A systematic review and meta-analysis of the utility of EUS for preoperative staging for gastric cancer

Double contrast-enhanced ultrasonography improves diagnostic accuracy of T staging compared with multi-detector computed tomography in gastric cancer patients

BACKGROUND

Gastric cancer (GC) is the most common malignant tumor and ranks third for cancer-related deaths among the worldwide. The disease poses a serious public health problem in China, ranking fifth for incidence and third for mortality. Knowledge of the invasive depth of the tumor is vital to treatment decisions.

AIM

To evaluate the diagnostic performance of double contrast-enhanced ultrasonography (DCEUS) for preoperative T staging in patients with GC by comparing with multi-detector computed tomography (MDCT).

METHODS

This single prospective study enrolled patients with GC confirmed by preoperative gastroscopy from July 2021 to March 2023. Patients underwent DCEUS, including ultrasonography (US) and intravenous contrast-enhanced ultrasonography (CEUS), and MDCT examinations for the assessment of preoperative T staging. Features of GC were identified on DCEUS and criteria developed to evaluate T staging according to the 8^th edition of AJCC cancer staging manual. The diagnostic performance of DCEUS was evaluated by comparing it with that of MDCT and surgical-pathological findings were considered as the gold standard.

RESULTS

A total of 229 patients with GC (80 T1, 33 T2, 59 T3 and 57 T4) were included. Overall accuracies were 86.9% for DCEUS and 61.1% for MDCT (P < 0.001). DCEUS was superior to MDCT for T1 (92.5% vs 70.0%, P < 0.001), T2 (72.7% vs 51.5%, P = 0.041), T3 (86.4% vs 45.8%, P < 0.001) and T4 (87.7% vs 70.2%, P = 0.022) staging of GC.

CONCLUSION

DCEUS improved the diagnostic accuracy of preoperative T staging in patients with GC compared with MDCT, and constitutes a promising imaging modality for preoperative evaluation of GC to aid individualized treatment decision-making.

A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer

BACKGROUND

We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) system for diagnosing the invasion depth of early gastric cancer (EGC), and we evaluated the performance of this system.

METHODS

A total of 8280 EUS images from 559 EGC cases were collected from 11 institutions. Within this dataset, 3451 images (285 cases) from one institution were used as a development dataset. The AI model consisted of segmentation and classification steps, followed by the CycleGAN method to bridge differences in EUS images captured by different equipment. AI model performance was evaluated using an internal validation dataset collected from the same institution as the development dataset (1726 images, 135 cases). External validation was conducted using images collected from the other 10 institutions (3103 images, 139 cases).

RESULTS

The area under the curve (AUC) of the AI model in the internal validation dataset was 0.870 (95% CI: 0.796-0.944). Regarding diagnostic performance, the accuracy/sensitivity/specificity values of the AI model, experts (n = 6), and nonexperts (n = 8) were 82.2/63.4/90.4%, 81.9/66.3/88.7%, and 68.3/60.9/71.5%, respectively. The AUC of the AI model in the external validation dataset was 0.815 (95% CI: 0.743-0.886). The accuracy/sensitivity/specificity values of the AI model (74.1/73.1/75.0%) and the real-time diagnoses of experts (75.5/79.1/72.2%) in the external validation dataset were comparable.

CONCLUSIONS

Our AI model demonstrated a diagnostic performance equivalent to that of experts.

Predictive nomogram for lymph node metastasis and survival in gastric cancer using contrast-enhanced computed tomography-based radiomics: a retrospective study

Background

Lymph node involvement significantly impacts the survival of gastric cancer patients and is a crucial factor in determining the appropriate treatment. This study aimed to evaluate the potential of enhanced computed tomography (CT)-based radiomics in predicting lymph node metastasis (LNM) and survival in patients with gastric cancer before surgery.

Methods

Retrospective analysis of clinical data from 192 patients diagnosed with gastric carcinoma was conducted. The patients were randomly divided into a training cohort (n = 128) and a validation cohort (n = 64). Radiomic features of CT images were extracted using the Pyradiomics software platform, and distinctive features were further selected using a Lasso Cox regression model. Features significantly associated with LNM were identified through univariate and multivariate analyses and combined with radiomic scores to create a nomogram model for predicting lymph node involvement before surgery. The predictive performance of radiomics features, CT-reported lymph node status, and the nomogram model for LNM were compared in the training and validation cohorts by plotting receiver operating characteristic (ROC) curves. High-risk and low-risk groups were identified in both cohorts based on the cut-off value of 0.582 within the radiomics evaluation scheme, and survival rates were compared.

Results

Seven radiomic features were identified and selected, and patients were stratified into high-risk and low-risk groups using a 0.582 cut-off radiomics score. Univariate and multivariate analyses revealed that radiomics features, diabetes mellitus, Nutrition Risk Screening (NRS) 2002 score, and CT-reported lymph node status were significant predictors of LNM in patients with gastric cancer. A predictive nomogram model was developed by combining these predictors with the radiomics score, which accurately predicted LNM in gastric cancer patients before surgery and outperformed other models in terms of accuracy and sensitivity. The AUC values for the training and validation cohorts were 0.82 and 0.722, respectively. The high-risk and low-risk groups in both the training and validation cohorts showed significant differences in survival rates.

Conclusion

The radiomics nomogram, based on contrast-enhanced computed tomography (CECT ), is a promising non-invasive tool for preoperatively predicting LNM in gastric cancer patients and postoperative survival.

Pre- and Post-treatment Double-Sequential-Point Dynamic Radiomic Model in the Response Prediction of Gastric Cancer to Neoadjuvant Chemotherapy: 3-Year Survival Analysis

BACKGROUND

Prognosis prediction of patients with gastric cancer after neoadjuvant chemotherapy is suboptimal. This study aims to develop and validate a dynamic radiomic model for prognosis prediction of patients with gastric cancer on the basis of baseline and posttreatment features.

PATIENTS AND METHODS

This single-center cohort study included patients with gastric adenocarcinoma treated with neoadjuvant chemotherapy from June 2009 to July 2015 in the Gastrointestinal Cancer Center of Peking University Cancer Hospital. Their clinicopathological data, pre-treatment and post-treatment computed tomography (CT) images, and pathological reports were retrieved and analyzed. Four prediction models were developed and validated using tenfold cross-validation, with death within 3 years as the outcome. Model discrimination was compared by the area under the curve (AUC). The final radiomic model was evaluated for calibration and clinical utility using Hosmer-Lemeshow tests and decision curve analysis.

RESULTS

The study included 205 patients with gastric adenocarcinoma [166 (81%) male; mean age 59.9 (SD 10.3) years], with 71 (34.6%) deaths occurring within 3 years. The radiomic model alone demonstrated better discrimination than the pathological T stage (ypT) stage model alone (cross-validated AUC 0.598 versus 0.516, P = 0.009). The final radiomic model, which incorporated both radiomic and clinicopathological characteristics, had a significantly higher cross-validated AUC (0.769) than the ypT stage model (0.516), the radiomics alone model (0.598), and the ypT plus other clinicopathological characteristics model (0.738; all P < 0.05). Decision curve analysis confirmed the clinical utility of the final radiomic model.

CONCLUSIONS

The developed radiomic model had good accuracy and could be used as a decision aid tool in clinical practice to differentiate prognosis of patients with gastric cancer.

[Fluorescence lymphoscopy with sentinel lymph node biopsy in research of lymphatic flow in early gastric cancer]

OBJECTIVE

To analyze the incidence and risk factors of regional lymph node metastatic lesions, as well as patterns of lymphatic drainage in early gastric cancer using indocyanine green (ICG).

MATERIAL AND METHODS

A prospective single-center non-randomized study included 67 patients with early gastric cancer between 2016 and 2019. All patients underwent endoscopic dissection or surgical resection with sentinel lymph node biopsy.

RESULTS

Regional lymph node metastatic lesions were detected in 12 (20.2%) out of 59 patients with examined lymph nodes. Of these, 11 out of 12 patients had sentinel lymph node lesion, and only 1 patient had metastasis outside this lymph node. The proposed technique for sentinel lymph node biopsy demonstrated high sensitivity, specificity and accuracy (93.2%, 100% and 98.3%, respectively). Risk factors for metastasis of early gastric cancer to regional lymph nodes were high grade adenocarcinoma (p=0.038) and tumor of anterior gastric wall (p=0.013). All patients with tumors of the upper third of the stomach had sentinel lymph node in the left gastric artery basin. Lymph flow was multidirectional in patients with tumors of the middle third of the stomach. In tumors of the lower third of the stomach, sentinel lymph node was located in the right gastroepiploic artery (50%) and left gastric artery basins (36.84%) (p=0.002). Sentinel lymph node was located in the left gastric artery basin in 84% of patients with tumors of the lesser curvature (p<0.001). Lymphatic drainage was multidirectional if tumors were localized on anterior and posterior walls, as well as on the greater curvature.

CONCLUSION

The proposed technique for sentinel lymph node biopsy demonstrated high sensitivity, specificity and accuracy (93.2%, 100% and 98.3%, respectively). ICG is valuable to identify the first lymph node in lymphatic drainage pathway in 83.6% of cases that makes it possible to assess the regional lymphatic collector. In addition, sentinel lymph node biopsy with ICG contributes to analysis of lymphatic drainage in early gastric cancer. The last one has both scientific and practical significance.

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.

Serum Interleukin 6 Level is Associated With Overall Survival and Treatment Response in Gastric and Gastroesophageal Junction Cancer

OBJECTIVE

To identify novel prognostic and predictive biomarkers for gastric and gastroesophageal junction (G+GEJ) adenocarcinoma.

BACKGROUND

There are few biomarkers to guide treatment for G+GEJ. The systemic inflammatory response of G+GEJ patients is associated with survival. In this study, we evaluated the relationship of circulating serum cytokine levels with overall survival (OS) and pathologic tumor regression grade (TRG) in G+GEJ patients.

PATIENTS AND METHODS

We queried the UT Southwestern gastric cancer biobank to identify consecutive patients diagnosed with G+GEJ from 2016 to 2022; these patients had pretreatment serum collected at diagnosis. For patients who received neoadjuvant therapy, an additional serum sample was collected immediately before surgical resection. An unbiased screen of 17 cytokines was measured in a discovery cohort. A multivariable Cox proportional hazards model was used to assess the association of cytokine concentration with OS. Findings were validated in additional patients. In patients who received neoadjuvant therapy, we assessed whether the change in interleukin 6 (IL-6) after therapy was associated with TRG.

RESULTS

Sixty-seven patients were included in the discovery cohort, and IL-6 was the only pretreatment cytokine associated with OS; this was validated in 134 other patients (hazard ratio: 1.012 per 1 pg/mL increase, 95% CI: 1.006-1.019, P = 0.0002). Patients in the top tercile of IL-6 level had worse median OS (10.6 months) compared with patients in the intermediate (17.4 months) and bottom tercile (35.8 months, P < 0.0001). Among patients who underwent neoadjuvant therapy (n = 50), an unchanged or decrease in IL-6 level from pretreatment to posttreatment, had a sensitivity and specificity of 80% for predicting complete or near-complete pathologic tumor regression (TRG 0-1).

CONCLUSIONS

Pretreatment serum level of IL-6 is a promising prognostic biomarker for G+GEJ patients. Comparing pre and post-neoadjuvant IL-6 levels may predict pathologic response to neoadjuvant therapy.

Early stage gastric adenocarcinoma: clinical and molecular landscapes

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

Hemostatic Radiotherapy for Gastric Cancer: MRI as an Alternative to Endoscopy for Post-Treatment Evaluation

INTRODUCTION

Pretreatment diagnosis by diffusion-weighted magnetic resonance imaging (DW-MRI) is useful to determine the effect of chemotherapy for gastric cancer. Here, we investigated the relationship among DW-MRI, endoscopy, and tumor markers.

PATIENTS

Eight patients underwent hemostatic radiotherapy (RT) for gastric cancer in this prospective study from 2019 to 2021. The patients completed MRI, endoscopy, and blood tests before RT; MRI, endoscopy, and blood tests 1 month after RT; and MRI and blood tests 3 months after RT. Correlations between changes in apparent diffusion coefficient (ADC) derived from DW-MRI and the tumor marker carcinoembryonic antigen (CEA) were investigated.

RESULTS

Univariate analysis of overall survival showed that sex and chemotherapy treatment were statistically significant factors. The CEA values before and 1 month after RT decreased significantly. There was no statistical difference between the CEA value 1 and 3 months after RT. The ADC value before and 1 month after RT increased significantly but not between 1 and 3 months after RT. Comparing the ratio of ADC before RT to 1 (or 3) month(s) after RT with that of CEA before RT to 1 (or 3) month(s) after RT, we found an inverse relationship between the two ratios.

CONCLUSIONS

Therefore, changes in ADC and CEA are correlated. Additionally, 3 months after RT, the decrease in ADC appeared earlier than the decrease in CEA. ADC may indicate a biological change earlier than CEA, and the ratios of ADC and CEA may be important factors. These aspects warrant further confirmation in a larger sample population.

Аre Multivisceral Resections for Gastric Cancer Acceptable: Experience from a High Volume Center and Extended Literature Review?

Introduction  Multivisceral resections (MVRs) in gastric cancer are potentially curable in selected patients in whom clear resection margins are possible. However, there are still uncertain data on their feasibility and safety considering short- and long-term results. The study compares survival, morbidity, mortality, and other secondary outcomes between standard and MVRs for gastric cancer. Materials and Methods  A monocentric retrospective study in patients with gastric adenocarcinoma, covering 2004 to 2020. Of the 336 operable cases, 101 patients underwent MVRs. The remaining 235 underwent standard gastric resections (SGRs), of which 173 patients were in stage T3/T4. To compare survival, a control group of 101 patients with palliative procedures was used-bypass anastomosis or exploration. Results  MVR had a lower survival rate than the SGR but significantly higher than the palliative procedures. The predominant gender in MVR was male (72.3%), with a mean age of 61 years. The perioperative mortality was 3.96% ( n  = 4), and the overall median survival was 28.1 months. The most frequently resected organs were the spleen (67.3%), followed by the pancreas (32.7%) and the liver (20.8%). In 56.4% of the cases two organs were resected, in 28.7% three organs, and in 13.9% four organs. The main complication was bleeding (9.9%). The major postoperative complications in the MVR were 14.85%, and in the SGR 6.4% ( p  < 0.05). Better long-term results were observed in patients who underwent R0 resections compared with R1. Conclusion  Multiorgan resections are characterized by poorer survival and a higher complication rate than gastrectomies. On the other hand, they have better long-term outcomes than palliative procedures. However, MVRs are admissible when performed by an experienced surgical team in high-volume centers.

Gastric cancer in 2022: Is there still a role for endoscopic ultrasound?

Gastric cancer (GC) represents the fourth leading cause of cancer death worldwide and many factors can influence its development (diet, geographic area, genetic, Helicobacter pylori or Epstein-Barr virus infections). High quality endoscopy represents the modality of choice for GC diagnosis. The correct morphologic classification during a high-resolution endoscopy is fundamental for oncologic diagnosis, staging and therapeutic decisions. Since its initial introduction in clinical practice the endoscopic ultrasound (EUS) has been considered a valuable tool for tumor (T-) and lymph nodes (N-) staging also in GC, in order to establish the best therapeutic strategy for the patient (e.g., upfront surgery vs neoadjuvant treatments). EUS tools as elastography, Doppler and contrast administration can improve diagnosis mainly in case of malignant lymph node evaluation. EUS has a marginal role in disease staging but has a fundamental role in case of a pre-endoscopic resection management and in the new era of endoscopic mucosal resection or submucosal dissection as minimally invasive surgery. Diagnosis and locoregional staging of GC with EUS are a method of inarguable value for the assessment of gastric wall involvement and presence of infiltrated paragastric lymph nodes. EUS can also have a role in disease restaging in those patients who have undergone neoadjuvant treatment. EUS can also have a role in the advanced phases of the disease, in facilitating palliative, minimally-invasive treatments, such as gastroenterostomy or biliary drainages. This review intends to discuss the modern role of EUS in GC topic.

Deep learning model for diagnosing early gastric cancer using preoperative computed tomography images

BACKGROUND

Early gastric cancer (EGC) is defined as a lesion restricted to the mucosa or submucosa, independent of size or evidence of regional lymph node metastases. Although computed tomography (CT) is the main technique for determining the stage of gastric cancer (GC), the accuracy of CT for determining tumor invasion of EGC was still unsatisfactory by radiologists. In this research, we attempted to construct an AI model to discriminate EGC in portal venous phase CT images.

METHODS

We retrospectively collected 658 GC patients from the first affiliated hospital of Nanchang university, and divided them into training and internal validation cohorts with a ratio of 8:2. As the external validation cohort, 93 GC patients were recruited from the second affiliated hospital of Soochow university. We developed several prediction models based on various convolutional neural networks, and compared their predictive performance.

RESULTS

The deep learning model based on the ResNet101 neural network represented sufficient discrimination of EGC. In two validation cohorts, the areas under the curves (AUCs) for the receiver operating characteristic (ROC) curves were 0.993 (95% CI: 0.984-1.000) and 0.968 (95% CI: 0.935-1.000), respectively, and the accuracy was 0.946 and 0.914. Additionally, the deep learning model can also differentiate between mucosa and submucosa tumors of EGC.

CONCLUSIONS

These results suggested that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.

Determinants of clinical outcomes of gastric cancer patients treated with neoadjuvant chemotherapy: a sub-analysis of the PRODIGY study

BACKGROUND

In this post hoc analysis of the PRODIGY study, we aimed to investigate factors associated with survival outcomes and provide evidence for designing optimal perioperative treatment strategies for gastric cancer patients receiving neoadjuvant chemotherapy.

PATIENTS AND METHODS

A total of 212 patients in the neoadjuvant chemotherapy group of the PRODIGY study were included as the study population. The prognostic impact of clinicopathologic factors, including the initial radiological clinical stage (cStage) and post-neoadjuvant chemotherapy pathological stage (ypStage), was analyzed.

RESULTS

The median age was 58 years. The majority of patients (77.4%) had cStage III disease, and about 10% and 25% had ypStage 0 and I disease, respectively. According to the initial cStage, progression-free survival (PFS) and overall survival (OS) were significantly different (P < 0.01). PFS and OS were also different according to the ypStage (P < 0.01). In multivariate analyses, cStage IIIC disease (vs. cStage II) and ypStage II and III disease (vs. ypStage 0/I) were independent factors for poor survival outcomes. Based on the patterns of PFS and OS according to both cStage and ypStage, three patient groups were defined. These groups showed distinct PFS and OS (P < 0.01) with 5-year PFS rates of 95.7%, 77.9%, and 31.3% and 5-year OS rates of 95.7%, 82.4%, and 42.5%, respectively.

CONCLUSIONS

Both initial cStage and ypStage were independent factors for survival outcomes of gastric cancer patients treated with neoadjuvant chemotherapy. Efforts should be made to develop optimal peri-operative treatment strategies for patients at different risks according to cStage and ypStage.

Clinical outcomes of gastroduodenal neuroendocrine tumors according to their WHO grade: A single-institutional retrospective analysis

The management of gastroduodenal neuroendocrine tumor (NET) has been controversial between radical surgical resection and local excision including endoscopic resection. A gastroduodenal NET grade (G), measured by their mitotic rate and Ki67 proliferation index, is important to predict prognosis. In this study, we aimed to compare the clinical outcomes of gastroduodenal NET according to grades in order to identify poor prognostic factors of gastroduodenal NETs. Fifty-four gastroduodenal NETs diagnosed between December 2008 and December 2020 in a tertiary referral hospital were retrospectively reviewed. The clinical outcomes of gastroduodenal NETs, according to tumor grades and factors associated with NET G2-3, were analyzed. A total of 52 gastroduodenal NET patients was enrolled. The mean follow-up period was 56.2 ± 40.1 months. The mean size of gastric and duodenal NET was 7.9 ± 11.0 mm and 9.8 ± 7.6 mm, respectively. During the study period, 72.7% (16/22) of gastric NETs and 83.3% (25/30) of duodenal NETS were G1. All G1 gastroduodenal NETs showed no lymph node or distant metastasis during the study periods. All G3 gastroduodenal NETs showed metastasis (one lymph node metastasis and 3 hepatic metastases). Among metastatic NETs, the smallest tumor size was a 13 mm gastric G3 NET. Factors associated with G2-3 NETs were larger tumor size, mucosal ulceration, proper muscle or deeper invasion, and lymphovascular invasion. A small-sized gastroduodenal NET confined to submucosa without surface ulceration may be suitable for endoscopic resection. After local resection of a gastroduodenal NET (G1) without lymphovascular and muscle proper invasion, follow-up examination without radical surgical resection can be recommended. G3 NETs may be treated by radical surgical resection, regardless of tumor size.

Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis

Objective

To evaluate the diagnostic performance of machine learning (ML) in predicting lymph node metastasis (LNM) in patients with gastric cancer (GC) and to identify predictors applicable to the models.

Methods

PubMed, EMBASE, Web of Science, and Cochrane Library were searched from inception to March 16, 2022. The pooled c-index and accuracy were used to assess the diagnostic accuracy. Subgroup analysis was performed based on ML types. Meta-analyses were performed using random-effect models. Risk of bias assessment was conducted using PROBAST tool.

Results

A total of 41 studies (56182 patients) were included, and 33 of the studies divided the participants into a training set and a test set, while the rest of the studies only had a training set. The c-index of ML for LNM prediction in training set and test set was 0.837 [95%CI (0.814, 0.859)] and 0.811 [95%CI (0.785-0.838)], respectively. The pooled accuracy was 0.781 [(95%CI (0.756-0.805)] in training set and 0.753 [95%CI (0.721-0.783)] in test set. Subgroup analysis for different ML algorithms and staging of GC showed no significant difference. In contrast, in the subgroup analysis for predictors, in the training set, the model that included radiomics had better accuracy than the model with only clinical predictors (F = 3.546, p = 0.037). Additionally, cancer size, depth of cancer invasion and histological differentiation were the three most commonly used features in models built for prediction.

Conclusion

ML has shown to be of excellent diagnostic performance in predicting the LNM of GC. One of the models covering radiomics and its ML algorithms showed good accuracy for the risk of LNM in GC. However, the results revealed some methodological limitations in the development process. Future studies should focus on refining and improving existing models to improve the accuracy of LNM prediction.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022320752

Computed Tomography-Based Deep Learning Nomogram Can Accurately Predict Lymph Node Metastasis in Gastric Cancer

BACKGROUND

Computed tomography is the most commonly used imaging modality for preoperative assessment of lymph node status, but the reported accuracy is unsatisfactory.

AIMS

To evaluate and verify the predictive performance of computed tomography deep learning on the presurgical evaluation of lymph node metastasis in patients with gastric cancer.

METHODS

347 patients were retrospectively selected (training cohort: 242, test cohort: 105). The enhanced computed tomography arterial phase images of gastric cancer were used for lesion segmentation, radiomics and deep learning feature extraction. Three methods were used for feature selection. Support vector machine (SVM) or random forest (RF) was used to build models. The classification performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC). We also established a nomogram that included clinical predictors.

RESULTS

The model based on ResNet50-RF showed favorable classification performance and was verified in the test cohort (AUC = 0.9803). The nomogram based on deep learning feature scores and the lymph node status reported by computed tomography showed excellent discrimination. AUC of 0.9978 was achieved in the training cohort and verified in the test cohort (AUC = 0.9914). Decision analysis curve showed the value of nomogram in clinical application.

CONCLUSION

The computed tomography-based deep learning nomogram can accurately and effectively evaluate lymph node metastasis in patients with gastric cancer before surgery.

Understanding the association between clinical staging accuracy, treatment response, and survival among gastric cancer patients through Bayesian analysis

BACKGROUND

Neoadjuvant therapy (NAT) improves survival among patients with locally advanced gastric cancer (GC), but it remains unclear whether its benefit is contingent on treatment response.

METHODS

This is a national cohort study of stage Ib-III GC patients in the National Cancer Data Base (2006-2015) treated with upfront resection or NAT followed by surgery. Bayesian analysis was used for NAT patients to ascertain staging concordance and to account for down-staging. We used multivariable Cox regression to evaluate the association between staging concordance, treatment, response to NAT, and survival.

RESULTS

The cohort included 13 340 patients treated at 1124 hospitals. Staging concordance ranged from 86.1% for cT3-4N+ to 34.7% for cT2N0 patients. Relative to accurately staged patients treated with upfront surgery, NAT was associated with a decreased risk of death if there was disease down-staging among those with cT1-2N+ (hazard ratio [HR]: 0.43 [0.30-0.61]), cT3-4N0 (HR: 0.69 [0.54-0.88]), and cT3-4N+ (HR: 0.51 [0.48-0.58]) tumors, and in the absence of down-staging among cT3-4N+ patients (HR: 0.83 [0.74-0.92]). Conversely, NAT without down-staging increased the risk of death among those with intermediate-stage disease.

CONCLUSIONS

NAT is associated with improved survival for GC, but it seems to be contingent on treatment response among patients with intermediate-stage disease.

Predictors of Metastatic Lymph Nodes at Preoperative Staging CT in Gastric Adenocarcinoma

Background. The aim of this study was to identify the most accurate computed-tomography (CT) dimensional criteria of loco-regional lymph nodes (LNs) for detecting nodal metastases in gastric cancer (GC) patients. Methods. Staging CTs of surgically resected GC were jointly reviewed by two radiologists, considering only loco-regional LNs with a long axis (LA) ≥ 5 mm. For each nodal group, the short axis (SA), volume and SA/LA ratio of the largest LN, the sum of the SAs of all LNs, and the mean of the SA/LA ratios were plotted in ROC curves, taking the presence/absence of metastases at histopathology for reference. On a per-patient basis, the sums of the SAs of all LNs, and the sums of the SAs, volumes, and SA/LA ratios of the largest LNs in all nodal groups were also plotted, taking the presence/absence of metastatic LNs in each patient for reference. Results. Four hundred and forty-three nodal groups were harvested during surgery from 107 patients with GC, and 173 (39.1%) were metastatic at histopathology. By nodal group, the sum of the SAs showed the best Area Under the Curve (AUC), with a sensitivity/specificity of 62.4/72.6% using Youden’s index with a >8 mm cutoff. In the per-patient analysis, the sum of the SAs of all LNs in the loco-regional nodal groups showed the best AUC with a sensitivity/specificity of 65.6%/83.7%, using Youden’s index with a >39 mm cutoff. Conclusion. In patients with GC, the sum of the SAs of all the LNs at staging CT is the best predictor among dimensional LNs criteria of both metastatic invasion of the nodal group and the presence of metastatic LNs.

Updated Evaluation of the Diagnostic Performance of Double Contrast-Enhanced Ultrasonography in the Preoperative T Staging of Gastric Cancer: A Meta-Analysis and Systematic Review

Objective

This study aimed to systematically evaluate the diagnostic performance of double contrast-enhanced ultrasonography (DCEUS) in the preoperative T staging of gastric cancer (GC).

Methods

Literature searches for eligible studies were performed using MEDLINE, EMBASE, and Cochrane Library. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver operating characteristic curve of DCEUS in the diagnosis of each T stage tumor were calculated. Meta-analyses were performed to obtain the pooled effects of risk ratio (RR) with 95% confidence interval (CI) in the comparison of DCEUS with CT/endoscopic ultrasound (EUS).

Results

A total of 8 studies including 1,232 patients were identified for inclusion in this meta-analysis. The pooled sensitivity and specificity were 0.78 (95% CI = 0.64–0.88) and 0.98 (95% CI = 0.96–0.99) for T1, 0.81 (95% CI = 0.76–0.86) and 0.96 (95% CI = 0.91–0.98) for T2, 0.88 (95% CI = 0.84–0.91) and 0.85 (95% CI = 0.79–0.90) for T3, and 0.81 (95% CI = 0.69–0.89) and 0.96 (95% CI = 0.93–0.97) for T4. Moreover, DCEUS demonstrated significant superiority to CT in diagnosing T1 (RR = 1.57, 95% CI = 1.20–2.05, p = 0.001) and T2 (RR = 1.41, 95% CI = 1.16–1.71, p = 0.001) and to EUS in diagnosing T3 (RR = 1.24, 95% CI = 1.08–1.42, p = 0.003) and T4 (RR = 1.40, 95% CI = 1.09–1.79, p = 0.008). However, it showed a lower diagnostic accuracy than EUS in T1 tumors (RR = 0.77, 95% CI = 0.62–0.94, p = 0.013).

Conclusions

DCEUS is a feasible complementary diagnostic tool for clinical T staging of GC. However, it is still far from a definitive conclusion for DCEUS to be proposed for use in routine clinical practice.

Gastric Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology

Gastric cancer is the third leading cause of cancer-related deaths worldwide. Over 95% of gastric cancers are adenocarcinomas, which are typically classified based on anatomic location and histologic type. Gastric cancer generally carries a poor prognosis because it is often diagnosed at an advanced stage. Systemic therapy can provide palliation, improved survival, and enhanced quality of life in patients with locally advanced or metastatic disease. The implementation of biomarker testing, especially analysis of HER2 status, microsatellite instability (MSI) status, and the expression of programmed death-ligand 1 (PD-L1), has had a significant impact on clinical practice and patient care. Targeted therapies including trastuzumab, nivolumab, and pembrolizumab have produced encouraging results in clinical trials for the treatment of patients with locally advanced or metastatic disease. Palliative management, which may include systemic therapy, chemoradiation, and/or best supportive care, is recommended for all patients with unresectable or metastatic cancer. Multidisciplinary team management is essential for all patients with localized gastric cancer. This selection from the NCCN Guidelines for Gastric Cancer focuses on the management of unresectable locally advanced, recurrent, or metastatic disease.

Radiomics signature based on computed tomography images for the preoperative prediction of lymph node metastasis at individual stations in gastric cancer: A multicenter study

BACKGROUND

Specific diagnosis and treatment of gastric cancer (GC) require accurate preoperative predictions of lymph node metastasis (LNM) at individual stations, such as estimating the extent of lymph node dissection. This study aimed to develop a radiomics signature based on preoperative computed tomography (CT) images, for predicting the LNM status at each individual station.

METHODS

We enrolled 1506 GC patients retrospectively from two centers as training (531) and external (975) validation cohorts, and recruited 112 patients prospectively from a single center as prospective validation cohort. Radiomics features were extracted from preoperative CT images and integrated with clinical characteristics to construct nomograms for LNM prediction at individual lymph node stations. Performance of the nomograms was assessed through calibration, discrimination and clinical usefulness.

RESULTS

In training, external and prospective validation cohorts, radiomics signature was significantly associated with LNM status. Moreover, radiomics signature was an independent predictor of LNM status in the multivariable logistic regression analysis. The radiomics nomograms revealed good prediction performances, with AUCs of 0.716-0.871 in the training cohort, 0.678-0.768 in the external validation cohort and 0.700-0.841 in the prospective validation cohort for 12 nodal stations. The nomograms demonstrated a significant agreement between the actual probability and predictive probability in calibration curves. Decision curve analysis showed that nomograms had better net benefit than clinicopathologic characteristics.

CONCLUSION

Radiomics nomograms for individual lymph node stations presented good prediction accuracy, which could provide important information for individual diagnosis and treatment of gastric cancer.

Nomograms for Predicting the Lymph Node Metastasis in Early Gastric Cancer by Gender: A Retrospective Multicentric Study

Background

Lymph node metastasis (LNM) has a significant impact on the prognosis of patients with early gastric cancer (EGC). Our aim was to identify the independent risk factors for LNM and construct nomograms for male and female EGC patients, respectively.

Methods

Clinicopathological data of 1,742 EGC patients who underwent radical gastrectomy and lymphadenectomy in the First Affiliated Hospital, Second Affiliated Hospital, and Fourth Affiliated Hospital of Anhui Medical University between November 2011 and April 2021 were collected and analyzed retrospectively. Male and female patients from the First Affiliated Hospital of Anhui Medical University were assigned to training sets and then from the Second and Fourth Affiliated Hospitals of Anhui Medical University were enrolled in validation sets. Based on independent risk factors for LNM in male and female EGC patients from the training sets, the nomograms were established respectively, which was also verified by internal validation from the training sets and external validation from the validation sets.

Results

Tumor size (odd ratio (OR): 1.386, p = 0.030), depth of invasion (OR: 0.306, p = 0.001), Lauren type (OR: 2.816, p = 0.000), lymphovascular invasion (LVI) (OR: 0.160, p = 0.000), and menopause (OR: 0.296, p = 0.009) were independent risk factors for female EGC patients. For male EGC patients, tumor size (OR: 1.298, p = 0.007), depth of invasion (OR: 0.257, p = 0.000), tumor location (OR: 0.659, p = 0.002), WHO type (OR: 1.419, p = 0.001), Lauren type (OR: 3.099, p = 0.000), and LVI (OR: 0.131, p = 0.000) were independent risk factors. Moreover, nomograms were established to predict the risk of LNM for female and male EGC patients, respectively. The area under the ROC curve of nomograms for female and male training sets were 87.7% (95% confidence interval (CI): 0.8397–0.914) and 94.8% (95% CI: 0.9273–0.9695), respectively. For the validation set, they were 92.4% (95% CI: 0.7979–1) and 93.4% (95% CI: 0.8928–0.9755), respectively. Additionally, the calibration curves showed good agreements between the bias-corrected prediction and the ideal reference line for both training sets and validation sets in female and male EGC patients.

Conclusions

Nomograms based on risk factors for LNM in male and female EGC patients may provide new insights into the selection of appropriate treatment methods.

Prediction of serosal invasion in gastric cancer: development and validation of multivariate models integrating preoperative clinicopathological features and radiographic findings based on late arterial phase CT images

BACKGROUND

To develop and validate multivariate models integrating endoscopic biopsy, tumor markers, and CT findings based on late arterial phase (LAP) to predict serosal invasion in gastric cancer (GC).

METHODS

The preoperative differentiation degree, tumor markers, CT morphological characteristics, and CT value-related and texture parameters of 154 patients with GC were analyzed retrospectively. Multivariate models based on regression analysis and machine learning algorithms were performed to improve the diagnostic efficacy.

RESULTS

The differentiation degree, carbohydrate antigen (CA) 199, CA724, CA242, and multiple CT findings based on LAP differed significantly between T1-3 and T4 GCs in the primary cohort (all P < 0.05). Multivariate models based on regression analysis and random forest achieved AUCs of 0.849 and 0.865 in the primary cohort, respectively.

CONCLUSION

We developed and validated multivariate models integrating endoscopic biopsy, tumor markers, CT morphological characteristics, and CT value-related and texture parameters to predict serosal invasion in GCs and achieved favorable performance.

Endoscopic diagnosis and treatment of gastric dysplasia and early cancer: Current evidence and what the future may hold

Gastric cancer accounts for a significant proportion of worldwide cancer-related morbidity and mortality. The well documented precancerous cascade provides an opportunity for clinicians to detect and treat gastric cancers at an endoscopically curable stage. In high prevalence regions such as Japan and Korea, this has led to the implementation of population screening programs. However, guidelines remain ambiguous in lower prevalence regions. In recent years, there have been many advances in the endoscopic diagnosis and treatment of early gastric cancer and precancerous lesions. More advanced endoscopic imaging has led to improved detection and characterization of gastric lesions as well as superior accuracy for delineation of margins prior to resection. In addition, promising early data on artificial intelligence in gastroscopy suggests a future role for this technology in maximizing the yield of advanced endoscopic imaging. Data on endoscopic resection (ER) are particularly robust in Japan and Korea, with high rates of curative ER and markedly reduced procedural morbidity. However, there is a shortage of data in other regions to support the applicability of protocols from these high prevalence countries. Future advances in endoscopic therapeutics will likely lead to further expansion of the current indications for ER, as both technology and proceduralist expertise continue to grow.

Identifying multiple swollen lymph nodes on preoperative computed tomography is associated with poor prognosis along with pathological extensive nodal metastasis in locally advanced gastric cancer

BACKGROUND

Advanced gastric cancer with extensive lymph node (LN) metastasis is associated with poor outcomes even after R0 gastrectomy. Although multi-detector row computed tomography (MDCT) is the basis of preoperative LN staging, the diagnostic accuracy of pathologically extensive LN metastasis detection by MDCT remains unsatisfactory.

METHODS

We retrospectively evaluated diagnostic accuracy for pN2/3 disease by size and number of depicted LNs on MDCT in a single-center cohort of 421 patients with pT2-4 gastric carcinoma. The positive predictive value (PPV) was determined based on the number and short-axis diameter (SAD) of identified LNs, and oncological outcomes were also evaluated according to clinical LN status and pN categories.

RESULTS

The PPV for detecting pN2/3 disease rose with the SAD value cut-off for one LN, reaching 84.6% at 10 mm with no further increase at 15 mm. However, the SAD cut-off value plateaued at 8 mm (91.3%) when at least two measurable LNs were identified on MDCT. Patients with two measurable LNs with SAD≥8 mm had significantly poorer 5-year overall and recurrence-free survival than patients with fewer than two measurable LNs in the pN2-3 disease. On multivariate analysis, two measurable LNs with SAD≥8 mm was an independent prognostic factor for overall and relapse-free survivals.

CONCLUSION

Locally advanced gastric cancer with two measurable LNs with SAD≥8 mm on preoperative MDCT is highly associated with pN2/3 disease and poorer outcomes with upfront surgery. This criterion might be a reasonable indicator for identifying candidates for neoadjuvant treatment of advanced gastric cancer.

Construction and Validation of a Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer

Background:

Increasing evidence indicated that the tumor microenvironment (TME) plays a critical role in tumor progression. This study aimed to identify and evaluate mRNA signature involved in lymph node metastasis (LNM) in TME for gastric cancer (GC).

Methods:

Gene expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was used to evaluate the TME of GC. The heatmap and Venn plots were applied for visualizing and screening out intersect differentially expressed genes (DEGs) involved in LNM in TME. Functional enrichment analysis, gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network were also conducted. Furthermore, binary logistic regression analysis were employed to develop a 4-mRNAs signature for the LNM prediction. ROC curves were applied to validate the LNM predictive ability of the riskscore. Nomogram was constructed and calibration curve was plotted to verify the predictive power of nomogram.

Results:

A total of 88 LNM related DEGs were identified. Functional enrichment analysis and GSEA implied that those genes were associated with some biological processes, such as ion transportation, lipid metabolism and thiolester hydrolase activity. After univariate and multivariate logistic regression analysis, 4 mRNAs (RASSF2, MS4A2, ANKRD33B and ADH1B) were eventually screened out to develop a predictive model. ROC curves manifested the good performance of the 4-mRNAs signature. The proportion of patients with LNM in high-risk group was significantly higher than that in low-risk group. The C-index of nomogram from training and test cohorts were 0.865 and 0.765, and the nomogram was well calibrated.

Conclusions:

In general, we identified a 4-mRNAs signature that effectively predicted LNM in GC patients. Moreover, the 4-mRNAs signature and nomogram provide a guidance for the preoperative evaluation and postoperative treatment of GC patients.

The New American Joint Committee on Cancer T staging system for stomach: increased complexity without clear improvement in predictive accuracy for endoscopic ultrasound

Background

The efficacy of endoscopic ultrasound (EUS) for determining the T category of gastric cancer is variable. The aim of this study was to evaluate the superiority of EUS by using the 6th edition American Joint Committee on Cancer (AJCC) staging system for stomach cancer compared to the new 7th/8th edition.

Methods

A retrospective analysis of clinical and EUS imaging features of 348 gastric carcinoma patients who underwent radical resection were retrospectively analyzed. Differences between the 6th and 7th/8th edition T staging systems for preoperative EUS evaluation were compared.

Results

The accuracy of EUS T staging was 72.4% for the 7th/8th edition and 78.4% for the 6th edition. T3 stage accuracy was significantly worse when the T3 group status was changed. The tumor location, echoendoscope type, and histological type were associated with inaccuracy. We further analyzed the EUS image features for each tumor T stage and found that an indistinctly visible muscularis propria (MP) or with obvious thickening was considered an indicator of lesions involved in the MP with a sensitivity of 81.3%; an MP completely disappeared and accompanied with a serosal layer intact may be a marker that the lesion invaded to the subserosa. We also found that irregularities in the outer edge of the gastric wall were markers of gastric serosal layer penetration with a positive predictive value of 92.2%.

Conclusions

The increased complexity of the 7th/8th edition T staging system is accompanied by worsening of the predictive accuracy for EUS as compared to the 6th edition. Furthermore, the tumor location, echoendoscope type, histological type, and EUS image features for each tumor T stage should warrant attention.

Current status and future perspectives on neoadjuvant therapy in gastric cancer

Gastric cancer, with high morbidity and mortality rates, is one of the most heterogeneous tumors. Radical gastrectomy and postoperative chemotherapy are the standard treatments. However, the safety and efficacy of neoadjuvant therapy (NAT) need to be confirmed by many trials before implementation, creating a bottleneck in development. Although clinical benefits of NAT have been observed, a series of problems remain to be solved. Before therapy, more contributing factors should be offered for choice in the intended population and ideal regimens. Enhanced computed tomography (CT) scanning is usually applied to evaluate effectiveness according to Response Evaluation Criteria in Solid Tumors (RECIST), yet CT scanning results sometimes differ from pathological responses. After NAT, the appropriate time for surgery is still empirically defined. Our review aims to discuss the abovementioned issues regarding NAT for GC, including indications, selection of regimens, lesion assessment and NAT-surgery interval time.

Utility of the gastric window in computed tomography for differentiation of early gastric cancer (T1 stage) from muscularis involvement (T2 stage)

OBJECTIVE

To analyze the diagnostic value of using the gastric window in computed tomography for differentiation of early gastric cancer (T1 stage) from muscularis involvement (T2 stage).

MATERIALS AND METHODS

All patients with pathologically confirmed T1 stage and T2 stage gastric cancer and who underwent endoscopic resection or gastrectomy at our institution from January 2011 to November 2018 were examined. Each patient received an enhanced CT scan of the abdomen before the operation. T staging of tumors based on the CT scans was performed independently by two radiologists using the gastric window (width 150-200 HU, level 80-100 HU) and the abdominal window (width 350-400 HU, level 50 HU).

RESULTS

Use of the gastric window to diagnose stage T1 EGC led to an accuracy of 88.9% for observer1 and 91.5% for observer2; use of the abdominal window led to an accuracy of 53.6% for observer1 and 51.6% (38/106) for observer2. Use of the gastric window to diagnose stage T2 led to an accuracy of 85.6% for observer1 and 82.4% for observer2; use of the abdominal window led to an accuracy of 52.3% for both observer1 and observer2. For observer1, use of the gastric window had a diagnostic accuracy of 69.2% for stage T1a and 62.5% for stage T1b; for observer2, the diagnostic accuracy was 65.1% for stage T1a and 67.0% for stage T1b. A Kappa test indicated moderate and substantial inter-observer agreement for T staging with gastric window (κ = 0.598, P < 0.001) and abdominal window (κ = 0.745, P < 0.001).

CONCLUSION

Use of the gastric window in computed tomography provided more accurate staging for T1 and T2 stages of gastric cancer than the conventional abdominal window.

Can endoscopic ultrasonography (EUS) improve the accuracy of clinical T staging by computed tomography (CT) for gastric cancer?

INTRODUCTION

With the introduction of new therapeutic options for gastric cancer treatment, more precise preoperative staging of gastric cancer is needed. The purpose of this study was to evaluate the role of endoscopic ultrasonography (EUS) for improving the accuracy of clinical T staging by computed tomography (CT) for gastric cancer.

MATERIALS AND METHODS

A total of 2636 patients underwent stomach protocol CT (S-CT) and EUS, followed by gastrectomy for primary gastric adenocarcinoma between September 2012 and February 2018 at Seoul National University Hospital. The results of preoperative S-CT and EUS were compared to the postoperative pathologic staging.

RESULTS

The overall accuracy of S-CT and EUS for T staging were 69.4% and 70.4%, respectively. When T staging was divided into T1-2 and T3-4 for clinically advanced gastric cancer (AGC), the positive predictive value for T3-4 using S-CT, EUS, and a combination of both modalities was 73.8%, 79.3%, and 85.6%, respectively. In 114 cases of indeterminate lesions between cT1 and cT2 by S-CT, EUS had a better prediction rate than the final decision based on endoscopy or the agreement between the two experts (Match rate: EUS vs. final decision, 69.3% vs. 58.8%).

CONCLUSION

EUS can be a complementary diagnostic tool to clinical T staging of gastric cancer by CT for selecting T3-4 lesion.

Effect of Preoperative Tumour Under-Staging on the Long-Term Survival of Patients Undergoing Radical Gastrectomy for Gastric Cancer

Purpose

This study aimed to evaluate the effect of preoperative tumor staging deviation (PTSD) on the long-term survival of patients undergoing radical gastrectomy for gastric cancer (RGGC).

Materials and Methods

Clinicopathological data of 2,346 patients who underwent RGGC were retrospectively analyzed. The preoperative tumor-lymph node-metastasis (TNM) under-staging group (uTNM) comprised patients who had earlier preoperative TNM than postoperative TNM, and the no preoperative under-staging group (nTNM) comprised the remaining patients.

Results

There were 1,031 uTNM (44.0%) and 1,315 nTNM cases (56.0%). Cox prognostic analysis revealed that PTSD independently affected the overall survival (OS) after surgery. The 5-year OS was lower in the uTNM group (41.8%) than in the nTNM group (71.6%). The patients less than 65 years old, with lower American Society of Anaesthesiologists score, 2–5 cm tumor located at the lower stomach, and cT1 or cN0 preoperative staging would more likely undergo D1+ lymph node dissection (LND) in uTNM (p < 0.05). Logistic analyses revealed that tumor size > 2 cm and body mass index ≤ 22.72 kg/m² were independent risk factors of preoperative TNM tumor under-staging in patients with cT1N0M0 staging (p < 0.05).

Conclusion

Underestimated tumor staging is not rare, which possibly results in inadequate LND and affects the long-term survival for patients undergoing RGGC. D2 LND should be carefully performed in patients who are predisposed to this underestimation.

Prognostic Implications of Tumor Differentiation in Clinical T1N0 Gastric Adenocarcinoma

Background

Current guidelines recommend neoadjuvant chemotherapy in patients with locoregional gastric adenocarcinoma. Patients diagnosed with early stage gastric adenocarcinoma are usually managed with upfront surgical intervention. However, pathologic staging in a subset of these clinically staged patients identifies more advanced locoregional disease requiring adjuvant treatment. Therefore, identifying these patients prior to surgical intervention is critical to ensure employment of the appropriate treatment paradigm. The aim of the current study was to define patient characteristics associated with clinical understaging in early gastric cancer.

Methods

Using the National Cancer Database (2004–2014) we identified 3,892 individuals with clinical T1N0 gastric adenocarcinoma who underwent upfront definitive surgery, had negative surgical margins, and did not receive preoperative chemotherapy or radiotherapy. Patient characteristics were compared between those with pathologic stage T1N0 disease and those who were upstaged upon surgery.

Results

Twenty‐seven percent of clinical T1N0 gastric adenocarcinomas had a change in stage because of pathologically defined ≥T2 disease or positive lymph nodes. Individuals who were upstaged had a higher tumor grade compared with those with pathologic stage T1N0 disease. Specifically, 41.9% (530/1,264) of individuals with a poorly differentiated tumor were upstaged, compared with only 10.7% (70/656) with a well‐differentiated tumor. Approximately 75% of cases involved upstaging because of T misclassification. The highest percentage of upstaging was shown for tumors located at the fundus and body of the stomach.

Conclusion

Upstaging of clinical T1N0 gastric adenocarcinoma is characterized by higher tumor grade and is mostly a result of a change in T stage. These findings mandate thorough workup in order to identify patients with clinically staged T1N0 disease requiring preoperative chemotherapy.

Implications for Practice

Upstaging of clinical T1N0 gastric adenocarcinoma is characterized by higher tumor grade and is mostly a result of a change in T stage. These findings mandate thorough workup in order to identify patients with clinically staged T1N0 disease requiring preoperative chemotherapy.

This article evaluates the frequency of upstaging following surgery among cT1N0 gastric cancer and defines the corresponding patient characteristics, with the goal of better identifying those patients who require preoperative chemotherapy.

Hospital clinical staging accuracy for upper gastrointestinal malignancy

BACKGROUND

Decisions about multimodality treatment for upper gastrointestinal malignancies are largely predicted on clinical staging information. However, hospital-level accuracy of clinical staging is currently unknown.

METHODS

A national cohort study of patients with adenocarcinoma of the esophagus, stomach, or pancreas in the NCDB (2006-2015) who were treated with upfront resection. Hospital-level staging accuracy (ascertained by comparing clinical stage to pathologic stage) was calculated. Within hospital correlation of staging accuracy across disease sites was evaluated using risk and reliability adjustment.

RESULTS

Overall, 1246 hospitals were evaluated. Median hospital T-staging accuracy was 77.5%, 73.7%, and 60.8% for esophageal, gastric, and pancreatic cancer, respectively. Median hospital N-staging accuracy was 80.2%, 72.9%, and 61.8%, respectively. For T-stage, over-staging was most frequently observed in esophageal patients (11.2%) while under-staging was most frequent in pancreatic patients (36.1%). For N-stage, over-staging was infrequent for all three, while under-staging was most common in pancreatic patients (37.4%). Correlation across disease sites was weak for both T- (best observed, r = .34) and N-stages (r = .30). When high volume hospitals were evaluated, correlation improved but accuracy rates were similar.

CONCLUSIONS

Despite the importance of clinical staging in multimodality treatment planning, hospitals inaccurately stage 20-40% of patients, with low correlation across disease sites.

Diagnostic accuracy of the gastric cancer T-category with respect to tumor localization

Purpose

Diagnosing early gastric cancer (EGC) or advanced gastric cancer (AGC) according to T-category is important for optimal GC treatment; however, the clinical and pathological diagnosis of tumor depths can sometimes vary. This study investigated the accuracy of clinical diagnosis of the tumor depth from the viewpoint of tumor localization and prognosis of patients with GC with discordance between clinical and pathological findings.

Methods

This study enrolled 741 patients with primary GC who underwent curative gastrectomy. Based on the clinical and pathological diagnosis of T-category, the patients were classified into four groups: Early-look EGC, Early-look AGC, Advanced-look EGC, and Advanced-look AGC. Tumor localization was classified longitudinally (the upper [U], middle [M], and lower [L] parts and cross-sectionally (the anterior [Ant] and posterior [Post] walls, and the lesser [Less] and greater [Gre] curvatures).

Results

Of the 462 clinical EGC cases, 52 were Early-look AGC cases that exhibited a significant association of tumor localization with the Post and Less in the U and M locations (UM-PL; p = 0.037). An Advanced-look EGC (p = 0.031) and Advanced-look AGC (p = 0.025) were independent prognostic factors for relapse-free survival each in pathological EGC and AGC, respectively.

Conclusions

Patients with clinically diagnosed EGC but with pathologically diagnosed AGC more frequently presented tumor in the UM-PL than in any other location. Selection of therapeutic strategy according to the clinical diagnosis might be critical; however, it should be also considered that the accuracy of preoperative assessments varies with tumor localization.

Electronic supplementary material

The online version of this article (10.1007/s00423-020-01971-3) contains supplementary material, which is available to authorized users.

Prediction of the Depth of Tumor Invasion in Gastric Cancer: Potential Role of CT Radiomics

RATIONALE AND OBJECTIVES

The aim of this study was to investigate the value of computed tomography (CT) radiomics for the differentiation between T2 and T3/4 stage lesions in gastric cancer.

MATERIALS AND METHODS

A total of 244 consecutive patients with pathologically proven gastric cancer were retrospectively included and split into a training cohort (171 patients) and a test cohort (73 patients). Preoperative arterial phase and portal phase contrast enhanced CT images were retrieved for tumor segmentation and feature extraction by using a dedicated postprocessing software. The random forest method was used to build the classifier models.

RESULTS

The performance of single phase radiomics models were favorable in the differentiation between T2 and T3/4 stage tumors. Arterial phase-based radiomics model exhibited areas under the curve of 0.899 (95% CI: 0.812-0.955) in the training cohort and 0.825 (95% CI: 0.718-0.904) in the test cohort. Portal phase-based radiomics model showed areas under the curve of 0.843 (95% CI: 0.746-0.914) and 0.818 (95% CI: 0.711-0.899) in the training and test cohort, respectively.

CONCLUSION

CT radiomics approach has a potential role in differentiation between T2 and T3/4 stage tumors in gastric cancer.

FKBP10 Acts as a New Biomarker for Prognosis and Lymph Node Metastasis of Gastric Cancer by Bioinformatics Analysis and in Vitro Experiments

Purpose

To explore the role of FKBP prolyl isomerase 10 (FKBP10) protein in the progression of gastric cancer.

Methods

Four independent gastric cancer databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD) were used to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify the abnormally active pathways in patients with gastric cancer. Univariate Cox regression analysis was used to identify genes with stable prognostic value in gastric cancer patients based on three independent gastric cancer databases (GSE15459, GSE62254, TCGA-STAD). Gene set enrichment analysis (GSEA) was used to explore the possible pathways related to FKBP10. The reverse transcription-polymerase chain reaction (RT-PCR) was employed to determine the expression of FKBP10 mRNA in the HGC-27 and MKN-7 cell lines. Adhesion assay was used to detect changes in cell adhesion ability. FKBP10, ITGA1, ITGA2, ITGA5, ITGAV, ITGA6, P-AKT₄₇₃, P-AKT₃₀₈, AKT, and β-actin were evaluated by Western blot (WB).

Results

We first performed differential expression genes (DEGs) screening of four independent GC databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD). Eighty-nine genes showed consistent up-regulation in GC, the results of pathway analysis showed that they were related to “Focal adhesion”. The prognostic value of these 89 genes was tested in three independent GC databases GSE15459, GSE62254 and TCGA-STAD cohort. Finally, 12 genes, in which the expression of FKBP10 was prominently increased in patients with lymph node metastasis (LNM), showed stable prognostic value. The following gene set enrichment analysis (GSEA) also showed that FKBP10 is mainly involved in cell adhesion process, while adhesion experiments confirmed that cell adhesion was down-regulated after silencing FKBP10 in GC cells, and adhesion-related molecules integrin αV and α6 were down-regulated.

Conclusion

FKBP10 may be used as a marker for lymph node metastasis of GC and could be used as a potential target for future treatment of GC.

Operative safety of curative gastrectomy after endoscopic submucosal dissection (ESD) for early gastric cancer - 1:2 propensity score matching analysis: A retrospective single-center study (cohort study)

BACKGROUND

This study aimed to evaluate the operative safety and long-term outcomes of additional curative gastrectomy (ACG) after non-curative endoscopic submucosal dissection (ESD), as compared with standard gastrectomy (SG) without ESD in patients with early gastric cancer.

MATERIALS AND METHODS

Data from 101 patients receiving ACG after non-curative ESD (Post-ESD group) and 1080 patients after SG without ESD (Surgery-only group), between 2009 and 2016, were reviewed retrospectively. Clinicopathologic characteristics, overall survival (OS), disease-specific survival (DSS), and relapse-free survival (RFS) were compared between groups, using propensity score matching analysis.

RESULTS

After propensity score matching, a total of 101 patients in the post-ESD group and 202 patients in the surgery-only group were analyzed. The post-ESD group had shorter operation times than did the surgery-only group (p = 0.005). Estimated blood loss and the incidence of postoperative morbidity did not differ between the two groups, and no differences were observed in pathologic outcomes, including N stage (p = 0.268). In addition, 5-year OS, DSS, and RFS rates were not significantly different between groups (OS; 95.1% vs. 98.2%, p = 0.535, DSS; 98.2% vs. 98.7%, p = 0.956, and RFS; 98.6% vs. 98.9%, p = 0.757, respectively).

CONCLUSION

ACG can be performed safely after non-curative endoscopic submucosal dissection, with good operative outcomes.

Predictors of lymph node metastasis and residual tumor in early gastric cancer patients after noncurative endoscopic resection: a systematic review and meta-analysis

BACKGROUND

It is challenging to identify the prevalence of lymph node metastasis (LNM) and residual tumor in patients with early gastric cancer (EGC) who underwent noncurative endoscopic resection (ER). This present meta-analysis was aimed to establish imperative potential predictive factors in order to select the optimal treatment method.

METHODS

A systematic literature search of PubMed, Embase, and Cochrane Library databases was performed through 1 February 2019 to identify relevant studies, which investigated risk factors for LNM and residual tumor in patients with EGC who underwent noncurative ER. Eligible data were systematically reviewed through a meta-analysis.

RESULTS

Overall, 12 studies investigating the risk factor of LNM were included, totaling 3015 patients, 7 of which also involved cancer residues. After the present meta-analysis, six predictors, including tumor size >30 mm, tumor invasion depth (⩾500 μm from the muscularis mucosae), macroscopic appearance, undifferentiated histopathological type, positive vertical margin, and presence of lymphovascular invasion (including lymphatic invasion and vascular invasion) were significantly associated with LNM, whereas tumor size >30 mm, positive horizontal margin, and positive vertical margin were identified as significant predictors for the risk of residual tumor. No evidence of publication bias was observed.

CONCLUSIONS

Six and three variables were established as significant risk factors for LNM and residual tumor in patients with EGC who underwent noncurative ER, respectively. Patients with EGC who present these risk factors after noncurative ER are strongly suggested to receive additional surgery, while others might be suitable for strict follow-up. This might shed some new light on the selection of follow-up treatment for noncurative ER.

SEOM clinical guideline for the diagnosis and treatment of gastric cancer (GC) and gastroesophageal junction adenocarcinoma (GEJA) (2019)

Gastric cancer (GC) is the fifth most common cancer worldwide with a varied geographic distribution and an aggressive behavior. In Spain, it represents the sixth cause of cancer death. In Western countries, the incidence is decreasing slightly, with an increase in gastroesophageal junction adenocarcinoma (GEJA), a different entity that we separate specifically in the guideline. Molecular biology advances have been done recently, but do not yet lead to the choice in treatment approach except in advanced disease with overexpression of HER2. Endoscopic resection in very early stage, perioperative chemotherapy in locally advanced tumors and preliminary immune therapy resulting in advanced disease are the main treatment innovations in the GC/GEJA treatment. We describe the different evidences and recommendations following the statements of the American College of Physicians.

Dealing with the gray zones in the management of gastric cancer: The consensus statement of the İstanbul Group

The geographical location and differences in tumor biology significantly change the management of gastric cancer. The prevalence of gastric cancer ranks fifth and sixth among men and women, respectively, in Turkey. The international guidelines from the Eastern and Western countries fail to manage a considerable amount of inconclusive issues in the management of gastric cancer. The uncertainties lead to significant heterogeneities in clinical practice, lack of homogeneous data collection, and subsequently, diverse outcomes. The physicians who are professionally involved in the management of gastric cancer at two institutions in Istanbul, Turkey, organized a consensus meeting to address current problems and plan feasible, logical, measurable, and collective solutions in their clinical practice for this challenging disease. The evidence-based data and current guidelines were reviewed. The gray zones in the management of gastric cancer were determined in the first session of this consensus meeting. The second session was constructed to discuss, vote, and ratify the ultimate decisions. The identification of the T stage, the esophagogastric area, imaging algorithm for proper staging and follow-up, timing and patient selection for neoadjuvant treatment, and management of advanced and metastatic disease have been accepted as the major issues in the management of gastric cancer. The recommendations are presented with the percentage of supporting votes in the results section with related data.

Gastric adenocarcinoma mimicking a submucosal tumor: A case report

BACKGROUND

Submucosal tumor (SMT)-like early-stage gastric cancer (GC) has rarely been reported. It is difficult to consider the possibility of GC and differentiate it from other submucosal lesions.

CASE SUMMARY

We present the case of a 50-year-old male patient with a 1.6 cm SMT-like flat elevated lesion covered by congested mucosa on the gastric angle. Magnifying endoscopy with narrow-band imaging, endoscopic biopsy, endoscopic ultrasound, and computed tomography were performed for diagnosis. Endoscopic submucosal dissection and gastrectomy with lymph node dissection were performed. The post-resection pathological analysis led to a final diagnosis of GC (Bormann type I, T1bN2M0).

CONCLUSION

GC should be considered when detecting an SMT-like lesion in the stomach.

A Meta-Analysis And Systematic Review Of Accuracy Of Endoscopic Ultrasound For N Staging Of Gastric Cancers

BACKGROUND

Endoscopic ultrasonography (EUS) is widely used as a staging modality for gastric cancer. However, the results of studies on the use of EUS for N staging in gastric cancer vary. This study aimed at studying the overall diagnostic accuracy of EUS for N staging of gastric cancer.

METHODS

Published studies were identified through searching the MEDLINE, Web of Science, EMBASE, SpringerLink and ScienceDirect databases. A bivariate random effect model was used to estimate the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). A hierarchical summary receiver operating characteristic curves (HSROC) based on the pooled data was also computed.

RESULTS

Fifty studies (5223 patients) were included in this analysis. The pooled sensitivity, specificity, PLR, NLR and DOR of EUS for N staging were 0.82 (95% CI 0.78 to 0.85), 0.68 (0.63 to 0.73), 2.6 (2.2 to 3.0), 0.27 (0.22 to 0.32), and 10 (8 to 12), respectively. The area under the HSROC was 0.83.

CONCLUSION

The EUS may provide a clinically useful tool to guide physicians in the N staging of gastric cancer. However, physicians must note that the EUS has a relatively low specificity.

CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

PURPOSE

To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer.

MATERIALS AND METHODS

This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts.

RESULTS

The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively.

CONCLUSIONS

The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer.

KEY POINTS

• CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer. • Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer. • The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer.

Cellular magnetic resonance imaging: in vivo tracking of gastric cancer cells and detecting of lymph node metastases using microparticles of iron oxide in mice

Background

Monitoring the fate of implanted cells over time in an experimental animal may provide a new way to track the metastatic process. Lymph node metastase is of extremely importance for the prognostic prediction of gastric carcinoma. The aim of this study was to assess the feasibility of magnetic resonance imaging (MRI), using micron-sized superparamagnetic iron oxide particles (MPIO), for monitoring of the fate of gastric cancer cells and detecting the migration of gastric cancer cells through the lymphatic system in a mouse model.

Methods

SGC-7901 gastric cancer cells were labeled with green fluorescent MPIO. The cells were monitored in vitro at multiple time points by staining for iron-labeled cells and by flow cytometric detection of the fluorescent MPIO. MPIO-labeled cells were implanted subcutaneously into nude mice, and cellular MRI was performed at different time points until 35 days postinjection.

Results

The potential for retention of the iron particles in vitro was evaluated. Our results showed that the labeling and uptake efficiency of MPIO reached 90.0% after 24 hrs of incubation, and a small percentage of cells that retained MPIO could be examined until 16 days after labeling. In vivo MRI-based tracking over several weeks in mice revealed regions of signal loss in the primary tumors for up to 5 weeks. Furthermore, small regions of signal void were detected in images of the inguinal lymph nodes in three mice at day 28 postinjection or later, and histological assays confirmed the presence of iron-labeled cancer cells.

Conclusion

This study supports MPIO-based cell tracking is a useful tool for monitoring the fate of gastric cancer cells in mice over time, which may facilitate progress in understanding the mechanisms of early regional lymph node micrometastases.

Imaging strategies in the management of gastric cancer: current role and future potential of MRI

Accurate preoperative staging of gastric cancer and the assessment of tumor response to neoadjuvant treatment is of importance for treatment and prognosis. Current imaging techniques, mainly endoscopic ultrasonography (EUS), computed tomography (CT) and ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET), have their limitations. Historically, the role of magnetic resonance imaging (MRI) in gastric cancer has been limited, but with the continuous technical improvements, MRI has become a more potent imaging technique for gastrointestinal malignancies. The accuracy of MRI for T- and N-staging of gastric cancer is similar to EUS and CT, making MRI a suitable alternative to other imaging strategies. There is limited evidence on the performance of MRI for M-staging of gastric cancer specifically, but MRI is widely used for diagnosing liver metastases and shows potential for diagnosing peritoneal seeding. Recent pilot studies showed that treatment response assessment as well as detection of lymph node metastases and systemic disease might benefit from functional MRI (e.g. diffusion weighted imaging and dynamic contrast enhancement). Regarding treatment guidance, additional value of MRI might be expected from its role in better defining clinical target volumes and setup verification with MR-guided radiation treatment.

Double Contrast-Enhanced Ultrasonography in Preoperative T Staging of Gastric Cancer: A Comparison With Endoscopic Ultrasonography

Objective: To compare the precision of double contrast-enhanced ultrasonography (DCEUS) to endoscopic ultrasonography (EUS) in preoperative T staging of gastric cancers.

Methods: This retrospective study consisted of 158 pathologically confirmed gastric cancer patients. All patients underwent DCEUS (intravenous contrast-enhanced ultrasonography combined with oral contrast-enhanced ultrasonography) and endoscopic ultrasonography (EUS) preoperatively. The histopathological findings of resected specimens were compared with the results of DCEUS and EUS retrospectively.

Results: The accuracy of DCEUS and EUS in evaluating the T staging of gastric cancer were 82.3% (T1 62.5%,T2 84.4%,T3 87.9%,T4 91.3%) and 76.6% (T1 84.4%,T2 82.2%,T3 72.4%,T4 65.2%), respectively. There were no significant differences between the methods for the overall T staging accuracy (χ² = 1.569, P = 0.210). But EUS was superior to DCEUS for T1 stage (χ² = 3.925, P = 0.048) and DCEUS was superior to EUS for T3 stage (χ² = 4.393, P = 0.036) and T4 stage (χ² = 4.600, P = 0.032).

Conclusion: DCEUS is a convenient and noninvasive method with high precision, which can be used as the primary imaging technique for advanced gastric cancer T staging. In early gastric cancer, we should prefer EUS. Two methods are complementary for assessing tumor invasion depth of gastric cancer.

Comparing PET/MRI with PET/CT for Pretreatment Staging of Gastric Cancer

18F-FDG PET/MRI has been applied to the diagnosis and preoperative staging in various tumor types; however, reports using PET/MRI in gastric cancer are rare because of motion artifacts. We investigated the value of PET/MRI for preoperative staging compared with PET/CT in gastric cancer (GC). Thirty patients with confirmed GC underwent PET/CT and PET/MRI. TNM staging for each patient was determined from the PET/MRI and PET/CT images. The diagnostic performance of PET/MRI and PET/CT was calculated compared with the pathologic TNM stage. The two methods were compared using statistical analyses. The accuracy for T staging between PET/MRI and PET/CT was 76.9% vs. 57.7%, respectively. In T₁ and T_4a staging, the sensitivity and specificity for PET/MRI vs. PET/CT was 1.0 vs. 0.6 and 1.0 vs. 0.8, respectively. The area under the curve (AUC) for PET/MRI vs. PET/CT was 1.00 vs. 0.78 in the T₁ stage, 0.73 vs. 0.66 in the T₂ stage, 0.72 vs. 0.57 in the T₃ stage, and 0.86 vs. 0.83 in the T₄ stage. The accuracy for N staging of PET/MRI vs. PET/CT was 53.9% vs. 34.0%, and that for N₀ vs. N₊ was 85.0% vs. 77.0%. The sensitivity for PET/MRI in N3 staging was 0.67 and 0 for PET/CT. There was a statistically significant difference in the AUC for N₁ staging (PET/MRI vs. PET/CT, 0.63 vs. 0.53, p = 0.03). SUVmax/ADC positively correlated with tumor volume and Ki-67. PET/MRI performs more accurately in TNM staging compared with PET/CT and is optimal for accurate N staging. SUVmax/ADC has positive correlations with tumor volume and Ki-67.

Different prognostic implication of ypTNM stage and pTNM stage for gastric cancer: a propensity score-matched analysis

Background

Pathological stage is considered as the best prognosis indicator for gastric cancer. With the increasing use of neoadjuvant chemotherapy (NACT), the latest TNM staging included a new pathological stage of ypTNM for patients with NACT. However, no study has investigated if ypTNM stage has the same prognostic implication as pTNM stage for gastric cancer.

Methods

We retrospectively selected eligible patients within a prospectively maintained database containing all patients treated with gastric cancer in Peking University Cancer Hospital from 2007 to 2015 using overall survival as the outcome. Patients using ypTNM and pTNM were 1:1 matched by propensity scores (PS) calculated from a model containing variables associated with ypTNM use or survival. Overall survival was compared by unconditional Cox regression. Conventional multivariate analysis was conducted to corroborate PS matching results.

Results

1441 patients were included in the analysis with a median follow-up of 37 months (range = 2–106). The matched sample contained 756 patients. After PS matching, patients with specific ypTNM stage were 1.34 (95%CI = 1.05–1.72, P = 0.019) times more likely to die than patients with the same pTNM stage. Similar to the results of PS matching, multivariate Cox regression yielded a hazard ratio (HR) of 1.35 (95%CI = 1.09–1.67, P = 0.006). Subgroup analysis indicated this survival difference between ypTNM and pTNM stage varied by the specific TNM stage of patients. The HR was 3.44 (95%CI = 1.06–11.18, P = 0.040) and 1.28 (95%CI = 1.00–1.62, P = 0.048) for patients in stage I and III, respectively; whereas for stage II patients, no significant difference was observed (HR = 1.37, 95%CI = 0.78–2.38, P = 0.27).

Conclusion

Gastric cancer patients with specific ypTNM stage had worse prognosis compared to those at the same stage defined by pTNM.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5283-3) contains supplementary material, which is available to authorized users.

Endoscopic ultrasonography for pretreatment T-staging of gastric cancer: An in vitro accuracy and discrepancy analysis

In the current era of multi-disciplinary treatment, precise and detailed diagnosis prior to treatment is crucial for clinical practice. For different lesions that fit different indications, the optimum approach for treatment differs significantly. Thus, the recent 8th American Joint Committee on Cancer classification system has introduced 'clinical stage' as a criterion. Endoscopic ultrasonography (EUS) has been the first-line choice for pretreatment staging; however, there is no standardization of the depth classification nor a standard EUS method. Additionally, the accuracy for this diagnostic test has ranged between <40 and 90% in previous studies. The aim of the present study was to determine the accuracy of EUS, identify the discrepancies between EUS and histological results, and analyze the underlying causes. Between June 2014 and February 2016, EUS was performed on gastric carcinoma specimens from 60 consecutive patients. EUS was performed on the resected specimens following surgery, but prior to fixation in formalin, invasion of the gastric wall was determined and the deepest location was marked with sutures. The ultrasound images were independently interpreted, and the quality of the images was scored by two endoscopists. Subsequently, the ultrasound images were compared with the pathological results of the same section. The overall accuracy of EUS was 75%. For locally advanced gastric cancers, EUS had a relatively high accuracy (33/43, 86%). The EUS results corresponded well with the pathological hematoxylin and eosin staining results, and the deepest points determined by EUS were confirmed by pathology in the majority of cases (85%). In total, 50 and 10 cases were scored as having high/moderate and low quality, associated with accuracies of 86% (43/50) and 20% (2/10), respectively. EUS is valuable for pretreatment T-staging, particularly for advanced cases. Proximal stomach cancer exhibited a tendency for improved accuracy. Overall, the results of the present study suggest that standardized scanning processes, particularly including all-encompassing scanning, proper probe-placement and high image quality, lead to improved accuracy of EUS.

Accuracy of endoscopic ultrasound in gastric adenocarcinoma patient selection for neoadjuvant therapy

Background

Recent studies demonstrated the positive impact of neoadjuvant treatment in locally advanced gastric cancer.

Objective

To assess the accuracy of endoscopic ultrasound (EUS) in the selection of patients with gastric adenocarcinoma for neoadjuvant therapy (T ≥ 2 and/or N+).

Methods

Retrospective analysis of patients with an anatomopathological diagnosis of gastric adenocarcinoma between January 2011 and June 2017, who had EUS for staging and underwent surgery as a first therapeutic attempt. The concordance (k) and accuracy (area under the curve (AUC)) of EUS for T ≥ 2 and/or N+ were assessed using the anatomopathological staging of the resected surgical specimen as the gold standard.

Results

The final sample included 152 patients (66.4% male, 67.1 ± 12.2 years). The concordance, accuracy, sensitivity and specificity of the EUS for T ≥ 2 and/or N+ were 0.72, 0.86 ± 0.03, 88.5% and 83.1%, respectively. The results were higher in proximal (k = 0.93, AUC = 0.96 ± 0.05, sensitivity (S) = 99.0% and specificity (E) = 90.9%) compared with distal lesions (k = 0.67, AUC = 0.84 ± 0.04, S = 85.7% and E = 81.5%), and in intestinal subtype (k = 0.77, AUC = 0.88 ± 0.04, S = 92.6% and E = 84.1%) compared with diffuse (k = 0.58, AUC = 0.79 ± 0.10, S = 85.0% and E = 72.7%) or mixed-subtype tumours (k = 0.65, AUC = 0.84 ± 0.10, S = 76.9% and E = 90.0%).

Conclusion

In one of the largest series of patients, we showed that EUS has overall high agreement and accuracy in the selection of patients with gastric adenocarcinoma for neoadjuvant therapy, although the agreement and accuracy are greater for proximal and intestinal lesions.