Gastric cancer and image-derived quantitative parameters: Part 2-a critical review of DCE-MRI and 18F-FDG PET/CT findings

OCTA-based research on changes of retinal microcirculation in digestive tract malignancy

PURPOSE

This cross-sectional study measured retinal vessel density (VD) in patients with digestive tract malignancy by optical coherence tomography angiography (OCTA), and compared them with healthy controls to explore the retinal microcirculation changes in patients with digestive tract malignancy.

METHODS

106 eligible participants were divided into three groups: gastric cancer (GC) group (36 individuals), colorectal cancer (CRC) group (34 individuals), and healthy control group (36 individuals). Angio 6 × 6 512 × 512 R4 and ONH Angio 6 × 6 512 × 512 R4 modes were performed to collect retinal vessel density data centered on fovea and papillary, respectively. The retina was automatically segmented into different layers (superficial vascular plexus (SVP), the inner retinal layer, radial peripapillary capillary plexus (RPCP), deep vascular plexus (DVP)) and areas to analyze.

RESULTS

At the optic nerve head (ONH) region, the VD of the inner retinal layer increased in both GC and CRC groups in all quadrants and areas. In the papillary area, VD in the inner retinal layer, SVP, and RPCP increased in the GC and CRC groups. In the parapapillary area, VD in the inner retinal layer increased in the GC and the CRC groups. Significant increase in the global VD were found in the GC group of the RPCP and SVP. Regarding the macular region, no statistical differences were observed in each layer.

CONCLUSIONS

The study suggested that retinal vessel density changed in patients with digestive tract malignancy, especially in the inner retinal layer of the ONH region, revealing the potential relevance of the relation between gastrointestinal cancer and retinal microcirculation.

Galunisertib promotes bevacizumab-induced vascular normalization in nasopharyngeal carcinoma: Multi-parameter MRI evaluation

Tumor vascular normalization (TVN) is associated with antitumor therapeutic efficacy in nasopharyngeal carcinoma (NPC). However, the short time window of TVN is the biggest hindrance to its wide clinical application. We investigated whether targeting transforming growth factor beta can enhance the TVN effect of bevacizumab (BEV)-induced patient-derived xenograft (PDX) models of NPC. We constructed mouse subcutaneous PDX models of NPC and classified the mice into four drug-treatment groups, namely placebo control, galunisertib, BEV, and galunisertib + BEV. We performed MRI multi-parameter examinations at different time points and evaluated the vascular density, vascular structure, and tumor hypoxia microenvironment by histopathology. The efficacy of chemotherapy and drug delivery was evaluated by administering cisplatin. We found that combined therapy with galunisertib and BEV significantly delayed tumor growth, enhanced the TVN effect, and improved chemotherapeutic efficacy compared with monotherapy. Mechanistically, galunisertib reversed the epithelial-mesenchymal transition process and inhibited the expression of hypoxia-inducible factor 1α and vascular endothelial growth factor by downregulating LAMC2. Correlation analysis of MRI data and pathological indicators showed that there was a good correlation between them.

Application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in recurrent anastomotic tumors after surgery in digestive tract tumors

BACKGROUND

This study was to investigate the application value of whole-body dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) imaging in recurrent anastomotic tumors of digestive tract after gastric and esophageal cancer surgery. Postoperative patients with gastric and esophageal cancer have a high risk of tumor recurrence, and traditional imaging methods have certain limitations in early detection of recurrent tumors. Whole-body dynamic 18F-FDG PET/CT imaging, due to its high sensitivity and specificity, can provide comprehensive information on tumor metabolic activity, which is expected to improve the early diagnosis rate of postoperative recurrent tumors, and provide an important reference for clinical treatment decision-making.

AIM

To investigate the clinical value of whole-body dynamic 18F-FDG PET/CT imaging in differentiating anastomotic recurrence and inflammation after the operation of upper digestive tract tumors.

METHODS

A retrospective analysis was performed on 53 patients with upper digestive tract tumors after operation and systemic dynamic 18F-FDG PET/CT imaging indicating abnormal FDG uptake by anastomosis, including 29 cases of gastric cancer and 24 cases of esophageal cancer. According to the follow-up results of gastroscopy and other imaging examinations before and after PET/CT examination, the patients were divided into an anastomotic recurrence group and anastomotic inflammation group. Patlak multi-parameter analysis software was used to obtain the metabolic rate (MRFDG), volume of distribution maximum (DVmax) of anastomotic lesions, and MRmean and DVmean of normal liver tissue. The lesion/background ratio (LBR) was calculated by dividing the MRFDG and DVmax of the anastomotic lesion by the MRmean and DVmean of the normal liver tissue, respectively, to obtain LBR-MRFDG and LBR-DVmax. An independent sample t test was used for statistical analysis, and a receiver operating characteristic curve was used to analyze the differential diagnostic efficacy of each parameter for anastomotic recurrence and inflammation.

RESULTS

The dynamic 18F-FDG PET/CT imaging parameters MRFDG, DVmax, LBR-MRFDG, and LBR-DVmax of postoperative anastomotic lesions in gastric cancer and esophageal cancer showed statistically significant differences between the recurrence group and the inflammatory group (P < 0.05). The parameter LBR-MRFDG showed good diagnostic efficacy in differentiating anastomotic inflammation from recurrent lesions. In the gastric cancer group, the area under the curve (AUC) value was 0.935 (0.778, 0.993) when the threshold was 1.83, and in the esophageal cancer group, the AUC value was 1. When 86 is the threshold, the AUC value is 0.927 (0.743, 0.993).

CONCLUSION

Whole-body dynamic 18F-FDG PET/CT imaging can accurately differentiate the diagnosis of postoperative anastomotic recurrence and inflammation of gastric cancer and esophageal cancer and has the potential to be an effective monitoring method for patients with upper digestive tract tumors after surgical treatment.

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.

Fibronectin-Targeting Dual-Modal MR/NIRF Imaging Contrast Agents for Diagnosis of Gastric Cancer and Peritoneal Metastasis

The prevalence and fatality rates of gastric cancer (GC) remain elevated, with advanced stages presenting a grim prognosis. Noninvasive diagnosis of GC cancer often proves challenging until the disease has progressed to an advanced stage or metastasized. Initially, the level of fibronectin (FN) in cancer-associated fibroblasts (CAFs) of GC was at least 3.7 times higher than that in normal fibroblasts. Herein, two FN-targeting magnetic resonance/near-infrared fluorescence (MR/NIRF) imaging contrast agents were developed to detect GC and peritoneal metastasis noninvasively. The probes CREKA-Cy7-(Gd-DOTA) and CREKA-Cy7-(Gd-DOTA)3 demonstrated significant FN-targeting capability (with dissociation constants of 1.0 and 2.1 mM) and effective MR imaging performance (with proton relaxivity values of 9.66 and 27.44 mM-1 s-1 at 9.4 T, 37 °C). In vivo imaging revealed a high signal-to-noise ratio and successful visualization of GC metastasis using NIRF imaging as well as successful tumor detection in MR imaging. Therefore, this study highlights the potential of FN-targeting probes for GC diagnosis and aids in the advancement of new diagnostic strategies for the clinical detection of GC.

18F-FDG PET/CT metabolism multi-parameter prediction of chemotherapy efficacy in locally progressive gastric cancer

PURPOSE

This study aimed to use an 18F-FDG PET/CT multiparametric quantitative analysis to determine the efficacy of neoadjuvant chemotherapy in patients with locally progressive gastric cancer.

MATERIALS AND METHODS

We conducted a retrospective analysis of 34 patients with pathologically identified gastric cancer who received neoadjuvant chemotherapy and surgery. Chemotherapy regimens were followed and 18F-FDG PET/CT was conducted. We ascertained multiparamaters of the target lesions pre- and post-treatment and determined the ideal cutoff values for the percentage change in biomarkers. Independent factors were evaluated using binary logistic regression. A response classification system was used to explore the association between metabolic and anatomical responses and the degree of pathological remission.

RESULTS

Binary logistic regression analysis showed that Lauren bowel type and change in total lesion glycolysis >45.2% were risk predictors for the efficacy of neoadjuvant chemotherapy; total lesion glycolysis demonstrated the best predictive efficacy. The categorical variable system of the two-module response (metabolic and anatomical response) group had a higher predictive accuracy than that of the single-module response (metabolic or anatomical response) group.

CONCLUSIONS

Using 18F-FDG PET/CT multiparametric quantitative analysis, Lauren bowel type and change in total lesion glycolysis >45.2% were independent predictors of the efficacy of neoadjuvant chemotherapy in patients with gastric adenocarcinoma. Additionally, the dual-module assessment demonstrated high predictive efficacy.

Value of 68Ga-FAPI-04 and 18F-FDG PET/CT in Early Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer

This prospective study investigated whether PET parameters from 18F-FDG and 68Ga-fibroblast activation protein inhibitor (FAPI)-04 PET/CT can predict a pathologic response to neoadjuvant chemotherapy (NAC) early in patients with locally advanced gastric cancer (LAGC). Methods: The study included 28 patients with LAGC who underwent 18F-FDG PET/CT and 68Ga-FAPI-04 PET/CT at baseline and after 1 cycle of NAC. PET parameters including SUV and tumor-to-background ratio (TBR), as well as the change rate of SUV and TBR, were recorded. Patients were classified as major or minor pathologic responders according to postoperative pathology findings. We compared the PET parameters between the 2 pathologic response groups and different treatment regimens and analyzed their predictive performance for tumor pathologic response. Results: Major pathologic responders had significantly lower 68Ga-FAPI change rates (percentage SUVmax [%SUVmax], percentage SUVpeak [%SUVpeak], and percentage TBR [%TBR]) than minor pathologic responders. Among the PET parameters, 68Ga-FAPI %SUVmax (area under the curve, 0.856; P = 0.009), %SUVpeak (area under the curve, 0.811; P = 0.022), and %TBR (area under the curve, 0.864; P = 0.007) were significant parameters for early prediction of pathologic response to NAC in LAGC; they had the same predictive accuracy of 89.29%, with the thresholds of decrease to at least 52.43%, 60.46%, and 52.96%, respectively. In addition, 68Ga-FAPI %SUVmax and %TBR showed significant differences between the different treatment regimens. Conclusion: In this preliminary study, 68Ga-FAPI-04 PET change rate parameters were preferable to 18F-FDG in predicting pathologic response to NAC at an early stage in LAGC. 68Ga-FAPI %SUVmax and %TBR may be better predictors of therapeutic response between different treatment regimens. These findings may help optimize the treatment for patients with LAGC.

Predictive value of 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity in the prognosis of gastric cancer

OBJECTIVE

We aimed to investigate the predictive value of pre-treatment 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity for gastric cancer prognosis.

METHODS

Seventy-one patients with gastric cancer were included. All patients underwent 18F-FDG PET/CT whole-body scans prior to treatment and had pathologically confirmed gastric adenocarcinomas. Each metabolic parameter, including SUVmax, SUVmean, MTV, and TLG, was collected from the primary lesions of gastric cancer in all patients, and the slope of the linear regression between the MTV corresponding to different SUVmax thresholds (40% × SUVmax, 80% × SUVmax) of the primary lesions was calculated. The absolute value of the slope was regarded as the metabolic heterogeneity of the primary lesions, expressed as the heterogeneity index HI-1, and the coefficient of variance of the SUVmean of the primary lesions was regarded as HI-2. Patient prognosis was assessed by PFS and OS, and a nomogram of the prognostic prediction model was constructed, after which the clinical utility of the model was assessed using DCA.

RESULTS

A total of 71 patients with gastric cancer, including 57 (80.3%) males and 14 (19.7%) females, had a mean age of 61 ± 10 years; disease progression occurred in 27 (38.0%) patients and death occurred in 24 (33.8%) patients. Multivariate Cox regression analysis showed that HI-1 alone was a common independent risk factor for PFS (HR: 1.183; 95% CI: 1.010-1.387, P < 0.05) and OS (HR: 1.214; 95% CI: 1.016-1.450, P < 0.05) in patients with gastric cancer. A nomogram created based on the results of Cox regression analysis increased the net clinical benefit for patients. Considering disease progression as a positive event, patients were divided into low-, intermediate-, and high-risk groups, and Kaplan-Meier survival analysis showed that there were significant differences in PFS among the three groups. When death was considered a positive event and patients were included in the low- and high-risk groups, there were significant differences in OS between the two groups.

CONCLUSION

The heterogeneity index HI-1 of primary gastric cancer lesions is an independent risk factor for patient prognosis. A nomogram of prognostic prediction models constructed for each independent factor can increase the net clinical benefit and stratify the risk level of patients, providing a reference for guiding individualized patient treatment.

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.

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.

Four-dimensional quantitative analysis using FDG-PET in clinical oncology

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) has been commonly used in many oncological areas. High-resolution PET permits a three-dimensional analysis of FDG distributions on various lesions in vivo, which can be applied for tissue characterization, risk analysis, and treatment monitoring after chemoradiotherapy and immunotherapy. Metabolic changes can be assessed using the tumor absolute FDG uptake as standardized uptake value (SUV) and metabolic tumor volume (MTV). In addition, tumor heterogeneity assessment can potentially estimate tumor aggressiveness and resistance to chemoradiotherapy. Attempts have been made to quantify intratumoral heterogeneity using radiomics. Recent reports have indicated the clinical feasibility of a dynamic FDG PET-computed tomography (CT) in pilot cohort studies of oncological cases. Dynamic imaging permits the assessment of temporal changes in FDG uptake after administration, which is particularly useful for differentiating pathological from physiological uptakes with high diagnostic accuracy. In addition, several new parameters have been introduced for the in vivo quantitative analysis of FDG metabolic processes. Thus, a four-dimensional FDG PET-CT is available for precise tissue characterization of various lesions. This review introduces various new techniques for the quantitative analysis of FDG distribution and glucose metabolism using a four-dimensional FDG analysis with PET-CT. This elegant study reveals the important role of tissue characterization and treatment strategies in oncology.

Computed tomography-based texture assessment for the differentiation of benign, borderline, and early-stage malignant ovarian neoplasms

OBJECTIVE

This study was performed to examine the value of computed tomography-based texture assessment for characterizing different types of ovarian neoplasms.

METHODS

This retrospective study involved 225 patients with histopathologically confirmed ovarian tumors after surgical resection. Two different data sets of thick (5-mm) slices (during regular and portal venous phases) were analyzed. Raw data analysis, principal component analysis, linear discriminant analysis, and nonlinear discriminant analysis were performed to classify ovarian tumors. The radiologist's misclassification rate was compared with the MaZda (texture analysis software) findings. The results were validated with the neural network classifier. Receiver operating characteristic curves were analyzed to determine the performances of different parameters.

RESULTS

Nonlinear discriminant analysis had a lower misclassification rate than the other analyses. Thirty texture parameters significantly differed between the two groups. In the training set, WavEnLH_s-3 and WavEnHL_s-3 were the optimal texture features during the regular phase, while WavEnHH_s-4 and Kurtosis seemed to be the most discriminative features during the portal venous phase. In the validation test, benign versus malignant tumors and benign versus borderline lesions were well-distinguished.

CONCLUSIONS

Computed tomography-based texture features provide a useful imaging signature that may assist in differentiating benign, borderline, and early-stage ovarian cancer.

Predictive value of DCE-MRI and IVIM-DWI in osteosarcoma patients with neoadjuvant chemotherapy

Objective

To investigate the predictive value of dynamic contrast enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for clinical outcomes of osteosarcoma patients with neoadjuvant chemotherapy.

Methods

The present prospective single-arm cohort study enrolled 163 patients of osteosarcoma during July 2017 to July 2022. All patients received the same treatment strategy of neoadjuvant chemotherapy. Both DCE-MRI and IVIM-DWI were conducted for the patients before the chemotherapy, as well as after one or two chemotherapy treatment cycles. The imaging parameters of contrast agent transfer rate between blood and tissue (K^trans), contrast agent back-flux rate constant (K_ep), extravascular extracellular fractional volume (V_e), as well as pure diffusion coefficient (D value), pseudo-diffusion coefficient (D* value), apparent diffusion coefficient (ADC) and the perfusion fraction (f value) were recorded. RECIST standard [complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD)] was used as the main clinical outcome.

Results

After two treatment cycles, 112 (68.71%) cases were with CR and PR, 31 (19.02%) cases were with SD and 20 cases (12.27%) were with PD. After 1~2 treatment cycles, patients with CR/PR showed significantly markedly lower K^trans, K_ep, V_e values, while higher D, ADC and f values compared with SD or PD patients. Alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) were positively correlated with values of K^trans, K_ep, and V_e, while negative correlation was observed between ALP and values of D, ADC and f, as well as between LDH and D and ADC after the whole treatment. D and K_ep values after two treatment cycles showed the best predictive value for diagnosis of PD. The values of K^tran, K_ep, ADC as well as ALP and LDH were all risk factors for PD after neoadjuvant chemotherapy.

Conclusion

DCE-MRI and IVIM-DWI have the potential to predict clinical outcomes of osteosarcoma patients with neoadjuvant chemotherapy.

Outcomes of a Phase II Study of Intraperitoneal Paclitaxel plus Systemic Capecitabine and Oxaliplatin (XELOX) for Gastric Cancer with Peritoneal Metastases

BACKGROUND

Adding intraperitoneal paclitaxel (IP-PTX) to paclitaxel/5-fluoropyrimidine has shown promising results in patients with gastric cancer peritoneal metastases (GCPM) but has not been studied with standard-of-care platinum/fluoropyrimidine combinations. Our goal to was evaluate IP-PTX with capecitabine/oxaliplatin (XELOX) in GCPM.

METHODS

Forty-four patients with GCPM received IP PTX (40 mg/m², Days 1, 8), oral capecitabine (1000 mg/m² twice daily, Days 1-14) and intravenous oxaliplatin (100 mg/m², Day 1) in 21-day cycles. Patients with synchronous GCPM underwent conversion surgery if they had good response after chemotherapy, conversion to negative cytology, no extraperitoneal metastasis, and no peritoneal disease during surgery. The primary endpoint was overall survival and secondary endpoints were progression-free survival and safety. Outcomes from the trial were compared against a matched cohort of 39 GCPM patients who received systemic chemotherapy (SC) comprising platinum/fluoropyrimidine.

RESULTS

The median OS for the IP and SC groups was 14.6 and 10.6 months (hazard ratio [HR] 0.44; 95% confidence interval [CI], 0.26-0.74; p = 0.002). The median PFS for the IP and SC group was 9.5 and 4.4 months respectively (HR 0.39; 95% CI 0.25-0.66; p < 0.001). Patients in the SC group were younger (IP vs. SC, 61 vs. 56 years, p = 0.021) and had better performance status (ECOG 0, IP vs. SC, 47.7% vs. 76.9%, p = 0.007) compared with the IP cohort. In IP group, conversion surgery was performed in 36.1% (13/36) of patients, with a median OS of 24.2 (95% CI 13.1-35.3) months and 1-year OS of 84.6%.

CONCLUSIONS

IP PTX with XELOX is a promising treatment option for GCPM patients. In patients with good response, conversion surgery was feasible with favourable outcomes.

Molecular imaging nanoprobes for theranostic applications

As a non-invasive imaging monitoring method, molecular imaging can provide the location and expression level of disease signature biomolecules in vivo, leading to early diagnosis of relevant diseases, improved treatment strategies, and accurate assessment of treating efficacy. In recent years, a variety of nanosized imaging probes have been developed and intensively investigated in fundamental/translational research and clinical practice. Meanwhile, as an interdisciplinary discipline, this field combines many subjects of chemistry, medicine, biology, radiology, and material science, etc. The successful molecular imaging not only requires advanced imaging equipment, but also the synthesis of efficient imaging probes. However, limited summary has been reported for recent advances of nanoprobes. In this paper, we summarized the recent progress of three common and main types of nanosized molecular imaging probes, including ultrasound (US) imaging nanoprobes, magnetic resonance imaging (MRI) nanoprobes, and computed tomography (CT) imaging nanoprobes. The applications of molecular imaging nanoprobes were discussed in details. Finally, we provided an outlook on the development of next generation molecular imaging nanoprobes.

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.

Advanced Magnetic Resonance Imaging (MRI) Techniques: Technical Principles and Applications in Nanomedicine

Simple Summary

Magnetic Resonance Imaging (MRI) is a consolidated imaging tool for the multiparametric assessment of tissues in various pathologies from degenerative and inflammatory diseases to cancer. In recent years, the continuous technological evolution of the equipment has led to the development of sequences that provide not only anatomical but also functional and metabolic information. In addition, there is a growing and emerging field of research in clinical applications using MRI to exploit the diagnostic and therapeutic capabilities of nanocompounds. This review illustrates the application of the most advanced magnetic resonance techniques in the field of nanomedicine.

Abstract

In the last decades, nanotechnology has been used in a wide range of biomedical applications, both diagnostic and therapeutic. In this scenario, imaging techniques represent a fundamental tool to obtain information about the properties of nanoconstructs and their interactions with the biological environment in preclinical and clinical settings. This paper reviews the state of the art of the application of magnetic resonance imaging in the field of nanomedicine, as well as the use of nanoparticles as diagnostic and therapeutic tools, especially in cancer, including the characteristics that hinder the use of nanoparticles in clinical practice.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Imaging of Gastric Carcinomatosis

Diagnosing the absence or presence of peritoneal carcinomatosis in patients with gastric cancer, including its extent and distribution, is an essential step in patients' therapeutic management. Such diagnosis still remains a radiological challenge. In this article, we review the strengths and weaknesses of the different imaging techniques for the diagnosis of peritoneal carcinomatosis of gastric origin as well as the techniques' imaging features. We also discuss the assessment of response to treatment and present recommendations for the follow-up of patients with complete surgical resection according to the presence of risk factors of recurrence, as well as discussing future directions for imaging improvement.

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

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

Intelligent Algorithm-Based CT Imaging for Evaluation of Efficacy of Docetaxel Combined with Fluorouracil on Patients with Gastric Cancer

The study focused on the dual-source computed tomography (CT) images segmented by the decision tree algorithm, to explore the efficacy of docetaxel combined with fluorouracil therapy on gastric patients undergoing chemotherapy. In this study, 98 patients with gastric cancer who were treated in the hospital were selected as the research subjects. The decision tree algorithm was applied to segment dual-source CT images of gastric cancer patients. The decision tree is established according to the feature ring and the segmentation position. The machine inductively learns from the decision tree to extract the features of the CT image to obtain the optimal segmentation boundary. The observation group was treated with docetaxel combined with fluorouracil, and the control group was treated with docetaxel combined with tegafur gimeracil oteracil potassium capsules. The general data of the two groups of patients were comparable and not statistically significant (P > 0.05). The two groups were compared for clinical efficacy, physical status, KPS score, improvement rate, and adverse drug reactions after treatment. The results showed that the improvement rate of physical fitness in the observation group was 38.78%, and the improvement rate in the control group was 18.37%. The total effective rate in the observation group was 42.85%, and the total effective rate in the control group was 36.73%. Obviously, the curative effect and improvement rate of physical fitness in the observation group were significantly better than those in the control group (P < 0.05). In conclusion, the decision tree algorithm proposed in this study demonstrates superb capabilities in feature extraction of CT images. The machine inductively learns from the decision tree to extract the features of the CT image to obtain the optimal segmentation boundary. The effect of docetaxel combined with fluorouracil is better than that of docetaxel combined with tegafur gimeracil oteracil potassium capsules.

18F-FDG PET/CT Radiomics for Preoperative Prediction of Lymph Node Metastases and Nodal Staging in Gastric Cancer

OBJECTIVES

The accurate assessment of lymph node metastases (LNMs) and the preoperative nodal (N) stage are critical for the precise treatment of patients with gastric cancer (GC). The diagnostic performance, however, of current imaging procedures used for this assessment is sub-optimal. Our aim was to investigate the value of preoperative 18F-FDG PET/CT radiomic features to predict LNMs and the N stage.

METHODS

We retrospectively collected clinical and 18F-FDG PET/CT imaging data of 185 patients with GC who underwent total or partial radical gastrectomy. Patients were allocated to training and validation sets using the stratified method at a fixed ratio (8:2). There were 2,100 radiomic features extracted from the 18F-FDG PET/CT scans. After selecting radiomic features by the random forest, relevancy-based, and sequential forward selection methods, the BalancedBagging ensemble classifier was established for the preoperative prediction of LNMs, and the OneVsRest classifier for the N stage. The performance of the models was primarily evaluated by the AUC and accuracy, and validated by the independent validation methods. Analysis of the feature importance and the correlation were also conducted. We also compared the predictive performance of our radiomic models to that with the contrast-enhanced CT (CECT) and 18F-FDG PET/CT.

RESULTS

There were 185 patients-127 men, 58 women, with the median age of 62, and an age range of 22-86 years. One CT feature and one PET feature were selected to predict LNMs and achieved the best performance (AUC: 82.2%, accuracy: 85.2%). This radiomic model also detected some LNMs that were missed in CECT (19.6%) and 18F-FDG PET/CT (35.7%). For predicting the N stage, four CT features and one PET feature were selected (AUC: 73.7%, accuracy: 62.3%). Of note, a proportion of patients in the validation set whose LNMs were incorrectly staged by CECT (57.4%) and 18F-FDG PET/CT (55%) were diagnosed correctly by our radiomic model.

CONCLUSION

We developed and validated two machine learning models based on the preoperative 18F-FDG PET/CT images that have a predictive value for LNMs and the N stage in GC. These predictive models show a promise to offer a potentially useful adjunct to current staging approaches for patients with GC.

Primary Gastro-Intestinal Lymphoma and Gastro-Intestinal Adenocarcinoma: An Initial Study of CT Texture Analysis as Quantitative Biomarkers for Differentiation

BACKGROUND

To explore the potential role of computed tomography (CT) texture analysis and an imaging biomarker in differentiating primary gastro-intestinal lymphoma (PGIL) from gastro-intestinal adenocarcinoma (GIAC).

METHODS

A total of 131 patients with surgical pathologically PGIL and GIAC were enrolled in this study. Histogram parameters of arterial and venous phases extracted from contrast enhanced modified discrete cosine transform (MDCT) images were compared between PGIL and GIAC by Mann-Whitney U tests. The optimal parameters for differentiating these two groups were obtained through receiver operating characteristic (ROC) curves and the area under the curve (AUC) was calculated.

RESULTS

Compared with GIAC, in arterial phase, PGIL had statistically higher 5th, 10th percentiles (p = 0.003 and 0.011) and statistically lower entropy (p = 0.001). In the venous phase, PGIL had statistically lower mean, median, 75th, 90th, 95th percentiles, and entropy (p = 0.036, 0.029, 0.007, 0.001 and 0.001, respectively). For differentiating PGIL from GIAC, V-median + A-5th percentile was an optimal parameter for combined diagnosis (AUC = 0.746, p < 0.0001), and the corresponding sensitivity and specificity were 81.7 and 64.8%, respectively.

CONCLUSION

CT texture analysis could be useful for differential diagnosis of PGIL and GIAC.

Accuracy of whole-body diffusion-weighted MRI (WB-DWI/MRI) in diagnosis, staging and follow-up of gastric cancer, in comparison to CT: a pilot study

Background

Accurate staging of patients with gastric cancer is necessary for selection of the most appropriate and personalized therapy. Computed tomography (CT) is currently used as primary staging tool, being widely available with a relatively high accuracy for the detection of parenchymal metastases, but with low sensitivity for the detection of peritoneal metastases. Magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) has a very high contrast resolution, suggesting a higher diagnostic performance in the detection of small peritoneal lesions. The aim of this study was to retrospectively evaluate the added value of whole-body diffusion-weighted MRI (WB-DWI/MRI) to CT for detection of peritoneal carcinomatosis (PC) and distant metastases in the preoperative staging of gastric cancer.

Methods

This retrospective study included thirty-two patients with a suspicion of gastric cancer/recurrence, who underwent WB-DWI/MRI at 1.5 T, in addition to CT of thorax and abdomen. Images were evaluated by two experienced abdominal radiologists in consensus. Histopathology, laparoscopy and/or 1-year follow-up were used as reference standard.

Results

For overall tumour detection (n = 32), CT sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) was 83.3%, 100%, 100% and 82.4% respectively. For WB-DWI/MRI these values were 100%, 92.9%, 94.7% and 100%, respectively. For staging (n = 18) malignant lymph nodes and metastases, CT had a sensitivity, specificity/PPV/NPV of 50%/100%/100%/71.4%, and 15.4%/100%/100%/31.3% respectively. For WB-DWI/MRI, all values were 100%, for both malignant lymph nodes and metastases. WB-DWI/MRI was significantly better than CT in detecting tumour infiltration of the mesenteric root, serosal involvement of the small bowel and peritoneal metastases for which WB-DWI/MRI was correct in 100% of these cases, CT 0%.

Conclusions

WB-DWI/MRI is highly accurate for diagnosis, staging and follow-up of patients with suspected gastric cancer.

Circulating serum exosomal miR-92a-3p as a novel biomarker for early diagnosis of gastric cancer

Gastric cancer (GC) is one of the common malignant tumors with high mortality. The abundance of miRNAs in serum exosomes has proved to have a high application value as a new noninvasive diagnostic method. The purpose of this study was to investigate whether serum exosomal miR-92a-3p could be used as a new biomarker for early diagnosis of GC and evaluate its clinical application value by detecting the expression of serum exosomal miR-92a-3p in 131 patients with primary GC and 122 healthy controls by real-time quantitative (qRT)-PCR. The results showed that the expression level of serum exosomal miR-92a-3p in GC patients was significantly lower than that in normal controls (p < 0.0001). In addition, the level was closely correlated with lymph node metastasis and tumor node metastasis stage of GC patients. The area under the curve for serum exosomal miR-92a-3p was 0.829, significantly higher than for other indicators. Furthermore, combined detection of serum exosomal miR-92a-3p, CEA and CA19-9 was more sensitive than any of the three alone or any pair. These results showed that serum exosomal miR-92a-3p could be used as a novel new tumor biomarker to improve diagnostic efficiency in GC.

Multidisciplinary team consultation for resectable Gastric Cancer: A propensity score matching analysis

Purpose: Previous studies proposed that the multidisciplinary team (MDT) consultation could improve tumor staging accuracy and outcomes of patients with gastric malignancy. However, evidence-based reports remain limited. This study aimed to determine the effectiveness of MDT for tumor staging accuracy and outcomes of patients with resectable gastric cancer, and to explore the potential factors affecting its effectiveness. Methods: This retrospective study enrolled 719 gastric cancer patients who underwent gastrectomy in our hospital. After propensity score matching, 378 patients were selected, including 189 in the non-MDT group and 189 in the MDT group. Data regarding baseline characteristics, staging, treatments, and survival were analyzed. Results: The data showed that the staging accuracy in the MDT group and non-MDT group was comparable (53% vs 61% for T stage, 46.1% vs 35.3% for N stage, and 78.3% vs 78.7% for M stage). The MDT group had a higher proportion of preoperative chemotherapy (39.2% vs 28%, p=0.03) and laparoscopic surgery (82.5% vs 72%, p=0.02) than the non-MDT group. However, the achievement of R0 resection was similar in the two groups (93.7% vs 88.9%, p=0.73). There was no significant difference in the 1-year and 3-year overall survival rates between the two groups. Moreover, we observed poor patient compliance when the MDT recommended further examinations, radiotherapy, or chemotherapy before surgical interventions. Conclusion: MDT consultation has limited effects on improving the staging accuracy and treatment outcomes including survival of patients with resectable gastric cancer. Poor patient compliance may be a factor affecting the effectiveness of MDT consultation.

Anti-tumor activity of resveratrol against gastric cancer: a review of recent advances with an emphasis on molecular pathways

Gastric cancer (GC) is one of the most common cancers with high malignancy. In spite of the great development in diagnostic tools and application of anti-tumor drugs, we have not witnessed a significant increase in the survival time of patients with GC. Multiple studies have revealed that Wnt, Nrf2, MAPK, and PI3K/Akt signaling pathways are involved in GC invasion. Besides, long non-coding RNAs and microRNAs function as upstream mediators in GC malignancy. GC cells have acquired resistance to currently applied anti-tumor drugs. Besides, combination therapy is associated with higher anti-tumor activity. Resveratrol (Res) is a non-flavonoid polyphenol with high anti-tumor activity used in treatment of various cancers. A number of studies have demonstrated the potential of Res in regulation of molecular pathways involved in cancer malignancy. At the present review, we show that Res targets a variety of signaling pathways to induce apoptotic cell death and simultaneously, to inhibit the migration and metastasis of GC cells.

The Preoperative Enhanced Degree of Contrast-enhanced CT Images: A Potential Independent Predictor in Gastric Adenocarcinoma Patients After Radical Gastrectomy

Aim

To discover the value of contrast-enhanced CT parameters in predicting the prognosis of gastric adenocarcinoma (GAC) patients after radical gastrectomy.

Methods

The patients with a clinical diagnosis of GAC were retrospectively enrolled. Two radiologists drew the regions of interest (ROIs) in CT images and measured the CT attenuate value (CAV) in each phase and the corrected CAV (cCAV) in each contrast-enhanced phase. Patients were divided into two groups (high/low-enhancement) according to receiver operating characteristic (ROC) curve. Kaplan–Meier curve and Cox proportional hazards regression analysis were performed to evaluate correlation between prognosis and variables. Subgroup analysis was used to further analyze the prognostic value of variables.

Results

In total 435 patients were included. According to ROC curve, the cCAV in delayed phase (DP-cCAV) with maximum AUC and Youden index was chosen. A total of 312 patients (71.7%) entered DP-cCAV^low group and remaining 123 (28.3%) patients were in DP-cCAV^high group. According to univariate (high vs low, HR=2.120, p<0.001) and multivariate (high vs low, HR=1.623, p<0.001) Cox regression analysis, the low-enhancement state was considered as an independent protective factor. Subgroup analysis was based on age, maximum diameter of tumor, differentiation, vascular invasion status, and TNM staging. In most subgroups, the overall survival (OS) of DP-cCAV^low group was overwhelmingly satisfactory (all HR >1, expect TNM stage I, IV and differentiated type subgroups).

Conclusion

The prognostic effectiveness of CT parameters as biomarkers for OS in GAC patients treated with radical gastrectomy has potential value.

Positron Emission Tomography for Response Evaluation in Microenvironment-Targeted Anti-Cancer Therapy

Therapeutic response is evaluated using the diameter of tumors and quantitative parameters of 2-[¹⁸F] fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET). Tumor response to molecular-targeted drugs and immune checkpoint inhibitors is different from conventional chemotherapy in terms of temporal metabolic alteration and morphological change after the therapy. Cancer stem cells, immunologically competent cells, and metabolism of cancer are considered targets of novel therapy. Accumulation of FDG reflects the glucose metabolism of cancer cells as well as immune cells in the tumor microenvironment, which differs among patients according to the individual immune function; however, FDG-PET could evaluate the viability of the tumor as a whole. On the other hand, specific imaging and cell tracking of cancer cell or immunological cell subsets does not elucidate tumor response in a complexed interaction in the tumor microenvironment. Considering tumor heterogeneity and individual variation in therapeutic response, a radiomics approach with quantitative features of multimodal images and deep learning algorithm with reference to pathologic and genetic data has the potential to improve response assessment for emerging cancer therapy.

Intra-tumor metabolic heterogeneity of gastric cancer on 18F-FDG PETCT indicates patient survival outcomes

The present study aimed to investigate the prognostic value of intra-tumor metabolic heterogeneity on 2-[18F] Fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) for patients with gastric cancer. Fifty-five patients with advanced gastric cancer that had received neoadjuvant chemotherapy and radical surgery were included. Clinicopathological information, ¹⁸F-FDG PET/CT before chemotherapy, pathological response, recurrence or metastasis, progression-free survival (PFS), and overall survival (OS) of the patients were collected. The maximum, peak, and mean standardized uptake values (SUV_max, SUV_peak, and SUV_mean), tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on PET/CT were measured. Heterogeneity index-1 (HI-1) was calculated as SUV_mean divided by the standard deviation, and heterogeneity index-2 (HI-2) was evaluated through linear regressions of MTVs according to different SUV thresholds. Associations between these parameters and patient survival outcomes were analyzed. None of the parameters on PET were associated with tumor recurrence. Pathological responders had significantly smaller TLR, MTV and HI-2 values than non-responders (P = 0.017, 0.017 and 0.013, respectively). In multivariate analysis of PFS, only HI-2 was an independent factor (hazard ratio [HR] = 2.693, P = 0.005) after adjusting for clinical tumor-node-metastasis (TNM) stage. In multivariate analysis of OS, HI-2 was also an independent predictive factor (HR = 2.281, P = 0.009) after adjusting for tumor recurrence. Thus, HI-2 generated from baseline ¹⁸F-FDG PET/CT is significantly associated with survival of patients with gastric cancer. Preoperative assessment of HI-2 by ¹⁸F-FDG PET/CT might be promising to identify patients with poor prognosis.

18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Metabolic Parameters Before and After Neoadjuvant Chemotherapy Can Predict the Postoperative Prognosis of Locally Advanced Gastric Cancer

Objective: To explore the value of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) metabolic parameters before and after neoadjuvant chemotherapy in predicting histopathological response and prognosis of locally advanced gastric cancer. Materials and Methods: A total of 56 patients with locally advanced gastric cancer underwent ¹⁸F-FDG PET/CT before and after neoadjuvant chemotherapy. The maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the lesions were measured before and after neoadjuvant chemotherapy. The percentage changes in the maximum standardized uptake value (ΔSUV_max%), mean standardized uptake value (ΔSUV_mean%), metabolic tumor volume (ΔMTV%), and total lesion glycolysis (ΔTLG%), which were derived from ¹⁸F-FDG PET/CT, were calculated, and the cutoff values were determined by receiver operating characteristic curve analysis. Differences in progression-free survival (PFS) and overall survival (OS) between groups dichotomized by these cutoffs were analyzed using the Kaplan-Meier method and Cox proportional hazards regression model. Results: The patients were divided into histopathological responders and nonresponders according to the following cutoff values: 58.8% SUV_max reduction, 45.8% SUV_mean reduction, 36.9% MTV reduction, and 57.8% TLG reduction. The differences in PFS and OS between groups dichotomized by these cutoffs were significant (all p < 0.01). Multivariate analysis suggested that a ΔTLG% > 57.8% was an independent postoperative risk factor for PFS (hazard ratio [HR] 0.348, 95% confidence interval [CI] 0.131-0.926, p = 0.035) and OS (HR 0.107, 95% CI 0.023-0.498, p = 0.004). Conclusions: The metabolic parameters before and after neoadjuvant chemotherapy of ¹⁸F-FDG PET/CT accurately reflected the chemotherapy effect, and ΔTLG% was the only independent postoperative predictive factor of PFS and OS for locally advanced gastric cancer.

Improving MR sequence of 18F-FDG PET/MR for diagnosing and staging gastric Cancer: a comparison study to 18F-FDG PET/CT

Purpose

Evaluate the feasibility of fluorine-18 (¹⁸F) fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging in patients with gastric cancer by optimizing the scan protocol and to compare the image quality to ¹⁸F FDG PET and computed tomography (CT).

Methods

The PET/CT and PET/MR imaging were sequentially performed in 30 patients with gastric cancer diagnosed by gastroscope using a single-injection-with-dual-imaging protocol. After intravenous injection of ¹⁸F-FDG (mean, 249 MBq), PET/CT imaging including low-dose CT was performed (mean uptake time, 47 ± 6 min), and PET/MR imaging including a T1-weighted Dixon sequence for attenuation correction and two different T2-weighted sequences was subsequently acquired (88 ± 15 min after ¹⁸F-FDG injection). Four series of images (CT from PET/CT, T1W, T2W Half-Fourier acquisition single-shot turbo spin-echo [T2W-HASTE] and T2W-BLADE from PET/MR) were visually evaluated using a 3–4 points scale for: (1) image artifacts, (2) lesion conspicuity and (3) image fusion quality. The characteristics of the primary lesions were assessed and compared between the PET/CT and PET/MR acquisitions.

Results

The image quality and lesion conspicuity of the T2W-HASTE images were significantly improved compared to that of the T2W-BLADE images. A significantly higher number of artifacts were seen in the T2W-HASTE images compared with the T1W and CT images (p < 0. 05). No differences in the accuracy of image fusion between PET/MR and PET/CT (p > 0. 05); however, significant difference was seen in the lesion conspicuity measurements (p < 0.05) with T2W-HASTE being superior. For information about the primary lesion characteristics, the T2W-HASTE images provided the most successful identifications compared with those of the T1W and PET/CT (13vs7vs5) images.

Conclusions

PET/MR with the T2W-HASTE was better at revealing the details of local stomach lesions compared with PET/CT imaging. Combining the PET/MR with the T2W-HASTE technique is a promising imaging method for diagnosing and staging gastric cancer.

Plasma cfDNA as a Potential Biomarker to Evaluate the Efficacy of Chemotherapy in Gastric Cancer

Objective

To investigate the clinical value of plasma cell-free DNA (cfDNA) as a potential biomarker for advanced gastric cancer (GC).

Patients and Methods

One hundred and six cases of advanced gastric cancer patients receiving chemotherapy were selected as study objects. Another 40 healthy volunteers were included as control groups. Plasma cfDNA concentration was detected by (SuperbDNA^TM) hybridization. Changes in cfDNA concentration during chemotherapy in patients with gastric cancer whose efficacy was assessed as partial response (PR), stable disease (SD) and disease progression (PD) were analyzed respectively. The relationship between the level of cfDNA and the efficacy of chemotherapy and clinical characteristics was also explored. In addition, cfDNA and other tumor markers were subjected to specificity and sensitivity analyses using ROC.

Results

cfDNA concentration in advanced GC patients was significantly higher than that in healthy controls (P<0.05). The concentration of plasma cfDNA in patients with PD showed an increasing trend over time. The concentration of plasma cfDNA in patients with therapeutic effect of PR decreased over time. In patients with therapeutic effect of SD, the plasma DNA concentration showed a stable trend over time. There was no significant correlation between cfDNA concentration and factors including gender, age, pathological type, CA724, CA125,CA199, AFP and CEA. ROC results showed that the area under the curve of cfDNA was larger than other tumor markers.

Conclusion

Plasma cfDNA concentration was significantly increased in patients with gastric cancer, and its diagnostic efficacy was superior to that of traditional tumor markers. It can be used as a tumor biomarker to monitor the efficacy of chemotherapy for gastric cancer.