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

Dual-energy CT for predicting progression-free survival of locally advanced gastric cancer after gastrectomy: Insights into tumor angiogenesis

OBJECTIVES

To investigate preoperative dual-energy CT (DECT)-derived independent risk factors affecting progression-free survival (PFS) in patients with locally advanced gastric cancer (LAGC) undergoing gastrectomy, and to reveal the underlying histopathologic changes.

METHODS

This prospective study included patients who underwent preoperative DECT scan and gastrectomy. Clinical data, DECT-derived morphological characteristics and iodine-related parameters were comprehensively collected. Univariate and multivariate analyses were carried out to identify independent risk factors associated with PFS. The prognostic performance of various parameters was evaluated using the bootstrap-based consistency index (C-index) and time-dependent receiver operating characteristic (ROC) analysis. Kaplan-Meier curves were used to assess the differences in survival analysis. The histopathologic underpinnings of the DECT-based combined parameter for evaluating PFS were explored.

RESULTS

120 LAGC patients (63.3 ± 10.9 years; 94 men) were analyzed. Age, arterial enhancement fraction (AEF), serosal invasion, and tumor thickness were identified as preoperative independent risk factors affecting PFS (all p < 0.05). The combined parameters based on these risk factors achieved a C-index of 0.75, significantly or slightly superior to that of any single risk factor (all p < 0.05) or postoperative pathological staging (C-index, 0.67; p > 0.05). For predicting the 0.5-, 1- and 2-year PFS, the combined parameter had an area-under-the-curve (AUC) of 0.72, 0.77, and 0.74, respectively. PFS significantly differed between patients of high- and low-risks assessed with the combined parameter (p < 0.001). Histopathologically, the combined parameter was associated with tumor microvessel density (r = 0.31, p < 0.001).

CONCLUSION

The combination of DECT-derived morphological characteristics, iodine-related parameters, and clinical data helped accurately stratify PFS in LAGC before surgery and is associated with tumor angiogenesis.

CLINICAL RELEVANCE STATEMENT

Dual-energy CT was promising in the preoperative evaluation of the progression-free survival in LAGC patients after gastrectomy.

The clinical applications of dual-layer spectral detector CT in digestive system diseases

OBJECTIVE

Dual-layer spectral detector CT (DLCT) has several advantages in clinical practice, this study aims to reveal the clinical applications of DLCT in digestive system diseases.

MATERIALS AND METHODS

We searched PubMed and Cochrane Reviews for articles published from January 1, 2010 to May 31, 2024, using the terms "dual-layer spectral detector CT" or "dual-layer CT" combined with "hepatic fat" or "hepatic fibrosis" "hepatocellular carcinoma" or "pancreatic ductal adenocarcinoma" or "pancreatic neuroendocrine tumors" or "gastric cancer" or "colorectal cancer" or "Crohn's disease" or "bowel ischemia" or "acute abdominal conditions".

RESULTS

DLCT consists of a top layer sensitive to lower-energy photons and a bottom layer sensitive to higher-energy photons. This configuration enables simultaneous acquisition of two energy spectra from a single X-ray beam ensuring consistent spatial alignment and temporal resolution. Spectral raw images allow image post-processing to improve image quality, reduce radiation doses and contrast media doses, and generate multiple quantitative parameters. It has broad potential for early detection, accurate staging, efficacy assessment, and prognosis prediction of liver, pancreatic, and gastrointestinal diseases, as well as for the assessment of digestive system vasculature.

CONCLUSIONS

DLCT not only provides valuable information for the clinical diagnosis and therapeutic effect evaluation of digestive system diseases but also may play a more important role in the overall management of digestive diseases and in the decision-making of individualized medicine.

KEY POINTS

Question What are the advantages of DLCT compared to traditional single-energy CT in the early detection, staging, and therapeutic evaluation of digestive system diseases? Findings DLCT enhances image quality, improves tissue characterization, and allows for multi-parametric analysis, making it superior in detecting and evaluating liver, pancreatic, and gastrointestinal diseases. Clinical relevance DLCT provides high-quality, multi-parametric imaging that improves the accuracy of diagnosing digestive diseases, facilitates more precise treatment planning, and enhances monitoring of treatment response, ultimately contributing to better patient management and prognosis.

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.

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

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

Differentiating gastric schwannoma from gastric stromal tumor (≤5 cm) by histogram analysis based on iodine-based material decomposition images: a preliminary study

Objective

This study aims to investigate the value of histogram analysis based on iodine-based material decomposition (IMD) images obtained through dual-energy computed tomography (DECT) to differentiate gastric schwannoma (GS) from gastric stromal tumor (GST) (≤5 cm) preoperatively.

Methods

From January 2015 to January 2023, 15 patients with GS and 30 patients with GST (≤5 cm) who underwent biphasic contrast-enhanced scans using DECT were enrolled in this study. For each tumor, we reconstructed IMD images at the arterial phase (AP) and venous phase (VP). Nine histogram parameters were automatically extracted and selected using MaZda software based on the IMD of AP and VP, respectively, including mean, 1st, 10th, 50th, 90th, and 99th percentile of the iodine concentration value (Perc.01, Perc.10, Perc.50, Perc.90, and Perc.99), variance, skewness, and kurtosis. The extracted IMD histogram parameters were compared using the Mann-Whitney U-test. The optimal IMD histogram parameters were selected using receiver operating characteristic (ROC) curves.

Results

Among the IMD histogram parameters of AP, the mean, Perc.50, Perc.90, Perc.99, variance, and skewness of the GS group were lower than that of the GST group (all P < 0.05). Among the IMD histogram parameters of VP, Perc.90, Perc.99, and the variance of the GS group was lower than those of the GST group (all P < 0.05). The ROC analysis showed that Perc.99 (AP) generated the best diagnostic performance with the area under the curve, sensitivity, and specificity being 0.960, 86.67%, and 93.33%, respectively, when using 71.00 as the optimal threshold.

Conclusion

Histogram analysis based on IMD images obtained through DECT holds promise as a valuable tool for the preoperative distinction between GS and GST (≤5 cm).