Evaluating the response of gastric carcinomas to neoadjuvant chemotherapy using iodine concentration on spectral CT: a comparison with pathological regression. Clin Radiol. 2015;70:1198-1204. [PMID: 26188843 DOI: 10.1016/j.crad.2015.06.083]

Preoperative prediction of tumor budding and lymphovascular invasion in colon cancer using dual-energy CT: a prospective study with internal model validation

OBJECTIVE

This study evaluates the potential of dual-energy CT (DECT) for preoperative prediction of tumor budding (TB) and lymphovascular invasion (LVI) in colon cancer.

METHODS

This prospective study enrolled 153 patients (mean age 61.33 years ± 0.88) with pathologically confirmed colon cancer. All participants underwent arterial and venous phase DECT scans within one week before surgery. Two radiologists independently analyzed the images, assessing tumor location, clinical N stage (cN stage), iodine concentration (IC), effective atomic number (Z-eff), and dual-energy index (DEI). The normalized iodine concentration (nIC) was obtained by comparing measured IC to the abdominal aortic IC. Logistic regression identified independent risk factors for high-grade TB and LVI positivity. The Akaike Information Criterion guided model selection, and the area under the curve (AUC) was calculated. Bootstrap validation with 1000 iterations was used for internal validation.

RESULTS

Tumor location and cN stage were identified as independent risk factors for high-grade TB, and nICA tumor and cN stage for LVI positivity. The optimal model for predicting high-grade TB included tumor location, cN stage, and DEIV tumor, with an AUC of 0.763 (sensitivity: 75.0%; specificity: 64.7%) and a mean AUC of 0.712. Similarly, the model for LVI positivity included nICA tumor, cN stage, and nICA peripheral fat, with an AUC of 0.811 (sensitivity: 71.7%; specificity: 76.6%) and a mean AUC of 0.814.

CONCLUSION

DECT could consistently quantify colon cancer characteristics, and DECT-based models performed well in the preoperative prediction of TB and LVI.

Development of a Preoperative Prediction Model Based on Spectral CT to Evaluate Axillary Lymph Node With Macrometastases in Clinical T1/2N0 Invasive Breast Cancer

OBJECTIVES

To develop a prediction model based on spectral computed tomography (CT) to evaluate axillary lymph node (ALN) with macrometastases in clinical T1/2N0 invasive breast cancer.

METHODS

A total of 217 clinical T1/2N0 invasive breast cancer patients who underwent spectral CT scans were retrospectively enrolled and categorized into a training cohort (n = 151) and validation cohort (n = 66). These patients were classified into ALN nonmacrometastases (stage pN0 or pN0 [i+] or pN1mi) and ALN macrometastases (stage pN1-3) subgroups. The morphologic criteria and quantitative spectral CT parameters of the most suspicious ALN were measured and compared. Least absolute shrinkage and selection operator (Lasso) was used to screen predictive indicators to build a logistic model. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the models.

RESULTS

The combined arterial-venous phase spectral CT model yielded the best diagnostic performance in discrimination of ALN nonmacrometastases and ALN macrometastases with the highest AUC (0.963 in the training cohort and 0.945 in validation cohorts). Among single phase spectral CT models, the venous phase spectral CT model showed the best performance (AUC = 0.960 in the training cohort and 0.940 in validation cohorts). There was no significant difference in AUCs among the 3 models (DeLong test, P > .05 for each comparison).

CONCLUSION

A Lasso-logistic model that combined morphologic features and quantitative spectral CT parameters based on contrast-enhanced spectral imaging potentially be used as a noninvasive tool for individual preoperative prediction of ALN status in clinical T1/2N0 invasive breast cancers.

Feasibility of iodine concentration parameter and extracellular volume fraction derived from dual-energy CT for distinguishing type I and type II epithelial ovarian carcinoma

OBJECTIVES

To investigate the feasibility of using the iodine concentration (IC) parameter and extracellular volume (ECV) fraction derived from dual-energy CT for distinguishing between type I and type II epithelial ovarian carcinoma (EOC).

METHODS

This study retrospectively included 172 patients with EOC preoperatively underwent dual-energy CT scans. Patients were grouped as type I and type II EOC according to postoperatively pathologic results. Normalized IC (NIC, %) values from arterial-phase (AP), venous-phase (VP) and delay-phase (DP) were measured by two observers. ECV fraction (%) was calculated by DP-NIC and hematocrit. Intra-observer correlation coefficient (ICC) was used to assess the agreement between measurements made by two observers. The differences of imaging parameters between the two groups were compared. Logistic regression was used to select independent predictive factors and establish combined parameter. Receiver operating characteristic curve was used to analyze performance of all parameters.

RESULTS

The ICCs for all parameters exceeded 0.75. All parameters in type II EOC were all significantly higher than those in type I EOC (all P < 0.05). VP-NIC exhibited the highest Area under the curve (AUC) of 0.804, along with 80.39% sensitivity and 71.43% specificity. VP-NIC was identified as the independent factor. The sensitivity and specificity of ECV fraction were 78.43% and 71.43%, respectively. The combined parameter consisting of AP-NIC, VP-NIC, DP-NIC, and ECV fraction yielded an AUC of 0.823, with sensitivity of 76.47% and specificity of 77.14%. The sensitivity of the combined parameter was significantly higher than that of AP-NIC (P = 0.049).

CONCLUSION

It is valuable for dual-energy CT IC-based parameters and ECV fraction in preoperatively identifying type I and type II EOC.

CRITICAL RELEVANCE STATEMENT

Dual-energy CT-normalized iodine concentration and extracellular volume fraction achieved satisfactory discriminative efficacy, distinguishing between type I and type II epithelial ovarian carcinoma.

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

OBJECTIVES

To develop a nomogram based on clinical features and spectral quantitative parameters to preoperatively predict the Lauren classification for locally advanced gastric cancer (LAGC).

METHODS

Patients diagnosed with LAGC by postoperative pathology who underwent abdominal triple-phase enhanced spectral computed tomography (CT) were prospectively enrolled in this study between June 2023 and December 2023. All the patients were categorized into intestinal- and diffuse-type groups according to the Lauren classification. Traditional characteristics, including demographic information, serum tumor markers, gastroscopic pathology, and image semantic features, were collected. Spectral quantitative parameters, including iodine concentration (IC), effective atomic number (Zeff), and slope of the energy spectrum curve from 40 keV to 70 keV (λ), were measured three times for each patient by two blinded radiologists in arterial/venous/delayed phases (AP/VP/DP). Differences in traditional features and spectral quantitative parameters between the two groups were compared using univariable analysis. Independent predictors of the Lauren classification of LAGC were screened using multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminating capability. Ultimately, the nomogram, including clinical features and spectral CT quantitative parameters, was developed.

RESULTS

Gender, nIC in AP (APnIC), and λ in DP (λd) were independent predictors for Lauren classification. The nomogram based on these indicators produced the best performance with an area under the curve of 0.841 (95% confidence interval: 0.749-0.932), specificity of 85.3%, accuracy of 76.4%, and sensitivity of 68.4%.

CONCLUSION

The nomogram based on clinical features and spectral CT quantitative parameters exhibits great potential in the preoperative and non-invasive assessment of Lauren classification for LAGC.

KEY POINTS

Question Can the proposed nomogram, integrating clinical features and spectral quantitative parameters, preoperatively predict the Lauren classification in locally advanced gastric cancer (LAGC)? Findings The nomogram, based on gender, arterial phase normalized iodine concentration, and slope of the energy spectrum curve in the delayed phase showed satisfactory predictive ability. Clinical relevance The established nomogram could contribute to guiding individualized treatment strategies and risk stratification in patients by predicting the Lauren classification for LAGC before surgery.

A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer

OBJECTIVES

To develop and validate a quantitative model for predicting serosal invasion based on multi-parameters in preoperative dual-energy CT (DECT).

MATERIALS AND METHODS

A total of 342 LAGC patients who underwent gastrectomy and DECT from six centers were divided into one training cohort (TC), and two validation cohorts (VCs). Dual-phase enhanced DECT-derived iodine concentration (IC), water concentration, and monochromatic attenuation of lesions, along with clinical information, were measured and collected. The independent predictors among these characteristics for serosal invasion were screened with Spearman correlation analysis and logistic regression (LR) analysis. A quantitative model was developed based on LR classifier with fivefold cross-validation for predicting the serosal invasion in LAGC. We comprehensively tested the model and investigated its value in survival analysis.

RESULTS

A quantitative model was established using IC, 70 keV, 100 keV monochromatic attenuations in the venous phase, and CT-reported T4a, which were independent predictors of serosal invasion. The proposed model had the area-under-the-curve (AUC) values of 0.889 for TC and 0.860 and 0.837 for VCs. Subgroup analysis showed that the model could well discriminate T3 from T4a groups, and T2 from T4a groups in all cohorts (all p < 0.001). Besides, disease-free survival (DFS) (TC, p = 0.015; and VC1, p = 0.043) could be stratified using this quantitative model.

CONCLUSION

The proposed quantitative model using multi-parameters in DECT accurately predicts serosal invasion for LAGC and showed a significant correlation with the DFS of patients.

CRITICAL RELEVANCE STATEMENT

This quantitative model from dual-energy CT is a useful tool for predicting the serosal invasion of locally advanced gastric cancer.

KEY POINTS

Serosal invasion is a poor prognostic factor in locally advanced gastric cancer that may be predicted by DECT. DECT quantitative model for predicting serosal invasion was significantly and positively correlated with pathologic T stages. This quantitative model was associated with patient postoperative disease-free survival.

Combination of clinical and spectral-CT iodine concentration for predicting liver metastasis in gastric cancer: a preliminary study

PURPOSE

This study aimed to determine the diagnostic efficacy of various indicators and models for the prediction of gastric cancer with liver metastasis.

METHODS

Clinical and spectral computed tomography (CT) data from 80 patients with gastric adenocarcinoma who underwent surgical resection were retrospectively analyzed. Patients were divided into metastatic and non-metastatic groups based on whether or not to occur liver metastasis, and the region of interest (ROI) was measured manually on each phase iodine map at the largest level of the tumor. Iodine concentration (IC), normalized iodine concentration (nIC), and clinical data of the primary gastric lesions were analyzed. Logistic regression analysis was used to construct the clinical indicator (CI) and clinical indicator-spectral CT iodine concentration (CI-Spectral CT-IC) Models, which contained all of the parameters with statistically significant differences between the groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the accuracy of the models.

RESULTS

The metastatic group showed significantly higher levels of Cancer antigen125 (CA125), carcinoembryonic antigen (CEA), IC, and nIC in the arterial phase, venous phase, and delayed phase than the non-metastatic group (all p < 0.05). Normalized iodine concentration Venous Phase (nICVP) exhibited a favorable performance among all IC and nIC parameters for forecasting gastric cancer with liver metastasis (area under the curve (AUC), 0.846). The combination model of clinical data with significant differences and nICVP showed the best diagnostic accuracy for predicting liver metastasis from gastric cancer, with an AUC of 0.897.

CONCLUSION

nICVP showed the best diagnostic efficacy for predicting gastric cancer with liver metastasis. Clinical Indicators-normalized ICVP model can improve the prediction accuracy for this condition.

Spectral CT vs. diffusion-weighted imaging for the quantitative prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer

OBJECTIVES

To compare the performance of spectral CT and diffusion-weighted imaging (DWI) for predicting pathologic response after neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC).

MATERIALS AND METHODS

This was a retrospective analysis drawn from a prospective dataset. Sixty-five patients who underwent baseline concurrent triple-phase enhanced spectral CT and DWI-MRI and standard NAC plus radical gastrectomy were enrolled, and those with poor images were excluded. The tumor regression grade (TRG) was the reference standard, and patients were classified as responders (TRG 0 + 1) or non-responders (TRG 2 + 3). Quantitative iodine concentration (IC), normalized IC (nIC), and apparent diffusion coefficient (ADC) were measured by placing a freehand region of interest manually on the maximal two-dimensional plane. Their differences between responders and non-responders were compared. The performances of significant parameters were evaluated by the receiver operating characteristic analysis. The correlations between parameters and TRG status were explored through Spearman correlation coefficient test. Kaplan-Meier survival analysis was adopted to analyze their relationship with patient survival.

RESULTS

nICDP and ADC were associated with the TRG and yielded comparable performances for predicting TRG categories, with area under the curve (AUC) of 0.674 and 0.673, respectively. Their combination achieved a significantly increased AUC of 0.770 (p ; 0.05) and was associated with patient disease-free survival, with hazard ratio of 2.508 (1.043-6.029).

CONCLUSION

Spectral CT and DWI were equally useful imaging techniques for predicting pathologic response to NAC in LAGC. The combination of nICDP and ADC gained significant incremental benefits and was related to patient disease-free survival.

CLINICAL RELEVANCE STATEMENT

Spectral CT and DWI-based quantitative measurements are effective markers for predicting the pathologic regression outcomes of locally advanced gastric cancer patients after neoadjuvant chemotherapy.

KEY POINTS

• The pathologic tumor regression grade, the standard criteria for treatment response after neoadjuvant chemotherapy in gastric cancer patients, is difficult to predict early. • The quantitative parameters of normalized iodine concentration at delay phase and apparent diffusion coefficients were correlated with pathologic response; their combination demonstrated incremental benefits and was associated with patient disease-free survival. • Spectral CT and DWI are equally useful imaging modalities for predicting tumor regression grade after neoadjuvant chemotherapy in patients with locally advanced gastric cancer.

Preliminary differentiation of benign and malignant gastric wall thickening using dual-layer spectral-detector CT

BACKGROUND

Dual-layer spectral-detector computed tomography (DLCT) may have the potential to evaluate gastric wall thickening.

PURPOSE

To evaluate the efficacy of DLCT quantitative parameters in differentiating between benign and malignant thickening of the gastric wall.

MATERIAL AND METHODS

A total of 58 patients with "gastric wall thickening" who underwent multi-phase abdominal enhanced DLCT scans were included in this study. Of these patients, 33 were malignant and 25 were benign. Parameters such as iodine concentration (IC), effective atomic number (Zeff), and attenuation of the lesions were measured during the arterial phase (AP) and venous phase (VP). Binary logistic regression was employed to calculate the combined prediction probabilities. The accuracy of the DLCT parameters was assessed using receiver operating characteristic (ROC) curves.

RESULTS

The values of IC, nIC, Zeff, normalized Zeff, and attenuation in the AP and VP were significantly higher (all P < 0.05) in the malignant group compared to the benign group. The ROC curves revealed that the IC, Zeff, and attenuation in the VP exhibited high diagnostic performance, with area under the ROC curve (AUC) values of 0.864, 0.862, and 0.840, respectively. The new combination of these three factors and gastric wall thickness had an AUC of 0.884, and the sensitivity and specificity were determined to be 81.8% and 92.0%, respectively.

CONCLUSION

Spectral CT parameters, particularly the combination of gastric wall thickness, attenuation, IC, and Zeff in VP, have value in distinguishing between benign and malignant gastric wall thickening.

Predicting human epidermal growth factor receptor 2 status of patients with gastric cancer by computed tomography and clinical features

Background

There have been no studies on predicting human epidermal growth factor receptor 2 (HER2) status in patients with resectable gastric cancer (GC) in the neoadjuvant and perioperative settings. We aimed to investigate the use of preoperative contrast-enhanced computed tomography (CECT) imaging features combined with clinical characteristics for predicting HER2 expression in GC.

Methods

We retrospectively enrolled 301 patients with GC who underwent curative resection and preoperative CECT. HER2 status was confirmed by postoperative immunohistochemical analysis with or without fluorescence in situ hybridization. A prediction model was developed using CECT imaging features and clinical characteristics that were independently associated with HER2 status using multivariate logistic regression analysis. Receiver operating characteristic curves were constructed and the performance of the prediction model was evaluated. The bootstrap method was used for internal validation.

Results

Three CECT imaging features and one serum tumor marker were independently associated with HER2 status in GC: enhancement ratio in the arterial phase (odds ratio [OR] = 4.535; 95% confidence interval [CI], 2.220-9.264), intratumoral necrosis (OR = 2.64; 95% CI, 1.180-5.258), tumor margin (OR = 3.773; 95% CI, 1.968-7.235), and cancer antigen 125 (CA125) level (OR = 5.551; 95% CI, 1.361-22.651). A prediction model derived from these variables showed an area under the receiver operating characteristic curve of 0.802 (95% CI, 0.740-0.864) for predicting HER2 status in GC. The established model was stable, and the parameters were accurately estimated.

Conclusions

Enhancement ratio in the arterial phase, intratumoral necrosis, tumor margin, and CA125 levels were independently associated with HER2 status in GC. The prediction model derived from these factors may be used preoperatively to estimate HER2 status in GC and guide clinical treatment.

Predicting pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer: The establishment of a spectral CT-based nomogram from prospective datasets

BACKGROUND

To establish a spectral CT-based nomogram for predicting early neoadjuvant chemotherapy (NAC) response for locally advanced gastric cancer (LAGC).

METHODS

This study prospectively recruited 222 cases (177 male and 45 female patients, 9.59 ± 9.54 years) receiving NAC and radical gastrectomy. Triple enhanced spectral CT scans were performed before NAC initiation. According to post-operative tumor regression grade (TRG), patients were classified into responders (TRG = 0 + 1) or non-responders (TRG = 2 + 3), and split into a primary (156) and validation (66) dataset at 7:3 ratio chronologically. We compared clinicopathological data, follow-up information, iodine concentration (IC), normalized ICs (nICs) in arterial/venous/delayed phases (AP/VP/DP) between responders and non-responders. Independent risk factors of response were screened by multivariable logistic regression and adopted for model construction. Model was visualized by nomograms and its capability was determined through receiver operating characteristic (ROC) curves. Log-rank survival analysis was conducted to explore associations between TRG, nomogram and patients' survival.

RESULTS

This work identified Borrmann classification, ICDP, and nICDP were independent risk factors of response outcomes. A spectral CT-based nomogram was built accordingly and achieved an area under the curve (AUC) of 0.797 (0.692-0.879) and 0.741(0.661-0.811) for the primary and validation dataset, respectively, higher than AUC of individual parameters alone. The nomogram was related to disease-free survival in the validation dataset (Hazard ratio (HR): 5.19 [1.18-12.93], P = 0.02).

CONCLUSIONS

The spectral CT-based nomogram provides an efficient tool for predicting the pathologic response outcomes of GC after NAC and disease-free survival risk stratification.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas

PURPOSE

To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9).

METHODS

This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test.

RESULTS

The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076).

CONCLUSIONS

Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023

The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence-based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti-angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)-positive and deficient DNA mismatch repair (dMMR)/microsatellite instability-high (MSI-H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

Value of spectral CT parameters in predicting the efficacy of neoadjuvant chemotherapy for gastric cancer

AIM

To investigate the value of pre-chemotherapy spectral computed tomography (CT) parameters in predicting neoadjuvant chemotherapy (NAC) response in gastric cancer (GC).

MATERIALS AND METHODS

Sixty patients with GC who received NAC and underwent spectral CT examination before chemotherapy were enrolled retrospectively and divided into a responsive group and a non-responsive group according to the postoperative pathological tumour regression grade. Clinical characteristics were collected. The iodine concentration (IC), water concentration (WC), and effective atomic number (Eff-Z) of the portal venous phases were measured before chemotherapy, and IC was normalised to that of the aorta to provide the normalised IC (NIC). An independent samples t-test, Mann-Whitney U-test, or chi-square test was used to analyse the differences between the two groups, and the receiver operating curve (ROC) was used to evaluate the predictive performance of different variables.

RESULTS

The neutrophil-to-lymphocyte ratio (NLR) was lower in the responsive group than in the non-responsive group (p<0.05). IC, NIC, and Eff-Z values were significantly higher in the responsive group than in the non-responsive group (p<0.01). The areas under the ROC curves for the NLR, IC, NIC, and Eff-Z were 0.694, 0.688, 0.799, and 0.690, respectively. The combination of NIC, Eff-Z, and NLR values showed good diagnostic performance in predicting response to NAC in GC, with an area under the ROC curve of 0.857, 76.92% sensitivity, 80% accuracy, and 85.71% specificity.

CONCLUSION

Spectral CT parameters may serve as non-invasive tools for predicting the response to NAC in patients with GC.

Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy

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

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.

Diagnosis of benign and malignant thyroid nodules by a dual-layer spectral detector CT-based nomogram

Introduction

Preoperative diagnosis of benign and malignant thyroid nodules is crucial for appropriate clinical treatment and individual patient management. In this study, a double-layer spectral detector computed tomography (DLCT)-based nomogram for the preoperative classification of benign and malignant thyroid nodules was developed and tested.

Methods

A total of 405 patients with pathological findings of thyroid nodules who underwent DLCT preoperatively were retrospectively recruited. They were randomized into a training cohort (n=283) and a test cohort (n=122). Information on clinical features, qualitative imaging features and quantitative DLCT parameters was collected. Univariate and multifactorial logistic regression analyses were used to screen independent predictors of benign and malignant nodules. A nomogram model based on the independent predictors was developed to make individualized predictions of benign and malignant thyroid nodules. Model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis(DCA).

Results

Standardized iodine concentration in the arterial phase, the slope of the spectral hounsfield unit(HU) curves in the arterial phase, and cystic degeneration were identified as independent predictors of benign and malignant thyroid nodules. After combining these three metrics, the proposed nomogram was diagnostically effective, with AUC values of 0.880 for the training cohort and 0.884 for the test cohort. The nomogram showed a better fit (all p &gt; 0.05 by Hosmer−Lemeshow test) and provided a greater net benefit than the simple standard strategy within a large range of threshold probabilities in both cohorts.

Discussion

The DLCT-based nomogram has great potential for the preoperative prediction of benign and malignant thyroid nodules. This nomogram can be used as a simple, noninvasive, and effective tool for the individualized risk assessment of benign and malignant thyroid nodules, helping clinicians make appropriate treatment decisions.

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.

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.

'FLARE' of tumor marker in advanced gastric cancer treated with first-line systemic therapy

BACKGROUND

Transient tumor marker elevations caused by chemotherapy were defined as 'Flare' and have been demonstrated in some solid tumors. In clinical practice, we observed that some patients were accompanied by elevated tumor markers during treatment, but subsequent imaging proved that the treatment they received was effective.

OBJECTIVES

We aimed to study the Flare and the prognosis in advanced gastric cancer.

DESIGN

This is an observational retrospective study. A total of 167 patients were enrolled in this study. Carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19-9 and CA125 values were obtained before the first, second, third, fourth, fifth and sixth cycles of treatment, respectively.

METHODS

Imaging for the first efficacy assessment was reviewed according to the Response Evaluation Criteria in Solid Tumors 1.1 (RECIST 1.1) criteria. Kaplan-Meier analyses and log-rank tests were performed for overall survival (OS) analyses. Univariate and multivariate Cox analyses were used to determine the prognostic factor for OS and progression-free survival (PFS).

RESULTS

37.1% of patients were accompanied with at least one tumor marker Flare during the course of treatment. The median time to tumor marker peak was 24-30 days and the Flare duration lasted 49-53 days. Patients with tumor markers Flare had a worse OS. Flare may be associated with the use of 5-fluorouracil. Baseline CEA and CA125 levels were the independent prognostic factors for OS and baseline CA125 level was the independent prognostic factor for PFS.

CONCLUSION

Initial elevation of tumor markers during treatment is not an indication of tumor progression. Patients with tumor markers 'Flare' may had a worse OS.

Enhanced CT-based radiomics predicts pathological complete response after neoadjuvant chemotherapy for advanced adenocarcinoma of the esophagogastric junction: a two-center study

Purpose

This study aimed to develop and validate CT-based models to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric junction (AEG).

Methods

Pre-NAC clinical and imaging data of AEG patients who underwent surgical resection after preoperative-NAC at two centers were retrospectively collected from November 2014 to September 2020. The dataset included training (n = 60) and external validation groups (n = 32). Three models, including CT-based radiomics, clinical and radiomics–clinical combined models, were established to differentiate pCR (tumor regression grade (TRG) = grade 0) and nonpCR (TRG = grade 1–3) patients. For the radiomics model, tumor-region-based radiomics features in the arterial and venous phases were extracted and selected. The naïve Bayes classifier was used to establish arterial- and venous-phase radiomics models. The selected candidate clinical factors were used to establish a clinical model, which was further incorporated into the radiomics–clinical combined model. ROC analysis, calibration and decision curves were used to assess the model performance.

Results

For the radiomics model, the AUC values obtained using the venous data were higher than those obtained using the arterial data (training: 0.751 vs. 0.736; validation: 0.768 vs. 0.750). Borrmann typing, tumor thickness and degree of differentiation were utilized to establish the clinical model (AUC-training: 0.753; AUC-validation: 0.848). The combination of arterial- and venous-phase radiomics and clinical factors further improved the discriminatory performance of the model (AUC-training: 0.838; AUC-validation: 0.902). The decision curve reflects the higher net benefit of the combined model.

Conclusion

The combination of CT imaging and clinical factors pre-NAC for advanced AEG could help stratify potential responsiveness to NAC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01273-w.

Computed tomography features and clinical characteristics of gastritis cystica profunda

Background

The diagnostic evidence of gastritis cystica profunda (GCP) are not adequately described due to its extremely low morbidity. This study aimed to analyze and summarize the comprehensive CT features and clinical characteristics of patients with GCP.

Results

Nineteen patients were enrolled, including eight men and eleven women, with a mean age of 55.53 years. Only one patient had the history of gastric polypectomy. Among the nineteen cases, two cases were in the gastric cardia, four in the gastric fundus, eight in the gastric body and five in the gastric antrum. The shapes were sphere in thirteen patients, hemisphere in five patients and diffuse in one patient. The mean size of eighteen local lesions was 1.63 cm. The cystic changes in submucosa were detected in fifteen patients. Compared with the pancreas, most GCP lesions were hypo-attenuated on unenhanced CT (n = 8), in arterial phase (AP) (n = 17) and venous phase (VP) (n = 11). Fifteen patients had the peak enhancement in VP and two in AP. The rim-like enhancement with central low attenuation was clearly observed in thirteen patients. For the GCP accompanied by adenocarcinoma, the enhancement peak was present in AP and the gradual expansion of enhancement area was in VP. All patients underwent surgical or endoscopic resection. Sixteen cases had remission of symptoms and no recurrence.

Conclusions

The careful analysis of CT features and clinical characteristics can provide support for deepening the understanding of the GCP. However, a more accurate diagnosis depends on histopathological features.

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.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021

There exist differences in the epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selections between gastric cancer patients from the Eastern and Western countries. The Chinese Society of Clinical Oncology (CSCO) has organized a panel of senior experts specializing in all sub-specialties of gastric cancer to compile a clinical guideline for the diagnosis and treatment of gastric cancer since 2016 and renews it annually. Taking into account regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted expert consensus judgment on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes in China. The 2021 CSCO Clinical Practice Guidelines for Gastric Cancer covers the diagnosis, treatment, follow-up, and screening of gastric cancer. Based on the 2020 version of the CSCO Chinese Gastric Cancer guidelines, this updated guideline integrates the results of major clinical studies from China and overseas for the past year, focused on the inclusion of research data from the Chinese population for more personalized and clinically relevant recommendations. For the comprehensive treatment of non-metastatic gastric cancer, attentions were paid to neoadjuvant treatment. The value of perioperative chemotherapy is gradually becoming clearer and its recommendation level has been updated. For the comprehensive treatment of metastatic gastric cancer, recommendations for immunotherapy were included, and immune checkpoint inhibitors from third-line to the first-line of treatment for different patient groups with detailed notes are provided.

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer-a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Background

To predict response to neoadjuvant chemotherapy (NAC) of gastric cancer (GC), prior to surgery, would be pivotal to customize patient treatment. The aim of this study is to investigate the reliability of computed tomography (CT) texture analysis (TA) in predicting the histo-pathological response to NAC in patients with resectable locally advanced gastric cancer (AGC).

Methods

Seventy (40 male, mean age 63.3 years) patients with resectable locally AGC, treated with NAC and radical surgery, were included in this retrospective study from 5 centers of the Italian Research Group for Gastric Cancer (GIRCG). Population was divided into two groups: 29 patients from one center (internal cohort for model development and internal validation) and 41 from other four centers (external cohort for independent external validation). Gross tumor volume (GTV) was segmented on each pre- and post-NAC multidetector CT (MDCT) image by using a dedicated software (RayStation), and 14 TA parameters were then extrapolated. Correlation between TA parameters and complete pathological response (tumor regression grade, TRG1), was initially investigated for the internal cohort. The univariate significant variables were tested on the external cohort and multivariate logistic analysis was performed.

Results

In multivariate logistic regression the only significant TA variable was delta gray-level co-occurrence matrix (GLCM) contrast (P=0.001, Nagelkerke R²: 0.546 for the internal cohort and P=0.014, Nagelkerke R²: 0.435 for the external cohort). Receiver operating characteristic (ROC) curves, generated from the logistic regression of all the patients, showed an area under the curve (AUC) of 0.763.

Conclusions

Post-NAC GLCM contrast and dissimilarity and delta GLCM contrast TA parameters seem to be reliable for identifying patients with locally AGC responder to NAC.

The Sensitivity Prediction of Neoadjuvant Chemotherapy for Gastric Cancer

The overall efficacy of neoadjuvant chemoradiotherapy (NACT) for locally advanced gastric cancer (LAGC) has been recognized. However, the response rate of NACT is limited due to tumor heterogeneity. For patients who are resistant to NACT, not only the operation timing will be postponed, patients will also suffer from the side effects of it. Thus, it is important to develop a comprehensive strategy and screen out patients who may be sensitive to NACT. This article summarizes the related research progress on the sensitivity prediction of NACT for GC in the following aspects: microRNAs, metabolic enzymes, exosomes, other biomarkers; inflammatory indicators, and imageological assessments. The results showed that there were many studies on biomarkers, but no unified conclusion has been drawn. The inflammatory indicators are related to the survival and prognosis of patients under NACT. For imageological assessments such as CT, MRI, and PET, with careful integration and optimization, they will have unique advantages in early screening for patients who are sensitive to NACT.

Dual-Energy CT-Based Nomogram for Decoding HER2 Status in Patients With Gastric Cancer

OBJECTIVE. The purpose of this study was to develop and evaluate a dual-energy CT (DECT)-based nomogram for noninvasive identification of the status of human epidermal growth factor receptor 2 (HER2; also known as ERBB2) expression in gastric cancer (GC). MATERIALS AND METHODS. A total of 206 patients with histologically proven GC who underwent pretreatment DECT were retrospectively recruited and randomly allocated to a training cohort (n = 144) or a test cohort (n = 62). Information on clinical characteristics, qualitative imaging features, and quantitative DECT parameters was collected. Univariate analysis and multivariate logistic regression were implemented to screen independent predictors of HER2 status. An individualized nomogram was built, and its discrimination, calibration, and clinical usefulness were assessed. RESULTS. Tumor location, the iodine concentration of the tumor in the venous phase, and the normalized iodine concentration of the tumor in the venous phase were significant factors predictive of HER2 status (all p < .05). After these three indicators were integrated, the proposed nomogram showed a favorable diagnostic performance, with AUCs of 0.807 (95% CI, 0.718-0.897) in the training cohort and 0.815 (95% CI, 0.661-0.968) in the test cohort. The nomogram showed a preferable fitting (all p > .05 by the Hosmer-Lemeshow test) and would offer more net benefits than simple default strategies within a wide range of threshold probabilities in both cohorts. CONCLUSION. The DECT-based nomogram has great application potential in terms of detecting HER2 status in GC, and can serve as a novel substitute for invasive testing.

Radiomics analysis of CT imaging for differentiating gastric neuroendocrine carcinomas from gastric adenocarcinomas

PURPOSE

To develop and evaluate a CT-based radiomics nomogram for differentiating gastric neuroendocrine carcinomas (NECs) from gastric adenocarcinomas (ADCs).

METHODS

CT images of 63 patients with gastric NECs were collected retrospectively, and 63 patients with gastric ADCs were selected as the control group. Univariate analysis was used to identify the significant factors of clinical characteristics and CT findings for differentiating gastric NECs from ADCs. Radiomics analysis was applied to CT images of unenhanced, arterial phase and venous phase, respectively. A radiomics nomogram incorporating the radiomics signature and the subjective CT findings was developed and its diagnostic ability was evaluated. The diagnostic performances of CT findings model, radiomics signature and radiomics nomogram were compared using DeLong test.

RESULTS

The tumor margin and lymph node (LN) metastasis were independent predictors for differentiating gastric NECs from ADCs. The radiomics signature based on venous phase presented superior AUC of 0.798 [95 % confidence interval (CI), 0.657-0.938] in validation cohort. The nomogram incorporated the radiomics signature, tumor margin and LN metastasis showed AUCs of 0.821 (95 %CI: 0.725-0.895) in the primary cohort and 0.809 (95 %CI: 0.649-0.918) in the validation cohort. Moreover, the radiomics nomogram showed good discrimination and calibration. The diagnostic performance of CT findings model was significantly lower than that of radiomics nomogram (p =  0.001) and radiomics signature (p = 0.025).

CONCLUSIONS

Radiomics analysis exhibited good performance in differentiating gastric NECs from ADCs, and the radiomics nomogram may have significant clinical implications on preoperative detection of gastric malignant tumors.

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.

Spectral CT in Lung Cancer: Usefulness of Iodine Concentration for Evaluation of Tumor Angiogenesis and Prognosis

OBJECTIVE. The purpose of this study was to investigate the correlation between iodine concentration (IC) derived from spectral CT and angiogenesis and the relationships between IC and clinical-pathologic features associated with lung cancer prognosis. SUBJECTS AND METHODS. Sixty patients with lung cancer were enrolled and underwent spectral CT. The IC, IC difference (ICD), and normalized IC (NIC) of tumors were measured in the arterial phase, venous phase (VP), and delayed phase. The microvessel densities (MVDs) of CD34-stained specimens were evaluated. Correlation analysis was performed for IC and MVD. The relationships between the IC index showing the best correlations with MVD and clinical-pathologic findings of pathologic types, histologic differentiation, tumor size, lymph node status, pathologic TNM stage, and intratumoral necrosis were investigated. RESULTS. The mean (± IQR) MVD of all tumors was 42.00 ± 27.50 vessels per field at ×400 magnification, with two MVD distribution types. The MVD of lung cancer correlated positively with the IC, ICD, and NIC on three-phase contrast-enhanced scanning (r range, 0.581-0.800; all p < 0.001), and the IC in the VP showed the strongest correlation with MVD (r = 0.800; p < 0.001). The correlations between IC and MVD, ICD and MVD, and NIC and MVD varied depending on whether the same scanning phase or same IC index was used. The IC in the VP showed statistically significant differences in the pathologic types of adenocarcinoma and squamous cell carcinoma, histologic differentiation, tumor size, and status of intratumoral necrosis of lung cancer (p < 0.05), but was not associated with nodal metastasis and pathologic TNM stages (p > 0.05). CONCLUSION. IC indexes derived from spectral CT, especially the IC in the VP, were useful indicators for evaluating tumor angiogenesis and prognosis.

The Correlation Between Computed Tomography Volumetry and Prognosis of Advanced Gastric Cancer Treated with Neoadjuvant Chemotherapy

Purpose

To investigate the feasibility and utility of computer tomography (CT) volumetry in evaluating the tumor response to neoadjuvant chemotherapy (NAC) in advanced gastric cancer (AGC) patients.

Patients and Methods

One hundred and seventeen Patients with AGC who received NAC followed by R0 resection between January 2006 and December 2012 were included. Tumor volumes were quantified using OsiriX software. The volume reduction rate (VRR) was calculated as follows: VRR = [(pre-chemotherapy total volume) − (post-chemotherapy total volume)]/(pre-chemotherapy total volume) × 100%. The optimal cut-off VRR for differentiating favorable from unfavorable prognosis was determined by receiver operating characteristic (ROC) analysis. Overall survival was calculated using Kaplan-Meier analysis and values were compared using the Log-rank test. Multivariate analysis was determined by the Cox proportional regression model.

Results

The optimal cut-off VRR was 31.95% according to ROC analysis, with a sensitivity of 70.4% and a specificity of 71.7%. Based on the cut-off VRR, patients were divided into the VRR-High (VRR ≥ 31.95%, n = 63) and VRR-Low (VRR < 31.95%, n = 54) groups. The VRR-Low group exhibited a worse prognosis than that of the VRR-High group (HR, 2.85; 95% CI, 1.69–4.82, P < 0.001), with 3-year survival rates of 40.7% and 79.4%, and 5-year survival rates of 31.5% and 63.5%, respectively.

Conclusion

CT volumetry is a feasible and reliable method for assessing the tumor response to NAC in patients with AGC.

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.

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.

The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of gastric cancer

China is one of the countries with the highest incidence of gastric cancer. There are differences in epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selection between gastric cancer patients from the Eastern and Western countries. Non-Chinese guidelines cannot specifically reflect the diagnosis and treatment characteristics for the Chinese gastric cancer patients. The Chinese Society of Clinical Oncology (CSCO) arranged for a panel of senior experts specializing in all sub-specialties of gastric cancer to compile, discuss, and revise the guidelines on the diagnosis and treatment of gastric cancer based on the findings of evidence-based medicine in China and abroad. By referring to the opinions of industry experts, taking into account of regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted experts' consensus judgement on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes. This guideline uses tables and is complemented by explanatory and descriptive notes covering the diagnosis, comprehensive treatment, and follow-up visits for gastric cancer.

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

Background

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

Methods

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

Results

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

Conclusion

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

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.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Effect of the degree of gastric filling on the measured thickness of advanced gastric cancer by computed tomography

Imaging of gastric cancer thickness is closely associated with the depth of tumor invasion, which provides guidance for clinical staging and assists the evaluation of the effects of adjuvant therapy. However, it is unclear whether the measurement of thickness is affected by the degree of gastric filling, and its accuracy and reliability are under-reported. The present study aimed to investigate the influence of the degree of gastric filling on the measurement of gastric cancer thickness. A total of 38 patients with advanced gastric cancer who underwent enhanced abdominal computed tomography (CT) scanning at the Department of CT and MR in The Fourth Hospital of Hebei Medical University (Shijiazhuang, China) between July and September 2016 were recruited, consisting of 21 newly diagnosed cases and 17 follow-up cases following non-surgical treatments. Plain scanning (prior to filling) and enhanced scanning in venous phase (following filling) were performed. Axial CT images prior to and following filling of the normal part of gastric wall and the lesions were compared. The same procedure was repeated on these participants 1 month later by the same radiologist, and the results were compared with those obtained previously. Normal gastric wall thickness prior to and following gastric filling was significantly different (all P<0.001) with the most substantial changes observed at the greater curvature. Lesion thickness prior to and following filling was similar in newly diagnosed patients, but significantly different in patients for re-examination (P<0.05). The two thickness measurements in the same patients were consistent. The measured thickness of gastric cancer in newly diagnosed patients was relatively stable, and could be used as an indicator in baseline CT examination. Maintaining a similar degree of gastric filling during re-examination could aid the accurate evaluation of treatment efficacy.

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.

Histopathological factors predicting response to neoadjuvant therapy in gastric carcinoma

BACKGROUND

Neoadjuvant therapy (NAT) is a useful therapeutic option. However, some patients respond poorly to it and can even show tumor progression. It is important to define factors that can predict response to NAT.

MATERIALS AND METHODS

This is a retrospective cohort study to define histopathological factors predicting response to NAT in gastric tubular carcinoma. This study has enrolled 80 patients receiving chemotherapy for locally advanced gastric carcinoma.

RESULTS

44.5% of the patients were men; mean age was 64.49 years. Only 5.7% of the patients showed a complete response to therapy, 10% had grade 1, 21.4% grade 2, and 62.9% grade 3 regression. On follow-up, 43.8% of the patients showed recurrence of disease (57.1% distant metastasis) and 33.8% eventually died of it. We found a statistically significant association between response and prognosis. We found a statistically significant association between regression and perineural, vascular, and lymph vessel invasion. Logistic regression model showed that only lymph vessel invasion had independent influence. Lymph vessel invasion not only indicated lack of response to therapy, but also higher incidence of lymph node involvement in the gastrectomy specimen.

DISCUSSION

Our study indicates that the presence of vascular or perineural invasion in the endoscopic biopsies and high histopathological grade predict poor response to therapy. This seems peculiar, for undifferentiated tumors are supposed to have better response to therapy.

CONCLUSION

Our study indicates that undifferentiated tumors respond worse to therapy. Furthermore, studies are necessary to define lack of response, to help avoid neoadjuvant therapy in unfavorable cases.

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.

Contrast-enhanced MDCT in patients with pancreatic neuroendocrine tumours: correlation with histological findings and diagnostic performance in differentiation between tumour grades

AIM

To identify the multidetector computed tomography (MDCT) features of pancreatic neuroendocrine tumours (pNETs), which correlate with tumour histology and enable preoperative grading.

MATERIALS AND METHODS

Thirty-nine patients with histologically confirmed pNET who underwent preoperative contrast-enhanced MDCT were included in this study. Nineteen tumours were classified as Grade 1 (G1) and 20 as Grade 2 (G2). Histopathology slides were reviewed to assess the intratumoural microvascular density (MVD) and the amount of tumour stroma. Computed tomography (CT) image analysis included tumour size, margin delineation, calcifications, homogeneity, contrast enhancement (CE) pattern, tumour absolute and relative enhancement, presence of cystic changes, pancreatic duct dilatation, regional and distant metastases. The diagnostic ability to predict tumour grade was measured for each MDCT finding and their combinations.

RESULTS

The mean arterial enhancement ratio had a mean±standard deviation of 1.53±0.45 in G1 and 1.01±0.33 in G2 pNETs (p=0.0003) and correlated with intratumoural microvascular density (MVD; r=0.55, p=0.0002). Tissue stroma percentage did not correlate with imaging findings. Late CE of the tumour (the peak attenuation observed in the venous phase) was significantly associated with G2. Tumour size >20 mm, arterial enhancement ratio <1.1, and late CE showed 74.4%, 79.5%, and 74.4% accuracy, respectively, in diagnosing G2 tumours, while the accuracy of at least two of these criteria used in combination was 82%. Based on these results, a diagnostic algorithm was proposed, which showed high interobserver agreement (k=0.82) in the prediction of tumour grade.

CONCLUSION

Contrast-enhanced MDCT features correlate with histological findings and enable the differentiation between G1 and G2 pNETs during preoperative examination.

CT spectral imaging for monitoring the therapeutic efficacy of VEGF receptor kinase inhibitor AG-013736 in rabbit VX2 liver tumours

PURPOSE

The aim of this study was to evaluate the value of computed tomography (CT) spectral imaging in assessing the therapeutic efficacy of a vascular endothelial growth factor (VEGF) receptor inhibitor AG-013736 in rabbit VX2 liver tumours.

METHODS

Twenty-three VX2 liver tumour-bearing rabbits were scanned with CT in spectral imaging mode during the arterial phase (AP) and portal phase (PP). The iodine concentrations(ICs)of tumours normalized to aorta (nICs) at different time points (baseline, 2, 4, 7, 10, and 14 days after treatment) were compared within the treated group (n = 17) as well as between the control (n = 6) and treated groups. Correlations between the tumour size, necrotic fraction (NF), microvessel density (MVD), and nICs were analysed.

RESULTS

The change of nICs relative to baseline in the treated group was lower compared to the control group. A greater decrease in the nIC of a tumour at 2 days was positively correlated with a smaller increase in tumour size at 14 days (P < 0.05 for both). The tumour nIC values in AP and PP had correlations with MVD (r = 0.71 and 0.52) and NF (r = -0.54 and -0.51) (P < 0.05 for all).

CONCLUSIONS

CT spectral imaging allows for the evaluation and early prediction of tumour response to AG-013736.

KEY POINTS

• AG-013736 treatment response was evaluated by CT in a rabbit tumour model. • CT spectral imaging allows for the early treatment monitoring of targeted anti-tumour therapies. • Spectral CT findings correlated with vascular changes after anti-tumour therapies. • Spectral CT is a promising method for assessing clinical treatment response.