Gastric cancer with synchronous and metachronous hepatic metastasis predicted by enhancement pattern on multiphasic contrast-enhanced CT

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.

Genomic biology and therapeutic strategies of liver metastasis from gastric cancer

The liver is a frequent site of metastasis in advanced gastric cancer (GC). Despite significant advancements in diagnostic and therapeutic techniques, the overall survival rate for patients afflicted with gastric cancer liver metastasis (GCLM) remains dismally low. Precision oncology has made significant progress in identifying therapeutic targets and enhancing our understanding of metastasis mechanisms through genome sequencing and molecular characterization. Therefore, it is crucial to have a comprehensive understanding of the various molecular processes involved in GCLM and the fundamental principles of systemic therapy to develop new treatment approaches. This paper aims to review recent findings on the diagnosis, potential biomarkers, and therapies targeting the multiple molecular processes of GCLM, with the goal of improving treatment strategies for patients with GCLM.

Criteria for assessing the diagnostic significance of modern methods of imaging gastrointestinal diseases in practical gastroenterology

Imaging methods are frequently used to diagnose gastrointestinal diseases and play a crucial role in verifying clinical diagnoses among all diagnostic algorithms. However, these methods have limitations, challenges, benefits, and advantages. Addressing these limitations requires the application of objective criteria to assess the effectiveness of each diagnostic method. The diagnostic process is dynamic and requires a consistent algorithm, progressing from clinical subjective data, such as patient history (anamnesis), and objective findings to diagnostics ex juvantibus. Caution must be exercised when interpreting diagnostic results, and there is an urgent need for better diagnostic tests. In the absence of such tests, preliminary criteria and a diagnosis ex juvantibus must be relied upon. Diagnostic imaging methods are critical stages in the diagnostic workflow, with sensitivity, specificity, and accuracy serving as the primary criteria for evaluating clinical, laboratory, and instrumental symptoms. A comprehensive evaluation of all available diagnostic data guarantees an accurate diagnosis. The “gold standard” for diagnosis is typically established through either the results of a pathological autopsy or a lifetime diagnosis resulting from a thorough examination using all diagnostic methods.

Enhancement Patterns in Differentiated and Undifferentiated Gastric Carcinoma: Multiphasic Contrast-Enhanced Computed Tomography Versus Histopathology

Background Gastric adenocarcinoma (GCA) poses a significant global health burden due to its prevalence and high morbidity and mortality rates. GCA is classified into three main histological types: well-differentiated (intestinal type), poorly differentiated (diffuse type), and mixed or indeterminate forms. These types vary in causes, epidemiology, and genetics, with the diffuse type often associated with the worst prognosis. Endoscopic biopsy is the primary method for characterization, but it has its limitations. There is potential in using contrast-enhanced computed tomography (CT) to differentiate between histological subtypes of gastric adenocarcinoma, which could aid subtype differentiation. Building on this, our study aims to assess CT's effectiveness in distinguishing between broad histological groups of gastric adenocarcinoma based on enhancement patterns, contributing to improved diagnostic accuracy Objective Our research focuses on evaluating the effectiveness of multiphasic contrast-enhanced computed tomography (CECT) in distinguishing between the three broad histopathological subtypes of gastrointestinal cancers. Methods This study was a prospective, analytical observational study that was approved and carried out in our institutional tertiary care hospital. Consecutive individuals who had undergone endoscopic-guided biopsy and demonstrated histological evidence of GCA were taken into consideration for participation in the study. In order to complete the clinical staging process, further multiphasic CT scans were carried out on each of the fifty patients and were categorised accordingly based on the findings of histopathology. Results In the differentiated type, segmental distribution was: 5.5% upper segment, 16.7% middle segment, 66.7% lower segment, and 11.1% diffuse type. Esophageal involvement was 5.6%, duodenal involvement was similar, and lymph node involvement was approximately 38.8%. TNM staging: 38.8% IIIB, 22.2% III, 27.8% IVA, and 11.1% IVB. In the undifferentiated type, segmental distribution: 6.2% upper segment, 31.2% middle segment, 50.0% lower segment, and 12.5% diffuse type. Esophageal involvement was around 6.25%, duodenal involvement was 18.75%, and lymph node involvement was about 71.8%. TNM staging: 34.4% IIIB, 21.8% III, 28.1% IVA, and 15.6% IVB. Conclusion Multiphasic CT evaluations provide valuable insights into the prognostic aspects of gastric carcinomas by assessing peak enhancement. Differentiated tumors typically exhibit arterial phase enhancement, while undifferentiated tumors show venous phase enhancement, reflecting their microvascular architecture. Recent studies emphasize the importance of understanding gastric carcinoma characteristics for diagnosis and prognosis. Our research aligns with this, revealing distinct contrast enhancement patterns between differentiated and undifferentiated types. However, discrepancies in histological classifications and contrast enhancement patterns across studies warrant further investigation. Integrating histopathological and radiological insights is essential for accurate diagnosis and treatment planning.

Clinical impact of very early recurrence after conversion surgery for stage IV gastric cancer

Background

The development and improved response to chemotherapy has resulted in a survival benefit of conversion surgery (CS) for advanced gastric cancer (GC). However, this benefit is limited in some cases, such as in those with very early recurrence (VER). This study investigated the relationship between outcome and clinicopathological characteristics after CS for stage IV GC, and the risk factors for VER after CS.

Methods

We retrospectively studied 184 patients with stage IV GC who initially underwent chemotherapy, including 36 patients who underwent CS between May 2007 and January 2022. We evaluated the long-term outcome after CS for stage IV GC and the clinicopathological characteristics of the patients who underwent CS.

Results

Median survival times (MSTs) in the chemotherapy alone and CS groups were 13.4 and 36.5 months, respectively (p < 0.0001). Of the 27 patients who underwent R0 resection, 22 remained free of early recurrence and five experienced VER. MSTs in the VER and free of early recurrence groups were 15.2 and 44.1 months, respectively (p < 0.0001). Significantly more patients had liver metastasis before initial treatment in the VER group than in the FER group (p = 0.016). There were more patients with preoperative PNI <40 in the VER group (p = 0.046).

Conclusion

CS is an effective treatment for stage IV GC, but VER is associated with poor prognosis. We need to carefully consider the indications for CS, especially for patients with poor nutritional status and liver metastases.

Efficacy Evaluation of 64-Slice Spiral Computed Tomography Images in Laparoscopic-Assisted Distal Gastrectomy for Gastric Cancer under the Reconstruction Algorithm

This study was aimed to analyze the application value of the filtered back-projection (FBP) reconstruction algorithm of computed tomography (CT) images in laparoscopic-assisted distal gastrectomy. In this study, 56 patients with gastric cancer were selected as research subjects and randomly divided into the control group (CT-guided laparoscopic radical gastrectomy) and the observation group (CT-guided laparoscopic radical gastrectomy with the FBP reconstruction algorithm), with 28 patients in each group. Fourier transform and iterative reconstruction were introduced for comparison, and finally, the postoperative curative effect and adverse events were compared between the two groups. The results showed that the CT image quality score processed by the FBP reconstruction algorithm (4.31 ± 0.31) was significantly higher than that of the iterative reconstruction method (3.5 ± 0.29) and the Fourier transform method (3.97 ± 0.38) (P < 0.05). The incidences of postoperative wound infection and gastric motility disorder (5.88% and 8.16%, respectively) in the observation group were significantly lower than those in the control group (8.21% and 10.82%, respectively) (P < 0.05). The levels of serum interleukin-6 (IL-6) (280.35 ± 15.08 ng/L) and tumor necrosis factor-α (TNF-α) (144.32 ± 10.32 ng/L) in the observation group after the treatment were significantly lower than those in the control group, which were 399.71 ± 14.19 ng/L and 165.33 ± 10.08 ng/L, respectively (P < 0.05). In conclusion, the FBP reconstruction algorithm was better than other algorithms in the processing of gastric cancer CT images. The FBP reconstruction algorithm showed a good reconstruction effect on CT images of gastric cancer; CT images based on this algorithm helped to formulate targeted surgical treatment plans for gastric cancer, showing a high clinical application value.

Segmentation of Gastric Computerized Tomography Images under Intelligent Algorithms in Evaluation of Efficacy of Decitabine Combined with Paclitaxel in Treatment of Gastric Cancer

To analyze the evaluation of artificial intelligence algorithm combined with gastric computed tomography (CT) image in clinical chemotherapy for advanced gastric cancer, 112 patients with advanced gastric cancer were selected as the research object. Among which, 56 patients in the experimental group received paclitaxel (PTX) combined with decitabine sequential decitabine maintenance therapy. Fifty-six patients in the control group received first-line treatment with decitabine combined with cisplatin. The image segmentation algorithm based on fast interactive dictionary selection was used to process gastric CT images. Complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), response rate (RR), disease control rate (DCR), and overall survival (OS) after treatment were recorded. The true-positive rate (TPR) and coincidence ratio (CR) of the proposed algorithm for image segmentation were significantly higher than those of the mean shift algorithm and the iCoseg algorithm. The mean edge distance (MED) and edge distance variance (EDV) were significantly lower than the mean shift algorithm and the iCoseg algorithm, and the differences were considerable (P < 0.05). The number of CR (5 cases), PR (13 cases), RR (18 cases), and DCR (44 cases) in the experimental group was significantly higher than that in the control group, while the number of PD (12 cases) was significantly lower than that in the control group (P < 0.05). The number of patients complicated with hematological toxicity, leucopenia, thrombocytopenia, and digestive tract reaction in the experimental group was less than that in the control group (P < 0.05). From the comparison of long-term efficacy, the survival rate of patients in both groups showed a decreasing trend within 24 months, but the decreasing trend of survival rate of patients in the experimental group was better than that in the control group. In short, the proposed algorithm had better segmentation performance than traditional algorithms. Compared with first-line treatment with decitabine and cisplatin, PTX in combination with decitabine sequential citabine maintenance regimens had better disease control rates, lower toxicity, and more effective improvements in patient quality of life and longer survival in patients with advanced gastric cancer.

Gastric poorly cohesive carcinoma: differentiation from tubular adenocarcinoma using nomograms based on CT findings in the 40 s late arterial phase

OBJECTIVES

To summarise the CT findings of gastric poorly cohesive carcinoma (PCC) in the 40 s late arterial phase and differentiate it from tubular adenocarcinoma (TAC) using an integrative nomogram.

METHODS

A total of 241 patients including 59 PCCs, 109 TACs, and 73 other type gastric cancers were enrolled. Thirteen CT morphological characteristics of each lesion in the late arterial phase were evaluated. In addition, CT value-related parameters were extracted from ROIs encompassing the area of greatest enhancement on four-phase CT images. Nomograms based on regression models were built to discriminate PCCs from TACs and from non-PCCs. ROC curve analysis was performed to assess the diagnostic efficiency.

RESULTS

Six morphological characteristics, 10 CT value-related parameters, and the enhanced curve types differed significantly among the above three groups in the primary cohort (all p < 0.05). The paired comparison revealed that 10 CT value-related parameters differed significantly between PCCs and TACs (all p < 0.05). The AUC of the nomogram based on the multivariate model for discriminating PCCs from TACs was 0.954, which was confirmed in the validation cohort (AUC = 0.895). The AUC of another nomogram for discriminating PCCs from non-PCCs was 0.938, which was confirmed in the validation cohort (AUC = 0.880).

CONCLUSIONS

In the 40 s late arterial phase, the morphological characteristics and CT value-related parameters were significantly different among PCCs, TACs, and other types. PCCs were prone to manifest mucosal line interruption, diffuse thickening, infiltrative growth, and slow-rising enhanced curve (Type A). Furthermore, multivariate models were useful in discriminating PCCs from TACs and other types.

KEY POINTS

• Multiple morphological characteristics and CT value-related parameters differed significantly between gastric PCCs and TACs in the 40 s late arterial phase. • The nomogram integrating morphological characteristics and CT value-related parameters in the 40 s late arterial phase had favourable performance in discriminating PCCs from TACs. • More useful information can be derived from 40 s late arterial phase CT images; thus, a more accurate evaluation can be made in clinical practice.

A Population-Based Analysis of Distant Metastasis in Stage IV Gastric Cancer

BACKGROUND Distant metastasis (DM) is a crucial problem in management of patients with gastric cancer. Identification of the risk factors for development of DM and the prognostic factors for patients with DM is essential in development of individualized treatment of patients at the advanced stage with specific metastasis. MATERIAL AND METHODS Records of patients with gastric cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Survival duration of patients with specific DM was estimated, and the prognostic factors were investigated using the Cox proportional hazard regression model. The logistic regression model was used to reveal the inherent risk factors for development of DM. RESULTS Eventually, 32.6% (11,918 out of 36,588) of gastric cancer patients were diagnosed with DM between 2010 and 2015, among whom 5,361, 1,778, 1,495, and 231 patients were diagnosed with liver, lung, bone, and brain metastasis, respectively. The median overall survival for patients with DM was 5.0 (95% CI: 4.8-5.2) months, with a 5-year survival rate of 3.9%. Primary tumor site, histology types, tumor grade, T stage, N stage, surgery, chemotherapy, and the number of metastases were associated with worse survival. Younger age and higher tumor grade were positively associated with the development of DM. CONCLUSIONS Initial DM was found in 32.6% of patients with gastric cancer. Homogenous and heterogenous predictive factors were identified for patients with a specific metastatic site, which can be used in targeted screening and individualized treatment.