significantly higher in poorly differentiated gastric adenocarcinomas (p = 0.005) than in moderately differentiated tumors (p = 0.013). There was no significant correlation between NIC and serosal involvement or distant metastasis. There was significant correlation between the NIC and MVD in gastric adenocarcinoma (arterial phase NIC, p = 0.013; portal venous phase NIC, p = 0.001). However, neither the arterial nor the portal venous phase NIC of gastric adenocarcinoma had a significant relation to lymphatic metastasis or pathologic TNM stage. There was a significant difference between the high and low MVD groups with respect to portal venous phase NIC (p = 0.045).

CONCLUSION

NIC can serve as a useful predictor of angiogenesis and degree of differentiation of moderately and poorly differentiated gastric adenocarcinomas.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Serum NDRG2 acts as a novel biomarker for the diagnosis of patients with gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common digestive malignancies worldwide. N-myc downstream-regulated gene 2 (NDRG2) is a differentiation-related gene which is considered to be a metastasis suppressor gene. The purpose of this study was to detect the serum expression of NDRG2 and its clinical significance in the early detection of patients with GC.

METHODS

Serum NDRG2 expression were examined in 107 patients with GC, 52 with benign gastric disease patients, and 64 healthy volunteers using reverse transcription quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis at mRNA and protein level, respectively. The relationship between NDRG2 expression and clinicopathologic characteristics was analyzed by chi-square test. The diagnostic value of NDRG2 was estimated via establishing the receiver operating characteristic (ROC) curve.

RESULTS

the serum NDRG2 expression was lower in GC patients than that in patients with benign disease and healthy volunteers both at mRNA and protein level (P<0.05). And the low NDRG2 expression was significantly associated with tumor size, lymph node metastasis and TNM stage. ROC curve manifested that NDRG2 had a high diagnostic value with an AUC of 0.896 corresponding with a sensitivity of 85.9% and a specificity of 62.6%.

CONCLUSION

The expression of NDRG2 was reduced in GC patients. Moreover, serum NDRG2 could be a potential diagnostic marker for GC.

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

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

Spectral computed tomography in advanced gastric cancer: Can iodine concentration non-invasively assess angiogenesis?

AIM

To investigate the correlation of iodine concentration (IC) generated by spectral computed tomography (CT) with micro-vessel density (MVD) and vascular endothelial growth factor (VEGF) expression in patients with advanced gastric carcinoma (GC).

METHODS

Thirty-four advanced GC patients underwent abdominal enhanced CT in the gemstone spectral imaging mode. The IC of the primary lesion in the arterial phase (AP) and venous phase (VP) were measured, and were then normalized against that in the aorta to provide the normalized IC (nIC). MVD and VEGF were detected by immunohistochemical assays, using CD34 and VEGF-A antibodies, respectively. Correlations of nIC with MVD, VEGF, and clinical-pathological features were analyzed.

RESULTS

Both nICs correlated linearly with MVD and were higher in the primary lesion site than in the normal control site, but were not correlated with VEGF expression. After stratification by clinical-pathological subtypes, nIC-AP showed a statistically significant correlation with MVD, particularly in the group with tumors at stage T4, without nodular involvement, of a mixed Lauren type, where the tumor was located at the antrum site, and occurred in female individuals. nIC-VP showed a positive correlation with MVD in the group with the tumor at stage T4 and above, had nodular involvement, was poorly differentiated, was located at the pylorus site, of a mixed and diffused Lauren subtype, and occurred in male individuals. nIC-AP and nIC-VP showed significant differences in terms of histological differentiation and Lauren subtype.

CONCLUSION

The IC detected by spectral CT correlated with the MVD. nIC-AP and nIC-VP can reflect angiogenesis in different pathological subgroups of advanced GC.

White Paper of the Society of Computed Body Tomography and Magnetic Resonance on Dual-Energy CT, Part 4: Abdominal and Pelvic Applications

This is the fourth of a series of 4 white papers that represent expert consensus documents developed by the Society of Computed Body Tomography and Magnetic Resonance through its task force on dual-energy computed tomography. This article, part 4, discusses DECT for abdominal and pelvic applications and, at the end of each, will offer our consensus opinions on the current clinical utility of the application and opportunities for further research.