Gastric Cancer Staging: Is It Time for Magnetic Resonance Imaging?

MRI versus Dual-Energy CT in Local-Regional Staging of Gastric Cancer

Background Preoperative local-regional tumor staging of gastric cancer (GC) is critical for appropriate treatment planning. The comparative accuracy of multiparametric MRI (mpMRI) versus dual-energy CT (DECT) for staging of GC is not known. Purpose To compare the diagnostic accuracy of personalized mpMRI with that of DECT for local-regional T and N staging in patients with GC receiving curative surgical intervention. Materials and Methods Patients with GC who underwent gastric mpMRI and DECT before gastrectomy with lymphadenectomy were eligible for this single-center prospective noninferiority study between November 2021 and September 2022. mpMRI comprised T2-weighted imaging, multiorientational zoomed diffusion-weighted imaging, and extradimensional volumetric interpolated breath-hold examination dynamic contrast-enhanced imaging. Dual-phase DECT images were reconstructed at 40 keV and standard 120 kVp-like images. Using gastrectomy specimens as the reference standard, the diagnostic accuracy of mpMRI and DECT for T and N staging was compared by six radiologists in a pairwise blinded manner. Interreader agreement was assessed using the weighted κ and Kendall W statistics. The McNemar test was used for head-to-head accuracy comparisons between DECT and mpMRI. Results This study included 202 participants (mean age, 62 years ± 11 [SD]; 145 male). The interreader agreement of the six readers for T and N staging of GC was excellent for both mpMRI (κ = 0.89 and 0.85, respectively) and DECT (κ = 0.86 and 0.84, respectively). Regardless of reader experience, higher accuracy was achieved with mpMRI than with DECT for both T (61%-77% vs 50%-64%; all P < .05) and N (54%-68% vs 51%-58%; P = .497-.005) staging, specifically T1 (83% vs 65%) and T4a (78% vs 68%) tumors and N1 (41% vs 24%) and N3 (64% vs 45%) nodules (all P < .05). Conclusion Personalized mpMRI was superior in T staging and noninferior or superior in N staging compared with DECT for patients with GC. Clinical trial registration no. NCT05508126 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Méndez and Martín-Garre in this issue.

Cross-sectional imaging of gastric cancer: pearls, pitfalls and lessons learned from multidisciplinary conference

Gastric cancer is rising in prevalence associated with high mortality, primarily due to late-stage detection, underscoring the imperative for early and precise diagnosis. Etiology involves an interplay of genetic susceptibilities and environmental factors with a prominent role of Helicobacter pylori infection. Due to its often-delayed symptom presentation, prompt and accurate diagnosis is necessary. A multimodal imaging approach, including endoscopic ultrasound (EUS), multi-detector computed tomography (MDCT), and magnetic resonance imaging (MRI) is critical for accurate staging. Each modality contributes unique advantages and limitations, highlighting the importance of integrating diagnostic strategy. Moreover, multidisciplinary conferences offer a vital collaborative platform, bringing together specialists from diverse fields for treatment planning. This synergistic approach not only enhances diagnostic precision but also improves patient outcome. This review highlights the critical role of imaging in diagnosis, staging, and management and advocates for interdisciplinary collaboration in early detection and comprehensive management of gastric cancer, aiming to reduce mortality.

Deep learning-accelerated T2WI: image quality, efficiency, and staging performance against BLADE T2WI for gastric cancer

PURPOSE

The purpose of our study is to investigate image quality, efficiency, and diagnostic performance of a deep learning-accelerated single-shot breath-hold (DLSB) against BLADE for T2-weighted MR imaging (T2WI) for gastric cancer (GC).

METHODS

112 patients with GCs undergoing gastric MRI were prospectively enrolled between Aug 2022 and Dec 2022. Axial DLSB-T2WI and BLADE-T2WI of stomach were scanned with same spatial resolution. Three radiologists independently evaluated the image qualities using a 5-scale Likert scales (IQS) in terms of lesion delineation, gastric wall boundary conspicuity, and overall image quality. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated in measurable lesions. T staging was conducted based on the results of both sequences for GC patients with gastrectomy. Pairwise comparisons between DLSB-T2WI and BLADE-T2WI were performed using the Wilcoxon signed-rank test, paired t-test, and chi-squared test. Kendall's W, Fleiss' Kappa, and intraclass correlation coefficient values were used to determine inter-reader reliability.

RESULTS

Against BLADE, DLSB reduced total acquisition time of T2WI from 495 min (mean 4:42 per patient) to 33.6 min (18 s per patient), with better overall image quality that produced 9.43-fold, 8.00-fold, and 18.31-fold IQS upgrading against BALDE, respectively, in three readers. In 69 measurable lesions, DLSB-T2WI had higher mean SNR and higher CNR than BLADE-T2WI. Among 71 patients with gastrectomy, DLSB-T2WI resulted in comparable accuracy to BLADE-T2WI in staging GCs (P > 0.05).

CONCLUSIONS

DLSB-T2WI demonstrated shorter acquisition time, better image quality, and comparable staging accuracy, which could be an alternative to BLADE-T2WI for gastric cancer imaging.

Gastric Cancer: A Comprehensive Literature Review

Gastric cancer stands as a significant global health concern, particularly prevalent in Eastern Asia, with high mortality rates urging urgent attention and research efforts. This article comprehensively explores the epidemiology, anatomy, risk factors, pathophysiology, clinical presentation, diagnosis, staging, treatment modalities, prevention strategies, and survival rates associated with gastric cancer. Notably, Helicobacter pylori infection, dietary choices, and intricate stomach anatomy play pivotal roles in disease development. Early detection, utilizing staging, grading, and genetic testing for personalized treatment approaches is emphasized. Treatment modalities encompass surgery, chemotherapy, radiation therapy, targeted therapy, and immunotherapy. Prevention strategies involve lifestyle changes, screening, and genetic counseling. Survival rates vary by stage, highlighting the need for individualized care. In conclusion, a collaborative global effort is essential to address the impact of gastric cancer and improve outcomes.

Gastric cancer-derived LBP promotes liver metastasis by driving intrahepatic fibrotic pre-metastatic niche formation

BACKGROUND

Liver metastasis (LM) is one of the most common distant metastases of gastric cancer (GC). However, the mechanisms underlying the LM of GC (GC-LM) remain poorly understood. This study aimed to identify the tumour-secreted protein associated with GC-LM and to investigate the mechanisms by which this secreted protein remodels the liver microenvironment to promote GC-LM.

METHODS

Data-independent acquisition mass spectrometry (DIA-MS), mRNA expression microarray, quantitative real-time PCR, enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) were performed to identify and validate the GC-secreted proteins associated with GC-LM. A modified intrasplenic injection mouse model of LM was used to evaluate the progression and tumour burden of LM in vivo. Flow cytometry, immunofluorescence (IF), western blots (WB) and IHC were performed to validate the pre-metastatic niche (PMN) formation in the pre-modelling mouse models. mRNA sequencing of PMA-treated THP-1 cells with or without lipopolysaccharide binding protein (LBP) treatment was used to identify the functional target genes of LBP in macrophages. Co-immunoprecipitation (Co-IP), WB, ELISA, IF and Transwell assays were performed to explore the underlying mechanism of LBP in inducing intrahepatic PMN formation.

RESULTS

LBP was identified as a critical secreted protein associated with GC-LM and correlated with a worse prognosis in patients with GC. LBP activated the TLR4/NF-κB pathway to promote TGF-β1 secretion in intrahepatic macrophages, which, in turn, activated hepatic satellite cells (HSCs) to direct intrahepatic fibrotic PMN formation. Additionally, TGF-β1 enhanced the migration and invasion of incoming metastatic GC cells in the liver. Consequently, selective targeting of the TGF-β/Smad signaling pathway with galunisertib demonstrated its efficacy in effectively preventing GC-LM in vivo.

CONCLUSIONS

The results of this study provide compelling evidence that serological LBP can serve as a valuable diagnostic biomarker for the early detection of GC-LM. Mechanistically, GC-derived LBP mediates the crosstalk between primary GC cells and the intrahepatic microenvironment by promoting TGF-β1 secretion in intrahepatic macrophages, which induces intrahepatic fibrotic PMN formation to promote GC-LM. Importantly, selectively targeting the TGF-β/Smad signaling pathway with galunisertib represents a promising preventive and therapeutic strategy for GC-LM.

Risk Stratification and Overall Survival Prediction in Advanced Gastric Cancer Patients Based on Whole-Volume MRI Radiomics

BACKGROUND

The prognosis of advanced gastric cancer (AGC) patients has attracted much attention, but there is a lack of evaluation method. MRI-based radiomics has the potential to evaluate AGC patients' prognosis.

PURPOSE

To identify and validate the risk stratification and overall survival (OS) in AGC patients using MRI-based radiomics.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 233 patients (168 males, 63.6 ± 11.1 years; 65 females, 59.7 ± 11.8 years) confirmed AGC were collected. The data were randomly divided into a training (164) and validation set (69).

SEQUENCE

A 3.0 T, axial T2-weighted, diffusion-weighted imaging, and contrast-enhanced T1-weighted (CE-T1WI).

ASSESSMENT

Radiologist 1 segmented 233 patients and radiologist 2 segmented randomly 50 patients on CE-T1WI. The risk score (RS) was summed by each sample based on the radiomics features and correlation coefficients. Patients were followed up for 7-67 months (median 41; 138 dead and 95 alive).

STATISTICAL TESTS

The intraclass correlation coefficient (ICC) and Kappa value were calculated. Differences in survival analysis were assessed by Kaplan-Meier curves and log-rank test. Cox-regression analysis was performed to identify the radiomics features and clinical indicators associated with OS. The calibration curves were built to assess the model. A two-tailed P value < 0.05 was considered statistically significant.

RESULTS

Integrated with age, lymphovascular invasion (LVI) and RS, a survival combined model was built. The area under the curve (AUC) for predicting 3-year and 5-year OS was 0.765 and 0.788 in the training set, 0.757 and 0.729 in the validation set. There was no significant difference between the radiomics model and survival combined model for 3-year (0.690 vs. 0.757, P = 0.425) and 5-year OS (0.687 vs. 729, P = 0.412) in the validation set. The calibration curves showed a high degree of fit for the survival combined model.

DATA CONCLUSION

This study established a survival combined model that might help AGC patients in future clinical decision-making.

EVIDENCE LEVEL

33 TECHNICAL EFFICACY: Stage 5.

Comparison of MRI and CT-Based Radiomics and Their Combination for Early Identification of Pathological Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer

BACKGROUND

Current radiomics for treatment response assessment in gastric cancer (GC) have focused solely on Computed tomography (CT). The importance of multi-parametric magnetic resonance imaging (mp-MRI) radiomics in GC is less clear.

PURPOSE

To compare and combine CT and mp-MRI radiomics for pretreatment identification of pathological response to neoadjuvant chemotherapy in GC.

STUDY TYPE

Retrospective.

POPULATION

Two hundred twenty-five GC patients were recruited and split into training (157) and validation dataset (68) in the ratio of 7:3 randomly.

FIELD/SEQUENCE

T2-weighted fast spin echo (fat suppressed T2-weighted imaging [fs-T2WI]), diffusion weighted echo planar imaging (DWI), and fast gradient echo (dynamic contrast enhanced [DCE]) sequences at 3.0T.

ASSESSMENT

Apparent diffusion coefficient (ADC) maps were generated from DWI. CT, fs-T2WI, ADC, DCE, and mp-MRI Radiomics score (Radscores) were compared between responders and non-responders. A multimodal nomogram combining CT and mp-MRI Radscores was developed. Patients were followed up for 3-65 months (median 19) after surgery, the overall survival (OS) and progression free survival (PFS) were calculated.

STATISTICAL TESTS

A logistic regression classifier was applied to construct the five models. Each model's performance was evaluated using a receiver operating characteristic curve. The association of the nomogram with OS/PFS was evaluated by Kaplan-Meier survival analysis and C-index. A P value <0.05 was considered statistically significant.

RESULTS

CT Radscore, mp-MRI Radscore and nomogram were significantly associated with tumor regression grading. The nomogram achieved the highest area under the curves (AUCs) of 0.893 (0.834-0.937) and 0.871 (0.767-0.940) in training and validation datasets, respectively. The C-index was 0.589 for OS and 0.601 for PFS. The AUCs of the mp-MRI model were not significantly different to that of the CT model in training (0.831 vs. 0.770, P = 0.267) and validation dataset (0.797 vs. 0.746, P = 0.137).

DATA CONCLUSIONS

mp-MRI radiomics provides similar results to CT radiomics for early identification of pathologic response to neoadjuvant chemotherapy. The multimodal radiomics nomogram further improved the capability.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: 2.

The Role of Staging Laparoscopy for Gastric Cancer Patients: Current Evidence and Future Perspectives

A significant proportion of patients diagnosed with gastric cancer is discovered with peritoneal metastases at laparotomy. Despite the continuous improvement in the performance of radiological imaging, the preoperative recognition of such an advanced disease is still challenging during the diagnostic work-up, since the sensitivity of CT scans to peritoneal carcinomatosis is not always adequate. Staging laparoscopy offers the chance to significantly increase the rate of promptly diagnosed peritoneal metastases, thus reducing the number of unnecessary laparotomies and modifying the initial treatment strategy of gastric cancer. The aim of this review was to provide a comprehensive summary of the current literature regarding the role of staging laparoscopy in the management of gastric cancer. Indications, techniques, accuracy, advantages, and limitations of staging laparoscopy and peritoneal cytology were discussed. Furthermore, a focus on current evidence regarding the application of artificial intelligence and image-guided surgery in staging laparoscopy was included in order to provide a picture of the future perspectives of this technique and its integration with modern tools in the preoperative management of gastric cancer.

Using nomogram, decision tree, and deep learning models to predict lymph node metastasis in patients with early gastric cancer: a multi-cohort study

The accurate assessment of lymph node metastasis (LNM) in patients with early gastric cancer is critical to the selection of the most appropriate surgical treatment. This study aims to develop an optimal LNM prediction model using different methods, including nomogram, Decision Tree, Naive Bayes, and deep learning methods. In this study, we included two independent datasets: the gastrectomy set (n=3158) and the endoscopic submucosal dissection (ESD) set (n=323). The nomogram, Decision Tree, Naive Bayes, and fully convolutional neural networks (FCNN) models were established based on logistic regression analysis of the development set. The predictive power of the LNM prediction models was revealed by time-dependent receiver operating characteristic (ROC) curves and calibration plots. We then used the ESD set as an external cohort to evaluate the models' performance. In the gastrectomy set, multivariate analysis showed that gender (P=0.008), year when diagnosed (2006-2010 year, P=0.265; 2011-2015 year, P=0.001; and 2016-2020 year, P<0.001, respectively), tumor size (2-4 cm, P=0.001; and ≥4 cm, P<0.001, respectively), tumor grade (poorly-moderately, P=0.016; moderately, P<0.001; well-moderately, P<0.001; and well, P<0.001, respectively), vascular invasion (P<0.001), and pT stage (P<0.001) were independent risk factors for LNM in early gastric cancer. The area under the curve (AUC) for the validation set using the nomogram, Decision Tree, Naive Bayes, and FCNN models were 0.78, 0.76, 0.77, and 0.79, respectively. In conclusion, our multi-cohort study systematically investigated different LNM prediction methods for patients with early gastric cancer. These models were validated and shown to be reliable with AUC>0.76 for all. Specifically, the FCNN model showed the most accurate prediction of LNM risks in early gastric cancer patients with AUC=0.79. Based on the FCNN model, patients with LNM rates of >4.77% are strong candidates for gastrectomy rather than ESD surgery.

Gastric adenocarcinoma: A review of the TNM classification system and ways of spreading

Gastric cancer is the fifth most common cancer in the world. The most common histologic subtype is adenocarcinoma. Gastric adenocarcinomas are staged using the American Joint Committee on Cancer's 8th TNM classification. The perigastric ligaments, mesentery, omentum, and potential spaces between the parietal and visceral peritoneal linings play are important structures for staging. The spread of disease is influenced by the location of the tumor within the stomach, as well as by the anatomy related to the ligaments and lymph vessels. CT is the imaging modality of choice for the preoperative clinical staging of gastric cancer, and it is essential for planning treatment. To be able to do an adequate imaging workup, radiologists need to know the different pathways through which gastric cancer can spread: lymphatic, subperitoneal, direct invasion, transperitoneal, hematogenous, and extramural venous invasion.

Incidental findings on prostate MRI: a close look at the field of view in this anatomical region

Magnetic resonance imaging (MRI) has been widely used as an advanced imaging modality to detect prostate cancer and indicate suspicious areas to guide biopsy procedures. The increasing number of prostate examinations with MRI has provided an opportunity to detect incidental lesions, and some might be very significant to elucidate patient symptoms or occult neoplastic process in the early stages. These incidental lesions might be located in the prostate gland, adjacent tissues, or organs around the prostate gland or out of the genitourinary system. The field of view of prostate MRI includes not only the prostate gland but also other critical pelvic organs in this specific anatomical region. Some of these incidental lesions might cause the same symptoms as prostate cancer and might explain the symptoms of the patient, and some might indicate early cancer stages located outside the prostate. Reporting these lesions might be life-saving by initiating early disease treatment. Awareness of the predicted locations of congenital anomalies would also be beneficial for the radiologists to mention these incidental findings.

Trametes robiniophila Murr Sensitizes Gastric Cancer Cells to 5-Fluorouracil by Modulating Tumor Microenvironment

Trametes robiniophila Murr (TRM) is a traditional Chinese medicine which has been used in clinics for enhancing immunity and improving the efficacy of chemotherapy. However, the mechanisms of action of TRM are unknown. In the previous study, we found that the Trametes robiniophila Murr n-butanol extract (TRMBE) comprises the major bioactive components of TRM. In the present study, we aimed to assess the combinational effects of TRMBE and 5-fluorouracil (5-FU) on the treatment of gastric cancer (GC) and explore its mechanism of action. It was found that TRMBE significantly potentiated the anticancer activity of 5-FU and prolonged the survival time of mice bearing Mouse Forestomach Carcinoma (MFC) xenograft tumors. We observed that the combination of TRMBE and 5-FU decreased the risk of liver metastasis in vivo. Furthermore, the combination of TRMBE and 5-FU reduced the levels of immune cytokines IL-6, IL-10, and TGF-β and increased the level of IFN-γ in peripheral blood. This combination therapy also significantly decreased the levels of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and PD-1-positive CD8⁺ T cells and increased the levels of NK cells in tumor microenvironment (TME). However, TRMBE treatment was unable to enhance the chemosensitivity of GC to 5-FU in vivo after the depletion of CD8⁺ T and NK cells. Taken together, our results demonstrate that TRMBE can reshape the TME of GC by regulating PMN-MDSCs, CD8⁺ T cells, and NK cells, therefore improving the therapeutic effects of 5-FU. This study suggests that the combination of TRMBE and 5-FU could enhance immunity and could be a promising approach for GC treatment.

Adoption of Two-Dimensional Ultrasound Gastrointestinal Filling Contrast on Artificial Intelligence Algorithm in Clinical Diagnosis of Gastric Cancer

This research was aimed to explore the value of gastrointestinal filling contrast-enhanced ultrasound (CEUS) and computed tomography (CT-)-enhanced scanning based on artificial intelligence (AI) algorithm in the evaluation of gastric cancer staging. 102 patients with gastric cancer were selected as the research objects. All of them underwent CEUS of gastrointestinal filling and 64-slice spiral CT before surgery. In addition, an improved mean shift algorithm was proposed based on differential optical flow and deep convolutional neural network (D-CNN), which was applied in image processing. The predicted positive rate (PPR), sensitivity, specificity, and accuracy of gastric cancer in different stages by CEUS and CT were calculated using pathological diagnosis results as the gold standard. 17 patients with T1 stage, 41 patients with T2-T3 stage, and 35 patients with T4 stage were detected by CEUS. 13 patients with T1 stage, 34 patients with T2-T3 stage, and 30 patients with T4 stage were detected by CT enhanced examination. The PPRs of CEUS for T1, T2-T3, and T4 stages of gastric cancer were higher than those of CT enhanced (P < 0.05). The PPR of CEUS for N0 staging of gastric cancer was higher than that of CT enhanced (P < 0.05), and it for N3 staging of gastric cancer was lower than that of CT enhanced (P < 0.05). From the analysis of M staging of gastric cancer, the PPRs of CEUS for M0 and M1 staging of gastric cancer were not statistically different from the PPRs of CT enhanced (P > 0.05). The sensitivity (95.6%), specificity (81.82%), and accuracy (94.12%) of CEUS in assessing resectability were significantly higher than those of CT enhancement (89.01%, 63.67%, and 86.27%, respectively), and the differences were statistically significant (P < 0.05). In summary, CEUS gastrointestinal filling based on the D-CNN algorithm could better improve the display rate of the tissue lesions around the stomach. It also helped to judge the lesion progress, the depth of infiltration, and lymph node metastasis of the lesion. In addition, it had excellent performance in evaluating the resectability of gastric cancer before surgery and had clinical promotion value.

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.

The Value of Whole-Tumor Histogram and Texture Analysis Using Intravoxel Incoherent Motion in Differentiating Pathologic Subtypes of Locally Advanced Gastric Cancer

Purpose

To determine if whole-tumor histogram and texture analyses using intravoxel incoherent motion (IVIM) parameters values could differentiate the pathologic characteristics of locally advanced gastric cancer.

Methods

Eighty patients with histologically confirmed locally advanced gastric cancer who received surgery in our institution were retrospectively enrolled into our study between April 2017 and December 2018. Patients were excluded if they had lesions with the smallest diameter < 5 mm and severe image artifacts. MR scanning included IVIM sequences (9 b values, 0, 20, 40, 60, 100, 150,200, 500, and 800 s/mm²) used in all patients before treatment. Whole tumors were segmented by manually drawing the lesion contours on each slice of the diffusion-weighted imaging (DWI) images (with b=800). Histogram and texture metrics for IVIM parameters values and apparent diffusion coefficient (ADC) values were measured based on whole-tumor volume analyses. Then, all 24 extracted metrics were compared between well, moderately, and poorly differentiated tumors, and between different Lauren classifications, signet-ring cell carcinomas, and other poorly cohesive carcinomas using univariate analyses. Multivariate logistic analyses and multicollinear tests were used to identify independent influencing factors from the significant variables of the univariate analyses to distinguish tumor differentiation and Lauren classifications. ROC curve analyses were performed to evaluate the diagnostic performance of these independent influencing factors for determining tumor differentiation and Lauren classifications and identifying signet-ring cell carcinomas. The interobserver agreement was also conducted between the two observers for image quality evaluations and parameter metric measurements.

Results

For diagnosing tumor differentiation, the ADC_median, pure diffusion coefficient median (Dslow_median), and pure diffusion coefficient entropy (Dslow_entropy) showed the greatest AUCs: 0.937, 0.948, and 0.850, respectively, and no differences were found between the three metrics, P>0.05). The 95th percentile perfusion factor (FP _P95th) was the best metric to distinguish diffuse-type GCs vs. intestinal/mixed (AUC=0.896). The ROC curve to distinguish signet-ring cell carcinomas from other poorly cohesive carcinomas showed that the Dslow_median had AUC of 0.738. For interobserver reliability, image quality evaluations showed excellent agreement (interclass correlation coefficient [ICC]=0.85); metrics measurements of all parameters indicated good to excellent agreement (ICC=0.65-0.89), except for the Dfast metric, which showed moderate agreement (ICC=0.41-0.60).

Conclusions

The whole-tumor histogram and texture analyses of the IVIM parameters based on the biexponential model provided a non-invasive method to discriminate pathologic tumor subtypes preoperatively in patients with locally advanced gastric cancer. The metric FP _P95th derived from IVIM performed better in determining Lauren classifications than the mono-exponential model.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

Accuracy of Endoscopic Ultrasonography for Gastric Cancer Staging

Gastric cancer remains a health problem, with treatment indications varying with the TNM stage. We aimed in this study to highlight the role of EUS in GC patients and also to calculate the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of EUS for T and N staging in our group of patients with this disease. In this study, we included 41 GC patients, and individual values for every T stage accuracy, sensitivity, specificity, PPV, NPV, correct staging, understaging, and overstaging were calculated. EUS overall accuracy for T staging was 58.53%, with the highest sensitivity reached for the T4 stage, 95.83%. For N+vs. N-staging, EUS accuracy was 68.29%, with a sensitivity of 75% and a specificity of 44.44%. The positive and negative predicted values for the presence or absence of nodal disease were 82.75%, respectively 33.33%. In conclusion, this study confirmed the importance of EUS for the assessment of GC T and N stage and highlighted the role of this tool in the detection of liver micrometastasis unrevealed by other imaging techniques like abdominal ultrasound or MSCT.

Immune Landscape of Gastric Carcinoma Tumor Microenvironment Identifies a Peritoneal Relapse Relevant Immune Signature

Background

Gastric cancer (GC) still represents the third leading cause of cancer-related death worldwide. Peritoneal relapse (PR) is the most frequent metastasis occurring among patients with advanced gastric cancer. Increasingly more evidence have clarified the tumor immune microenvironment (TIME) may predict survival and have clinical significance in GC. However, tumor-transcriptomics based immune signatures derived from immune profiling have not been established for predicting the peritoneal recurrence of the advanced GC.

Methods

In this study, we depict the immune landscape of GC by using transcriptome profiling and clinical characteristics retrieved from GSE62254 of Gene Expression Omnibus (GEO). Immune cell infiltration score was evaluated via single-sample gene set enrichment (ssGSEA) analysis algorithm. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to select the valuable immune cells and construct the final model for the prediction of PR. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to check the accuracy of PRIs. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to explore the molecular pathways associated with PRIs.

Results

A peritoneal recurrence related immune score (PRIs) with 10 immune cells was constructed. Compared to the low-PRIs group, the high-PRIs group had a greater risk. The upregulation of the focal adhesion signaling was observed in the high-PRIs subtype by GSEA and KEGG. Multivariate analysis found that both in the internal training cohort and the internal validation cohort, PRIs was a stable and independent predictor for PR. A nomogram that integrated clinicopathological features and PRIs to predict peritoneal relapse was constructed. Subgroup analysis indicated that the PRIs could obviously distinguish peritoneal recurrence in different molecular subtypes, pathological stages and Lauren subtypes, in which PRIs of Epithelial-Mesenchymal Transitions (EMT) subtype, III-IV stage and diffuse subtype are higher respectively.

Conclusion

Overall, we performed a comprehensive evaluation of the immune landscape of GC and constructed a predictive PR model based on the immune cell infiltration. The PRIs represents novel promising feature of predicting peritoneal recurrence of GC and sheds light on the improvement of the personalized management of GC patients after surgery.

Tumor-Associated Macrophages and Inflammatory Microenvironment in Gastric Cancer: Novel Translational Implications

Gastric cancer (GC) represents the fifth most frequently diagnosed cancer worldwide, with a poor prognosis in patients with advanced disease despite many improvements in systemic treatments in the last decade. In fact, GC has shown resistance to several treatment options, and thus, notable efforts have been focused on the research and identification of novel therapeutic targets in this setting. The tumor microenvironment (TME) has emerged as a potential therapeutic target in several malignancies including GC, due to its pivotal role in cancer progression and drug resistance. Therefore, several agents and therapeutic strategies targeting the TME are currently under assessment in both preclinical and clinical studies. The present study provides an overview of available evidence of the inflammatory TME in GC, highlighting different types of tumor-associated cells and implications for future therapeutic strategies.

Controversies in EUS: Do we need miniprobes?

This is the fifth in a series of papers entitled "Controversies in EUS." In the current paper, we deal with high-resolution catheter probes, otherwise known as EUS miniprobes (EUS-MPs). The application of miniprobes for early carcinomas in the entire intestinal tract, for subepithelial lesions, and for findings in the bile duct and pancreatic duct as well as endobronchial use is critically discussed. Submucous lesions, especially in the colon, but also early carcinomas in special cases are considered the most important indications. The argument is illustrated by numerous examples.